Thermodynamic Optimization of Steam Boiler Parameter Using Genetic Algorithm

Abstract

In this paper, genetic algorithm implemented in Matlab is used for the optimization of the boiler unit at Egbin power plant. Based on thermodynamic consideration of a boiler, the thermal efficiency of the boiler for 2008 and 2009 is computed. The thermal efficiency is defined as the objective function and is  maximized using genetic algorithms subject to a list of constraints for obtaining the numerical values of the optimum operating parameters. These determined optimum operating parameters will serve as basis for improving the performance of the power plant and this is the significance of this study.    The effects of genetic algorithm options (such as initial population, elite children, and crossover ratio) on the optimization results are also established. It is observed that applying genetic algorithm in the thermodynamic optimization of a case study (Egbin power plant) boiler, the percentage increase in the thermal efficiency is 4.76% and 3.89% in comparison with the existing values for the studied boiler at Egbin thermal power plant for 2008 and 2009 respectively.

Keywords: Thermodynamics, Optimization, Genetic Algorithm, Steam Boiler, Power Plant.