pablo ruiz minguela - Bilbao Marine Energy Week

TECHNO-ECONOMIC
CONSIDERATIONS FOR
THE COMPETITIVE
DEVELOPMENT OF
OCEAN ENERGY FARMS
Pablo Ruiz-Minguela
Marine Renewable Energy
[email protected]
Session 2: Ocean
Energy Projects
18th April, 2013
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7.
8.
Who we are
Techno-economic Tools
Project Size
Deployment Site
Mooring System
Grid Connection
Maintenance Planning
Conclusions
2
Who we are
TECNALIA is the first Applied Research Centre in Spain and one of the most
important in Europe with around 1.500 staff, 116 million Euro turnover and over
4.000 clients.
Organised in 7 Business Divisions: we work from the experience and
the expertise we have acquired in the markets in which we operate, with
an efficient and proactive attitude.
ENERGY &
ENVIRONMENT
INDUSTRY &
TRANSPORT
INNOVATION
STRATEGIES
ICT - European
Software Institute
TECHNOLOGICAL
SERVICES
SUSTAINABLE
CONSTRUCTION
HEALTH
We transform Energy and Environmental Challenges into
Business Opportunities
Smart Grids
Renewable Energy
Electric Storage and Mobility
Marine Energy
Solar Power
Offshore Wind
The Energy
System of
The Future
Integral approach based on
the deployment of marine
energy farms and their costefficiency over the whole
lifecycle
Energy
and
Environment
Sustainability as
Mega-trend
Environment
and Climate
Change
New materials
from Waste
Prediction Systems
Water Cycle
Wave Energy
6
Technoeconomic tools
for Ocean Energy
7
Affordability of Ocean Energy: Cost Reduction
Three Possible Ways: Innovation, Learning-by-doing and Economies of scale
“Business as usual”
Innovation scenario
Tidal Energy
Wave Energy
(Source: Carbon Trust, 2011)
8
COE as the Driving Factor to select Technical Alternatives
Integral approach:
Farm performance, not only device performance;
Project lifecycle cost, not only manufacturing costs
Project life,
Discount rate
FINANCIAL
PARAMETERS
WEC, Mooring,
Electric lines,
Installation,
Decommisioning,
Insurance
CAPITAL
EXPENDITURE (CAPEX)
Vessels, staff,
spares
OPERATION
EXPENDITURE (OPEX)
Device type,
No. units, Power,
Performance
Financial
model of the
farm
COE
NPV
n
ENERGY
PRODUCTION
NPV =
∑
t =1
Ce * energy
n
(1 + k )
n
− CAPEX −
OPEX
∑ (1 + k )
n
t =1
ENVIRONMENTAL
PARAMETERS
Water depth, Resource,
Environmental loads, Distance
to PCC, Distance to port
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Parametric Models
They make it possible to compare
and assess different alternatives
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When it comes to ocean energy …
size matters!
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Device Level Decisions
Optimal device sizing (in terms of COE) depends on Type of Device and Deployment Site
Point absorbers and floating OWCs seem to be mostly efficient
when deployed with relatively small diameters
12
Array Level Decisions
The influence of the scale of the farm is crucial to obtain competitive COE
For smaller farms, the cost of the electrical infrastructure has a
significant impact on the COE
13
Rough seas
make good
sailors …
but maybe not big profits!
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Deployment Site Decisions: CAPEX
Higher CAPEX for structural and moorings systems is required in most energetic sites in
order to meet survivability conditions
SITE
High energy
flux
Moderate
energy flux
Low energy
flux
Increase In Hull Weight for a Typical Point Absorber of d = 6 m
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Deployment Site Decisions: OPEX
Component reliability is linked to conditions of operation in the deployment site:
higher exposition reduces component life and increases OPEX
Hs = 5,5 m
Hs = 0,5 m
Bearing fatigue life in years for
different sea-states
Instantaneous & cumulative damage
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A ship should not ride
on a single anchor …
Cost-effective moorings are needed!
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Mooring Line Decisions
Mooring system represents a significant investment (literature: 15% of CAPEX)
Catenary with
Surface Buoy and
Clump Weight
Catenary
Depth = 120 m
Load = 4,000 kN
SF = 1,67
Selection of Line Type & Optimal Configuration to Reduce CAPEX
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Array Mooring Decisions
Sharing mooring lines and components could significantly reduce costs
3-Line Mooring
System (reference)
Aquaculture inspired
Mooring System
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Energy cannot
be created or
destroyed …
but it can be easily lost!
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Farm Layout Decisions
Clustering depends on global factors: Number of units, Power per unit, Location of the
farm, WEC technology, Inter-device minimum distance, Mooring system
Full String
String Series
Redundant
String
Star or Radial
… and constraints:
Series DC
•Electrical physical barriers (max no. of
devices per cluster)
•Distribution mode (AC/DC)
•Redundancy level
•Switchgear system
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Electric Lines Decisions
Selection of output voltage influences maximum cable losses and section (i.e. CAPEX)
Energy storage contributes to reduce instantaneous power fluctuations
Grid connection
Opt 1 Opt 2
Output voltage - Umbilical cable (kV) 13.2
6
BMH voltage – Static cable (kV)
13.2
13.2
Losses (% of total generation)
3,14% 4,32%
Cores (Kg) (% increase)
0%
33,42%
Opt 3
Opt 4
3
0.6
13.2
13.2
7,22%
8,64%
88,68% 118,05%
Wave farm integration at bimep (20 MW)
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Information is
power …
Let’s use it to increase profit!
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Site Accessibility and Operability Decisions
OPEX is dependant on Resource Conditions, Duration, Availability of Dedicated , Limit
Conditions … and access predictability
Estimating bimep accessibility for a corrective maintenance
requiring 3 h towing to port and 8 h work with Hs max = 1 m
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Maintenance Planning Decisions
Maximise Project Profitability
OPEX Costs
Preventive
Maintenance
Unavailability
Energy
Estimates
Predictive
Maintenance
Accessibility
Resource
Constraints
Limit
Conditions
Dedicated
Vessels
Duration
Devices
Works at Sea
Generation
Marine Safety
η
Forecasts
Maintenance
Strategies
Environment
CMS
Maintenance Orders
Personnel
Plans
Corrective
Maintenace
Navigation
Failures
Revenues
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Final word …
Techno-economic tools are important
to address high level challenges of
Ocean Energy projects
•
•
•
•
•
An integral approach to cost reduction
Model design parameters interdependencies
Assess technical alternatives
Identify improvement areas
Deal with uncertainties (what-if questions)
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