Exergoeconomic analysis and optimisation of a gas-turbine power plant using PSO, GA and fuzzy logic system
by Maryam Khademi; Ahmad Khosravi
International Journal of Exergy (IJEX), Vol. 19, No. 2, 2016

Abstract: Optimally tuning design parameters of gas-turbine power plants from an exergoeconomic perspective is a challenging optimisation problem. This study first develops a cost function based on key parameters of the plant which include air compressor pressure ratio, combustion chamber inlet temperature, gas-turbine inlet temperature, gas-turbine and compressor isentropic efficiency. Evolutionary algorithms such as genetic algorithm and particle swarm optimisation are applied to minimise the cost function and optimally adjusting five design parameters. A fuzzy logic system is also developed to choose the best optimisation algorithm by matching the optimised parameters with respect to the base case. The proposed methods and algorithms are implemented for a gas-turbine power plant made by Siemens (model V94.2). Simulated results indicate that application of genetic algorithm method leads to better results in terms of cost per unit.

Online publication date: Wed, 30-Mar-2016

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