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Identification of Key Parameters for Benchmarking of Combined Cycle Power Plants Retrofit
Authors: S. Sabzchi Asl, N. Tahouni, M. H. Panjeshahi
Abstract:
Benchmarking of a process with respect to energy consumption, without accomplishing a full retrofit study, can save both engineering time and money. In order to achieve this goal, the first step is to develop a conceptual-mathematical model that can easily be applied to a group of similar processes. In this research, we have aimed to identify a set of key parameters for the model which is supposed to be used for benchmarking of combined cycle power plants. For this purpose, three similar combined cycle power plants were studied. The results showed that ambient temperature, pressure and relative humidity, number of HRSG evaporator pressure levels and relative power in part load operation are the main key parameters. Also, the relationships between these parameters and produced power (by gas/ steam turbine), gas turbine and plant efficiency, temperature and mass flow rate of the stack flue gas were investigated.Keywords: Combined cycle power plant, energy benchmarking, modelling, Retrofit.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1125635
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[1] S. C. Kaushik, V. S. Reddy, and S. K. Tyagi, “Energy and exergy analyses of thermal power plants: A review,” Renew. Sustain. Energy Rev., vol. 15, no. 4, pp. 1857–1872, 2011.
[2] H. H. Erdem, A. V. Akkaya, B. Cetin, A. Dagdas, S. H. Sevilgen, B. Sahin, I. Teke, C. Gungor, and S. Atas, “Comparative energetic and exergetic performance analyses for coal-fired thermal power plants in Turkey,” Int. J. Therm. Sci., vol. 48, no. 11, pp. 2179–2186, 2009.
[3] S. Benchmarking, “Benchmarking for Success.” 2003.
[4] R. C. Camp, Benchmarking: the search for industry best practices that lead to superior performance. Milwaukee, Wis.: Quality Press; Quality Resources, 1989., 2013.
[5] N. Keren, H. H. West, and M. S. Mannan, “Benchmarking MOC practices in the process industries,” Process Saf. Prog., vol. 21, no. 2, pp. 103–112, 2002.
[6] A. Lissitsa, T. Coelli, and D. S. P. Rao, “Agricultural economics education in Ukrainian Agricultural Universities: An efficiency analysis using data envelopment analysis,” in Proceedings 11th International Congress of European Association of Agricultural Economists, 2005.
[7] C. H. Liu, S. J. Lin, and C. Lewis, “Evaluation of thermal power plant operational performance in Taiwan by data envelopment analysis,” Energy Policy, vol. 38, no. 2, pp. 1049–1058, 2010.
[8] C. P. Barros, “Efficiency analysis of hydroelectric generating plants: a case study for Portugal,” Energy Econ., vol. 30, no. 1, pp. 59–75, 2008.
[9] M. Nakano and S. Managi, “Regulatory reforms and productivity: an empirical analysis of the Japanese electricity industry,” Energy Policy, vol. 36, no. 1, pp. 201–209, 2008.
[10] T. Thakur, S. G. Deshmukh, S. C. Kaushik, and M. Kulshrestha, “Impact assessment of the Electricity Act 2003 on the Indian power sector,” Energy Policy, vol. 33, no. 9, pp. 1187–1198, 2005.
[11] A. Vaninsky, “Efficiency of electric power generation in the United States: analysis and forecast based on data envelopment analysis,” Energy Econ., vol. 28, no. 3, pp. 326–338, 2006.
[12] K. Sarıca and I. Or, “Efficiency assessment of Turkish power plants using data envelopment analysis,” Energy, vol. 32, no. 8, pp. 1484–1499, 2007.