Flicker’s sources identification using a case-based reasoning prototype

A. Miron, A. Cziker, Hadrian C. Bogariu
{"title":"Flicker’s sources identification using a case-based reasoning prototype","authors":"A. Miron, A. Cziker, Hadrian C. Bogariu","doi":"10.1109/UPEC.2019.8893585","DOIUrl":null,"url":null,"abstract":"Flicker is an issue of power quality that affects both the utility companies and consumers. To mitigate and eliminate flicker, the first stage is to identify the source. This paper presents an application of artificial intelligence techniques, namely a knowledge-based system, dedicated for detecting the flicker source. The application is a prototype that was built using case-based reasoning. The main elements of the prototype are the cases that were obtained from in-situ measurements at a power substation over an observation period of a year. The prototype was tested using data from a different power substation. The results show that the prototype detects properly the sources, confirming the utility of artificial intelligence in this field ofpower quality.","PeriodicalId":6670,"journal":{"name":"2019 54th International Universities Power Engineering Conference (UPEC)","volume":"65 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 54th International Universities Power Engineering Conference (UPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UPEC.2019.8893585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Flicker is an issue of power quality that affects both the utility companies and consumers. To mitigate and eliminate flicker, the first stage is to identify the source. This paper presents an application of artificial intelligence techniques, namely a knowledge-based system, dedicated for detecting the flicker source. The application is a prototype that was built using case-based reasoning. The main elements of the prototype are the cases that were obtained from in-situ measurements at a power substation over an observation period of a year. The prototype was tested using data from a different power substation. The results show that the prototype detects properly the sources, confirming the utility of artificial intelligence in this field ofpower quality.
使用基于案例的推理原型的闪烁源识别
闪烁是一个影响公用事业公司和消费者的电能质量问题。为了减轻和消除闪烁,首先要确定闪烁的来源。本文介绍了人工智能技术的一种应用,即基于知识的闪烁源检测系统。该应用程序是使用基于案例的推理构建的原型。原型的主要元素是在一年的观察期内从变电站的现场测量中获得的案例。原型机使用来自另一个变电站的数据进行了测试。实验结果表明,该样机能够很好地检测出源,证实了人工智能在电能质量检测领域的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信