Forecasted inflow is one of the most important input information for reservoir operation planning. However, current inflow prediction accuracy is difficult to meet the needs of long-term operation. Therefore, it is of great significance to consider the uncertainty of inflow forecast and study its influence on reservoir operation decisions. In this paper, a long-term scheduling framework considering inflow forecast uncertainty based on a temporal disaggregation method is proposed. First, the uncertainty of forecast is described from two aspects. Gaussian distribution is used to simulate the annual forecast error, and an Adaptive Nearest Neighbor Gaussian sampling method (A-NGS) is proposed to decompose annual inflow into temporal series. Based on the implicit scheduling model, the sample set of generation scheduling plans, actual dispatching schemes and theoretical optimal results are constructed. On this basis, a series of indexes are presented to evaluate the inflow simulation performance and the scheduling benefits. A case study of the Xiluodu-Xiangjiaba cascade reservoirs is conducted to analyze the effects of forecast uncertainty on operation benefits, and the effectiveness of forecast information is identified. Compared with the deterministic fragment method, the inflow processes simulated by A-NGS achieve better precision and behave more conducive to the scheduling. Although the uncertainty of forecast errors will bring some hydropower generation losses, a certain degree of forecast accuracy is effective to improve scheduling benefits when in the electricity market.

预测的流入量是水库调度中最重要的输入信息之一。但是，当前的流入预测精度难以满足长期运行的需求。因此，考虑入流预报的不确定性，研究其对水库调度决策的影响具有重要意义。本文提出了一种基于时间分解方法的考虑入水预报不确定性的长期调度框架。首先，从两个方面描述了预测的不确定性。利用高斯分布来模拟年均预报误差，并提出了一种自适应最近邻高斯抽样方法（A-NGS）将年入流量分解为时间序列。基于隐式调度模型，生成调度计划的样本集，建立了实际的调度方案和理论上的最优结果。在此基础上，提出了一系列指标来评估入流模拟性能和调度效益。以溪洛渡—香家坝梯级水库为例，分析了预测不确定性对运行效益的影响，确定了预测信息的有效性。与确定性分段方法相比，A-NGS模拟的流入过程具有更高的精度，并且行为更有利于调度。尽管预测误差的不确定性会带来一些水力发电损失，但一定程度的预测准确性可有效提高电力市场中的调度效益。提出了一系列指标来评估流入模拟性能和调度效益。以溪洛渡—香家坝梯级水库为例，分析了预测不确定性对运行效益的影响，确定了预测信息的有效性。与确定性分段方法相比，A-NGS模拟的流入过程具有更高的精度，并且行为更有利于调度。尽管预测误差的不确定性会带来一些水力发电损失，但一定程度的预测准确性可有效提高电力市场中的调度效益。提出了一系列指标来评估流入模拟性能和调度效益。以溪洛渡—香家坝梯级水库为例，分析了预测不确定性对运行效益的影响，确定了预测信息的有效性。与确定性分段方法相比，A-NGS模拟的流入过程具有更高的精度，并且行为更有利于调度。尽管预测误差的不确定性会带来一些水力发电损失，但一定程度的预测准确性可有效提高电力市场中的调度效益。以溪洛渡—香家坝梯级水库为例，分析了预测不确定性对运行效益的影响，确定了预测信息的有效性。与确定性分段方法相比，A-NGS模拟的流入过程具有更高的精度，并且行为更有利于调度。尽管预测误差的不确定性会带来一些水力发电损失，但一定程度的预测准确性可有效提高电力市场中的调度效益。以溪洛渡—香家坝梯级水库为例，分析了预测不确定性对运行效益的影响，确定了预测信息的有效性。与确定性分段方法相比，A-NGS模拟的流入过程具有更高的精度，并且行为更有利于调度。尽管预测误差的不确定性会带来一些水力发电损失，但一定程度的预测准确性可有效提高电力市场中的调度效益。