长江科学院院报 ›› 2012, Vol. 29 ›› Issue (3): 1-6.

• 水资源与环境 •    下一篇

基于改进遗传算法的生态友好型水库调度

陈  端 1,2,陈求稳 1,陈  进 2   

  1. 1.中国科学院 生态环境研究中心,北京  100085; 2. 长江科学院,武汉  430010
  • 收稿日期:2011-02-28 出版日期:2012-03-01 发布日期:2012-05-15
  • 通讯作者: 陈 端(1978-),男,四川大竹人,高级工程师,博士研究生,主要从事水工水力学及生态水力学研究

Reservoir Operation in an Eco-friendly Manner Based on Adaptive Genetic Algorithm

CHEN Duan 1,2 ,CHEN Qiu-wen 1 ,CHEN Jin 2   

  1. 1.Research Center for Eco-environmental Sciences, Chinese Academy of Sciences, Beijing 100085,China;2.Yangtze River Scientific Research Institute, Wuhan 430010, China
  • Received:2011-02-28 Online:2012-03-01 Published:2012-05-15

摘要: 以锦屏梯级水库为案例,从系统工程论的角度出发,将梯级水库作为物理系统,以年发电量为目标函数,建立了梯级水库调度优化模型。为减少水库调度对河道生态系统的影响,在鱼类栖息地模拟的研究基础上,引入目标物种的生态需水过程对调度模型进行动态约束,并采用改进的遗传算法进行求解。研究得到了满足目标鱼类生态需水条件下发电量最大的梯级水库调度策略,并对生态流量满足程度与工程效益损失之间的定量响应关系进行了研究,提出了折中方案选择的基本原则。

关键词: 生态友好调度, 改进遗传算法, 生态需水过程, 优化模型

Abstract: A model with annual power generation as objective function was established to optimize cascaded reservoir operation by using adaptive genetic algorithm. In addition to conventional constraints of water level and discharges etc, the model took ecological flow demand (EFD) into consideration. The model was applied to the operation of two cascade reservoirs on Yalong River in Southwest China. The optimal operation scheme was obtained through genetic algorithm, where a maximum total power generation could be achieved and all the constraints including EFD were satisfied. However, this solution would bring 8% hydropower loss compared with the optimal operation without EFD. In view of this, the quantitative response relation between hydropower loss and ecological flow demand were studied. The trade-off was found at the point when 70% EFD was guaranteed.

Key words: eco-friendly reservoir operation, adaptive genetic algorithm, ecological flow, optimization model

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