Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant

Ugwuoke Philip Emeka; Obodeh Otunuya

doi:doi:10.11648/j.epes.20170606.12

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Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant

Ugwuoke Philip Emeka, Obodeh Otunuya

Published in American Journal of Electrical Power and Energy Systems (Volume 6, Issue 6)

Received: 11 July 2017 Accepted: 7 August 2017 Published: 15 November 2017

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Abstract

The operating cost for optimal performance of 100MW Delta IV gas turbine unit of Ughelli power plant was determined using optimum operating parameters and exergoeconomics. The optimizatioon tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in Matlab (Version 2011b) programming language. Eight optimal operating parameters of the plant were involved; compressor inlet temperature (T₁), compressor pressure ratio (r_p), compressor isentropic efficiency (η_ic), turbine isentropic efficiency (η_it), turbine exhaust temperature (T₄), air mass flow rate (m_a), fuel mass flow rate (m_f) and fuel supply temperature (T_f). Eight decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. An objective function representing the total operating cost of the plant was defined in terms of N per hour as sum of operating cost (relating to the fuel consumption), rate of capital cost (relating to capital investment and maintenance expenses), and rate of exergy destruction cost. The optimal values of the decision variables (constraints) were obtained by minimizing the objective function. The GA optimal results obtained were m_a= 530kg/s, m_f= 7.00g/s. The GA operating cost and the component GA optimum results for exergy destruction cost rate and capital investment cost rate required to sustain optimum performance were obtained. The operating cost (Ċ_f), cost of exergy destruction rate (Ċ_D) and capital investment cost rate (Z_K) for the compressor, combustion chamber and turbine are: (Ċ_f) = N244.72 per hour giving a variation of -0.57%, Ċ_Dc = N87,728.32 per hour giving a variation of +13.59%, (Ż_C) = N936,016.00 per hour giving a variation of -37.6% , (Ċ_DCC) = N470,288 per hour, a variation of -88.73%, Ż_CC = N93,160.8 per hour, a variation of +305.6%, Ċ_Dt = N144,278.4 per hour, a variation of -84.31%, Ż_t = N1,428,252.8 per hour a variation of +160.1%. These variations were in relation to base results.

Published in	American Journal of Electrical Power and Energy Systems (Volume 6, Issue 6)
DOI	10.11648/j.epes.20170606.12
Page(s)	88-93
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Operating Cost, Optimal Performance, Optimization, Exergoeconomic, Genetic Algorithm

References

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[2]	Bejan, A., Tsatsaronis, G. and Moran, M. (1996). Thermal Design and Optimization. Wiley, New York.
[3]	Coley, A. D. (1999); An Introduction to Genetic Algorithms for Scientists and Engineers, 2^th Edition, World Scientific Publishing Co. Pte. Ltd, Singapore, 211pp.
[4]	Malhotra, R.; Singh, N. and Singh, Y. (2011); Genetic Algorithms: Concepts, Design for Optimization of Process Controllers, Computer and Information Science, Vol. 4, No. 2, pp. 39-54.
[5]	PHCN (2015); Ughelli Power Plant Logbook, Ughelli, Delta State, Nigeria.
[6]	Obodeh, O. and Ugwuoke, P. E. (2017); Optimal Operating Parameters Of 100mw Delta Iv Ughelli Gas Turbine Power Plant Unit, in press.
[7]	Moran, M. J. and Shapiro, H. (2000). Fundamentals of Engineering Thermodynamics, 4^th Edition, Wiley, New York.
[8]	Khosravi, A.; Gorji-Bandpy, M. and Fazelpour, F. (2014); Optimization of a Gas Turbine Cycle by Genetic and PSO Algorithms, Journal of Middle East Applied Science and Technology (JMEAST), Issue 21, pp. 706-711.
[9]	Emefiele, G. (2016). MPR: Banks Raise Interest Rates on Existing Loans. Punch Newspapers, July 29.
[10]	Moran, M. J. (1982). Availability Analysis; A Guide to Efficient Energy Use, USA: Prentice Hall, Englewood Cliffs, N. J.
[11]	Ebadi, M. and Gorji-Bandpy, M. (2005). Exergetic Analysis of Gas Turbine Plants. International Journal of Exergy 2 (4), 31-39.
[12]	Gorji-Bandpy, M. and Goodarzian, H. (2011). Exergoeconomic Optimization of Gas Turbine Power Plant Operating Parameters Using Genetic Algorithm: A Case Study. J Thermal Science, 15, 43-54.
[13]	Srinivas, N. and Deb, K. (2002); Multi-Objective Optimization using Non-Dominated Sorting in Genetic Algorithms, Journal of Evolutional Computation, Vol. 2, No. 3, pp. 221-248.
[14]	Jomison Janawitz, James Masso and Christopher Childs (2015). Heavy-Duty Gas Turbine Operating and Maintenance Consideration Ger 3620M. GE Power and Water, Atlanta, Georgia, February.

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APA Style

Ugwuoke Philip Emeka, Obodeh Otunuya. (2017). Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant. American Journal of Electrical Power and Energy Systems, 6(6), 88-93. https://doi.org/10.11648/j.epes.20170606.12

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Ugwuoke Philip Emeka; Obodeh Otunuya. Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant. Am. J. Electr. Power Energy Syst. 2017, 6(6), 88-93. doi: 10.11648/j.epes.20170606.12

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AMA Style

Ugwuoke Philip Emeka, Obodeh Otunuya. Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant. Am J Electr Power Energy Syst. 2017;6(6):88-93. doi: 10.11648/j.epes.20170606.12

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@article{10.11648/j.epes.20170606.12,
  author = {Ugwuoke Philip Emeka and Obodeh Otunuya},
  title = {Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {6},
  number = {6},
  pages = {88-93},
  doi = {10.11648/j.epes.20170606.12},
  url = {https://doi.org/10.11648/j.epes.20170606.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20170606.12},
  abstract = {The operating cost for optimal performance of 100MW Delta IV gas turbine unit of Ughelli power plant was determined using optimum operating parameters and exergoeconomics. The optimizatioon tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in Matlab (Version 2011b) programming language. Eight optimal operating parameters of the plant were involved; compressor inlet temperature (T1), compressor pressure ratio (rp), compressor isentropic efficiency (ηic), turbine isentropic efficiency (ηit), turbine exhaust temperature (T4), air mass flow rate (ma), fuel mass flow rate (mf) and fuel supply temperature (Tf). Eight decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. An objective function representing the total operating cost of the plant was defined in terms of N per hour as sum of operating cost (relating to the fuel consumption), rate of capital cost (relating to capital investment and maintenance expenses), and rate of exergy destruction cost. The optimal values of the decision variables (constraints) were obtained by minimizing the objective function. The GA optimal results obtained were ma= 530kg/s, mf= 7.00g/s. The GA operating cost and the component GA optimum results for exergy destruction cost rate and capital investment cost rate required to sustain optimum performance were obtained. The operating cost (Ċf), cost of exergy destruction rate (ĊD) and capital investment cost rate (ZK) for the compressor, combustion chamber and turbine are: (Ċf) = N244.72 per hour giving a variation of -0.57%, ĊDc = N87,728.32 per hour giving a variation of +13.59%, (ŻC) = N936,016.00 per hour giving a variation of -37.6% , (ĊDCC) = N470,288 per hour, a variation of -88.73%, ŻCC = N93,160.8 per hour, a variation of +305.6%, ĊDt = N144,278.4 per hour, a variation of -84.31%, Żt = N1,428,252.8 per hour a variation of +160.1%. These variations were in relation to base results.},
 year = {2017}
}

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TY  - JOUR
T1  - Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant
AU  - Ugwuoke Philip Emeka
AU  - Obodeh Otunuya
Y1  - 2017/11/15
PY  - 2017
N1  - https://doi.org/10.11648/j.epes.20170606.12
DO  - 10.11648/j.epes.20170606.12
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 88
EP  - 93
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20170606.12
AB  - The operating cost for optimal performance of 100MW Delta IV gas turbine unit of Ughelli power plant was determined using optimum operating parameters and exergoeconomics. The optimizatioon tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in Matlab (Version 2011b) programming language. Eight optimal operating parameters of the plant were involved; compressor inlet temperature (T1), compressor pressure ratio (rp), compressor isentropic efficiency (ηic), turbine isentropic efficiency (ηit), turbine exhaust temperature (T4), air mass flow rate (ma), fuel mass flow rate (mf) and fuel supply temperature (Tf). Eight decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. An objective function representing the total operating cost of the plant was defined in terms of N per hour as sum of operating cost (relating to the fuel consumption), rate of capital cost (relating to capital investment and maintenance expenses), and rate of exergy destruction cost. The optimal values of the decision variables (constraints) were obtained by minimizing the objective function. The GA optimal results obtained were ma= 530kg/s, mf= 7.00g/s. The GA operating cost and the component GA optimum results for exergy destruction cost rate and capital investment cost rate required to sustain optimum performance were obtained. The operating cost (Ċf), cost of exergy destruction rate (ĊD) and capital investment cost rate (ZK) for the compressor, combustion chamber and turbine are: (Ċf) = N244.72 per hour giving a variation of -0.57%, ĊDc = N87,728.32 per hour giving a variation of +13.59%, (ŻC) = N936,016.00 per hour giving a variation of -37.6% , (ĊDCC) = N470,288 per hour, a variation of -88.73%, ŻCC = N93,160.8 per hour, a variation of +305.6%, ĊDt = N144,278.4 per hour, a variation of -84.31%, Żt = N1,428,252.8 per hour a variation of +160.1%. These variations were in relation to base results.
VL  - 6
IS  - 6
ER  -

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Author Information

Ugwuoke Philip Emeka

Mechanical Engineering Department, Petroleum Training Institute, Effurun, Nigeria
Obodeh Otunuya

Mechanical Engineering Department, Ambrose Alli University, Ekpoma, Nigeria

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APA Style

Ugwuoke Philip Emeka, Obodeh Otunuya. (2017). Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant. American Journal of Electrical Power and Energy Systems, 6(6), 88-93. https://doi.org/10.11648/j.epes.20170606.12

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ACS Style

Ugwuoke Philip Emeka; Obodeh Otunuya. Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant. Am. J. Electr. Power Energy Syst. 2017, 6(6), 88-93. doi: 10.11648/j.epes.20170606.12

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AMA Style

Ugwuoke Philip Emeka, Obodeh Otunuya. Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant. Am J Electr Power Energy Syst. 2017;6(6):88-93. doi: 10.11648/j.epes.20170606.12

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@article{10.11648/j.epes.20170606.12,
  author = {Ugwuoke Philip Emeka and Obodeh Otunuya},
  title = {Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {6},
  number = {6},
  pages = {88-93},
  doi = {10.11648/j.epes.20170606.12},
  url = {https://doi.org/10.11648/j.epes.20170606.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20170606.12},
  abstract = {The operating cost for optimal performance of 100MW Delta IV gas turbine unit of Ughelli power plant was determined using optimum operating parameters and exergoeconomics. The optimizatioon tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in Matlab (Version 2011b) programming language. Eight optimal operating parameters of the plant were involved; compressor inlet temperature (T1), compressor pressure ratio (rp), compressor isentropic efficiency (ηic), turbine isentropic efficiency (ηit), turbine exhaust temperature (T4), air mass flow rate (ma), fuel mass flow rate (mf) and fuel supply temperature (Tf). Eight decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. An objective function representing the total operating cost of the plant was defined in terms of N per hour as sum of operating cost (relating to the fuel consumption), rate of capital cost (relating to capital investment and maintenance expenses), and rate of exergy destruction cost. The optimal values of the decision variables (constraints) were obtained by minimizing the objective function. The GA optimal results obtained were ma= 530kg/s, mf= 7.00g/s. The GA operating cost and the component GA optimum results for exergy destruction cost rate and capital investment cost rate required to sustain optimum performance were obtained. The operating cost (Ċf), cost of exergy destruction rate (ĊD) and capital investment cost rate (ZK) for the compressor, combustion chamber and turbine are: (Ċf) = N244.72 per hour giving a variation of -0.57%, ĊDc = N87,728.32 per hour giving a variation of +13.59%, (ŻC) = N936,016.00 per hour giving a variation of -37.6% , (ĊDCC) = N470,288 per hour, a variation of -88.73%, ŻCC = N93,160.8 per hour, a variation of +305.6%, ĊDt = N144,278.4 per hour, a variation of -84.31%, Żt = N1,428,252.8 per hour a variation of +160.1%. These variations were in relation to base results.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Operating Cost for Optimal Performance of 100MW Gas Turbine Unit of Ughelli Power Plant
AU  - Ugwuoke Philip Emeka
AU  - Obodeh Otunuya
Y1  - 2017/11/15
PY  - 2017
N1  - https://doi.org/10.11648/j.epes.20170606.12
DO  - 10.11648/j.epes.20170606.12
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 88
EP  - 93
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20170606.12
AB  - The operating cost for optimal performance of 100MW Delta IV gas turbine unit of Ughelli power plant was determined using optimum operating parameters and exergoeconomics. The optimizatioon tool is an evolutionary algorithm known as Genetic Algorithm (GA). The computer application used in this work is written in Matlab (Version 2011b) programming language. Eight optimal operating parameters of the plant were involved; compressor inlet temperature (T1), compressor pressure ratio (rp), compressor isentropic efficiency (ηic), turbine isentropic efficiency (ηit), turbine exhaust temperature (T4), air mass flow rate (ma), fuel mass flow rate (mf) and fuel supply temperature (Tf). Eight decision variables were optimally adjusted by the Genetic Algorithm (GA) to minimize the objective function. An objective function representing the total operating cost of the plant was defined in terms of N per hour as sum of operating cost (relating to the fuel consumption), rate of capital cost (relating to capital investment and maintenance expenses), and rate of exergy destruction cost. The optimal values of the decision variables (constraints) were obtained by minimizing the objective function. The GA optimal results obtained were ma= 530kg/s, mf= 7.00g/s. The GA operating cost and the component GA optimum results for exergy destruction cost rate and capital investment cost rate required to sustain optimum performance were obtained. The operating cost (Ċf), cost of exergy destruction rate (ĊD) and capital investment cost rate (ZK) for the compressor, combustion chamber and turbine are: (Ċf) = N244.72 per hour giving a variation of -0.57%, ĊDc = N87,728.32 per hour giving a variation of +13.59%, (ŻC) = N936,016.00 per hour giving a variation of -37.6% , (ĊDCC) = N470,288 per hour, a variation of -88.73%, ŻCC = N93,160.8 per hour, a variation of +305.6%, ĊDt = N144,278.4 per hour, a variation of -84.31%, Żt = N1,428,252.8 per hour a variation of +160.1%. These variations were in relation to base results.
VL  - 6
IS  - 6
ER  -

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