Optimization of fire tube heat recovery steam generators for cogeneration plants through genetic algorithm

Abstract

Abstract In the present paper, a small cogeneration system including a gas microturbine and a fire tube heat recovery steam generator (HRSG) is considered. The HRSG system is optimized considering two different objective functions. Sum of the exergy losses resulting from the gases leaving the stack and the exergy destruction due to the internal irreversibility is considered as the first objective function while the second objective function is considered to be the sum of annualized values of the capital cost and the cost of the energy loss. The cost of energy loss includes the cost of the loss by hot gases leaving the stack and the cost of the reduction in the power production in the microturbine as the result of the pressure drop in the HRSG. Finally multi-objective optimization method via genetic algorithm is employed to find the optimum values of the design parameters. A decision making process based on finding the closest point to the ideal point is used. Results of different optimum points on the Pareto front are compared and discussed. The results show that the thermodynamic optimization doesn’t lead to major improvement of the total cost of the HRSG although the thermoeconomic and multi-objective methods improve the total cost of the system due decrease in the cost of energy loss due to decrease in the pinch point.