考虑蓄水期弃水风险的水库长期发电调度方法

短期径流的大幅波动使得以平均径流为基础制定的水库长期调度方案面临较大弃水风险，是影响水库长期调度决策合理性的重要因素。本文考虑日尺度径流波动影响，提出一种蓄水期弃水风险量化方法，并建立了耦合弃水风险的水库长期发电调度模型。利用长系列日径流资料，结合风险最小蓄水规则，以不蓄弃水流量为指标量化蓄水期各月弃水风险；采用Copula函数构建月均入流与弃水风险的联合分布和条件概率分布，明晰了特定入流条件的风险置信区间；最后，将弃水风险以弃电损失函数融入优化模型，以获得更符合实际的长期调度方案。以澜沧江流域小湾水库为工程背景进行调度模拟分析，结果表明本文方法能够有效降低水库长期优化调度方案的弃水风险，有利于提高优化结果的可操作性，与传统方法相比，能够使多年平均弃水减少约4.76亿m³、发电量增加约1.15亿kW·h。

Long-term optimal operation of reservoir considering the water spillage risk during the impoundment period

The large volatility of short-term inflow makes the long-term operation of the reservoir face a greater risk of water spillage, which is an important factor that affects the rationality of the long-term operation of the reservoir. Considering the impact of daily inflow fluctuations, a quantitative evaluation method for the water spillage risk during the impoundment period is proposed, and a long-term optimal operation model for the reservoir considering the water spillage risk is established. Incorporating with the minimum risk rules, we take the non-storage spillage as the risk indicator and use historical daily inflow data to calculate the possible water spillage risk for each month of the impoundment period. The Copula model is used to construct the joint distribution and conditional probability distribution of the monthly average inflow and the water spillage risk, so as to obtain the risk confidence interval for the specific inflow condition. Finally, the water spillage risk is integrated into the long-term optimization model in the form of energy loss to obtain a more practical operation plan. The controlling reservoir Xiaowan in the Lancang River Basin is used as an example to simulate the operation. The results show that the method proposed in this paper can effectively reduce the water spillage risk in long-term operation of the reservoir and improve the operability of the optimization results. Compared with the conventional method, the proposed method can reduce the average annual spillage by about 476×10⁶ m³ and increase the power generation by about 115×10⁶ kW·h.