Aiming at the problems of high relative error of line trip fault identification results and redundant judgment process of line trip fault,a multi-information source line trip fault identification method based on big data is proposed.According to the working characteristics of transmission line,a transmission line model is established,the current information is collected,and the multi-information source fusion mechanism is established.Using big data technology,we analyze chaotic variables in trans-mission lines,identify abnormal data in characteristic data and control redundant variables.The abnormal line data from multi-ple information sources are summarized,and the fuzzy clustering classifier is used to complete the tripping fault identification.The simulation results show that compared with the normal state,the line current amplitude is greatly reduced,and the average relative errors of trip fault identification are reduced by 13％and 22％,respectively.
关键词
大数据/多信息源/线路故障/跳闸/故障识别
Key words
big data/multi-information source/line fault/tripping operation/fault identification
维普
万方数据