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Int. J. Engg. Res. & Sci. & Tech. 2014 K K Ikpambese et al., 2014
PERFORMANCE EVALUATION OF GAS TURBINE
POWER STATION: OMOTOSHO PHASE 1
K K Ikpambese1*, J N Akaaza1 and A Iortsor
In this paper, performance evaluation of gas turbine power station of Omotosho phase 1 stationin Nigeria was carried out. The evaluation was carried out for a period of three years based onperformance indices such as availability, capacity, utilization and load factors. Others werethermal efficiency and percentage contribution of each unit to the total power generation of thestation. The indices showed that the plant was running at an average utilization of 32.9% asagainst the international best practices of over 95%. This data was confirmed by using ANOVA(analysis of variance) to analyze the factors /indices above at 5% significant level and it showedthere was no difference between the variables. Hence, the failure of the power station wasattributed to the environmental and technical problems as well as poor training of operation andmaintenance personnel.
Keywords: Performance evaluation, Performance indices, Omotosho power station, Gasturbine
*Corresponding Author: K K Ikpambese � [email protected]
INTRODUCTION
The significance of electricity as a source of
energy in the socio-economic development of
Nigeria cannot be over-emphasized. Over the
years concerted efforts have been made to
improve on the electricity generation and
distribution in the country. This, however, have
not yielded the required results as current installed
capacity for electric energy generation is put at
6200 MW while actual output hovers between
2500 MW and 3200 MW (Nigerian statistics
Bureau, 2007).
1 Department of Mechanical Engineering, University of Agriculture Makurdi -Nigeria.
Int. J. Engg. Res. & Sci. & Tech. 2014
ISSN 2319-5991 www.ijerst.com
Vol. 3, No. 3, August 2014
© 2014 IJERST. All Rights Reserved
Research Paper
The increasing concern about the lowelectricity generation capacity in Nigeria and itseffects on the socio-economic development ofthe country lead to the establishment ofOmotosho phase 1 power station with totalinstalled capacity of 335 MW to boost generation/distribution of electricity in Nigeria.
Omotosho gas turbine power station is locatedat Omotosho town along Lagos/Benin expressway in Ondo State, Nigeria. This location waschosen due to availability of fuel supplies forcombustion, fresh water for cooling, transmission
facilities and accessibility.
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Int. J. Engg. Res. & Sci. & Tech. 2014 K K Ikpambese et al., 2014
In an attempt to improve on the capacity
utilization of Nigerian power stations, several
works have been carried out by different
researchers. Hart (1995) did a study on the “First
Decade of Large-Power Gas Turbine in Nigeria”.
In his study, he used Sapele gas turbine plant as
a case study. He evaluated the performance value
of the turbine sets and also their maintenance
history for the period under study. In his work he
found out that the gas turbine sets did not fare
well in the first ten years of installation. This was
mainly due to the peculiar environmental
conditions such as high ambient temperature,
large amount of dust in the air and instability of
the national grid system.
Odi-Owei (1992), also conducted a study on
the “Performance Appraisal of the Afam Gas
Turbine plant”. He evaluated the performance of
each turbine set for the various plants. He also
took a survey of trips based on the nature and
causes of the outages. In his research, he
discovered that the performance was below
expectations and attributed it to forced outages
caused by disturbances in the national grid and
internal problems in the gas turbine. He opined
that poor preventive maintenance as well as
overhaul history of the turbine and lack of funds
for replacement of damaged components were
responsible for the low performance.
Obodeh and Isaac (2011), also did a study on
the “Performance Analysis for Sapele Thermal
Power Station: A Case Study of Nigeria”. In this
work, performance indices as measured by
percentage shortfall of energy generated, load
factor, utilization factor and capability factor of
Sapele power station in the period of 1997 to 2006
was presented. They discovered that the large
gap between installed and actual operational
capacity of the plant may be due to ageing facilities
and poor maintenance of the plant. Measures to
improve the performance indices were
suggested, such as regular training of operation
and maintenance staff; improvement in operation
and maintenance culture, proper spare parts
inventory, regular management meetings and
good housekeeping of the plant.
Despite efforts made by previous researchers
in the area of power generation and distribution
in Nigeria, the fact remains that electricity
generation capacity utilization of Nigerian power
stations is still very low compared to their
designed output. This study carried out a detailed
performance evaluation of Omotosho Gas
Turbine plant in order to compare its actual with
designed values and recommend possible ways
of optimizing the plant in order to achieve better
output to boost the national grid. As the
contribution of this plant to the national grid would
go a long way in enhancing large scale production
in industries and improve socio-economic
activities in Nigeria.
MATERIALS AND METHODS
Data were obtained from Omotosho power station’s
logbook. These are inventory records of monthly
energy generation between 2009 and 2011 and
operational statistics showing the period of major
outage and the time of maintenance. In processing
the data for this evaluation work, the main focus
was on the following diagnostic techniques/formulas
which were used to monitor and measure the
performance of the gas turbine plant: Load factor,
Capability factor, Utilization factor, Frequency factor,
Capacity factor, Availability factor and Percentage
contribution to station total output by units. The
station performance was assessed using the
following parameters determined on both monthly
and annual basis.
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Int. J. Engg. Res. & Sci. & Tech. 2014 K K Ikpambese et al., 2014
( )Load Factor FL
AverageGenerationOutput
The peak load during the same period
=
...(1)
( )Capability Factor Fp
AvailableGenerationCapability
Net Installed Capacity
=
...(2)
( )
exp
UtilizationFactor Fu
EnergyActuallyproducedbyaunitinagiventime
Energythatcouldhavebeen ortedif theunitoperatedatitsinstalledcapacity
=
...(3)
( ) 100Energy Generated
Frequency Factor FcAvailable Energy
= ×
...(4)
The following parameters are used in
assessing individual unit’s performance:
( )cCapacityFactor F
Energyactuallyproducedbyaunitinagiventime
Energythatcouldhavebeenproducedif theunitoperatedatitsinstalledcapacity
=
...(5)
Availability Factor(F ) =a
Actual Time(running hpurns)the plant wasin service
Thetotal timeinterval under consideration
...(6)
int
PercentageContributiontoStationTotalOutput=
Total Energy generated byaunit ina giventime erval
Total energy generated bythestationinthesame period
...(7)
Another parameter used in this evaluation
work is Thermal efficiency of the Gas Turbine
Plant.
Note: average generation output =
Hours in a year =8760 h
Available generation capability = Capability x
number of units available
Available energy =Operating capacity x time
the machine actually run.
Energy that could have been generated at that
interval = Installed capacity x available time
RESULTS AND DISCUSSION
Energy Generated, Consumed andExported
The plant generated between 76MW and 152 MW
of electricity as seen in Figure 1 as against the
installed capacity of 335 MW. It was observed
that there was a constant decrease in generation
throughout the three years under review. The
station generated a total of 396,833 MWH in
2009,388,272 MWH in 2010 and 371,997 MWH
in 2011. This drop in generation could be attributed
to rising cost of machine inputs, e.g., cost of fuel
(gas), aging facilities coupled with poor
maintenance of the plant. Statistically, using
ANOVA it was observed that there was no
difference between the variables under analysis
for energy generated at 5% significant level.
The consumption of the generated energy
stood at 11,753 MWH in 2009, 14,169 MWH in
2010 and 13,352 MWH in 2011 as seen in Figure
2. It was again observed that statistically, there
was no difference between the variables using
ANOVA for energy consumed at 5% significant
level.
In terms of energy exported to the national grid
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Figure 1: Varuation of Energy Generated with Months
Figure 2: Varuation of Energy Consumed with Months
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Figure 3: Varuation of Energy Exported to the National Grid with Months
as observed from Figure 3 dropped from 385,080
MWH in 2009 to 381,333 MWH in 2010 and to
366,202.09 MWH in 2011, showing a decrease
of 0.97 % in 2010 and 3.4% in 2011. Statistically,
using ANOVA, there was no difference between
the variables under analysis for energy exported
at 5% significant level.
Availability and Capacity Factor
The variations of availability factor with each of
the gas turbine units are shown in Figure 4. It can
be seen that in 2009, GT4 had the highest
availability factor of 36.52%, while GT3 had the
lowest factor of 3.18%. In 2010, GT8 had the
highest availability of 50.4% while GT2 and GT4
recorded the lowest availability factor of 0% due
to generator differential fault. In 2011, GT1 had
the highest availability factor of 71.04% while GT2
and GT4 still had the lowest factor due to the
generator differential fault in 2010. This shows
that the performance of the various units could
not be improved since the availability was low.
Statistically using ANOVA, it was observed that
there was no difference between the variables
under analysis for availability factor at 5%
significant level.
The annual variation of capacity factor is
shown in Figure 5. It was observed that in 2009,
GT4 had the highest capacity factor of 23.06%
while GT3 had the lowest factor of 2.06%. In 2010,
GT8 had the highest capacity factor of 41.01%
while GT2 and GT4 had 0%. In 2011, GT1 had
the highest capacity factor of 42.85% while GT2
and GT4 had 0%.
The above data has shown that the plant
performance was far below the international best
practices of between 50% and 80%. The capacity
and utilization factors are the main pointers to
the wellbeing of the plant in terms of output. A low
capacity factor signifies that the average energy
generation from the plant is low. This could also
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Figure 4: Varuation of Availability Factors with Gas Turbine Units
Figure 5: Varuation of Availability Factors with Gas Turbine Plants for 2009, 2010 and 2011
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Int. J. Engg. Res. & Sci. & Tech. 2014 K K Ikpambese et al., 2014
mean that plant failure is high hence low capacity
utilization during the year leading to high cost of
operating the plant. High capacity factor is desired
for economic operation of the plant (Obodeh and
Isaac, 2011). Statistically, using ANOVA, it was
observed that there was no difference between
the variables under analysis for capacity factor
at 5% significant level.
Utilization Factor and Load Factor
The maximum utilization factor for 2009 was
87.37% and the minimum was 10.84% as shown
in Figure 6. In 2010, the highest utilization factor
was 51.68% and minimum of 11%. In 2011, it was
60.27% maximum and minimum of 4.21%. The
average utilization factor for the years under
review 2009, 2010 and 2011 are 31.54%, 34.64%
and 32.56%, respectively.
This data falls far below the international best
practices of over 95% (Obodeh and Isaac, 2011).
This was due to the fact that some of thegenerating equipments were not utilized at all,while some were under utilized for reasons ofroutine inspection and maintenance. Statisticallyusing ANOVA, it was observed that there was nodifference between the variables under analysisfor utilization factor at 5% significant level.
Figure 7 shows load factor for the period underreview. The load factor is an indication of theutilization of power plant capacity. A high loadfactor means that the total plant capacity isutilized for most of the time as is desirable fromthe point of view of reducing cost of generationper unit of energy produced (Obodeh and Isaac,2011). The maximum load factors for 2009, 2010and 2011 were 87.96%, 80.64%, and 84.23%,
respectively. This shows that the little available
plant capacity was well utilized within the period
Figure 6: Variations of Utilization Factor with Months
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Figure 7: Variations of Load Factor with Months for 2009, 2010, and 2011
and conforms to International best practices of
80%. However, the plant could not run all the time
at this acceptable rate, hence the minimum load
factors for 2009, 2010 and 2011 were 22.26%,
13.02% and 41.13%, respectively.
Statistically, using ANOVA, it was observed that
there was no difference between the variables
under analysis for load factor at 5% significant
level.
Gas Consumed Thermal Efficiency andPercentage Contribution to the NationalGrid
Figure 8 shows the variations of gas consumed
with each month of the year under review. The
station consumed a total of 4359, 116,936 scf of
fuel in 2009, 5,190,460,760 scf in 2010, and
4,395,938,025.60 scf of fuel in 2011. Statistically,
using ANOVA it was observed that there was no
difference between the variables under analysis
for gas consumed at 5% significant level.
Figure 9 shows the variation of thermal
efficiency with months in the years under review.
The average thermal efficiency for the year
2009, 2010 and 2011 was 34.226%, 30.32% and
30.48%, respectively. This compares favorably
with the designed cycle thermal efficiency of
32.4% and 48.2% under cold-air-standard
assumptions.
Figures 10, 11 and 12 show the percentage
contribution of each unit to the station total
generation for 2011, 2010 and 2009 respectively.
In 2011, GT1 made the highest contribution of
157,216 MWH representing 42.03% of the total
generation. GT2 and GT4 were not working at all,
while GT5 contributed only 201 MWH which is
0.05% of total generation.
In 2010, GT8 made the highest contribution of
150,469 MWH representing 38.72% of total
generation. GT3 made the lowest contribution of
only 9 MWH In 2009, GT4 made the highest
contribution of 84,577 MWH representing 21.31%
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Figure 8: Variation of Energy Consumed with Months for 2009, 2010, and 2011
Figure 9: Variations of Thermal Efficiency with Months
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Int. J. Engg. Res. & Sci. & Tech. 2014 K K Ikpambese et al., 2014
Figure 10: Percentage Contribution of Each Gas Turbine Unit to Station's Total in 2009
Figure 11: Percentage Contribution of Gas Turbine Units to Station's total in2010
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Int. J. Engg. Res. & Sci. & Tech. 2014 K K Ikpambese et al., 2014
Figure 12: Percentage Contribution of Each Gas Turbine Unit to Station's Total in 2009
of station total. All the plants were in operation
with GT3 making the lowest contribution of 7,581
MWH representing 1.91%. Statistically, using
ANOVA, it was observed that there was no
difference between the variables under analysis
for percentage contribution by each GT unit at
5% significant level.
CONCLUSION
Having evaluated the performance of Omotosho
Phase 1 gas Turbine Power Plant from 2009 to
2011; it is obvious that the plant performed below
average capacity throughout the period under
review. The station had low availability factor, low
capacity factor, and low utilization factor which
ranged from 31.54% to 34.64% as against the
International best practice of over 95%.
The following causes were identified as being
responsible for the low performance indices and hence
the general poor performance of the power plant.
1. Generator differential fault which brought
down GT2 and GT4 during 2010-2011.
2. GT3 and GT6 were not available due to high
bearing vibration and both were shutdown
in April and May 2010, respectively.
3. Excitation and high vibration problems were
reasons for low performance of GT5 and
GT6 in 2011.
4. High idle time for some plants in the name
of routine inspection /maintenance.
5. National Grid related problems also
contributed to low performance.
6. Others were environmental conditions such
as high ambient temperature and large
amount of dust in the air.
7. Lack of consumables like spares and
materials for repairs.
8. The plant is an old one as well as the
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technology. This culminated in the frequent
breakdowns and equipments failures.
Consequently, there was high rate of repairs
and maintenance activities leading to high
man hour lost and low productivity of the plant.
9. The Chinese language used in the
operational manuals also caused difficulties
for maintenance crew to understand what
should be done in times of equipment failure.
10. The removal of fuel subsidy by the President
in 2011 also affected output due to increased
cost of plant operation as a result of high
cost of fuel.
RECOMMENDATIONS
The following measures have been proffered to
improve performance of Omotosho Phase 1
power plant:
1. Provision of enough running spares as well
as proper spare parts inventory control.
2. Training and retraining of the operation and
maintenance personnel who could be more
vast in the operation of the plant, rather than
depending on the Chinese Technicians which
increased cost of operation and caused delays
in solving problems.
3. Translation of the operational manuals from
Chinese to English would go a long way in
reducing down time of the plant.
4. The compressed air unit should be rehabilitated
to blow out dust particles trapped in the air
using an automatic inlet filter instead of the
manual cleaning that takes a lot of time to do.
5. Planned maintenance programs should be
established and strictly followed to improve
reliability and plant performance.
6. Constant supply of gas to the plant should be
ensured at an affordable rate.
7. Energy conservation of the plant by way of
reinjection of heat from the plants to run the
turbines. This will also solve the environmental
problem of pollution by exhaust gases which
affect the ozone layer.
REFERENCES
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(iso) Gas Turbine Power Plant at
Omotosho, Ondo State”, NSE Report.
2. ECN (Ed.) (2003), The Nigerian Energy
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3. Edeoja A ( 2010), Thermodynamics lecture
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