水库群蓄水调度多目标随机规划与聚类分析

Multi-objective stochastic programming and clustering analysis for reservoirs refilling operation

梯级水库群汛后蓄水期蓄水时机、速率、次序决策面临径流不确定、多目标竞合关系复杂等问题。针对蓄水期决策难题,构建发电、蓄满、生态、上、下游防洪安全等指标的水库群多目标随机规划模型,生成非劣解集;采用K均值聚类法提取非劣解集类别特征,分析目标矛盾关系及蓄水机制。以溪洛渡-葛洲坝梯级水库群为例,结果表明:蓄水期来水越枯,蓄水难度越大,综合效益越低,枯水年发电量较丰水年下降了21.6%;上游防洪安全与发电量矛盾性最强,由枯到丰相关系数降低了0.047;溪洛渡、三峡蓄水呈分段式变化,前期快速蓄水,中后期缓速蓄水。本研究提出的耦合水库群多目标随机规划与聚类分析方法对于科学制定水库群蓄水方案具有参考价值。

For cascade reservoirs in the period after main flood process,decision-making on the timing,rate and sequence of their refilling is faced with problems such as runoff forecast uncertainty and complex multi-objective competition-cooperation relationships.To deal with such difficulties in the refilling decision-making,we develop a stochastic optimization operation model for the water refilling of cascade reservoirs with five objectives,power generation,refilling degree,ecology,and upstream and downstream flood risks.We generate a non-inferior solution set for the refiling,use the K-means clustering method to extract its features,and analyze the contradiction relationship between the objectives and the refilling mechanism.Application to a case study of the cascade reservoirs on the Yangtze River mainstream from Xiluodu to Gezhouba shows a drier water refilling period leads to a greater difficulty in the refilling and lower comprehensive benefits.For these reservoirs,the total power output in a dry year is 21.6%lower than that of a wet year;the strongest contradiction occurs between upstream flood control safety and power generation,with the correlation coefficient decreasing by 0.047 from a dry to wet year.The refilling in the Xiluodu and Three Gorges reservoirs varies in stages,rapid in the early stage and slow in the middle and later stages.The multi-objective stochastic programming and clustering analysis method developed in this study for reservoir refilling helps formulate better refilling schemes.