Solving the Energy Management Problems Using Thermal Exchange Optimization

IF 0.9 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
Zahia Djeblahi, B. Mahdad, K. Srairi
{"title":"Solving the Energy Management Problems Using Thermal Exchange Optimization","authors":"Zahia Djeblahi, B. Mahdad, K. Srairi","doi":"10.5152/electrica.2024.23045","DOIUrl":null,"url":null,"abstract":"This paper proposes a new metaheuristic optimization algorithm, namely thermal exchange optimization (TEO), to solve the optimal power fl ow (OPF) problems. Various con fl ict objective functions, such as the total fuel cost (TFC), the total power loss, total emission gas (TEG), and the total voltage deviation have been optimized individually and simultaneously. The proposed TEO is validated on the electric test system Institute of Electrical and Electronics Engineers 30-Bus. The optimization results achieved by the proposed method in solving single-objective functions were more e ff ective in fi nding the optimal solution compared to several well-known algorithms. The results clearly show the superiority of the proposed method in the majority of the case studies, with a better solution and competitive computational time. In contrast, the proposed multi-objective TEO (MOTEO) based OPF is investigated to solve the multi-objective OPF. It can be noticed from the results obtained that the proposed MOTEO achieved the better optimum compromise solution with a TFC value of 822.4796 $/h and a TEG value of 0.26939 ton/h, which yields a competitive total cost (970.8219 $/h) compared to those obtained by other algorithms. Moreover, the statistical analysis proves that the proposed MOTEO needs a lower number of trials to locate the best solution, also the standard deviation required to solve the single-objective problems is 0.03361, which is better compared to other techniques. The simulation results achieved by this method compared with other competitive algorithms proved the superiority of MOTEO in fi nding better solutions while also producing a high-quality Pareto front with appropriate precision.","PeriodicalId":36781,"journal":{"name":"Electrica","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Electrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5152/electrica.2024.23045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

This paper proposes a new metaheuristic optimization algorithm, namely thermal exchange optimization (TEO), to solve the optimal power fl ow (OPF) problems. Various con fl ict objective functions, such as the total fuel cost (TFC), the total power loss, total emission gas (TEG), and the total voltage deviation have been optimized individually and simultaneously. The proposed TEO is validated on the electric test system Institute of Electrical and Electronics Engineers 30-Bus. The optimization results achieved by the proposed method in solving single-objective functions were more e ff ective in fi nding the optimal solution compared to several well-known algorithms. The results clearly show the superiority of the proposed method in the majority of the case studies, with a better solution and competitive computational time. In contrast, the proposed multi-objective TEO (MOTEO) based OPF is investigated to solve the multi-objective OPF. It can be noticed from the results obtained that the proposed MOTEO achieved the better optimum compromise solution with a TFC value of 822.4796 $/h and a TEG value of 0.26939 ton/h, which yields a competitive total cost (970.8219 $/h) compared to those obtained by other algorithms. Moreover, the statistical analysis proves that the proposed MOTEO needs a lower number of trials to locate the best solution, also the standard deviation required to solve the single-objective problems is 0.03361, which is better compared to other techniques. The simulation results achieved by this method compared with other competitive algorithms proved the superiority of MOTEO in fi nding better solutions while also producing a high-quality Pareto front with appropriate precision.
利用热交换优化解决能源管理问题
本文提出了一种新的元启发式优化算法,即热交换优化算法(TEO),用于解决最优电网(OPF)问题。对总燃料成本(TFC)、总功率损耗、总排放气体(TEG)和总电压偏差等各种冲突目标函数进行了单独和同时优化。提出的 TEO 在电气与电子工程师协会 30 总线电力测试系统上进行了验证。与几种著名算法相比,拟议方法在求解单目标函数时获得的优化结果在找到最优解方面更加有效。结果清楚地表明,在大多数案例研究中,所提出的方法具有更优越的解法和更短的计算时间。相比之下,本文研究了基于多目标 TEO(MOTEO)的 OPF,以求解多目标 OPF。从得到的结果可以看出,提议的 MOTEO 实现了更好的最优折中方案,TFC 值为 822.4796 美元/小时,TEG 值为 0.26939 吨/小时,与其他算法相比,总成本(970.8219 美元/小时)具有竞争力。此外,统计分析表明,拟议的 MOTEO 需要较少的试验次数才能找到最佳解决方案,而且解决单目标问题所需的标准偏差为 0.03361,优于其他技术。与其他竞争性算法相比,该方法取得的仿真结果证明了 MOTEO 在找到更好的解方面的优越性,同时还产生了具有适当精度的高质量帕累托前沿。
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
Electrica
Electrica Engineering-Electrical and Electronic Engineering
CiteScore
2.10
自引率
0.00%
发文量
59
×
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