A Smart Home Energy Consumption Optimisation Based on Multi-Constraints PSO Strategy

Marwa Ben Arab, M. Rekik, L. Krichen
{"title":"A Smart Home Energy Consumption Optimisation Based on Multi-Constraints PSO Strategy","authors":"Marwa Ben Arab, M. Rekik, L. Krichen","doi":"10.1109/IC_ASET53395.2022.9765907","DOIUrl":null,"url":null,"abstract":"The smart home, which is regarded as a key component of the smart grid consumption, uses innovative communication and information technologies in order to improve the reliability, stability, and efficiency of the electric system. Plug-in electric vehicle (PEV) which is a controllable component, has the flexibility of charging and discharging through a domestic charging socket at home. In this paper, a home energy management system optimisation HEMSO is suggested to arrive at an optimal scheduling of PEV in a smart home in order to smooth its power profile, obtaining a free charging of plug-in electric vehicles (PEV) and reducing the electricity bill. The proposed framework is implemented through Particle Swarm Optimization (PSO) algorithm to improve the efficacy of the proposed strategy.","PeriodicalId":6874,"journal":{"name":"2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","volume":"58 1","pages":"544-549"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 5th International Conference on Advanced Systems and Emergent Technologies (IC_ASET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC_ASET53395.2022.9765907","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

The smart home, which is regarded as a key component of the smart grid consumption, uses innovative communication and information technologies in order to improve the reliability, stability, and efficiency of the electric system. Plug-in electric vehicle (PEV) which is a controllable component, has the flexibility of charging and discharging through a domestic charging socket at home. In this paper, a home energy management system optimisation HEMSO is suggested to arrive at an optimal scheduling of PEV in a smart home in order to smooth its power profile, obtaining a free charging of plug-in electric vehicles (PEV) and reducing the electricity bill. The proposed framework is implemented through Particle Swarm Optimization (PSO) algorithm to improve the efficacy of the proposed strategy.
基于多约束粒子群策略的智能家居能耗优化
智能家居被认为是智能电网消费的关键组成部分,它利用创新的通信和信息技术来提高电力系统的可靠性、稳定性和效率。插电式电动汽车(PEV)是一种可控部件,可以灵活地在家中通过家用充电插座进行充放电。本文提出了一种家庭能源管理系统优化HEMSO,以达到智能家庭中PEV的最优调度,使其电力分布平滑,从而获得插电式电动汽车(PEV)的免费充电并降低电费。通过粒子群优化(PSO)算法实现该框架,提高了该策略的有效性。
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