Monitoring, Predicting, and Optimizing Energy Consumptions

P. Cardoso, J. Monteiro, C. Cabrita, J. Semião, D. Cruz, Nelson Pinto, C. Ramos, Luís M. R. Oliveira, J. Rodrigues
{"title":"Monitoring, Predicting, and Optimizing Energy Consumptions","authors":"P. Cardoso, J. Monteiro, C. Cabrita, J. Semião, D. Cruz, Nelson Pinto, C. Ramos, Luís M. R. Oliveira, J. Rodrigues","doi":"10.4018/978-1-7998-2112-0.ch005","DOIUrl":null,"url":null,"abstract":"Energy consumption and, consequently, the associated costs (e.g., environmental and monetary) concern most individuals, companies, and institutions. Platforms for the monitoring, predicting, and optimizing energy consumption are an important asset that can contribute to the awareness about the ongoing usage levels, but also to an effective reduction of these levels. A solution is to leave the decisions to smart system, supported for instance in machine learning and optimization algorithms. This chapter involves those aspects and the related fields with emphasis in the prediction of energy consumption to optimize its usage policies.","PeriodicalId":342576,"journal":{"name":"Research Anthology on Clean Energy Management and Solutions","volume":"93 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research Anthology on Clean Energy Management and Solutions","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-7998-2112-0.ch005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Energy consumption and, consequently, the associated costs (e.g., environmental and monetary) concern most individuals, companies, and institutions. Platforms for the monitoring, predicting, and optimizing energy consumption are an important asset that can contribute to the awareness about the ongoing usage levels, but also to an effective reduction of these levels. A solution is to leave the decisions to smart system, supported for instance in machine learning and optimization algorithms. This chapter involves those aspects and the related fields with emphasis in the prediction of energy consumption to optimize its usage policies.
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
监测、预测和优化能源消耗
能源消耗及其相关成本(如环境成本和货币成本)关系到大多数个人、公司和机构。用于监测、预测和优化能源消耗的平台是一项重要资产,它不仅有助于了解当前的使用水平,而且还有助于有效地降低这些水平。一个解决方案是将决策留给智能系统,例如在机器学习和优化算法的支持下。本章涉及这些方面和相关领域,重点是能源消耗预测,以优化其使用政策。
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
Energy Consumption Optimization in Agriculture and Development Perspectives An Integrated Entropy-TOPSIS Methodology for Evaluating Green Energy Sources Design of Solar System for LTE Networks Creation of Financial and Environmental Values With Solar Photovoltaic Projects While Managing Risks Photovoltaic Solar Modules of Different Types and Designs for Energy Supply
×
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