Optimization of combined cycle power plants using evolutionary algorithms

This paper deals with the application of an evolutionary algorithm to the minimization of the product cost of complex combined cycle power plants. Both the design configuration (process structure) and the process variables are optimized simultaneously. The optimization algorithm can choose among several design options included in a superstructure of the power plant such as different gas turbine systems available at the market, up to three pressure levels for steam generation in the heat-recovery steam generator, supplementary firing, steam reheat, parallel arrangement of heat exchangers in the gas path, and steam injection into the gas turbine. For the assumptions and simplifications made in this study, a 240 MW combined cycle power plant with a large gas turbine (150 MW), a two-pressure heat recovery steam generator with a reheater but without supplementary firing is favored from an economic viewpoint. A detailed exergy analysis of selected intermediate solutions and the final optimal design identifies the magnitude, location and causes of the thermodynamic inefficiencies.