Application of Hybrid Particle Swarm Optimization Algorithm in the Optimal Water Operation of Cascade Reservoirs in Dry Season

摘要：

　　In this paper,a hybrid particle swarm optimization(HPSO)algorithm is proposed to solve the problem of optimal water operation of cascade reservoirs in dry season.Based on the basic particle swarm optimization(PSO)algorithm,chaos algorithm is introduced to traverse the search space to generate the initial population and improve the global searching ability of the algorithm.A self-adaptive inertial weighting method based on optimized inertial weighting coefficient is adopted to improve the ability of particle individual search and avoid local optimum.The proposed algorithm is applied to the optimal water operation in dry season of cascade reservoirs on the mainstream of Xijiang River.The results show that the HPSO algorithm can effectively improve the guarantee degree of ecological flow and suppressing salinity flow in the control reach of Wuzhou station under different typical dry year scenarios.

作者: Sen Wang Fang Yang Zhipeng Ma Shanzong Li Yunyun Shi

作者单位: The Pearl River Hydraulic Research Institute,Guangzhou 510611,China;Key Laboratory of the Pearl Rive Technical Advisory Center of Pearl River Resources Commission,Ministry of Water Resources,Guangzhou

会议类型: 国际会议

会议名称: 2018 International Symposium on Water System Operations(ISWRSO 2018)(2018年水资源系统及调度国际研讨会)

会议地点: 北京

会议语种:英文

页码: 1-6

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）