Operating rules for multireservoir systems
Operating rules for multireservoir systems
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DOI：
10.1029/96wr03745
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发表时间：
1997-04
影响因子：
5.4
通讯作者：
R. P. Oliveira;D. Loucks
中科院分区：
文献类型：
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作者：
R. P. Oliveira;D. Loucks
多水库运行策略通常由规则定义，这些规则根据一年中的时间和所有水库的现有总库存量指定单个水库的期望（目标）库存量或期望（目标）释放量。本文的重点是使用遗传搜索算法来推导这些多水库的操作策略。遗传算法使用实值向量，其中包含定义系统释放量和单个水库储存量目标所需的信息，作为每年多个时间段内总储存量的函数。在算法中使用精英主义、算法交叉、突变和“整体”替换来生成连续的可能操作策略集。然后使用模拟对每个策略进行评估，以计算给定流序列的性能指数。然后使用性能较好的策略作为生成新可能策略集的基础。重复改进的策略生成和评估过程，直到性能没有进一步改善为止。将该算法应用于供水和水电水库系统实例。
Multireservoir operating policies are usually defined by rules that specify either individual reservoir desired (target) storage volumes or desired (target) releases based on the time of year and the existing total storage volume in all reservoirs. This paper focuses on the use of genetic search algorithms to derive these multireservoir operating policies. The genetic algorithms use real‐valued vectors containing information needed to define both system release and individual reservoir storage volume targets as functions of total storage in each of multiple within‐year periods. Elitism, arithmetic crossover, mutation, and “en bloc” replacement are used in the algorithms to generate successive sets of possible operating policies. Each policy is then evaluated using simulation to compute a performance index for a given flow series. The better performing policies are then used as a basis for generating new sets of possible policies. The process of improved policy generation and evaluation is repeated until no further improvement in performance is obtained. The proposed algorithm is applied to example reservoir systems used for water supply and hydropower.