Parametric Optimization of Organic Rankine Cycle by Genetic Algorithm

Abstract

Organic Rankine Cycle (ORC) is widely used in the field of low temperature waste heat recovery, including solar, biomass and geothermal energy, among others. Based on the thermodynamic model of ORC system built up in Matlab, this study employ Genetic Algorithm (GA) on ORC system for parametric optimization and select a ratio of heat transfer area to total net power output as the performance evaluation criterion to predict the economy of system. R11, R113, R123 and isopentane are choosed as the working medium. The results show that the ORC system with isopentane has the minimum objective function value of 0.429m2/kw. The corresponding condensing temperature and degree of supercooling are generally located at lower boundary over their parametric design ranges, and the corresponding pinch point temperature difference are located at upper boundary. For different working fluids, there exist an optimum evaporating temperature and degree of superheat.