摘要
运用机器学习算法,结合实际运行数据,构建了一个能够精确识别和预测电力系统运行风险的模型。同时,科学地划分风险等级,并设定相应的阈值,以便在实际运行中快速、准确地进行风险预警。从多个层面验证和分析模型的性能,结果表明所构建的风险预警模型在电力调度的实际应用中展现出较高的可靠性和精确性。
In this paper,a model which can accurately identify and predict the operation risk of power system is constructed by using machine learning algorithm and combining with actual operation data.At the same time,scientifically divide the risk level and set the corresponding threshold,so as to carry out risk early warning quickly and accurately in actual operation.The performance of the model is verified and analyzed from many aspects,and the results show that the risk early warning model has high reliability and accuracy in the practical application of power dispatching.
作者
刘生红
LIU Shenghong(State Grid Gansu Power Company Pingliang Power Supply Company,Pingliang 744000,China)
出处
《通信电源技术》
2023年第22期100-102,共3页
Telecom Power Technology
关键词
电力调度
安全风险
风险预警
electric power dispatching
security risk
risk early warning
作者简介
刘生红(1975-),女,甘肃平凉人,本科,高级工程师,主要从事电网调度运行管理工作。
