tnbr insight - TNB Research Sdn. Bhd.

TNBR INSIGHT
PP 17410/06/2012(0310122)
“R&D and Innovation for
Operational Excellence and Beyond”
Traditionally, the drivers of economic growth and
wealth creation of a nation lay in the domain of land,
labor and capital. Today, the focus has shifted to an
innovation and knowledge-driven economy to ensure that the country remains ahead of competition.
TNB Research Sdn Bhd
No. 1, Lorong Air Hitam
Kawasan Institusi Peyelidikan
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Selangor Darul Ehsan
Malaysia
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VOLUME 4
MARCH 2014
MD’s Foreword
(DR. IR CHEONG KAM HOONG)
It gives me great pleasure to pen a few words in this fourth issue of TNBR INSIGHT, which is an annual bulletin from TNB Research
(TNBR), the R&D arm of Tenaga Nasional Berhad (TNB). With a primary objective of enriching the Malaysian innovation circle which
consists of the ministries, government agencies, research institutes, universities and technology entities, TNBR INSIGHT features review
of technologies and publication of research findings undertaken by TNBR within the Malaysian Electricity Supply Industry (MESI).
During the 2014 National Budget presentation, Prime Minister Datuk Seri Najib Tun Razak identified innovation to be one of the critical
success factors for our nation to become a developed nation by 2020. He acknowledged that the world economy would be driven
by innovation. However, the journey toward innovation would not be an easy one as it required continuous development of talents
and sustained investment as well as a supportive eco-system. Furthermore, it would require full support from the government and
industries. Ultimately all parties involved have to be in the right mindset. Toward this end, he announced the setting up of Malaysian
Global Innovation and Creative Centre (MAGIC) as a one-stop center for entrepreneurs.
In line with the nation’s aspiration, TNBR has over the years, developed its people through R&D program/projects, its laboratory
facilities as well as attachment to industries and renowned institutions. TNBR is well aware of the needs of the MESI in general and
TNB in particular. We have been conducting research in areas that could further enhance the availability, reliability, and efficiency of
the entire electricity supply system as well as in the area of green technology. Many of our R&D findings have been adopted, applied
and brought value to the industry.
With the recently launched TNB’s Transformation Program, there are many challenges embedded in it that we have to overcome
to ensure its success. TNBR needs to be more focused and value driven in helping TNB to achieve its KRA3 – Drive operational cost
efficiency. To support KRA 4 – Grow profitable new business, we have established our service subsidiary TNBR QATS to undertake the
provision of products and services as well as commercialization of our innovations. This will allow TNBR to focus on “breakthrough”
R&D that will bring about high value impact to the company and its customers.
Moving forward, to be a successful R&D company, it requires many ingredients as rightly highlighted by our Prime Minister, i.e.,
talented and passionate researchers, sustained R&D investment, a supportive eco-system, right mindset, and most important of all,
the close collaboration between government, industries, and the R&D institutions.
We hope that through TNBR INSIGHT, we will be able to disseminate information on some of the R&D undertaken by TNBR so that
there will be greater awareness of TNBR’s research programs and service offerings. With this, we hope to spur efforts to leverage on
our Malaysian know-hows, strengthen our expert networks and collaborations in achieving our nation’s aspiration of Vision 2020.
Achievements
Award Winners at TNB 8th R&D Convention 2013
TNB Generation Division won the Harvest Award for their project “Bioremediation Of Oil Contaminated Soil Within TNB Power Station
and TNB Storages”. Dato’ Roslan Ab. Rahman, Chief Corporate Officer represented Dato’ Ir Azman Mohd, Chief Executive Officer of
TNB to present the award at the 8th TNB R&D Convention 2013. At the same convention, Dato’ Roslan presented the Researcher
of the Year Award to Madam Ng Guat Peng, recognising her contribution in the forensic engineering research area. Dato’ Roslan
also presented the Promising Researcher of the Year Award to Mr. Mohd Iqbal Ridwan for his research work in electrical substation
automation. During this convention too, recognition in the form of incentive payments were made to recipients Mr. Azlan Abdul Rahim
and Mr. Huzainie Shafi Abd Halim for their successfully commercialized Intellectual Property. Their invention, the Cable Earth Fault
Indicator was successfully used and commercialized.
& Highlights
TNBR Retreat and Breakthrough Lab
To strengthen TNBR’s role in supporting TNB, a retreat was held at Shah Alam Convention Centre in
October 2013. Dato’ Ir Azman Mohd, Chief Executive Officer of TNB, Vice Presidents, key Divisions‘
representatives, TNBR Board Members, TNBR Management and TNBR Researchers were among the
attendees of the retreat session. Attendees had a fruitful discussion, and the key message for TNBR
was that it needs to be forward looking and be more focused on breakthrough research. Subsequent
to the retreat, TNBR had also organized a Lab session, sponsored by Dato’ Ir Azman Mohd. The
Lab was intended at identifying the most suited model to produce high impact and breakthrough
research, as well as identifying ways for TNBR to achieve financial sustainability. Members of this lab
which was held in December 2013, was made up of representatives from core divisions; Generation,
Transmission, Distribution and a few Managers and Researchers from TNBR. These two events
portray the commitment of TNBR as a research & development company in supporting TNB to face
the challenges in electricity supply industry, and at the same time bringing added value for TNB and
its stakeholders.
TNBR Signs MOU with KEPRI
A two year Memorandum of Understanding was signed between TNBR and KEPRI (KEPCO
Research Institute) in June 2013 with the objectives to encourage the development of
research, technological and business co-operation between both parties. This is an extension to the first MOU which was signed in 2004. The MOU signals a
continual commitment by both parties to increase international co-operation in the
area of power plant material research, diagnosis of failure mechanism and corrosion
analysis
TNBR Leadership Talk
TNBR Leadership Talk was held at TNB Research on December 2013. The invited
speaker was Encik Mohd Izani Ashari, Chief Executive (Special Projects) from
Khazanah Nasional Berhad. The key objective of the Talk was to prepare future
leaders to meet the challenges of today’s economy and business world. TNBR Board
Members, Managing Director of ILSAS / Yayasan Tenaga Nasional and representative
of UNITEN’s Vice Chancellor were among of the attendees of the TNBR Leadership
Talk.
CREAM Visits TNBR
Institut Penyelidikan Pembinaan Malaysia (CREAM) recently visited TNB Research
as part of its benchmarking assignment. The delegation of five senior members
was headed by Ir Dr Zuhairi Abdul Hamid, Executive Director of CREAM. Dr Ir
Cheong Kam Hoong, Managing Director of TNBR, welcomed the delegation and
explained the organization and function of TNBR.
About TNBR
One of the main topics discussed was the concept of R&D management. This
discussion has provided greater clarity about the subject as both parties can
practically see how to put the concept into action. Discussions were not
limited to R&D management, but also on how to coordinate R&D activities
with the company’s business objective and strategies, as well as how to
create value to investors.
The delegates were interested in several projects being carried out at TNBR
and requested more information. The meeting has lay down the basis for
further collaboration between TNBR and CREAM.
Established as a department in TNB, TNB Research (TNBR)
has evolved into a subsidiary of Tenaga Nasional Berhad (TNB)
in 1993. TNBR focuses in conducting R&D that adds value and
aligned to TNB’s corporate needs as well as national aspiration.
TNBR aspires to be at the forefront of the technology related to
renewable and green energy – providing solutions to TNB and other utilities in the region and Asia through its Advanced Research
programme in the area of :
•
Green Technology
•
Smart Grid
•
Low Carbon Power Generation
•
Emission & Waste Management
TNBR INSIGHT Team
Advisor
Dr. Ir. Cheong Kam Hoong
Editorial Team
Ragavan & SMOD Team
Contributors
Razwan
Dr. Hariffin
Roslin
Dr. Azmi
Syahila
Dr. Syuib
Dr. Radzian
Featured Article
R&D and Innovation for Operational Excellence in
the Power Industry
DR. MOHD HARIFFIN BOOSROH
General Manger (Generation & Environment)
[email protected]
Power Industry and Operational Excellence
Business Dictionary and Wikipedia define Operational Excellence
as “a philosophy of leadership, teamwork and problem
solving resulting in continuous improvement throughout
the organization by focusing on the needs of the customer,
empowering employees, and optimizing existing activities in
the process.” In the context of power industry, operational
excellence is typically considered as delivering electricity in an
efficient, effective and reliable manner across the process chain
with a focus on delivering value to customers.
For a regulated industry, operational excellence is a key tool in
the balancing act between keeping prices down for consumers
and providing value for shareholders. Thus, power utility
companies are consistently facing pressure from the public and
regulators to keep retail prices down and for their influence on
the market to be reduced. New plants need to be built to meet
increasing demand, while existing and ageing plants need to
be maintained or decommissioned. In addition, environmental
concern such as climate change is placing an ever increasing
burden on the utilities and regulators. These factors broadly
align with the major challenges facing operational excellence in
utilities across the globe i.e. market reforms, changing customer
expectation and shifting energy landscape.
In Malaysia, the drive for operational excellence in the
electricity supply industry is becoming more significant with
the implementation of incentive-based regulation (IBR). The
scheme is intended among others to strengthen the incentive
mechanism to promote efficiency and service standards in the
electricity supply industry.
Power Industry and Challenges
Electricity supply industry has always been one which is largely
consumer orientated. Market changes and new innovations
are now making it even more so. Offering a superior service to
clients through operational excellence will allow companies to
remain competitive. But this task is not an easy one. It is also
widely accepted now that utilities are no longer competing on
price, but rather on service, and this places pressure not only on
supply but back office functions.
A decade into the twenty-first century, electricity supply
industry finds itself in the midst of transformative change. A lowcarbon and more decentralised electricity generation system is
emerging, while smart grid technologies are creating significant
new capabilities. Change also is coming as a ‘new downstream’
service model based around energy efficiency offerings,
decentralised generation, and new products and services.
Meanwhile, the industry is grappling with how to ensure this
transformation achieves decarbonisation and energy security
objectives whilst keeping costs at manageable levels.
He also stressed that in order to make it work, the industry
should not be too punitive in order to encourage more
innovation.
Power Industry and Innovation
These changes and pressures have propelled innovation to
the fore in the power sector. From a relatively peripheral
phenomenon, innovation now is central to fundamental shifts
in power sector value creation as well as a precondition for
achievement of societal objectives. All power sector participants
– from equipment manufacturers to energy retailers – will need
to find new ways to improve their products and manage their
businesses. (Source: EURELECTRIC, 2013)
Figure 1. Potential value of innovation in the EU power sector
The potential value of power sector innovation is truly significant.
The Union of the Electricity Industry (EURELECTRIC) estimated
that accelerated innovation in power supply technologies and
business models for energy efficiency could be worth 70 billion
euro to the EU economy in 2030 (Figure 1).
The essence of technological innovation management involves
mobilizing and coordinating the company’s resources e.g.
R&D, commercial, operations, human resources, finance,
and planning, as well as the resources outside the company
e.g. customers, suppliers, research institutions, and funding
agencies, to explore technological opportunities and the
market, aligned with the company’s strategic priorities. This
is the direction that TNB and TNB Research are consistently
pursuing to realize the aspiration for operational excellence.
Innovation is a process that involves the entire organization.
It infers the full commitment of top management and funding
allocation that reflects the priority given to innovation, and
the adoption of specific technological innovation management
processes and tools used by the operating areas involved, with
emphasis on the R&D, operational, and business aspects.
Figure 1. Potential value of innovation in the EU power sector
~70 +X
-10
X
-30
-30
Electricity
cost
reduction
Energy
savings
Macroeconomi
cs benefits
Additional
benefits¹
Total²
Additional benefits are also expected in energy security,
lower system costs, and consumer convenience. Conversely,
if innovation were to slow, the adverse impact could deal a
severe blow to power sector growth and competitiveness. The
power industry has come a long way in creating conditions for
innovation. Yet much remains to be done to create the market
setting in which innovation can thrive, and to steer public
support for innovation effectively.
Capturing the potential of innovation requires a dynamic
power sector, acting within a strong enabling policy framework.
Speaking at the “Game Changers” Innovation Showcase,
Prime Minister Datuk Seri Najib Abdul Razak has called for the
strengthening of innovation ecosystem in the country, a move
in making innovation as the key enabler towards achieving
Vision 2020. “We have to build our strong intellectual capital.
We must have a very responsive ecosystem in the sense that we
must provide opportunities (and) we must encourage people”
he said.
References:
Carvalho, R.Q, dos Santos, G.V. Manoel Clementino de Barros, M.C, R&D and
Innovation Strategic Management in a Public Company in the Brazilian Electric
Sector; Journal of Technology Management, Vol. 8 No. 2, 2013
Ibrahim, A., Malaysia ready for innovation era, Columnist, The New Strait
Times, 21 Jan. 2014
Three Challenges Facing Operational Excellence in Utilities, Process Excellence
Network (http://www.processexcellencenetwork.com); 2013
Utilities: Power Houses of Innovation – Full Report, EURELECTRIC, May 2013
MOHD RAZWAN RUSLI
Researcher
(Green Technology)
[email protected]
ROSLIN MOHD SHAFIE
Principal Researcher
(Green Technology)
[email protected]
Introduction
Solar Photovoltaic (PV) has shown impressive growth since
the launched of the Feed-in Tariff (FiT) scheme in 2012. At the
end of 2013, 80 MW of PV systems were in operation, feeding
40,000 MWh of clean electricity to the grid. And the buildup is expected to remain strong to meet the government’s
target of 850 MW by 2030 and more than 8,000 MW by
2050. The government is also considering additional policies
besides the FiT that will spur the local PV industry. The new
policies include net energy metering (NEM) and utility scale
PV power plant. Judging by the interests in the FiT scheme,
we can expect a surge in new installations, when the new
policies are implemented.
The main goal of the FiT scheme is to catalyse the generation
of renewable energy (including PV) in the country to
complement the National Renewable Energy Policy. However,
PV is not without its challenges. Top on the list is managing
the fluctuation of PV power. This article will examine this
issue to identify its impact to the power system as a whole
and will propose a solution to overcome this challenge.
Understanding PV Fluctuation
The flexibility of a power plant is characterized in terms of
start-up and shutdown time or ramp rate. Thermal plants
with boilers have the longest start-up time between 8 – 24
h. Peaking gas turbines have a start-up time between 15 – 20
min while hydroelectric plants can start almost immediately
in about 1 min. Their shutdown times vary at about the same
range. But most importantly, they are dispatchable.
PV Power Forecasting
for Grid Operation and
Planning
Currently, in the management of the power grid, the system
planning managers typically use day-ahead commitment process
to assign generators to match the forecasted demand. Every 30
min, the operator will change the output of committed generators
to meet the actual demand throughout the day. Appropriate
reserves are also scheduled to balance the grid.
The response time of a PV plant, however, is almost instantaneous,
in seconds, as shown in Figure 1. Its output follows the sudden
change in the solar irradiance level due to passing clouds. When
the PV modules are shaded, the output drops to almost zero.
After a while, the output suddenly rises to maximum when
the sun is uncovered by the clouds allowing the PV modules to
receive sunlight.
This sudden rise causes an excess of power in the system. The
system operator must ramp down generation from other sources
to reduce this excess in electricity and to balance the grid. When
the PV modules are shaded by the clouds again, power in the
system is decreasing and the operator has to turn on other power
sources.
This scenario is called the “solar ramp” problem and is considered
one of the greatest challenges in operating the power grid. Since
the changes in solar radiation is on a time scale of minute or less,
forecasting the PV output on a very short time periods becomes
very important.
Figure 1. Changes in solar irradiance (red line) and PV power output (blue line) of 5 s
lag. In the upper side the selected area between 12:30 and 13:30 is magnified. Data
measured at TNB Research Centre in Kajang, Malaysia on 26 May 2012.
Photovoltaic yield prediction for system planning
Meanwhile, the power system planning managers require
every power plant to provide expected yield one day in advance
to match it with the forecasted demand. With this information
the planner can coordinate reserve sources to be on stand-by
in case of unplanned outage. For conventional power plants,
the calculation is straight forward based on the available fuel at
hand and plant efficiency. However, for a PV power plant, the
calculation requires reliable weather forecasts for the next day.
But the prediction can become a little bit easier when planning
for the next few years provided that historical data is available
In short, forecasting PV power and yield depends upon accurate
and reliable forecast of solar radiation and a localised PV Power
conversion model. Figure 2 illustrates the building blocks of a
generic PV forecasting.
Solar
Radiation
Forecast
Power
Conversion
Model
PV Power
Forecast
Figure 2. Building blocks of a generic PV Power Forecast.
Proposed PV Power Forecasting System
To deal with the PV fluctuation in the future, we propose a PV
Power Forecasting System for Grid Operation and Planning in
Malaysia. Figure 3 demonstrates the overview of the multihorizon forecasting system beneficial to both system operation
and planning. The proposed system was formulated after a
survey of solar energy forecasting systems under development
or in operation all over the world and by considering the
characteristics of the Malaysian power system and climate.
Intra-hour forecasting tool
In dealing with solar ramp events, an intra-hour forecasting
tool that can provide forecast information between 15 min to
2 hours in advance is proposed. The tool can serve forecast
as frequent as every 1 min up to 30 min depending on needs
to cater for voltage and frequency regulation which will help
the operator manages rapid ramp events from the PV plant.
To obtain the forecast in this category, the tool requires data
from ground station sited at a PV power plant and the plant
efficiency.
Intrahour
Intraday
Day
ahead
15 min – 2 h
1h–6h
1 day – 3 days
Sky facing camera may also be deployed to track cloud
movement in order to increase the accuracy of the forecast.
Currently, a similar forecasting tool as illustrated in Figure 4 is
under development at TNB Research.
Intra-day forecasting tool
The second forecast tool will provide forecast information for 1
h up to 6 h in advance. The time resolution can be as frequent
as every 30 min up to 1 hour which will aid the system operator
and planning managers to balance the grid and to meet
forecasted demand. Currently, the best forecast tool in this
category requires analysis of satellite imagery and numerical
weather prediction (NWP). However, techniques that employ
rich historical ground observed data have emerged as simpler
and more cost effective alternative.
Day-ahead forecasting tool
For unit commitment and transmission scheduling required by
the planning managers, a day-ahead forecast tool is proposed
to administer hourly forecast from 1 day up to several days in
advance. Due to complex nature of the weather forecasting,
this tool depends on inputs from NWP. Combining the analyses
of satellite imagery can also produce more reliable forecast.
Recommendations for the Implementation of the PV Power
Forecasting System
• Upgrade/Expand weather stations measuring solar
radiation
• PV Power plants must provide weather and generation
data
• A standardised and uniform forecasting system
• Stimulate research on satellite imagery analyses and NWP
• Aggregate small scale systems within a certain area
Conclusion
The Malaysian power system in the future is envisioned to
include high capacity of fluctuating and non-dispatchable PV
power. This can be managed by deploying a multi-horizon PV
power forecasting system to serve the system operator and
planning managers. Three components of this system are (1)
intra-hour forecasting for real time power system regulation,
(2) intra-day forecasting for grid balancing, and (3) day-ahead
forecasting unit commitment in system planning.
Forecasting
horizon
Time resolution
Related to
1 min up to 30 min
30 min to 1 hour
Hourly
Ramping events,
variability related to
operation
Load
following/balancing
Unit commitment,
Transmission
scheduling
Ground observation and time series
Required input
Satellite imagery and numerical weather
prediction (NWP)
Figure 3. Proposed PV Power Forecasting System.
Figure 4. Intra-hour PV forecasting tool employing sky-facing camera
under development at TNB Research.
Management of Maintenance Based on Condition Monitoring
Tools and Technology for Plant Reliability and Availability
Dr. Shuib Husin
Principal Researcher
(Material Engineering)
[email protected]
Introduction
Operational excellence has broad views of definitions and
varied parameters that contribute to achieving it. However, it
can be narrowed to the elements of organizational leadership
that stress the application of tools and technology towards
the sustainable improvement of performance. For power
utilities, the performance of its power generation plants is one
aspect that inevitably has to be seriously monitored and given
priority. Outage related matters such as machine breakdown
and problems, safety, spare parts, labours etc. which are
complicated, can be eased by the application of specific tools
or technology which can provide an early indication of many
potential problems based on the recognized symptoms that
are indicative of forthcoming severe problems.
Maintenance performance is measured and appreciated
by contributions to plant productivity and profitability. The
maintenance process, complemented by specific tools and
technology, helps in decision making for planned outage; this
leads to reliability and availability of plant. The definition of
“reliability” is the probability of zero failures over a defined
time interval (required operating hours), whereas “availability”
is defined as the percentage of time a machine or system is
considered ready to use when tasked. Operational excellence
involves human assets, technical and technological, that
have to be incorporated in order to achieve plant reliability
and availability. One of the factors that contributes to a
reliable plant and profitability is “process and management of
maintenance”.
This is about information gathering, monitoring, predicting,
preventing, proactivity, planning works and decision making
in dealing with outage or plant performance contributed by
the maintenance process. The process and its assurance is
highly influenced by employing special tools or technology for
maintenance purposes in anticipating and heading off failures,
and significantly contributes to improving reliable plant
capacity.
One of significant roles of research organization like TNB
Research (TNBR) is to acknowledge and identify the emerging
condition monitoring technology, evaluate and develop
guidelines and procedures before employing them at power
stations to achieve and sustain reliability and availability
of plant. Fig 1 shows the impact of proactive maintenance
in reducing short notice outage, particularly unscheduled
short notice outage. Proactive maintenance contributes to
the increase reliability of plant, reducing unplanned outage
and this provide the opportunity for maintenance people to
execute waiting work orders that are preferable as preventive
types of jobs instead of being reactive types of jobs.
Fig 1: Change from reactive maintenance philosophy
to proactive maintenance resulted plant reliability
Elements in Operational Excellence
Awareness of process care and asset care by employees is
the key to achieving operational excellence. Specific training
in knowledge and skills should be provided to employees to
practically and effectively manage both the asset and process. Three primary elements; people care, process care and
asset care in the operational excellence model, as shown in
Fig 2, produce the following outcomes; reliability and quality,
sustenance and productivity of the plant when the combination of two primary elements takes place. Clearly, the model
represents that the integration of the three primary elements
(people, asset and process care) will produce the so-called
product of “operational excellence”. The maintenance process and asset management are matters cannot be separated
within plant operation. Taking care to integrate these two elements brings sustainability and growth in business.
Effective maintenance involves proactive works to be in place
before breakdowns occur and these can be approached
through preventive and predictive maintenance. The current
trend for using predictable maintenance, based on condition
monitoring assessment, promises operating conditions that
will optimize equipment availability with little or no downtime
of critical systems and components.
Condition Monitoring
Condition monitoring is defined as a means of a close
observation and extraction of information of a machine’s
current condition that indicates the state of the machine.
Condition monitoring provides an early indication of many
potential problems which helps in the process and management
of maintenance strategies to maximize machine life and avoid
unplanned outages.
Condition-based maintenance (CBM), methods and
technology, based on the actual condition and predicted future
use of systems and components, allows maintenance to be
performed at the best possible date for each component in a
system.
CBM benefits from on-line monitoring, such as those offered by
special tools, are effective in heading off failures to maximize
the machine or plant operation and maintain them at the
minimum possible cost. Losses from a maintenance aspect
have always been referred to as outage time.
Preventive maintenance in industry is often executed from
a schedule according to a predetermined period of time in
service and the current condition of machines or components.
If the component is in good condition, and therefore no
maintenance is necessary, this leads to the deferral of costly
off-line maintenance. However, this can only be achieved by
knowing the current condition of the machine/components.
Condition Monitoring Tools and Technology
The application of special tools and technology significantly
helps in the predictive maintenance programme of any
industry. Predictive maintenance uses technically sophisticated
diagnostic equipment to provide an early warning of any
developing equipment problems.
The vibration method and AE technology are among the special
tools that are being used widely for condition monitoring of
industrial components, particularly for rotating machinery.
However, vibration analysis is shown to be incapable of incipient
fault detection. AE technology is sensitive and practical for
on-line monitoring and incipient defects detection. It is
based on the energy of wave propagation (see Fig 3) instead
of energy impact as experienced by the vibration technique.
AE technology has also been used in structural integrity
assessment for pressure/storage vessels. AE technology has
been well accepted as a new effective condition monitoring or
on-line monitoring and prognostic tool.
For power energy material integrity assessment, proactive
inspection-work and base-line data are of paramount important.
For instance, for a boiler tube, base-line data such as hardness,
microstructure, and creep data are important parameters for
the assessment of a component’s remaining life.
Techniques adopted for boiler tubes, include in-situ replication
technique for microstructure examination, portable hardness
tester for hardness measurement, metal magnetic memory
(MMM) technology for stress measurement and concentration
where it uses natural magnetization and the after-effects are
displayed as the magnetic memory of metal to actual strains and
structural change (see Fig 5), instrumented indentation te (IIT)
for power piping and tubes which automatically represents the
results of indentation of the material surface as associated to
the tensile strength, 3-Dimensional Displacement Measurement
System (3DDMS) for power piping displacement monitoring and
stress calculation (see Fig 7).
Fig 4: MMM technology
fundamentals of magnetic leakage on the material’s surface
Fig 5: Superheater coils
testing by MMM method
Fig 6: Instrumented Indentation Technique for aging and life assessment
boiler equipment
Concluding remarks
It can be concluded that the benefits of on-line and predictive
maintenance lead to condition monitoring where diagnosis and
prognosis can be established and recognized as:
•
Fig 3: AE fundamentals for incipient defects detection and
on-line monitoring
It provides a means for decision making on the right time to
change a part or outage time planning to repair a machine,
Reduction in maintenance costs.
Early warning of incipient component failure.
Improved safety measures.
Greater machine availability.
Lower insurance cost.
•
•
•
•
•
It is apparent that the application of specific tools and technology
in both maintenance management and process provides very
significant savings, and plant reliability and availability. It
involves people, processes and asset management all of which
contribute to operational excellence for the plants.
Real-Time Corrosion Monitoring in Thermal
Power Plant
Ir. Dr. Azmi Ahmad
Principal Researcher
(Combustion)
[email protected]
Corrosion in Thermal Power Plant
Corrosion (or oxidation) of metal structures, especially the
wetted parts in power plant facilities (such as in boiler tube
inner walls and condensers) presents a very real threat to the
performance of the entire power plant. On top of that, thermal
power plants are normally located at the seaside (i.e. chloridebased environment which is corrosive to steel). Corrosion may
cause the affected parts to leak, crack, and eventually, fail
(Figure 1).
Corrosion Monitoring Program
Corrosion monitoring and evaluation program in power plants is
very important because it provides comprehensive observation
of all critical components of the plants for the signs of corrosion.
The monitored parameters will be in the form of location,
rate, and underlying causes of corrosion. The results obtained
from this program will be used to predict the remaining life
of the object affected by corrosion, life extension strategies,
prospective material selection, and cost-effective methods for
refurbishment work.
Corrosion monitoring techniques play a key role in efforts to
combat corrosion, which can have major economic and safety
implications. The method often employed to determine the
general and localized corrosion is by using sacrificial samples
(coupons) placed at the interested location (Figure 2). To get
more accurate corrosion behavior of the plant, more coupons
would be placed and at wider locations.
Figure 1: Corroded inner pipe.
Thus, it is very important for the plant owner to implement
corrosion monitoring and control to protect the structure,
reduce costly and time consuming maintenance, and optimize
the performance of the facility. According to NACE (National
Association of Corrosion Engineers) International (2002), based
on the analysis on a number of key sectors (infrastructure,
utilities, government, transport and manufacturing), Malaysia
incurred annual cost of corrosion of about USD 6.7 billion (note:
GDP 2009 = USD 207.4 billion).
Figure 2: Typical set-up of test coupon.
(a)
(b)
Corrosion Monitoring Advancement - Real-time Corrosion
Measurement
The corrosion sensor is the essential element of all corrosion
monitoring systems. The sensor can be regarded as an
instrumented coupon. Over the years, corrosion evaluation
tools have been developed to help the corrosion engineer do
his or her job more efficiently so that he/she is able to react
before significant damage has occurred. As the technology in
microelectronics advances, real-time corrosion measurement
techniques can now be done and the data can be obtained
on-line as the equipment is constantly exposed to the process
stream (Figure 4). The system works on highly sensitive
measurements, with a signal response taking place essentially
instantaneously as the corrosion rate changes.
Figure 4: Corrosion transmitter
Advantages of Real-time Corrosion Measurement
1. Rather than determining corrosion occurrence over a
period of time using an outdated technique, corrosion
can now be monitored like any other process variable
(i.e., pressure, flow, level, temperature, pH) by the plant
operator or control systems engineer using the existing
human-machine interface (HMI). It acts as an evaluation
tool of system integrity and asset damage.
2. The operator can evaluate historical corrosion rates to
current rates and quickly determine changes in water
quality, chemical changes, and inhibitor performance.
3. The operator can plan for replacement of suspect
equipment as part of a predictive maintenance schedule.
4. The actual conditions of the process could be precisely
determined than the off-line information (Figure 5).
5. Be used as a proactive tool to assist with operating a plant
more effectively, thereby prolonging its life and gaining
optimum output
Figure 5: The difference in corrosion data distribution between
off-line information and on-line data (actual conditions).
Concluding Remarks
This article has presented the advanced online condition
monitoring system envisaged to be installed especially in all
TNB thermal power plants which are located at corrosion-prone
area. The most critical part is the steam condensing system
of which seawater is used as a cooling medium. With the
availability of this advanced monitoring system, more proactive
steps could be taken in operating the plant more effectively,
thereby prolonging its life and reducing unplanned outage. In
trying to achieve that, detail research in this area would be
carried-out by TNBR’s materials research group.
Power Transformer Online Monitoring for Improving
Productivity and Efficiency of Diagnostic Tasks
Dr. Mohd Radzian Abdul Rahman
Principal Researcher
(Smart Grid)
Readers could easily notice that Level 1 is total manual process
and Level 8 is autonomous automation process, whereas Level
2 to level 7 is semi-autonomous processes.
[email protected]
Introduction
Traditionally, the diagnostic processes using dissolved gas
analysis (DGA) for power transformer condition-based and
preventive maintenance are carried out manually; that is human
performs all the tasks; right from the collection of sample
at site to the action implementation on the transformer. In
recent years, with the advancement of Smart Grid Technology,
the automation of some diagnostic tasks to ensure “Safe and
Reliable” national grid and power system are made possible.
In the diagnostic context, the paradigm which claims “human
perform best in every processes” is old; while the idea
which states “automation could perform everything perfect
autonomously” is difficult to be realized. Therefore, a semiautonomous system (human-machine collaboration system),
that encompasses the strategic question - “Who (human or
automation) perform what tasks and when?” is more pragmatic.
As a part of Smart Grid Initiative, this article describes the
automation of power transformer diagnostic tasks, from
oil sampling to data analysis. The main contribution of this
research is the creation of an Analytics System, used to process
diagnostic inputs and produce operation and maintenance
decision recommendation outputs.
This article is structured as follow. Section 2 explains the Level of
Automation in a Human-Machine Collaboration System, Section
3 describes the power transformer online monitoring system,
Section 4 explains the Knowledge-Based Analytics System and
Section 5 briefly describes the benefits of an online monitoring
system.
Levels of Automation in Human-Machine System
In order to understand how human and automation
collaborates, different levels of automation are structured as in
Table 1 [Sheridan, 2002].
Level
1
2
3
4
Tasks
Human do all, machine do not help.
Machine offers human alternatives ways to do the tasks.
Machine select one way to do the task.
Machine selects one way to do the task and executes the
task if human approves.
5
Machine selects one way to do the task and allows human
restrictive time to veto before automatic execution.
Machine selects one way to do the task, executes tasks
automatically and obligatory informs human.
6
7
8
Machine selects one way to do the task, executes the tasks
automatically and informs human only if it is asked.
Machine selects one way to do the task, executes tasks
automatically and ignores human.
Table 1: Levels of Automation
Figure 1: Comparison of Different Methods
By introducing the power transformer online monitoring,
increase of automation level of diagnostic tasks is depicted as
in Figure 1. As an example, for manual DGA method (red line),
human does everything from data acquisition to implementation
of maintenance action.
On the other hand, the available commercial automation
system (black line) increases automation to Level 8 for data
acquisition and Level 2 for analyzing data. The system that we
develop (Scenario 1) increases automation to Level 8 for data
acquisition and data analyses, and Level 3 for decision-making.
The human operator is given the authority to implement decision
such as shutdown of power transformer, filter transformer oil or
perform preventive maintenance.
Power Transformer Online Monitoring System
The network architecture of the power transformer online
monitoring system is shown as in Figure 2.
Figure 2: Network Architecture
Sensors are installed at MidValley Megamall substation (PPU).
The sensors include DGA sensors, analogue sensors (moisture,
winding temperature, current (load), ambient temperature),
and a digital sensor (cooling fan on/off).
The DGA sensor uses photoacoustic spectroscoply technics to
determine the magnitude of the dissolved gases in oil (via infrared and microphone).
The system uses modbus TCP/IP for data transfer from PPU
MidValley to TNB Research office. Existing TNB fibre-optics and
pilot cable network are used, patched with ethernet cables for
end-communication to the sensors and the human-machine
interface.
Knowledge-Based Analytics System
In order to process the acquired data into outputs that could
recommend maintenance actions, knowledge-based methods
are used to construct several pieces of power transformer
condition evidence.
First, cummulative Weibull failure functions are utilized to
measure the criticality of power transformer condition, Duval
Triangle is constructed to detect faults and stray gases ratios are
introduced to detect and prevent noise gases from significantly
influencing the result. Second, these pieces of evidence
are fused through the Dempster-Shafer (DS) Approach, and
modified by Radzian (R) threshold interpretation rule (Radzian,
2011).
Finally, to refine the result further, the output of DS-R processes
are integrated with inputs such as load, winding temperature,
and cooling fan status through a structured decision tree
analysis. Examples of Human Machine Interface developed in the
Knowledge-Based System are shown in Figure 3, 4 and 5.
Figure 3: Duval Triangle for Fault Detection
Figure 4: Trend of Individual Combustible Gas
Figure 5: DS-R Fusion of Transformer Evidences
Benefits
The benefits of power transformer online monitoring system is
tremendous if the system is installed at critical places such as
urban commercial and industrial complexes, hospital and etc.
The main benefits are:
1. Increase productivity of the monitoring task up to one
sample per hour. (The cost of urgent DGA sample if taken
manually is around RM 600/sampling)
2. Increase efficiency of the diagnostic task due to reduction
of complex human thinking process and workload.
3. Increase of system operator’s situational awareness ability
through more frequent sampling, structured diagnostic
interferences and consideration of more condition inputs.
4. Reduction of risk of customer losses due to unplanned
shutdown.
In all, online monitoring system allows maintenance to be
planned as not to compromise safety and electricity delivery of
the transformer.
Concluding Remarks
This article has presented the proposition of an analytics
system for power transformer diagnostic tasks automation.
Automation is supposed to serve human and not the other
way around and it is already here and will remain. Its main
contribution to the society is the increase of productivity and
efficiency of diagnostic tasks, which end result, reduces losses
due to unplanned shutdown. In the future, this system could be
upgraded to automate the diagnostic task of a fleet of critical
power transformers instead of a single transformer.
Technical Training on Condition Monitoring and Assessment of
Power Transformer Using Insulating Oil and Electrical Testing
Nor Syahila Ahmad Marzuki
Assistant Lab Manager
(Oil And Fuel Laboratory)
[email protected]
Introduction
Power transformer is one of the most critical and costly
equipment used in the electrical power network. The failure of
transformers can cause interruption of power supply and result
in loss of revenue both to the company and as well as to the
society. Therefore, reliability of power transformers is of utmost
importance within the operations of the electric power utility.
Reliability is vital to the success of an organization, and in today’s
highly competitive business environment, unexpected failures
and unplanned downtime is no longer considered acceptable.
Thus, condition based maintenance through oil analysis and
electrical testing is becoming crucial to power utilities. Based
on the criticality of the subject, TNBR QATS lab personnel have
taken the initiative to conduct a technical training on the topic,
“Condition monitoring and assessment of power transformer
using insulating oil and electrical testing”. This technical training
has been successfully conducted between 21-23 January 2014.
Objective
The objective of the training is to make sure that all participants
will be able to:
• Determine the current standard used for transformer oil
management.
•
Determine the common incipient fault of transformer
based on Dissolved Gas Analysis.
•
Understand the importance of oil analysis, diagnostic and
corrective action to be taken.
•
To estimate the remaining life of transformer based on
furan analysis and Degree of Polymerization (DP).
•
To explain the important of oil sampling correctly.
•
To describe the complete process of oil sampling correctly.
•
Determine the basic electrical testing
•
Determine the advanced electrical testing
The scope that was covered in the technical training is
Transformer Oil Condition Assessment, Oil Analysis and
Diagnostic, Oil sampling, Basic Electrical Test and Advanced
Electrical Testing. The summary of the scope that has been
discussed during the training are as follows:
Transformer Oil Condition Assessment
Analysis of insulating oils is commonly used to diagnose and
assess the condition of transformers. This will provide an
overview of the most common tests, available standard and
TNB practice.
Transformer Analysis & Diagnostic
Currently there are three types of oil diagnostic methods to
assess the condition of transformer, oil or paper insulation:
Dissolved Gas Analysis (DGA)
DGA is a condition monitoring technique to detect incipient
thermal and electrical faults by analyzing the gas generation
within the transformer.
Oil Quality Analysis
The quality of the oil greatly affects the insulation and cooling
properties of the transformer. Performing tests to evaluate the
quality of the transformer oil constitute an important part for
the condition monitoring of transformers.
Furan Analysis
Transformer life depends on the life of the oil impregnated
paper insulation system. Degradation of the cellulose insulation
is an irreversible process. Chemical reaction of paper cellulose
cause opening of glucose rings providing free glucose molecules,
water, CO2 and organic acids. These glucose monomers further
decompose and produce furanic compounds as end products.
Furan and Degree of polymerization (DP) tests are used to
identify the extent of ageing of the cellulose in paper insulation
of the transformer.
Oil Sampling
The sampling procedure can be the weakest link in the chain of
operations when evaluating the quality of any insulating oil. The
validity of test results is dependent upon the quality of sample
that is truly representative of the oil in the equipment.
Electrical Testing
Oil diagnostic testing provides only partial information about the
condition of in-service transformer. In order to have complete
evaluation of overall condition of transformer, electrical testing
is needed.
Periodical field electrical diagnostic testing monitors the
condition of the transformer insulation and evaluates the useful
remaining life. The electrical diagnostics of power transformer
can be divided into two parts which are basic electrical diagnostic
testing and advanced electrical diagnostic testing.
Basic electrical diagnostic testing is a non-destructive test
conducted to determine the initial condition of the transformer
core and winding structure assembly as well as the insulation
system. This test includes but is not limited to the tan delta
measurement; turn ratio measurement, excitation current,
winding resistance and insulation resistance measurement.
In addition, when oil diagnostic testing and basic electrical
tests indicate potential problems in a transformer, an advanced
electrical diagnostic testing could be applied to determine the
root cause of the abnormalities and providing more reliable
information. Examples of advanced electrical diagnostic test
presented in this course are Frequency Response Analysis (FRA)
and Frequency Dielectric Spectroscopy (FDS).
Participants
Besides participants from TNB, this technical training successfully
also attracted participants from Electrical Contractors and
Consultants Companies as well as the Petrochemical industry. In
total there were about 25 participants for this technical training.
The participants commented that the course was indeed very
informative and very useful for their line of work.
Fig 2: En Zulfadhly session on Transformer Analysis
Fig 1: Opening ceremony by Pn Malathy, GM TNBR QATS Sdn Bhd
Fig 3: Normisahili on High Voltage briefing session
Fig 4: The Participants
TNBR Quality Assurance & Testing Services Sdn. Bhd.
A subsidiary of TNB Research Sdn. Bhd.
Scientific Services
The Oil and fuel (OFL) lab as well as the HV lab services
are parked under this section. Majority of the tests
conducted in these lab are ISO/IEC 17025 accredited. The
OFL is the largest transformer oil lab in the country and
has received “Certificate of excellence” for proficiency
testing by Institute Interlaboratory Studies, Netherlands
for 6 consecutive years
HV Lab
Oil Fuel Lab
Technical Services
Under Technical Services, there are 2 niche services that
we offer. The Forensic Engineering Group (FEG) which
conducts failure analysis on failed equipment and Plant
Inspection services (PINS) which conducts condition
assessment of power plant components .
PINS
Quality Assurance
Product Inspection (accredited to MS ISO/IEC 17020)
and Quality Audits. TNBR QATS has the capability of
conducting Product Inspection (PI) on a wide range of
products and we also have a highly experienced team
of auditors who have passed the IRCA ISO 9001 Lead
Auditor Course. Senior auditors have also been granted
Certified Quality Auditor (CQA) by the American Society
for Quality (ASQ)
FEG
The team have experience carrying out inspections and
audits all around the globe.
Quality Audit
TNB RESEARCH TECHNICAL EXPERTS
Hamdan Hassan
Technical Expert
(Combustion Performance)
Abdul Bahari Othman
Technical Expert
(Hydro System Optimization)
Ir. Ng Guat Peng
Technical Expert
(Failure Analysis)
Mohd Aizam Talib
Technical Expert
(Transformer)
Ir. Harriezan Ahmad
Technical Expert
(Switchgear)
Huzainie Shafi Abd Halim
Technical Expert
(Cable)
Muhammad Lutfi Ibrahim
Technical Expert
(Plan Life Assesment)
Ir. Noradlina Abdullah
Technical Expert
(Lightning Protection)
Contact us at www.tnbr.com.my