摘要
配电网停电故障是影响电力供应可靠性的主要因素之一,为了提高故障研判的准确性和效率,文章提出了一种基于多元异构模型数据融合的配电网停电故障研判方法。该方法将不同类型的数据和模型进行整合,通过数据清洗、特征提取、数据对齐和模型融合等技术,得到更全面、更准确的故障研判结果。文章采用了支持向量机、朴素贝叶斯、决策树等模型,并结合现场实际情况,对配电网停电故障进行研判。实验结果表明,此方法可以有效地提高故障研判的准确性和效率。
Distribution network outage fault is one of the main factors affecting the reliability of power supply.In order to improve the accuracy and efficiency of fault diagnosis,this paper proposes a distribution network outage fault diagnosis method based on data fusion of multiple heterogeneous models.This method integrates different types of data and models,and obtains more comprehensive and accurate fault diagnosis results through data cleaning,feature extraction,data alignment and model fusion.Specifically,this paper adopts support vector machine,naive Bayes,decision tree and other models,combined with the actual situation of the field,to study and judge the distribution network outage fault.Experimental results show that the proposed method can effectively improve the accuracy and efficiency of fault diagnosis.
作者
叶宁
江慧
Ye Ning;Jiang Hui(Guodian Nanjing Automation Co.,Ltd.,Nanjing 211100,China)
出处
《无线互联科技》
2023年第18期105-108,132,共5页
Wireless Internet Technology
关键词
多元异构模型
数据融合
停电研判
multivariate heterogeneous model
data fusion
power failure research and judgment
