Multi-objective optimization of a combined heat and power (CHP) system for heating purpose in a paper mill using evolutionary algorithm

摘要

The present study deals with a comprehensive thermodynamic modeling of a combined heat and power (CHP) system in a paper mill, which provides 50 MW of electric power and 100 ton h~(-1) saturated steam at 13 bars. This CHP plant is composed of air compressor, combustion chamber (CC), Air Preheater, Gas Turbine (GT) and a Heat Recovery Heat Exchanger. The design parameters of this cycle are compressor pressure ratio (r_(AC)), compressor isentropic efficiency (η_(AC)), GT isentropic efficiency (η_(GT), CC inlet temperature (T_3), and turbine inlet temperature (T_4). In the multi-objective optimization three objective functions, including CHP exergy efficiency, total cost rate of the system products, and CO_2 emission of the whole plant, are considered. The exergoenvironmental objective function is minimized whereas power plant exergy efficiency is maximized using a Genetic algorithm. To have a good insight into this study, a sensitivity analysis of the results to the interest rate as well as fuel cost is performed. The results show that at the lower exergetic efficiency, in which the weight of exergoenvironmental objective is higher, the sensitivity of the optimal solutions to the fuel cost is much higher than the location of the Pareto Frontier with the lower weight of exergoenvironmental objective. In addition, with increasing exergy efficiency, the purchase cost of equipment in the plant is increased as the cost rate of the plant increases.