耦合集合预报信息的水库高效调度方法研究

预报不确定性是水库调度领域亟待解决的关键难题。集合预报能有效的刻画预报不确定性，但将其直接耦合在水库多目标优化调度模型中会极大地增加计算负担。为此，本文提出了一种耦合集合预报信息的水库高效调度方法。首先，采用同步回代缩减算法将集合预报样本缩减为几种典型场景及对应的发生概率；然后，基于典型预报场景构建水库多目标优化调度模型，使得水库在多场景下性能指标的期望值最优；最后，采用“参数-模拟-优化”框架优化调度规则参数。以引汉济渭跨流域调水工程为例，研究结果表明：基于本文提出的方法制订的调度规则能有效应对预报的不确定性，各性能指标较优且计算负担较小。

An efficient method for deriving reservoir operating rules by coupling ensemble forecasting information

Forecast uncertainty is a key issue for reservoir operation. Ensemble forecasting can effectively depict forecast uncertainties, but it may increase the computational burden when directly incorporated into a multi-objective reservoir operation model. This paper presents an effective method for deriving multi-objective operating rules by incorporating ensemble forecasting. First, ensemble forecasting samples are reduced to several typical scenarios and their corresponding occurrence probabilities by using a simultaneous backward reduction method. Then, based on the typical scenarios, a multi-objective operation optimization model is constructed to optimize the expected values of reservoir performance indexes. Finally, a parameterization-simulation-optimization framework is adopted to derive multi-objective reservoir operating rules. The Han to Wei interbasin water transfer project in northwest China was selected for a case study. Results show that the proposed method yields effective reservoir operating rules with low computational burden.