水力发电学报2011，Vol.30Issue(6)：171-177,7.
基于加速遗传算法的梯级水电站联合优化调度研究
Study on combined optimal operation of cascade hydropower stations based on accelerating genetic algorithm
摘要
Abstract
Combined optimal operation of cascade hydropower stations is an optimized decision-making problem of large complicated system,and it involves various disciplines and agencies.Study of this issue is of great significance to regional water-use planning and sustainable development of regional economy.When a swarm intelligent optimization algorithm is applied to this problem,a large system of complex constraint conditions and curse of dimensionality often cause practical difficulties in their treatments.In this study,an accelerating genetic algorithm（AGA） was adopted to solve the problem.By principle of classification and hypothesis,a feasible decision space with a reverse time was constructed for the optimization variables of different stations,and then initial population individuals could be generated.This paper focuses on a discussion of the approaches for implementing and realizing this constraint system by AGA.Application to Wujiang cascade hydropower stations of typical hydraulic and power features shows that AGA has a strong adaptability and global searching ability of the constraint system.In comparison with the design case,the average annual yield of the stations is increased by 2.60%.Thus use of the swarm intelligent optimization algorithm to optimal operation problem by the principle above is feasible and reasonable,and this work provides a tool of scientific and effective decision for centralized dispatching operation of cascade hydropower stations.关键词
梯级水电站/优化调度/加速遗传算法Key words
cascade hydropower stations/optimal operation/accelerating genetic algorithm分类
建筑与水利引用本文复制引用
吴成国,王义民,黄强,金菊良,张永永..基于加速遗传算法的梯级水电站联合优化调度研究[J].水力发电学报,2011,30(6):171-177,7.基金项目
国家重点基础研究发展计划 （）
国家公益性行业科研专项 （）
陕西省教育厅科学研究计划 （）
国家自然科学基金项目 （）
