首页    期刊浏览 2024年07月03日 星期三
登录注册

文章基本信息

  • 标题:Study on the Feature Space Detection Method of DC Arc Fault for Photovoltaic system
  • 本地全文:下载
  • 作者:Liling Sun ; Han Wu ; Xiangdong Lu
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:256
  • 页码:1-5
  • DOI:10.1051/e3sconf/202125601015
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:An arc fault on the DC side of the photovoltaic system is a potential safety hazard and is difficult to detect due to the complexity of photovoltaic systems. The detection method of series arc fault in photovoltaic systems is investigated here. The DC arc fault test platform for a photovoltaic system is established to collect the current signal under normal and fault conditions. In this study, the time domain characteristics, frequency domain characteristics, and time-frequency domain characteristics are compared by analysing the current data from the photovoltaic system in before and after fault states: corresponding feature vectors are used to construct the arc fault feature space of the system, and according to the position of the current signal in the feature space the fault is detected, so as to realise effective arc fault feature information. Then the method of establishing the arc fault feature space is introduced and key parameters of the feature space are determined. Finally, the anti-interference ability of arc fault feature space detection is verified. The results showed that the detection method is both feasible and accurate.
国家哲学社会科学文献中心版权所有