摘要
随着现代电力系统复杂性的增加,准确、有效地监控和预测用户负荷响应,实现电力系统的稳定运行,已成为亟待解决的问题。为此,提出一种三级阶梯预警模型。基于负荷曲线数据对变电站下属用户进行聚类,并结合负荷构成数据进行修正优化,形成“变电站—配电变电站—终端用户”三级阶梯预警机制。通过提取负荷特征、构建预警模板,实现异常负荷的自动识别与分级预警。实例分析表明,所提出的模型能有效识别工业与居民用户的异常负荷,预警准确率达89.6%,显著提升了电力系统运维的实时性与可靠性。
With the increasing complexity of modern power systems,accurately and effectively monitoring and predicting user load response has become a critical issue for realizing the stable operation of power systems.For this purpose,this paper proposes a three-stage early warning model.The users under substations are clustered based on load curve data,and the clustering is revised and optimized using load composition data,forming a three-stage early warning mechanism of substation,distribution substation and end users.By extracting load features and constructing early warning templates,automatic identification and hierarchical early warning of abnormal loads are achieved.Case analysis shows that the proposed model can effectively identify abnormal loads of industrial and residential users,with a early warning accuracy of 89.6%,which significantly improves the timeliness and reliability of power system operation and maintenance.
作者
孔德诗
贺辉
李博
KONG Deshi;HE Hui;LI Bo(Marketing Service Center of State Grid Sichuan Electric Power Company,Chengdu 610000,China)
出处
《微型电脑应用》
2025年第12期114-117,共4页
Microcomputer Applications
基金
国网四川省电力公司科技项目资助(51199923000A)。
关键词
电力系统
用户负荷响应
三级阶梯预警
性能测试
power system
user load response
three-stage early warning
performance test
