{"title":"频率估计算法的小信号近似","authors":"J. Wold, F. Wilches-Bernal","doi":"10.1109/td43745.2022.9817012","DOIUrl":null,"url":null,"abstract":"Estimates of power system frequency are beginning to be used in critical, real-time applications such as synthetic inertia. The behavior of the algorithms used to estimate frequency from point-on-wave signals can be complicated, and algorithm tuning difficult for non-experts. In this paper, small-signal approximations for four common frequency estimation algorithms are presented. These approximations are demonstrated to be both theoretically and empirically sound. They are valuable for three primary reasons: 1) they reduce the level of technical expertise required for effective tuning; 2) they effectively capture the dynamics of the algorithm so can be used as a proxy for the algorithm itself in the analysis of feedback control loops that employ frequency feedback; and 3) they can easily be implemented in transient stability simulation software in order to represent realistic frequency estimation.","PeriodicalId":241987,"journal":{"name":"2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Small-signal Approximations of Frequency Estimation Algorithms\",\"authors\":\"J. Wold, F. Wilches-Bernal\",\"doi\":\"10.1109/td43745.2022.9817012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Estimates of power system frequency are beginning to be used in critical, real-time applications such as synthetic inertia. The behavior of the algorithms used to estimate frequency from point-on-wave signals can be complicated, and algorithm tuning difficult for non-experts. In this paper, small-signal approximations for four common frequency estimation algorithms are presented. These approximations are demonstrated to be both theoretically and empirically sound. They are valuable for three primary reasons: 1) they reduce the level of technical expertise required for effective tuning; 2) they effectively capture the dynamics of the algorithm so can be used as a proxy for the algorithm itself in the analysis of feedback control loops that employ frequency feedback; and 3) they can easily be implemented in transient stability simulation software in order to represent realistic frequency estimation.\",\"PeriodicalId\":241987,\"journal\":{\"name\":\"2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/td43745.2022.9817012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/td43745.2022.9817012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Small-signal Approximations of Frequency Estimation Algorithms
Estimates of power system frequency are beginning to be used in critical, real-time applications such as synthetic inertia. The behavior of the algorithms used to estimate frequency from point-on-wave signals can be complicated, and algorithm tuning difficult for non-experts. In this paper, small-signal approximations for four common frequency estimation algorithms are presented. These approximations are demonstrated to be both theoretically and empirically sound. They are valuable for three primary reasons: 1) they reduce the level of technical expertise required for effective tuning; 2) they effectively capture the dynamics of the algorithm so can be used as a proxy for the algorithm itself in the analysis of feedback control loops that employ frequency feedback; and 3) they can easily be implemented in transient stability simulation software in order to represent realistic frequency estimation.