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首页> 外文期刊>Journal of Hydroinformatics >Single-reservoir operating rules for a year using multiobjective genetic algorithm
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Single-reservoir operating rules for a year using multiobjective genetic algorithm

机译：使用多目标遗传算法的一年单水库调度规则

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A monthly operating rule for single-reservoir operation is developed in this study. Synthetic inflow data over 100 years are generated by using a time series model, AR(1), and piecewise-linear operating rules consisting of 4 and 5 linear lines are found using the implicit stochastic optimization method. In order to consider multiobjective functions in reservoir system operation, a multiobjective genetic algorithm (NSGA-II) is adopted to obtain the optimization results. The search space of NSGA-II is carefully refined using frequency analysis of historical data, and the relationship between inflow and constraints is also investigated. It is determined that 4 and 5 segments are the optimal number of segments for the piecewise-linear operating rule, and the effect of random number seeding on NSGA-ll is evaluated. Six years of historical inflow data are used for the simulation model and the results show that the developed operating rule would handle various inflow series. As a result, probabilistic reservoir storage forecasts can be provided to a system operator so as to enable the operator to evaluate the current status of a reservoir quantitatively.
机译：本研究制定了单水库作业的每月作业规则。通过使用时间序列模型AR（1）生成100年的合成流入数据，并使用隐式随机优化方法找到由4条和5条线性线组成的分段线性操作规则。为了考虑水库系统运行中的多目标函数，采用多目标遗传算法（NSGA-II）获得优化结果。通过对历史数据进行频率分析，仔细地细化了NSGA-II的搜索空间，并研究了流入量与约束条件之间的关系。确定4和5个片段是分段线性操作规则的最佳片段数，并且评估随机数播种对NSGA-11的影响。仿真模型使用了六年的历史流入数据，结果表明所开发的操作规则可以处理各种流入序列。结果，可以将概率储层存储预测提供给系统操作员，以便使操作员能够定量地评估储层的当前状态。

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