Multi-objective reservoir operation using particle swarm optimization with adaptive random inertia weights

作     者：Hai-tao Chen Wen-chuan Wang Xiao-nan Chen Lin Qiu Hai-tao Chen;Wen-chuan Wang;Xiao-nan Chen;Lin Qiu

作者机构：School of Water ResourcesNorth China University of Water Resources and Electric PowerZhengzhou 450046China Construction and Administration Bureau of South-to-North Water Diversion Middle Route ProjectBeijing 100038China 

出 版 物：《水科学与水工程：英文版》 (Water Science and Engineering)

年 卷 期：2020年第13卷第2期

页      面：136-144页

核心收录：

学科分类：081504[工学-水利水电工程] 08[工学] 081104[工学-模式识别与智能系统] 0707[理学-海洋科学] 0815[工学-水利工程] 0813[工学-建筑学] 0824[工学-船舶与海洋工程] 0814[工学-土木工程] 0811[工学-控制科学与工程] 

基　　金：supported by the Foundation of the Scientific and Technological Innovation Team of Colleges and Universities in Henan Province(Grant No.181RTSTHN009) the Foundation of the Key Laboratory of Water Environment Simulation and Treatment in Henan Province(Grant No.2017016). 

主　　题：Particle swarm optimization Genetic algorithm Random inertia weight Multi-objective reservoir operation Reservoir group Panjiakou Reservoir 

摘      要：Based on conventional particle swarm optimization(PSO),this paper presents an efficient and reliable heuristic approach using PSO with an adaptive random inertia weight(ARIW)strategy,referred to as the ARIW-PSO algorithm,to build a multi-objective optimization model for reservoir operation.Using the triangular probability density function,the inertia weight is randomly generated,and the probability density function is automatically adjusted to make the inertia weight generally greater in the initial stage of evolution,which is suitable for global searches.In the evolution process,the inertia weight gradually decreases,which is beneficial to local searches.The performance of the ARIWPSO algorithm was investigated with some classical test functions,and the results were compared with those of the genetic algorithm(GA),the conventional PSO,and other improved PSO methods.Then,the ARIW-PSO algorithm was applied to multi-objective optimal dispatch of the Panjiakou Reservoir and multi-objective flood control operation of a reservoir group on the Luanhe River in China,including the Panjiakou Reservoir,Daheiting Reservoir,and Taolinkou Reservoir.The validity of the multi-objective optimization model for multi-reservoir systems based on the ARIW-PSO algorithm was verified.