摘要
针对传统流域梯级电站控制方法在发电效率与水资源利用方面存在的不足,提出基于云计算与分布式大数据架构的流域梯级电站集中控制方法。首先,分析流域梯级电站特性,形成水力-电力耦合模型,作为协同控制机制的输入;基于云计算与分布式大数据架构,设计云-边-端协同架构,实现数据高效处理与实时控制;采用改进NSGA-II算法,构建包含防洪、发电、生态三维度目标的优化模型,生成调度计划,对流域梯级电站进行集中控制,实现多目标优化调度与实时响应。试验结果表明:该方法应用后,流域梯级电站在各时段的发电量均达到了1200万kW·h以上,显著高于传统控制方法,且在不同的生态流量需求场景下,其平均发电耗水率降低幅度达到了50%以上,集中控制效果优势显著。
To address the limitations of traditional control methods in terms of power generation efficiency and water resource utilization for cascade hydropower stations in river basins,this paper proposes a centralized control approach based on cloud computing and distributed big data architecture.First,the characteristics of cascade hydropower stations are analyzed to establish a hydro-power coupling model,which serves as the input for a collaborative control mechanism.A cloud-edge-terminal coordinated framework is then designed using cloud computing and distributed data processing technologies to achieve efficient data handling and real-time control.An improved NSGA-II algorithm is employed to construct a multi-objective optimization model encompassing flood control,power generation,and ecological targets,generating dispatch plans and enabling centralized control of the cascade system for multi-objective optimization and real-time responsiveness.Experimental results show that,with the application of this method,the power generation of the cascade hydropower stations exceeded 12 million kW·h in all time periods,significantly outperforming traditional control methods.Moreover,under various ecological flow demand scenarios,the average water consumption rate for power generation was reduced by over 50%,demonstrating the significant advantages of the proposed centralized control strategy.
作者
邹毅
ZOU Yi(Gansu Electric Power Investment Hexi Hydropower Development Co.,Ltd.,Zhangye 734000,China)
出处
《中国水能及电气化》
2025年第9期5-9,共5页
China Water Power & Electrification
关键词
云计算
分布式大数据架构
流域
梯级电站
集中控制
cloud computing
distributed big data architecture
river basin
cascade hydropower stations
centralized control
