摘要
针对现有辨识方法在对电力系统运行不良数据辨识时,存在辨识速度慢、辨识精准度低的问题,引入BP神经网络,开展对辨识方法的设计研究。采集电力系统的运行数据,利用BP神经网络,提取不良数据特征。根据不良数据的特征,通过支持向量机分类算法完成对不良数据的辨识,并通过试验验证该方法的辨识速度和表示精准度。
In view of the problems of slow identification speed and low identification accuracy in identifying the poor operation data of the power system,BP neural network is introduced to carry out the design research of the identification method.Collect the operation data of the power system,and the BP neural network are used to extract the bad data features.According to the characteristics of the bad data,the bad data is identified by the SVM classification algorithm.Finally,the identification speed and representation accuracy of the proposed method are verified through experiments.
作者
王壮壮
张为兵
宫玉洁
WANG Zhuangzhuang;ZHANG Weibing;GONG Yujie
出处
《电力系统装备》
2023年第5期89-91,共3页
Electric Power System Equipment
关键词
BP神经网络
数据
不良
运行
电力系统
辨识
BP neural network
data
bad
operation
power system
identification
