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水力发电学报 ›› 2024, Vol. 43 ›› Issue (5): 43-53.doi: 10.11660/slfdxb.20240505

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基于麻雀搜索算法的梯级泵站优化调度

  

  • 出版日期:2024-05-25 发布日期:2024-05-25

Optimal scheduling of cascade pumping stations based on sparrow search algorithm

  • Online:2024-05-25 Published:2024-05-25

摘要: 针对梯级泵站系统运行效率普遍偏低、能耗损失较大等问题,建立了梯级泵站优化调度模型,引入了寻优能力强、搜索精度高的麻雀搜索算法(SSA),对算法中安全阈值和侦察者占比两参数进行了比选;据此提出了基于SSA算法的梯级泵站优化调度方法,并将其应用于密云水库调蓄工程中的三级泵站优化调度研究。结果表明,三种不同流量工况下,相较于现状方案,PSO及GA算法所得优化方案其系统运行效率可提升0.03% ~ 0.18%,年运行成本可节省¥9,700 ~ ¥69,500。利用SSA算法所获优化方案在两项指标改进方面更为突出,可达到0.98% ~ 1.20%的效率提升及¥369,000 ~ ¥443,900的年运行费用的节省,验证了SSA算法在梯级泵站优化调度中的可行性和高效性,可为梯级泵站优化调度提供一种合理可靠的方法。

关键词: 梯级泵站, 优化调度, 麻雀搜索算法, 高效运行, 大系统分解协调模型

Abstract: Aimed at the problems of low operating efficiency and high energy consumption loss, an optimal scheduling model of cascade pumping stations is developed. This model adopts the sparrow search algorithm (SSA) of strong searching ability and high exploratory accuracy, and compares and selects its two parameters: safety threshold and scout ratio. Then, based on this algorithm, we formulate a new optimal scheduling method for cascade pumping stations, and apply it in the case study of a three-stage pumping station in the Miyun Reservoir regulation and storage project. The results show that under three different flow conditions, compared with the current scheme, the system efficiency of the optimized scheme obtained by the particle swarm optimization (PSO) and Pareto-archived (GA) algorithm are increased by 0.03% - 0.18%, and the annual operating cost is saved by ¥9,700 - ¥69,500. More prominent is the SSA optimized scheme in ameliorating the two indexes mentioned above, which can achieve an efficiency increase of 0.98% - 1.20% and an annual operating cost saving of ¥369,000 - ¥443,900. This verifies the feasibility and efficiency of SSA in the optimal scheduling of cascade pumping stations, along with its application to the scheduling as a reasonable and reliable method.

Key words: cascade pumping station, sparrow search algorithm, optimal scheduling, efficient operation, large system decomposition-coordination model

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