Transformers Fleet Management Through the use of an Advanced Health Index

F. Scatiggio, M. Pompili, Luigi Calacara
{"title":"Transformers Fleet Management Through the use of an Advanced Health Index","authors":"F. Scatiggio, M. Pompili, Luigi Calacara","doi":"10.1109/EIC.2018.8481030","DOIUrl":null,"url":null,"abstract":"Power transformers represent the highest value of the equipment installed in transmission substations, comprising up the 60% of the total investment. They are expected to operate for several decades without faults and possibly without relevant unscheduled maintenance practice. The new approach is developed for reducing time based maintenance and, increasing condition based maintenance and to introduce predictive maintenance as well. The aim of predictive maintenance is first to predict when transformer failure might occur, and secondly, to prevent occurrence of the failure by performing maintenance. Diagnostic information can be evaluated individually or better by a complex algorithm which merges all the single inputs and their Rate of Increase (RoI) creating a mono-dimensional figure called Health Index (HI). This concept represents a real ‘shifting of paradigm’, as it deeply affects the criteria for transformers grid management and selection of the electrical utilities and grid companies.","PeriodicalId":184139,"journal":{"name":"2018 IEEE Electrical Insulation Conference (EIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Electrical Insulation Conference (EIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EIC.2018.8481030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12

Abstract

Power transformers represent the highest value of the equipment installed in transmission substations, comprising up the 60% of the total investment. They are expected to operate for several decades without faults and possibly without relevant unscheduled maintenance practice. The new approach is developed for reducing time based maintenance and, increasing condition based maintenance and to introduce predictive maintenance as well. The aim of predictive maintenance is first to predict when transformer failure might occur, and secondly, to prevent occurrence of the failure by performing maintenance. Diagnostic information can be evaluated individually or better by a complex algorithm which merges all the single inputs and their Rate of Increase (RoI) creating a mono-dimensional figure called Health Index (HI). This concept represents a real ‘shifting of paradigm’, as it deeply affects the criteria for transformers grid management and selection of the electrical utilities and grid companies.
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
通过使用高级健康指数来管理变形金刚车队
电力变压器是变电站设备中价值最高的设备,占总投资的60%。它们预计将运行几十年而不会出现故障,也可能没有相关的计划外维护实践。新方法的开发是为了减少基于时间的维护,增加基于状态的维护,并引入预测性维护。预测性维护的目的首先是预测变压器何时可能发生故障,其次是通过维护来防止故障的发生。诊断信息可以单独评估,也可以通过一个复杂的算法更好地评估,该算法将所有单一输入及其增长率(RoI)合并在一起,创建一个称为健康指数(HI)的单维图。这一概念代表了真正的“范式转变”,因为它深刻地影响了变压器电网管理和电力公用事业和电网公司选择的标准。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Experimental Research on Flashover Characteristics of Insulator with N2 Dissolved Gas Analysis (DGA) of Arc Discharge Fault in Transformer Insulation Oils (Ester and Mineral Oils) Nonparametric Kernel Density Estimation Model of Transformer Health Based on Dissolved Gases in Oil Experimental validation of a moisture sensor for cellulosic insulation of power transformers Development Process of Vibration Sparking Erosion on Stator Bars
×
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