Comparative Study of Optimization Algorithms for The Optimal Reservoir Operation

Key Laboratory of River Regulation and Flood Control of MWR, Changjiang River Scientific Research Institute, Wuhan 430010, China
College of Hydropower & Information Engineering, Huazhong University of Science & Technology, Wuhan, 430074, China

^* Corresponding author: wishesliu@gmail.com
chen_lu@hust.edu.cn

Abstract

Apart from traditional optimization techniques, e.g. progressive optimality algorithm (POA), modern intelligence algorithms, like genetic algorithms, differential evolution have been widely used to solve optimization problems. This paper deals with comparative analysis of POA, GA and DE and their applications in a reservoir operation problem. The results show that both GA and DES are feasible to reservoir operation optimization, but they display different features. GA and DE have many parameters and are difficult in determination of these parameter values. For simple problems with mall number of decision variables, GA and DE are better than POA when adopting appropriate parameter values and constraint handling methods. But for complex problem with large number of variables, POA combined with simplex method are much superior to GA and DE in time-assuming and quality of optimal solutions. This study helps to select proper optimization algorithms and parameter values in reservoir operation.