摘要
为提升排涝泵站运行效率和机组可靠性,针对不同排涝需求和常见运行优化方法寻优速度慢、鲁棒性差的情况,提供一种基于改进麻雀算法的排涝泵站优化运行方法。综合考虑机组台数、叶片角度、时段时长等关键因素,以能耗最低和机组损耗最小为目标,构建排涝泵站多目标运行优化模型;引入自适应权重和量子扰动机制改进麻雀算法,对模型予以求解。文章以瓜洲排涝泵站为研究对象,设置不同抽水需求下不同时段长的试验情景,验证模型有效性。结果表明:所构建方法能实现不同情景下排涝泵站运行优化,为排涝泵站智能化运行提供了新思路。
To enhance the operational efficiency and unit reliability of drainage pumping stations,this paper proposes an optimized operation method based on an improved Sparrow Search Algorithm(SSA),addressing the challenges of slow convergence and poor robustness in conventional optimization approaches under varying drainage demands.Key factors such as the number of operating units,blade angle,and time duration are considered,and a multi-objective optimization model is established with the goals of minimizing energy consumption and equipment wear.The SSA is improved by incorporating adaptive weights and a quantum disturbance mechanism to solve the model effectively.Using the Guazhou Drainage Pumping Station as a case study,multiple experimental scenarios with varying water extraction demands and time durations are designed to validate the model.Results demonstrate that the proposed method can effectively optimize the station’s operation under different conditions,offering a novel approach for intelligent management of drainage pumping stations.
作者
鲁鹏
LU Peng(Liaoning Northwest Water Supply Co.,Ltd.,Shenyang 110400,China)
出处
《中国水能及电气化》
2025年第12期37-46,共10页
China Water Power & Electrification
关键词
排涝泵站
优化运行
麻雀算法
自适应权重
量子扰动
drainage pumping station
operation optimization
Sparrow Search Algorithm
adaptive weight
quantum disturbance
