A Novel Optimization Method for Multi-Reservoir Operation Policy Derivation in Complex Inter-Basin Water Transfer System

被引:0
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作者
Wenhua Wan
Xuning Guo
Xiaohui Lei
Yunzhong Jiang
Hao Wang
机构
[1] Tsinghua University,State Key Laboratory of Hydro
[2] General Institute of Water Resources and Hydropower Planning and Design,science and Engineering
[3] MWR,State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin
[4] China Institute of Hydropower and Water Resources,undefined
来源
关键词
Complex inter-basin water transfer system; High-dimensional optimization problem; Operation policy; Shape constraints; PRA-PSO;
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学科分类号
摘要
Joint operation of multiple reservoir system in inter-basin water transfer-supply project is a complex problem because of the complicated structure and cooperated operation policy. The combination of high-dimensional, multi-peak and multiple constraints makes it incredibly difficult to obtain the optimal rule curves for multi-reservoir operation. In view of this, we constructed a joint optimization operation model, considering both water supply and transfer, and proposed the concept of “shape constraints”. To obtain the solution of this high-dimensional optimization model, a novel progressive optimum seeking method, namely Progressive Reservoir Algorithm-Particle Swarm Optimization (PRA-PSO), is presented based on the nature of progressive optimization algorithm (POA) and standard particle swarm optimization (PSO). The water transfer project in northeast China, consisting of three routes eight reservoirs, is selected as a case study. The results show that (1) PRA-PSO is yielding much more promising results when compared with other optimization techniques; (2) shape constraints would narrow the scope of feasible solution area but increase the convergence of algorithm; (3) because of the strong interaction between water transfer and water supply action, the progressive setting of PRA-PSO should be in accordance with the order of reservoir water transfer. The case study indicates the novel optimization method could effectively increase the chance of jumping out of local optimal points, thereby searching for better solutions.
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页码:31 / 51
页数:20
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