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水力发电学报 ›› 2025, Vol. 44 ›› Issue (9): 15-26.doi: 10.11660/slfdxb.20250902

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考虑动库容影响的水库发电优化调度研究

  

  • 出版日期:2025-09-25 发布日期:2025-09-25

Study on optimal scheduling of reservoir power generation considering dynamic capacity impact

  • Online:2025-09-25 Published:2025-09-25

摘要: 针对河道型水库动库容变化及库区干支流非恒定流传播对发电调度的影响,本文构建了一种耦合一维河网非恒定流模型的水库发电优化调度模型。该模型采用基于OpenMP的并行动态规划算法进行求解,并应用于三峡水库发电调度实例研究。结果表明:所建模型能有效模拟三峡库区干支流河道沿程流量和水位变化过程;与静库容模型相比,动库容模型在消落期、汛期和蓄水期的发电量变化呈明显差异——消落期和汛期变化过程更平稳,而蓄水期波动幅度增大,三个时期总发电量分别减少2.06亿kW·h、1.29亿kW·h和0.47亿kW·h,其中动库容对消落期总发电量影响最大;在消落期和蓄水期调度初期,动库容模型通过增大出库流量来提高发电量。研究结果可为河道型水库发电调度精细化模拟提供参考。

关键词: 发电优化调度, 河道型水库, 动库容, 一维河网非恒定流, 并行动态规划

Abstract: For a river-type reservoir, a reasonable hydropower generation scheduling should consider the effects of its dynamic reservoir capacity and unsteady flow propagation in the mainstream and tributaries within a certain area. Aimed at such an issue, this paper constructs a reservoir optimal power generation scheduling model coupled with a one-dimensional river network unsteady flow model, which is solved using an OpenMP-based parallel dynamic programming algorithm and applied to a case study of the Three Gorges Reservoir (TGR). The results show this dynamic capacity model is effective in simulations of the spatial-temporal variations of discharges and water levels along the mainstream and tributaries within the TGR area. Compared with the static capacity model, it shows distinct differences in power generation process across operational periods—more stable variations in drawdown period and flood period, while experiencing significantly more fluctuations during impoundment period. Specifically, in these three periods, the total power generation decreases by 206 million kW·h, 129 million kW·h, and 47 million kW·h, respectively, with the most significant impact observed during drawdown period. And, during the initial stages of drawdown and impoundment, the model enhances power generation due to an increase in outflow discharges. This study would help refined simulations of the hydropower generation scheduling for river-type reservoirs.

Key words: power generation optimization, river-type reservoirs, dynamic capacity, one-dimensional unsteady flow in river networks, parallel dynamic programming

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