Multi-objective linear regression based optimization of full repowering a single pressure steam power plant

A. Mehrpanahi, S. Nikbakht Naserabad and G. Ahmadi

Energy, 2019, vol. 179, issue C, 1017-1035

Abstract: Full repowering of Be'sat steam power plant has been studied in this work. The methodology is used to simulate the new cycle according to its principal specifications and to optimize it based on the objective functions. Objective functions are electricity cost per kWh and exergy efficiency. These parameters are functions of the pinch and approach point temperature differences at high and low pressure points and at the pre-heater in the heat recovery steam generator (HRSG), steam turbine inlet flow rate, gas turbine (GT) isentropic efficiency, air compressor isentropic efficiency and compressor pressure ratio. Finally, considering the introduced objective functions, it is tried to achieve the most optimized techno-economic characteristics for Be'sat power plant repowering cycle using the genetic algorithm with two scenarios of single and multi-objective optimizations. The results show that the efficiencies of the repowered cycle are 52.59% and 51.3% for two cases of unfired and fired duct burners, respectively.

Keywords: Linear regression; Full repowering; Steam power plant; Gas turbine; Combined cycle (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:179:y:2019:i:c:p:1017-1035

DOI: 10.1016/j.energy.2019.04.208

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