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

• DOI: 10.1016/j.wse.2020.06.005
• Publication Date: 2020-06-26T20:07:28Z
• Authors: Hai-tao Chen; Wen-chuan Wang; Xiao-nan Chen; Lin Qiu
• Keywords: River, lake, and water-supply engineering (General); TC401-506; Multi-objective reservoir operation; Genetic algorithm; Reservoir group; Particle swarm optimization; Panjiakou Reservoir; 0208 environmental biotechnology; 02 engineering and technology; Random inertia weight

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