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采用梯级水电站动态弃水策略的多目标短期优化调度
Short Term Multi-objective Optimization Scheduling With Dynamic Water Spillage Strategy for Cascade Hydroelectric Plants

作  者: ; ; ;

机构地区: 广西大学电气工程学院

出  处: 《中国电机工程学报》 2011年第4期15-23,共9页

摘  要: 弃水是影响梯级水电站经济运行的一个重要因素,针对静态弃水策略的不足,在协调条件的基础上,建立了梯级水电站的动态弃水模型,以此为基础建立调度期内发电量最大、年调节或季调节水库末蓄水量最大、日调节水库末蓄水量偏差平方和最小、总耗水量最小及末级水电站弃水量最小的多目标短期优化调度模型。针对仿电磁学算法原理(electro-magnetism-like mechanism,ELM)简单及收敛迅速的特点,采用嵌入数据包络分析(data envelopment analysis,DEA)的混合仿电磁学算法对多目标优化调度模型进行求解,该算法避免了传统权重系数法的盲目性。对一个8级梯级水电站系统进行仿真分析,结果表明所提出的动态弃水策略可以有效地提高梯级水电站的发电效益,同时也验证了混合仿电磁学算法在求解多目标优化问题时的有效性。 One of the key factors of affecting hydroelectric plant economic operation is water spillage. A novel dynamic water spillage model was presented based on the coordination condition in view of the insufficiency of the static water spillage strategy. A novel multi-objective scheduling model for maximizing the total power generation in all schedule time, maximizing the final water storage for yearly or quarterly regulating reservoir, minimizing the sum of bias squares of final water storage for daily regulating reservoir, minimizing the total water consumption and minimizing the total water spillage of the last hydroelectric plant was proposed based on the dynamic water spillage strategy to realize the optimal trade-off between water volume for generation and power generation. A hybrid global optimization method which can overcome the shortcoming of weighted method was proposed for solving multi-objective optimization problem efficiently by embedding data envelopment analysis (DEA) into electro-magnetism-like mechanism (ELM). Simulations for a test system with eight hydroelectric plants were executed. Results show that the novel water spillage model can improve the synthesis generation benefits of cascade hydroelectric plants and the effectiveness of the novel hybrid method in determining the optimal solution for the multi-objective scheduling model.

关 键 词: 梯级水电站 多目标短期优化调度 动态弃水策略 数据包络分析 仿电磁学算法

领  域: [电气工程]

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