Fault Diagnostic Method for Photovoltaic Grid Inverter Based on Online Extreme Learning Machine

摘要：

　　As the key equipment in photovoltaic system,the operating reliability of photovoltaic grid inverter influences on the security and stability of photovoltaic system deeply.To diagnose the fault of photovoltaic grid inverter effectively,the paper proposes an online extreme learning machine algorithm for fault diagnosis of photovoltaic grid inverter,which uses wavelet analysis method to analyze the output current signal of the inverter.Using extreme learning machine algorithm for online learning,the fault feature of different fault status can be obtained.The proposed algorithm is applied to fault diagnosis of the actual photovoltaic grid inverter,the experimental results demonstrate the effectiveness of the algorithm.

关键词： Wavelet analysis Online extreme learning machine Inverter Fault diagnosis

作者: Pu Yang Xiao Li Jiangfan Ni Jing Zhao

作者单位: College of Automation Engineering,Nanjing University of Aeronautics and Astronautics,Nanjing 210016,Jiangsu,China

会议类型: 国际会议

会议名称: The 2015 Chinese Intelligent Automation Conference(2015中国智能自动化会议)

会议地点: 福州

会议语种:英文

页码: 495-503

在线出版日期: 2015-05-08（万方平台首次上网日期，不代表论文的发表时间）