公寓能源管理系统的多目标改进蟑螂群算法

IF 2.4 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Information (Switzerland) Pub Date : 2023-09-25 DOI:10.3390/info14100521
Bilal Naji Alhasnawi, Basil H. Jasim, Ali M. Jasim, Vladimír Bureš, Arshad Naji Alhasnawi, Raad Z. Homod, Majid Razaq Mohamed Alsemawai, Rabeh Abbassi, Bishoy E. Sedhom
{"title":"公寓能源管理系统的多目标改进蟑螂群算法","authors":"Bilal Naji Alhasnawi, Basil H. Jasim, Ali M. Jasim, Vladimír Bureš, Arshad Naji Alhasnawi, Raad Z. Homod, Majid Razaq Mohamed Alsemawai, Rabeh Abbassi, Bishoy E. Sedhom","doi":"10.3390/info14100521","DOIUrl":null,"url":null,"abstract":"The electrical demand and generation in power systems is currently the biggest source of uncertainty for an electricity provider. For a dependable and financially advantageous electricity system, demand response (DR) success as a result of household appliance energy management has attracted significant attention. Due to fluctuating electricity rates and usage trends, determining the best schedule for apartment appliances can be difficult. As a result of this context, the Improved Cockroach Swarm Optimization Algorithm (ICSOA) is combined with the Innovative Apartments Appliance Scheduling (IAAS) framework. Using the proposed technique, the cost of electricity reduction, user comfort maximization, and peak-to-average ratio reduction are analyzed for apartment appliances. The proposed framework is evaluated by comparing it with BFOA and W/O scheduling cases. In comparison to the W/O scheduling case, the BFOA method lowered energy costs by 17.75%, but the ICSA approach reduced energy cost by 46.085%. According to the results, the created ICSA algorithm performed better than the BFOA and W/O scheduling situations in terms of the stated objectives and was advantageous to both utilities and consumers.","PeriodicalId":38479,"journal":{"name":"Information (Switzerland)","volume":"31 1","pages":"0"},"PeriodicalIF":2.4000,"publicationDate":"2023-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems\",\"authors\":\"Bilal Naji Alhasnawi, Basil H. Jasim, Ali M. Jasim, Vladimír Bureš, Arshad Naji Alhasnawi, Raad Z. Homod, Majid Razaq Mohamed Alsemawai, Rabeh Abbassi, Bishoy E. Sedhom\",\"doi\":\"10.3390/info14100521\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The electrical demand and generation in power systems is currently the biggest source of uncertainty for an electricity provider. For a dependable and financially advantageous electricity system, demand response (DR) success as a result of household appliance energy management has attracted significant attention. Due to fluctuating electricity rates and usage trends, determining the best schedule for apartment appliances can be difficult. As a result of this context, the Improved Cockroach Swarm Optimization Algorithm (ICSOA) is combined with the Innovative Apartments Appliance Scheduling (IAAS) framework. Using the proposed technique, the cost of electricity reduction, user comfort maximization, and peak-to-average ratio reduction are analyzed for apartment appliances. The proposed framework is evaluated by comparing it with BFOA and W/O scheduling cases. In comparison to the W/O scheduling case, the BFOA method lowered energy costs by 17.75%, but the ICSA approach reduced energy cost by 46.085%. According to the results, the created ICSA algorithm performed better than the BFOA and W/O scheduling situations in terms of the stated objectives and was advantageous to both utilities and consumers.\",\"PeriodicalId\":38479,\"journal\":{\"name\":\"Information (Switzerland)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information (Switzerland)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/info14100521\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information (Switzerland)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/info14100521","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 1

摘要

电力系统的电力需求和发电量目前是电力供应商最大的不确定性来源。对于一个可靠和经济上有利的电力系统,需求响应(DR)的成功是家电能源管理的结果,引起了人们的极大关注。由于电费和使用趋势的波动,确定公寓电器的最佳时间表可能很困难。在此背景下,将改进的蟑螂群优化算法(ICSOA)与创新公寓家电调度(IAAS)框架相结合。利用所提出的技术,分析了公寓电器的电力成本降低、用户舒适度最大化和峰值-平均比降低。通过与BFOA和W/O调度实例的比较,对该框架进行了评价。与W/O调度相比,BFOA方法降低了17.75%的能源成本,而ICSA方法降低了46.085%的能源成本。结果表明,所创建的ICSA算法在既定目标方面优于BFOA和W/O调度情况,并且对公用事业和消费者都有利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
A Multi-Objective Improved Cockroach Swarm Algorithm Approach for Apartment Energy Management Systems
The electrical demand and generation in power systems is currently the biggest source of uncertainty for an electricity provider. For a dependable and financially advantageous electricity system, demand response (DR) success as a result of household appliance energy management has attracted significant attention. Due to fluctuating electricity rates and usage trends, determining the best schedule for apartment appliances can be difficult. As a result of this context, the Improved Cockroach Swarm Optimization Algorithm (ICSOA) is combined with the Innovative Apartments Appliance Scheduling (IAAS) framework. Using the proposed technique, the cost of electricity reduction, user comfort maximization, and peak-to-average ratio reduction are analyzed for apartment appliances. The proposed framework is evaluated by comparing it with BFOA and W/O scheduling cases. In comparison to the W/O scheduling case, the BFOA method lowered energy costs by 17.75%, but the ICSA approach reduced energy cost by 46.085%. According to the results, the created ICSA algorithm performed better than the BFOA and W/O scheduling situations in terms of the stated objectives and was advantageous to both utilities and consumers.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Information (Switzerland)
Information (Switzerland) Computer Science-Information Systems
CiteScore
6.90
自引率
0.00%
发文量
515
审稿时长
11 weeks
期刊最新文献
Weakly Supervised Learning Approach for Implicit Aspect Extraction Science Mapping of Meta-Analysis in Agricultural Science An Integrated Time Series Prediction Model Based on Empirical Mode Decomposition and Two Attention Mechanisms Context-Aware Personalization: A Systems Engineering Framework Polarizing Topics on Twitter in the 2022 United States Elections
×
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