基于数据挖掘和主成分分析的电力设备状态评价

Condition Evaluation of Power Equipment Based on Data Mining and Principal Component Analysis

电力设备运行的健康状态直接影响着电力系统的安全稳定。基于数据挖掘技术,利用主成分分析方法对反映电力设备状态的海量数据进行了深入分析,形成了融合电力设备状态关键参量信息的主成分体系。基于该主成分体系,建立了电力设备运行状态的综合评价模型,实现了电力设备健康状态的动态评估和异常状态的快速检出。文中以变压器绝缘状态评估为例,证明了文中提出的方法可以弥补传统的状态评估方法的不足,具有一定的可靠性和实用性。

Based on data mining technology, this article uses principle component analysis algorithm to make in-depth analysis of huge amount of data related to power equipment condition. Hence, a principle component system with information fusion of key parameters of power equipment condition is formed. A comprehensive evaluation model of power equipment operation condition is built on the basis of the system, and it can make dynamic health assessment and rapid detection of abnormal state of power equipment. Transformer insulation condition is taken as an example. Results show that the proposed method can make up for the defects of traditional state evaluation methods, so it has certain reliability and practicability.