金沙江下游梯级与三峡梯级多目标联合防洪优化调度研究  

Study on optimal scheduling of multi-objective joint flood control for lower Jinsha River cascade reservoirs and Three Gorges reservoir

作　　者：欧阳硕[1] 周建中[1] 张睿[1] 王学敏[1] 王浩[1,2] 

机构地区：[1]华中科技大学水电与数字化工程学院,武汉430074 [2]中国水利水电科学研究院水资源研究所,北京100038

出　　处：《水力发电学报》2013年第6期43-49,56,共8页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金重点项目(51239004);高等学校博士学科点专项科研基金(20100142110012)

摘　　要：针对金沙江下游梯级及三峡梯级水库群联合防洪调度这一大规模水库群多目标防洪调度问题,均衡考虑水库群大坝安全及上下游不同防护区防洪要求等多个目标,建立了梯级水库群多目标防洪优化调度模型,并提出了一种自适应多目标仿电磁学算法。该算法采用仿电磁学算法实现可行解集的进化,并根据水库群多目标防洪优化调度问题的特点构建了外部档案集,同时引入了基于个体聚集密度的外部档案集更新方法,保证了非劣调度方案的多样性;在此基础上,加入一种自适应的扰动因子对算法的局部随机搜索操作进行修正,改善了算法的全局寻优能力。工程实例验证以及不同情景的调度方案的对比分析结果表明,联合调度方案在保证三峡坝前水位不变的前提下,进一步减少水库群最大下泄流量,增强梯级水库群的防洪能力。This paper develops an optimization model of multi-objective flood control for cascaded reservoirs to solve scheduling problem of large-scale reservoirs on the middle and upper Yangtze River. This is a synthetic model considering the requirements by various factors such as dam safety, flood control over the upstream area and flood control over the downstream protected area. To solve the model, we formulate an adaptive algorithm of multi-objective electromagnetism-like mechanism （MOEM） for evolution of the feasible solution sets. This algorithm adopts an update method of external archive set to ensure the diversity of pareto optimal set based on individual crowding-density. It also uses an adaptive disturbance factor to correct the random local search operator for improvement of its global optimization ability. A case study of practical project was tested and scheduling calculations in different situations were compared. The results show that, at the same water stage in the Three Gorges reservoir, the joint scheme can reduce the maximum discharge volume from the reservoirs and their flood control capacity can be improved.

关 键 词：联合防洪 多目标 仿电磁学算法 梯级水库群 

分 类 号：TV697[水利工程—水利水电工程]