Exergoeconomic Based Optimization of a Gas Fired Steam Power Plant Using Genetic Algorithm

摘要

This research paper mainly deals with exergy, economic, and environmental investigation of a 250 MW steam power plant located in Iran. In order to model this power plant, energy balance equations are used and each part of the power plant is modeled accordingly. Further by introducing the boiler as the main source of irre-versibility, two approaches are presented to improve the boiler performance, reduction of excess air, and temperature reduction of gasses leaving the stacks. To study the effect of these two approaches, an objective function including the cost rate of exergy destruction of boiler, fuel cost, and cost rate of environmental impact is presented. The optimization process is done using a genetic algorithm. It is concluded that by optimizing, 20% reduction in the overall cost rate and 88% reduction in the cost rate of environmental impact can be achieved.