Zongshuai Jin, Hengxu Zhang, Fang Shi, Weisheng Liu, Yuanlong Liu
{"title":"基于鲁棒回归平滑的自适应次/超同步分量检测方法","authors":"Zongshuai Jin, Hengxu Zhang, Fang Shi, Weisheng Liu, Yuanlong Liu","doi":"10.1109/POWERCON.2018.8601600","DOIUrl":null,"url":null,"abstract":"The increasing penetrations of converter-based renewable energy resources and nonlinear loads make it urgent to develop a detection method to adaptively monitor the sub/super-synchronous components to further detect the potential risk of the co-existence and cooperation of hundreds or thousands of converters. This paper proposes an enhanced adaptive sub/super-synchronous components detection method based on robust regression smoothing filtering (RRSF). According to simulation tests, the proposed method can detect the time-varying sub/super-synchronous components in the noisy signals with SNR of 0 dB and is robust to the colored property of background noise.","PeriodicalId":260947,"journal":{"name":"2018 International Conference on Power System Technology (POWERCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive Sub/Super-synchronous Components Detection Method Based on Robust Regression Smoothing\",\"authors\":\"Zongshuai Jin, Hengxu Zhang, Fang Shi, Weisheng Liu, Yuanlong Liu\",\"doi\":\"10.1109/POWERCON.2018.8601600\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The increasing penetrations of converter-based renewable energy resources and nonlinear loads make it urgent to develop a detection method to adaptively monitor the sub/super-synchronous components to further detect the potential risk of the co-existence and cooperation of hundreds or thousands of converters. This paper proposes an enhanced adaptive sub/super-synchronous components detection method based on robust regression smoothing filtering (RRSF). According to simulation tests, the proposed method can detect the time-varying sub/super-synchronous components in the noisy signals with SNR of 0 dB and is robust to the colored property of background noise.\",\"PeriodicalId\":260947,\"journal\":{\"name\":\"2018 International Conference on Power System Technology (POWERCON)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Power System Technology (POWERCON)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/POWERCON.2018.8601600\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Power System Technology (POWERCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/POWERCON.2018.8601600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive Sub/Super-synchronous Components Detection Method Based on Robust Regression Smoothing
The increasing penetrations of converter-based renewable energy resources and nonlinear loads make it urgent to develop a detection method to adaptively monitor the sub/super-synchronous components to further detect the potential risk of the co-existence and cooperation of hundreds or thousands of converters. This paper proposes an enhanced adaptive sub/super-synchronous components detection method based on robust regression smoothing filtering (RRSF). According to simulation tests, the proposed method can detect the time-varying sub/super-synchronous components in the noisy signals with SNR of 0 dB and is robust to the colored property of background noise.