Multi-objective Ecological Operation of Reservoir in Luanhe River Based on Improved Particle Swarm Optimization

Abstract

River ecosystem is one of the most important ecosystems, and it provides many ecosystem services for human beings. However, river health has also been damaged by over-exploitation and water pollution. In the process of reservoir operation, the ecological flow demand of rivers should be fully considered and multi-objective ecological dispatch of reservoirs should be implemented. On basis of the traditional particle swarm optimization (PSO), the improved PSO with adaptive random inertia weights (ARIW) is proposed to deal with the problem of ecological optimal operation of the reservoir in the paper. According to the evolutionary process, based on the probability distribution density function of triangle, the inertia weight can be adjusted randomly and adaptively to meet the global or local optimization requirements. By typical mathematical function, the improved PSO algorithm is compared with traditional PSO and genetic algorithm (GA) and is proved to be more efficient and accurate. Taking Panjiakou Reservoir on the mainstream of Luanhe River in China as an example, the multi-objective ecological optimal dispatch of the reservoir has been analysed and calculated with the improved PSO algorithm under different targets years, considering flood control, water supply, and ecological demand. The research results can provide reference for developing rationally Luanhe River water resources, and making scientifically ecological dispatch plan of the Panjiakou reservoir.