意大利中压网络电压跌落特性的高阶统计量

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}
引用次数: 2

摘要

本文提出了一种基于高阶静力学(HOS)的事后分析方法,用于表征由RSE管理的研究监测系统QuEEN在意大利配电网中记录的电压降(VDs)。HOS基本上就是一个信号波形压缩:把信号看作一个概率分布函数,用它的统计矩来近似;在这项工作中,第二(方差),第三(偏度)和第四(峰度)阶矩已经被考虑。该技术已应用于与QuEEN监测系统记录的事件相关的一组波形。相关的VDs已经在剩余电压和持续时间方面被表征;此外,通过考虑峰度和偏度的行为,还可以检测出“真”和“假”VDs。通过这种方式,可以为QuEEN功能的未来开发实现高效和有效的处理技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Spectral and Discriminant Analysis Based Classification of Faults in Induction Machines Overview of distribution grid test systems for benchmarking of power system analyses Exploit GaN FET technologies in high efficiency flyback topologies: pros and cons of different architectures Modeling the OHL vulnerability to strong wind New flexibility services and technologies: ENEL experiences in Italy
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1