Peng Zhang, Q. Feng, Ran Chen, Dalong Wang, Lijia Ren
{"title":"配电网电能质量的分类与识别","authors":"Peng Zhang, Q. Feng, Ran Chen, Dalong Wang, Lijia Ren","doi":"10.1109/ICPRE51194.2020.9233147","DOIUrl":null,"url":null,"abstract":"There are a large number of power quality problems with large-capacity dedicated line users of the power grid. The monitoring data of power quality presents a large number of irregular characteristics. The signal samples obtained directly by measuring the signals contain a lot of complicated and useless information, and cannot be used for the type identification of special load power quality. Regarding this problem, this paper proposes a method for identifying the type of power quality disturbances with special loads based on S transform and support vector machine (SVM). Simulation and actual data experiments show that the method can accurately identify, and it is of great significance for grasping the features of power quality, as well as useful for the supervision, analysis and management of power quality.","PeriodicalId":394287,"journal":{"name":"2020 5th International Conference on Power and Renewable Energy (ICPRE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Classification and Identification of Power Quality in Distribution Network\",\"authors\":\"Peng Zhang, Q. Feng, Ran Chen, Dalong Wang, Lijia Ren\",\"doi\":\"10.1109/ICPRE51194.2020.9233147\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"There are a large number of power quality problems with large-capacity dedicated line users of the power grid. The monitoring data of power quality presents a large number of irregular characteristics. The signal samples obtained directly by measuring the signals contain a lot of complicated and useless information, and cannot be used for the type identification of special load power quality. Regarding this problem, this paper proposes a method for identifying the type of power quality disturbances with special loads based on S transform and support vector machine (SVM). Simulation and actual data experiments show that the method can accurately identify, and it is of great significance for grasping the features of power quality, as well as useful for the supervision, analysis and management of power quality.\",\"PeriodicalId\":394287,\"journal\":{\"name\":\"2020 5th International Conference on Power and Renewable Energy (ICPRE)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Power and Renewable Energy (ICPRE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPRE51194.2020.9233147\",\"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 5th International Conference on Power and Renewable Energy (ICPRE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPRE51194.2020.9233147","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification and Identification of Power Quality in Distribution Network
There are a large number of power quality problems with large-capacity dedicated line users of the power grid. The monitoring data of power quality presents a large number of irregular characteristics. The signal samples obtained directly by measuring the signals contain a lot of complicated and useless information, and cannot be used for the type identification of special load power quality. Regarding this problem, this paper proposes a method for identifying the type of power quality disturbances with special loads based on S transform and support vector machine (SVM). Simulation and actual data experiments show that the method can accurately identify, and it is of great significance for grasping the features of power quality, as well as useful for the supervision, analysis and management of power quality.