Exergetic, Exergoeconomic and Exergoenvironmental Multi-Objective Genetic Algorithm Optimization of Qeshm Power and Water Cogeneration Plant

Abstract

In this study, optimization of Qeshm power and water desalting cogeneration plant has been investigated. The objective functions are related to maximizing exergetic efficiency and minimization of exergoeconomic and exergoenvironmental parameters. Also, the integration of RO desalination with the existing plant has been evaluated based on these analyses. This plant includes two MAPNA 25 MW gas turbines, two heat recovery steam generators, and two MEDTVC desalination units. Thermodynamic modeling and simulation of the plant have been performed in MATLAB software. The thermodynamic simulation verified by Thermoflex software and plant data with high accuracy. Also, the computer code has been developed to perform exergetic, exergoeconomic and exergoenvironmental analysis. Multi-Objective Genetic Algorithm (MOGA) has been applied to find optimum objective functions and decision variables based on exergetic, exergoeconomic and exergoenvironmental parameters. Results show that in the optimum plant overall exergetic efficiency of the plant has been increased by 27.78%, and total exergetic cost and total exergoenvironmental impacts have been decreased by 0.93% and by 0.89%.