摘要
为了提升电力系统故障诊断的精准性与效率,本文通过介绍基于数据挖掘模型的构建过程,深入分析了数据挖掘技术在识别电力系统复杂故障模式中的应用。具体而言,首先构建了一个适用于电力系统故障分析的数据挖掘模型,该模型能够有效整合历史数据与实时监测信息;随后,基于该模型提出了电力系统故障诊断的新方法,实现了故障的快速定位与原因解析。仿真实验结果表明,所提方法显著提高了故障诊断的准确性和时效性,为电力系统的安全稳定运行提供了有力支持。
In order to improve the accuracy and efficiency of power system fault diagnosis,this article introduces the construction process based on data mining models and deeply analyzes the application of data mining technology in identifying complex fault patterns in power systems.Specifically,a data mining model suitable for power system fault analysis was first constructed,which can effectively integrate historical data with real-time monitoring information;Subsequently,a new method for power system fault diagnosis was proposed based on this model,achieving rapid fault localization and cause analysis.The simulation experiment results show that the proposed method significantly improves the accuracy and timeliness of fault diagnosis,providing strong support for the safe and stable operation of the power system.
作者
苏潇毅
Su Xiaoyi(Fengxian Power Supply Branch of State Grid Shaanxi Electric Power Co.,Ltd.,Baoji,China)
出处
《科学技术创新》
2024年第24期217-220,共4页
Scientific and Technological Innovation
关键词
数据
挖掘
模型
电力系统
故障诊断
data
excavate
model
power system
fault diagnosis
