M. Zanoni, C. Chiappa, R. Chiumeo, L. Tenti, H. Shadmehr
{"title":"意大利中压网络电压跌落特性的高阶统计量","authors":"M. Zanoni, C. Chiappa, R. Chiumeo, L. Tenti, H. Shadmehr","doi":"10.23919/AEIT50178.2020.9241206","DOIUrl":null,"url":null,"abstract":"In this paper, an ex-post analysis based on Higher-Order Statics (HOS) has been proposed for characterizing voltage dips (VDs) recorded in the Italian distribution network by the research monitoring system QuEEN, managed by RSE. HOS basically consists in a signal waveform compression: by considering the signal as a probability distribution function, it can be approximated with its statistical moments; in this work the second (variance), the third (skewness) and the fourth (kurtosis) order moments have been considered. This technique has been applied on a set of waveforms associated to events recorded by the QuEEN monitoring system. The associated VDs have been characterized in terms of residual voltage and duration; moreover, by considering the behavior of the kurtosis and skewness also the “true” and “false” VDs can be detected. In this way an efficient and effectiveness processing technique can be implemented for future developments of the QuEEN functionalities.","PeriodicalId":6689,"journal":{"name":"2020 AEIT International Annual Conference (AEIT)","volume":"10 46 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Higher-Order Statistics for Voltage Dips Characterization on Italian MV Networks\",\"authors\":\"M. Zanoni, C. Chiappa, R. Chiumeo, L. Tenti, H. Shadmehr\",\"doi\":\"10.23919/AEIT50178.2020.9241206\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, an ex-post analysis based on Higher-Order Statics (HOS) has been proposed for characterizing voltage dips (VDs) recorded in the Italian distribution network by the research monitoring system QuEEN, managed by RSE. HOS basically consists in a signal waveform compression: by considering the signal as a probability distribution function, it can be approximated with its statistical moments; in this work the second (variance), the third (skewness) and the fourth (kurtosis) order moments have been considered. This technique has been applied on a set of waveforms associated to events recorded by the QuEEN monitoring system. The associated VDs have been characterized in terms of residual voltage and duration; moreover, by considering the behavior of the kurtosis and skewness also the “true” and “false” VDs can be detected. In this way an efficient and effectiveness processing technique can be implemented for future developments of the QuEEN functionalities.\",\"PeriodicalId\":6689,\"journal\":{\"name\":\"2020 AEIT International Annual Conference (AEIT)\",\"volume\":\"10 46 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 AEIT International Annual Conference (AEIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/AEIT50178.2020.9241206\",\"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 AEIT International Annual Conference (AEIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/AEIT50178.2020.9241206","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Higher-Order Statistics for Voltage Dips Characterization on Italian MV Networks
In this paper, an ex-post analysis based on Higher-Order Statics (HOS) has been proposed for characterizing voltage dips (VDs) recorded in the Italian distribution network by the research monitoring system QuEEN, managed by RSE. HOS basically consists in a signal waveform compression: by considering the signal as a probability distribution function, it can be approximated with its statistical moments; in this work the second (variance), the third (skewness) and the fourth (kurtosis) order moments have been considered. This technique has been applied on a set of waveforms associated to events recorded by the QuEEN monitoring system. The associated VDs have been characterized in terms of residual voltage and duration; moreover, by considering the behavior of the kurtosis and skewness also the “true” and “false” VDs can be detected. In this way an efficient and effectiveness processing technique can be implemented for future developments of the QuEEN functionalities.