{"title":"三相电力系统非线性状态空间频率估计器","authors":"S. Talebi, S. Kanna, D. Mandic","doi":"10.1109/IJCNN.2015.7280689","DOIUrl":null,"url":null,"abstract":"Frequency estimation in three-phase power systems is considered from a state space point of view, and a robust and fast converging algorithm for estimating the fundamental frequency of three-phase power systems is introduced. This is achieved by exploiting the Clarke transform to incorporate the information from all the phases and then designing a widely linear state space estimator that can accurately estimate the fundamental frequency of both balanced and unbalanced three-phase power systems. The framework is then expanded to modify the state space model in order to account for the presence of harmonics in the system. The performance of the developed algorithm is validated through simulations on both synthetic data and real-world data recordings, where it is shown that the developed algorithm outperforms standard linear and the recently introduced widely liner frequency estimators.","PeriodicalId":6539,"journal":{"name":"2015 International Joint Conference on Neural Networks (IJCNN)","volume":"55 1","pages":"1-7"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"A non-linear state space frequency estimator for three-phase power systems\",\"authors\":\"S. Talebi, S. Kanna, D. Mandic\",\"doi\":\"10.1109/IJCNN.2015.7280689\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Frequency estimation in three-phase power systems is considered from a state space point of view, and a robust and fast converging algorithm for estimating the fundamental frequency of three-phase power systems is introduced. This is achieved by exploiting the Clarke transform to incorporate the information from all the phases and then designing a widely linear state space estimator that can accurately estimate the fundamental frequency of both balanced and unbalanced three-phase power systems. The framework is then expanded to modify the state space model in order to account for the presence of harmonics in the system. The performance of the developed algorithm is validated through simulations on both synthetic data and real-world data recordings, where it is shown that the developed algorithm outperforms standard linear and the recently introduced widely liner frequency estimators.\",\"PeriodicalId\":6539,\"journal\":{\"name\":\"2015 International Joint Conference on Neural Networks (IJCNN)\",\"volume\":\"55 1\",\"pages\":\"1-7\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Joint Conference on Neural Networks (IJCNN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IJCNN.2015.7280689\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Joint Conference on Neural Networks (IJCNN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.2015.7280689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A non-linear state space frequency estimator for three-phase power systems
Frequency estimation in three-phase power systems is considered from a state space point of view, and a robust and fast converging algorithm for estimating the fundamental frequency of three-phase power systems is introduced. This is achieved by exploiting the Clarke transform to incorporate the information from all the phases and then designing a widely linear state space estimator that can accurately estimate the fundamental frequency of both balanced and unbalanced three-phase power systems. The framework is then expanded to modify the state space model in order to account for the presence of harmonics in the system. The performance of the developed algorithm is validated through simulations on both synthetic data and real-world data recordings, where it is shown that the developed algorithm outperforms standard linear and the recently introduced widely liner frequency estimators.