Contribution of Energy Efficiency Measures to

Transcription

Scientific Support in the Preparation of Proposals
for an EU Energy Roadmap
Concrete Paths of the European Union to the 2°C
Scenario: Achieving the Climate Protection Targets
of the EU by 2050 through Structural Change, Energy
Savings and Energy Efficiency Technologies
Accompanying scientific report –
Contribution of
energy efficiency measures to climate protection
within the European Union until 2050
Project Number: 405/2010
FKZ: UM 10 41 913
Fraunhofer Institute for Systems and Innovation Research ISI
Karlsruhe, 20 March 2012
Authors:
Tobias Boßmann
Phone: 0721/6809-257
E-Mail: [email protected]
Wolfgang Eichhammer
Phone: 0721/6809-158
Rainer Elsland
Phone: 0721/6809-438
Fax 0721/809-272
Fraunhofer-Institut für System- und
Innovationsforschung ISI
Breslauer Str. 48, 76139 Karlsruhe
Executive Summary
Given the risks associated with global warming and its potential consequences due
to the uncontrolled emissions of greenhouse gases (GHG), the European Union
(EU) has pledged to reduce its emissions by 20% until 2020 and by at least 80%
until 2050 compared to 1990 levels.
In this context, the energy sector plays a crucial a role, since approximately 80% of
European GHG emissions in 2009 were from this sector. Moreover, this sector offers the chance of almost complete decarbonisation based on a variety of technologies ranging from carbon-neutral electricity generation through highly-efficient
energy conversion processes to energy-saving options. The political challenge
here consists of developing a set of technology options which will ensure the shift
takes place towards a sustainable European energy system which still complies
with the constraints imposed by competitiveness and the security of supply.
Since energy efficiency represents a powerful tool to tackle these objectives, the
present study analyses in detail to what extent energy savings can contribute to
GHG emission mitigation in the EU until the year 2050 and which technologies are
required for the energy saving potentials identified. This report provides detailed
information. The policy report gives an overview of the main insights.
The technology-based, bottom-up approach also sets this study apart from most of
the other existing reports. The study comparison carried out clearly shows that
most of the time energy efficiency options are not being considered to their full extent as a technology option for carbon mitigation in the various scenarios. Moreover, the level of detail regarding the deployment of efficiency measures is well
below the accuracy usually applied to the analysis of the energy supply side, particularly the power sector.
The analysis of the different sectors reveals the largest final energy saving potential to be in the buildings sector, whereas the highest financial benefits can be
gained in the transport sector. In 2050, the overall final energy demand could be
reduced by 57% compared to the baseline projection, triggering cost savings of
about 500 billion €’05. With regard to primary energy demand, efficiency improvements when converting primary to final energy are also considered. The shift towards a highly efficient power sector results in reductions of 25% in the primary
energy demand and 15% in GHG emissions. Saving options related to final energy
use deliver additional reductions of 42% and 52%, respectively.
Finally, the energy-saving potentials identified are compared to the energy demand
trajectories presented in the recently published EU Energy Roadmap 2050 of the
European Commission.
Contents
Page
1
BACKGROUND ....................................................................................................................... 1
2
OBJECTIVES OF THE STUDY .................................................................................................... 5
3
STUDY COMPARISON FOR THE CONTRIBUTION OF ENERGY EFFICIENCY IN THE EU27 TO THE
2050 CLIMATE TARGETS ................................................................................................................. 6
4
3.1
INTRODUCTION ........................................................................................................................ 6
3.2
PRIMARY ENERGY DEMAND ........................................................................................................ 9
3.3
FINAL ENERGY DEMAND........................................................................................................... 12
3.4
SECTORAL ANALYSIS ................................................................................................................ 14
3.5
ELECTRICITY DEMAND ............................................................................................................. 16
3.6
FINAL ENERGY DEMAND – OTHER ENERGY CARRIERS THAN ELECTRICITY ............................................. 17
3.7
CONCLUSIONS FROM THE STUDY COMPARISON............................................................................. 19
QUANTIFICATION OF TECHNICAL AND ECONOMIC ENERGY SAVING AND EMISSION
REDUCTION POTENTIALS.............................................................................................................. 22
4.1
METHODOLOGY OF POTENTIAL DETERMINATION .......................................................................... 23
4.1.1
Methodology to determine the technical final energy saving potentials ..................... 24
4.1.2
Adjustment of data due to new framework conditions ................................................ 33
4.1.3
Specific issues concerning the methodology to determine economic final energy saving
potentials ................................................................................................................................... 36
4.1.4
Methodology to determine the technical primary energy saving potentials................ 42
4.1.5
Methodology to determine the greenhouse gas emission reduction potentials .......... 46
4.2
ENERGY SAVING AND EMISSION REDUCTION POTENTIALS OF „CALCULATED WEDGES“ ........................... 48
4.2.1
Households, tertiary - Building envelope ...................................................................... 53
4.2.2
Households, tertiary - Heating and cooling systems ..................................................... 61
4.2.3
Households, tertiary - Lighting...................................................................................... 69
4.2.4
Households, tertiary - Green ICT ................................................................................... 77
4.2.5
Households - Household appliances ............................................................................. 86
4.2.6
Industry - Paper and pulp industry ................................................................................ 94
4.2.7
Industry - Steam and hot water generation................................................................ 102
4.2.8
Industry - Electric drives .............................................................................................. 111
4.2.9
Industry – E-drive system optimisation ....................................................................... 119
4.2.10
Transport - Technical improvements ...................................................................... 126
4.2.11
Transport – Behavioural changes ........................................................................... 134
4.2.12
Transport – e-Mobility ............................................................................................ 141
4.3
TECHNICAL ENERGY SAVING POTENTIALS OF “ESTIMATED WEDGES” ................................................ 147
Household sector ........................................................................................................................... 147
Tertiary sector ................................................................................................................................ 147
Industry sector ............................................................................................................................... 150
Transport sector ............................................................................................................................. 154
Energy conversion .......................................................................................................................... 156
Energy transmission and distribution ............................................................................................. 157
4.4
OVERVIEW OF TECHNICAL AND ECONOMIC ENERGY SAVING AND EMISSION REDUCTION POTENTIALS ..... 161
EU-wide saving potentials on sectoral level................................................................ 161
4.4.1
Household sector ................................................................................................................................ 161
Tertiary sector ..................................................................................................................................... 166
Industry sector .................................................................................................................................... 169
Transport sector .................................................................................................................................. 173
4.4.2
Overview of potentials on national levels ................................................................... 177
Germany ......................................................................................................................................... 180
France ............................................................................................................................................. 182
Italy ................................................................................................................................................. 184
Spain ............................................................................................................................................... 187
Poland............................................................................................................................................. 190
Comparison of national saving potentials ...................................................................................... 192
5
SUMMARY AND DISCUSSION OF RESULTS ......................................................................... 195
5.1
OVERALL FINAL ENERGY SAVING POTENTIALS.............................................................................. 195
5.2
OVERALL PRIMARY ENERGY SAVING AND GHG EMISSION REDUCTION POTENTIALS ............................ 203
5.3
REARRANGEMENT OF WEDGES ................................................................................................ 211
ANNEX I
SCENARIO DESCRIPTIONS ...................................................................................... 218
ANNEX II
OVERVIEW OF POTENTIAL WEDGES FOR IN-DETAIL ANALYSIS .............................. 221
II.I
Introduction..................................................................................................................... 221
II.II
Historic development of primary and final energy demand in the EU27 .................... 222
II.III
Selection of wedges .................................................................................................... 226
II.III.I
Buildings ..................................................................................................................... 228
II.III.II
Appliances and IT ................................................................................................... 229
II.III.III
Industry sector – Cross-cutting technologies .......................................................... 230
II.III.IV
Industry sector – Process technologies ................................................................... 231
II.III.V
Transport sector ..................................................................................................... 232
II.III.VI
Conversion sector ................................................................................................... 233
II.IV
Summary of potential estimation ............................................................................... 234
ANNEX III
METHODOLOGY OF THE ECONOMIC POTENTIAL OF CHP PLANTS .......................... 237
ANNEX IV
ENERGY SAVINGS THROUGH ELECTRIC VEHICLES .................................................. 240
IV.I
Detailed calculation methodology .............................................................................. 240
IV.II
Scenario assumptions and results ............................................................................... 244
ANNEX V
ELECTRICITY SAVING POTENTIALS ......................................................................... 247
REFERENCES ............................................................................................................................... 249
GLOSSARY .................................................................................................................................. 257
1
1
Background
It is the aim of the European Union (EU) to limit in a worldwide cooperation the
global temperature rise in this century to not more than 2°C beyond the preindustrial level because there is strong scientific evidence that a larger temperature
increase may imply considerable danger for the development of life. If 2°C are not
to be exceeded, it is necessary that the worldwide greenhouse gas emissions
(GHG) reach their maximum between 2020 and 2030 and are then reduced to half
the amount of 1990 by 2050 1. In order to achieve this target both developed and
developing countries need to make considerable efforts, independent from the discussion on historic responsibilities for the greenhouse gas effect. The developed
countries and in particular the European Union need to play a prominent role and
reduce the emissions by at least 80 % in 2050 2, 3.
Potential pathways towards this 80% reduction target were analysed in the framework of the EU Energy Roadmap 2050, which was published in December 2011 by
the European Commission (European Commission, 2011e). Apart from a Reference Scenario, five decarbonisation scenarios were analysed, which combine to
varying degrees the low-carbon options of renewables, nuclear, energy efficiency
and CCS. The scenarios show that meeting the 80% GHG reduction target is feasible regardless of the technology mix applied.
1
Proposal of the EU Commission for a comprehensive ambitious new global climate protection
agreement (Post Kyoto): in order to limit the global temperature rise to 2°C, worldwide emissions
should reach their maximum before 2020 and fall to half the level of 1990 by 2050. This target
was also announced at the G8 Summit in summer 2008. In order to reach this target, developed
countries should reduce their emissions by 30 % up to 2020 (compared to 1990) while the developing countries, except the poorest have to reduce their emissions by 15-30 % compared to
Business-as-usual. European Commission (2009): Communication from the Commission to the
European Parliament, the Council and Social Committee and the Committee of the Regions - Towards a comprehensive climate change agreement in Copenhagen. COM(2009) 39 final. Brussels, 28.1.2009.
2
In October 2009 the EU Head of States decided on a long-term reduction target of 80-95 % by
2050 in comparison to 1990.
Council of the European Union, 15265/1/09 REV 1, Brussels, 1 December 2009
http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/110889.pdf and
http://ec.europa.eu/governance/impact/planned_ia/docs/225_ener_low_carbon_energy_system_2
050_en.pdf
3
European Climate Change Foundation ECF: Roadmap 2050
http://www.roadmap2050.eu/
2
In March 2011, the EU Commission presented its 2050 Low Carbon Economy
Roadmap 4, which has as a target the development of the EU climate (and energy)
policy for the next 40 years. This roadmap was the first official document to set the
scene for the European energy and climate policy up to 2050. The analysis shows
that all sectors need to contribute in different proportions to the target, reaching
from a reduction in GHG emissions of 42-49 % for the agricultural sector compared
to 1990 up to 93-99 % for the power sector (Table 1-1).
By 2030 a reduction of 40 to 44 % in GHG emissions is required for the EU to keep
the path.
Table 1-1:
Sectoral reductions required in the EU Low Carbon Roadmap
Source: (European Commission, 2011a)
In order to reach these ambitious long-term targets the EU needs to reduce its
emissions as an interim target by around 30 % by 2020 compared to 1990. The
European Union decided in 2008 the European Climate and Energy Package with
concrete measures and directives up to 2020, which shall reduce the GHG emissions in the period 1990-2020 by 20 % respectively 30 %, if the necessary conditions are fulfilled 5. Part of this package are the increase of the share of renewables
in the total EU energy consumption to 20 % by 2020 and the reduction of energy
consumption by 20 % compared to the trend up to 2020. This last target has not
been translated in the Climate and Energy Package of 2008 into a legally binding
text. Nevertheless, the European Council has included in March 2010 the 20 %
energy efficiency target – together with the two other climate protection and energy
4
Communication from the Commission to the European Parliament, the Council, the European
Economic and Social Committee and the Committee of the Regions, A Roadmap for moving to a
competitive low carbon economy in 2050, SEC(2011) 287 final, SEC(2011) 288 final, SEC(2011)
289 final, Brussels, 8.3.2011, COM(2011) 112 final. (http://ec.europa.eu/clima/documentation/
roadmap/ index_en.htm)
5
Both at EU-level as well as on national European levels there are increasing voices which demand to take the steps towards a 30 % GHG-target for the EU, in particular when it is considered
that the emissions in the EU develop less rapidly than originally expected due to the financial and
economic crises, http://www.co2-handel.de/article185_14724.html.
3
policy targets – as one important key target in the central economic and competition strategy of the EU 6. In the document "Europe 2020: Strategy for intelligent,
sustainable and integrated growth " 7 this target is together with the other targets of
the strategy taken up in a yearly progress monitoring, in particular based on indicators.
The recent discussion concerning a possible mandatory target for energy efficiency
shows that this element is on one hand still insufficiently anchored in the EU and
Member States legal building but is on the other hand the most central element of
any climate strategy. At present, only the Energy Efficiency and Energy Services
Directive 2006/32/EC foresees in a legal text up to 2016 a reduction of the energy
consumption in the European Union by 9 % (indicative reduction target for energy
consumption). National Energy Efficiency Action Plans NEEAPs shall explain how
the targets are reached. In addition, many EU Member States have national energy
efficiency and saving targets. Germany for example has committed in the Energy
Concept from September 2010 to reduce energy consumption by 50 % in 2050 and
electricity consumption by 25 % and confirmed these targets in the update of the
Energy Concept from June 2011.
At EU-level the actualisation of the EU efficiency strategy was published in March
2011 in the form of an EU Energy Efficiency Plan EEP 8. The EU fixes a two-step
approach, pushing a possible overall mandatory energy efficiency target back to
2014 (originally 2013) but advancing in the field of individual energy efficiency policies that was affirmed in the proposal for a new Energy Efficiency Directive 9 from
June, 22nd 2011. The EEP details sector by sector envisaged energy efficiency
actions, in particular in the building sector.
At the same time, due to the economic and financial crises, the very volatile energy
prices at the international energy markets, increasing concentration of energy resources on few supplying countries with markets that are largely regulated by the
6
European Council: Conclusions, 25/26 March 2010,
http://www.consilium.europa.eu/uedocs/cms_Data/docs/pressdata/en/ec/113591.pdf
7
http://ec.europa.eu/eu2020/pdf/COMPLET%20%20DE%20SG-2010-80021-06-00-DE-TRA-00.pdf
(S. 34)
8
Communication from the Commission to the European Parliament, the Council, the European
Economic and Social Committee and the Committee of the Regions,, Energy Efficiency Plan
2011, SEC(2011) 275/276/277/278/279/280, Brussels, COM(2011) 109/4
(http://ec.europa.eu/clima/documentation/roadmap/index_en.htm)
9
“Finally, the proposal provides for the establishment of national energy efficiency targets for2020
and requires the Commission to assess in 2014 whether the Union can achieve its target of 20 %
primary energy savings by 2020. The Commission is required to submit its assessment to the
European Parliament and the Council, followed, if appropriate, by a legislative proposal laying
down mandatory national targets.” (European Commission, 2011c, p. 5)
4
state, temporary supply bottlenecks and new resource which are more difficult to
open up, factors like supply security and the cost of energy supply take more
weight in the public perception. This makes it necessary to develop a detailed medium to long-term perspective for energy efficiency, as a main contributor to the
problem solutions.
5
2
Objectives of the study
The main purpose of this study is to analyse in depth the potentials and contributions of energy efficiency and energy saving options to the climate policy targets in
the EU up to 2050 with quantified intermediate targets for the years 2020, 2030,
2040 und 2050. A second study is investigating in detail the design of a European
electricity sector based on renewables to up to 100 % (cf. “Tangible ways towards
climate protection in the European Union - EU Long-term scenarios 2050”).
In the present study, a guiding path is to be developed for these time horizons underlain with concrete technical potentials and cost curves.
The whole study is divided into the following working packages:
1. Potential analysis to reduce greenhouse gas emissions through the increase of energy efficiency and energy savings by 2050 in the form of
“wedges”.
2. Cost and benefit analysis of climate protection measures through enhanced
energy efficiency and energy savings.
3. Contribution of energy efficiency enhancement to climate protection in
2050.
4. Short-term advice concerning questions related to EU climate and energy
policy.
After determining the potentials, the results are compared to the scenario results of
the recently published EU Energy Roadmap 2050 (European Commission, 2011e).
This report presents the detailed results of the work package one to three. Apart
from the technical and economic potential analysis of energy efficiency technologies to reduce final as well as primary energy demand and the emission of greenhouse gases, this report includes a comparison of existing studies of the European
energy market.
An additional policy report summarizes the main insights of this study and the resulting conclusions.
6
3
Study comparison for the contribution of energy
efficiency in the EU27 to the 2050 climate targets
3.1
Introduction
In this section a number of energy forecasts are analysed regarding the projected
final and primary energy demand, the future electricity demand and the contribution
of energy efficiency measures to energy savings up to 2050. Table 3-1 lists the
studies included in this report, their key features and the scenarios analysed.
All the data publicly available have been included in this study comparison. However, there are big gaps in data availability and inconsistent assumptions that limited the choice of analysed data and aspects.
Due to the fact the reports focus on different geographical regions (EU27 or EU27
+2, including Switzerland and Norway), the overall figures might not be directly
comparable. Therefore relative changes are calculated and compared with each
other.
In the following sections only studies reaching up to 2050 were considered (while
the overview in Table 3-1 also mentions further studies reaching up to 2030, in
particular the two studies I-TREN2030 and HOP! focusing on the transport sector
in the first, and on high oil prices in the second case).
7
Table 3-1:
Overview of EU Energy scenarios
Study
PRIMES: Baseline
2009
European Commission: ADAM
European Commission: WETO-H2 11
IEA: World Energy
Outlook 2010
IEA: Energy Technology Perspectives
2010 12
GP - Greenpeace
/EREC: Energy
[R]evolution
ECF/McKinsey:
Roadmap 2050
Final energy consumption
compared to Base Year (BY),
by 2050
Base
Ref
Ref
450ppm
400ppm
Ref
H2
CCC
CPS
NPS
450ppm
compared to Reference Scenario by
2020
2030
2050
-1%
-2%
0%
-12%
-22%
-38%
-16%
-29%
-48%
-3%
-5%
-4%
-8%
-11%
-10%
-2%
-5%
-4%
-9%
-
Blue
Scenario
yes
-
-
-31%
-
Reference
GP-Ref
-
-
-
+20% (‘07)
Advanced [R]evolution
GP-Adv. E[R]
-8%
-18%
-36%
-24% (‘07)
Reference
80% RES
Ref
80% RES
-
-
-
-
Time
PubGeographihoriScenarios
lished
cal spread
zon
Baseline 2009
2010 2030 EU27
Reference
Reference
2009 2050 EU27 +2 10 450ppm
400ppm
Reference
EU27+2
2007 2050 +TR
H2 Case
+Balkan
Carbon Constraint Case
CPS
2010 2035 EU27
NPS
450ppm
2010 2050
OECDEurope 13
2010 2050 EU27
2010 2050 EU27+2
Code
2030: +4% (BY: 05)
2030: +1% (’05)
+14% (‘05)
-30% (‘05)
-43% (‘05)
+20% (‘01)
+17% ('01)
+8% (01)
2035: +10% (08)
2035: +2% (‘08)
2035: -3% (‘08)
10 EU27 +2 comprises EU27 plus Norway and Switzerland
11 Has not been included in the detailed scenario comparison due to the differing geographical spread
12 Has not been included in the detailed scenario comparison due to differing geographical spread and lack of data
13 OECD-Europe comprises all European Union Member countries of the OECD, i.e. countries in EU15 plus the Czech Republic, Hungary, Iceland, Norway, Poland,
Slovak Republic, Switzerland, Turkey
8
Study
iTREN 2030
HOP!
European Commission: EU Energy
Roadmap 2050
compared to Base Year (BY),
by 2050
Ref
compared to Reference Scenario by
2020
2030
2050
-
Integr.Tr.
-12%
-20%
-
2030: -6% (‘05)
Ref
-
-
-
Primary: +12% (‘05)
150
-
-17%
-14%
Primary: +4% ('05)
220
-
-11%
-12%
Primary: +2% (‘05)
Reference
Ref
-
-
-
+5% (’10)
Current Policy Initiatives
CPI
-6%
-4%
-5%
-0% (’10)
Energy efficiency
High EE
-9%
-14%
-40%
-36% (’10)
Time
PubGeographihoriScenarios
lished
cal spread
zon
Reference (pre-crisis)
2010 2030 EU27
Integrated Transport
(with crisis)
Reference
150 Smooth (high oil
2007 2050 EU27
price)
220 Smooth (high oil
price)
2011 2050 EU27
Source: Fraunhofer ISI
Code
2030: +18% (‘05)
9
3.2
Primary energy demand
Figure 3-1 shows the projected primary energy demand in different scenarios for
the EU27 14. Since the primary energy demand can be calculated by using different
methods (e.g. the calculation of the primary energy demand for RES) an entire
comparability of the data cannot be guaranteed. An analysis of the calculation
methods applied has not been undertaken.
The red lines represent the primary energy demand forecast according to the
PRIMES 2009 scenarios. They represent the business-as-usual trend, considering
no further effort than national and EU policies implemented until April 2009 (cf.
Baseline scenario) or adopted until December 2009, respectively (cf. Reference
scenario).
Figure 3-1:
Total primary energy demand by scenario, EU27
14 In the case the data was only available for EU27+2 (ADAM report and ECF report), an adjustment
was carried out, reducing the overall energy demand by eliminating Norway and Switzerland according to their share in the year 2008
10
The green dotted line represents the reduction pathway towards the 20 % energy
saving target for 2020, as announced in the 2006 Energy Efficiency Action Plan
(European Commission, 2006). Since this target is related to the pre-recession
scenario of the PRIMES 2007 baseline, the green graph in Figure 3-1 represents
the pathway from the PRIMES 2007 baseline value in 2010 (1852 Mtoe) towards
the absolute target of 1602 Mtoe in 2020 (instead of 1971 Mtoe in the 2007 baseline scenario) 15.
Figure 3-1 clearly depicts that only the ambitious Greenpeace scenario (which is
called “advanced Energy [R]evolution” scenario) complies with the -20 % efficiency
target.
However, there are further essential differences among the studies examined:
• According to the IEA-450ppm scenario, by 2020 primary energy demand
decreases only by 7 % compared to the EU baseline scenario. By 2035 it
will decline by 9 % compared to the IEA Baseline scenario and less than
5 % compared to the 2008 emissions level, accounting for almost 340 Mt
GHG emissions abatement. The main drivers are greater efficiency in direct
combustion of fossil fuels and lower electricity demand attributable to
greater efficiency in end use.
• Considering no further policies (Current policies scenario, CPS), an increase of primary energy demand will occur, comparable with the demand
level of the PRIMES baseline. The implementation of broad policy commitments that have already been announced (see New Policies Scenario,
NPS) would only lead to a stagnation of energy demand by 2030.
• Under the Greenpeace Energy [R]evolution scenario, the most ambitious
primary energy efficiency measures are assumed, targeting on an energy
demand reduction of 11 % by 2020 16 and 40 % by 2050 (compared to the
Greenpeace Reference scenario).
• The ADAM scenarios represent a compromise of the first two cases, reaching a primary energy demand reduction of about 28 % in the 450ppm scenario and 36 % in the 400ppm scenario compared to the ADAM Reference
scenario. The final energy demand reduction in the ADAM-400ppm scenario is higher than in the Greenpeace Advanced Energy [R]evolution sce-
15 The target value of 1602 Mtoe is calculated by applying the 20 % reduction on the forecasted
energy demand of PRIMES 2007 for energy uses, excluding non-energy uses.
16 This implies that the Greenpeace Energy [R]evolution scenario only reaches the absolute level of
the primary energy 20 % reduction target set by the PRIMES 2007 baseline due to the already
rather moderate baseline development of the Greenpeace Reference scenario.
11
nario. However, regarding primary energy, the Greenpeace scenario
reaches higher energy saving targets. This is linked to the fact, that the
Greenpeace scenario is mainly based on Renewable energy sources (see
Figure 3-2). Since the primary energy demand of RES is normally calculated by using a conversion efficiency of 100 %, an increasing share of RES
goes along with a relative decrease in primary energy demand.
• Under the Reference scenario of the EU Energy Roadmap 2050 is approximately stagnating on today’s level, whereas the most recent policy actions and the consequences of the financial and economic crisis from
2007/2008 result in long-term savings of nearly 8 % compared to 2010 (cf.
CPI scenario). The most ambitious energy demand trajectory is determined
under the efficiency scenario, where primary energy demand is reduced by
about 38% compared to the Reference projection. The 20 % efficiency target is missed in all Roadmap scenarios.
Regarding the general fuel composition of primary energy demand, the scenarios
provide different approaches towards a decarbonised energy system (cf. Figure
3-2). The IEA-450 ppm scenario suggests an immediate increase of nuclear energy
sources and RES, compensating for a declining consumption of coal, natural gas
and oil. On the long term view (Blue map scenario) all newly installed coal and
most of the gas power plants are equipped with Carbon Capture and Storage
(CCS) technology. The combination of CCS and nuclear power ensures a stabilization of CO2 emissions at the 450 ppm level despite the limited exploitation of energy efficiency measures and RES.
The Greenpeace scenario is mainly based on RES (86 % in 2050) and oil and gas,
aspiring to a phase out of nuclear power in the medium term (around 2030) and of
coal power in the long run (by 2050). The ADAM-400ppm scenario combines the
further extension of RES and nuclear power (33 % and 19 % respectively in 2050)
in order to realize the phase out of carbon intensive coal and a reduction in oil and
gas consumption.
The Energy Roadmap’s Reference scenario mainly relies on oil (32 % of primary
energy consumption in 2050). Nuclear and renewable energy sources increase
their contribution up to 17 % and 20 %, respectively. Under the efficiency scenario,
the trend is partly reversed. Only 15 % of the entire primary energy demand in
2050 is covered by oil whereas RES contribute 43 % and gas 24 %.
12
Figure 3-2:
Total primary energy demand by fuel, EU27
3.3
Final energy demand
Figure 3-3 shows the final energy consumption of EU 27 divided by sectors and by
fuels. In 2008, the total final energy demand of 1170 Mtoe is consisting of the
transport (32 %), industry (27 %), household (25 %) and tertiary sector (12 %). The
main end use energy carriers are oil products, different kinds of natural gas derivatives and electricity.
The various final energy consumption projections differ a lot from one to another
(cf. Figure 3-4). While some forecasts expect a decrease in energy demand even
in the business-as-usual scenarios (PRIMES Baseline 2009 and ADAM Reference
scenario) others forecast a further increase (such as the IEA Current policies scenario) if no additional measures are undertaken.
13
Figure 3-3:
Historical final energy demand in EU 27
Source: Eurostat
Regarding the sectoral spread of energy demand reductions in the decarbonisation
scenarios, there is not a particular sector that can be identified as the crucial one.
Transport and residential sector experience the strongest decrease in energy demand, however other sectors register a declining demand, too. Further details can
be found in the paragraph on the sectoral analysis and Figure 3-5.
Figure 3-4:
Final energy demand in the different scenarios, EU27
14
The IEA-450ppm scenario does apply efficiency measures as a main tool for GHG
emissions abatement, but equally prioritises the use of CCS technology and nuclear power. That is the reason for a first increase in final energy demand that
drops only after 2020. Considering the introduction of a number of new policies
aiming on the 450ppm target would lead to a decrease in final energy demand of
only 9% by 2030, compared to the reference development.
In contrast, the decarbonisation scenarios of the EU Energy Roadmap, ADAM and
Greenpeace envisage strong efficiency measures from the very beginning. Comparing the gradual increase of energy savings (see Table 3-2), an equally spread
increase can be observed in the ADAM scenarios, whereas the Greenpeace scenario attains its maximal rise in the 2030 to 2040 decade. Under the efficiency scenario of the Energy Roadmap, energy savings are stepwise increased, reaching
their maximum reduction after 2030. The high energy saving rates in the ADAM
scenario are based on the fact that the total energy savings are higher than in any
other scenario.
According to Greenpeace, the condition for the realisation of the mentioned energy
saving potentials consists of binding energy saving targets, strict efficiency standards for vehicles, improved heat insulation and building design as well as efficient
electrical machines and drives.
Table 3-2:
3.4
Final energy demand reduction compared to the base year (BY)
BY - ‘20
2020‘30
2030‘40
2040‘50
BY - ‘50
IEA-450ppm
+1.3%
-1.6%
-
-
-
ADAM-450ppm
-9.8%
-11.4%
-10.7%
-9.9%
-42%
ADAM-400ppm
-13.9%
-14.4%
-12.8%
-11.4%
-52%
GP-adv. E[R]
-4.4%
-6.9%
-9.8%
-2.9%
-24%
Roadmap-High EE
-3.5%
-8.3%
-12.7%
-12.0%
-36%
Sectoral analysis
Comparing the two most energy consuming sectors (industry and transport, cf.
Figure 3-5) shows a much higher decrease in the transport sector in all scenarios,
15
where energy demand can be reduced by up to 50 % by 2050 (cf. Greenpeace
Energy [R]evolution scenario). Already in the first decade energy savings of up to
15 % can be realised in the most ambitious cases.
The ADAM scenario assumes a decreasing energy demand even in the Reference
scenario. In the industry sector, this development might be explained by an autodiffusion of energy and cost-efficient industry technologies due to international
competition. Decreasing energy demand in the transport sector can be traced back
to decreasing population numbers (decrease of 5 % between 2010 and 2050 in all
scenarios) and a shift to highly end-use efficient electric vehicles.
Building related energy demand is supposed to increase in all business-as-usual
trajectories. However, if efficiency measures are undertaken, demand can be reduced by more than 60 % according to the ADAM 400ppm scenario.
Figure 3-5:
Final energy demand in the buildings 17, industry and transport sector 18, EU27
17 comprises the demand of households, services and other sectors
18 The 20 % energy saving target is not represented in this chart since it is related to primary energy
demand on the overall level.
16
3.5
Electricity demand
Electricity as one of the final energy carriers is analysed more in detail due to its
increasing significance. Figure 3-6 depicts the future electricity demand. The total
electricity consumption in the decarbonised scenarios is marginally lower (cf. GP
scenario) or even above the demand in the Reference scenarios (cf. ECF scenario). Only in the ADAM-450ppm/-400ppm scenarios, a decrease of electricity
demand can be observed due to strong efficiency measures.
The shift from conventional drive technologies of cars with internal combustion engines to electric vehicles and plug-in hybrids as well as a shift from road to rail
transport (modal shift) lead to an essential increase in electricity demand in the
transport sector. Additionally, the substitution of thermal heating in buildings and
industry applications by electric heat pumps is amplifying the electrification effect. A
virtually decarbonised power sector (as foreseen in most of the mitigation scenarios) is the main driver for this shift, enabling the buildings and transport sectors to
reduce CO2 emissions by additional electrification.
Figure 3-6:
Final electricity demand by sector, EU27
Figure 3-7 illustrates exemplarily the compensation effect and the reasoning for the
strong increase in electricity demand throughout the decarbonisation scenarios. As
17
can be clearly seen, a higher deployment of electric transport means and electric
heating compensates for the electricity demand reduction through increased efficiency in buildings and industry.
Figure 3-7:
Compensation effect of energy efficiency by electrification
Source: (ECF, 2010a)
3.6
Final energy demand – other energy carriers than
electricity
Regarding the final energy demand being covered from any other energy carrier
than electricity, three main observations can be made:
• The consumption of oil and gas derivatives is declining in all reference and
decarbonisation scenarios. Limited availability of crude oil 19 and the associated rise in prices are supposed to be the main drivers for such a development that is even more distinct in the decarbonisation scenarios.
19 According to the IEA’s World Energy Outlook 2010, oil extraction will stagnate on nowadays’ level
before declining within the coming years. See IEA, World Energy Outlook 2010, page 122
18
• Renewable energy sources compensate the decreasing use of oil derivatives (e.g. biofuels) and cover an increasing share in heat supply (e.g. wood
pellets). In decarbonised energy scenarios the deployment of renewable
raw material grows faster due to corresponding policies. However, the total
exploitation of those renewable resources differs among the scenarios
based on different assumptions on the sustainable potential of biomass.
• While electricity demand is supposed to rise even in most of the decarbonisation scenarios, the net final energy savings are realized in the field of the
other energy carriers. In the Reference scenarios, however, final energy
demand remains in a range of about 15 % above or below today’s level.
Figure 3-8:
Final energy demand by energy carrier (except electricity), EU27
19
3.7
•
Conclusions from the study comparison
Regarding the methodology:
The main focus of all studies is set on the reduction of CO2-emissions. Energy
efficiency is considered as one of the most powerful options to reduce GHG emissions. However, renewable energy sources (RES), Carbon Capture and Storage
(CCS) and other “pro-active” measures (such as e-Mobility, nuclear power supply) are discussed much more in detail than energy saving and energy efficiency
measures. Most of the studies lack a detailed analysis of single energy efficiency
technologies. Only the overall energy saving potential and some general energy
efficiency measures are roughly drafted in most of the studies. It can therefore be
concluded that none of the studies (except the ADAM study) included a detailed ambitious analysis of energy efficiency options up to 2050.
The power sector represents the main if not the only subject analysed in the majority of the studies (e.g. European Climate Foundation, “Roadmap 2050”). Electricity generation and transport options are discussed in detail whereas the building
and transport sector despite their high energy efficiency potentials attract much
less attention.
•
Regarding the results:
A general finding of all studies is the fact that ambitious energy efficiency policies
are needed in order to stabilize CO2 emissions on a level of 450ppm. There is a
common understanding that although energy efficiency measures can be combined with a number of other CO2 abatement options (such as RES, nuclear power,
CCS), they represent an indispensable option for reducing greenhouse gas
emissions. Neglecting this option cannot be compensated by an increased deployment of one of the options mentioned above. Nevertheless final energy demand projections in the majority of the scenarios considered are not falling
below the 50 % threshold of the respective reference energy demand in 2050.
The EU announced in its 2008 climate and energy package the non-binding target
of reducing primary energy demand by 20 % compared to the PRIMES 2007 baseline scenario by 2020 and reconfirmed it in the Energy Efficiency Plan from March
2011. This 20 %-target is only met in the Greenpeace decarbonisation scenario.
Even under the decarbonisation scenarios of the EU Energy Roadmap 2050 this
target is missed.
20
Apart from the ADAM report, all studies come to the conclusion that electricity
demand will increase in the decarbonisation scenarios. This development is due
to a further electrification in the industrial, heat and transport sector (such as electric vehicles, heat pumps for industrial and residential use). The easier realization
of decarbonisation of electricity represents the main driver for the shift from other
energy carriers towards electricity. Energy efficiency measures are only a minor
driver for this shift. As a general conclusion for the development of the electricity demand it can also be stated that most of the scenarios lack a detailed
analysis of the demand development in the context of ambitious electricity
reduction policies.
Assigning carbon a price is a major pre-requisite for successful climate policy, even
though it is not a sufficient stand-alone instrument. However, all studies confirm
that a worldwide, multi sectoral and strictly organised emissions trading scheme
is an important incentive for a further increase in energy efficiency.
•
Comparative evaluation:
Although some scenarios forecast an increase in final energy consumption if no
further political measures are undertaken, such a development seems rather
unlikely compared to the historical evolution of energy demand. Hence, a rather
stagnating energy demand at the level of the last two decades of about 1,200
Mtoe seems most likely to arise for the EU27 in the absence of further policies to reduce demand (reference development).
The reduction scenarios also differ widely. In many cases the focus is on CO2reduction and energy efficiency is not developed to its full potential and
other options take renewables, CCS or nuclear take over. Therefore, none of
these scenarios, except the ADAM scenarios which carried out a more detailed
demand analysis, reach a level of 50 % demand reduction as compared to present.
The increasing electricity demand in the majority of the scenarios is subject to
discussion: Strict housing insulation standards for new dwellings such as specified
in the recently recast Energy Performance of Buildings Directive 20 will drive a
strong decrease in heat demand. Consequently, the need for heat pumps might
turn out less important than assumed in most of the studies. Moreover, the little
heat demand of such buildings might be covered by direct electric heating coming
from intermittent RES. However, the effect of electric vehicles can be assumed as
an important driver for a moderate increase in electricity demand.
20 Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings
21
On the basis of this analysis of different energy scenarios, a strong need for
a more in-depth analysis of single energy efficiency technologies is identified. In order to exploit the energy saving potential that is advocated as an important option in the whole set of all decarbonisation scenarios, concrete technologies
need to be evaluated regarding their potential and their cost-effectiveness.
22
4
Quantification of technical and economic energy
saving and emission reduction potentials
This chapter presents the results of work package 1.3 work package 2 and work
package 3. The main outcome is the technical and economic assessment of energy saving potentials based on specific efficiency technologies and the resulting
primary energy savings and greenhouse gas emission reductions.
All efficiency technologies are grouped in so-called “wedges”. According to
S.Pacala und R.Socolow wedges are subdivisions of necessary energy savings
into comparable units (Pacala, 2004). These units are sufficiently small that they
represent a single technology or a selection of technologies that can be tackled
with well-defined policy packages but still represent ambitious levels of savings.
The aim of the subdivision is to identify different options for action and to show that
the target can be achieved. Further information on the wedges philosophy can be
found in Annex II.I.
In a first step the wedges were shaped according to their topical similarities.
Within a second step, the wedges were split into two groups with regard to their
impact on energy savings and their ability of clear definition. The detailed selection
method is described in Annex II.III. The first group of wedges, which are selected to
undergo a detailed analysis, are named “calculated wedges”. They are explicitly
described in paragraph 4.1.4 using a specific fact sheet format. The second group
of wedges contains the so-called “estimated wedges”, that are rather shortly explained in 4.3
The third step consists of a subsumption of all wedges on a sectoral level (for the
household, tertiary, transport and industry sector, cf. 4.4.1) as well as on a national
level for a selection of specific countries (Germany, France, Spain, Italy, Poland, cf.
4.4.2).
Subsequently, the highest level of aggregation is reached by summarizing all final
energy saving potentials. (see paragraph 5.1).
Step five consists summarizing the overall primary energy savings and potential
greenhouse gas emission reductions that result from the final energy saving potentials (cf. 5.2).
In a last step, the wedges identified earlier are rearranged with regard to primary
energy savings and the achievement of the European Union’s 20 % efficiency target by 2020 (cf. section 5.3). The chapter is concluded by a taut summary and an
interpretation of the overall results.
23
In order to better understand the potentials identified, the main assumptions and
the adjustment of data are given beforehand (see 4.1).
4.1
Methodology of potential determination
This section presents the methodology used to determine the technical and economic energy saving potentials and the consequential greenhouse gas (GHG)
emission reduction in the following sections.
This study does not contain original modelling work but is mainly based on two
previous studies:
•
The European-wide study on energy efficiency potentials up to the year
2030 (ISI, 2009a).
•
The ADAM report for the time horizon between 2030 and 2050 (ISI, 2009c).
Given the fact that the economic boundary conditions as well as the energy prices
have changed since the underlying reports were made, explanations are provided
regarding the adjustment of data. Due to the fact that no original modelling work
was performed up to 2050, a certain number of simplifications had to be made.
We will provide in particular the following information:
•
Short presentation of the underlying studies
•
Which models and data have been used? What is the origin of the framework assumptions (e.g. energy prices)?
•
How were the results exploited and to which questions answers should be
provided?
•
How do we know the diffusion rate of energy efficient technologies? How do
we determine autonomous progress?
•
How exact are the results? How sensitive are they against changes?
•
How conservative are the results (e.g. with respect to energy prices)?
•
How are cost/benefits calculated?
•
How is the conversion of the final energy saving potentials into primary energy saving and GHG emission reduction potentials carried out?
24
4.1.1
Methodology to determine the technical final energy
saving potentials
Underlying studies
The technical and economic potentials presented in the following sections are
based on two studies:
•
One European-wide study on energy efficiency potentials up to the year
2030 carried out in the frame of the EU Directive for Energy Efficiency and
Energy Services ESD (“ESD potential study”. This study provides until 2030
(in fact the projection goes up to 2035), a detailed technology specific description identifying the main energy saving drivers and saving technologies
in a detailed manner (ISI, 2009a).
•
For the time horizon between 2030 and 2050, a further general outlook on
the energy saving potentials is given. Due to the high long term uncertainty,
the displayed potentials are not directly related to specific end-uses. These
data are based on the ADAM report (ISI, 2009c). The ADAM scenarios
were described in section 3.
•
For comparison purposes, the PRIMES 2009 baseline was extrapolated for
the time beyond 2030, using the scaled development of the ADAM report.
This approach enables the consideration of the economic crisis (see section
4.1.2).
Models and data sources used for the evaluation of energy efficiency potentials in the ESD Potential Study
The evaluation of energy efficiency and energy savings potentials at the demand
side in the ESD potential study was based on the bottom-up MURE simulation
tool. MURE (Mesures d'Utilisation Rationnelle de l'Énergie) has a rich technological structure for each of the four demand sectors (residential, transport, industry
and services) in order to describe the impact of energy efficient technologies
(Figure 4-1). Only a simulation model with sufficient technological details such as
MURE is well adapted to the purpose; Macro- and General Equilibrium models do
not have enough details in their sectoral representation for the required work. During the work performed in ISI (2009a) the technological details of the model were
further enriched to include more details on electric appliances and in particular on
IT appliances and IT infrastructures such as servers, as well as on industrial crosscutting technologies such as electric motors.
25
The structure described in a technological manner in MURE comprises modules
for:
o
Residential Sector Buildings
o
Residential Electric Appliances
o
Transport Sector
o
Industrial Sector: Processes
o
Industrial Sector: Electric Cross-cutting Technologies (pumps, ventilators, compressed air…)
o
Industrial Sector: Electric Cross-cutting Technologies (pumps, ventilators, compressed air…)
o
Service Sector Buildings
o
Service Sector Electric Appliances
o
IT Appliances (all sectors)
o
Demand-side CHP (all sectors)
As an example the representation of industrial processes is shown in Table 4-1.
The potentials for decentralised renewables such as solar thermal collectors and
decentralised PV installations were evaluated with the Green-X model run by TU
Vienna in cooperation with Fraunhofer ISI. This model was used extensively to
determine renewables potentials in the past and was used in the ESD potential
study in support of the MURE model.
The main data sources used in the study are also shown in Figure 4-1:
•
The statistical information was mainly derived from Eurostat data and the
Odyssee Database on Energy Indicators (http://www.odysseeindicators.org/) which is a harmonised data collection of national energy
data.
•
For the projections of activities determining the energy consumption this
was mainly data from the PRIMES 2007 baseline (more information on this
baseline is given below). This was a pre-recession baseline and corrections
were made in the present study to take into account the changed context
(see section 4.1.2).
•
Further, a multitude of technical information concerning energy efficiency
technologies for the various end-uses was collected in ISI (2009a) and discussed in expert rounds in order to describe as far as possible future developments and autonomous progress for the different technologies.
26
As mentioned above, to ensure compatibility with official EU Commission projections, it was decided to rely in ISI (2009a) on the choices of drivers of the baseline
scenario calculated with the PRIMES model (PRIMES 2007 projections). From these
projections drivers such as the number buildings, energy prices, the development of
value added of industry etc were chosen in order to be consistent with these projections.
27
Figure 4-1:
Models and data sources used for the evaluation of energy efficiency potentials in the ESD Potential Study
Analysis of Energy
Saving Potentials
Feeding sources:
 Existing technology information within MURE and other
sectoral models used by the
team
 Odyssee Database
 Sectoral and country studies
MURE Demand Simulation Modules
 Residential Sector Buildings
Demand
Technology Database
 Residential Electric Appliances
 Transport Sector
 Industrial Sector: Processes
 Industrial Sector: Cross-cutting Technol.
Induced Technological
Change
Feeding sources:
 Official DG TrEn and national
projections
Scenario Database
 Official EU and national statistics
Induced Technological
Change
 Service Sector Buildings
 Service Sector: Electric Appliances
 IT Appliances (all sectors)
 Demand-side CHP (all sectors)
RES
Technology DataGreen-X Model for renewables
 (decentral) RES-E
 (decentral) RES-H
Source: (ISI, 2009a)
Output Database
Communication of
Results
28
Table 4-1:
Example for the technology-rich structure of the demand side model
used: Processes by sub-sector implemented in the industrial submodel of MURE
Iron and Steel
Non-ferrous metals
Paper and Printing
Sinter
Primary Aluminium (Hall-Heroult)
Paper
Blast furnace
Secondary Aluminium
Mechanical Pulp
EAF
Aluminium Further Treatment
Chemical Pulp
Rolled steel
Primary Copper
Recovered Fibres
Coke oven
Secondary Copper
Smelting reduction
Copper Further Treatment
Direct reduction
Primary Zinc: Imperial Smelting
Zinc: Galvanizing
Glass
Cement
Chemicals
Container glass
Clinker burning-Dry
Chlorine-Hg (mercury)
Flat glass
Clinker burning-Semidry
Chlorine-Membrane
Other glass
Clinker burning-Wet
Chlorine-Diaphragm
Quarrying
Polypropylene (PP)
Raw material preparation
Polyethylene (PE)
Cement Grinding
Polyvinyl chloride (PVC)
Lime milling
Gypsum milling
However, some differences exist between the PRIMES 2007 baseline and the
baseline from ISI (2009a) concerning the assumptions on the success of important
policies The PRIMES 2007 Baseline scenario included policies and measures implemented in the Member-States up to the end of 2006. Differences with the ISI
(2009a) arise from the fact that the PRIMES baseline includes impacts from the
Energy Performance Directive of Buildings, while the baseline in ISI (2009a) excludes the impacts from the Directive; only the Autonomous Progress Scenario +
Recent Policies of this study does include the success of this policy. Further, in
difference to previous PRIMES projections success was not taken for granted for
the CO2 agreement for cars, although some further progress was assumed. As the
potentials from ISI (2009a) are referring to the Autonomous Progress Scenario,
compared to the present, some part of the potentials may have been taken up to
the point indicated by the “Autonomous Progress Scenario + Recent Policies” sce-
29
nario of ISI (2009a). In the following section 4.1.2 an approximate adjustment is
made of the energy efficiency potentials already taken up by ongoing energy efficiency policies after 2006.
Methodology for the determination of the technical and economic potentials
based on a scenario approach
In this section we will briefly describe the main methodological issues for the determination of the technical and economic potentials which are discussed in more
detail in ISI (2009a), in particular:
•
The dependency of the technical and economic potentials on a scenario
approach
•
The determination of autonomous progress for energy efficiency.
It may at first seem strange to define energy efficiency potentials - and in particular
technical potentials - in a scenario context: a certain technology may be able to
save X % of energy as compared to a reference technology and hence the technical potential of this technology is X %. However, this is too simplistic a view. Such
type of potentials may only be an indication of the long-term technical potentials
and could rather be called theoretical potentials. More realistic technical potentials need to take into account the dynamic aspects in the uptake of technologies as well as the time horizon during which a technology may reasonably be available. Two examples illustrate this issue:
•
For example buildings may reach zero-energy level or even become positive energy buildings. This is, however, only possible from today’s perspective for new buildings at some reasonable cost. Existing buildings must be
replaced by new buildings to achieve the same level of performance. However, it is a very strong assumption that buildings are torn down for energy
efficiency purposes before the end of their lifetime. ISI (2009a) has taken
the stake that energy efficiency is not a major driver for destroying old building stock. In the future, this may not be totally excluded but would need
quite dramatic events to have such actions to be taken.
•
The same arguments are valid for cars: experimental results have shown
that very light cars with special constructions may run 1500 km with 1 Litre
of gasoline (that is 1/15 of a litre per 100 km). In theory, if all friction losses
are overcome, cars may even run without fuel consumption at all. However,
30
this again is unlikely to occur in the time span of a few decades and is not
very helpful when considering concrete policies.
It is therefore necessary to go beyond the simple (static) theoretical potentials
which - depending on the time horizon – are largely overestimating the (dynamic)
technical potentials available at a given point in time. Hereby it is important to specify the meaning of the word “dynamic” which is underlying the scenario approach of
ISI (2009a).
Realistic technical energy saving potentials depend on the future development
of drivers such as the economic or social development (e.g. the stock of existing buildings, appliances, equipment of a type may be increasing or decreasing over time etc.). This takes into account that there are reinvestment
cycles which depend on factors other than energy efficiency.
ISI (2009a) has taken a rather conservative approach in that (with few exceptions) the usual investment cycles are not substantially modified. This is why
the diffusion of energy efficiency potentials takes time and the X% of the technological potential mentioned above is not penetrating the market immediately but
takes at least the lifetime of the reference technology. Although, ISI (2009) took a
rather conservative approach with respect to the degree to which behaviour can be
influenced.
One exception in ISI (2009a) to this was the assumption that the refurbishment
cycles for buildings can be enhanced by policy measures but which seems a rather
realistic assumption. In ISI (2009a) it was further assumed that behavioural or comfort factors would be influenced in a limited manner. For example, although it was
assumed that the speed of trucks may be influenced in order to enhance energy
efficiency or that the size of cars could be indirectly influenced by policy measures
such as the “Bonus-Malus” System of France (cars with low CO2 emissions – generally small cars - have an incentive compared to large cars), it was thought unrealistic that the size of houses may be strongly influenced by energy efficiency policies. This may have to be reconsidered if the impacts of climate change become
more dramatic.
Another aspect is that there are also competing energy efficiency technologies
which may penetrate with different speed. For example with respect to economic potentials one may have energy efficient technologies which save less energy but cost less and may, at intermediate levels conquer the market and open up
the path for the next more efficient technology (this is for example the case of electric A-class refrigerators which have opened up the way for the more efficient A+++
refrigerators. Though such intermediate steps may not be necessary, the real world
development has shown that most development towards energy efficient technolo-
31
gies is evolutionary and that it is unlikely that intermediate generations of energy
efficiency technologies are not required.
A third dynamic aspect to be considered is that technological innovation (learning
by searching) and scale effects (learning by doing) lead to a decrease in the cost of
energy saving technology over time.
All this discussion shows that it is reasonable to state that the dynamic dimensions
of the energy efficiency potentials lead to the necessity to define scenarios to
realise the potentials taking into account the (largely unchanged reinvestment cycles) and competing energy efficiency options.
In addition, it is important to understand that technology diffusion is a process in
time which might occur autonomously during normal reinvestment cycles or could
be influenced by market energy prices and/or energy efficiency policies. This is
why the dynamic technical and economic potentials have to be determined with
respect to a reference development which has a similar development of drivers for
energy consumption and penetration of (less efficient) reference technologies.
(Figure 4-2) summarises the different dynamic aspects of the potential determination which are:
 The general respect of reinvestment cycles which is expressed in the development of the drivers for energy consumption over time and (with few
exceptions) largely determined by factors outside the field of energy efficiency policies (dynamics in drivers)
 The competition and dynamics over time between more or less energy efficient savings options (dynamics in technology diffusion)
 Learning and scale effects which lead to a cost decrease of energy efficient
technologies over time (dynamics in technology innovation)
The first two dimensions are important for the definition of all potentials, including
the technical potentials while the last dimension is important for the definition of
economic potentials.
32
Figure 4-2:
Explanation of the notion "dynamic" in the context of economic and
technical potentials
For the calculation of these potentials in the scenario approach described above
the following three steps were carried out in ISI (2009a) for each energy use:
 Step 1: Set up saving options. For this step it was necessary to define
first possible saving options and then describe their technical performance
as well as their possible penetration in the future
 Step 2: Describe cost development. For each of the technology options
identified in the previous step it is necessary to describe the investment costs
and maintenance costs of each option. These cost categories are described
in general as differential costs compared to a standard technology or standard development, unless there is an acceleration of the investment cycle
beyond the usual values. In such cases the full costs or a larger cost are applied to the options scaled to the acceleration of the penetration of the energy
efficient technologies. In addition it is also necessary to consider that the differential costs will evolve dynamically over time and decrease down to the
level of the less efficient reference technology or even further. Over the past
decade an important body of empirical evidence has been gathered on energy efficient demand technologies which shows this important effect.
33
 Step 3: Set up the scenario mix. The different options defined in Step 1
may generally be realised altogether in a certain mix up to a given time horizon. It is therefore necessary to describe different scenarios of how the different options mix, depending on the potential considered.
In the scenario approach developed in ISI (2009a) it was necessary to describe
how much of the potentials are realised autonomously. The potentials specified
here and in that study refer to a reference development based on autonomous
progress. This is a difficult exercise which may be based on the progress achieved
in the past. However, the past development may have been influenced by higher
(or lower) energy price levels or by energy efficiency measures of the past. Energy
efficiency may also be influenced by structural changes or comfort factors in positive or negative way (for example the energy consumption of houses per square
metre increased in the past due to increasing room temperatures despite better
building regulations: there is about 7 % increase in energy consumption for every
degree higher room temperatures. Therefore, the consideration of past developments was complemented with expert interviews on the drivers of progress of energy efficient technologies in the absence of policies.
4.1.2
Adjustment of data due to new framework conditions
Adjustments of the potentials to new frame conditions
Due to the fact that the main studies the report is based on, ISI (2009a) and ISI
(2009c), did not consider the effects of the economic crisis, a subsequent adjustment of the energy saving potentials was necessary.
Both studies used the macroeconomic parameters provided by the PRIMES 2007
report (European Commission, 2008). The updated version, PRIMES 2009 (European Commission, 2010), forecasted a much more cautious increase of GDP and
final energy demand. Thus, the ratio between both final energy demand developments in the older and the newer version of the PRIMES forecasts was used as an
index for scaling down the energy saving potentials. Where the information was
available, the final energy demand of specific sectors or even user/appliance
groups was used.
This approach does not consider second order effects due to the change in frame
conditions. For example, the influence of other driving parameters such as new
energy price projections (compared to the former assumptions) could not be considered in detail since this would require a completely new modelling of the potentials. However, using the final energy demand index mentioned before, partly accounts for the price changes, too. The energy price changes where nevertheless
34
taken into account in the revision of the cost curves as the basis for the determination of economic potentials (see next section).
Rebasing the potentials in the new baseline in such a way does also take into account changes in energy efficiency policies which have occurred between 2007
and early 2009 to the degree that this is included in PRIMES. However, in specific
countries this does not include important policies since 2009. In particular in Germany progress has occurred since then with the ENEV 2009 which brought important changes for the existing buildings, which have to be renovated almost in all
occasions when there is more than just repainting of the facade (e.g. when the
plaster is changes of a house).
Figure 4-3:
Comparison of the final energy demand under PRIMES 2007 and
PRIMES 2009
Source: (European Commission, 2008), (European Commission, 2010)
Adjustments of the potentials to new energy prices
The version of the PRIMES projections used was European energy and transport:
Trends to 2030 – Update 2007 21. This baseline took into account policy developments up to the end of 2006 and was based on higher energy import prices compared to the 2005 edition of the baseline but considerably lower than the PRIMES
2009 baseline and present price levels which exceed 100 Dollar/barrel in nominal
terms. For example the oil price level of 62.8 US$2005 (real prices 2005) in 2030
(Table 4-2) roughly present today’s oil price level which to a certain degree may be
influenced by political events in the Arab world and other political events but also
the increasing scarcity of fossil fuels. It is difficult to provide for an exact estimate of
21 European Commission (2008): European energy and transport: Trends to 2030 – Update 2007.
Luxembourg: Office for Official Publications of the European Communities,
http://ec.europa.eu/dgs/energy_transport/figures/trends_2030_update_2007/index_en.htm
2008.
35
the impacts of higher energy prices on the potentials without full modelling. Nevertheless, adjustments were made to take into account changes to energy prices
between PRIMES 2007 and PRIMES 2009 projections in particular for the economic calculations.
Table 4-2:
Prices for EU imports of fossil fuels in $/boe in US$ used in PRIMES
(2007) and ISI (2009a), as well as PRIMES (2009)
2005
2010
2015
2020
2025
2030
PRIMES 2007 (US$2005/boe)
Oil
54.5
54.5
57.9
61.1
62.3
62.8
Gas
34.6
41.5
43.4
46.0
47.2
47.6
Coal
14.8
13.7
14.3
14.7
14.8
14.9
PRIMES 2009 (US$2008/boe)
Oil
59.4
71.9
72.6
88.4
101.6
105.9
Gas
39.7
44.2
49.5
62.1
74.6
76.6
Coal
14.0
17.2
21.7
25.8
29.2
29.3
Source: (European Commission, 2008 and European Commission, 2010)
From the changes in import prices new final user prices were calculated under the
assumption that there were no changes in the tax regimes for energy carriers in the
different countries (Figure 4-4).
36
Figure 4-4: New end-user prices used for the economic calculations up to 2050
4.1.3
Specific issues concerning the methodology to determine economic final energy saving potentials
Cost-benefits
Cost-benefits were calculated in ISI (2009a) from an end-user perspective by taking into account:
•
differential investments of energy efficient technologies as compared to the
standard technologies,
•
by making assumptions about the possible cost degression considering
empirical knowledge of the previous introduction of energy efficient technologies,
•
by annualising the differential investment using discount rates which are differentiated across sectors
•
by considering the annual costs of saved energy.
From this net benefits were calculated and translated into cost-reduction curves
which present the net cost of the saved energy (annualised investments mines the
annual costs of saved energy) versus the energy efficiency potentials available at
that net cost. No consideration was given to external costs which would further shift
37
the balance in favour of energy efficiency options as compared to the fossil fuel
alternatives.
Assumptions on discount rates used in ISI (2009a) are reported in Table 4-3 together with PRIMES discount rates. All rates are in real terms, i.e. after deducting
inflation. There are major differences between the two studies because PRIMES
converts non-economic barriers to high discount rates what distorts the information
on real costs of new technologies. The study ISI (2009a) distinguishes the Low
Policy Intensity (LPI) scenario with high discount rates which reflects economic
barriers to some degree (but still considerably lower than PRIMES 2007, except for
the industrial sector), and the High Policy Intensity (HPI) scenario with low discount
rates indicating policies to overcome barriers. Major differences between the HPI
and the LPI are also that non-economic barriers are removed to a large degree in
the first while they continue to act in the second: e.g. in the HPI it was assumed
that due to increased control of compliance with building regulation and training of
architects and installers, gaps to full compliance were largely removed.
Table 4-3:
Discount rates used in PRIMES 2007 and ISI (2009a)
ISI (2009a)
PRIMES
LPI
HPI
Industry
12%
30%
8%
Services and agriculture
12%
8%
6%
Households
17.5%
8%
4%
Private passenger transport
17.5%
8%
4%
Trucks and inland navigation
12%
8%
6%
Public transport energy investment
8%
8%
4%
Abbreviations: Low Policy Intensity (LPI) scenario and High Policy Intensity (HPI) scenario
Source: (European Commission, 2008) for the PRIMES column; (ISI, 2009a)
In the original study ISI (2009a) the energy efficiency options in the cost curves
were classified into three groups:
•
Options which in 2020 were economic also under the large discount rates of
the Low Policy Intensity (LPI) scenario shown in Table 4-3 (these potentials
were called LPI-Potentials).
•
Options which in 2020 were economic under the smaller discount rates of
the High Policy Intensity (LPI) scenario shown in Table 4-3 (these potentials
were called HPI-Potentials). The low discount rates are justified by supporting policies which help to overcome existing barriers.
38
•
Options which in 2020 were not economic even under the smaller discount
rates of the High Policy Intensity (LPI) scenario shown in Table 4-3 (these
potentials were called Technical Potentials). Due to the rather conservative
approach in ISI (2009), this does not include very exotic options and may
be called near-economic potentials.
This division into three groups of potentials was also kept in this study; however, in
order to avoid confusion with the original study and also because the potentials
and cost figures were extended to 2050, three new names were used to designate
the potentials and which also may better represent the nature of these three
groups:
•
“Low-hanging fruits (LHF)”: These are potentials which are economic already under high discount rates reflecting high risk perception.
•
“High-hanging fruits (LHF)”: These are potentials which are economic under low discount rates reflecting the removal of economic
and non-economic barriers by different policy instruments.
•
“Immature fruits (IF)”: These are potentials which are neareconomic under low discount rates but may be realised under acceptable additional costs.
These expressions will be used throughout this chapter to characterise these three
groups of potentials. The following has to be kept in mind, however:
-
The allocation of the options on the three groups in this study is not fully
identical in all cases with the allocation in ISI (2009) to the three groups LPI,
HPI and Technical. This is due to the shift in 2020 of the options to the new
energy price levels. For example some options in the building sector which
were still near-economic in ISI (2009) have become economic under the
higher energy carrier assumptions and are correspondingly allocated to the
“High-Hanging Fruits HHF” and not the “Immature Fruits IF”.
-
The division of the energy efficiency options on these three groups was
made for the year 2020. The allocation of an option was also kept for the
following decades 2030, 2040 and 2050 in order to be able to read the cost
curves more easily. However, some options may have moved from one
category to the other due to the increase in energy carrier prices and due to
the cost degression assumed for the options. This may have happened for
near-economic potentials in 2020 which could become economic in 2030 or
later.
39
Extension of the cost curves to 2050
The cost curves available from ISI (2009a) were available for 2020 and had to be
extended to 2030/2040/2050, by the following procedure:
-
From the cost curves developed for 2020, the original investment costs (in
real prices) were recalculated taking into account the original energy carrier
prices.
-
From the investment costs we recalculated the new cost curves for
2020/2030/2040/2050 taking into account the new energy prices of Figure
4-4. This took also into account that larger potentials are available for the
decades beyond 2020.
-
As the original cost curves includes a certain amount of technological learning which is derived from typical learning curves at the demand side, similar
cost degression levels are also included in the following decades. We did,
however, not make the assumption that with strong energy efficiency
policies over time up to 2050 this learning effect could be enhanced.
This is likely but so far there is no empirical evidence for this assumption. In
a conservative approach it was therefore assumed that also in the future
new generations of energy efficient technologies would come in at about
the same cost differential as during the decade up to 2020 and that those
costs will decrease over time until the next generation of more energy efficient technology comes in, again at a cost level like the previous generation.
-
Finally, we had to take into account an evolution of the energy carrier mix
up to 2050 in agreement with ISI (2009) and the ADAM-Study, which reflects the penetration of certain technologies such as heat pumps or renewables in the building environment. The development of the split of energy
carriers in the case of the built environment is shown in Figure 4-5, Figure
4-6 as well as Figure 4-7.
40
Figure 4-5:
Evolution of the energy carrier mix for space heating in households
up to 2050
Figure 4-6:
Evolution of the energy carrier mix for water heating in households
up to 2050
41
Figure 4-7:
Evolution of the energy carrier mix for space heating in the tertiary
sector up to 2050
42
4.1.4
Methodology to determine the technical primary energy
saving potentials
The transformation of final into primary energy saving potentials can be realised by
retracing the energy conversion chain and applying the overall conversion efficiency (see Figure 4-8). Given the fact that very different types of final energy carriers are saved through the efficiency measures (such as electricity, heat or natural
gas), the individual conversion pathways need to be considered.
Figure 4-8:
Energy conversion chain
Source: (Kaltschmitt, 2007)
According to the simplified scheme of the energy conversion chain in Figure 4-8,
two types of final energy can be distinguished. On the one hand side there are energy carriers that are directly converted from primary to final energy, featuring only
singular losses for conversion and distribution. In the present study, this energy
carrier type comprises all kinds of oil products (heating oil, gasoline, diesel and
kerosene) as well as natural gas, solids and renewable energy sources (RES). The
conversion efficiency of the respective energy carriers is shown in Table 4-4.
The second group of final energy carriers are those that cannot be directly generated from primary energy sources: electricity and heat. They are produced on the
basis of secondary energy which corresponds to the first group of energy carriers,
explained prior to this. Hence, the production of electricity and heat includes two
transformation processes that involve each conversion and distribution losses.
While the conversion efficiency from primary to secondary energy is equivalent to
43
the one explained further above, the conversion from secondary to final energy
strongly depends on the type of fuel (e.g. gas, coal or nuclear) and the type of conversion technology (e.g. a simple gas turbine or a high-efficient combined-cycle
gas turbine). From this it follows that an improvement of the generation efficiency
for heat and electricity can be directly translated into primary energy savings 22.
Kerosene
97 %
89 %
95 %
95 %
95 %
95 %
100 %
2020
97 %
89 %
95 %
95 %
95 %
95 %
100 %
2030
97 %
90 %
95 %
95 %
95 %
95 %
100 %
2040
97 %
89 %
95 %
95 %
95 %
95 %
100 %
2050
97 %
89 %
95 %
95 %
95 %
95 %
100 %
RES 24
Diesel
2010
Solids23
Gasoline
Heating oil
Efficiency for the conversion from primary to secondary/final energy
Natural Gas
Table 4-4:
Source: (FfE, 1999), (Öko-Institut, 2006)
The translation of final energy into primary energy savings consists of six steps that
are explained in the following:
1. The PRIMES 2009 baseline final energy demand is translated into a primary energy demand baseline (cf. Figure 4-9), considering the fuel mix and
the conversion efficiency as reported in (European Commission, 2010). For
the years beyond 2030, a trend extrapolation was carried out. In the case of
electricity and heat, the final energy is re-converted into secondary energy
first, and in a second step into primary energy. The detailed figures are
shown in Table 4-5.
2. Due to the relatively low level of detail of the data from PRIMES 2009
(European Commission, 2010), the transformation procedure of step one
22 For further information regarding this effect, see also (Harmsen, 2011)
23 Solids comprise hard coal, lignite and coke.
24 Renewable energy source (RES) comprise biomass, biogas, solar-thermal heat, geothermal heat
44
implies a certain inaccurateness, that is compensated by calibration of the
results with the actual primary energy data as delivered by PRIMES 25.
3. As mentioned earlier, changes in the fuel mix for the generation of electricity and heat directly imply primary energy savings. Hence, the final energy
demand of the PRIMES 2009 baseline is translated into a primary energy
demand baseline, considering this time the much more ambitious conversion efficiency (and the fuel mix) of the “EU long-term scenarios 2050”
study 26, 27, Scenario B, for the generation of electricity 28. The conversion
efficiency and fuel mix are given in Table 4-6.
4. Subtracting the primary energy demand as calculated on the basis of the
“EU long-term scenarios 2050” study from the PRIMES 2009 baseline gives
the primary energy savings through a more ambitious conversion efficiency
for the generation of electricity (cf. the slice “Conversion savings” in Figure
4-9).
5. The transformation of the final energy savings through efficiency measures
into primary energy savings is carried out according to the procedure in
step 3, using the more ambitious conversion efficiency of the “EU long-term
scenarios 2050” study.
6. The baseline, determined in step 3, less the saving potentials, calculated in
step 5, give the remaining primary energy demand. Hence, the primary energy demand can be reduced by the means of final-energy related efficiency measures AND a highly ambitious electricity generation mix as determined in the “EU long-term scenarios 2050” study, and the technical potential for the reduction of primary energy is composed by both 29.
25 A direct use of the data for the PRIMES 2009 baseline primary energy demand is not possible,
since this data is only available until 2030 and it is not distinguished by primary energy carrier.
26 This study is likewise carried out by Fraunhofer ISI on behalf of the German Federal Ministry for
the Environment.
27 Throughout this study, the baseline calculated on the basis of the “EU long-term scenarios 2050”
study will also be called “Ambitious RES” baseline, for reasons of comprehensibility.
28 For the generation of heat, the conversion efficiency as reported by PRIMES 2009 is assumed for
both baselines.
29 That does not mean that primary energy demand cannot be further reduced. Any kind of policy
measures addressing behavioural changes can potentially trigger further efficiency improvements
that results in an additional decrease of primary energy demand.
45
Figure 4-9:
Schematic illustration of primary energy savings
Table 4-5:
Fuel mix for electricity generation and conversion efficiency for electricity and heat generation according to the PRIMES 2009 baseline
Natural gas
Heating oil
Biomass 31
Other RES
Mean
conversion efficiency for
electricity 30
2010
34 %
30 %
20 %
2%
5%
8%
35 %
81 %
2020
31 %
29 %
20 %
2%
6%
12 %
37 %
86 %
2030
33 %
24 %
17 %
1%
7%
16 %
39 %
91 %
2040
34 %
22 %
16 %
1%
8%
19 %
40 %
91 %
2050
35 %
20 %
13 %
1%
9%
22 %
40 %
92 %
Nuclear
Solids
Secondary energy shares
for electricity generation
Mean
conversion efficiency for
heat
Source: Based on (European Commission, 2010)
30 Converting electricity savings into primary energy savings would actually require a detailed temporary disaggregation of the savings in order to determine by which type of power plant the electricity is produced (marginal power plant approach) and which is the actual conversion factor. Given
the complexity of this approach a mean conversion efficiency was assumed in this study.
31 Biomass comprises also waste
46
Table 4-6:
Fuel mix for electricity generation and conversion efficiency for electricity and heat generation according to the "EU long-term scenarios
2050" study
Secondary energy shares
heat
efficiency
for electric-
2010
34 %
30 %
20 %
2%
5%
8%
35 %
81 %
2020
35 %
27 %
25 %
0%
8%
16 %
50 %
86 %
2030
7%
17 %
29 %
0%
14 %
33 %
64 %
91 %
2040
1%
2%
26 %
0%
20 %
50 %
74 %
91 %
2050
0%
0%
8%
0%
26 %
66 %
80 %
92 %
Nuclear
Other RES
ity
Biomass
sion efficiency for
Heating oil
Mean
conver-
Natural gas
Mean conversion
Solids
for electricity generation
Source: Based on ISI (2011b)
The type of illustration chosen in Figure 4-9 for the presentation of the primary energy savings is likewise applied in the factsheets (paragraph 4.1.5) and in the sectoral overviews (paragraphs 4.4.1 and 5.1). For readability reasons the actual projection of the PRIMES 2009 as well as the “EU long-term scenarios 2050” baseline
is not explicitly depicted in the respective charts.
4.1.5
Methodology to determine the greenhouse gas emission reduction potentials
In order to establish the contribution of energy efficiency measures to climate protection, the reduction of greenhouse gas (GHG) emissions 32 needs to be determined. This paragraph exposes the calculation methodology of GHG emission reductions, based on the primary energy demand in the baseline scenarios and the
respective primary energy savings through efficiency measures that are determined according to the methodology explained in section 4.1.4.
32 According the UNFCCC GHG data register, the overall energy related GHG emissions in 2009
mounted up to 3659 Mt CO2-eq, whereof 97 % came from carbon dioxide (CO2), 2 % from methane (CH4) and 1 % from nitrous dioxide (N2O). Hence, in the subsequent analysis, the focus is
only set on these three types of greenhouse gases.
47
The determination of the direct GHG emissions 33 and the respective reduction
potential is based on the conversion of primary energy demand (distinguished by
fuels) into GHG emissions by means of the emission factors in Table 4-7.
Table 4-7:
Emission factors of primary energy carriers (in Mt CO2-eq per Mtoe)
[Mt CO2eq/Mtoe]
Solids
Nuclear
Natural
gas
Oil
Biomass 34
RES
CO2
3.858
0.000
2.106
3.079
0.000
0.000
CH4
0.008
0.000
0.004
0.002
0.026
0.000
N2O
0.017
0.000
0.001
0.007
0.052
0.000
Source: (NCASI, 2005), (Öko-Institut, 2006), (Öko-Institut, 2007), (Quaschning,
2011)
The step-wise procedure of the conversion from primary energy into GHG emissions follows strongly the methodology for the conversion of final into primary energy, as explained in 4.1.4:
1. Transformation of the PRIMES 2009 baseline primary energy demand into
a GHG emission baseline.
2. Calibration of the emissions 35 according to the PRIMES data reported in
(European Commission, 2010).
3. Transformation of the baseline primary energy demand that was calculated
using the fuel mix and conversion efficiency from the “EU long-term scenarios 2050” study into a GHG emissions baseline.
4. Calculation of the GHG emission reduction through a fuel and technology
shift in power generation by subtracting the emissions from the “EU longterm scenarios 2050” from the PRIMES 2009 baseline (labelled as “Conversion savings” in the subsequent paragraphs).
33 In the framework of this study, only direct GHG emissions are considered, that are released during
the combustion process of the fuel.
34 Assuming a sustainable use of biomass including afforestation
35 In the PRIMES 2009 baseline, electricity generation is partly ensured by the use of CCS (carbon
capture and storage) technology. Since there is no detailed information available on the degree of
utilisation, the adjustment of the calculated GHG emissions is carried out by “distributing” the GHG
emission reduction through CCS over the different sectors according to their specific degree of
electrification.
48
5. Determination of the GHG emission reduction potential of final energy related efficiency measures by converting the calculated primary energy demand into GHG emission amounts.
6. Determination of the actual remaining emissions that represent the lowest
realisable emission reduction pathway by means of end-use related efficiency measures AND the reduction of GHG emission through a power mix
with an ambitious share of renewables as calculated on the basis of the “EU
long-term scenarios 2050” in step 3 (technical potential for the reduction of
GHG emissions).
4.2
Energy saving and emission reduction potentials of
„calculated wedges“
In this section the main energy efficiency technologies that can provide significant
energy savings are described in individual factsheets, sorted by the sector of application. Every factsheet has the following structure:
1. Firstly, the main result is shown: the description of the technical energy
saving potential compared to the historical final energy demand development (mainly based on data from (Odyssee, 2011) and the energy demand
forecasts delivered by the PRIMES 36 2009 baseline scenario (European
Commission, 2010). The potential is depicted up to 2050. Until 2030 a detailed differentiation according to the saving measures can be undertaken,
whereas for the time 2030 to 2050 a general assessment of the overall energy saving potential is carried without a clear definition of the pathway of
the single technologies due to limited predictability.
2. Based on the potential determination in the first block, a cost-benefitanalysis is carried out, identifying the share of the technical potential that is
already cost-efficient and the remaining part that is still limited by financial
barriers. The result of the analysis is depicted in a cost curve (see Figure
4-10) that shows the specific potential as well as the financial benefits/costs
involved for the years 2020, 2030, 2040, 2050. For the year 2020, the single
measures are pointed out by means of coloured blocks. For the subsequent
years, the order of the cost curve from the year 2020 is maintained and ori-
36 The PRIMES model is used by the National Technical University of Athens (E3MLab) who are
preparing the main energy forecasts for the European Commission. The PRIMES 2009 baseline
scenario is a widely recognised reference scenario forecasting the business as usual development if no climate mitigation action is undertaken.
49
entation lines help identifying the evolution of every single measure over
time. For reasons of comparability, the vertical axis, representing the specific
energy saving costs in M€’05/Mtoe are kept constant, whereas the horizontal axis, showing the saving potential in Mtoe, is adjusted according to the
dimension of the potential for readability reasons.
Figure 4-10: Exemplary illustration of the cost curve arrangement
If not stated differently, the overall potential is subdivided into three categories:
•
“Low hanging fruits” (LHF) contain all the potentials that were
originally identified under the LPI (Low policy intensity scenario, as
described in 4.1.3) scenario and adjusted according to the new
framework conditions. The LHF potentials are highly economic, however, they imply continued high barriers that can be overcome by a
low policy effort. They are even economic under high discount rates
for investments in energy efficiency.
•
“High hanging fruits” (HHF) represent potentials that were determined under the HPI scenario (high policy intensity scenario) as well
as technical potentials that simply became cost-effective (i.e. energy
saving costs below zero that create net benefits) due to the adjustment of the economic framework conditions to higher energy price
levels (mainly fuel prices). Hence, the HHF potentials do also trigger
net cost savings on a life cycle basis, however a high policy effort is
needed in order to overcome the barriers and the discount rates for
investments are lower than in the LHF case.
50
•
“Immature fruits” (IF) cover all the potentials that are near economic under low discount rates but may be realised under acceptable additional costs. They have not reached the state of costeffectiveness yet (hence called “immature) on a life cycle basis. They
represent all the saving potentials that were identified under the
Technical scenario that are more expensive than LHF and HHF potentials but that are still fairly realistic options – no exotic technologies.
On top of every cost curve a bar chart provides the information on how the
energy saving potential is distributed over the three categories mentioned
above (LHF, HHF, IF). Potential blocks that are initially identified as HHF or
IF keep this label over the subsequent years despite their further cost reduction. Mainly in the case of the immature fruits, this practice permits to figure
out when an immature fruit potential becomes cost-efficient and is shifting
towards the economic potential (i.e. below the horizontal axis). However,
given the fact that the potential determination for the years 2040 and 2050 is
carried out using sectoral extrapolation indices from the ADAM report (ISI,
2009c), the potentials of the different categories are evolving identically.
Hence, the shares are the same for the years 2030 to 2050.
3. The third sub-section gives insights into how the identified final energy savings might trigger primary energy savings and a reduction of greenhouse gas emissions. In the style of the illustration of the final energy savings, the savings depicted in this block are likewise shown in comparison to
a baseline development. Since the fuel mix for the final energy generation
has additional effects on primary energy savings (see also the methodology
chapter 4.1.4), two baselines are used: the PRIMES 2009 baseline and the
so-called “Ambitious RES” baseline which is based on the “EU long-term
4. A short section on the sector itself and the historical development of specific
key figures provides the reader with some general information facilitating
the understanding of the energy saving potentials.
5. A separate section on general technology information aims on giving a
short introduction into the technologies prevalent in the respective sector.
They provide the knowledge necessary for understanding the potential efficiency improvements listed in section 4.
6. In this section the energy efficiency technologies responsible for the saving potentials mentioned in section one are explained. The listing of technologies is only a limited selection without demanding completeness due to
51
the wide range of existing technologies and the limited coverage of this report.
Every technology is rated regarding its technical development status. The
definition of the different technology status levels corresponds to the following convention (based on (Martin, 2000)):
•
R&D: The technology still needs further research and development efforts before providing net energy savings or working under standard
conditions.
•
DEMO: The technology already exists at a demonstration or pilot scale.
Further research needs to be done in order to make this technology applicable and cost-efficient under current user patterns.
•
EMRG: The technology is closed to the market entry (i.e. emerging
technology) but still encounters problems regarding user acceptance,
high costs or strong competition.
•
COMM: The technology is already commercially available at the market.
7. In a last sub-section, general information regarding the calculation methodology is provided, in the case that the calculation procedure differs from
the general approach as explained in section 4.1.
The listing of all factsheets shows that firstly the focus is set on efficiency technologies available in the households and tertiary sector. Afterwards, household
appliances (so called “white goods”) as solely prevalent in the household sector are
analysed. Factsheet six until nine deal with efficiency technologies for process
technologies (PT) as well as for cross-cutting technologies (CCT). Finally, the assessment of technical efficiency improvements and behavioural changes in the
transport sector is carried out.
Table 4-8:
Overview of the factsheets
#
Sector
Wedge
1
Households, tertiary
Building envelope
2
Heating and cooling systems
3
Lighting
4
Green ICT
5
Households
Household appliances
6
Industry (PT)
Paper and pulp industry
7
Industry (CCT)
Steam / hot water generation
8
Industry (CCT)
Electric drives
52
9
Industry (CCT)
E-drive system optimisation
10
Transport (road)
Technical improvements
11
Transport (road)
Behavioural changes
12
Transport (road)
e-Mobility
4.2.1
53
Building envelope
Households, tertiary - Building envelope
Final energy saving potentials
Final energy demand for heating and cooling in the residential and tertiary sector
can be reduced by more than 42 % or 152 Mtoe by 2030 (51 % by 2050) compared to the PRIMES 2009 baseline through efficient building envelope design.
Due to the long lifespan of the building stock, refurbishment measures have a significantly stronger impact on the saving potential than the construction of new,
more efficient dwellings. More than two thirds of the savings arise from refurbishment of existing buildings (76 Mtoe in the household sector, 27 Mtoe in the
tertiary sector) whereas new buildings account for 37 Mtoe and 10 Mtoe.
One should bear in mind that the energy savings of new buildings that are reported
here, are also resulting from new efficient heating systems. However, the savings
through improved insulation are supposed to be much higher, reducing the heating
demand (and the related saving potential) to a minimum level.
Figure 4-11:
Energy saving potentials by efficient building envelope in the household and tertiary sector, compared to PRIMES baseline for heating
and cooling energy demand in the household and tertiary sector
Source: historical data: (Odyssee, 2011), FED projections: (European Commission, 2010),
energy saving potentials: (ISI, 2009a)
54
Building envelope
Cost curve for final energy saving measures
As indicated in Figure 4-12 the energy efficiency options for building envelopes are
largely cost-effective, except some IF options for existing buildings in the household and tertiary sector that are uneconomic. When looking at the development of
the IF options between 2020 and 2050 one can witness that in the long run they
will become cost-effective as can be seen in 2040 and beyond. This illustrates that
the specific costs for energy saving options in buildings change crucially on a long
term basis due to increasing fuel prices. Therefore, to attain potentials in the short
term, ambitious political instruments have to be installed, because 63 % in 2020
are assigned to HHF and IF.
In 2020 the LHF potentials related to new buildings are 12 Mtoe in total and the
potential of existing buildings is 24 Mtoe. Despite the fact that the amount of new
buildings is much smaller than the existing stock their impact is a lot stronger due
to the high energy efficiency of new buildings whereas the potentials of the household sector are a little bit smaller. For HHF and IF in 2020 the potentials of households exceed tremendously, which proves the necessity of ambitious policy measures in the long term. That counts for the years 2030 to 2050 as well. The overall
benefits of the economic potentials mount up to €26 billion, whereof nearly one fifth
would be required to unlock the IF potentials. In 2050, all potentials are economic
and cause benefits of more than €100 billion (whereof households cover 70 %).
Figure 4-12: Cost curve for building related saving options, up to 2050
55
Building envelope
Primary energy saving and GHG emission reduction potentials
Figure 4-13:
Primary energy savings compared to the PRIMES 2009 baseline
demand for heating and cooling in the residential and tertiary sector
As one of the most important measures to reduce primary energy demand and thus
to mitigate greenhouse gas emissions the improvement of the building envelope
has a potential to decrease the primary energy demand of 41 % compared to the
PRIMES 2009 baseline and 51 % compared to the “Ambitious RES” baseline (191
Mtoe) by 2050. The difference between the two baselines has to be interpreted
against the backdrop of the fuel and technology switch for electricity generation
(from the PRIMES 2009 mix to the generation mix from the “EU long-term scenarios 2050” study). The key determinant to exploit the energy saving potential is the
refurbishment of existing buildings which is about 131 Mtoe (cf. Figure 4-13).
As indicated in Figure 4-14 the potential to mitigate emissions due to a higher efficiency of the building envelope is about 277 Mt CO2-eq in 2050, which is about
43 % in comparison to the PRIMES 2009 baseline. And further 13 % of the GHG
emissions (88 Mt CO2-eq) can be reduced by conversion savings.
Figure 4-14:
56
Building envelope
GHG emission reduction compared to the calculated emissions from
the PRIMES 2009 baseline energy demand for heating and cooling
in the residential and tertiary sector
General information
The energy use of residential and non-residential buildings accounts for 40 % of
the total energy use in the EU (Eurostat 2010). The building envelope plays a
substantial role in this context as this determines the heating and cooling load for
the desired indoor temperature. Because of this, efficiency standards and requirements have been continuously enhanced over the years in terms of refurbishing existing dwellings as well as constructing new ones. However, this trend
towards increased efficiency is offset by the other trend observed in the residential
sector that the total number of households is growing while the number of inhabitants per household is declining due to demographic and social changes.
Thus, the living area per dwelling has increased steadily which is a driving force
for the total energy demand of buildings (ISI, 2009a), (Eurostat, 2011) (Eurostat,
2011), (Odyssee, 2011).
Figure 4-15:
57
Building envelope
PRIMES 2009 forecast of the EU27 building stock
2
1.75
1.5
1.25
1
Source: (eepotential, 2012)
Figure 4-16:
Expected average living area per dwelling (in m²/dwelling)
Technology information
Buildings can be seen as a system of technologies consisting of the building
envelope (walls, doors, windows and the roof), heating and air-conditioning. Thus,
a systems approach is necessary to improve their energy efficiency. Therefore,
several low-energy building standards have been established that define different
58
Building envelope
levels of building efficiency comprising all the mentioned elements. In particular
these approaches seek to limit the energy use for space heating by defining specific thresholds on an annual basis. Thus, the contribution of the building envelope
is to minimise all thermal bridges regarding their degree of insulation. Moreover,
self-sufficient buildings using renewable energy sources to generate their own
power play a crucial role which is not able to be considered here. In principal, all
the low-energy building standards presented below can already be achieved with
state-of-the-art technology. But it should be mentioned that the specifications used
to define these standards can be ambiguous in the literature and therefore vary
from country to country (Passivhaus Institut, 2009), (Torcellini, 2006), (Voss, 2008):
•
In general a Low-Energy-House (LEH) is a building standard that defines
the degree of efficiency of transmission heat losses through the building
envelope as well as a certain threshold for the total energy demand of the
heating system. In Germany, for example, the annual energy consumption
of the heating system of houses entitled to carry the LEH-label has to be
below 50 kWh/(m²a); this is equivalent to 5 litres of heating oil for each
square metre of heated space per year.
•
The Passive House (PH) concept represents a standard with an annual
energy demand for heating that does not exceed 15 kWh/(m²a). In general,
this standard is based on minimizing heat losses combined with the maximal use of solar power. The detailed requirements are the following: thermal insulation (U-values < 0.1 W/m²K), thermal bridges (U-value < 0.8
W/m²K), high solar transmission of thermal bridges (> 50 %) and high degree of heat recovery of ventilation system (> 75 %) with a low electricity
demand (> 0.45 W/m³).
•
Zero-Net-Energy-Buildings (ZNEB) require an annual net energy supply
from the grid of zero kWh/m². Therefore, these buildings can be powered
autonomously. The principle of this building type is to combine energy production using renewable technologies like solar and wind power with extremely efficient HVAC and lighting technologies.
•
An Energy-Plus-Building (EPB) produces more energy using renewable
energy sources than it needs for its own consumption. Thus, energy can be
exported into the grid. This can be achieved with low-energy building standards like PH in combination with a decentralised heat and power supply
based on renewable energies. This type of building design should be
treated more as a vision than a solution in the near future.
59
Building envelope
Energy efficiency technologies
A set of structural changes and replacements of specific building envelope elements have to be applied to comply with the above mentioned
building standards and reduce the energy consumption determined by
the conductivity of the building envelope. Building typology plays a key
Techn.
status
role regarding the feasibility of the refurbishment measure ((ECOFYS,
2005), (Wietschel, 2010), (SAENA, 2009), (Passivhaus Institut, 2009)).
•
Improvements by structural changes to the building design are
usually limited to the construction of new dwellings. Typical examples are porch installations to provide shading and solar protections of windows.
•
Due to the fact that the building envelope mainly comprises
the walls and the roof, a high degree of insulation of both elements is crucial. The typical material deployed is mineral wool
with glass padding and polystyrene (EPS), which has a thermal
conductivity of 0.03-0.04 W/mK. More innovative alternatives
that are still very costly and therefore in the R&D development
stage include aerogel (0.012-0.022 W/mK) and vacuum insulation systems (0.004 W/mK).
•
Generally the degree of window insulation is determined by
the optimal thickness of the space between the panes containing gas or a vacuum. While too little space results in relatively
high losses, too large a gap results in increased convection. By
using high-performance windows like triple glazing, U-values of
0.6 W/m²K are possible. Through further R&D, vacuum glazing
(0.4 W/m²K), which minimises conductive heat losses between
the panes, is expected evolve to commercial status.
DEMOCOMM
R&DCOMM
R&DCOMM
Calculation methodology
As described in the general methodology section the potentials have been calculated on a scenario approach. Details of the methodology are presented in ISI
(2009a); this section provides only an overview of the most important elements.
At the basis of the potential evaluation in the residential sector is a description of
the European building stock according to building age and type, average living
area, climate zone, energetic standard, etc. On the basis of this historic description
of the building stock energy efficient building options were defined for both the new
buildings (4 more and more efficient building types up to passive house standard)
60
Building envelope
and existing buildings to be refurbished (3 refurbishment packages up to a level of
low energy houses). Each of these options and packages were described on a detailed technical level and were allowed to penetrate the market in accordance with
maximum penetration rates. For the technical scenarios at the basis of the potentials presented here, refurbishment rates and compliance with building regulation
were enhanced.
The methodology was similar for the tertiary sector buildings. However, the historic
database was based on a less detailed dataset. The buildings differ between small
and large; small buildings refer to smaller than 1.000 m2 and larger to more than
1.000 m2. In order to characterise the specific energy consumption per building, the
same energy consumption values as for residential buildings were taken for the
scenario calculations.
4.2.2
61
Households, tertiary - Heating and cooling systems
The increasing level of individual comfort demanded and climate change lead to
increasing energy consumption for heating and cooling devices and furthermore to
high saving potentials. Until 2030, 41 Mtoe of final energy demand can be reduced
by solely renewed efficient heating systems in households. In total, the overall
saving potentials 37 are assessed to be 57 Mtoe, which is about 16 % compared to the PRIMES 2009 baseline projection (in this case the aggregated FED
for heating and cooling of the household and tertiary sector). Until 2050, the saving potential is further increasing up to 66 Mtoe, which equals to 19 % energy
demand reduction compared to the baseline.
Figure 4-17:
Energy saving potentials of efficient heating in the household and
tertiary sector compared to the baseline heating/cooling energy demand
37 It has to be mentioned that the potentials discussed in this factsheet are limited to existing buildings. The energy saving potential of heating and cooling systems in new buildings is discussed in
the building envelope factsheet, as for new buildings an integrated approach regarding insulation
and heating measures was carried out.
62
Due to structural differences in the tertiary sector air-conditioning systems are limited to central appliances. Air-conditioning in the residential sector could not be
analysed due to a rather weak database. Moreover, the interpretation of the saving
potentials has to be regarded under the restriction that heat pumps are not explicitly considered in the tertiary sector. Thus, the total amount of saving potentials in
the residential and tertiary sector is even higher than revealed. Moreover, the trend
towards an increasing degree of insulation of the building envelope has to be considered.
Saving potentials in the field of industrial space heating are neglected in the analysis due to significantly differing heating concepts (such as waste heat use) that
cannot be applied in the residential and tertiary sector.
Due to the long lifetime of cooling and heating devices most options are costeffective despite associated high investments. In terms of costs the centralized air
conditioning should be addressed first in the tertiary sector with specific costs of 964. M€’05/Mtoe in 2020. All efficiency measures classified under air-conditioning
are highly rewarding and thus declared as LHF. Further LHF are represented by
the increase of heating efficiency in the tertiary and household sector with specific
costs of -446 M€’05/Mtoe and -373 M€‘05/Mtoe respectively. Taking the high hanging fruits also into account the cost-effective potentials represent 65% in 2020. In
comparison to 2020 the share of LHF decreases slightly in the subsequent years of
about 8% on a level of 60%.
Looking at the heating potentials of the household and tertiary sector in all four cost
curves shows that the fuel shift does not lead to any essential changes in the structure of the curves. This means that the effects of various differential costs and fuel
prices do internalise each other. In total the saving potential of heating and cooling
in the household and tertiary sector is 66 Mtoe in 2050.
Despite the fact, that tertiary air-conditioning (AC) features the highest specific cost
reduction per unit of energy saved by 2020, heating systems in the household sector trigger three times as much benefit as the AC systems, namely €4.9 billion.
The net benefits (benefits from economic measures less the additional financial
efforts for unlocking the non-economic potential) account for €8 billion by 2020 and
up to €43 billion in 2050, when all measures are cost-effective.
Figure 4-18:
63
Cost curve for heating and cooling related saving options
Figure 4-19:
Primary energy savings compared to the PRIMES baseline energy
demand for heating and cooling in the residential and tertiary sector
64
The primary energy savings in Figure 4-19 illustrate a constantly increasing potential until 2030, which is 67 Mtoe. Afterwards the overall savings due to more
efficient heating and cooling increase only slightly on a level of 72 Mtoe in 2050
(15 % compared to the PRIMES baseline). This development has to be interpreted
in the light of more energy efficient building standards that lead to a falling heat
demand after 2030. The savings in the residential sector are essentially related to
the diffusion of heat pumps and thus attributable to reduced electricity consumption. Conversion savings equal 97 Mtoe in 2050, i.e. 21 % compared to the
PRIMES 2009 baseline.
As indicated in Figure 4-20 the potential to reduce greenhouse gas emissions develops equal to the primary energy savings with a steady increase until 2030. Subsequently the GHG emission reduction potentials remain almost on a constant
level. In 2030 the greenhouse gas emission reduction is about 127 Mt CO2-eq
and in 2050 about 114 Mt CO2-eq. As for the primary energy savings the energy
efficient refurbishment of buildings results in a downside trend in terms of reduction
potential. Due to a very efficient electricity generation mix under the “Ambitious
RES” baseline the conversion savings rise to 88 Mt CO2-eq unto 2050.
Figure 4-20:
GHG emission reduction from efficient heating and cooling systems
compared to the calculated emissions from the PRIMES 2009 baseline energy demand for heating and cooling in the residential and
tertiary sector
65
General information
The residential and tertiary sectors in Europe represent 40 % of today’s total final
energy demand (Eurostat, 2011). Thereof, a substantial share that is crucially determined by the insulation type of the building shell is related to heating and airconditioning cooling systems (see also factsheet about building envelope). When
investigating the energy demand for heating and cooling technologies, it is necessary to distinguish between different country-specific needs in the various climate
zones and to take the increasing amount of heating degree days (HDD) and cooling degree days (CDD) due to climate change into account. HDD and CDD are
indexes representing the actual heating/cooling demand. They are calculated as
the sum of temperature variation above/below room temperature over a specific
time horizon (typically one year). I.e. the higher the temperature deviation is or the
longer the hot/cool periods last, the higher is the HDD or CDD, respectively.
By dividing the European building stock into three climate zones - cold (> 4,200
HDD), moderate (2,200-4,200 HDD) and warm (< 2,200 HDD) - a varying distribution of building types and hence requirements in terms of heating and cooling demand can be observed (ISI, 2009a). While the number of heating appliances has
almost reached the level of saturation, the penetration of air conditioning cooling
systems have increased in number extensively over the last decades (ISI,
2009a), (ISI, 2009b). Nevertheless, a dynamic evolution of heating systems can be
observed, whilst taking into account the continuously increasing share of renewable energies and heat pumps in the technological mix (Wietschel 2010). Besides these technological drivers, social aspects like the enhanced living area per
dwelling in the light of a rising total number of dwellings and the rebound effect
due to an increase of individual thermal comfort needs in winter and summer
seasons needs to be (ISI, 2009b).
Figure 4-21:
Heating and cooling degree days in three climatic zones of the EU27
Source: (ISI, 2009b)
66
Multiple technologies are applied in the residential and the tertiary sector to provide
the energy service heating. Depending on the building design, heat is either supplied from a centralised source with a subsequent distribution system or decentralised which only plays a minor role nowadays. In centralised systems the generation
of heat is realised by a boiler that also provides the function of storing heat in a
vessel. Thereby, the energy source for heat generation can vary: oil, coal, gas or
even solar power. In order to further improve heat generation, condensing boilers
are employed that also utilise the latent heat of water (heat released or absorbed
by a chemical substance or a thermodynamic system during a change of state)
produced from the burning of fuel. A further way to provide locally usable heat is by
connecting building units to a district heating system. In the proper sense, district
heating cannot be considered as a generation technology even so, it provides the
same function (Schmid, 2003), (Wietschel, 2010), (ISI, 2009a).
Corresponding to heating systems, air conditioning can be distinguished with
regard to the location of their generation unit: room air conditioners (RAC) and
central air conditioners (CAC). RACs are separate components that are mainly
found in the residential sector, while CAC are characterised by a central refrigerating unit which is generally bigger in size and mostly found in the tertiary sector.
There are different types of commonly used RAC appliances. Split-packaged
units and multi-split-packaged units are comprised of an indoor unit (evaporator
and fan) and one or more outdoor units respectively (compressor and condenser)
connected by a pipe which transfers refrigerant. In single-packaged units, one
side of the RAC is in contact with the outside air for condensation, while the other
side provides direct cooling on the inside with a fan. In single-duct units, the condenser ejects hot air through a duct to the exterior. These RACs can be either water- or air-cooled, although the vast majority of them uses air as the heat-transfer
medium. CACs perform technically like RACs, but are characterised by a central
refrigerant unit operating together with an air treatment unit and a distribution system that transports cold to the air conditioned space by using air and/or water as
fluid. Due to the fact that air conditioners are essentially based on heat pumps,
they provide two operating modes: cooling only and reverse cycle (operates as
space heating). Therefore, the formerly used heat source (heat exchanger) needs
to be replaced by a heat sink which can be provided by a refrigeration system (Adnot, 1999), (Adnot, 2003), (Adnot, 2004), (IEA, 2003).
In the process of setting new building efficiency standards (see factsheet building envelope), the mix of technologies applied for heat gen-
Techn.
status
67
eration generally shifts towards an increasing deployment of renewable
energy sources, like solar heating systems and geothermal devices.
Nevertheless, the listed saving technologies are limited to conventional
energy sources (Schmid, 2003), (Wietschel, 2010), (Adnot, 1999), (Adnot J. , 2004):
•
In order to generate heat more efficiently than conventional or
condensing boilers, heat pumps are used to convey heat from
DEMOCOMM
a natural source like ground water or a geothermal hot-pool to a
heat exchanger which transfers this heat into the building’s
heating system. Thus the energy consumption for heating is
mainly determined by the difference in temperature between the
heat source and the demanded comfort indoors.
•
The heat transfer in the heat exchanger, relevant for heating
and cooling purposes, can be improved by increasing the coil
area and the density of the fins, by adding additional refrigerant
tubing through increasing the coils depth, and by internal grooving.
•
Besides the replacement or improvement of single components,
further saving potential can be gained by considering general
aspects - typical examples are to avoid oversizing, usage of
EMRGCOMM
R&DCOMM
variable speed drives or alternative drive technologies like gas
motors, improvement of insulation and performance monitoring
by implementing an e-drive system optimisation process.
•
To attain self-sufficiency and a more efficient mode of energy
supply, the concept of combined heat and power generation
(CHP) has been adapted to residential and non-residential
housing by introducing micro combined heat and power
EMRGCOMM
(mCHP), with an installation usually less than 5 kWe (15 % – 42
% of primary heat are converted to electricity and most of the
remaining heat is captured for hot water or space heating). Due
to the non-existent demand for heating in the summer season, a
combination of CHP with a heat-driven refrigerating machine
can essentially increase the annual full load hours.
68
The energy efficient options were first described in terms of useful energy (see
factsheet on the building envelope) and then combined with certain types of heating devices compatible with the insulation standard and the building types. The
heating devices considered where mainly heat pumps, biomass boilers (advanced
pellet heating), solar heating systems, gas standard and condensing boilers, district
heating systems.
Building shell and heating technologies are interlinked. For the heating devices the
input data were the useful energy consumption, the energy consumption share of
the heating technologies and the corresponding efficiencies of the heating systems. For the reference year the data of the energy consumption shares at country
level were provided by the EuP-Eco-design study on boilers.
There is a strong penetration of heat pumps (30 % – 36% of the heating equipments stock in 2030) and renewable energy sources (solar heating/geothermal, up
to 40 % depending on the country climate) in the market for heating devices in the
technical, while district heating is stagnating and fossil-fired heating sources are
decreasing. Similar penetration of heating devices was assumed for the residential
and the tertiary sector.
4.2.3
69
Lighting
Households, tertiary - Lighting
For residential lighting, the energy-saving options are driven by the most efficient
technologies replacing incandescent as well as halogen lamps through more efficient compact fluorescent lamps (CFLs) and through light-emitting diodes (LEDs).
This evolution can be translated into an energy saving potential of more than
8 Mtoe until 2030, corresponding to a 16 % reduction of the total residential
electricity consumption for lighting and appliances. The tertiary sector 38 features
a similarly significant potential of more than 6 Mtoe by 2030 through efficient office
lighting. This increases to 8 Mtoe when adding the saving potential from street
lighting. It can be translated into a 16 % reduction of tertiary electricity consumption for lighting and appliances by 2030. By 2050, overall technical savings
mount up to 20 Mtoe or an 18 % reduction.
Figure 4-22:
Energy saving potentials of efficient lighting in household and tertiary
sector compared to the demand for electric appliances and lighting
Source: historical data and FED projections: (European Commission, 2010), energy saving
potentials: (ISI, 2009a)
38 In the industry sector, energy savings through lighting are lower than in the other sectors and the
lighting technology being applied differs from the domestic sectors. Hence, these potentials are
not considered in this paragraph.
70
Lighting
As indicated in Figure 4-23 the potentials are clustered in efficient lighting for
households and efficient street as well as office lighting for the tertiary sector. Contrary to the saving options in the household sector, the tertiary is not further subdivided because all potentials are considered to be LHF measures.
Looking at the household sector shows that the bulk of the potential can be attained cost-effective in 2020, which is 1.8 Mtoe with specific costs of -1282
M€’05/Mtoe and -1196 M€’05/Mtoe, respectively. By taking also uneconomic options into account in 2020 the potential of the household sector can be increased
by one third, triggering net cost savings of €1.7 billion (and €8.4 billion by 2050).
Looking at the tertiary sector leads to the conclusion that all options are very rewarding in 2020, with specific costs of -1159 M€’05/Mtoe and an energy saving
potential of 0.8 Mtoe as well as -932 M€’05/Mtoe and 3 Mtoe, respectively, triggering benefits of €3.6 billion. Due to the fact that the increase of electricity prices is
the key driver, the cost curve moves slightly down, causing energy related cost
reductions of nearly €12 billion.
The total cost-effective potential of lighting triples from 6 Mtoe to 18 Mtoe between
2020 and 2050. The overall saving potential is quantified as 20 Mtoe in 2050.
Figure 4-23:
Cost curve for lighting related saving options in the household and
tertiary sector
71
Lighting
Figure 4-24:
Primary energy savings from efficient lighting compared to PRIMES
2009 baseline energy demand for electric appliances and lighting in
the residential and tertiary sector
As indicated in Figure 4-24 the summed up savings of primary energy demand
due to more energy efficient lighting is about 25 Mtoe in 2050. Corresponding to
the final energy demand savings the reduction of the primary energy demand is
equal in households as well as the tertiary sector. In comparison to the PRIMES
2009 baseline, which is at 285 Mtoe in 2050, efficient lighting can contribute by
9 % to primary energy savings. The conversion savings constantly increase until
2050 up to a level of 146 Mtoe in 2050, which is 51 % compared to the PRIMES
2009 baseline.
The analysis of the greenhouse gas emissions points out that the overall mitigation
potential due to efficient lighting increases until 2030 up to 38 Mt CO2-eq (cf. Figure
4-25). Afterwards, a cleaner generation of electricity leads to a declining trend of
lighting contribution. In 2050 the total emission reduction amounts to 5 Mt CO2eq, which is 3 % compared to the PRIMES 2009 baseline and 18 % compared
to the “Ambitious RES” baseline.
Figure 4-25:
72
Lighting
GHG emission reduction from efficient lighting compared to the calculated emissions from the PRIMES 2009 baseline energy demand
for electric appliances and lighting in the residential and tertiary sector
General information
Electricity demand for lighting occurs everywhere regardless of the analysed sector. For the residential sector, it is relatively easy to quantify the demand for lighting, which accounts for about 10 % to 12 % of all residential electricity demand,
whereas no data are available regarding the energy consumption due to lighting in
the tertiary and industry sectors. Despite the decrease in the energy consumption
of light bulbs and the market entry of new, energy-saving lighting technologies (cf.
next section), the total electricity demand for lighting has still increased. This is due
to the increasing number of households, the increasing floor area per dwelling and
the increased number of light sources per dwelling.
Figure 4-26:
73
Lighting
Final energy demand for lighting in absolute numbers and as specific yearly consumption per dwelling in the household sector
Source: (Odyssee, 2011)
Figure 4-27:
Distribution of electricity by end-use in households, EU15, 2004
Source: (IES, 2007)
In order to compare the performance of light bulbs, the luminous flux (visible energy measured in lumen, lm) is considered, which is an indicator for the luminosity.
Consequently, the efficiency of light bulbs is expressed in lumen per Watt (lm/W).
74
Lighting
The numerous existing lamp types can generally be classified as incandescent
lamps, discharge lamps and LEDs. Incandescent lamps, which are still very widespread, transform about 95 % of the electricity consumed into invisible infrared
radiation, whereas only 5 % are converted into visible light. The average efficiency
is about 13 lumen/W (lm/W), which is slightly exceeded by halogen lamps (up to
30 lm/W), a special type of incandescent lamp. They are equipped with a tungsten
filament contained within an inert gas and a small amount of a halogen such as
iodine or bromine, permitting higher operating temperatures and thus higher efficiency.
About 50 lm/W can be attained with discharge lamps, also called fluorescent
lamps. Larger fluorescent lamps are mostly used in commercial and institutional
buildings, whereas compact fluorescent lamps, CFL, are available in the same size
as traditional incandescents and now used as energy saving alternative (thus also
called energy saving lamps). High efficiency discharge lamps are rated category A
within the EU energy labelling system due to 50 % to 80 % lower energy consumption compared to standard halogen lamps (category D). An additional benefit of
CFLs is the significantly longer lifetime of between 10000 and 15000 hours compared to conventional incandescent lamps (about 3000 hours).
An even higher light yield (more than 80 lm/W) is achieved by the new LED (light
emitting diode) technology which is currently entering the market. LEDs are semiconductor light sources that were initially used as indicator lamps in electronic devices before being increasingly applied for lighting purposes.
Efficiency gains in lighting can be realised by three different options:
decreasing the actual usage rate of the luminaire by demand-related
control systems, increasing the efficiency of existing lighting technologies (cf. section above), or introducing new lighting technologies
Techn.
status
It is important to note that the maximum efficiency of a lamp is
reached when all electrical energy is converted into visible electromagnetic radiation. The maximum value for a perfect cool white light source
is 348 lm/W. (VITO, 2007a), (VITO, 2009)
Demand-related control systems
•
Luminaires with presence detection automatically switch on
when people enter a room. The motion detector can be installed
in the luminaire or be part of the building management system
that gives the lamp the necessary signal. Motion sensors exist
with very low standby losses of less than 0.002 W.
EMRGCOMM
•
75
Light-responsive sensors, integrated in the lamp or the building
management system, enable a daylight responsive dimming
of the luminaire. For indoor use, this type of technology can only
be used in the proximity of windows (typically up to 3 m). Dimmable street lighting can adjust the light intensity in response to
traffic density, weather conditions and real life lighting performance on the street (also called “intelligent street lighting”)
Lighting
EMRGCOMM
R&D DEMO
(VITO, 2007b) .
Improved existing technologies
•
Incandescent lamps using a tungsten photonic lattice could
further improve the rather low efficiency of incandescent lamps.
R&D
A tungsten filament fabricated with an internal crystalline pattern
could transmute the majority of wasted infrared radiation into
frequencies of visible light.
•
Equipping halogen lamps with reflectors increases the lumi-
COMM
nous flux by reducing spilled backward light, directing the light
to the intended surface. Anti-reflective coating on the front cover
of the lamp increases the transmission of visible radiation, increasing the luminous flux leaving the lamp by 3 % to 6 % (but
still less than 30 lm/W).
•
It is possible to improve the efficiency of CFLs by integrating
more sophisticated electronic circuits with low power consumption and increasing the efficiency of the switching semiconductor, which can compensate the relatively higher costs. A 10 %
efficiency gain can be obtained by operating the lamp at high
frequencies (10 kHz instead of 50 or 60 Hz) using electronic
ballasts.
R&D COMM
New lighting technologies
•
Reflector lamps with WLED (white light emitting diode) use the
novel LED technology, which is currently mainly used in display
backlighting of portable devices and traffic signs. Further research promises light yields of up to 150 lm/W by combining
WLEDs with special lenses.
•
R&D –
COMM
Organic LEDs (OLED) are made by placing a series of thin organic films between two conductors. When a current is applied,
a bright light is emitted. This technology is particularly advantageous for indoor lighting since OLEDs could be applied as a
R&D EMRG
76
Lighting
type of “glowing wallpaper”. Up to 64 lm/W can be emitted by
OLEDs.
(2009a). This section provides only an overview of the most important elements.
For residential lighting the potential of energy savings is driven by the penetration
of the most efficient technologies in the household stock with the following settings:
The CFL lamps substitute the incandescent (and halogen) lamps, the LED technology substitutes the CFL lamps. The penetration takes the technical maturity into
account. By 2030 60% of stock is composed by CFL lamps and 40% of by the LED
technology. The penetration is simulated with a stock model considering the lifetime of lighting options. Rebound effects such as longer use of lighting due to lower
energy consumption are taken into account.
For office and street lighting an approach was used considering the shares of each
end-use in electricity consumption.
The data were based on various technical studies, in particular the preparatory
studies for Eco-design Requirements of EuPs (Lot 19: Domestic lighting, Lot 8:
Office Lighting, Lot on Public street lighting. The fact that these studies aim at finding the policy option with the lowest life cycle costs (LLCC) leads to an underestimation of the technical scenario, as very costly options are not considered.
In cases where no data was available, case studies on saving potentials in certain
companies were used as basis for own estimates, using the following equation:
Pot tech, Rem, t = Pot tech, Ref * (Sh Applicable - Sh Applied, t)
For each saving option a technical saving potential, Pot tech, Ref, t, is calculated as
average value from the case studies. This is corrected by the share of cases or
companies in which the saving option is applicable, Sh Applicable, and the share of
companies that have already applied the option at a certain point in time, Sh Applied, t.
Result is the remaining technical saving potential at this point in time, Pot tech, Rem, t.
4.2.4
77
Green ICT
Households, tertiary - Green ICT
Comparing the energy savings of IT appliances and TVs with the electricity demand in the residential and tertiary sector shows only a slight reduction of the
growing demand. In 2030, the total consumption increase would be limited to
75 % instead of 87 % (as forecasted by PRIMES 2009), compared to 2000 values.
Until 2050 the overall energy demand for ICT appliances is further growing, hence
fully depleting the additional saving gains of 1 Mtoe. The bulk of the energy savings
can be attained through energy-efficient TVs (45 % of all savings) and desktop
PCs (22 %) e.g. via reduced standby-losses. At the same time, efficiency gains in
TV technology risk being partially compensated (or even over-compensated) by
increasing screen size (also known as “Rebound effect”). The same applies for
server technology due to higher security and data backup demands.
In any case, it is necessary mentioning the uncertainty of forecasting mid and longterm developments in the IT sector, due to very dynamic market behaviour, high
stock turnover rates and constantly new inventions.
Figure 4-28:
Energy saving potentials by Green ICT in the household and tertiary
sector compared to the demand for electric appliances and lighting
Source: historical data and FED projections: (European Commission, 2010), energy saving
potentials: (ISI, 2009a)
78
Green ICT
The very unpredictable dynamic technology development makes it difficult to estimate the realistic cost for energy saving options for green ICT. However the
considerable drop in product prices over the past years suggest that at least best
available technology (BAT) saving options which are represent the main driver for
cost-effective saving potentials in this study should not result in appreciable additional costs 39. Consequently the overall saving potential is divided into a major part
that is economic (solely low hanging fruits, i.e. highly beneficial under high discount
rates) due to a wide-spread diffusion of BAT and a second part which needs further
financial effort in order to trigger a further diffusion of BAT as well as the market
introduction of so-called BNAT (best not available technologies).
While set-top boxes and modem routers promise the highest specific benefits
(more than -2000 M€’05/Mtoe), IT appliances in the tertiary sector represent
the bulk of overall financial savings (€1.4 billion in 2020, €2.4 billion in 2050).
TVs and residential desktop PCs experience a boost of the overall potential by factor four in 2030 whereof an important part (2.5 Mtoe) needs to be unlocked by
means of political and financial incentives.
Figure 4-29:
Cost curve for ICT related saving options
39 According to the EuP case studies, the costs of the BAT options are assumed to be neutral even if
the competitive market situation is not taken into account.
79
Green ICT
Figure 4-30:
Primary energy savings from Green ICT compared to the PRIMES
2009 baseline energy demand for electric appliances and lighting in
the residential and tertiary sector
In analogy to the final energy demand potential the primary energy demand reduction due to Green ICT appliances is only minor. As indicated in Figure 4-30 the
summed up savings of primary energy demand increase until 2030 and almost
remain constant afterwards. In 2050 the overall potential due to more energy
efficiency lighting is about 10 Mtoe. In comparison to the PRIMES 2009 baseline, which is at 285 Mtoe in 2050, efficient lighting can contribute by 4 % to
primary energy savings. While comparing the lighting savings to the “Ambitious
RES” baseline the contribution of efficient lighting has a share of 7 % in 2050.
As indicated in Figure 4-31 the overall mitigation potential based on the diffusion of
Green ICT appliances increases until 2030 up to 15 Mt CO2-eq, which is 6 % in
comparison to the PRIMES 2009 baseline. Afterwards, a cleaner generation of
electricity leads to a declining trend of Green ICT contribution down to a total
mitigation of 2 Mt CO2-eq in 2050. Thus, the overall share compared to the
PRIMES 2009 baseline is less than 1 %. On the other hand the share of Green ICT
in 2050 compared to the “Ambitious RES” baseline is about 8 %, considering conversion savings of about 132 Mt CO2-eq.
Figure 4-31:
80
Green ICT
GHG emission reduction from Green ICT compared to the calculated
emissions from the PRIMES 2009 baseline energy demand for electric appliances and lighting in the residential and tertiary sector
General information
Information and communication technology (ICT) comprises all technical means
used to manage information and enable communication, including computer
and network hardware, communication middleware as well as necessary software.
This includes also telephony, broadcast media, all types of audio and video processing and transmission and network-based control and monitoring functions.
An increasing diffusion of ICT appliances in the residential and tertiary sector combined with longer using times drive the significance of the ICT-related electricity
consumption, exceeding the average consumption of traditional appliances within a
household (see Figure 4-32).
Moreover, the transferred data volume rises due to an increasing demand for video
and TV internet applications (such as High Definition Television, HDTV) by 46 %
per year (cf. Figure 4-33). About 75 % of the total data transfer will be related to
residential ICT use (CISCO, 2008), (ISI, 2009a).
Figure 4-32:
81
Green ICT
Typical OECD household electricity consumption of major traditional
and digital appliances
Source: (IEA, 2009b)
Figure 4-33:
CISCO forecast of global, monthly IP traffic, 2005-2012
Source: (CISCO, 2008)
In this factsheet, the following ICT components are taken into account:
Server and data centres are responsible for computing and managing data in
local systems. About 50 % of FED from computing centres is used for cooling issues (BMU, 2009).
82
Green ICT
End user appliances can be seen as terminals or access points to the system,
controllable by the end user. The traditional appliances are laptops and desktop
PCs combined with monitors. Due to the increasing shift from analogue to digital
TV transmission, and the combination of phoning, TV and internet (Triple-PlayService), TV screens and PC monitors are assumed to represent the same kind of
appliance. The former traditional CRT (cathode ray tube) TV screen is increasingly
replaced by LCD (liquid crystal display) screens and other new technologies (see
energy efficiency technology section).
A general and very important issue of ICT components is the so-called standby
mode which enables power saving while the appliance is not actively used and a
faster start up of the system without needing to reboot. On the other hand, many
appliances cannot be completely shut down, consequently requiring a steady wattage.
The energy efficiency technologies mentioned in the following are distinguished according to the type of component. However, improvements in standby energy consumption apply for all components and are
Techn.
status
therefore presented beforehand.
Standby mode: technical (and behavioural) options to lower standby
consumption of appliances (IZM, 2007a) (IZM, 2007b)
•
Integration of a hard off-switch can be easily installed in all
COMM
products.
•
Auto- standby / auto-off functions reduce the energy consumption by shortening the on-mode time or by turning the device from a high to a low standby mode (mainly applicable for
job related products, e.g. printers)
•
Improved circuit design permits lower wattage of the actual
standby-function due to more dedicated microcontrollers
•
Secondary power supply (e.g. batteries or super-capacitors)
for standby-functions potentially decrease energy demand, deactivating the main power supply, if higher efficiency in the low
power range is attained
Servers and data centres (BMU, 2009), (BITKOM, 2008), (IZM, 2009),
(dena, 2009): the cooling demand in data centres accounts for up to
50 % of their total final energy demand. Thus, the bulk of energy savings can be attained in this field:
EMRGCOMM
R&DCOMM
R&D
•
83
Green ICT
Providing a sufficiently dimensioned air intake for the server
permits optimum convection cooling, operation at higher supply
air temperatures and less active cooling demand. A modular
design of the server units and automatic temperature control
enhance the cooling efficiency.
•
Designing the server for higher operating temperatures of 27
EMRGCOMM
R&D
to 35°C (currently 18°C to 23°C) significantly reduces the cooling demand (up to 30 %), but requires higher standards for all
system components.
•
Waste heat recovery is an efficient option for satisfying heating
and cooling demands simultaneously. Generally, this technology is combined with so-called water-cooling, where the server
cabinet doors are used as a heat exchanger, permitting the heat
R&D –
EMRG
to be evacuated that is then directly transported to closed heat
sinks (office, flat).
•
Blade server consists of a number of similar modules that possess only a micro-processor, primary storage and one or two
hard drives. All other equipment that is generally needed exists
only once within the whole system in order to minimise power
consumption.
EMRGCOMM
•
Virtualisation software enables a better workload of server
R&D COMM
and data centres (from 5 % to 15 % up to 60 % to 85 %), thus
reducing energy demand by up to 20 %. The idea is to run two
or more logical computer systems on one set of physical hardware, reducing the need for basic equipment.
Screens: the traditional CRT (cathode ray tube) TV is being steadily
replaced by new technologies that work both as a TV as well as a PC
screen (IZM, 2007a) (IZM, 2007b), (IVF, 2007):
•
In LCD screens, changing from fluorescent to LED backlight
unit (BLU) reduces the energy consumption by up to 25 %.
•
R&D –
EMRG
Plasma display panels (PDP) are flat panel displays with pixels relying on plasma cells. A gas discharge generates ultraviolet radiation that excites phosphor, converting the radiation into
controllable visible light flux. Currently, PDPs are still much
more energy-consuming than conventional CRT and LCD
screens. However, in the long run, manufacturers expect significant efficiency gains, reducing electricity demand for a 50”
R&D –
DEMO
84
Green ICT
screen from today’s 400 W down to 70 W.
•
OLED screens consist of several thin layers that emit light
when voltage is applied. Thus, they do not need backlighting
R&D EMRG
(like LCD screens) and consume less power. Currently, they are
mainly used in small portable appliances due to low life expectancy and higher costs.
Desktops PCs consume about 1 W in standby mode, 2.5 W in sleep
mode and about 23 W in idle mode. Lower consumptions can be
reached through the following technologies (IVF, 2007), (IZM, 2009):
•
Multi core processors permit simultaneous treatment of several tasks and running at lower clock frequencies compared to
R&D –
COMM
single core processors. Since clock frequency and energy consumption directly correlate, efficiency can be improved (e.g. up
to 40 % by replacing a single core by a dual core processor).
•
Optimised design of power supply with efficiencies of more
COMM
than 90 % instead of former 65 % decrease heat losses.
•
Using flash memories instead of hard drives can significantly
decrease energy consumption (0.5 W compared to 2 W, which
is the approximate consumption of a hard drive during the reading/writing process).
•
Thin clients are PCs without a hard drive. They contain an operating system, but all other software applications are stored on
a common server that is used by several thin clients within one
system. Energy consumption is very low due to the lower number of components existing in the overall system.
•
R&D –
EMRG
The cloud computing idea describes a centralised data and
software management approach, comparable with thin clients.
But in this case the user is not aware of the physical location
and the system configuration, since all applications are used in
the online mode. Consequently, the equipment of end-user PCs
can be further minimised, reducing final energy demand.
Laptops consume (regarding best available technologies in 2007)
about 0.4 W in standby mode, 0.8 W in sleeping mode and 7 W in idle
mode. All component improvements mentioned for desktop PCs count
likewise for laptops. Hence, additional saving potentials can only be
exploited by improving battery efficiency (IVF, 2007):
EMRGCOMM
R&D EMRG
•
85
Green ICT
New battery chemicals such as lithium-mangan-oxide-spinell
R&D –
EMRG
(LiMn2O4) or ion-phosphate (FePO4) aim for higher energy capacity, slower battery ageing and a lower self-discharging rate.
•
Fuel cells represent an option in the long run to substitute conventional batteries. Direct methanol fuel cells (DMFC) are the
R&D
most appropriate fuel cell type for laptops. Related energy savings depend on the efficiency of the fuel cell, as well as on the
efficiency of hydrogen generation.
Households
4.2.5
86
Households - Household appliances
Comparing the final energy savings to the PRIMES 2009 baseline, the increasing
electricity demand (for appliances and lighting) can be depreciated by some 10
% by 2030. Compared to the value in 2007 the demand increases by 15 % versus
28 % in the baseline scenario.
The absolute saving potential sums up to almost 5.6 Mtoe in 2030, mainly triggered through efficient dryers and refrigerators. This potential is rising by 10 %
over the subsequent two decades to 6.2 Mtoe until 2050. The relative energy demand reduction is practically stagnating.
The main savings results from efficiency improvements in dryers and refrigerator,
whereas the other appliances hardly contribute any essential savings.
Figure 4-34:
Energy saving potentials in the EU27 until 2030 through efficient
household appliances in the household sector compared to the
overall residential energy demand for electric appliances and lighting
Source: historical data: (Odyssee, 2011), adjusted, FED projections: (European Commission, 2010), energy saving potentials: (ISI, 2009a)
Households
87
The cost-effectiveness as well as the energy saving potential of the considered
household appliances in 2020 is very heterogeneous. Some options are highly
economic and have a high energy saving potential (e.g. refrigerators. Further options have a high energy saving potential as well, but are uneconomic (e.g. dryers)
and thus require financial support of nearly €1 billion in 2020 in order to fully deplete the potential. The remaining appliances, such as dishwashers have a pretty
small area under the curve (i.e. very low financial benefits) based on very small
energy savings or even sometimes not visible in the chart due to their small potentials. Looking at the saving potentials in 2020 shows that four out of nine costeffective saving potentials can be declared as LHF and the remaining five saving
options with negative specific costs are defined as HHF. The IF-options are four in
number. By far the highest cost-effective saving potential can be attained by efficient refrigerators with a LHF saving potential of 0.4 Mtoe and specific costs of 1363 M€’05/Mtoe. To generate energy savings of refrigerators beyond the LHF, i.e.
HHF and IF, this technology needs to be addressed by more ambitious policy instruments. In comparison to refrigerators, the other cost-effective saving potentials
do not play a key role in 2020. Calculating the net benefits deriving from the entire
appliance related saving mounts up to €0.2 billion by 2020 (i.e. the cost savings
are nearly compensated by the need for financial support) and €1.6 billion by 2050.
Figure 4-35:
Cost curve for saving options in household appliances
Households
88
Due to the fact that electricity prices are expected to increase in the upcoming
years and the differential costs of the considered appliances remain almost the
same the cost curve moves slightly down over the time horizon. Accordingly, no
structural changes in the cost curve can be witnessed in the time steps 2020 up to
2050. Comparing the percental share of LHF, HHF and IF in the scope of 2020 and
2050 leads to the conclusion that all three categories develop almost simultaneously. The cost-effective potential increases over the horizon from 1.2 Mtoe to
3.6 Mtoe and the potential of the IF-options from 2.5 Mtoe to 2.6 Mtoe. Overall, the
saving potential of household appliances is quantified as 6 Mtoe in 2050.
Figure 4-36:
Primary energy savings from efficient household appliances compared to the PRIMES 2009 baseline energy demand for electric appliances and lighting in the residential sector
The increasing baseline electricity demand in the household sector (see Figure
4-34) can potentially be reversed into a declining primary energy demand for electric appliances and buildings through a more efficient electricity generation mix (see
“conversion savings” in Figure 4-36).
In compliance with the rather limited final energy saving potential, the effective
primary energy savings through efficient household appliances add up to 8
Mtoe in 2050, which corresponds to relative savings of 5 % compared to the
PRIMES 2009 baseline and 10 % compared to the “Ambitious RES” baseline.
Households
89
The contribution of energy saving potentials to the reduction of GHG emissions is
dominated by the decarbonisation of the power sector. Especially the continuous
reduction of the specific emissions per unit of electricity in the “Ambitious RES”
baseline leads to a decreasing effect of emission reduction through energy savings
(cf. Figure 4-37).
Hence, the GHG emission reduction potential grows up to 12 Mt CO2-eq until
2030, before dropping down to 2 Mt CO2-eq in 2050. This phenomenon results
in a contribution of efficient household appliances to the emission reduction of 6 %
and 1 % respectively compared to the PRIMES baseline in 2030 and 2050. Putting
the results into relation to the “Ambitious RES” scenario features a stable contribution of 10 %.
Figure 4-37:
GHG emission reductions from efficient household appliances compared to the calculated emissions from the PRIMES 2009 baseline
energy demand for electric appliances and lighting in the residential
sector
General information
European households reported an increasing number of electric appliances
over the past years. For example, in 1990 the dishwasher ownership rate was only
0.17 whereas, in 2008 almost every second household had a dishwasher (ownership rate of 0.5). Similar increases can be witnessed for all other types of household appliance (in this section, we consider refrigerators, freezers, dishwashers,
Households
90
washing machines and dryers as household appliances whereas TVs and all information and communication technology is addressed in a separate factsheet).
Simultaneously, the specific consumption of appliances was able to be reduced by
between 25 % and almost 40 %. This improvement was mainly driven by national
and European legislation such as the EU Energy Labelling Directive, 92/75/EEC
(which has been amended by Directive 2010/30/EU that will be applied from 31
July 2011, introducing energy labels up to A+++), and the EU Ecodesign Directive
96/57/EC (amended by Directive 2005/32/EC).
Figure 4-38:
Number of household appliances in EU27
Figure 4-39:
Average yearly specific consumption of household appliances
A rough overview of the different product categories is given in order to facilitate
assessing the energy efficiency technologies mentioned in the next section (IEA,
2003), (ISI, 2009a).
Households
91
Most of the refrigeration technologies (freezers and refrigerators) use a vapour
compression refrigeration cycle to cool stored food. Side-by-side refrigerator/freezers typically use 35 % more energy than models with the freezer on top.
Currently, the most efficient category is A++, corresponding to an Energy Efficiency
Index (EEI, calculated as the ratio between yearly energy demand and volume of
compartments) of less than 30.
Washing machines in Europe use horizontal axis drums (which are more energyefficient and water-efficient than the vertical ones) and most of them heat up the
water internally (with the exception of some appliances in Ireland and the UK). Up
to 90 % of the energy used to wash clothes is used for water and load heating. The
highest energy category of A is attained if the energy needed for one kilo of washing (using a cotton cycle at 60°C with a maximum declared load) is below 0.19
kWh.
Clothes dryers exist as stand-alone appliances as well as integrated in washerdryers. In the latter case, energy consumption for thermal drying can be significantly decreased by an intensified use of mechanical spin drying. The efficiency
classification ‘A’ represents the most energy-efficient drying class, needing less
than 0.68 kWh per kg of washing in the combined case.
Dishwashers are usually connected to the cold water tap and heat up the water
internally (which accounts for about 80 % of the total energy consumed). For the
most common size, the 12 place setting machine, the best energy classification A
is awarded to appliances using less than 1.06 kWh per washing cycle.
Since the overall efficiencies of household appliances have already
increased significantly in the past, further improvements require greater
Techn.
status
efforts and promise only minor savings. (APS, 1999)
Refrigerators and freezers (ISIS, 2008), (IEA, 2003)
•
Efficiency can be improved by better insulation, including decreased door leakage, using vacuum insulation panels (maximum energy savings: 20 %) or aerogel as insulating material.
The latter is a low-density material, featuring pores like a
sponge but on a nano-scale size, providing huge surface areas
and thus perfect insulation.
•
More efficient compressors represent another option for energy savings. Variable-speed or rated-speed compressors show
higher energy conversion efficiency due a special drive enabling
COMM
R&D EMRG
DEMOCOMM
Households
92
adjustable speed.
•
Optimised electronic control result in improved temperature
adjustment and defrost mechanisms avoiding frost on the
R&D COMM
evaporator surface that is substantially lowering the efficiency.
Dishwashers (ISIS, 2007)
•
Improving mechanical and hydraulic aspects (alternating
water spraying and higher pressure water spraying) can reduce
the amount of water consumed (from 13-14 litres down to 9-10
litres) which has a direct impact on the energy demand required
for water heating.
•
Intelligent sensors detect load weight and degree/type of dirti-
EMRG
EMRG
ness of dishes and water and automatically adjust temperature
and amount of water, detergent and timing.
•
Reduced thermal bridging between the appliance’s interior
and its exterior avoids heat losses and unnecessary water heating. (Cross flow) heat exchangers recover the heat from the
R&D –
EMRG
drained hot water to preheat the incoming fresh water.
Washing machines and dryers (ISIS, 2007)
•
Sophisticated electronic control of load, water and temperature can determine a large part of the washing cycle independently, optimising consumer behaviour regarding programme settings, thus saving water and electricity.
•
Enhanced spinning speed increases electricity consumption in
R&D –
COMM
EMRG
the washing cycle (by 5 % to 10 % at speeds above 1200 rpm)
while decreasing the remaining moisture content of the washed
load, improving the overall efficiency of the washing-drying cycle.
•
Mixed appliances which combine washer, dryer and airconditioner are designed with an air-conditioning cycle, like an
R&D
air-conditioner with a compressor. They enable washing and
drying while simultaneously cooling the room where the laundry
is washed. Electricity and water demand can be significantly reduced (water: 6 to 4 litres).
•
New and alternative washing systems shall use much less
water, re-use water or not use water at all, e.g. ozone treatment
of the wash liquor, ultrasonic agitation, high performance osmo-
R&D
Households
93
sis/filtration and steam cleaning.
The total amount of energy savings is calculated as the product of the specific energy saving of every single technology or energy labelling category and the share
of these categories in annual sales. Since the focus here is on the technical potential, the share of technologies is determined by considering the fastest entry to the
market of the more efficient products and the fastest phase-out of the least efficient
ones.
The calculated potentials are based on specific energy consumption data supplied
by a manufacturer database and on the average parameter values concerning the
appliance use at EU level. The latter may vary considerably in accordance with
user habits which might be addressed by energy policies aiming at behavioural
changes favouring energy savings. However, only technical improvements were
considered here, not behavioural aspects of appliance use.
Industry (PT)
4.2.6
94
Industry - Paper and pulp industry
In the short run, the bulk of energy savings in the paper and pulp industry can be
realised using heat recovery systems, increased use of recovered paper and a
further diffusion of the shoe press technology. In the longer term, black liquor gasification technology and water-free paper production might considerably decrease
the specific energy demand of paper production.
Assuming full implementation of the energy saving technologies mentioned, final
energy savings of 4 Mtoe in 2030 and 8 Mtoe in 2050 could be realised. This
translates into a 12 % decrease in final energy demand by 2030 compared to the
PRIMES 2009 baseline projection (2050: 24 %), reaching the 1993 level.
The potentials and technologies identified exclusively based on a decrease in the
process-specific final energy demand. Additional potentials, not included above,
can be found in efficient electric drives (integrated in pumps, presses, rolls) and
efficient steam and hot water generators (see respective factsheets).
Figure 4-40:
Energy saving potentials by efficient paper and pulp process technologies, compared to the FED of the paper industry
Industry (PT)
95
It is often difficult or impossible to allocate costs to the saving options, as for example it is not possible to draw an adequate system boundary. Moreover energy efficiency is often not the main driver for the implementation of saving options related
to process improvements, thus their costs can often not be allocated to the energy
saved. Consequently the economic potentials need to be interpreted with caution.
Regarding the paper and pulp industry all process technologies considered in the
potential analysis are supposed to be cost-efficient. As mentioned before, the cost
assessment is very difficult to carry out. Hence, the simplified assumption is made
that all cost-effective process technologies are supposed to be HHF due to their
limited range of application whereas all economic cross-cutting technologies are
supposed to be LHF potentials given their wide-spread deployment.
In the base year 2020, the potentials are rather equally spread over the different
technologies and the specific cost reduction is homogenous. Over the subsequent
decades mainly mechanical pulp and black liquor gasification experience a
strong growth of the potential. Simultaneously, process technologies that are
mainly driven by basic energy carriers (oil, natural gas, coal), such as thermo
compressors or the shoe press, report disproportionately high cost reductions. This
is due to the fact that the price rise for the mentioned basic energy carriers is supposed to be stronger than for electricity and heat. Thus, the typical upward trend
from most cost-efficient towards most expensive measure is disrupted by single
measures that experience cost reductions above the average.
Figure 4-41:
Cost curve for saving options in the paper and pulp industry
Industry (PT)
96
Summing up the overall financial benefits through saving technologies reaches €2
billion by 2020 and more than €7 billion by 2050.
Figure 4-42:
Primary energy savings from efficient paper industry processes
compared to the PRIMES 2009 baseline energy demand for the paper industry
The primary energy saving potential of efficiency measures in the paper industry mounts up to 5 Mtoe in 2030 and 10 Mtoe in 2050 (see Figure 4-42).
These savings are not significantly higher than the final energy savings, given the
fact that the fuel mix for the paper industry is assumed to be mainly relying on electricity as well as natural gas and oil products which feature relatively high (oil and
gas) or at least increasing conversion efficiencies.
The relative demand reduction through efficiency measures equals 17 % in 2050
compared to the PRIMES 2009 baseline and 24 % if conversion savings are deduced from the overall baseline.
With regard to the energy-related GHG emissions of the paper industry, efficiency
measures can contribute a 14 Mt CO2-eq cut by 2050. This can be translated
into a 19 % emission reduction compared to the PRIMES projections or a 24 %
reduction with regard to the “Ambitious RES” baseline (cf. Figure 4-43).
Industry (PT)
Figure 4-43:
97
GHG emission reduction from efficient paper industry processes
compared to the calculated emissions from the PRIMES 2009 baseline energy demand for the paper industry
General information
The paper and pulp industry is one of the most energy consuming branches in
Europe, accounting for more than 10 % of Europe’s total industrial energy consumption. While the total production of paper increased by 60 % between 1990
and 2007, final energy demand grew by 47 %. That can be translated into a specific energy efficiency improvement of 10 %.
The main paper producing countries in the EU are Germany, Finland and Sweden.
Industry (PT)
Figure 4-44:
98
Gross value, final energy demand and specific energy demand of
the European paper and pulp industry
0.42
0.41
0.40
0.39
0.38
0.37
0.36
0.35
0.34
0.33
Figure 4-45:
Paper production in the EU27
Paper is made from pulp which can be produced using wood or recycled paper.
Pulp production can be differentiated into three alternative processes using different kinds of raw materials and producing different qualities of pulp. In the production of mechanical pulp, wood is shredded and refined to obtain a fibrous pulp.
Huge amounts of waste heat are a typical by-product. Chemical pulp is also
based on wood as the raw material and is produced using chemicals (sulphite or
sulphate), which are used to separate the lignin content from the wood fibres in a
cooking process. The lignin (around 50 % of the initial wood) is then burnt in order
to generate the high amounts of steam needed for this process. The third process
is the production of pulp from waste paper.
Industry (PT)
99
The most energy consuming process is the actual paper production process that
converts pulp and other raw materials into paper. The pulp needs to be refined first
before it is pressed and dried in order to extract the water. The whole process is
very water- and steam-intensive, but electricity consumption is also high due to the
large number of electric motor applications in the paper machine.
Due to wide range of different technologies applied in the paper production process, the efficiency technologies are listed according to the
different process steps (Wietschel, 2010).
Techn.
status
Mechanical pulp (Franzen, 2006)
•
•
Energy efficiency improvements concentrate on shredding and
refining the wood, where a series of innovative concepts was
developed in the last decade. Although the recovery of waste
heat is already widespread, there are still significant saving potentials remaining.
In the long run, large energy savings could be made by switching to water-free paper production where resin or artificial ad-
COMM
R&D
hesive agents provide the adhesion between fibres. First attempts succeeded in decreasing steam demand but increased
electricity demand. Further research is needed in order to attain
a net (primary) energy saving.
Chemical pulp (Joelsson, 2008)
•
Long-term efficiency improvements concentrate on the more efficient (energetic) use of by-products like black liquor and the
general development towards a bio-refinery. The gasification
DEMO
of black liquor is discussed as a possible key element of such
a bio-refinery that would lead to significant efficiency improvements compared to the direct combustion of black liquor.
Recovered paper (Blum, 2007)
•
Greater use of recovered paper has immense potential in several European countries. Moreover, it is possible to improve the
efficiency of the individual process steps. Examples are efficient
de-inking, and efficient screening or high-consistency pulping.
Paper production (Laurijssen, 2010), (Blum, 2007)
For paper production, efforts concentrate on the efficiency of paper
COMM
Industry (PT)
100
drying - the process step that consumes the largest share of steam in
the paper machine.
•
Paper drying: Improved mechanical dewatering reduces the
need for thermal drying. Although these techniques are already
widespread, there is still potential for further diffusion.
The shoe press technology keeps the paper inside the press
COMM
for a longer period, extracting water from the paper using mechanical pressure and therefore reducing the need for thermal
drying by 10 % to 15 %.
COMM
Thermo compressors increase the pressure of low pressure
waste heat, converting it into useful heat for other processes.
•
Pulp refining: New refining concepts that claim huge efficiency
gains of up to 20 or 30 % have been entering the market in recent years.
The chemical modification of fibres is based on new insights
into the binding forces between the fibres which differ from the
classical theory of hydrogen bonds. A reduced energy demand
for mechanical fibre processing results in improved dewatering
capabilities and possibly reduced demand for fibres for the
DEMO
same amount of paper with the same strength. (Erhard, 2010)
Better use of waste heat and heat integration means that significant steam savings of up to 20 % can be realised in paper
factories as shown by a number of recent case studies.
R&D COMM
The paper production sector is divided into products and process steps with corresponding saving options. Given the fact that all these processes have a certain
specific energy consumption that shows, how much energy is used for a certain
amount of physical output (energy consumption per tonne of paper), saving options
exist, that can decrease the specific consumption and thus, make the process
more energy efficient. In total, about 80 distinct saving options are considered and
allocated to the relevant processes. The saving options that were identified have
the highest potentials and still moderate costs; Very exotic and still very expensive
saving options were not considered even in the technical potential. The technical
Industry (PT)
101
potential is characterised by a high diffusion rate (maximum boundary given by
stock and lifetime of technologies) that is: re-investment cycles are considered in
the calculated technical potentials.
Saving potentials due to dynamics in drivers, e.g. shifts between substitutable
processes towards more or less energy intensive processes are not explicitly considered as distinct saving option, still, the effects of process substitutions have an
influence on the development of energy intensity and energy demand. These effects are considered part of the autonomous progress for the industrial sector.
Industry (CCT)
4.2.7
102
Industry - Steam and hot water generation
The saving potential in industrial heat generation of 13 percent compared to the
PRIMES baseline is primarily due to the diffusion of efficient space heating technologies, a further diffusion of combined heat and power (CHP) technology replacing units of separate heat and electricity generation as well as to efficiency improvements of separate and combined heat generation technologies. Approximately 20 Mtoe of all savings result from space heating, another 9 Mtoe result from
CHP diffusion and 10 Mtoe from efficiency improvements in boiler and CHP technology. The total technical saving potential mounts up to 44 Mtoe by 2030 and
to 95 Mtoe by 2050 compared to the baseline.
Not considered are the savings from the application of solar thermal energy as this
has hardly been used in industry so far. Furthermore, in the case of CHP it needs
to be emphasised that the saving potentials can technically not be considered as
final energy because savings only arise if the comparison with a reference with
separate generation of heat and electricity occurs at the level of primary energy.
Figure 4-46:
Energy saving potentials by efficient steam and hot water generation
compared to the overall industrial final energy demand
Industry (CCT)
103
As mentioned beforehand, energy saving options in industrial steam and hot water
generation were summarized into three groups: efficient industrial space heating,
further diffusion of CHP as well as efficiency improvement of separate and combined heat and power (SHP) generation.
For space heating, it is rather easy to determine the economic potentials, assuming
that similar investments need to be undertaken as in the tertiary sector for large
buildings. Thus the saving potential is divided into a low hanging fruit part (since all
economic potentials are highly beneficial even under high discount rates, there are
no high hanging fruits) which represents roughly one third and an immature fruit
part for the rest. While the LHF potential is further increasing over up to 2050 from
4 Mtoe to 14 Mtoe, the cost reduction involved increases from €0.4 up to €10 billion. The non-economic potential becomes only cost-efficient by 2050, if no financial incentives are undertaken beforehand in order to compensate for the additional
investment of the efficiency technology compared to the reference technology.
Figure 4-47:
Cost curve for efficiency improvements in industrial steam and hot
water generation
Regarding CHP, one can assume that the investment for a CHP plant is even lower
than for the construction of two separate plants that generate the same amount of
heat and electricity individually. Consequently, the investment add-on for a CHP
plant is equal to or even lower than zero. Hence, the decisive factors for the cost-
Industry (CCT)
104
effectiveness of a new CHP plant comprise the fuel mix of the generation capacity
that is displaced by the CHP plant, the price spread between the fuels used and
the electricity produced as well as the efficiency of the CHP and the competing
SHP.
Since this is a large set of regulating screws that can be adjusted, a parameter
variation has been carried out in order to depict the entire range of CHP costeffectiveness. The results and the main assumptions of this sensitivity analysis can
be found in the paragraph on the methodology of the potential calculation further
below in this fact sheet.
For this present economic potential assessment the most probable case has been
chosen: new SHP plants consisting of 50 % hard coal fuelled (from 2030 onwards
equipped with CCS technology) and 50 % natural gas fuelled plants will be displaced by CHP plants with a mix of 80 % biomass and 20 % natural gas. For SHP
as well as for CHP an efficiency improvement in assumed. This scenario is also
used in the further potential summation on sectoral as well as on the overall level.
Figure 4-47 shows the cost curve of the analysis as well as the specific cost reductions through space heating. While energy saving options for space heating experience a further decrease in specific costs, for CHP the opposed trend can be
observed. This effect is driven through a decreasing fuel price spread between the
fuels used in SHP and CHP and the electricity produced. Hence, the cost advantage of the CHP plant is continuously compensated by relatively slower increasing
fuel prices for SHP plants.
The primary energy savings in Figure 4-48 illustrate a constantly increasing potential until 2050. The amount of savings due to CHP is 54 Mtoe and the improved
efficiency of space heating sums up to 47 Mtoe. Thus, compared to the PRIMES
2009 baseline 17 % could be saved until 2050. Taking also the conversion savings from the industry sector into account (173 Mtoe) an overall primary energy
reduction of 46 % in 2050 can be attained.
Industry (CCT)
Figure 4-48:
105
Primary energy savings from efficient industrial steam and hot water
generation compared to the PRIMES 2009 baseline energy demand
for the industry sector
As indicated in Figure 4-49 the potential to reduce greenhouse gas emissions due
to the diffusion and increased efficiency of CHP and more efficient space heating
develops in analogy to the primary energy savings with a constant increase until
2050. In 2050 the greenhouse gas emission reduction is about 244 Mt CO2-eq
which is a share of 29 % of the overall emissions compared to the PRIMES
2009 baseline. Combined with the emission reduction through conversion savings
in the industry sector (that occur independently from the CHP diffusion) the total
GHG emission reduction might mount up to 433 Mt CO2-eq or 56 %.
Industry (CCT)
Figure 4-49:
106
GHG emission reduction from efficient industrial steam and hot water generation compared to the calculated emissions from the
PRIMES 2009 baseline energy demand for the industry sector
General information
Steam and hot water are used in industry for a wide variety of different purposes.
Whereas temperatures below 100 °C tend to be used for water and space heating in the food and tobacco industries as well as in textiles, temperatures between
100 and 500 °C are needed for many different industrial processes like paper or
polyvinyl chloride production. Heat use of temperatures up to 1000 °C and above
is very specialised and process-specific, e.g. iron and steel or glass and ceramics (Eichhammer 2009). Based on the predicted trend of the PRIMES 2009 baseline scenario, the energy consumption of steam and hot water appliances is likely
to remain more or less stable in the future. Due to the fact that modern appliances
for steam and hot water generation already have efficiency levels of 90-95 %, this
technology can be described as highly developed (Schmid, 2003).
Industry (CCT)
Figure 4-50:
107
Share of total heat demand in the industry sector in EU27
Source: (Schmid, 2003)
Different types of boilers and burners are applied to generate steam and hot water
for industrial use. Commonly used boilers work in a power range of 100 kW – 50
MW and are typically fired by oil, lignite, hard coal, electricity, natural gas (mixed
with biogas) or biomass. The choice of boiler generally depends on the process
requirements (ISI, 2009a), (ISI, 2009c), (Schmid, 2003), (IEA, 2009a):
•
A fire-tube boiler is a type of boiler in which hot gases from a fire pass
through one or more tubes that run through a sealed container of water.
The heat from the gases is transferred through the walls of the tubes by
thermal conduction, heating the water and ultimately creating steam. Firetube boilers are the most widespread boilers used in industry, usually running at a pressure level of 10 to 20 bar with a power of 5 to 15 t/h (89 - 90
% efficiency).
•
For appliances with a steam demand above 50 t/h and a pressure level
above 20 bar, water tube boilers are employed (94-95 % efficiency). A water tube boiler circulates water in externally heated tubes. Because the
heating surface can be increased indefinitely, the steam output is theoretically not limited to a certain degree.
•
Unlike the previous boiler types, high-speed steam generators heat and
evaporate while the feed water is running through tubes. Due to this technical principle, high-speed steam generators are utilised everywhere in indus-
Industry (CCT)
108
try where steam is needed in a relatively short period of time. Therefore, the
power of high-speed steam generators is limited to 5 t/h and a pressurerange of 1 - 30 bar (87-88 % efficiency).
•
When high operating temperatures in the range of 200 - 300 °C and high
pressures like 80 bar are needed, e.g. in drying processes in the chemical
industry, thermal oil heaters are applied (85-89 % efficiency). In contrast
to water-based heat generators, thermal oil heaters use oil as the energy
carrier.
Besides technical improvements to the above mentioned boilers, alternative generation concepts and the greater integration of renewable
energies offer substantial saving potentials (ISI, 2009a), (ISI, 2009c),
(Schmid, 2003), (IEA, 2009a):
•
Combined heat and power generation systems (CHP system)
can be used instead of steam boilers to provide steam for processes up to 500 °C. In CHP systems, a variety of technologies
is applied such as steam backpressure turbines, condensing
Techn.
status
EMRGCOMM
turbines, gas turbines and combined cycle gas turbines. Their
efficiency increases from the former to the latter by approximately 20 % to an overall efficiency above 40 %.
•
To increase the heat produced by CHP technologies above
500°C, one option might be to apply a solid oxide fuel cell
(SOFC). Their higher operating temperature up to 900°C makes
SOFCs suitable candidates for application with CHP.
•
Economisers operate in a similar way to heat exchangers, ex-
R&DDEMO
COMM
tracting residual heat from flue gases to subsequently preheat
the feed water. Besides integrated solutions, economisers can
also be used to retrofit existing generation appliances.
•
To apply condensing heating technology, a heat exchanger is
installed downstream to the economiser, which cools the flue
gases below condensation temperature. During this process,
condensing heat is released, which is directly supplied to the
closed heating circuit.
•
Depending on the age and fuel type of the burner, the operating
excess air lies within a range between 5 and 20 %. Calorific energy is purged in this process. By implementing O2-regulation
COMM
R&DCOMM
Industry (CCT)
109
equipment the air supply can be optimised and energy demand
minimised.
•
Using a continuously variable burner enables boilers to be
run in a partial-load operation range which can prevent frequent
start-and-stop operation. This can reduce idling losses because
the furnace no longer needs to be purged before being triggered.
•
Surface heat losses can be reduced by improving boiler insulation. Typical insulation materials applied include polyurethane
DEMOCOMM
R&DCOMM
foam and mineral wool.
As described in the general methodology section the technical potentials have
been calculated on a scenario approach. Details of the methodology are presented
in ISI (2009a); this section provides only an overview of the most important elements.
The calculation of technical potentials considers eight technology groups for the
generation of heat in industry, of which only boilers represent the separate heat
production (SHP), all other technologies are applied for combined heat and power
generation (CHP): Steam backpressure turbine, Steam condensing turbine, Gas
turbine, Combined cycle, Fuel cells, Internal combustion engine, Boilers, Others.
Main input variable for the calculations is the heat demand of industry. It is derived
in the first part of the model, taking into account the development of production and
value added as well as certain sector specific energy saving options and assuming
an average combustion efficiency of 85 %. In the next step, the total heat demand
is allocated to different temperature levels, as the possibilities and the technologies
for supplying heat depend strongly on the temperature needed.
Two general groups of saving options in heat generation are implemented: improved diffusion of combined heat and power replacing separate generation of heat
and electricity and improved efficiencies in separate as well as combined heat
generation. We applied a methodology in accordance with Eurostat (Eurostat
2001) that calculates the savings by comparing the CHP system with an alternative
system that might be in place, if the CHP unit would not have been built. The saving potential is defined as the difference between primary energy demands of both
systems. Consequently, the choice and definition of the alternative system - the
system that was replaced by the CHP plant – has considerable influence on the
results.
Industry (CCT)
110
The technical potential is characterised by a high diffusion rate of CHP (max 90%
of a sector's heat consumption below 500 C to be generated in CHP plants) and a
fast EU-wide convergence of plants' mean efficiency values.
Regarding the assessment of the economic potential, a parameter variation was
carried-out. A detailed description of the calculation procedure carried out can be
found in Annex III.
Industry (CCT)
4.2.8
111
Electric drives
Industry - Electric drives
Due to the already high efficiency of electric drives the energy saving potentials
attributed to this technology are rather low despite their wide range of application.
As indicated in the chart, the overall potential of fans, compressed air appliances
and pumps are almost equal, which is in the range of 0.25 to 0.3 Mtoe, whereas
the savings of cold appliances are just 0.12 Mtoe. The improvement of miscellaneous electric motor driven appliances accounts for about 0.8 Mtoe. Thus, the electricity demand in the European industrial sector can be reduced by 1.8 Mtoe
or 0.5 percent until 2030. By 2050, the potential doubles up to 4 Mtoe or 1 %
energy savings compared to the baseline. In comparison to the energy savings
from system optimisation of motor driven appliances (cf. 4.2.9) the potential of the
motor itself is nine times lower.
Figure 4-51:
Energy saving potentials of efficient electric drives in the industry
sector, compared to overall industrial final energy demand
Industry (CCT)
112
Electric drives
The implementation of energy saving options in cross-cutting technologies is basically very cost-effective. Thus, these options can be achieved with minimal political
incentives and therefore are declared as LHF.
As indicated in Figure 4-52 the cost curve for electric drives is very easy to interpret. Looking at the year 2020 on the cost curve shows that the potentials are 0.8
Mtoe in the first time interval. To attain this potential the specific costs are -1056
M€’05/Mtoe. Due to the fact that the efficiency of an average electric drive is nowadays about 90 - 95 % the specific costs only change marginally in the subsequent
years in comparison to 2020. The specific costs decrease slightly down to -1156
M€’05/Mtoe in 2050 and the saving potentials from 2020 to 2050 are almost quadrupled. Overall, the saving potential of electric drives is quantified as 4 Mtoe.
The quadruplication of the saving potential can be entirely translated to the equivalent evolution of the cost savings, growing from nearly €1 billion in 2020 up to more
than €4 billion in 2050.
Figure 4-52:
Cost curve for the implementation of high-efficient electric drives in
the industry sector
Industry (CCT)
113
Electric drives
Figure 4-53:
Primary energy savings from efficient electric drives compared to the
PRIMES 2009 baseline energy demand for the industry sector
As indicated in Figure 4-53, the primary energy saving potential increases steadily up to 5 Mtoe until 2050. Thus, in comparison to the PRIMES 2009 baseline
approximately 0.8 % of the overall primary energy demand could be reduced by
improving electric drive efficiency. Whereas the percental share compared to the
“Ambitious RES” baseline is 1.1 %. Due to the ambitious transformation of energy
supply combined with the fact that electric drives are not very significant in terms of
primary energy reduction the overall potential in 2050 to abate greenhouse gas
emissions amounts for only 1 Mt CO2-eq (Figure 4-54). Therefore the contribution of electric drives is for each baseline below 1 %.
Industry (CCT)
Figure 4-54:
114
Electric drives
GHG emission reduction from efficient electric drives compared to
the calculated emissions from the PRIMES 2009 baseline energy
demand for the industry sector
General information
In contrast to process technologies that are solely deployed in specific branches
cross-cutting technologies are spread over all industrial sectors (cf. Figure 4-55).
The cross-cutting technology applied most is the category of electric drives, accounting for 60-70 % of the industrial electricity consumption (cf. Figure 4-56).
Typical electric motor-driven applications are pumps, compressors and fans that
account for 30 % of the total electricity demand combined. Depending on the type
of branch the share of electric drives varies between 35 % and 90 % (ISI, 2009c),
(Wietschel, 2010).
Industry (CCT)
Figure 4-55:
115
Electric drives
Electricity demand share of cross-cutting technologies by appliance
in the European industry sector
Figure 4-56:
European industrial electricity demand by appliances in the industry
Industry (CCT)
116
Electric drives
In general, electric drives convert electric energy into mechanical energy. To
provide this function the majority of electric drives operates by the interaction between magnetic fields and current-carrying conductors to generate force to spin the
rotor, whereas a minority uses electrostatic fields. In addition most electric drives
are also able to run as a generator by reversing this process and thus producing
electrical form mechanical energy. For instance, the generator function is necessary when recovering braking energy or any other form of kinetic energy (Almeida
2008).
Although a high variety of electric drives is available, asynchronous motors are
most prevalent – basically in the power range of a few hundred watts up to 7.5
kW. Their key advantages are to be robust, low-priced and very energy efficient.
Therefore, about 80 % of the European energy demand of electrical drives is associated to asynchronous motors (Almeida 2008). Further types of electric drives are
usually deployed for niche applications with special requirements.
Electric drives are already applied in industrial sector since the mid of the nineteenth century. Since then, continuous improvements in terms of energy efficiency have been accomplished up to a level of 90-95 % (Odyssee, 2011). Nevertheless, a development towards more efficient electric drives is still in progress.
(The partially double-labelling of the characteristic curve below is due to the introduction of a new efficiency classification: IE1 = formerly eff2, IE2 = formerly eff1,
IE3, etc. Motors labelled with IE4 and even more ambitious IEC-Classifications are
not defined, yet.)
Figure 4-57:
Differences in efficiency of 4 poled electric motors
Source: (Almeida, 2008)
Industry (CCT)
Figure 4-58:
117
Electric drives
Market share of EFF-motors in the EU27
Source: (CEMEP, 2011)
Due to the fact that the efficiency of best available drive technology has
already reached a level of 95 %, further improvement is hard to gain.
Nevertheless, in the light of 60-70 % of industrial electricity consumption, a significant amount in overall savings can already be achieved by
Techn.
status
small steps towards a more efficient design.
•
By replacing the aluminium rotor through copper the electrical resistance decreases. Thereby, the asynchronous motor efficiency can be increased by additional 1.5 to 3.3 percentage
F&ECOMM
points (Deivasahayam, 2005). As a result of a simulation study
(Doppelbauer, 2005) even computed an enhancement of efficiency from 2.1 to 6.9 percentage points, depending on the
power class of the electric drive.
•
In smaller performance categories permanent-magnet motors
can even achieve a better efficiency than the most efficient
R&DCOMM
asynchronous motor. A permanent-magnet motor does not have
a filed winding on the stator frame, instead relying on permanent magnets to provide the magnetic field against which the rotors field interacts to produce torque (Lindegger, 2006).
•
Superconducting motors are new types of alternating current
(AC) synchronous motors that employ HTS (high temperature
superconductor) windings in place of conventional copper coils.
R&DDEMO
Industry (CCT)
118
Electric drives
Because HTS wire can carry significantly larger currents than
copper wire, these windings are capable of generating much
more powerful magnetic fields in a given volume of space.
Therefore, minimum losses in conduction of electricity can be
achieved (Wietschel, 2010).
The main database is represented by the preparatory studies for energy using
products on Lot 11 covering electric motors. For electric motors a stock model was
used based on motor efficiency classes IE1 to IE4. The technical potentials was
characterised by a high diffusion rate of saving options (maximum boundary given
by stock and lifetime of technologies).
Industry (CCT)
4.2.9
119
Industry – E-drive system optimisation
As illustrated in the chart, holistic improvements of motor driven systems can lead
to a fundamental decrease in electricity consumption until 2030. Variable speed
drives are estimated to have the highest saving potential with 4 Mtoe, followed
by the implementation of demand related control systems (2.2 Mtoe) and the
avoidance of oversizing (2 Mtoe). Compared to the technical improvements, the
separately listed organizational measure, regular maintenance, has a minor impact
which is a share of five percent of the overall saving potential. In comparison to the
physical improvements of electric drives (see factsheet electric drives) these
measures can lead to a nine times higher saving potential. Putting this into perspective to the PRIMES baseline projection, the overall energy savings assessed
for the optimisation of electric motor driven systems is 19 Mtoe or 6 % by
2030 and 40 Mtoe or 11 % by 2050.
Figure 4-59:
Energy saving potentials of e-drive system optimisation measures in
the industry, compared to overall industrial final energy demand
Industry (CCT)
120
The implementation of the energy saving options in cross-cutting technologies is
basically very cost-effective. Thus, these options can be achieved with minimal
political incentives and therefore are declared as LHF.
As indicated in Figure 4-60 the energy saving potentials as well as the specific
costs for e-drive system optimisation are steadily growing until 2050. The utilization
of variable speed drives is the most cost-effective saving measure with -912
M€’05/Mtoe and energy savings of 3 Mtoe, which is 21% of the overall energy savings in 2020. Looking at the combination of energy saving potentials and specific
costs in 2020 of the remaining options the avoidance of oversizing, demand related
control systems and the application of high efficiency appliances are in the second,
third and fifth place in terms of specific costs each with an energy saving potential
between 1.2 and 1.7 Mtoe. Furthermore, the utilization of direct drives instead of
belts and the optimisation of ducting are exclusively illustrated in the chart as costeffective measures, but only with a minor impact regarding their saving potential.
Figure 4-60:
Cost curve for energy savings through e-drive system optimisation
Last but not least all the other saving options that are not discussed in detail in this
study play a substantial role as well. These options are illustrated en bloc referred
to as other options with specific costs of -1113 M€’05/Mtoe and energy savings of
4.9 Mtoe in 2020. Just the regular maintenance is not cost-effective, which results
from high labour costs for maintenance specialists. These costs do not compensate the monetary energy savings. Comparing the costs and energy potentials of
the subsequent years with 2020, nothing surprising can be witnessed. The energy
potentials gain for every measure, the negative specific costs increase steadily and
Industry (CCT)
121
the positive specific costs of the regular maintenance decrease respectively, which
is based on the reason of growing electricity prices. Overall, the saving potential of
e-drive system optimisation is quantified as 40 Mtoe in 2050.
The net benefits resulting from e-drive system optimisation mount up to nearly €14
billion by 2020 (whereof less than one percent is needed to compensate for the
additional costs through regular maintenance) and €45 billion by 2050.
Figure 4-61:
Primary energy savings from e-drive system optimisation compared
to the PRIMES 2009 baseline energy demand for the industry sector
Until 2050 there is a constant increase of primary energy savings up to 50 Mtoe
(cf. Figure 4-61). In relation to the PRIMES 2009 baseline the optimisation of electric drive systems amounts for 8 %. Given the potential of conversion savings of up
to 173 Mtoe in 2050 the percental share of primary energy savings compared to
the “Ambitious RES” baseline is 12 %.
Regarding greenhouse gas emissions the reduction that can be achieved increases to a level of 41 Mt CO2-eq until 2030 and afterwards decreases down to
10 Mt CO2-eq in 2050. Thus, the contribution of optimised electric drives ranges
between 1 % and 2 % (see Figure 4-62).
Industry (CCT)
Figure 4-62:
122
GHG emission reduction from e-drive system optimisation compared
to the calculated emissions from the PRIMES 2009 baseline energy
demand for the industry sector
General information
E-drive system optimisation is a holistic approach that considers all elements of a
technical system. Therefore, instead of solely improving the performance of physical components the system optimisation approach aims to increase the efficiency
of the system as a whole by involving technical as well as organizational improvements. To ensure the prevention of overlapping between system optimisation measures and electric drives, technical improvements of the motor itself are
not considered as system optimisation. Hence, no double counting of potentials
does take place.
Per definition, e-drive system optimisation influences organizational and technical
procedures as well as behavioural patterns in order to reduce the total operational
energy consumption, to use basic and additional materials economically and to
continuously improve the energy efficiency in the company. In other words, system
optimisation is a tool to enable continuous and systematic use of added energy saving potential to ensure minimum energy consumption for the current activity.
Industry (CCT)
123
Due to high expected energy saving potentials associated with system optimisation
the Directive EN 16001 came into force in 2009 defining standardised EU-wide
criteria. EN 16001 is a classical management system standard which is in principle
not specifically sector-oriented or designed for certain types of companies. In terms
of electric drive related system issues all kind of aspects can be defined as energy
management or system optimisation, they simply need to increase the overall efficiency by improving the configuration of the system.
In contrast to the other wedges where short term and long term perspectives are distinguished due to the development stage of the considered technology, the holistic approach of e-drive system optimisation
cannot be divided in this manner. Thus, all measures introduced in the
following could – in theory – immediately be implemented (Almeida,
VSDs for electric motor systems, 2000) (Almeida, VSDs for electric
motor systems, 2000), (Almeida, Improving the penetration of energy-
Techn.
status
efficient motors and drives, 2001), (Almeida, 2008), (IEA, 2009a).
•
An adjustment of speed and torque to the load requirements
could be achieved by using variable-speed drives (VSD). VSD
EMRGCOMM
is a system for rotational speed of an alternating current electric
drive by controlling the frequency of the electrical power supplied to the motor.
•
Despite the fact that belt drives are not state-of-the-art anymore,
some motor related devices still utilise this mechanism to
transmit the torque from an electric drive to the application. The
associated slip losses can be avoided by using direct drives
instead of belts.
•
•
When using electric motors to drive pumps, fans or compressed
air components the optimization of ducting leads to further
COMM
improvement of energy efficiency.
EMRGCOMM
The degree of efficiency in a technical system is generally determined as the product of efficiencies of the single components. Thus, just by exclusively using high efficiency appliances the possibility to consume an optimum or rather a mini-
EMRGCOMM
mum of electricity can be achieved.
•
To avoid oversizing electric drives, the motor specifications
need to be matched with the requirements of the application or
the whole system, respectively. Otherwise the motor runs at a
COMM
Industry (CCT)
124
sub-optimal load factor which significantly reduces the efficiency
of power use.
•
A further controlling aspect to improve electricity efficiency is to
implement a demand related control system. This kind of systems are nowadays usually designed as a closed loop control
which automatically move the system to the desired operating
point and maintain it at that point thereafter by using some or all
of the outputs as input parameters to optimise the system in
terms of efficiency.
•
Besides technical aspects further efficiency can be achieved by
proper and regular maintenance. Depending on the type of
system, e.g. compressed air or ventilation, the workload to realise this measure varies. Thus, costs are the limiting factor to
gain the optimal potential in this case.
•
Besides these measures to improve efficiency a multitude of
small / other options exists to save electricity in a motor driven
system. Measures attributed to this category are in general directly linked to specific cross-cutting technologies like surface
smoothing and coating is related pumps or frequent replacement of filters, which is relevant for compressed air as well as
for ventilation systems.
EMRGCOMM
COMM
R&DCOMM
In order to estimate the impacts of holistic system optimisation on motor systems,
case studies on saving potentials in certain companies were used as basis for own
estimates, and used in the following equation:
Pot tech, Rem, t = Pot tech, Ref * (Sh Applicable - Sh Applied, t)
For each saving option a technical saving potential, Pot tech, Ref, t, is calculated as
average value from the case studies. This is corrected by the share of cases or
companies in which the saving option is applicable, Sh Applicable, and the share of
companies that have already applied the option at a certain point in time, Sh Applied, t.
Result is the remaining technical saving potential at this point in time, Pot tech, Rem, t.
Industry (CCT)
125
The interactions between different saving options acting on the same system were
taken into account by reducing the mutual potentials.
Transport (road)
4.2.10
126
Transport - Technical improvements
In 2030, the technical potential of road transport efficiency technologies sums up
to more than 77 Mtoe energy savings, accounting for about 26 % reduction of
final energy demand in 2030 compared to the PRIMES 2009 baseline. That can
be translated by a decline in energy demand back to the 1990 level. Further
savings of 13 Mtoe permit reducing the final energy demand of road transport by
means of technical improvements by one third up to 2050.
More than half of the saving potential is based on improved efficiency of passenger cars and one third results from more efficient trucks and light duty vehicles.
In addition to the technologies mentioned above that focus only on conventional
internal combustion engines, alternative fuels (e.g. liquefied petroleum gas, LPG,
or hydrogen) and alternative drive concepts represent additional energy saving
options. They are analysed in further detail in the factsheet called “e-Mobility”.
Figure 4-63:
Energy saving potentials of technical improvements, compared to
the overall final energy demand in the road transport sector
Transport (road)
127
Analysing the technical potentials regarding their financial costs and benefits leads
to the conclusion that the predominant potentials from technical improvements in
passenger cars are mostly cost-effective, featuring specific energy saving reduction costs of -1152 M€’05/Mtoe (LHF) and -732 M€’05/Mtoe (HHF), respectively.
Only motorcycles report even more attractive cost reductions, however their overall impact is quite smaller due to the little potentials.
Freight transport represents the opposed picture: in 2020, more than half of the
potential is non economic, hence requiring additional financial support which even
exceeds the specific benefits from the passenger transport LHF potential (1517
ME’05/Mtoe vs. 1153 M€’05/Mtoe). Nevertheless, the potential from the passenger cars related low hanging fruits is twice as much as the potential of the freight
transport related immature fruits, hence entirely compensating for additional costs.
Figure 4-64:
Cost curve for saving options through technical improvement in the
transport sector
Creating incentives for the entire deployment of the cost-effective potential (i.e. the
low and high hanging fruits) could trigger benefits of more than €26 billion in 2020.
If the political measures are enlarged on the entire set of cost-effective measures,
the benefits would exceed €30 billion by 2020. Nearly one third of these benefits would be sufficient for unlocking the potentials that are not cost-efficient yet
Transport (road)
128
(basically technical improvements in road freight transport), leading to netbenefits of €18 billion in 2020.
Over the subsequent decades up to 2050 the specific financial savings as well as
the overall cost-efficient potentials savings will roughly double, resulting in an approximate quadruplication of the financial benefits by 2050. Although the
share of immature fruits is further growing, its specific costs are decreasing too,
reducing the need for financial incentives to such an extent that the net benefits
are even growing by factor five.
The fuel mix is the main driver for the degree of fuel price reduction over time.
Since motorcycles are solely gasoline-fuelled and gasoline is the most expensive
fuel, a similar percental price increases for all fuels lead to surpassing cost reductions for motorcycles. This explains why motorcycles are actually reporting the
strongest cost reduction over time which is the reason for the increasing deformation of the cost curve shape.
Consequently, diesel fuelled trucks and LDVs benefit less from fuel price rises
than diesel and gasoline fuelled passenger cars which in turn benefit less than
motorcycles regarding the net decrease of specific energy saving costs.
Primary energy saving and GHG emission reduction potential
Figure 4-65:
Primary energy savings from technical improvements compared to
the PRIMES 2009 baseline energy demand for the road transport
sector
Transport (road)
129
The ratio between final and primary energy demand in the transport sector differs
substantially from the remaining sectors. Given the fact that oil products represent
the predominant energy carrier in the transport sector 40 being generated with
relatively low conversion losses (see also section 4.1.4), final and primary energy
demand as well as the respective saving potentials are of the same order of magnitude. Thus, the conversion chain from primary to final energy provides only limited potential for further efficiency improvement. Hence, technical improvements
in the road transport sector represent primary energy saving potentials of 84
Mtoe by 2030 and 93 Mtoe by 2030. These figures correspond to a 20 % and 25
% reduction compared to the PRIMES baseline or a 21 % and 26 % reduction
compared to the “Ambitious RES” baseline (cf. Figure 4-65).
Figure 4-66:
GHG emission reduction from technical improvements compared to
the calculated emissions from the PRIMES 2009 baseline energy
demand for the road transport sector
The conversion of primary energy savings into GHG emission reductions results in a decrease of 254 Mt CO2-eq by 2030 and 278 Mt CO2-eq by 2050. The
bulk of the savings is the delivered by technical improvements in passenger cars
(170 Mt CO2-eq in 2050) and in goods transport vehicles (99 Mt CO2-eq in 2050).
40 In the present analysis the focus is set on the assessment of the energy saving potential through
conventional drive concepts. Alternative drive concepts using other energy carriers such as electricity are addressed separately in 4.2.12 and Annex IV.
Transport (road)
130
The relative emission reduction in 2050 equals 28 % compared to the PRIMES
2009 baseline and 29 % compared to the “Ambitious RES” baseline (see Figure
4-66).
General information
The development in the road transport sector is characterised by a steady increase in the final energy demand (FED) amounting to 30 % over the past two
decades (in 2007: 303 Mtoe), although some countries (such as Germany,
France, Italy or UK) are already showing stabilised or even decreasing trends.
Passenger transport accounts for nearly 60 %, goods traffic for about 38 % of FED
in road transport, while public transport and motorcycles represent only 2 % and 1
%, respectively. The specific fuel consumption of passenger cars (measured in
litres of fuel per 100 kilometres) reported an actual efficiency improvement.
However, total energy demand increased due to increasing passenger and goods
transport (cf. Figure 4-73)
The number of gasoline cars grew by only 10 % compared to 1990s level, while
the number of diesel vehicles increased dramatically (350 % for passenger cars,
150 % for trucks and light duty vehicles, LDVs). Consequently, 232 million passenger cars, about 35 million trucks and LDVs and roughly 30 million motorcycles are on Europe’s streets today.
This factsheet only addresses energy saving technologies for conventional cars
equipped with an internal combustion engine. Alternative drive concepts (such as
electric vehicles or fuel cell cars) and fuel savings through behavioural changes
are discussed in the respective factsheets.
Figure 4-67:
Final energy demand of road transport in EU27
Transport (road)
Figure 4-68:
131
Average specific fuel consumption of passenger cars (existing stock
compared to new cars)
9.0
8.5
8.0
7.5
7.0
6.5
6.0
5.5
5.0
Public and goods transport is mainly based on diesel (about 94 % in 2007),
whereas the majority of passenger cars run on gasoline. However, there is a remarkable shift taking place from gasoline to diesel engines (in 2000, only 25 % of
all cars ran on diesel, in 2008, already nearly every second car did so). The growing interest in diesel-fuelled cars is due to the major advantage of diesel engines, which have about 35 % greater fuel economy than gasoline engines
with similar CO2 emissions.
According to the EU Car Labelling Directive 1999/94/EC (European Commission,
1999), cars emitting less than 100 g/km of CO2 are rated best (A), while those
emitting more than 250 g/km have the lowest rating, i.e. G. For gasoline, A corresponds to about 4.1 litres per 100 kilometres and G to about 9.5 litres per 100
kilometres.
Energy saving technologies
Since most of the efficiency technologies that can be applied to passenger cars are suitable for both light and heavy duty vehicles, they are
not distinguished by car type if there are no major differences.
The bulk of energy savings are covered by fuel efficiency improvements inside the engine, however the whole range of potential measures is listed below (IEA, 2005), (IEA, 2010b), (Kobayashi, 2009):
•
Engine: The average efficiency of the engine and the drivetrain
can be increased by reducing internal friction losses (e.g. us-
Techn.
status
Transport (road)
132
ing low friction oils), limiting the engine’s consumption during
idling and braking periods and direct fuel injection. Direct injection a more accurate fuel proportioning of the fuel injected
and improved injection timing. Thus more complete combustion
delivers higher performance with up to 18 % lower fuel consumption. This efficiency gain is partly due to intake valve control and other engine technologies, too. Other important technologies include cylinder shutoff during low load conditions
and improved valve timing and lift controls.
Diesel engines can be further improved by combining direct
fuel injection and turbocharging (also called fuel stratified in-
COMM
COMM
EMRG
COMM
jection). This allows more compressed air and fuel to be injected into the cylinders, generating extra power from each explosion, i.e. smaller engines but the same performance.
•
Transmission: Limiting engine speed makes it possible to run
the engine at the optimal operation point. Altering engine speed
is done by changing the transmission ratios through the use of 6
or 7 speed manual or automatic gear boxes.
Continuously variable transmission (CVT) uses a pair of
variable-diameter pulleys connected by a belt or chain that can
produce an infinite number of engine/wheel speed ratios instead
R&D –
COMM
EMRGCOMM
of relying on a fixed number of metal gears.
•
Body: Reducing the tractive force requirements results in direct
fuel savings. Light weight vehicle body constructions made of
aluminium can result in up to 0.3 l/km per 100 kg of weight
saved.
Aerodynamic efficiency (drag reduction) is expected to con-
R&D –
COMM
R&D –
COMM
tinue to improve (after mean improvements of 10 to 15 % every
decade in the past) until practical thresholds are reached beyond which any further improvement will involve significant
compromises in appearance and space utilisation.
COMM
Low rolling resistance tyres reduce hysteresis losses by using new types of rubber and new belt materials and by improving the design of the tread and side-wall. Decreased rolling resistance lowers gasoline consumption by an estimated amount
of 1.5 – 4.5 %. (CEC, 2003)
•
Accessories: Typical engine-related accessories include the al-
R&D –
Transport (road)
133
ternator, the power steering pump or the oil and water pump
which have low efficiencies due to low costs. Integrating very
efficient accessories can further decrease the fuel demand.
Advanced air conditioning systems using electrical heat
pumps can reduce loads by 70 to 75 %. Improved roof insulation and using specially tinted glass as a barrier to infrared
COMM
R&D
radiation are other options.
Data from the TREMOVE model have been chosen as the source from which all
activity data needed for transport were taken. This is due to the fact that the energy drivers considered by this model are taken from PRIMES which was used to
analyse other energy efficiency potentials. In particular also rebound effects in the
form of increased car size were taken from this model.
For the estimate of the technical potential 80g CO2/km were considered to be
achievable as a maximum in 2025 (125g CO2/km in 2012, 95g CO2/km in 2020;
80g CO2/km in 2025; value constant after 2025 up to 2030) According to the
European Parliament, long-term targets “will possibly require further emissions
reductions to 70g CO2/km or less by 2025.” Nevertheless, it can be assumed that
such a target may also require additional adding of biofuels. The ability to add
further biofuels (at least the ones of first generation) is currently an issue of debate. Starting from these average values for Europe, country specific developments were determined based on present level differences among the stocks in
the countries. For light duty vans the technical potential was considered to be at
130g CO2/km in 2020 (160g CO2/km in 2012; value decreasing to 120g CO2/km
up to 2030). The technical potentials for trucks and trailers have been investigated
empirically by truck manufacturers and were used to calculate energy efficiency
potentials for goods transport.
Transport (road)
4.2.11
134
Behavioural changes
Transport – Behavioural changes
The total amount of energy savings sums up to 38 Mtoe in 2030, which corresponds to a 13 % demand reduction compared to the PRMIES baseline projection. In the short term, passenger road transport promises fast efficiency gains
whereas the influence of goods transport prevails in the long run. By 2050, only
a slight potential rise of some additional 6 Mtoe permits dropping the overall final
energy demand of road transport by 16 %.
Generally speaking, eco-driving plays a more important role in passenger transport whereas the load factor increase is considered more significant for freight
transport. The decreasing technical potential for passenger cars beyond 2015 can
be explained by an assumed enhanced autonomous diffusion of energy saving
technologies in the baseline scenario, reducing the actual amount of additional
energy savings.
Figure 4-69:
Energy saving potentials of behavioural changes, compared to the
total final energy demand of road transport
Transport (road)
135
Behavioural changes
Figure 4-70 depicts very well that any kind of behavioural change in passenger
transport is directly correlated with a net financial benefit. While between 2020
and 2030 a certain number of technical efficiency improvements (see also 4.2.10)
are supposed to occur that drop the saving potential of behavioural oriented measures, the financial advantage of behavioural change is steadily increasing due to
rising fuel prices. The matter of fact that some potential need stronger political push
(HHF, -838 M€’05/Mtoe) than others (LHF, -1900 M€’05/Mtoe) can be explained by
the various types of side-effects (e.g. avoiding high speeds is related to longer driving periods).
This effect is even more significant in freight transport where single measures
(such as lower driving speeds) directly correlate with increased labour costs.
Hence, nearly 44 % of all behavioural changing measures in road freight transport
are considered as immature fruits until rising fuel prices compensate additional
labour costs.
Nonetheless, the deployment of the entire range of potentials drives benefits of €23
billion for passenger and €4 billion for goods transport in 2020, rising up to
€33 billion and €20 billion respectively by 2050.
Figure 4-70:
Cost curve for saving options through behavioural changes in the
transport sector
Transport (road)
136
Behavioural changes
Figure 4-71:
Primary energy saving potentials from behavioural changes compared to the PRIMES 2009 baseline energy demand for the transport sector
Figure 4-71 depicts the primary energy saving potentials from behavioural changes
in the passenger and goods road transport. The potentials equal 41 Mtoe in 2030
and 46 Mtoe in 2050 which corresponds to roughly half of the savings deriving
from technical improvements. Putting the potentials into relation with the PRIMES
2009 and the “Ambitious RES” baseline (PRIMES 2009 baseline less the savings
from a more efficient energy conversion process of primary into final energy) leads
to relative reductions of 10% and 11 % in 2030 as well as 12 % and 15 % in 2050.
In terms of emission reductions, behavioural changes can potentially contribute
126 Mt CO2-eq in 2030 and 141 Mt CO2-eq in 2050. The relative reduction compared to the baseline pathways is slightly higher for the years 2030 and 2050: 11
% and 14 % with regard to the PRIMES 2009 baseline as well as 12 % and 17 %
with regard to the “Ambitious RES” baseline (cf. Figure 4-72).
Transport (road)
Figure 4-72:
137
Behavioural changes
GHG emission reduction from behavioural changes compared to the
calculated emissions from the PRIMES 2009 baseline energy demand for the transport sector
General information
Passenger as well as goods traffic have increased by more than 40 % and 70
%, respectively, over the last two decades. At the same time final energy demand
increased by only 30 % which might be linked to the registered 12 % decrease in
specific fuel demand per person kilometre, or ton-kilometre, respectively. This improvement is not necessarily due to technological progress, but could be related to
changes in driving behaviour, too. However, statistics verify that the average load
of passenger cars has been steadily decreasing since 1994 (by 10 % until
2008) resulting from a significant increase in the passenger car stock instead of
a declining car use.
This factsheet addresses solely behavioural changes, fuel saving driving patterns
and optimization of load factors and transportation needs. All the information regarding technological improvements and alternative drives is collected in the respective factsheets.
Transport (road)
Figure 4-73:
Behavioural changes
138
Total passenger and goods traffic and their specific consumption in
the EU27
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
Figure 4-74:
Specific vehicle load of passenger cars and goods traffic
Driving behaviour information
In order to identify the main factors determining fuel demand in the transport sector, the following aspects need to be considered:
•
specific consumption of the car per kilometre,
•
the specific car load (in terms of persons or tons of goods transported by
one vehicle),
•
the total number of persons and tons of goods transported and
•
the distance covered.
The last three points are related to the actual need for driving. Optimizing one of
them can be directly translated as a reduction in vehicle use, whereas the first point
is related to the car’s technical efficiency and how it is used. In this factsheet, all
Transport (road)
139
Behavioural changes
four issues are addressed by so-called behaviour influencing measures that are
partly based on the introduction of additional technologies.
The following section first deals with the possibilities and technologies to reduce
the demand for car transportation. Afterwards the focus shifts to energy-efficient
driving patterns (eco-driving).
Behavioural changes and efficiency technologies
Most of the efficiency gains due to behavioural changes could theoretically be implemented in the short run, since they do not necessarily need the assisting technology. However, despite the economic advantage that is often linked to these
changes, incentives need to be established first to raise public awareness of them.
Distinguished by the type of efficiency, potential behavioural changes and the assisting technologies are described in the following (Leonardi, 2004), (Kobayashi,
2009), (TNO, 2006), (TNO, 2009):
Logistics and route efficiency
•
The vehicle load factor for passenger cars can be increased by simply forming groups to share the same car for a trip, whereas in the field of freight
transport, trip optimisation software and IT-based scheduling is used to
plan and schedule the routes for trucks and vehicles. Such software minimises empty trips, optimises the choice of vehicle category and helps to optimise the entire transportation chain from origins to delivery. Moreover, a
holistic approach to managing numerous transport units of a company allows substantial minimization of the average transport distance.
•
Additionally, using information and communication technologies (ICT)
can supply the car driver with additional information regarding road conditions or traffic which can help to optimise the itinerary.
•
Infrastructure improvements and intelligent transport technologies (e.g.
better routing systems, mainly in urban areas) reduce congestion, increase
the average speed and thereby decrease the specific fuel consumption.
Eco-driving
•
Fuel consumption can be decreased by up to 10 % with training or assistance from on-board units used for measuring specific components of driving behaviour.
•
Running the engine in its most efficient operating range, i.e. where fuel
efficiency is highest (between 1200 and 3000 rotations per minute (rpm)),
permits significant fuel savings. This can be done by shifting gear earlier
(2000 to 2500 rpm), avoiding unnecessary (too strong) accelerations, high
Transport (road)
140
Behavioural changes
speeds and keeping the speed as steady as possible. Gear shift indicators inform the driver when the engine is running under unfavourable conditions. Driver assistance systems, such as automated manual transmission, decide for the driver when shifting gear is appropriate without affecting the driving itself, only the efficiency.
•
Keeping the car rolling without disengaging the clutch in the highest gear
possible or avoiding unnecessary braking avoids fuel wastage but requires that the driver can anticipate upcoming traffic situations.
•
Regular checks of tyre pressure, avoiding vehicle idling, e.g. by turning the
engine off when the vehicle is stationary, or even avoiding the use of air
conditioning can add substantial fuel savings without any need for new
technologies.
Measures taken into account in analysing non-technical potentials in the transport
sector (where this type of potentials are most relevant at present) are in particular,
eco-driving strategies for passenger transport, as well as speed reduction for
freight transport and the increase in the freight load factors.
For eco-driving strategies the technical potentials were linked to the maximum performance that could be achieved on average in typical eco-driving tests and programmes (around 10 % of the energy could be saved) and it was assumed that the
changes in behaviour would be permanent. Similar from load management studies
it was deduced that a maximum of 3 % of freight energy could be saved through
improved load management. Thirdly, the impact of reduced speed for freight traffic
was deduced from energy consumption studies of truck manufacturers.
Between technical improvements and behavioural energy saving potentials interactions were considered, i.e. for example when cars get more efficient from a technical point of view, less savings are achievable through behavioural changes.
Transport (road)
4.2.12
141
e-Mobility
Transport – e-Mobility
Energy saving potentials on EU level
The diffusion of electric, grid-connected car drive concepts, i.e. battery electric
vehicles (BEV) and plug-in hybrid vehicles (PHEV) can drive additional final
energy savings. However the comparison of electric and conventional vehicles
(equipped with an internal combustion engine) neglects the fact that electricity and
fossil fuels are two very different energy carriers 41. Moreover one should note that
all kind of electric vehicles are still considered as niche applications. Thus it is difficult to forecast to which extend they will actually prevail against competing technologies (such as hydrogen, biofuel or gas fuelled cars) and diffuse into the market.
Figure 4-75:
Energy savings through e-Mobility in two scenarios, compared to the
final energy demand of passenger road transport
energy saving potentials: Fraunhofer ISI
41 Electricity is a highly valuable energy carrier that is mainly produced with significant losses (if not
generated from renewable energy sources) whereas its conversion efficiency into other energy
types is particularly high. Instead, fossil fuels (such as gasoline or diesel) are produced in refineries with rather low losses (less than 10 %), whereas the conversion into mechanical energy
causes the bulk of losses (more than 50 %).
Transport (road)
142
e-Mobility
In the present analysis, two diffusion scenarios are analysed. Their results are
nevertheless are strongly sensitive on the various assumptions and simplifications 42. More detailed information can be found in Annex III.
The energy saving potential estimation carried out does only consider passenger
cars since the application of electric drives in light duty vehicles and trucks is still
uncertain and strongly depends on the further evolution of battery technology.
Figure 4-75 gives an overview of the energy saving potentials under the two scenarios analysed. The Moderate scenario presumes a relevant stock increase of
electric vehicles (BEV and PHEV at the same pace) from 2025 onwards, leading to
a 30% share of electric vehicles by 2050 (cf. Figure 4-76), as expected in (EWI,
2010). This is equivalent to roughly 80 million electric cars, considering an overall
car stock of 280 million passenger cars, cf. (ISI, 2009c).
The associated energy savings, based on specific fuel consumptions that are explained in more detail in the subsequent sections, mount up to 1 Mtoe by 2030 and
16 Mtoe by 2050. Related primary energy savings mount up to comparable values.
Figure 4-76:
Stock of electric vehicles in the Moderate and the Ambitious scenario, EU27
The Moderate scenario was completed by a second, more ambitious scenario
(called “Ambitious scenario”) that is partially based on the projection from (ISI,
2008) The projection presumes an early growth of PHEV stock from 2020 onwards
whereas BEV will only experience their large-scale market introduction by 2030. In
42 Hence, the final energy saving potential which is mentioned in the following and completed by a
primary energy savings assessment is addressed separately from the overall saving potentials
calculated in the transport sector and excluded from the assessment of the overall saving potentials.
Transport (road)
e-Mobility
143
2050, two cars out of three on Europe’s streets are either a PHEV or BEV, i.e. 190
million electric cars in total. Consequently, the final energy saving potential could
be increased up to 4 Mtoe in 2030 and 36 Mtoe in 2050.
A cost-benefit-analysis was not carried out for e-Mobility since an independent
study would be required in order to account for the complexity of this topic.
General information
Electricity used in electric vehicles or plug-in hybrids is supposed to play an increasingly important role not only in meeting transport fuel demand in the future.
They can also help mitigating problems over the fluctuating nature of some renewable energy sources (such as wind power and photovoltaics) by providing their
battery capacity for short term electricity storage during peak RES power production.
According to the latest IEA Technology Roadmap (IEA, 2011a) from June 2011, eMobility has already arrived on the political agenda. In the last 12 months, various
EV and PHEV sales targets existing were formulated on national level (cf. Table
4-9.
Table 4-9:
Overview of different national electric vehicle sales targets within the
EU27
Country
Electric vehicles
Plug-in hybrids
France
2,000,000 by 2020
Germany
1,000,000 by 2020
Spain
2,500,000 by 2020
1,200,000 stock by 2020
350,000 stock by 2020
3,300,000 stock by 2030
7,900,000 stock by 2030
United Kingdom
Source: (IEA, 2011a)
Although the majority of the current car fleet uses a gasoline or diesel fuelled internal combustion engine (ICE), there are alternative fuel and drive concepts.
Alternative fuels for running on a combustion engine
Minor technical changes of the ICE technology permit natural gas (CNG), petroleum gas (LPG) or hydrogen combustion. CNG/LPG cars provide a higher efficiency if they are designed for only one fuel. This is due to the higher antiknock
properties of the gas that allow higher compression and thus increase the effi-
Transport (road)
144
e-Mobility
ciency, whereas the combined use of gas and gasoline results in a reduced efficiency (Pehnt, 2011).
Hydrogen (H2) has a very high mass related energy density and features a particularly efficient combustion process. However, the storage of hydrogen in cars
requires high pressures or very low temperatures in order to enable sufficient
amount of hydrogen stored in the tank. Otherwise a comparable cruising range of
hydrogen fuelled cars with conventionally fuelled ICE cars is not given. The leakage of the hydrogen fuel tank represents another serious issue that needs to be
addressed in future research.
Biofuels represent another alternative fuel type that does not require significant
modifications of the conventional ICE.
To which extent these fuels drive additional energy savings, cannot be assessed
within the framework of this study.
Alternative drive concepts
The main focus in this factsheet is set on cars using electric drive concepts. The
electric drive is either powered by electricity delivered by the battery stack or by
electricity delivered by a fuel cell system. In the latter case, the energy as such is
stored in the form of hydrogen. Consequently, we distinguish four different types of
electric-powered cars (ISI, 2010):
•
Hybrid electric vehicles (HEV) combine a conventional ICE with an electric motor. In addition to the fuel tank a battery package is installed in order
to store the electric energy delivered by the electric motor. In parallel HEVs
the electric motor and the engine can provide the drive torque independently from each other, whereas in series HEVs the car is driven by the electric motor and the electric energy is delivered by the ICE-generator system
via the battery.
•
Plug-in-hybrid vehicles (PHEV) are HEV that are additionally equipped
with a power connection enabling battery charging by the motor as well as
by the power grid.
•
Battery-electric vehicles (BEV) are comparable to a PHEV but without the
conventional thermal engine concept. They are solely driven by the electric
motor and need to be charged by an external electric source, i.e. the power
grid.
•
Fuel cell electric vehicles (FCEV) are comparable to a BEV but the bulk
of energy is saved in the form of hydrogen which is transformed into electricity by means of a fuel cell. The hydrogen supply is provided by a public
Transport (road)
145
e-Mobility
supply grid. A reconversion of electricity into hydrogen inside the car is not
envisaged. The FCEV concept will not be further analysed within the
framework of this report since the main focus is set on battery HEVs and
BEVs.
Figure 4-77:
Overview of hybrid and electric drive train concepts
Source: (MIT, 2008), Fraunhofer ISI
Energy saving technologies
In a first step, the simple shift from conventional towards electric vehicles represents an energy saving option whose saving potentials are shown in Figure 4-75.
However, the fact that the drive concepts mentioned above include an electric motor allows for the following additional final energy saving options to be applied
(Pehnt, 2011):
•
Recuperation of the kinetic energy that is transformed into electric energy
during braking processes. Primarily in urban areas the characteristic stopand-go traffic offers significant energy saving potentials.
•
Intelligent demand management enables a better balancing of ICE and
electric drive mode. Since conventional ICEs reach their optimal operation
point only at higher load ranges, the starting torque is delivered by the electric motor until battery load reaches a critical level or until a high power demand occurs.
•
Downsizing of the ICE to a lower power range with lower power consumption due to the electric motor assistance implies that the ICE reaches faster
Transport (road)
146
e-Mobility
the optimal operation point. Consequently, the entire hybrid drive concept is
optimised with regard to efficiency aspects.
However, the extension of a conventional car by an electric motor system results
simultaneously in a number of disadvantages which can potentially compensate
the energy savings. A main handicap is the increase in vehicle weight which might
lead in extra urban areas to an overcompensation of the savings and a net overconsumption. Thus the efficiency gain of HEVs is strongly correlated with the purpose and the usage profile. (Hybrids and EVs are more efficient in low speed and
start/stop modes, where ICEs operate in an unfavourable combustion mode.)
The energy saving potential of alternative drive concepts cannot be determined by
simply assessing the final energy savings of the respective technologies compared
to conventional ICE technology. This would be equivalent to a tank-to-wheel analysis (cf. Figure 4-78) which focuses only on the energy conversion efficiency of the
final energy carrier that is stored in the tank/battery (i.e. gasoline, diesel, electricity
or hydrogen). Thus, the analysis would result in a clear argument in favour of electric motors which feature efficiencies of roughly 84 % compared to some 30 % of
conventional combustion engines or fuel-cell-electric-motor-systems.
Instead the whole supply chain, including the processing efficiencies necessary for
the production of the respective fuel types (i.e. refineries for the gasoline and diesel
production, conventional and renewable power generation units for the provision of
electricity, electrolysis or steam reforming for the production of hydrogen) needs to
be included in order to carry out a comparable well-to-wheel-analysis.
Figure 4-78:
Boundaries of the energy balance
Source: (DGES, 2011)
147
4.3
Technical energy saving potentials of “estimated
wedges”
In order to get a holistic overview of the technical energy saving potentials in the
different sectors, this section shortly summarizes efficiency technologies and saving potentials that were not addressed in detail within the framework of the factsheets.
The results of the classification of the technical potentials deriving from the “estimated wedges” into cost-efficient and non-cost-efficient technologies are not
shown in this paragraph for reasons of comprehension and straightforwardness.
However, they are implicitly included in the sectoral cost curve-approach that is
carried out in section 4.4.1.
Household sector
In the households sector, the majority of energy saving potentials has already been
addressed in the framework of the respective factsheets. The missing energy consumer is heat generation for sanitary hot water. The share of sanitary hot water
heating compared to other building related measures is relatively low, accounting
for less than 7 % of the total energy saving potential in the household sector. However, it is more important than the potentials from household appliances or efficient
lighting (accounting for 6 % and 5 % respectively).
Energy savings in hot water supply can be realised through coupling with the district heating or the local heating system, the further diffusion of energy efficient
boilers (condensing heating technologies, electric instantaneous water heaters) or
heat pumps. The energy saving potential achievable by energy efficient hot water
generation is comparable to the potential of electric appliances, mounting up to 12
Mtoe or 4 % (compared to the PRIMES 2009 baseline).
Tertiary sector
The factsheet collection already mentioned energy saving technologies for the tertiary sector, resulting from building related improvements (building envelope, heating and cooling systems), as well as from lighting and Green ICT. While the cooling
section addressed solely centralised air-conditioning systems, further gains are
included in commercial refrigeration and freezing as well as in fans which were
separately analysed in ISI (2009a). Another aspect is the improvement of other
motor appliances than the ones, used in fans and air-conditioning systems. The
148
entirety of those additional appliances accounts for nearly 40 % of all electricity
consumption in the tertiary sector (cf. Figure 4-79).
Figure 4-79:
Shares of tertiary electricity consumption by appliance, EU27, 2004
•
Commercial refrigeration and freezing comprises all kind of cooling appliances used in supermarkets, restaurants, hotels or cafés. Energy efficiency measures include electronically commutated motors (ECM) evaporator fans, addition of a glass door/lid for open cases, improved insulation
by using argon instead of air in glass doors, high efficient lighting and increased heat exchanger surface. The total saving potential equals 2 Mtoe
in 2030, which is equivalent to a 1 % reduction compared to the baseline
(BIOIS, 2007).
•
Ventilation is one of the most energy consuming appliances in the EU, being responsible for about 17 % of all electricity consumption in the tertiary
sector. In accordance with Radgen (2007) and ISI (2009a) only considers
fans above 125 W in order to exclude residential fans and fans for appliances, such as computers. The fan as main ventilation system can be subdivided in three main components: the motor, the transmission and the fan
itself. Consequently, efficiency measures can address all of these components, such as an improved aerodynamic profile of the fan (increased efficiency from 40 % up to 88 %), V-belt transmission or improved induction
motors. Hence, total energy savings of up to 3 Mtoe (equals a 2 % reduction compared to the baseline) can be obtained by 2030 (ISI, 2009a),
(Radgen, 2007).
149
•
Even though the most significant electric motor appliances were already
mentioned (i.e. fans), numerous other motor appliances do exist (e.g. lifts,
conveyors, pumps, compressed air systems) and represent a non-negligible
saving potential. According to (Bertoldi, 2006), miscellaneous motor appliances with a rated power below 10 kW are responsible for 10 % of all electricity consumption in the tertiary sector. Energy savings can be realised
through the use of high efficiency motors (such as IE2 or even better, cf.
factsheet about electric drives), variable speed drives, improved demand
related control systems (cf. factsheet about e-drive system optimisation), direct coupling of motor and application instead of V-belt and avoidance of
oversizing. Since electric motors feature already high efficiencies, the related energy saving potential equals to roughly one Mtoe, which is even
less than 1 % compared to the baseline.
Figure 4-80:
Energy saving potentials of the estimated wedges in the tertiary sector, EU27, until 2050
Summarising all the potentials mentioned above, the total energy saving potential
through efficient commercial refrigerators and freezers as well as fans and other
motor appliances sums up to 6.6 Mtoe in 2030 and to 9.3 Mtoe in 2050. Compared
to the 64 Mtoe / 81 Mtoe potential resulting from the calculated wedges, this potential is relatively low, verifying a good representation of the saving potentials through
150
the calculated wedges. Figure 4-80 gives an overview of the temporary development of the saving potentials over the next four decades.
Industry sector
Apart from the energy savings potentials identified in the paper and pulp industry
and the different cross-cutting technologies mentioned in the respective factsheets
(cf. section 4.1.4) additional potentials are included in the process technologies of
the iron and steel, non-ferrous metals, chemicals and non-metallic minerals industry. Following this order, they are shortly explained in this section.
Figure 4-81 gives an overview of the individual shares of final energy demand in
the different industrial sub-sectors. The iron and steel industry as well as the
chemical industry are the main energy consuming sub-sectors in the European
industry.
Figure 4-81:
Final energy demand in the industry sector in EU27 (historical and
forecast)
Source: 1990-2008: (Odyssee, 2011); 2009: average value; 2010-2030: (European
Commission, 2010)
In order to get an impression of the significance of the process technologies and
their energy saving potentials in the various sectors, Figure 4-82 depicts the share
of cross-cutting and process technologies within the sectors. Electricity demand in
the non-metallic minerals industry (such as glass, ceramics and cement) results
mainly from cross-cutting technologies. The associated saving potentials were already covered in the factsheets whereas the metallic minerals industry is strongly
dominated by process specific technologies.
151
Figure 4-82:
Share of cross-cutting technologies in by sector
•
The iron and steel industry is the most energy consuming industry in
Europe, amounting for about 20 % of the total industrial final energy demand and more than 5 % of the total European energy consumption (Odyssee, 2011). In this industry branch two types of production processes need
to be distinguished. The blast furnace route is manufacturing pig iron and
crude steel based on the raw materials iron ore, coke and coal. It is very
energy consuming, requiring about 0.29 – 0.36 toe/t of pig iron and 0.43 –
0.48 toe/t of crude steel (IISI, 1998). Alternatively, the electric arc furnace
(EAC) is using recycled scrap thereby skipping the energy intensive process of ore reduction and thus requiring only 0.07 – 0.12 toe/t of crude steel.
The strip casting process promises the most significant energy savings.
Instead of re-heating the steel for final shaping, a continuous near net
shape casting is attached to the steel production process, reducing the
specific energy demand by 75 % down to 0.002 toe/t of steel. Further improvements can be deduced from heat recovery from steel rolling and
the use of top gas from blast furnace (ISI, 2011a).
•
Among non-ferrous metals aluminium production is responsible for more
than 50 % of the total energy demand. Primary aluminium production
consists of bauxite (a type of aluminium ore) mining, production of alumina
(aluminium oxide) from bauxite, extraction of the aluminium through elec-
152
trolysis and final rolling. The production of primary aluminium requires about
1.3 toe/t of aluminium whereas the use of recycled aluminium reduces the
energy demand to approximately 5% (IEA, 2007).
Energy savings can be triggered through the implementation of so so-called
PFPB (Point Feeder Pre-Baked) electrodes and improved operation of
the furnaces as well as of the entire process (ISI, 2011a). In the long run
the integration of superconductive inductive magnet heating promises
savings from up to 50% compared to conventional fuel driven heating and
melting processes (Bührer, 2009).
•
The chemical industry is the second largest energy consumer of the
European manufacturing industry, accounting for 57 Mtoe final energy demand in 2007. According to the PRIMES 2009 forecast, chemical industry is
supposed to experience a further increase within the next 20 years, thus
even exceeding the iron and steel industry (European Commission, 2010).
The chemical industry is characterised by a significant heterogeneity, featuring numerous types of processes applied. Consequently the identification
of energy saving technologies comprises a whole range of process related
measures. However, they can be traced back to a few fundamental principles, such as the application of more efficient catalysts, increased heat
integration, the implementation of more energy efficient separation units,
the use of more efficient heat pumps and compressors and the adoption of
advanced process automation (ISI, 2011a). The bulk of energy savings in
the chemical industry can be tracked in the sectors of refineries mainly
linked to partition wall columns (ISI, 2009a).
•
In this study the production of non-metallic minerals comprises glass and
cement products, accounting for nearly 14 % of the industrial energy consumption.
Cement production is one of the major energy consuming industry
branches in the European Union. A mixture of limestone, clay and sand is
pre-treated (refining and mixing) for further processing in the furnace where
the bulk of energy is needed. The temperature increase implies chemical
reactions that transform the raw material into pellets, called clinker. By adding gypsum, cement is attained. The global average energy intensity ranges
between 0.07 and 0.11 toe/t of cement (IEA, 2007). Due to the high energy
intensity of cement production various energy efficiency savings have already been exploited in the past (such as waste heat recovery). Further
savings might be related to the coupling of waste heat recovery and electricity generation (e.g. through the Organic-Rankine-Cycle, ORC) or the
153
substitution of limestone through alternative materials that require less
process energy.
There are different types of glass products, however the individual processes all include the following steps: selection of raw material (silica sand,
soda ash, limestone), batch preparation (weighing and mixing of the raw
materials), melting (most energy consuming process step) and refining,
conditioning and forming and post-processing (IEA, 2007). Increased efficiency focus mainly on the actual melting process by using oxygen as a
substitute for the combustion air in the furnace and waste heat recovery
from the exhaust gas, used to preheat to the combustion air.
•
Other industry branches, such as machinery construction, textile as well
as food, drink and tobacco industry feature additional saving potentials that
were not analysed in detail due to their relatively low significance. However,
a rough estimation of the saving potential accounts for 12 Mtoe by 2030.
Although originally foreseen, saving potentials deriving from surface technologies
are not addressed in an individual analysis since they are partly included in the
factsheets dealing with technical improvements in the transport sector as well as in
the potentials of other industry branches.
The total energy saving potential for all industrial process technologies mounts up
to 18 Mtoe in 2030 and up to 40 Mtoe in 2050. This is comparable to a 5 % / 11 %
reduction relative to the baseline scenario. Compared to the overall saving potential of calculated and estimated wedges, the estimated industrial wedges represent
approximately 21 %.
154
Figure 4-83:
Energy savings through process technologies in the industry sector
(only estimated wedges), EU27, until 2050
Transport sector
While the factsheets, addressing the transport sector, focus on technical improvements in road transport (i.e. passenger cars and freight transport as well as motorcycles and public road transport) and energy savings through behavioural changes
(such as “eco-driving”), the objective of this section consists of the potential determination through modal shift and efficiency improvements in rail transport and aviation.
•
Modal shift is defined as covering distances, which would have been travelled anyway, with less energy intensive transport modes. In practice, many
existing policies aim at both shifting towards “more sustainable” transport
modes and avoiding trips. In the present case only the first aim is targeted,
while the latter is already partly addressed in the factsheet dealing with behavioural changes.
In urban transport, the bulk of energy savings is gained through a shift from
individual motorised transport to public transport and bicycles. Interurban
freight transport provides energy saving potentials through shifting from
155
road transport to more efficient rail transport and shipping. Interurban passenger transport promises high energy savings by a shift from aviation and
road transport to rail and public transport (such as long distance busses)
(IEA, 2010b).
The total energy saving potential through modal shift in passenger transport
mounts up to 14 Mtoe by 2030, compared to 5 Mtoe resulting from freight
transport modal shift. These potentials can be translated by a 4 % and 1 %,
reduction compared to the PRIMES 2009 baseline (ISI, 2009a).
•
Apart from energy savings through a general road-to railway-shift, further
savings can be obtained by increased efficiency of rail transport, e.g.
through more efficient engines and an improved railway infrastructure permitting enhanced driving route optimisation. However, there is a trade-off
between increased speed and more efficient engines and rolling infrastructure that may diminish the available potential. Hence, the total potential in
rail transport is limited to 2 Mtoe in 2030, which is just 0.5 % of the baseline
energy consumption in the transport sector.
•
A comparatively higher potential is deducible from technical and operational
improvements in the aviation sector. Lightweight plane construction, optimised aerodynamics and more efficient propulsion units (such as open rotors or turbofans) decrease the plane’s fuel intensity. Operational measures
such as optimised plane load factor, reduced travel weight (e.g. through distance dependent refuelling) and air traffic management (ATM, includes for
example flight path optimisation, flight time reduction) increase fuel efficiency. The aviation related energy saving potential mounts up to 19 Mtoe
by 2030.
The entirety of energy saving measures in the transport sector covered by the estimated wedge yield some 40 Mtoe by 2030 and 47 Mtoe by 2050 which corresponds to 11 % and 14 % respectively of the total final energy demand in the
baseline scenario. Roughly half of the potential is covered by modal shift in passenger and freight transport, whereas nearly the other half is represented by savings in air traffic. Rail transport plays only a minor part.
Comparing the saving potential of the estimated wedge with the overall potential in
the transport sector, a coverage of roughly 26 % through estimated wedges can be
reported.
156
Figure 4-84:
Energy savings through estimated wedges in the transport sector,
EU27, until 2050
Energy conversion
The assessment of saving potentials in the field of energy conversion and transport
differs from the branches analysed before, since efficiency improvements applied
in this field are not related to the demand side but rather to the supply side. Hence,
the energy efficiency measures shown in the following have a rather representative
significance. They are not included in the summation of the energy saving potentials of calculated and estimated wedges.
Electricity generation costs are strongly correlating with the price of the primary
energy carrier as well as with the conversion efficiency of the power plant. Thus it
is obvious that any new fossil power plant in the EU is built according to best
available technology (BAT) standards. This trend is also included in the PRIMES
baseline assumptions 43 and depicted in Figure 4-85.
43 The PRIMES projections do also forecast a further diffusion of combined heat and power generation. Large scale deployment of CCS is only expected after 2020.
157
Figure 4-85:
Average power plant efficiency of fossil fuelled power plants, EU27
Source: (Graus, 2009)
Though a certain potential exists to improve the efficiency of existing fossil fuelled power plants, such potential should be assessed in a context of continued
stock turnover and decarbonisation of the power sector. Based on current age distribution of power plants, it is expected that by 2030 only 30% of the current stock
of fossil power production plants in the EU-27 is still in production; this could resemble around 900 TWh. Retrofitted energy efficiency measures that improve the
control of power plants could increase their efficiency with 1 - 2 %. Such measures
would save a maximum of 4.4 Mtoe energy inputs to the power generation,
assuming 35 % average efficiency for the existing plants. This number is indeed
very small compared to the overall economy wide savings potential identified in this
study. Moreover, the 4.4 Mtoe of savings could partly be offset by increased use of
CCS in the case of new fossil power plants (ECF, 2010b).
In summary, we considered no substantial additional energy savings beyond business as usual for the fossil fuelled power generation sector, for both existing and
new fossil fuelled power plants.
Energy transmission and distribution
Electricity transport involves grid losses due to the fact that the voltage decreases
with increasing power line length as a result of the ohmic resistance. Part of the
electric energy is transformed into heat and dissipated to the environment. This
heat loss correlates with the length of the power line and the squared amperage.
Consequently, an increase in voltage results in a decrease in amperage and thus
in a lower grid loss. This is also the reason why long-distance power transmission
158
in Europe is realised on a very high tension level of up to 380 kV (compared to the
0.2 kV domestic power connections) (Konstantin, 2009). For the distribution of
electricity in load centres, the tension needs to be transformed to a lower level in
order to comply with the individual standards of private or industrial consumer.
Hence, there are different tension levels for different purposes:
•
extra-high tension above 220 kV for long distance power transmission,
•
medium to high tension, ranging between 10 and 110 kV, for the supply of
energy intensive industry and the distribution of electricity to regional load
centres,
•
low tension of up to 0.4 kV for the supply of households and medium and
small enterprises.
Every transformation from one voltage level to another is accompanied by additional energy losses due to a partial transformation of the electric energy into heat.
As mentioned before, the transmission and distribution losses are related to the
tension level of the power line. Hence, losses in distribution grids are up to 5 times
higher than in transmission grids (assuming moderate long distance power lines,
as they typically occur in Europe), as can be seen in Table 4-10.
Table 4-10: Transmission losses (typical values) published by the Swedish grid
operator "Svenska Kraftnät"
Source: (KFB, 2000)
Transmission power line technology is dominated by alternating current (AC)
systems. Moreover, most of the lines are overhead lines, which are preferentially
installed due to the higher costs of underground cable lines (three to four times
higher investment costs) despite significantly lower losses of up to 50 % (Oswald,
2007). However, there is a remarkable shift towards cable lines resulting from a
lower impact on the natural scenery and thus a higher public acceptance.
159
According to the IEA, transmission losses in the European Union in 2008
summed up to approximately 6 % of the gross electricity generation (IEA,
2011). An exemplary 380 kV overhead line features a 360 kW loss per km (at a
2000 A current), which is equal to 260 GWh loss for a 60 km line during one year
(NStK, 2007). Generally speaking, losses in AC lines directly correlate with the
length of a line, i.e. the longer it is the lower is the output at the end of the line.
Hence, there is an important need for efficiency improvements which can potentially be realised by the following efficiency technologies (NStK, 2007), (ABB,
2007), (Greenpeace, 2010b):
•
Gas-insulated transmission lines (GIL) are similar to a pipeline, composed of an AC conducting medium and a surrounding gas mixture as insulation medium (80 % nitrogen, 20 % SF6). Every system consists of single
units of three pipelines (approx. 50 cm diameter) of a length between 11
and 14 m that are weld together. The transmission loss is up to 65 %
lower than in over head AC lines (roughly 130 kW per kilometre) while the
investment costs are about seven times higher. This type of power line was
invented by SIEMENS and it is already commercially available.
•
High voltage direct current (HVDC) systems have about 50 % lower
losses than AC lines, which is equal to 2 - 3 % of the transmitted power –
independently from the line length. However, power plants usually generate
alternating current (AC). Thus a rectifier needs to transform the electricity
into DC and after transmission an inverter has to transform it back to AC,
which implies additional energy losses. Hence, HVDC lines are only suitable for long distances (more than 600 km) where the transformer losses
are overcompensated by the gains through higher transmission efficiency,
or for submarine cables of more than 30 km length, connecting two continents or off-shore wind parks with the power grid. Since European power
plants are located close to the load centres, there is no significant potential
for this technology yet. Only in a long term view, this technology might become more important in view of a pan-European super grid, connecting
generation units in Northern Africa, Turkey or the Scandinavian countries
directly to the Central European grid.
•
But the Swiss company ABB has developed a new type of HVDC lines,
called HVDC light which is also applicable for short distances. These lines
are underground or submarine cable lines that suitable for distance of more
than 150 km. Up to now the voltage level is relatively low, thus further R&D
is necessary in order to increase the transmission capacity and the energy
savings which are currently in the order of magnitude of 5 %.
160
•
High-temperature superconducting cables (HTS) have the ability to conduct electricity with near-zero-resistance, thus featuring losses of only half
a percent of the transmitted power. Since they can only operate below a
characteristic temperature (near liquid nitrogen temperature) further R&D is
necessary in order to reduce the energy demand for cooling. Moreover they
can carry three to five time the power of conventional cables.
Since the transmission and distribution losses are not only linked to the amount of
power transmitted but also on the future expansion and design of the European
electricity grid, it is extremely difficult to estimate the overall saving potential related
to avoided grid losses. Only a detailed and holistic scenario analysis can deliver
electricity generation capacity figures, the type of energy source used (renewable
or conventional energy sources), the individual geographical location of supply and
load centres and the resulting grid structure. Such a complex analysis cannot be
carried out in the framework of this study 44.
Hence, only a rough estimation of how much of today’s energy losses could potentially be avoided is delivered. Summarizing the findings of the technology overview
leads to the conclusion that roughly half of the losses currently occurring in AC
lines could be halved by the integration of new AC and DC distribution and transmission technologies. Based on the IEA statistics that in 2008 the electricity losses
mounted up to 206 TWh (or 6 % of the gross production), the energy saving potential thus accounts for some 100 TWh or 9 Mtoe of final energy demand. A
detailed timeline of the availability of the potential cannot be developed due to lacking data regarding grid refurbishment cycles.
Due to the fact that the energy savings outlined earlier in the factsheet and in the
estimated wedges section are compared to the net final energy demand (not including self consumption of energy conversion units and transmission losses), the
saving potentials from reduced grid losses are not comprised in the summation
carried out within the next sections.
44 A complete analysis was carried out by the German company Energynautics, for example. After
the initial of an entire energy supply scenario, commissioned by Greenpeace, the necessary grid
infrastructure and the subsequent grid losses were estimated (Energynautics, 2011). The result
was a reduction of grid losses from 6 % in 2008 to 5 % in 2030 and 2050, respectively despite a
significant grid extension due to a 100 % RES power supply.
161
4.4
Overview of technical and economic energy saving
and emission reduction potentials
This section aims on merging the information of the two previous chapters on a
higher aggregated level. In 4.4.1 the data from calculated and estimated wedges is
summarized on sectoral level, pointing out the most promising efficiency measures
with regard to the size of the potential, its cost-effectiveness and their contribution
to primary energy demand reduction and GHG emission mitigation.
In 4.4.2, we step one aggregation level further up, bringing together the national
sectoral potential results for a number of specific countries. The overall assembly
of the sectoral potentials on the EU27 level is described in chapter 5.
4.4.1
EU-wide saving potentials on sectoral level
Based on the in-depth analysis of the calculated and estimated wedges, an evaluation of the identified saving potentials shall be drawn on a sectoral level. Until 2030,
a detailed technology specific depiction allows identifying the main energy saving
measures, summarizing the data from the factsheets as well as from section 4.3
(all based on (ISI, 2009a)).
For the time horizon between 2030 and 2050, a further general outlook on the energy saving potentials is given. Due to increasing uncertainty in the long term view,
the displayed potentials can hardly be allocated to specific technologies. However
the share of the technology potentials in the year 2030 is kept constant over the
following 20 years in order to get a rough idea about the significance of the single
technologies. The potential data for the time between 2030 and 2050 is based on
the ADAM report (ISI, 2009c). For comparison purposes, the PRIMES 2009 baseline was extrapolated for the time beyond 2030, using the scaled development of
the ADAM reference scenario. This approach enables the consideration of the
economic crisis.
Even though the results of cost-benefit-analysis for measures from the estimated
wedges group were not reported in detail in section 4.3, they are now included in
the overall sectoral cost curves in order to give a complete overview.
Household sector
As shown Figure 4-86, adding up all final energy saving potentials leads to a 61 %
decrease by 2030 compared to the PRIMES baseline, lowering the final energy
demand to 120 Mtoe. Until 2050, the slight decrease of FED in the baseline sce-
162
nario continues, reaching 290 Mtoe due to autonomous diffusion of efficiency technologies and slightly declining population numbers (cf. (ISI, 2009b)). The main energy savings are achievable through further efficiency improvements in the building
shell as well as in heating systems and appliances. Moreover the specific energy
demand of appliances is reduced to a minimum level. Thus, the energy demand
declines to 82 Mtoe by 2050. This is comparable to a 71 % final energy demand
reduction, equal to 207 Mtoe. However, there is a clear trend break in the year
2030. On the one hand side, this break can be explained with an increased share
of efficient and refurbished dwellings featuring a reduced saving potential. On the
other hand side it needs to be pointed out that given the fact that the potential trajectory is based on two different studies (see also the methodology section 4.1),
the scenario-specific trends do not necessarily fully match. Presuming an entirely
consistent scenario approach would lead to a distinct s-shaped development of the
potential curve that is gradually approaching a certain saturation level.
Figure 4-86:
Total final energy saving potentials in the EU27 until 2050 in the
household sector
Regarding the time-scale of the potential development, the most significant cuts
can be obtained within the next two decades (2007-2030: -187 Mtoe / -57 % final
163
energy decrease), while in the long run it is more difficult to exploit further saving
potentials (2030-2050: -39 Mtoe or -14 % relative to the pre-crisis value of 2007).
Figure 4-87:
Cost curve for the household sector, EU27
Figure 4-87 illustrates very well, that the bulk of energy related cost reductions derives from efficiency improvements in the buildings sector (i.e. building shell and
heating system, that contain the measures mentioned earlier in the fact sheets
which results in more than three blocks of every option within the cost curve).
Among the economic potentials, electric appliances and lighting are clearly the
most attractive energy saving option regarding the specific cost reduction per unit
of energy saved. However, their contribution to the overall cost benefit is extremely
small compared to the benefits through building related measures: €4 billion versus
€26 billion by 2020.
The net benefits that take into account additional financial efforts for the realisation of the immature fruits (partially building related measures as well as BAT electric appliances) account for €25 billion in 2020 and more than €120 billion by
2050. The extraordinarily high cost reduction by 2050 is basically triggered by increasing fuel prices that make the additional investments worthwhile.
Based on these results it is obvious that the majority of the potentials can be activated through measures that focus on non-financial barriers. Only one fifth of the
overall potential in 2020 requires additional financial aids to lift the saving options
on a cost-effective level.
164
Figure 4-88:
Primary energy savings in the household sector compared to the
PRIMES 2009 baseline energy demand
The primary energy related analysis of the household sector (see Figure 4-88)
permits four main conclusions:
First, the overall primary energy demand will further increase up to 2020 before entering a reverse trend and dropping to a level of 451 Mtoe by 2050, if no
additional measures are undertaken.
Second, the primary energy demand can be reduced by up to 28 % until 2050
considering a more efficient electricity generation mix (in this case considering
80 % instead of 54 % conversion efficiency; see also section 4.1.4).
Moreover, the overall primary energy saving potential through final energy
related efficiency measures mounts up to 230 Mtoe by 2050, reducing the
remaining demand to 94 Mtoe. In comparison with the PRIMES 2009 baseline,
the savings equal 51 %. With regard to the “Ambitious RES” baseline, the savings
represent even 71 % of the primary energy demand in 2050.
At last, the bulk of the savings originates from energy saving options related to
buildings (i.e. to the building envelope and the heating system). Despite the comparatively low electrification of this sector, which makes the potential becoming less
important than from a final energy point of view, buildings represent roughly 80
% of the household related primary energy savings.
165
Figure 4-89:
GHG emission reduction from the household sector compared to the
calculated emissions from the PRIMES 2009 baseline energy demand
The conclusions for the primary energy demand count likewise for the GHG emission reduction potential. However, under the PRIMES 2009 baseline, GHG emissions experience an important decline of 42 % between 2010 and 2050 due to
the increasing decarbonisation of the power sector and the advancing electrification of the heating sector.
Given the fact that the increasing diffusion of heat pumps triggers an increase in
electricity demand, the household sector is additionally benefitting from the decarbonisation of the power generation sector. Hence, GHG emissions can potentially be reduced by 21 % in 2050 (see the “conversion savings” slice in Figure
4-89).
Final energy related efficiency measures account for overall emission reductions
of up to 371 Mt CO2-eq in 2030. This value is declining afterwards to 259 Mt CO2eq in 2050 due to the fact that the increasing decarbonisation of the power sector
moderates the actual GHG reduction effect. Hence, GHG emissions can potentially
drop to a level of 128 Mt CO2-eq by 2050.
The contributions from the buildings sector to the overall GHG emission reduction potential increase from 83 % in 2020 (193 Mt CO2-eq) to 92 % in 2050 (237 Mt
CO2-eq).
166
Tertiary sector
The technical final energy saving potentials in the tertiary sector based on the calculated wedges are completed by savings from fans, commercial refrigeration and
freezing as well as other motor appliances that account for some additional 6 Mtoe
in 2030. This corresponds to almost 10 % of the total saving potential of 71 Mtoe,
which is reducing the final energy demand by 45 % to 86 Mtoe by 2030. Comparable to the residential sector, efficient heating and insulation systems are responsible for the bulk of the overall savings.
Figure 4-90:
tertiary sector
In the long run the trend of rising energy demand in the baseline scenario reverses,
resulting in a FED of 149 Mtoe in 2050 which is close to the current level. The energy saving trend beyond 2030 is supposed to continue, even though at a lower
rate. While the average annual saving rate between 2007 and 2030 amounts to
3.9 % (based on the 2007 value), it declines to 1.9 % for the period between 2030
and 2050. Final energy demand beyond 2030 can only be reduced by additional
28 Mtoe, down to 59 Mtoe by 2050. This can be translated to a 61 % reduction
compared to the PRIMES baseline as well as to the 2007 level.
167
Figure 4-91:
Cost curve for the tertiary sector, EU27
Regarding the cost-effectiveness of the potentials identified, three points need to
be raised. By 2020, already 85 % (about 40 Mtoe) of the overall technical potential
is economic. Electric appliances and lighting are basically entirely economic, representing about one quarter of the cost-effective potential. The remaining share is
deduced from building related measures whereof two fifth represent low-hanging
fruits that require low policy effort to overcome the barriers and that feature high
discount rates for investments. However, the total financial benefit of efficiency
measures in electric appliances and in buildings is equal and mounts up to about
€10 billion in each case.
The non-economic potentials become cost-effective only by 2040 if no financial
incentives are undertaken beforehand. They mainly consist of high-technology efficiency measures in the building shell and the heating system.
By 2050, the entirety of all potentials triggers net cost reductions of more
than €70 billion under the preconditions explained earlier.
168
Figure 4-92:
Primary energy savings from the tertiary sector compared to the
In terms of primary energy savings, the shift towards a high efficient power sector reduces tertiary primary energy demand by more than one third in 2050
(cf. Figure 4-92). This effect occurs at a much stronger intensity than in any of the
other sectors which is mainly based on the fact that the final energy demand is
dominated by electricity as the main energy carrier. Moreover, the growing diffusion
of heat pumps is driving a further increase of the electricity demand.
Nearly the same amount of savings (32 % or 102 Mtoe) is delivered by the
actual energy efficiency measures, compared to the PRIMES baseline. In relation to the “Ambitious RES” baseline (PRIMES baseline less the conversion savings), primary energy demand can be reduced by 50 % until 2050. The remaining
primary energy demand can consequently be reduced to 103 Mtoe by 2050.
Half of the energy saving potential is based on the improved insulation of
existing buildings and the construction of new, highly efficient buildings.
Some additional 20 % are added through the improvement of energy efficient heating and cooling technologies. The remaining share represents mainly electricity
driven appliances. Their primary energy saving potential is declining after 2030
since the improving conversion efficiency of the power sector over-compensates
the growing electricity saving potential.
169
Figure 4-93:
GHG emission reduction from the tertiary sector compared to the
With regard to GHG emissions the effect of the transformation towards a lowcarbon, high-efficient power sector gains additionally in importance. Already under
the PRIMES 2009 baseline, emissions are strongly declining by 46 % between
2010 and 2050 as a result of the decarbonisation of the power sector. By 2050,
some 36 % of the remaining energy related GHG emissions from the tertiary
sector can potentially be reduced through conversion savings and even lower
specific emissions per unit of electricity than under the PRIMES baseline.
Compared to the PRIMES 2009 baseline GHG emissions, some extra 32 % can be
saved through final energy related efficiency measures. In absolute terms, the
GHG emission reduction potential culminates in 2030 at 165 Mt CO2-eq, before
declining to 125 Mt CO2-eq by 2050. Hence, GHG emissions can potentially be
reduced to a level of 105 Mt CO2-eq in the long-run.
While in 2020, building related efficiency measures cover only 77 % of the overall
saving potential, their share exceeds 95 % by 2050.
Industry sector
The estimated wedges, completing the full range of final energy savings in the industry sector, comprise iron and steel industry, refineries, non-ferrous metal indus-
170
try, cement, chemicals and glass industry as well as other minor energy intensive
branches. Their total energy savings sum up to 18 Mtoe by 2030. This is roughly
one third of the potential covered by the calculated wedges, accounting in their
entirety for an 88 Mtoe reduction by 2030. The entire savings reach 26 % reduction compared to the PRIMES baseline.
Most of the short-term energy savings can be exploited by improved holistic optimisation of electric motor driven systems and energy efficient heat generation. In the
long run, further energy savings can compensate for the increasing baseline energy demand and promise even higher demand reductions. Provided a full implementation of the potentials by 2050, final energy demand would reach the 176
Mtoe level, verifying a 52 % reduction compared to the PRIMES 2009 baseline.
Figure 4-94:
industry sector
Even though efficient steam and hot water generation technologies (i.e. efficiency
improvement of heat generation units, further CHP diffusion and highly efficient
industrial space heating) represent the bulk of the technical final energy saving
potential, their contribution to the economic savings is quite smaller and strongly
depends on the assumptions made regarding the fuel mix of the generation capacities displaced by CHP (see also the respective fact sheet, 4.2.7).
171
Instead, electric drive based system optimisation measures trigger an immediate
cost reduction (apart from regular maintenance that causes additional labour
costs), nearly doubling the benefits deriving from process technologies (nearly €14
vs. 7€ billion). Adding up all costs and benefits leads to a net cost reduction of
€25 billion by 2020 and more than €100 billion by 2050. Excluding the cost
benefits from CHP that are highly sensitive regarding the price and fuel mix assumptions, reduces the net-benefits down to €21 and €90 billion.
Figure 4-95:
Cost curve for the industrial sector, EU27
Figure 4-96 shows the primary energy demand in the industry sector. If no measures are undertaken, PRIMES 2009 forecasts a further increase of energy demand
up to 592 Mtoe by 2050.
Primary energy savings in the industry sector are two-part. By 2050, 29 % of the
overall PRIMES 2009 baseline demand can be reduced through efficiency
improvements in the power sector.
Final energy related efficiency technologies are able to deliver an additional
36 % reduction compared to the PRIMES baseline. This corresponds to 215
Mtoe. While in the short-run more than one third of the savings are delivered
through e-drive system optimisation measures, this share declines subsequently.
This is due to the fact that the increasing power generation efficiency is partly compensating the significance of electricity saving measures. Hence, efficiency technologies for steam and hot water generation gain in importance, representing
nearly half of the primary energy saving potential by 2050.
172
Figure 4-96:
Primary energy savings from the industry sector compared to the
Figure 4-97 depicts the reduction of GHG emissions through efficiency improvements in the power sector (cf. the “conversion savings” slice) and final energy related efficiency technologies compared to the calculated emissions from the
PRIMES 2009 baseline energy demand.
It is obvious that even in the PRIMES baseline scenario GHG emission reductions
will occur to a level of 767 Mt CO2-eq by 2050. Efficiency improvements in power
generation support a decline in GHG emissions by 20 % to a level of 610 Mt CO2eq.
The actual industry related efficiency technologies drive a further decrease
of GHG emissions by additional 49 % compared to the overall baseline, limiting
the emissions to 233 Mt CO2-eq.
An increasing share of the emission reduction potential is based on efficiency
technologies in steam and hot water generation as well as other process-specific
efficiency technologies that trigger savings of energy carriers other than electricity.
This is due to the fact that electricity savings feature a decreasing emission reduction effect because of efficiency improvement and decarbonisation in the power
sector.
173
Figure 4-97:
GHG emission reduction from the industry sector compared to the
Transport sector
The transport sector is supposed to feature net final energy savings beyond 2020
in the baseline scenario due to the predominating autonomous shift towards more
efficient transport technologies. Faster reduction of final energy demand can be
mainly attained by prompting technical improvements in passenger as well as
goods and freight transport, accounting for nearly 50 % of the overall saving potential (excluding savings through e-Mobility) in 2030.
Behavioural changes have quite larger impacts in the road freight transport (about
17 % of the overall potential) than in the passenger transport (about 7 %).
Modal shift as well as aviation and rail transport that were not further analysed in
the factsheets account for 13 %, 12 % and 1 % respectively of all savings by 2030.
Due to the introduction of new drive technologies such as electric cars, hydrogen
fuelled fuel cell cars or cars based on biofuels, a further decrease in final energy
demand is supposed to occur. As pictured in Figure 4-98 e-Mobility can trigger
additional savings of up to 4 Mtoe in 2030 and 36 Mtoe in 2050 (in the Ambitious
scenario). Nevertheless, this potential is neither included in the overall potential
summation nor in the following determination of primary energy demand and GHG
174
emission reduction since cuts in final energy demand by means of e-Mobility limit
simultaneously the saving potential of the other transport-related efficiency measures mentioned beforehand.
Consequently, the total final energy saving potential (excluding e-Mobility) by 2030
sums up to 156 Mtoe, compared to 379 Mtoe in the baseline development, resulting in a 41 % demand reduction. By 2050, the potential grows up to 181 Mtoe,
reducing the PRIMES 2009 baseline demand by 53 %.
Figure 4-98:
Total final energy saving potential in the EU27 until 2050 in the
transport sector
Figure 4-99 depicts the cost curve for efficiency measures in the transport sector.
By 2020, nearly 80 % of the technical potential identified is economic.
In the upcoming decades, strong shifts within the cost curve order can be witnessed due to differently developing cost reductions among the various drive concepts. Efficiency improvements for motorcycles that solely run on gasoline (most
expensive fuel in the transport sector) experience much higher cost reductions than
measures in the freight transport or even aviation, due to lower fuel prices (as a
consequence of lower tax rates). Consequently, by 2050, a rearrangement of the
cost curve would be necessary that shows, that energy saving options for motorcy-
175
cles and passenger cars experience a stronger increase in the specific cost reduction per unit of energy saved. On the overall cost saving level, this order shift has
no direct effect, since the potentials of the other driving options are growing faster.
By 2050, the net cost savings have more than tripled from €62 billion in 2020
up to €190 billion.
Figure 4-99:
Cost curve for the transport sector, EU27
In compliance with the final energy demand projections, primary energy demand is
likewise supposed to decline beyond 2020 according to the PRIMES 2009 baseline
(see Figure 4-100).
The transport sector features the particularity that the contribution of efficiency improvements in the power generation sector has only a marginal impact on
the overall primary energy demand (4 % by 2050). This can be explained with
the low share of electricity as final energy carrier in the transport sector 45.
The saving potential through final energy related efficiency measures
mounts up to 188 Mtoe by 2050. Compared to the PRIMES 2009 baseline, energy demand can be potentially reduced to a level of 167 Mtoe or 49 %.
Nearly half of the saving potential is related to technical improvements in road
transport whereas the remaining half is fairly split into savings from behavioural
45 In the present analysis the focus is set on conventional drive concepts. Alternative car drive concepts using other energy carriers such as electricity are excluded in this analysis and addressed
separately (see 4.2.12 and Annex IV).
176
changes and various other measures (such as modal-shift or efficiency improvements in aviation and rail transport).
Figure 4-100: Primary energy savings from the transport sector compared to the
Based on the PRIMES 2009 primary energy demand the calculation of the GHG
emissions was carried out. A further calibration of the results by means of an average GHG emission indicator from the PRIMES baseline gave the GHG emission
projection as shown in Figure 4-101.
In terms of GHG emission reductions, the contribution from a shift to a highefficiency power sector is as marginal as it is for the primary energy demand reduction. Hence, the overall decreasing trend from the PRIMES baseline (of 19 % between 2010 and 2050) is not significantly changed.
Final energy related efficiency measures in the transport sector lead to GHG
emission reductions of 562 Mt CO2-eq or 57 % by 2050 compared to the overall
baseline. Half of this potential is represented by technical improvements in the road
transport. Realising the entire energy saving potential results in a limitation of
GHG emissions at a level of 404 Mt CO2-eq.
177
Figure 4-101: GHG emission reduction from the transport sector compared to the
4.4.2
Overview of potentials on national levels
This section examines the potentials in a few selected countries, which are: Germany, France, Italy, Spain and Poland.
These countries do not only play a prominent role in the context of international
climate and energy policy negotiations, but there are also responsible for more
than 50 % of the overall final energy demand of the European Union (cf. Figure
4-102).
178
Figure 4-102: Final energy demand by country, EU27, 2007
Figure 4-103 shows the relative GDP development in the five countries compared
to the 1990 level, whereas Figure 4-104 depicts the historical evolution of the final
energy demand between 1990 and 2008. Against one’s expectations, Poland features only a slight increase of 6 % in final energy demand despite the doubling of
GDP. At the same time, Spain, Italy and France experience strong increases in
energy demand, ranging from 15 % (France) to 66 % (Spain), while Germany reports a net decline of 4 % in 2008 compared to the base year.
179
Figure 4-103: Relative GDP development compared to 1990 for selected countries, 1990-2008
Figure 4-104: Final energy demand in specific countries, 1990 – 2008
Final energy demand
250
200
Poland
150
Spain
100
Italy
50
0
France
Germany
180
Figure 4-105: Energy intensity in absolute values and relative to 1990
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
Source: (Odyssee, 2011), own calculations
In the following, the energy saving potentials 46 of all the five countries are shortly
summarized, in the order of decreasing energy demand.
Germany
Germany is the most populous country in and an important industrial location of the
European Union, responsible for approximately one quarter of all the European
industrial value added. Hence, it is also the most energy consuming country in the
EU, covering about 18 % of the total FED.
Over the past 20 years the German final energy demand was roughly stagnating at
a level between 217 and 225 Mtoe per year, featuring a slight demand shift from
industry and tertiary (including agriculture) towards households and transport. In
2008, households, industry and transport represented likewise 28 % of the final
energy demand, compared to 15 % in the tertiary sector. The most energy consuming industrial branches are the steel industry (2008: 23 % of all industrial energy
demand), the chemical industry (18 %) as well as the machinery construction and
the paper and pulp industry with equal shares of 9 %.
46 In order to ensure the representation of the total energy demand, sectors not mentioned in detail
(e.g. agriculture) are included in the tertiary figures.
181
Comparable to the European level, the household sector features the highest
technical energy saving potential. The PRIMES 2009 baseline forecasts a further
increase of FED up to 69 Mtoe, which is later on dropping on today’s level of about
61 Mtoe. The exploitation of the energy saving potentials decreases the FED by
69 % until 2030 compared to the 2007 level, down to 17 Mtoe, through improved
housing insulation and energy efficient heating and cooling systems.
The transport sector promises halving of today’s energy demand, down to 30
Mtoe, which corresponds to a 47 % reduction of energy demand by 2030 compared to the baseline, due to an autonomous demand decrease in the PRIMES
projection. The main drivers are on the one hand improvements in passenger
transport, principally through technical but also through behavioural measures as
well as modal shift, accounting for about 43 % of all savings. On the other hand,
some additional 40 % result equally from technical improvements and behavioural
changes in goods transport; modal shift plays only a minor role. The remaining
share is predominantly covered through improvements in the air traffic branch, accounting for 11 % of the total saving potential.
The industry sector reports an energy saving potential of 12 Mtoe, which leads to
a relatively low FED reduction of only 23% compared to the baseline development, limiting FED at 40 Mtoe in 2030. As a result of an autonomous decrease in
the PRIMES forecast from 62 Mtoe in 2008 to 53 Mtoe in 2030, the overall demand
decrease compared to today’s level mounts up to 34 %. Four main technology
groups can be identified, primarily accounting for the 12 Mtoe saving potential: energy efficient cross-cutting technologies for heat generation (4.9 Mtoe, through efficiency improvements and further diffusion of CHP), e-drive system optimisation in
cross-cutting electric appliances (3.8 Mtoe, mainly through variable speed drive
and demand related control systems) and energy efficient process technologies in
the iron and steel industry (1 Mtoe, largely through thin slap or strip casting technology, cf. the respective factsheet). The remaining amount of savings can be realised through efficient lighting and efficient process technologies in the various industry branches
Energy savings in the tertiary sector are comparably high as in the industry sector, about 13 Mtoe, but the relative saving is significantly higher, mounting up to a
43 % decrease by 2030 compared to the PRIMES baseline. Comparable to the
household sector, the bulk of savings is linked to building related energy consumption: 30 percentage points can be delivered through refurbishment and efficient
heating in existing buildings, further 5 percentage points result from energy efficient
new buildings. The remaining share is delivered equally by efficient electric appliances and efficient lighting.
182
The aggregated potentials can trigger energy savings of 48 % by 2030 compared
to the PRIMES baseline (199 Mtoe in 2030). Relative to today’s level, final energy
demand would be reduced by even 52 %, reaching 104 Mtoe by 2030.
Figure 4-106: Technical energy saving potentials in Germany, by sector
France
France is sharing the second place of the most energy consuming countries within
the European Union together with the United Kingdom, accounting for 157 Mtoe in
2008, which equals to 13 % of the overall European FED. Approximately one
third of all final energy is used in the transport sector, which is followed by the
household sector (27 %), the industry (24 %) and the tertiary sector at last (17 %).
However, it is worth noting that there is a clear shift from industry towards the tertiary sector. Compared to 1990, final energy demand in the tertiary sector increased
by nearly 50 %, while the industry sector experienced a slight decrease (cf. Figure
4-107).
The French industry energy demand is dominated by the chemical industry (9
Mtoe), iron and steel industry (6 Mtoe), paper and printing industry (4 Mtoe) and
machinery construction (3 Mtoe).
The PRIMES 2009 baseline forecasts a slight further increase of the overall FED
up to 160 Mtoe by 2020, followed by a decline back to today’s level of 156 Mtoe.
183
Figure 4-107: Sectoral final energy demand evolution compared to 1990, France
As in other countries, the household sector drives the strongest absolute energy
demand reductions of 66 % compared to the baseline, limiting it to 15 Mtoe by
2030. 26 Mtoe of the 30 Mtoe saving potential result from building and heating related efficiency improvements, subdivided in 19 Mtoe from existing dwellings and 7
Mtoe from new dwellings. The remaining 4 Mtoe can be realised through efficient
sanitary hot water heating (1.5 Mtoe) and efficient electric appliances (mainly lighting, refrigerators and dryers).
The transport sector features energy savings of 20 Mtoe over the two coming
decades, lowering the energy demand by 47 % compared to the baseline and by
53 % compared to the 2008 level of 50 Mtoe. Almost three quarter of the savings
are covered through behavioural changes and technical improvements in the
goods transport as well as technical improvements in the passenger traffic (23 %
each). Modal shift in passenger and goods transport as well as behavioural
changes in passenger transport play a minor role, representing 6 % each of the
total saving potential in the transport sector. The remaining gap of 14 % is closed
by efficiency improvements in air traffic (10 %) and other means, such as motorcycles, public transport and rail.
A FED reduction by one fifth or 8.6 Mtoe is achievable through efficiency improvements in the French industry sector, compared to the PRIMES baseline.
6.5 Mtoe result from efficiency improvements in cross-cutting technologies. They
comprise efficient heat generation technologies as well as e-drive system optimisation measures (such as variable speed drive, demand related control systems or
avoidance of oversizing). Process technologies play a minor role (about 2.1 Mtoe).
184
Here, the highest savings are related to iron and steel as well as chemical industry
and refineries.
Despite the lower total final energy demand compared to the industry sector, the
tertiary sector promises higher energy savings of 10 Mtoe by 2030. In comparison to the baseline value of 30 Mtoe in 2030, that can be translated by a 34% demand reduction. 23 percentage points originate again from energy efficient building envelope as well as heating and cooling system of existing and new dwellings.
Some additional percentage points can be gained through efficiency improvements
in office lighting, fans and commercial refrigeration (4, 2 and 1.5 percentage points
respectively).
Adding all sectoral energy saving potentials leads to a total demand reduction of
45 % compared to the baseline by 2030, which equals to a residual FED of 86
Mtoe instead of 156 Mtoe in the PRIMES forecast.
Figure 4-108: Technical energy saving potentials in France, by sector
Italy
Italy reported a final energy demand of 130 Mtoe in 2008, which corresponds to
a 20 % rise compared to the 1990 level. Compared to the total final energy demand of the European Union, Italy accounts for a share of 11 %. It is the fourth
most important energy consumer of whole Europe and the biggest one of Southern
Europe (including Spain and Greece, excluding Turkey).
The strong increase in FED over the past years is largely due to a strong increase
in the tertiary and the transport sector. The latter is responsible for one third of
185
all Italian energy demand, directly followed by the industry sector, accounting for
roughly 30 %. Contrarily to the Western European countries mentioned above, final
energy demand of households plays a less significant role (20 % of the overall
FED) due to climate conditions and a limited need for heating. The tertiary sector
experienced nearly a doubling of energy demand since 1990, resulting in a 17 %
share in 2008 (cf. Figure 4-109).
Due to the fact that the gross value added of Italy rised at the same scale as the
energy demand, stagnating energy intensity can be reasoned.
For the coming two decades, the PRIMES baseline considers a fast return to the
pre-crisis level of 131 Mtoe and a further increase of 11 % up to 145 Mtoe in
2030.
Figure 4-109: Sectoral final energy demand evolution compared to 1990, Italy
In the household sector, a further increase in energy demand up to 36 Mtoe is
assumed in the PRIMES baseline, which is mainly related to rising cooling demand. Thus the energy saving potential of 16 Mtoe by 2030, leads to a 44 %
reduction compared to the baseline and to a 20 % reduction compared to the
2008 level (26 Mtoe). Two thirds of the saving potential (10.6 Mtoe) result from
efficiency improvements in existing buildings (comprising insulation, heating systems). Another 12 % are linked to the construction of energy efficient new buildings
and the installation of efficient sanitary hot water supply, respectively. The remaining share arises from efficiency improvements in electric appliances, mainly lighting, TVs, refrigerators and desktops.
Assuming no exploitation of saving potentials, the transport sector is supposed to
get back to the 2007 level of 45 Mtoe by 2019 (2009 post-crisis level: 43 Mtoe) and
186
to further increase up to 46 Mtoe by 2025, stagnating at this level until 2030, according to the PRIMES baseline. On the contrary, the realisation of the saving potential of 15 Mtoe would reduce the FED by 32 % to 31 Mtoe by 2030. 9 Mtoe are
resulting from savings in passenger transport (6 Mtoe from technical improvements
and 1.5 Mtoe from modal shift and behavioural changes respectively), 1.6 Mtoe
from technical improvements and behavioural changes in goods transport, respectively. Efficiency improvements in air traffic account for 1.7 Mtoe and in motorcycles
for 0.5 Mtoe. The latter is a singularity of the Italian transport sector compared to
other European countries.
The industry sector is supposed to recover rather fast from the economic crisis,
according to PRIMES. Up to 2030, a continued energy demand growth will lead to
45 Mtoe. The exploitation of the technical saving potential of nearly 9 Mtoe
would diminish the 2030 FED by 19 %. Slightly more than one third of all savings
are related to efficient heat generation. Another third results from efficient electric
cross-cutting technologies (particularly e-drive system optimisation measures, accounting for 3 Mtoe) and the last quarter arises from process specific technologies,
essentially from refineries and the iron and steel industry.
According to PRIMES, the FED of the tertiary sector will further increase, even
though the growth rate will be lower than before the economic crisis. The relative
saving potential in the tertiary sector is comparable to the transport sector, leading
to a 32 % FED decrease in comparison with the baseline by 2030. In absolute
figures, the actual saving potential is quite smaller, accounting for 6 Mtoe. 4.4 Mtoe
result from building related efficiency measures (building envelope, heating, cooling) of existing (3.9 Mtoe) and new dwellings (0.5 Mtoe). The remaining share is on
the one hand linked to efficiency improvements in air-conditioning, fans and commercial refrigeration and on the other hand to office lighting.
The overall saving potential of Italy sums up to 46 Mtoe by 2030, which translates to a 31 % reduction compared to the baseline, reducing the FED from 146
Mtoe to 100 Mtoe. The household as well as the transport sector represent one
third each, while the remaining third is covered by industry and tertiary sector.
Compared to the pre-crises level of 2007 (131 Mtoe), the reduced FED will be 24
% lower.
187
Figure 4-110: Technical energy saving potentials in Italy, by sector
Spain
Spain has experienced one of the strongest final energy demand increases
among all European countries of nearly 75 % between 1990 and 2007 (in the
same range as Ireland and Cyprus) (Eurostat, 2011). This growth was mainly
driven by a doubling of FED in the tertiary sector and an 80 % increase in the
households and transport sector, in contrast to 50 % in the industry.
The increase in FED went along with a strong economic growth of almost 70 %
before the entering of the crisis (cf. Figure 4-103). The energy intensity, which is
an indicator for the energy demand per unit of value added, did not experience an
essential efficiency improvement. Figure 4-105 depicts the energy intensity of all
the five countries. As can be clearly seen, the relative energy intensity even increased, indicating a slight increase up to 12 % above the 1990 level. In absolute
figures, the intensity ranged between 0.121 and 0.135 toe/€2000, which is clearly
above the level of Italy, France and Germany (0.103, 0.096 and 0.095 toe/€2000
respectively in 2008).
In 2007, the total FED mounted up to 102 Mtoe, consisting of 40 % related to the
transport sector, 30 % to the industry, 17 % to households and 13 % to the tertiary
sector (cf. Figure 4-111).
For the next two decades, PRIMES forecasts a further FED growth up to 124 Mtoe
by 2030, mainly in the industry and transport sector.
188
Figure 4-111: Sectoral final energy demand in Spain, 1990 - 2008
The Spanish household sector experienced a slight drop in FED due to the economic crisis. According to PRIMES, the 2007 level of 17 Mtoe will be reached by
2013 again and a slight further increase up to 18 Mtoe by 2020 is assumed, where
FED will sort of stagnate for the following 10 years. Efficiency measures promise a
FED reduction by two third compared to the baseline in 2030. Hence, energy
demand can be reduced from 18 Mtoe down to 6 Mtoe. 85 % of all savings, i.e.
10 Mtoe, result from building related efficiency improvements. It is a Spanish phenomenon that the bulk of savings is related to the construction of new efficient
buildings (5.3 Mtoe), whereas the refurbishment and efficient heating systems lead
only to 3.3 Mtoe. Efficient sanitary hot water supply, efficient lighting and efficient
electric appliances (particularly TVs) account for 1 Mtoe each.
The transport sector, as the most energy consuming sector, is supposed to further increase from currently 40 Mtoe up to 48 Mtoe by 2030, if no efficiency measures are realised. However, the energy saving potential is very important, promising nearly a halving of the baseline FED by 2030, reducing the demand by 24
Mtoe. 20 Mtoe of savings are equally delivered by improvements in the goods and
passenger transport. While for goods transport, technical improvements and behavioural changes account likewise for a 4.5 Mtoe reduction, savings in passenger
transport are dominated by technical improvements (6.6 Mtoe) and the remaining
3.5 Mtoe are similarly realised through behavioural changes and modal-shift. Additional savings are related to air traffic (2.5 Mtoe) and other transport means (motorcycles, public road and rail), accounting for 1 Mtoe.
As mentioned before, the FED of the Spanish industry sector will feature an important further growth of 43 % until 2030 compared to the 2007 level (i.e., 43 Mtoe
189
instead of 30 Mtoe), if no active efficiency improvements are undertaken. However,
the technical saving potential of 10.8 Mtoe by 2030 will not trigger additional
savings compared to the level in 2007, but at least soften the future demand
increase to 7 % instead of 43 %. Similarly to the other countries, the bulk of savings is related to efficient cross-cutting technologies: 5.8 Mtoe originate from efficient heat generation, 1.9 Mtoe from e-drive system optimisation measures and 0.2
Mtoe from efficient lighting and efficient motors respectively. Process technologies
account for 2.6 Mtoe in total, mainly dominated by efficiency gains in the iron and
steel as well as in the chemical industry.
The PRIMES forecast predicts a significantly slower increase in FED in the tertiary
sector, compared to the past 20 years. By 2030 FED will have reached 15 Mtoe
compared to 14 Mtoe in 2007. The saving potential sums up to 6.4 Mtoe by
2030, leading to a 43 % demand reduction and thus to 8.4 Mtoe remaining FED.
Contrarily to the households sector, the bulk of saving is resulting from efficiency
improvements in existing buildings (3.4 Mtoe) and less from new buildings (1
Mtoe). Other savings are related to efficient air-conditioning (1 Mtoe) and efficient
office lighting (0.4 Mtoe).
The overall saving potential of Spain sums up to 53 Mtoe by 2030. In comparison with the PRIMES baseline, FED is reduced by 43 % to 71 Mtoe instead of
124 Mtoe. Half of the savings result from transport, a quarter from households and
the remaining quarter from industry and tertiary sector.
Figure 4-112: Technical energy saving potentials in Spain, by sector
190
Poland
Poland has experienced an extraordinary economic growth over the past 20 years,
doubling the GDP value from 1990 (cf. Figure 4-103). Simultaneously the Polish
final energy demand experienced only a slight increase of 6 % compared to
1990. This can mainly be explained by an important improvement of energy efficiency and structural changes in the Polish economy, shifting from industry towards
the tertiary sector. Figure 4-105 shows a clear decline of the energy intensity between 1990 and 2009 from 0.44 to 0.23 koe/€2000, which equals a 51 % reduction
or, in other words, a doubling of energy efficiency. However, compared to other,
more efficient countries such as Germany, the Polish energy intensity was still
more than 138 % above the German value.
Despite the fact that FED did not rise much over the last two decades, the single
sectors experienced very much different developments in FED (cf. Figure 4-113).
The transport and tertiary sector experienced a clear and steady growth of 118 %
and 23 % respectively between 1990 and 2008, while the household sector had a
strong increase in the early 1990s, but is now continuously dropping back to the
1990 level. The growth in these three sectors is mostly compensated by a FED
decline in the industry sector, which is (as mentioned above) linked to increased
efficiency.
In 2008, the total FED summed up to 60 Mtoe, being composed of the household
sector (31 %), equal shares of industry and transport sector (25 % each) and the
tertiary (18 %). For the upcoming two decades, PRIMES predicts a 25 % increase
until 2030, which is equally spread over the transport, industry and tertiary sector.
Figure 4-113: Sectoral final energy demand in Poland, 1990 - 2008
191
According to PRIMES 2009, the household sector is the one expecting the lowest
growth in FED, rising from 18 Mtoe in 2007 up to 20 Mtoe in 2030. Exploiting the
technical energy saving potential would reduce the energy demand by nearly the
half (47 %) compared to the baseline, leading to 10 Mtoe of residual demand.
Two thirds or 6.4 Mtoe of all savings are related to efficiency improvements in existing buildings, another 1.8 Mtoe result from efficient new buildings. The remaining
one Mtoe is mainly covered by efficient lighting and water heating, whereas efficient electric appliances play a minor role of only 0.3 Mtoe.
The FED in the transport sector is expected to continue its significant growth,
further rising from 15 Mtoe in 2007 to 22 Mtoe by 2030, which equals to a 46 %
increase if no efficiency action is undertaken. In the short term, 2.6 Mtoe of savings can simply be triggered through a modal shift in passenger transport,
covering already almost half of the savings achievable. By 2030, the total saving
potential mounts up to 9 Mtoe, hence compensating for the further increase and
even driving additional savings, reducing the FED by 41 % (compared to the
baseline) to 13 Mtoe. Nearly half of the savings result from goods transport (2
Mtoe from technical improvements and behavioural changes, respectively), 15 percentage points from passenger transport (in 2030 dominated by technical improvements) and one additional Mtoe from efficient air traffic.
The industry sector experienced a decline in FED over the past 20 years despite
a stable industrial output and a significant increase of the industrial value added
(see also the introduction of this section). Apart from structural changes, this is
particularly related to an increase in energy efficiency. However, for the period until
2030, PRIMES forecasts an increase in FED that goes along with a further augmentation of value added and energy efficiency. By 2030, the industrial energy
demand is supposed to reach 19 Mtoe according to PRIMES, compared to 16 Mtoe
in 2007. Exploiting the total technical energy saving potential would limit the FED
to 15 Mtoe by 2030, hence reducing the energy demand by 20 % compared to
the baseline. One quarter of the 3.8 Mtoe saving potential is largely related to improvements through the holistic optimisation of electric motor driven systems but
also to efficient lighting and from electric motors itself. Some additional 2 Mtoe result from efficient heat generation and a further diffusion of CHP technology.
Roughly one Mtoe can be gained in process specific technologies, in particular in
the iron and steel sector.
Comparable to the transport sector, the tertiary sector’s FED is likewise expected
to increase over the next two decades by nearly 40 % from 10 Mtoe in 2007 to 14
Mtoe in 2030, in the baseline scenario. The technical saving potential is one and a
half time as big as the FED growth, making the FED drop by 6 Mtoe down to 8
Mtoe by 2030. 5 Mtoe are related to efficiency improvements in buildings (heating
192
and insulation), whereby the contribution from existing buildings doubles the one
from new buildings. The remaining one Mtoe is mainly triggered by efficiency improvements in office lighting, fans and commercial refrigeration and freezing.
Bringing together all technical saving potentials permits a 38 % reduction in
energy demand by 2030 compared to the baseline. That translates by a decrease
from 75 Mtoe to 47 Mtoe. Due to the fact, that energy savings in the transport,
tertiary and industry sector largely compensate for further demand increases and
do not drive significant additional savings compared to today’s level, the net savings are mainly driven by the household sector and sum up to 13 Mtoe (or 22 %) in
comparison with 60 Mtoe in 2007.
Figure 4-114: Technical energy saving potentials in Poland, by sector
Comparison of national saving potentials
Table 4-11 gives a final overview of the saving potentials in the various countries. It
is worth noting that in the short term (by 2020) Germany features the highest relative as well as absolute savings of nearly 30 % compared to the PRIMES 2009
baseline, whereas Italy reports only a 21 % saving potential. While this saving potential is dominated by the households sector in central European countries (Germany and Poland) due to the climatic circumstances, the transport has a major
influence in the Southern European countries. By 2030, Germany would be able to
halve its FED compared to the 2007 level, due to the declining energy demand in
the baseline, whereas Poland’s saving potential is the lowest one (22 % relative to
2007) since FED in the baseline will further increase. Compared to the EU average
of 38 % (in comparison with 2007), only Germany and France promise higher saving potentials, whereas the other three countries are significantly falling below this
193
value. Assuming a full implementation of the saving potentials, Italy would report a
residual FED of 100 Mtoe which is higher than the French one and almost as high
as the German demand.
194
Table 4-11:
Overview of final energy demand and energy saving potentials in specific countries and EU27
195
5
Summary and discussion of results
In this chapter, the potentials for the technical and economic final energy savings
as well as for the primary energy demand reduction and for the greenhouse gas
emission mitigation are brought together on the highest level of aggregation.
In the first part, the final energy related results from the sectoral overviews (cf. section 4.4.1) are summarised and the technical potential trajectory as well as the
overall cost curve are shown for the EU27.
In a second part, the same procedure is carried out for primary energy saving and
GHG emission reduction potentials.
Given the results from the second part, in the last section a rearrangement of energy saving wedges is done in the light of the achievement of the 20 % efficiency
target.
5.1
Overall final energy saving potentials
This section summarises the results of the assessment of the technical and economic potentials on sectoral level and sums up to an overall survey.
It is worth noting that generally speaking the technical saving potential assessed in
this study is a rather conservative estimation. Given the fact that final energy savings from a shift in car propulsion technology as well as from efficiency improvements in electricity generation and transport were not included in this report, the
actual potential is supposed to be even higher than the data presented. The reason
therefore lay in the fact that the two main underlying studies ((ISI, 2009a) and (ISI,
2009c)) did not include these sectors. Hence, a rough estimation of the saving potentials was carried out. However, a detailed assessment of the potentials could
not be completed in the framework of this study thus resulting in the exclusion of
these potentials from the overall potential assessment.
As can be clearly seen in Table 5-1, the highest technical saving potential is related to the refurbishment of existing buildings. Further short-term potentials can be
exploited through efficient industrial heat generation and the construction of efficient new residential buildings. By 2030, the significance of saving potentials
slightly shifts. Efficient heating systems as well as technical improvements in passenger cars gain in importance. However, the bulk of savings is still related to the
same saving options as in the first two decades.
196
Table 5-1:
Technical energy saving potentials in all sectors (not taking into account e-Mobility), EU27
197
Adding all saving potentials together results in a 41 % FED reduction by 2030
compared to the PRIMES 2009 baseline 47, reducing energy demand from 1216
Mtoe down to 714 Mtoe, if the saving potential of e-Mobility is not included.
By 2050, final energy demand in the baseline scenario is supposed to experience a slight decrease of 3 % compared to 2030. The entire technical energy
saving potentials promise a reduction of 57 %, decreasing the total FED to a
level of 512 Mtoe.
The total savings of 671 Mtoe are covered through households (207 Mtoe), industry (192 Mtoe), transport (181 Mtoe) and tertiary (90 Mtoe). Any more detailed
information regarding the energy savings on sectoral level can be found in section
4.4.1.
If the final energy savings through e-Mobility are included (see also Figure
5-1) the saving potential in 2030 mounts up to 507 Mtoe (instead of 502 Mtoe) and
to 707 Mtoe (instead of 671 Mtoe) in 2050, resulting in a 42 % and 60 % reduction,
respectively.
Figure 5-1:
Total energy saving potentials in the EU27 until 2050
Figure 5-2 depicts to what extent the potentials identified can be covered by concrete measures that are explained in the fact sheets (cf. 4.1.4). The coverage
through the calculated wedges rises from 72 % at the beginning of the period under review up to 85 % by 2030 (and keeping constant at this level up to 2050)m
47 In order to cover the total final energy demand, sectors not mentioned before, such as agriculture,
are herein included in the tertiary sector numbers in order to represent the entire baseline value.
198
resulting in an average coverage of about 83 %. While in the first decades, only in
the household sector the majority of measures were subject to an in-depth analysis
(apart from sanitary hot water heating), potentials in the transport as well as in the
industry sector are underrepresented in the fact sheets (only about 80 %).
Figure 5-2:
Overview of the coverage of saving potentials by means of calculated 48 and estimated wedges
Comparing the technical saving potential identified in the framework of this study
with the final energy demand reduction trajectories (cf. Figure 5-3) clearly underlines, that most of the studies do not expect the energy demand decrease to the
extent that is technically possible. In contrary, even ambitious studies such as the
Greenpeace Energy [R]evolution (Greenpeace, 2010a) suppose only half of the
technical saving potential to be exploited. In the ambitious 450ppm scenario of the
IEA (IEA, 2010a) the demand projection is even close to the PRIMES baseline,
hence not assuming demand reduction measures at all.
48 The calculated wedge for transport also includes the potential from e-Mobility
199
Figure 5-3:
Comparison of the technical saving potential (not taking into account
e-Mobility) and the results from other studies
Figure 5-4 shows the cost curve of all measures 49 being identified in the four sectors: household, tertiary, industry and transport. Three main conclusions can be
drawn from the chart. Firstly, the overall saving potential (economic as well as
technical) is dominated by measures located in the households and transport sector. Secondly, measures from the transport sector represent the most cost-effective
as well as the most cost-intense options for reducing the final energy demand. Finally it is obvious that over the coming decades a strong shift within the order of the
cost curve will occur.
49 apart from e-Mobility and efficiency improvements in energy generation, transmission and distribution
200
Figure 5-4:
Overall cost curve for all sectors, EU27
Hence, a second type of illustration was chosen that depicts in a clearer way the
evolution of the cost curve shape over the next 40 years. In Figure 5-5 the four
yearly cost curves integrated in Figure 5-4 are shown separately. The elements
included in the cost curves were rearranged by increasing specific energy saving
costs. Thus, it can be observed, that efficiency measures in the household and
industry sector that were part of the most cost-effective options in 2020 (such as
residential lighting or industrial electric drive system optimisation) are steadily
pushed aside by more cost-efficient measures in the transport sector (particularly in
the passenger transport sector). The main driver for this shift of the order of options
is mainly driven through the differing increase in fuel prices. For instance, building
related measures that represent an enormous energy saving potential, do not experience the same rise in cost reduction than efficiency improvements in the transport sector because the absolute cost increase for natural gas (used in households
for heating) is lower than for gasoline (used in passenger cars and motorcycles)
even though the relative price rise is equivalent.
201
Figure 5-5:
Overview of the overall cost curves in the years 2020, 2030, 2040,
2050, EU27
Table 5-2 summarises again the main results of the economic assessment. It reports on the one hand side the economic energy saving potentials, i.e. all saving
potentials with specific costs below zero Euro per unit of energy saved (this is
equal to all the potential blocks below the horizontal axis in the cost curve charts)
which comprises all low hanging and high hanging fruits as well as former immature fruits that became cost-effective due to fuel price rise. The financial benefits
related to these potentials are given in the “economies” column.
On the other hand side, the overall (technical) saving potential is pointed out and
the net-benefit is calculated. This benefit is equal to or below the benefit of the
cost-efficient measures mentioned beforehand, since additional financial effort is
required in order to deploy the non-economic potential. However, overall, even
including the technical potentials considered here, there are still economies as
compared to the reference development.
202
Table 5-2:
Overview of the overall energy saving potentials and financial benefits due to energy saving options, EU27
2020
2030
2040
2050
Potential
Economies
Potential
Economies
Potential
Economies
Potential
Economies
[Mtoe]
[bn €’05]
[Mtoe]
[bn €’05]
[Mtoe]
[bn €’05]
[Mtoe]
[bn €’05]
House-
Cost-efficient
81
31
146
75
164
100
199
127
holds
Overall
101
25
187
68
199
96
207
124
Tertiary
Cost-efficient
40
20
58
40
82
55
90
71
Overall
47
19
71
39
82
55
90
71
Cost-efficient
45
29
71
44
129
74
173
105
Overall
57
25
88
41
143
70
192
102
Transport 50
Cost-efficient
88
80
119
116
131
161
153
210
Overall
112
62
156
91
171
138
181
191
Overall
Cost-efficient
255
159
395
275
506
389
615
514
Overall
317
131
502
239
595
359
669
488
Industry
50 Excluding savings due to e-Mobility
203
Considering the data from Table 5-2 as well as the information from Figure 5-5
permits drawing the following conclusions:

The highest sectoral benefits can be triggered through deployment of
transport related energy saving measures (€210 billion for the economic
measures, €191 billion for all measures) whereas

the highest sectoral energy saving potential is located in the household
sector (199 Mtoe economic potential and 207 Mtoe technical potential).

In the long-run (beyond 2040) the entire saving potential in the tertiary
sector is cost-effective whereas

the industry sector requires only very little financial incentives in order to
unlock the remaining non-economic saving potential.

The economic saving potential increases by more than 140 % between
2020 and 2050 (255 vs. 615 Mtoe) while the benefit deriving from costeffective measures is more than tripling up to €514 billion by 2050 due to
the expected increase in fossil fuel prices.

The share of the economic potential compared to the technical potential
increases from 80 % in 2020 up to 92 % by 2050.

In order to deploy the entire technical saving potential by 2050 (this equals
to an increase of 8 %), the benefits would be reduced by 5 % which is
comparable to mean benefits from energy savings of roughly 490
M€’05/Mtoe. This shows that even including the technical potentials considered here, there are still economies as compared to the reference development.
5.2
Overall primary energy saving and GHG emission
reduction potentials
Bearing in mind the results of the final energy savings from the previous chapter,
this section focuses on the consequential implications of final energy related efficiency measures and improved energy conversion efficiency on the primary energy
demand and the overall GHG emissions.
Figure 5-6 summarises the sectoral results of chapter 4.4.1 by depicting the overall
primary energy savings. The saving potential is actually split in two parts. The first
part of savings originates from efficiency improvements in the electricity generation
process (cf. the slice “Conversion savings”). By the year 2050, the overall primary
204
energy demand as forecasted in PRIMES 2009 (European Commission, 2010)
can be potentially reduced by 25 % through a shift towards a high-efficient
electricity generation mix, as considered in the “EU long-term scenarios 2050”
study 51. The bulk of conversion savings results from the household and tertiary as
well as from the industry sector. This is due to the fact that these sectors feature
the highest degree of electrification. In the transport sector, this effect is more limited, since this sector according to the assumptions taken in this study on Emobility is still mainly relying on oil products as energy carriers. Only 10 % of the
passenger car stock is shifted to electricity by 2050.
Subtracting the conversion savings from the PRIMES 2009 baseline leads to the
so-called “Ambitious RES” baseline which represents the reference pathway for the
assessment of the final energy related efficiency measures. The coloured parts in
Figure 5-6 represent the primary energy savings through the calculated as well as
the estimated wedges. By the year 2050, the overall savings will have summed
up to 736 Mtoe which equals a 47 % reduction compared to the “Ambitious RES”
baseline. With regard to the PRIMES 2009 baseline, these savings deliver an
additional 35 % reduction, leading to a remaining primary energy demand of
568 Mtoe in 2050.
51 As mentioned earlier, this study is likewise carried out by Fraunhofer ISI on behalf of the German
Federal Ministry for the Environment. From this study scenario B was used for the calculation of
the primary energy savings.
205
Figure 5-6:
Overall primary energy savings compared to the PRIMES 2009
baseline energy demand
Savings energy
conversion
Savings final demand
Table 5-3 gives an overview of the sectoral energy savings in 2030 and 2050. By
2050, the industry sector can contribute most to the reduction of primary energy
demand with 389 Mtoe saving potential which is equal to a 65 % demand reduction
compared to the industrial baseline value. Such a strong potential decline in energy
demand is only exceeded by the households sector with 76 % energy saving potential until 2050. The transport sector features a very strong energy saving potential through final energy related efficiency measures. However, the overall relative
savings are lower than in the other sectors, given the fact that the transport sector
is less benefitting from increased conversion efficiency in the electricity sector due
to the low share of electricity among the final energy carriers.
206
Table 5-3:
Year
2010
2030
2050
Overview of primary energy savings in the different sectors
Sector
PRIMES
baseline
[Mtoe]
Conversion
savings
Saving
potential
wedges
[Mtoe]
HH
484
-
-
-
-
484
TE
327
-
-
-
-
327
IN
544
-
-
-
-
544
TR
411
-
-
-
-
411
Total
1767
-
-
-
-
1767
HH
486
19 %
232
48 %
67 %
161
TE
342
26 %
93
27 %
53 %
161
IN
566
21 %
114
20 %
41 %
335
TR
418
2%
170
41 %
43 %
240
Total
1813
17 %
608
34 %
51 %
897
HH
451
25 %
230
51 %
76 %
94
TE
323
36 %
102
32 %
68 %
103
IN
592
29 %
215
36 %
65 %
203
TR
368
4%
188
51 %
55 %
167
Total
1735
25 %
736
42 %
67 %
568
Relative
savings
through
wedges
Overall
savings
Remaining demand
[Mtoe]
With regard to the GHG emission reduction potential, the picture looks slightly different than for primary energy demand. While primary energy demand is further
growing in the PRIMES 2009 baseline, GHG emissions are subject to a 31 %
reduction between 2010 and 2050 (see Figure 5-8). This evolution is based on
the fact that the generation of electricity is to an increasing extent ensured by decarbonised generation technologies, mainly nuclear and CCS power plants but
also renewable energy sources. Hence, the electricity generation mix in the alternative baseline (which is based on the “EU long-term scenarios 2050” study) affects the GHG emission development much less than the primary energy demand,
207
since the overall efficiency is much higher in the alternative baseline, whereas the
specific GHG emissions decrease significantly in both scenarios (cf. Figure 5-7).
Figure 5-7:
Comparison of the development of the electricity generation efficiency and the specific GHG emission per unit of electricity under
the two baselines
Thus the contribution of the “conversion savings” equals a 15 % (or 389 Mt
CO2-eq) GHG emission reduction by 2050 (see also Table 5-4). While this share
is similar in 2020 (10 %), it is much lower for the years 2020 and 2030. This can be
explained by the fact that by 2020, the PRIMES baseline sticks to conventional
power generation whereas for the alternative electricity generation mix a strong
shift from solids towards renewable energy sources takes place, which is substantially depleting the specific emissions. Under PRIMES the fuel shift is occurring in
the years 2030 and 2040 (mainly towards nuclear and CCS) whereas the alternative baseline experiences a cutback of nuclear that diminishes the specific emission reduction pathway.
The overall contribution from the use of final energy related energy efficiency
measures lowers the overall GHG emissions to the level of 871 Mt CO2-eq by
2050 which equals 33 % of the PRIMES baseline emissions. Hence, the emission reduction potential of efficiency measures is equivalent to a 1359 Mt CO2-eq.
The emission reduction potential grows strongest during the first two decades,
given the fact that the declining specific GHG emissions for electricity are not only
lowering the baseline emissions but also affecting the energy saving measures.
208
Figure 5-8:
Overall GHG emission reduction potential compared to the calculated emissions from the PRIMES 2009 baseline energy demand
The contribution of the various sectoral efficiency measures permits a clear tripartition of the emission reduction potential in 2050: roughly one third originates from
the transport sector, nearly one third is represented by the industry sector and the
remaining third is based on efficiency measures in the household and tertiary sector.
As mentioned earlier, it is worth noticing that the higher the share of electricity as
final energy carrier in a sector, the lower the contribution from this sector to GHG
emission reduction due to the increasing decarbonisation of the power sector.
209
Table 5-4:
Year
2010
2030
2050
Overall GHG emission reduction potential in the different sectors
Sector
PRIMES
baseline
[Mt CO2eq]
Conversion
savings
Saving
potential
wedges
[Mt CO2eq]
Relative
savings
through
wedges
Overall
savings
Remaining
emissions
[Mt CO2eq]
HH
919
-
-
-
-
919
TE
629
-
-
-
-
629
IN
1072
-
-
-
-
1072
TR
1203
-
-
-
-
1203
Total
3823
-
-
-
-
3823
HH
716
5%
399
56 %
61 %
282
TE
472
7%
165
35 %
42 %
275
IN
896
5%
237
26 %
31 %
616
TR
1165
0%
511
44 %
44 %
650
Total
3248
3%
1312
40 %
44 %
1824
HH
538
21 %
295
55 %
76 %
128
TE
336
32 %
125
37 %
69 %
105
IN
767
20 %
377
49 %
70 %
233
TR
978
1%
562
57 %
59 %
404
Total
2619
15 %
1359
52 %
67 %
871
Summarising the main insights from this section leads to the following conclusion:
 Primary energy demand and GHG emissions can be reduced most efficiently by addressing final energy demand with concrete energy saving
measures and by moving to a high-efficient, low carbon electricity generation mix.
 Primary energy demand can be reduced in the long-run (2050) to a level of
568 Mtoe (67 % below the PRIMES baseline and 66 % below 1990 levels).
210
 GHG emissions can be potentially reduced to 871 Mt CO2-eq by 2050 (67
% below the PRIMES baseline and 80 % below the 1990 levels 52, 53).
 Final energy related efficiency measures can deliver long-term primary energy savings of 736 Mtoe and a reduction of GHG emissions of 1359 Mt
CO2-eq.
 Shifting to a high-efficient, low-carbon energy supply system, such as the
one assumed in the “EU long-term scenarios 2050” study, can significantly
contribute to the reduction of primary energy demand by 444 Mtoe in 2050,
and to the reduction of GHG emissions by 389 Mt CO2-eq compared to the
PRIMES baseline.
 Among both types of efficiency potentials (final energy and energy conversion related) the first deliver the largest savings in both primary energy and
GHG emissions. This varies across the sectors: some sectors, such as the
transport sector, do not benefit from increased conversion efficiency due to
a high energy chain efficiency (e.g. for oil products) whereas other sectors
show limited final energy saving potentials (e.g. electric appliances in the
household sector) but strong demand reductions by means of a highly efficient electricity generation.
 The analysis shows that there is a strong interaction between the penetration of renewables in the power sector and savings in the final energy sectors: On the one hand side, applying final energy use related efficiency
measures helps lowering the energy demand and hence raising the share
of decarbonised energy conversion technologies, whereas on the other
hand side high-efficient renewable energy sources trigger additional benefits regarding the overall primary energy efficiency.
52 The aim of the European Union is to reduce GHG emission by 80 to 95 % compared to the 1990
level (Council of the European Union, 15265/1/09 REV 1, Brussels, 1 December 2009
http://www.consilium.europa.eu/uedocs/cms_data/docs/pressdata/en/ec/110889.pdf). This equals
a corridor of 214 to 857 Mt CO2-eq. The calculated 871 Mt CO2-eq clearly underline the significance of energy efficiency measures, increased conversion efficiency and a decarbonised energy
sector in order to reach this target. Further emission reductions can be triggered through the carbon-neutral generation of final energy carriers other than electricity (e.g. geo-thermal heat, solar
thermal heat, biomass, biofuels etc.)
53 In 1990 energy related GHG emissions of the EU-27 were equivalent to 4283.9 Mt CO2-eq according to (UNFCCC, 2011).
211
5.3
Rearrangement of wedges
On the basis of the energy saving and emission reduction potentials, determined in
the previous chapters, at this point a final rearrangement of the wedges is carried
out. The main target of this task is to determine “efficiency technology packages” of
comparable size that might pave the way towards the 20% efficiency target by
2020 that was announced by the European Commission in various documents 54.
The 20 % efficiency target is formulated as a 20 % decrease of primary energy
demand by 2020 compared to the PRIMES 2007 baseline (European Commission,
2008). From the Impact Assessment accompanying the Energy Efficiency Plan
2011 (European Commission, 2011d) it becomes clear that this relative demand
reduction excludes the non-energy use for 2020 (126 Mtoe). Hence, the absolute
saving target is calculated as follows: 1971 Mtoe (primary energy forecast for 2020
according to PRIMES 2007) less the non-energy use (126 Mtoe) multiplied by 20
%. The result is 368 Mtoe of savings or in other words the reduction to a level of
1602 Mtoe by 2020.
The latest projections from the European Commission based on the PRIMES 2009
calculations (European Commission, 2010) forecast a primary energy demand in
2020 of 1828 Mtoe. This value differs from the target mentioned beforehand by
only 14 % or 226 Mtoe and is the consequence of lower than expected economic
growth and the further penetration of GHG reduction measures.
Within the next steps, the aim is to identify efficiency wedges that might help to
overcome the gap of the 226 Mtoe towards the 20 % efficiency target and to determine to which extent the application of these wedges is required.
As explained in section 5.2, the overall primary energy savings through final energy
related efficiency measures mount up to 404 Mtoe 55 by 2020. Further savings of
195 Mtoe can potentially be generated through the shift towards a high-efficient
electricity generation mix (so-called “conversion savings”).
In order to split up the 404 Mtoe of savings identified, 10 similarly sized wedges of
roughly 40 Mtoe are created. In order to pool the various efficiency technologies
analysed in this report, a specific filtering procedure is applied considering the following criteria:
54 e.g. in the Communication on the “Strategy for competitive, sustainable and secure energy”, from
10 November 2010, COM(2010) 639 final
55 This figure includes the savings from calculated and estimated wedges.
212
•
Cost-efficiency of the measure/technology: roughly 80 Mtoe of primary
energy savings are not cost-efficient by 2020. These measures are subdivided by sector into wedge 9 (households and tertiary) and 10 (industry
and transport). All cost-efficient measures need to be further filtered.
•
Type of measure (behaviour related or technical): behaviour related measures appear in the transport and industry sector. They were sub-divided according to their sectoral belonging (wedge 5 and 7). Technical measures
dominate the saving potentials. They were further split according to the next
criteria.
•
Sectoral belonging: given the fact that the “efficiency technology packages” shall be likewise addressed by “policy measure packages” a subdivision regarding the sectoral belonging was carried out. Wedge 8 covers
technical improvements in the transport sector. Measures from the household, tertiary and transport sector need to be further distinguished.
•
Type of final energy carrier: efficiency measures are addressed to specific applications that are potentially dominated by particular fuels. In the industry sector, process specific saving technologies help reducing the demand for electricity as well as heat and other energy carriers. They are
grouped together with CHP in wedge 6. The remaining industrial efficiency
technologies (efficient electric drives and lighting) are included in the industry wedge 5. In the households and tertiary sector, a large number of efficiency technologies address electricity consuming appliances. They are
hence combined in wedge 4. The remaining efficiency measures in the
household and tertiary sector are related to the buildings sector.
•
Heating vs. building technologies: all efficiency measures related to the
efficient generation of heat or cold are merged in wedge 3. The remaining
measures aim on a reduced heat consumption.
•
New vs. existing buildings: finally, building related measures are divided
into those addressing the refurbishment of existing (wedge 2) or the construction of new buildings (wedge 1).
Table 5-5 gives an overview of the newly arranged wedges and their specific characteristics.
213
Table 5-5:
#
1
2
Overview of the characteristics of the newly arranged wedges
Title of wedge
New buildings
Refurbishment of existing buildings
Sector
addressed
HH, TE
HH, TE
Applications addressed
- New buildings
- Refurbishment of existing
buildings
Costefficient
yes
yes
- Heating in existing buildings
3
Efficient heating &
cooling
- Water heating
HH, TE
- Centralised air-conditioning
yes
(TE)
- fans in (TE)
- Household appliances
- Green ICT
4
Electricity using appliances
HH, TE
- Lighting
- Commercial refrigeration and
yes
freezing (TE)
- Other motor appliances (TE)
Electric cross-cutting
5
technologies/ meas-
- E-drive system optimisation
IN
ures
6
Process-technologies
and CHP
- Electric drives
yes
- Industrial lighting
- Process technologies
IN
- CHP
yes
- Industrial space heating
- Behavioural changes in pas-
7
Behaviour related
measures
senger and freight road transTR
port
yes
- Modal shift in passenger and
freight road transport
- Technical improvements in the
passenger and freight road
8
Technical and other
improvements
transport
TR
- Motor cycles
yes
- Public transport
- Aviation
- Rail
- Refurbishment of existing
Non cost-effective
9
measures in households and tertiary sector
HH, TE
buildings
- Heating in existing buildings
- Household appliances
no
214
- Green ICT
- Lighting
- Other motor appliances (TE)
- Industrial space heating
- Process technologies
- Technical improvements in the
passenger and freight road
Non cost-effective
10
measures in industry
and transport
IN, TR
transport
no
- Motor cycles
- Public transport
- Aviation
- Rail
Combining the rearranged wedges and putting them into relation to the PRIMES
2009 baseline illustrates that the bulk of energy demand reduction up to 2020
could potentially be realised through conversion savings (see Figure 5-9). Only a
single efficiency wedge would be required to achieve the 20 % savings objective
(considering the assumptions regarding the fuel mix as explained in 4.1.4).
Figure 5-9:
Overview of the primary energy savings through conversion savings
and rearranged wedges
215
Assuming a less ambitious shift towards a high-efficient electricity generation mix
might necessitate the realisation of a number of additional wedges in order to attain
the efficiency target. Figure 5-10 illustrates that up to six wedges would be required
in order to lower primary energy demand to the 1602 Mtoe the European Commission is aiming for.
Given the fact that the determination of the primary energy saving potential was
calculated by means of the ambitious conversion efficiency from the “EU long-term
scenarios 2050” study, a less ambitious efficiency would result in higher saving
potentials. Hence, less than six wedges might be necessary in order to comply with
the efficiency target.
Figure 5-10:
Overview of primary energy savings through rearranged efficiency
wedges and conversion savings
Table 5-6 gives a quantitative overview of the rearranged wedges in order to better
understand to which extent the rearranged wedges imply energy savings, GHG
emission reductions and trigger financial benefits.
Even though it is difficult to rank the rearranged wedges regarding their merits and
drawbacks, Table 5-6 provides the information that wedge two (refurbishment of
existing buildings), seven (behaviour related measures in the transport sector) and
eight (technical and other improvements in the transport sector) have the strongest
impact on final as well as primary energy demand reduction and on GHG emission
mitigation while triggering important financial benefits – from a 2020 point of view.
216
In the long-run, wedge six (industrial process technologies and CHP) can deliver
the highest final as well as primary energy savings.
Summarizing the results of chapter 5 clearly underlines that both, final energy related efficiency measures as well as a high efficient electricity generation mix, deliver substantial primary energy savings and emission reductions. Nevertheless, in
a long-term perspective up to 2050 final energy efficiency measures contribute the
bulk of energy savings and emission reductions. On the one hand side this has a
direct impact on the competitiveness of the European economy and on the other
hand side this is substantial to ensure security of supply.
217
Table 5-6:
Overview of energy saving and emission reduction potentials of the newly arranged wedges (the fields pointed out in
red/green feature the highest energy savings/benefits in 2020/2050; negative values represent financial benefits)
Final energy savings [Mtoe]
Energy saving costs
[bn €’05]
Primary energy savings [Mtoe]
GHG emission reduction [Mt CO2-eq]
2020
2030
2050
2020
2030
2050
2020
2030
2050
2020
2030
2050
1 - New buildings (HH, TE)
34
48
55
-10
-22
-38
42
58
61
75
99
79
2 - Refurbish. existing build. (HH, TE)
46
70
119
-16
-33
-64
53
80
131
106
157
198
3 - Eff. heating and cooling (HH, TE)
30
63
84
-13
-32
-59
40
76
94
73
140
134
4 - Electricity using appliances (IN)
11
24
31
-12
-28
-37
23
40
38
32
53
8
5 - Electric cross-cutting techn. (IN)
15
21
46
-16
-23
-53
32
36
57
45
47
12
6 - Process-technologies & CHP (IN)
30
49
125
-13
-22
-53
37
57
135
91
144
325
7 - Behav. related measures (TR)
47
46
67
-47
-54
-92
50
49
69
155
151
212
8 - Technical improvements (TR)
42
74
86
-34
-62
-118
46
80
89
137
242
265
9 - Non cost-effective (HH, TE)
27
54
8
7
8
4
38
70
10
66
114
2
10 - Non cost-effective (IN, TR)
35
55
49
22
29
23
42
62
53
108
165
124
Total
317
502
671
-131
-239
-488
404
608
736
886
1312
1359
218
Annex I Scenario descriptions
Study
Scenario
Scenario description
Scenario of the EU energy system under current trends and policies; includes current trends on
PRIMES, Base- 2009 Basepopulation and economic development including the recent economic downturn; includes national
line
line 2009
and EU policies and measures implemented until April 2009.
(European
Same macroeconomic, price, technology and policy assumptions as the baseline; includes policies
Commission,
adopted between April 2009 and December 2009; assumes that national targets under the RES DiReference
2010)
rective 2009/28/EC and the GHG effort sharing Directive 2009/406/EC are achieved in 2020.
In the Reference scenario policies are continued as defined in the year 2007. There are no GHG
emission targets defined for the longer term i.e. for the years 2020 and 2050. It is assumed that cliReference
mate change is actually occurring i.e. the world is facing an increase of temperature by +4-degree
European
Celsius by 2100 compared with pre-industrial levels.
Commission,
The first 2-Degree scenario aiming on a concentration of 450 ppm CO2eq in the long run. After 2008
ADAM
450ppm
mitigation policies are implemented and climate change is successfully limited to +2°C (50% likeli(ISI, 2009c)
hood), such that adaptation impacts to climate change remain very limited.
The second 2-Degree scenario, targeting a concentration of 400ppm CO2eq providing a 70% likeli400ppm
hood that the 2°C target is achieved.
The Reference projection describes a continuation of existing economic and technological trends,
Reference
including short-term constraints on the development of oil and gas production and moderate climate
policies for which it is assumed that Europe keeps the lead.
European
Commission,
The hydrogen scenario is derived from the carbon constraint case, but also assumes a series of
WETO-H2
Hydrogen
technology breakthroughs that significantly increase the cost-effectiveness of hydrogen technologies,
(European
case (H2)
in particular in end-use. The assumptions made on progress for the key hydrogen technologies are
Commission,
deliberately very optimistic.
2007)
Carbon
This scenario explores the consequences of more ambitious carbon policies that aim at a long-term
constraint
stabilisation of the concentration of CO2 in the atmosphere close to 500 ppm by 2050.
case (CCC)
IEA, World EnCurrent
A baseline in which only policies already formally adopted and implemented are taken into account
219
Study
ergy Outlook
2010
(IEA, 2010a)
Scenario
policies
scenario
(CPS)
New
policies
scenario (NPS)
450ppm
IEA,
Energy
Baseline
Technology
Perspectives
2010
BLUE Map
(IEA, 2010c)
Greenpeace,
Energy
[R]evolution
(Greenpeace,
2010)
Reference
Advanced
Energy
[R]evolution
ECF, Roadmap
Baseline
2050
(Reference)
(ECF, 2010)
Assumes the introduction of new measures (but on a relatively cautious basis) to implement the
broad policy commitments that have already been announced, including national pledges to reduce
greenhouse-gas emissions and, in certain countries, plans to phase out fossil energy subsidies.
This scenario sets out an energy pathway consistent with the goal of limiting the global increase in
average temperature to 2°C, which would require the concentration of greenhouse gases in the atmosphere to be limited to around 450 ppm CO2-eq. Its trajectory to 2020 is somewhat higher than in
WEO-2009, which started from a lower baseline and assumed stronger policy action before 2020.
The decline in emissions is, by necessity, correspondingly faster after 2020.
This scenario assumes that no new policies are introduced and follows the WEO 2009 Reference
scenario to 2030.
This scenario assumes that global energy-related CO2 emissions are reduced to half their 2005 levels by 2050 and is broadly optimistic for all technologies.
This scenario is based on the reference scenario published by IEA in World Energy Outlook 2009.
This only takes existing international energy and environmental policies into account. Its assumptions
include, for example, continuing progress in electricity and gas market reforms, the liberalisation of
cross-border energy trade and recent policies designed to combat environmental pollution. The Reference scenario does not include additional policies to reduce greenhouse gas emissions. As the
IEA’s projection only covers a time horizon up to 2030, it has also been extended by extrapolating its
key macroeconomic and energy indicators forward to 2050.
The advanced Energy [R]evolution scenario is aimed at a very ambitious decrease in CO2 emissions
(195 million tonnes in 2050). All general framework parameters such as population and economic
growth remain the same as in the Reference scenario.
This scenario is based on sources like the IEA’s WEO 2009, UN or Oxford Economics, while detailed
breakdowns and interpolations have been developed by the project team. Economic growth by sector
and region is based on Oxford Economics and WEO 2009, and shares of energy and power demand
and supply by region based on PRIMES. Growth in demand and emissions from 2030 to 2050 is ex-
220
Study
Scenario
80% RES
Baseline
(Reference)
I-TREN2030
(i-TREN, 2010)
Integrated
Transport
policies
Reference
HOP!
(TRT, 2008)
150 Smooth
European Comission, EU Energy Roadmap
2050
(European Commission, 2011a)
220 Smooth
Reference
Current
Policy Initiatives
Energy efficiency
trapolated using similar trends in energy, power and emissions intensity as 2010 to 2030.
Main focus on power sector, where 80% of power capacities consist of RES, 10% of CCS and 10%
of nuclear power. Fossil fuel prices are modelled as per the IEA WEO 2009 “450 Scenario” (which
projects lower future prices than the WEO 2009 “Reference” scenario due to the assumption of lower
future demand). The WEO 2009 projections carry out to 2030, after which prices have been assumed
to stay flat in real terms through 2050.
The Reference Scenario is not intending to provide forecasts of the most likely future. It is built on the
assumption of frozen policy as of 2008 i.e. only policies are included that are decided by EU Council
or EU parliament until mid 2008. It is model-based i.e. driven by the inherent and harmonised trends
of the iTREN-2030 model suite. The economic crisis is not considered.
The Integrated Scenario builds on the Reference Scenario. It includes energy and transport policies/measures that will be taken between 2008/2009 and 2025. Policies should be: relevant and
likely. The policies reflect the pressures and opportunities coming from the three major policy drivers
of the next two decades: climate policy, fossil fuel scarcity, new technologies. The economic crisis of
2008/2009 is included.
The scenario Ref 70 (Reference Scenario) assumes high amounts of oil reserves and can be seen
as an optimistic scenario. It reaches an oil price of about 70 €2000/bbl in 2020, smoothly rising to
140 €2000/bbl by 2050. Investment in energy efficiency and alternative energy sources follows common trend. Taxation takes the current excise duties plus the changes through the diesel directive into
account. A carbon dioxide value rising from 5 €/t CO2 to 30 €/t CO2 is taken into consideration.
The scenario 150 Smooth assumes a smoothly increasing oil price which reaches a level of 150
€2000/bbl in 2020. This leads to increased investment in energy efficiency as well as in alternative
sources.
220 Smooth investigates a higher oil price than 150 Smooth (> 220 €/bbl in 2020).
Scenario includes national and EU policies and measures implemented until March 2010 .
The scenario includes measures adopted and being proposed in the context of the “Energy 2020
communication”.
Normative scenario aiming on 85 % energy related CO2 emission reduction by 2050, in particular by
means of energy efficiency options.
221
Annex II Overview of potential wedges for in-detail
analysis
II.I Introduction
This paper presents a first choice of energy efficiency “wedges”. According to S.
Pacala und R. Socolow wedges are subdivisions of necessary energy savings into
comparable units (Pacala, 2004). These units are sufficiently small so that they
represent a single technology or a selection of technologies that can be tackled
with well-defined policy packages but still represent ambitious levels of savings.
The aim of the subdivision is to identify different options for action and to show that
the target can be achieved.
Figure II-1: Definition of “wedges”
The final selection of wedges once made by the client (Federal Ministry of Environment) will determine which wedges will be analysed in further detail in the context of work packages 1.3 to 3.
The document mainly consists of a table presenting a larger number of potential
wedges covering different sectors (section II.III). Beforehand a short overview of
the historic evolution of final energy demand in EU27 is given. The main arguments
for the wedges chosen are summarized in section II.IV.
222
II.II Historic development of primary and final energy demand
in the EU27

According to Figure II-2 both primary energy and final energy demand
seem to saturate in the EU27 since a few years. The total final energy
demand increased still a bit before 2004 from 1,100 up to nearly 1,200 Mtoe
but now seems to have reached a plateau. The 2009 values (not shown
here) are considerably lower due to the impacts of the economic crisis. This
saturation is a bit less emphasised when looking at the data corrected for
annual climate variations and needs to be confirmed in the coming years.

While according to the PRIMES-2007 projections (European Commission,
2008) both, final and primary energy, are still on the rise up to 2030 (Table
II-1), they are projected to stagnate in that period in the most recent
PRIMES projections (European Commission, 2010) confirming that a decoupling of economic growth and energy consumption is taking place.
Table II-1:
Projections of primary and final energy of the EU27 according to the
PRIMES projections
EU27: Baseline 2007
Mtoe
2000
2005
2010
2015
2020
2025
2030
Gross Inland Consumption
1712
1811
1852
1929
1971
2003
2007
Final Energy Demand
1103
1162
1234
1300
1346
1381
1404
Mtoe
2000
2005
2010
2015
2020
2025
2030
Gross Inland Consumption
1723
1826
1767
1810
1828
1823
1813
Final Energy Demand
1113
1174
1169
1211
1229
1227
1216
EU27: Baseline 2009
Source: (European Commission, 2008), (European Commission, 2010)
223
Figure II-2: Total final and primary energy demand in EU27
Final/primary energy consumption [Mtoe]
1900
1800
1700
1600
Total primary consumption
Total primary consumption with climatic corrections
Total final consumption
Total final consumption with climatic corrections
1500
1400
1300
1200
1100
1000
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
Figure II-3:
Primary energy demand by type of energy carrier in EU27
100%
Industrial Solid Waste
80%
Other Renewable Energies (wind, hydro, solar
thermal, PV, geothermal)
Renewable Energies (biogas)
Renewable Energies (biofuels)
60%
Renewable Energies (solid biomass/wastes)
Electrical Energy (net imports/exports)
40%
Nuclear Energy
Gas
20%
Crude oil and Petroleum Products
Solid fuels (lignite and dervatives)
0%
2000
2001
2002
-20%
Source: (Eurostat, 2011)
2003
2004
2005
2006
2007
2008
Solid fuels (hard coal and dervatives)
224
The split of the primary energy consumption by energy carrier (Figure II-3) shows
that in the period 2000-2008 the share of renewable energy sources has been increasing from 5.7 to 8.4 %, mainly at the expense of solid fuels, petroleum products and nuclear energy.
Figure II-4 to Figure II-7 show the historic evolution of final energy demand in EU27
from 2000 to 2008 by sector.
Figure II-4: Total final energy demand in EU27 by sector
Source: Eurostat
The total final energy demand is distributed on three main sectors:
•
Industry sector (318 Mtoe in 2008, equal to 27 % of total final energy demand): the bulk of this energy amount (about 60 %) is consumed by iron
and steel, chemical, non-metallic mineral as well as paper and pulp industry. All the industry branches show a constant energy demand over the past
years. Only for 2008, a slight decrease in demand can be observed due to
the economic crisis. This is further accentuated in 2009.
•
Transport sector (374 Mtoe, equal to 32 %): the main share of final energy
consumption (more than 80 %) arises from road transport. Consequently
the main final energy carrier in this sector consists of oil derivatives such as
diesel and petrol. Over the past years the road transport sector experienced
a further increase of about 9 % compared to the year 2000. It is unclear yet
whether the saturation observed since 2007 is due to the high oil prices and
will be a lasting effect.
•
Household, services and other sectors (477 Mtoe, equal to 41 %): the
household sector is the most energy consuming sector in 2008 due to high
225
energy demand for residential space heating (about two thirds of all energy
consumed in the residential sector) and high electricity demand in the service sector. Fluctuations in the final energy demand are mainly linked to
fluctuations in the demand for space heating due to climatic reasons (e.g.
2007 as a particularly hot year in the European average).
Figure II-5: Final energy demand in the industry sector in EU27
Figure II-6:
Final energy demand in the transport sector in EU27
226
Figure II-7:
Final energy demand in the household, service and other sectors in
EU27
II.III Selection of wedges
In this section a number of wedges are presented. They present the basis for a
final choice of wedges that shall be discussed in further detail within the next work
packages. The wedges shown in the table were preselected according to the discussions held with the client on November 8th 2010.
All wedges are grouped according to the different sectors (see first column). For
every wedge the main features and technologies are shortly summarised in the
second column. The middle columns provide arguments in favour of (“pro” column)
or against the selection of the specific wedge (“contra” column).
Wedges highlighted in light grey are a recommendation of choice made by Fraunhofer ISI balancing the arguments of the “pro” and “contra” columns for this wedge.
Additional charts show historic evolutions or forecasts of key indicators (such as
final energy demand, value added) for specific sectors or subsectors, in order to
make the arguments mentioned in the columns more comprehensible. The forecasts originate from the baseline scenario of the PRIMES 2009 calculations (European Commission, 2010), realized for the European Commission. They show a
future development under the condition that no further policies are included except
national and EU policies implemented until April 2009.
227
In order to estimate the significance of a wedge, a first guess of the technical final
energy saving potential and the corresponding primary energy saving potential 56
by 2030 is compared to the final energy demand in 2008 (last three columns). The
data provided is based on the “Study on the Energy Saving Potentials in EU Member States, Candidate Countries and EEA Countries”, published by Fraunhofer ISI
in cooperation with ISIS (Italy), Enerdata (France), Wuppertal Institut (Germany)
and TU Vienna (Austria) (ISI, 2009a).
 The potentials presented in this overview are based on existing studies.
They are a rough first estimate of technical potentials. A detailed analysis of
the potentials and the assumptions behind the different studies was only
carried out in the framework of work package 1.3. The respective results
can be found in chapter 4. However one should keep in mind that the
potential calculations are based on certain scenario assumptions.
Even technical potentials are limited by “natural” boundaries for the diffusion of single technologies (e.g. reinvestment cycle are kept as they are
with exceptions such as enhanced refurbishment of buildings). For that reason every potential designation is based on an underlying technology mix.
Further information on this topic can be found in section 4.1.
56 The primary energy demand is calculated on the base of an average energy conversion efficiency
of 40% for electricity generating units. Since the composition of the transformation sector is not
analysed in detail, this conversion calculation is a very simplified estimate.
228
II.III.I Buildings
Sector/
Subsector
1
Building
envelope (1)
Heating
and
cooling
systems
(1)
Hot
water (1)
Features/Characteristics
- energy efficient envelope of existing and new buildings:
=> refurbishment of existing dwellings
=> new buildings with nearly zero
energy standard
- generation of space heat
- use of heat pumps, distributed
renewables, energy efficient boilers
- generation of space heat
- use of heat pumps, distributed
renewables, energy efficient boilers
Pro
Contra
- very high energy saving
potential
- increasing number of
dwellings over the past
years
- high potential
- increasing cooling demand
in Southern European countries
- increasing number of
dwellings over the past
years
- medium potential but rather
homogeneous technology
group
- numerous policies already implemented =>
difficult to assess the effect of additional
measures 57
- difficult to define general requirements for all
EU countries due to different climatic conditions
- difficult to make a clear cut between energy
efficiency technologies (such as more efficient
boilers) and RES technologies (such as solar
thermal heating)
- numerous different technologies can be
applied according to the size and the use of
the building
- difficult to make a clear cut between energy
efficiency technologies (such as more efficient
boilers) and RES technologies (such as solar
thermal heating)
Approximate FED in
2008
(Odyssee
database)
200 Mtoe
(space heat
households)
77 Mtoe
(space heat
services)
32 Mtoe
(space heat
industry)
42 Mtoe
(households)
Technical
FE saving
potential
by 2030
Technical
PE savingpotential by
2030 (3)
160 Mtoe
(2)
173 Mtoe
57 Mtoe
62 Mtoe
12 Mtoe
(households)
17 Mtoe
(1) It could be difficult to split off heating systems and hot water from the building envelope
(the Energy performance Directive for Buildings is na integrative approach to the buildings...). An alternative could be to split by sector (households, services, industry)
(2) Includes existing stock and new dwellings in the household
and services sector
(3) Share of electricity for the given use as in 2008. Conversion
with a factor of 2.5.
57 Recast of the EU Energy Performance of Buildings Directive (2010/31/EU), setting up minimum energy performance standards for new buildings and major renovations, with regular updating of these standards.
229
II.III.II Appliances and IT
Sector/
Subsector
2
Pro
Contra
Lighting
- concerns all kind of lighting
- replacement of conventional
incandescent bulbs by energy
saving bulbs, LEDs/OLEDs
Large
household
appliances
- household appliances such as
refrigerators, freezers, washing
machines, dish washer, dryer
- clearly distinguishable
- different policies already
implemented 58
- FED forecast is supposed
to decrease after 2015
- includes computers, monitors,
servers, router, laptops, screens
- increasing demand due to further
diffusion of additional appliances
and increasing significance of the
tertiary sector
- relatively low potential
Green IT
Approximate FED
in 2008
(Odyssee database)
Technical
FE saving
potential by
2030
Technical
2030 (3)
106 Mtoe (electricity demand of
households and
tertiary excl. electric space heating), of which large
HH appliances
excl. TV 16 Mtoe;
TV 4.3 Mtoe; other
IT around 9 Mtoe
19 Mtoe
48 Mtoe
HH (excl.
TV):
6 Mtoe
14 Mtoe
HH+TE
7 Mtoe (incl.
TV)
16 Mtoe
60
270
50
260
40
250
30
240
20
230
10
220
0
1990
1995
2000
2005
2010
Heating and cooling (incl. cooking)
2015
2020
2025
2030
FED - appliances and lighting [Mtoe]
FED - heating and cooling [Mtoe]
Final energy demand forecast residential sector
280
Note: electric cooking and heating is included in the category
heating/cooling. Therefore differences with the figures in the
table
Electric appliances and lighting
Source: (European Commission, 2010)
58 such as the EU Energy Labelling Directive (2010/30/EU) establishing an energy consumption labelling scheme that displays the relative energy efficiency of a
product when offered for sale or rent, and the EU Ecodesign Directive for energy using products (2005/32/EC) that establishes a framework under which manufacturers of energy-using products will, at the design stage, be obliged to reduce the energy consumption and other negative environmental impacts occurring
throughout the product life cycle
230
II.III.III
Sector/
Subsector
Industry sector – Cross-cutting technologies
Pro
Contra
Electric drives
- motors used in industry (fans,
pump systems, cooling devices,
compressed air systems) with a
focus on the motor itself
4
E-drive system
optimisation
- holistic system management approach, considering all the elements
of a technical system
- high potential
- difficult to quantify the potential
- difficult to distinguish the exact system borders in the different applications
5
Steam / hot
water generator
- CHP
- energy efficiency improvement
- high potential
- interference with other technologies
- risk of interference with heat generation from RES
Industrial
dryers
- energy efficiency improvement
- new drying processes
- medium potential
Surface technologies
- includes reduction of surface friction, self-cleaning surfaces, corrosion and deterioration protection
- might become an
important technology in
the long run
- high R&D still needed => deployment
only in the latter decades
3
Approximate
FED in 2008
(Odyssee
database)
- wide spread technology
- high potential
Technical
FE saving
potential
by 2030
Technical
2030 (3)
2 Mtoe
5 Mtoe
17 Mtoe
43 Mtoe
25 Mtoe
25 Mtoe
66 Mtoe
73 Mtoe
231
II.III.IV Industry sector – Process technologies
Sector/
Subsector
Pro
Contra
Approximate FED
in 2008
(Odyssee
database)
Technical
FE saving
potential
by 2030
Technical
2030 (3)
36 Mtoe
6 Mtoe
(4)
11 Mtoe
(4)
- high energy saving potential
(compared to energy demand)
Paper and pulp
production
- energy efficient drying and refining processes, integrated pulp and
paper mills, heat recovery
7
Iron- and steel
production
- energetic optimisation of the blast
furnace, waste heat recovery
- constantly important value
added over the next years
- final energy demand second
most important
- limited energy savings potentials
60 Mtoe
5 Mtoe
(4)
10 Mtoe
(4)
8
Cement industry
- optimised process
- waste heat recovery
- shift to best available technologies (BAT)
- third highest final energy
demand
- relatively constant production
and value added
- limited energy savings potentials
43 Mtoe
1 Mtoe
(4)
2 Mtoe
(4)
Chemical industry
- application of best practice technologies (BPT)
- process intensification/integration
- CHP, recycling, energy recovery
- new separation technologies,
optimize catalytic processes
- high potential
- sector with highest final energy
demand
- relatively high value added
- huge number of technologies
and processes that are used =>
difficult to assess the potential
- several measures need much
further R&D efforts before producing substantial savings
55 Mtoe
1 Mtoe
(4)
2 Mtoe
(4)
6
- high share of electricity consumption
(4) Excludes potentials
from CHP and
cross-cutting technologies
Source: European Commission, 2010)
232
II.III.V Transport sector
Sector/
Subsector
Features/
Characteristics
Pro
Contra
- high potential
- road transports represents
bulk of final energy demand
in transport
9
Road transport
– technical
changes
10
Road transport
– behavioural
changes
- modal shift
- change of behaviour
- high potential
- difficult to assess the potential from behaviour
changing measures
e-Mobility
- shift from conventional
internal combustion
engine vehicles to electric vehicles
- increasing significance
within the next
years/decades, since numerous R&D projects were
initiated
- net efficiency improvements on the primary
energy demand side are not necessarily guaranteed (for a detailed see 4.2.12)
- primary energy savings depend strongly on the
power mix and the conversion efficiency of
power plants => subject of power generation
risks to be mixed up with RES topic
- technical improvements
Approximate FED
in 2008
(Odyssee
database)
Technical
FE saving
potential
by 2030
Technical
2030 (3)
72 Mtoe
72 Mtoe
58 Mtoe
58 Mtoe
304 Mtoe
10 Mtoe
(10% share
of car stock
electric cars;
50% renewables in
power mix)
233
II.III.VI Conversion sector
Sector/
Subsector
11
Energy conversion, transmission and distribution efficiency
Features/
Characteristics
- efficiency improvements of conventional power plants by optimised control
- efficiency improvement in power
and heat transport systems (electricity grids: temperature monitoring, HVDC grids)
Contra
Approximate FED
in 2008
(Eurostat)
- decreasing demand for
additional conventional power
capacity makes analysis less
necessary
Fuel input to
thermal
power
plants: 412
Mtoe
Pro
- mainly in Eastern Europe the
average conversion efficiency of
power plants is relatively low =>
high energy saving potential
- bulk of electricity grid needs to be
renewed within the next decade
- CCS may drive the consumption of those plants up
- difficult to assess the energy
saving potential of HVDC or
other grid types
- risks to be mixed up with
power generation from RES
(5) Out of the 93 Mtoe around 50 Mtoe are in refineries which increasing energy consumption trends due
to sulphur legislation for transport fuels
(6) It is assumed that new power plants will be built according to the best efficiency available. No potential
from using gas instead of coal power plants is included as it is assumed that the choices among fuels
occur autonomously. From the fossil fired plants only around 1/3 will still be running in 2030. It is assumed that around 4% of the fuel inputs can be saved, e.g. through improved regulation of the plants
with IT technologies
Energy
sector consumption:
93 Mtoe (5)
Grid losses:
26 Mtoe
Technical
FE saving
potential
by 2030
Fuel input
to thermal
power
plants:
(6 Mtoe)
Energy
sector
consumption: small
Grid
losses:
6 Mtoe
Technical
2030 (3)
Fuel input to
thermal
power
plants:
6 Mtoe
Energy
sector consumption:
small
Grid losses:
14 Mtoe
234
II.IV Summary of potential estimation
A short overview of all the wedges presented in the sections II.III.I to II.III.VI can be
found in Table II-2, sorted by decreasing technical final energy saving potential. In
the following we provide a summary of the arguments for the selection and raise a
few questions for further discussion.
The energy saving potential of the buildings envelope is the biggest one among all
sectors and is recommended. Second follows the heating and cooling systems in
the building sector. However this wedge is not recommended for a further analysis
since the scope of energy efficiency technologies that can be applied in this sector
is large (large number of heating systems). Moreover, it is difficult to distinguish
explicitly efficiency technologies, considering RES as alternative technologies that
might be deployed in this area. This also holds for sanitary hot water preparation in
the residential sector.
 It may, however be discussed in how far distributed renewables should be
considered as being part of the wedges.
 It may further be discussed, in view of the fact that the Energy Performance
Directive for Buildings works on a primary energy integrative basis (the
building including the heating system is considered as a unit) whether it
makes more sense to split the two wedges rather by sector (residential,
service sector and industrial sector buildings) and concentrate for example
on the first or the first two.
In contrast, most of the other high potential technologies, promising energy saving
between 10 and 90 Mtoe, are recommended to be further examined. Not only is
there a high energy saving potential, but also those are widely spread over different sectors which is an important driver for this choice. In order to avoid large saving efforts from single sectors, the wedges cover more or less equally the different
main energy consuming sectors: buildings envelope in residential, tertiary and industry sector (170 Mtoe technical final energy saving potential by 2030), transport
sector (160 Mtoe), industry sector (71 Mtoe).
A rough energy saving estimation for the energy conversion and transport sector
was carried out which showed that the major focus could be on electricity transport
and distribution losses. This wedge is recommended due in order to have one
wedge on the transformation sector and in order to show its limited importance.
 This sector may still be completed with estimates concerning district heating
losses. However, district heating is seen as a technology with limited scope
given the spread of near-zero energy houses.
235
Table II-2:
Overview of energy efficiency wedges, sorted by decreasing saving potential (estimated numbers; entries highlighted in
grey are recommended by Fraunhofer ISI for a more detailed analysis within the framework of work package 1.3)
Approx. FE saving potential
[Mtoe]
160
Approx. PE saving potential
[Mtoe]
173
Road transport – technical improvements
72
72
Road transport – behavioural changes
58
58
Buildings
57
62
Industry – cross-cutting technologies
Energy efficient dryer and steam / hot water generator
25
25
Appliances and IT
Lighting (in residential, tertiary and industry sector)
19
48
Industry – crosscutting technologies
System optimisation of electric drive systems
17
43
Buildings
Sanitary hot water
12
17
Energy conversion
Energy conversion, transport and distribution
(12)
20
Industry – process technologies
Paper and pulp production
6
11
Appliances and IT
Green IT (in residential and tertiary sector)
7
16
Appliances and IT
Big household appliances
6
14
Iron and steel production
5
10
Industry – cross-cutting technologies
Energy efficient electric drives
2
5
Cement industry
1
2
Chemical industry
1
2
Sector
Technologies
Buildings
Building envelope
Transport
Transport
Transport
e-Mobility
n/a
Industry – crosscutting technologies
Surface technologies
n/a
Sum – selected wedges
Sum – all wedges
375 (32 % of the final energy 2008
excl. the conversion efficiency wedge)
460 (39 % of the final energy 2008
excl. the conversion efficiency wedge)
422 (23 % of the primary energy
2008)
578 (32 % of the primary energy
2008)
236
 It is supposed that new power plants will rely on renewable energy sources
or that they will be replaced by fossil-fired plants featuring the maximum
possible efficiency for a given fuel. The fuel choice is considered to be market driven. To be further debated.
All proposed wedges sum up to a total technical energy saving potential of
441 Mtoe by 2030, or 429 Mtoe if the conversion wedge is excluded. The latter
figure corresponds to a 37 % decrease in final energy demand compared to 2008
(1169 Mtoe according to Eurostat). If all wedges are included this percentage
raises to 47 %). In primary energy terms the reduction by the technical potentials is
30 % in 2030 respectively proposed for the wedges and 39 % for all wedges considered. In view of 2050 these wedges may therefore be suitable steps to achieve
the required 50 % reduction.
The reduction is smaller in primary energy terms due to the fact that there are only
small options for energy efficiency on the supply side and that most of the improvement would come from renewables and from the autonomous replacement of
old with new power plants. However, quite a substantial contribution to the reduction of primary energy would come from the penetration of renewables in the power
sector given that most renewables are counted with an efficiency of 100 % in the
power supply.
237
Annex III Methodology of the economic potential of CHP
plants
In the following the calculation methodology for the determination of the economic
potential of combined and power plants is explained.
As already mentioned in section 4.2.7, the additional investments for a CHP plant
are equal to zero or even below, compared to the construction of two SHP plants
with the similar capacity. However, there are other factors that influence the costeffectiveness of a CHP plant:
•
fuel mix of the CHP plant
•
fuel mix of the SHP plant that would have been built instead
•
fuel prices
•
energy conversion efficiency of the CHP and the SHP plant (which are directly influencing the final price for the electricity and heat produced).
Table III-1: Fuel mixes in the different CHP scenarios
Scenario
New SHP plants displaced
New CHP plants built instead
Energy
carrier
Share
Energy
carrier
Share
1
Coal
100%
Gas
100%
2
Coal + CCS
(beyond 2030)
100%
Gas
100%
3
Gas
100%
Gas
100%
Gas
100%
Coal + CCS
4
5
(beyond 2030)
50%
Gas
50%
Coal + CCS
(beyond 2030)
50%
Gas
20%
Gas
50%
Biomass
80%
238
Five scenarios have been analysed that vary the parameters mentioned above in
order to trace out the whole range of specific costs/savings through energy efficiency improvement of CHP plants as well as further CHP diffusion. Table III-1
shows the assumptions regarding the fuel mix. The fuel prices are supposed to
develop in all scenarios as mentioned in section 4.1.2. For CHP as well as for SHP
plants, a steady conversion efficiency increase is supposed to occur. Only for coal
power plants equipped with CCS, efficiency drops instantaneously by 2030, when
the technology is newly applied, but rises again afterwards due to technological
learning.
Figure III-1 summarises the results of the parameter variation. As can be clearly
seen, CHP features the highest cost reduction through energy savings in scenario
3. This is due to the fact, that the fuel costs for SHP and CHP plants are the same
since the same fuel is used, but CHP benefits from its increasing efficiency improvement.
A less favourable situation is drafted in scenario 5. CHP plants initially benefit from
low biomass prices that are rising the attractiveness of investing in CHP plants. At
the same time, new SHP plants become progressively competitive, given the fact
that the coal price does not experience the same price increase as gas and biomass. The introduction of CCS with its accompanying conversion efficiency drop
has only a minor effect on the overall cost-effectiveness of CHP. Scenario 5 is
supposed to be the most likely one. Thus it is used in all further economic potential
summation on a higher aggregated level (cf. section 4.4.1 and 5.1).
Scenario 4, 2 and 1 are drafting step-wise less favourable framework conditions for
the diffusion of CHP. In scenario 4, CHP loses its winning margin from scenario 5
since the original biomass share is replaced by additional more expensive gas.
The situation is even deteriorating in scenario 2, when SHP plants entirely run on
low-cost coal. Only the introduction of CCS by 2030 permits no further cost increase for CHP compared to the coal-fired separate generation of heat and electricity.
If no CCS is applied on the SHP plants (scenario 1), the price spread between coal
and gas is further rising, making an investment in CHP plants not attractive at all, if
no financial incentives are set by politics.
239
Figure III-1: Cost curves for the different CHP scenarios
240
Annex IV Energy savings through electric vehicles
The energy saving results mentioned in the fact sheet on e-Mobility (cf. 4.2.12), are
based on various assumptions that can be distinguished into two types.
The first type of assumption is dealing with the specific energy savings (i.e. unit of
energy saved per km or mile) of an electric or plug-in hybrid car compared to a
conventional car with internal combustion engine. It considers the entire energy
conversion chain from the raw energy carrier over the actual “tank” to the wheel.
The calculation methodology of the specific savings as well as the underlying assumptions is discussed in Annex IV.I.
The second type of assumption deals with the multipliers that permit to deduce the
overall energy savings from the specific ones. These assumptions depend on the
scenario definition and are listed in Annex IV.II.
IV.I Detailed calculation methodology
As mentioned before, the e-Mobility analysis is largely based on a life cycle assessment study carried out by Fraunhofer ISI and Ludwig-Bölkow-Systemtechnik
GmbH (ISI, 2010). Hence, only the main assumption and methodology is explained
in the following. Any further details can be found in the underlying study.
The fuel consumption of the various drive concepts and car types (apart from medium-sized passenger cars and LDVs, the Fraunhofer ISI report also analysed
compact cars, buses and inland water vessels) was carried out by analysing the
conversion efficiency of the final energy supply chain (i.e. the Well-to-Tank chain)
and an assessment of the fuel consumption and potential savings of the actual
drive train (i.e. the Tank-to-Wheel chain).
Well-to-Tank
The car fuels considered in this analysis are gasoline, diesel as well as electricity
based on the EU27 electricity generation mix. The average efficiency of the respective production pathways is shown in
Figure IV-1. The refining process for gasoline and diesel does not differ between
2015 and 2030 and features an efficiency of 88 % and 86 % respectively.
241
Figure IV-1: Mean energy conversion efficiencies for the Well-to-Tank chain
Source: (ISI, 2010), adapted
Regarding the European power generation mix an adaptation of the fuel shares
and average conversion efficiencies was conducted for the time 2015 until 2050,
referring to the EU27 electricity generation mix from the Trans-CSP scenario which
was provided by the German Aerospace Centre (DLR, 2006), cf. Figure IV-2. The
average conversion efficiency of the European electricity mix is supposed to improve from 47 % in 2015 up to 55 % in 2030 and 75% in 2050. This is related to
the rising share of RES and efficient gas power plants. Grid losses at the 0.4 kV
voltage level are estimated to the electricity transmitted by approximately 5 %. Particularly high grid losses for an increasing share of electricity imports, e.g. from
Northern Africa, were not considered.
242
Figure IV-2: Electricity generation by energy carrier, TRANS-CSP scenario, EU27
Source: Based on (DLR, 2006)
Tank-to-Wheel
For the different car types and drive concepts, individual average fuel consumptions were assumed, as can be seen in Figure IV-3. For gasoline fuelled passenger
cars, the average fuel consumption is supposed to decline from approximately 5.9
l/100 km in 2015 to 4.5 l/100 km in 2030 59. Hybrid electric vehicles, that are supposed to substitute new gasoline cars by 2030, feature savings of 15 % compared
to pure ICE driven cars.
PHEVs are assumed to cover 60 % of the overall fuel consumption with electricity.
Their efficiency is further increasing between 2015 and 2030, whereas the efficiency of electric vehicles is supposed to remain constant. This is due to the assumption that the conventional drive train experiences further efficiency improvements while the electric drive train has already attained its maximum. It is obvious
that this is a strong simplification, since further improvement is supposed to occur,
above all in the field of battery technologies. Nevertheless, this assumption can be
justified against the background of a rather conservative assessment approach.
For the time beyond 2030 no further efficiency are supposed to occur – neither for
conventional nor for electric cars.
59 Assuming a conversion factor of 9.01 kWh/l of gasoline and of 9.96 kWh/l of diesel, as published
by the German association “Arbeitsgemeinschaft Energiebilanzen“, (AGEB, 2012)
243
With regard to the determination of the specific fuel savings, BEV and PHEV are
supposed to substitute gasoline fuelled cars with a conventional ICE drive until
2015. Afterwards, HEV technology is assumed to be the predominating drive concept which serves as basis comparison.
Figure IV-3: Tank-to-Wheel energy consumption of various car types
Well-to-Wheel
Figure IV-4 depicts the specific well-to-wheel energy consumption of a mediumclass passenger car. As can be clearly seen, the PHEV is favourable in comparison with the conventional ICE car due to a 60 % electricity share of the total consumption. By 2015, the combination of gasoline and electricity based on the European electricity mix leads to a reduction of overall energy demand of about one
third. It is assumed that battery research will not progress as much as it is necessary in order to conceive battery stacks with a sufficient storage capacity for long
distances. Thus, until 2015, BEV technology is only supposed to enter the compact
car market due to the characteristically short distance rides, whereas the PHEV
configuration does not represent a realistic option.
By 2030, the spread of energy consumption among the different drive concepts
declines due to further efficiency improvements of conventional engines by up to 33 % compared to 2015. This phenomenon is also linked to the fact that gasoline
cars are supposed to feature a hybrid drive train as standard configuration, reduc-
244
ing the fuel consumption by roughly 15 % simply through energy recuperation. In
2030, BEV technology has reached the level of technological maturity to be applied
in medium-sized cars. PHEVs experience a further improvement of the overall efficiency of 15 to 20 %. This improvement is related to improvements of the conventional ICE engine whereas the electric drive train is not supposed to undergo further improvements. However, the increase in the overall conversion efficiency of
the European electricity generation mix due to an increase in power generation
from renewable energy sources and high efficient gas power plants also benefits
electric cars. This effect persists until 2050, further reducing the energy demand of
electric vehicles whereas the efficiency of conventional drive technologies is supposed to stagnate at the level of the year 2030.
Figure IV-4: Energy consumption of passenger cars with different drive concepts
(well-to-wheel)
IV.II Scenario assumptions and results
In order to calculate the final and primary energy savings presented in 4.2.12, assumptions regarding the specific consumptions of future vehicles and the evolution
of the stock turnover need to be made.
Regarding the stock turnover of the European car fleet a differentiation of two scenarios was carried out: a moderate scenario, aligned with a study from the EWI
245
institute (EWI, 2010) as well as an Ambitious scenario which was inspired by a
study from Fraunhofer ISI (ISI, 2008).
Table IV-1: Scenario assumptions for the Moderate and the Ambitious scenario
Moderate scenario
Total car stock in 2050
Share of electrification in 2050
Average yearly mileage per
vehicle
Ambitious scenario
280,000,000 (ISI, 2009c)
30 %
68 %
14,000 km (EWI, 2010)
Useful life time
12 years
For both scenarios, apart from the data shown in Table IV-1, the following assumptions were made:
•
Only passenger road transport is considered
•
All passenger cars feature the specific consumption of mid-range cars
•
Battery electric as well as plug-in hybrid vehicles are supplied by electricity
from the European electricity mix which is based on the Trans-CSP study of
DLR (DLR, 2006).
The energy savings through electric passenger cars were determined by considering a certain share of the newly registered cars being electric vehicles that would
stepwise replace new conventional cars.
Multiplying the number of new electric vehicles that replace the respective number
of conventional vehicles in one year by the average mileage and the average fuel
savings of this year permits the determination of the yearly savings through the
new electric cars in this year. Summing up the savings of all new electric cars over
the total period under review allows an estimation of the overall energy saving potential, see Table IV-2.
246
Table IV-2: Assumptions and results of the two e-Mobility scenarios
Moderate scenario
Ambitious scenario
2020
2030
2050
2020
2030
2050
Total number of
BEVs [M]
0.2
2.3
41.8
0.1
0.6
93.0
Total number of
PHEVs [M]
0.2
2.3
41.8
3.4
30.4
97.7
Final energy savings [Mtoe]
0.1
1.0
15.9
0.8
4.9
35.9
Primary
energy
savings [Mtoe]
0.1
0.7
15.6
0.7
4.2
35.5
Related electricity
demand [TWh]
0.6
7.5
140.4
4.3
39.5
318.3
Given the fact that the electric vehicles are partially or fully fuelled by electricity, an
increase of electricity demand will occur (cf. Figure IV-5). In the Moderate scenario
the additional electricity demand will equal some 8 TWh by 2030, whereas the Ambitious scenario makes the demand grow to 40 TWh. Compared to the net electricity consumption in 2030 in the PRIMES baseline scenario of 3517 TWh, the electric
vehicles would account for some additional 0.2 % and 1.1 %. For 2050, electricity
demand rises up to 140 TWh and 319 TWh respectively.
Figure IV-5: Electricity demand through electric vehicles
247
Annex V Electricity saving potentials
A particular view is taken in this section on the issue of electricity savings and the
question how the savings relate to the electricity consumption pathway of the
PRIMES 2009 baseline as well as the consumption pathway outlined in the “EU
Long-term scenarios 2050” project, that is likewise carried out by Fraunhofer ISI on
behalf of the German Federal Ministry for the Environment.
Figure V-1: Electricity saving potential compared to the PRIMES 2009 baseline
Source: (European Commission, 2011a), Fraunhofer ISI
In order to determine the remaining gross electricity consumption, the following
calculation procedure was run through:
•
In a first step, the PRIMES 2009 baseline was extrapolated for the time beyond 2030 using the electricity consumption indicator from the ADAM reference scenario (ISI, 2009b).
•
Given the fact that the ADAM 450 ppm scenario (ISI, 2009c) which represents the basis for scenario A of the EU Long-term Scenarios 2050 study,
considers a more significant share of electric vehicles and heat pumps 60,
60 In 2050, the ADAM 450ppm scenario considers some additional 60 TWh of electricity consumption
for ca. 23 Mio additional electric vehicles and about 68 TWh of additional electricity consumption
for heat pumps in the households and tertiary sector.
248
the baseline consumption was adjusted by adding the respective additional
electricity consumption.
•
For the period up to 2030 the electricity saving potential that was determined in (ISI, 2009a) was deduced from the gross electricity consumption
reported in (PRIMES, 2009), giving the “remaining electricity demand”.
•
For the years 2030 up to 2050, the electricity saving potential was determined by carrying out an additional calculation: by means of indexing, the
“remaining electricity demand” from the step before was extrapolated, using
the trajectory from the ADAM-400ppm scenario (ISI, 2009c). The difference
of this time-series and the extrapolated baseline from step one resulted in
the electricity saving potential until 2050.
Figure V-1 shows that if substantial electricity saving measures are undertaken, the gross electricity consumption in the EU-27 by 2050 can be reduced
to less than 2500 TWh which is 9 % below the value of the year 2000. This is in
line with the electricity consumption of scenario A presented in the “EU Long-term
249
References
ABB. (2007). Energy Efficiency in the Power Grid. Norwalk.
Adnot, J. (1999). Limiting the Impact of Increasing Cooling Demand in the European Union: Results from a Study on Room Air-Conditioner Energy Efficiency.
Paris.
Adnot, J.. (2003). Energy Efficiency and Certification of Central Air Conditioners
(EECCAC) - Final Report. Paris.
Adnot, J. (2004). Technisches Modul zum Thema Klimatisierung. Paris.
AGEB. (2012). Einheitenumrechner. Arbeitsgemeinschaft Energiebilanzen.
http://www.ag-energiebilanzen.de/viewpage.php?idpage=67. Accessed March 13,
2012. Berlin.
Almeida, A. (2000). VSDs for electric motor systems. Coimbra: ISR-University of
Coimbra.
Almeida, A. (2001). Improving the penetration of energy-efficient motors and
drives. Coimbra: University of Coimbra.
Almeida, A. (2008). Preparatory study for the Energy Using Products (EuP) Directive - Lot 11: Motors. Coimbra.
APS. (1999). Energy Answers: Energy-Efficient Home Appliances. Arizona: Arizona Public Services Company.
ATKearney. (2009). Energiewirtschaft macht mobil. Düsseldorf.
Bertoldi, P. (2006). Residential Lighting Consumption and Saving Potential in the
Enlarged EU. Brussels: European Commission – DG Joint Research Centre, Institute for Environment and Sustainability, Ispra. Proceedings of EDAL'06 Conference, London, UK, 21-23.06.2006.
BIOIS. (2007). Preparatory Studies for Eco-design Requirements for EuP – Lot 12:
Commercial refrigerators and freezers. Paris: Bio Intelligence Service.
BITKOM. (2008). Energy efficiency in the data centre. Berlin: BITKOM.
Blum, O. (2007). Revision of Best Available Technique Reference Document for
the Pulp & Paper Industry: Use of Energy Saving Techniques. München: Papiertechnische Stiftung.
BMU. (2009). Energieeffiziente Rechenzentren - Beispiele aus Europa, USA und
Asien. Berlin: BMU.
250
Bührer, C.; Hagemann, H. (2009). Efficient magnetic billet heating by direct current.
Elektro Wärme International – Zeitschrift für elektrothermische Prozesse 2 2009.
Bundesregierung Deutschland, (2011). Merkel: Elektroautos gehört die Zukunft.
Available at http://www.bundesregierung.de/Content/DE/Artikel/2011/05/2011-0514-podcast.html. Accessed July 30, 2011.
CEC. (2003). California State fuel-efficient tire report: Volume I. California Energy
Commission.
CEMEP. (2011). Energy saving motors result 1998 – 2009. Available at
http://www.cemep.org. Accessed March 15, 2011.
CISCO. (2008). Approaching the Zettabyte Era. CISCO.
Deivasahayam, M. (2005). Energy Conservation through Efficiency Improvement in
Squirrel Cage Induction Motors by using copper die cast rotors. EEMEDS.
dena. (2009). Green IT - Potential für die Zukunft. Berlin: dena.
DGES. (2011). Vergleich verschiedener Technologien.
http://www.dges.de/relaunch/23.html. Accessed March 15, 2011.
Available
at:
DLR. (2006). Trans-Mediterranean Interconnection for Concentrating Solar Power.
Stuttgart: Deutsches Institut für Luft- und Raumfahrt.
Doppelbauer, M. (2005). Performance Characteristics of Driver Motors Optimized
for Die-cast Copper Cages. EEMEDS.
ECF. (2010a). Roadmap 2050. A practical guide to a prosperous, low-carbon
Europe. Den Haag: European Climate Foundation
ECF. (2010b). Energy savings 2020 – How to triple the impact of energy saving
policies in Europe. Den Haag: European Climate Foundation.
ECOFYS. (2005). Cost-effective Climate Protection in the Building Stock of the
New EU Member States. Beyond the EU Energy Performance of Buildings Directive. Brussels, Cologne: European Insulation Manufacturers Association (EURIMA).
eepotential.
(2012).
Data
Base
on
Energy
Saving
Potentials.
http://www.eepotential.eu. Accessed March 15, 2012.
Energynautics. (2011). European grid study 2030/2050. Langen.
Erhard, K. (2010). Einsparung von Prozessenergie und Steuerung von Papiereigenschaften durch gezielte chemische Fasermodifizierung. European Journal of
Wood and Wood Products.
251
European Commission, (1999), Commission Directive 1999/94/EC relating to the
availability of consumer information on fuel economy and CO2 emissions in respect
of the marketing of new passenger cars. Brussels.
European Commission, (2006), Communication from the Commission, Action Plan
for Energy Efficiency: Realsing the Potential, Brussels.
European Commission. (2007). World Energy Technology Outlook - WETO H2.
Brussels.
European Commission. (2008). EU energy trends to 2030 - Update 2007. Brussels.
European Commission. (2010). EU energy trends to 2030 - Update 2009. Brussels.
European Commission. (2011a). A Roadmap for moving to a competitive low carbon economy in 2050. COM(2011) 112 final. Brussels.
European Commission. (2011b). Energy Efficiency Plan 2011. COM(2011) 109
final. Brussels.
European Commission. (2011c), Proposal for a Directive on energy efficiency and
repealing Directives 2004/8/EC and 2006/32/EC, COM(2011) 370 final. Brussels.
European Commission. (2011d), Impact Assessment: accompanying document to
the Energy Efficiency Plan 2011. SEC(2011) 277 final. Brussels
European Commission. (2011e). Energy Roadmap 2050. COM(2011) 885/2. Brussels.
Eurostat. (2011). Eurostat. Available at http://epp.eurostat.ec.europa.eu/. Accessed
March 15, 2011.
EWI. (2010). Potenziale der Elektromobilität bis 2050. Energiewirtschaftliches Institut der Universität zu Köln. Köln.
FfE. (1999). Ganzheitliche Bilanzierung von Grundstoffen und Halbzeugen. Forschungsstelle für Energiewirtschaft, Munich.
Franzen, R. (2006). Recent developments in mechanical pulping. The magazine for
the international pulp & paper industry , S. 43-50.
Graus. (2009). Trend in efficiency and capacity of fossil power generation in the
EU. Energy Policy 37 (2009) 2147-2160.
Greenpeace. (2010a), Energy [R]evolution. A sustainable World Energy Outlook.
Amsterdam.
Greenpeace. (2010b). [r]enewables 24/7 – Infrastructure needed to save the climate. Amsterdam
252
Hulme, M., Neufeldt, H., Colyer, H. (2009). Adaptation and Mitigation Strategies:
Supporting European Climate Policy. The Final Report from the ADAM Project.,
Norwich: Tyndall Centre for Climate Change Research, University of East Anglia.
Harmsen, R., Wesselink, B., Eichhammer, E., Worrel, E. (2011). The unrecognized
contribution of renewable energy to Europe’s energy savings target. Utrecht.
IEA. (2003). Cool appliances - Policy Strategies for Energy Efficient Homes. Paris:
International Energy Agency.
IEA. (2005). Making cars more fuel efficient. Paris: International Energy Agency.
IEA. (2007). Tracking Industrial Energy Efficiency and CO2 Emissions. Paris: International Energy Agency.
IEA. (2008). Energy Technology Perspectives 2008: Scenarios and Strategies to
2050. Paris: International Energy Agency.
IEA. (2009a). Energy technology transitions for industry. Paris: International Energy
Agency.
IEA. (2009b). Gadgets and Gigawatts - Policies for Energy Efficient Electronics.
Paris: International Energy Agency.
IEA. (2009c). World Energy Model. Methodology and assumptions. Available at:
http://www.worldenergyoutlook.org/docs/weo2009/World_Energy_Model.pdf.
IEA. (2009d). World Energy Outlook 2009. Paris: International Energy Agency.
IEA. (2010a). World Energy Outlook 2010. Paris: International Energy Agency
IEA. (2010b). Transport Energy Efficiency. Paris: International Energy Agency.
IEA. (2010c). Energy Technology Perspectives 2010. Paris: International Energy
Agency
IEA. (2011). IEA Energy Statistics – Electricity for the European Union. Available at
http://www.iea.org/stats. Accessed March 15, 2011.
IEA, (2011a). Technology Roadmap - Electric and plug-in hybrid electric vehicles.
Paris: International Energy Agency
IES. (2007). Electricity Consumption and Efficiency Trends in the Enlarged European Union - Status report 2006. ISPRA: Institute for Environment and Sustainability.
IISI. (1998). Energy use in the steel industry. Brussels: International Iron and Steel
Institute.
IPCC, (2001). IPCC Special Reports on Climate Change. Available at:
http://www.grida.no/publications/other/ipcc%5Fsr/. Accessed January 27, 2011.
253
IPCC, (2007). Climate Change 2007 - Mitigation of Climate Change: Working
Group III contribution to the Fourth Assessment Report of the IPCC 1st ed. Cambridge University Press.
ISI. (2008). Quo vadis Elektromobilität? Energiewirtschaftliche Tagesfragen,
12/2008. Karlsruhe.
ISI. (2009a). Study on the Energy Savings Potentials in EU Member States, Candidate Countries and EEA Countries. Karlsruhe: Fraunhofer Institute for Systems and
Innovation Research.
ISI. (2009b). ADAM report, M1, D2: Report of the Reference and 2°C Scenario for
Europe. Karlsruhe: Fraunhofer Institute for Systems and Innovation Research.
ISI. (2009c). ADAM report, M1, D3: ADAM 2-degree scenario for Europe – policies
and impacts. Karlsruhe: Fraunhofer Institute for Systems and Innovation Research.
ISI. (2010). Vergleich von Strom und Wasserstoff als CO2-freie Endenergieträger.
Karlsruhe: Fraunhofer Institute for Systems and Innovation Research.
ISI. (2011a). Möglichkeiten, Potenziale, Hemmnisse und Instrumente zur Senkung
des Energieverbrauchs und der CO2-Emissionen von industriellen Branchentechnologien durch Prozessoptimierung und Einführung neuer Verfahrenstechniken.
Berlin: Umweltbundesamt.
ISI. (2011b). Tangible ways towards climate protection in the European Union (EU
Long-term scenarios 2050). Karlsruhe.
ISIS. (2007). Preparatory Studies for Eco-design Requirements of EuPs - LOT 14:
Domestic Washing Machines and Dishwashers. Rome.
ISIS. (2008). Preparatory Studies for Eco-design Requirements of EuPs - LOT 13:
Domestic Refrigerators & Freezers. Rome.
i-TREN (2010). Integrated transport and energy baseline until 2030 . Available at:
http://cms.isi.fraunhofer.de/isi/projects/itren-2030/index.php
IVF. (2007). Preparatory studies for Eco-design Requirements of EuPs - Lot 3 Personal Computers (desktops and laptops) and Computer Monitors. Mölndal: IVF
Industrial Research and Development Corporation.
IZM. (2007a). EuP Preparatory Studies - Lot 5: Televisions. Berlin: Fraunhofer Institute for Reliability and Microintegration.
IZM. (2007b). EuP Preparatory Study - Lot 6: Standby and Off-mode Losses. Berlin: Fraunhofer Institute for Reliability and Microintegration.
IZM. (2009). Abschätzung des Energiebedarfs der weiteren Entwicklung der Informationsgesellschaft. Berlin: Fraunhofer Institute for Reliability and Microintegration.
254
Joelsson, J. (2008). CO2 emission and oil use reduction through black liquor gasification and energy efficiency in pulp and paper industry. Resources, Conservation
and Recycling.
Kaltschmitt, M. (2007). Renewable energy: technology, economics, and environment. Berlin: Springer-Verlag.
KFB. (2000). Environmental assessment of energy supply systems to electric propelled road traffic. Stockholm
Kobayashi, S. (2009). Energy efficiency technologies for road vehicles. Energy
Efficiency .
Konstantin, P. (2009). Praxisbuch Energiewirtschaft. Berlin: Springer Verlag.
Laurijssen, J. (2010). Optimizing the energy efficiency of conventional multicylinder dryers in the paper industry. Energy , S. 3738-3750.
Leonardi, J. (2004). CO2 efficiency in road freight transportation: Status quo,
measures and potential. Transport Research Part D .
Lindegger, M. (2006). Wirtschaftlichkeit, Anwendungen und Grenzen von effizienten Permanentmagnet Motoren. Bern: Bundesamt für Energie.
Martin, N. (2000). Emerging energy-efficient industrial technologies. Berkeley: Lawrence Berkeley National Laboratory.
MIT. (2008). Electric Powertrains. Cambridge, USA: Massachusetts Institute of
Technology.
NCASI. (2005). Calculation tools for estimating greenhouse gas emissions from
paper and pulp mills. Corvallis: National Council for Air and Steam Improvement.
NStK. (2007). Fakten zum Netzausbau. Hannover: Niedersächsische Staatskanzlei
Odyssee. (2011). Odyssee database on energy efficiency indicators. Available at
http://odyssee.enerdata.net. Accessed March 15, 2011.
Öko-Institut. (2006). Stand und Entwicklung von Treibhausgasemissionen in den
Vorketten für Erdöl und Erdgas. Darmstadt.
Öko-Institut. (2007). Treibhausgasemissionen und Vermeidungskosten der nuklearen, fossilen und erneuerbaren Strombereitstellung. Darmstadt.
Oswald, B. (2007). Vergleichende Studie zu Stromübertragungstechniken im
Höchstspannungsnetz. Oldenburg
Pacala, S. (2004). Stabilization Wedges: Solving the Climate Problem for the Next
50 Years with Current Technologies. Science, Vol. 305, No. 5686, pp. 968-972.
255
Passivhaus Institut. (2009). Altbaumodernisierung mit Passivhaus-Komponenten.
Darmstadt.
Pehnt, M.. (2011). Energieeffizienz: Ein Lehr- und Handbuch. Berlin: Springer Verlag
Quaschning, V. (2011). Regenerative Energiesysteme: Technologie – Berechnung
– Simulation. München: Carl Hanser Verlag
Radgen, P. (2007). Preparatory studies for ecodesign requirements for EuPs – Lot
11: Fans for ventilation in non residential buildings. Karlsruhe
SAENA. (2009). Gebäudedämmung - Baustoffe mit Potenzial. Dresden: Sächsische Energieagentur.
Schmid, C. (2003). Möglichkeiten, Potenziale, Hemmnisse und Instrumente zur
Senkung des Energieverbrauchs branchenübergreifender Techniken in den Bereichen Industrie und Kleinverbrauch. Karlsruhe, Berlin.
SRU. (2010). 100 % Erneuerbare Stromversorgung bis 2050: Klimaverträglich,
sicher, bezahlbar. Stellungnahme. Berlin: Sachverständigenrat für Umweltfragen
TNO. (2006). Review and analysis of the reduction potential and costs of technological and other measures to reduce CO2-emissions from passenger cars. Delft.
TNO. (2009). Impact of Information and Communication Technologies on Energy
Efficiency in Road Transport - Final Report. Delft.
Torcellini, P. (2006). Zero Energy Buildings: A Critical Look at the Definition. Oak
Ridge: NREL.
TRT. (2008). HOP! - Macro-economic impact of High Oil Price in Europe. Milano:
Transporti e Territorio. Available at http://www.hop-project.eu. Accessed January,
23 2011.
UNFCCC. (2011). GHG Data – Global Map - Annex 1. Available at
http://maps.unfccc.int/di/map/. Accessed November 11 2011.
VITO. (2007a). Preparatory Studies for Eco-design Requirements of EuPs - Lot 8:
Office Lighting. Mol.
VITO. (2007b). Preparatory Studies for Eco-design Requirements of EuPs - Lot:
Public street lighting. Mol.
VITO. (2009). Preparatory Studies for Eco-design Requirements of EuPs - Lot 19:
Domestic lighting. Mol.
256
Voss, K. (2008). Nullenergiehaus, Plusenergiehaus, Nullemissionshaus - Was
steckt dahinter und wie gelingt die Umsetzung? Wuppertal: Bergische Universität
Wuppertal.
Wietschel, M. (2010). Energietechnologien 2050. Karlsruhe: Fraunhofer Verlag.
257
Glossary
English term
Meaning
German term
Blast furnace
Metallurgical furnace used for
Hochofen
smelting to produce industrial
metals, mainly iron.
Combined heat and power
Simultaneous generation of heat
Kraft-Wärme-Kopplung
(CHP)
and electricity by a heat engine
(KWK)
or power station.
Compact fluorescent lamp
Fluorescent lamp, designed to
Kompaktstoffleuchte,
(CFL)
replace the conventional incan-
Energiesparlampe
descent lamp.
Electric arc furnace (EAF)
Furnace that heats charged ma-
Elektrolichtbogenofen
terial by means of an electric arc.
Electrical ballast
Device intended to limit the
Vorschaltgerät
amount of current in an electric
circuit.
Electronically
commutated
motor (ECM)
Synchronous
electric
motor
powered by direct-current (DC)
Bürstenloser
Gleich-
strommotor
electricity and having electronic
commutation systems, instead
og mechanical commutators and
brushes.
FED
Final energy demand
Endenergieverbrauch
GHG emissions
Greenhouse gas emissions; the
Treibhausgas-
only relevant emissions from the
Emissionen
energy
sector
comprise
CO2
(carbon dioxide), CH4 (methane)
and N2O (nitrous dioxide)
Halogen lamp
Incandescent lamp with a tung-
Halogen-(Glüh-)Lampe
sten filament contained within an
inert gas
Incandescent lamp
Lamp that emits light by heating
a metal filament wire to a high
Glühlampe
258
temperature until it glows.
Light emitting diode (LED)
Semiconductor light source.
Leuchtdiode (LED)
Renewable energy sources
Energy sources based on natural
Erneuerbare
(RES)
resources such as sunlight, wind,
giequellen (EE)
rain, tides, and geothermal heat.
Top gas
By-product of blast furnaces that
Gichtgas
is generated when iron ore is
reduced with coke to metallic
iron.
V-belt transmission
A drive belt with a V-shaped
cross section, for transmission of
low to moderate forces; typically
used to drive generators, water
pumps, air pumps, air conditioner
compressor
units
power steering pumps.
and
V-Riemen
Ener-

Contribution of Energy Efficiency Measures to

Transcription

Similar documents

Vapiano invests in Winterhalter technology for long term savings

ADIABATIC WATER COOLER www.ewk.eu

The Chalkboard - Washington Area FCU

Jessamine County Fiscal Court

Bulk Whole Foods - Your Coastal Connection

IKI-DuoLock

Bankruptcy may not be best way

the banana boat bronte junior ocean swim

NCPC-SA Services to Industry

go green. think blue.