{"title":"基于信号处理技术的配电系统故障检测与分类","authors":"Kumari Sarwagya, S. Ranjan","doi":"10.1109/ICCECE48148.2020.9223072","DOIUrl":null,"url":null,"abstract":"Signal processing techniques (i.e. Wavelet Transform & Stockwell Transform) are implemented for fault detection and classification in distribution system integrated with distributed generation. The validation of the proposed techniques are tested for a Line-Ground (LG), Line-Line-Ground (LLG), Line-Line (LL) and 3-phase faults on a 4- Bus test system using PSCAD/EMTDC software. Performance analysis of both the techniques are done in presence of disturbance or noise and it is found that WT based method gets affected in presence of noise whereas in ST there is no such problems which concludes that ST have the better ability to differentiate between noise and fault than WT.","PeriodicalId":129001,"journal":{"name":"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detection and Classification of Faults in Distribution System Using Signal Processing Techniques\",\"authors\":\"Kumari Sarwagya, S. Ranjan\",\"doi\":\"10.1109/ICCECE48148.2020.9223072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Signal processing techniques (i.e. Wavelet Transform & Stockwell Transform) are implemented for fault detection and classification in distribution system integrated with distributed generation. The validation of the proposed techniques are tested for a Line-Ground (LG), Line-Line-Ground (LLG), Line-Line (LL) and 3-phase faults on a 4- Bus test system using PSCAD/EMTDC software. Performance analysis of both the techniques are done in presence of disturbance or noise and it is found that WT based method gets affected in presence of noise whereas in ST there is no such problems which concludes that ST have the better ability to differentiate between noise and fault than WT.\",\"PeriodicalId\":129001,\"journal\":{\"name\":\"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCECE48148.2020.9223072\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE48148.2020.9223072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection and Classification of Faults in Distribution System Using Signal Processing Techniques
Signal processing techniques (i.e. Wavelet Transform & Stockwell Transform) are implemented for fault detection and classification in distribution system integrated with distributed generation. The validation of the proposed techniques are tested for a Line-Ground (LG), Line-Line-Ground (LLG), Line-Line (LL) and 3-phase faults on a 4- Bus test system using PSCAD/EMTDC software. Performance analysis of both the techniques are done in presence of disturbance or noise and it is found that WT based method gets affected in presence of noise whereas in ST there is no such problems which concludes that ST have the better ability to differentiate between noise and fault than WT.