Identification and feature selection of non-technical losses for industrial consumers using the software WEKA

Caio Cesar, Oba Ramos, Andre Nunes De Souza, Danilo S. Gastaldello, J. Papa
{"title":"Identification and feature selection of non-technical losses for industrial consumers using the software WEKA","authors":"Caio Cesar, Oba Ramos, Andre Nunes De Souza, Danilo S. Gastaldello, J. Papa","doi":"10.1109/INDUSCON.2012.6451485","DOIUrl":null,"url":null,"abstract":"This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids.","PeriodicalId":442317,"journal":{"name":"2012 10th IEEE/IAS International Conference on Industry Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 10th IEEE/IAS International Conference on Industry Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDUSCON.2012.6451485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11

Abstract

This work has as objectives the implementation of a intelligent computational tool to identify the non-technical losses and to select its most relevant features, considering information from the database with industrial consumers profiles of a power company. The solution to this problem is not trivial and not of regional character, the minimization of non-technical loss represents the guarantee of investments in product quality and maintenance of power systems, introduced by a competitive environment after the period of privatization in the national scene. This work presents using the WEKA software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithms, this way, can be possible to automate applications on Smart Grids.
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
使用WEKA软件对工业消费者进行非技术损失的识别和特征选择
这项工作的目标是实现一种智能计算工具,以识别非技术损失并选择其最相关的特征,考虑到数据库中的信息与电力公司的工业消费者概况。这一问题的解决不是微不足道的,也不是区域性的,尽量减少非技术损失是保证在产品质量和电力系统维修方面的投资,这是在国家舞台私有化时期之后的竞争环境所带来的。本文介绍了利用WEKA软件提出的目标,比较了各种分类技术并通过智能算法进行优化,这样,就有可能在智能电网上实现自动化应用。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Practical comparisons among electronic energy meters, a precision energy meter and IEEE1459 for reactive energy measurements, under unbalanced and non-sinusoidal conditions A new design methodology for multipulse rectifiers with Delta auto-connected transformers and a retrofit application in Adjustable Speed Drives (ASDs) A single-phase single-stage buck-boost inverter intended for low power alternative energy conversion systems: Analysis, design and experimentation Interferometric measurements of nanometric displacements in a Piezoelectric Flextensional Actuator by using the new J1…J5 method Identification and feature selection of non-technical losses for industrial consumers using the software WEKA
×
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:604180095
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