Managing Power Flows in SmartGrids with Physically-Inspired Reactive Agents

Franck Gechter, Lauri Fabrice, Gussy Anthony, Staine Florian
{"title":"Managing Power Flows in SmartGrids with Physically-Inspired Reactive Agents","authors":"Franck Gechter, Lauri Fabrice, Gussy Anthony, Staine Florian","doi":"10.1109/ICTAI.2018.00072","DOIUrl":null,"url":null,"abstract":"Managing electrical energy is nowadays a challenge of paramount importance in many countries. One of the numerous problems of this challenge is the one that consists in determining (and managing) the power flows between consumers and producers in a micro-grid (i.e. a local electrical connected network nearly isolated from the main, national level, electricity network), so as to take advantage of the renewable sources, typically solar panel and wind generator, and solicit the main grid (i.e. the global network) the least possible in order to fulfill the demand, for instance. To manage the power flows, we propose in this paper an approach based on agents that represent consumers and producers. They are moved by attractive and repulsive forces, inspired by Newtonian Physics, whose intensities depend on the amount of electrical power available by the ones and required by the others. Experimental results obtained from simulations show that this approach can manage power flows in an open system by avoiding black-out. Moreover, the results obtained show adaptability skills (i.e. producers can be added and removed in runtime).","PeriodicalId":254686,"journal":{"name":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTAI.2018.00072","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

Managing electrical energy is nowadays a challenge of paramount importance in many countries. One of the numerous problems of this challenge is the one that consists in determining (and managing) the power flows between consumers and producers in a micro-grid (i.e. a local electrical connected network nearly isolated from the main, national level, electricity network), so as to take advantage of the renewable sources, typically solar panel and wind generator, and solicit the main grid (i.e. the global network) the least possible in order to fulfill the demand, for instance. To manage the power flows, we propose in this paper an approach based on agents that represent consumers and producers. They are moved by attractive and repulsive forces, inspired by Newtonian Physics, whose intensities depend on the amount of electrical power available by the ones and required by the others. Experimental results obtained from simulations show that this approach can manage power flows in an open system by avoiding black-out. Moreover, the results obtained show adaptability skills (i.e. producers can be added and removed in runtime).
使用物理启发的反应代理管理智能电网中的潮流
管理电能是当今许多国家最重要的挑战。这一挑战的众多问题之一是确定(和管理)微电网中消费者和生产者之间的电力流动(即几乎与国家一级的主要电网隔离的本地电力连接网络),以便利用可再生能源,通常是太阳能电池板和风力发电机,并要求主电网(即全球网络)尽可能少地满足需求,例如。为了管理电力流,本文提出了一种基于代表消费者和生产者的代理的方法。它们受引力和排斥力的影响,受牛顿物理学的启发,引力和排斥力的强度取决于一方可用的电力和另一方所需的电力。仿真实验结果表明,该方法可以有效地控制开放系统中的潮流,避免停电。此外,获得的结果显示适应性技能(即可以在运行时添加和删除生产者)。
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