求解经济负荷调度问题的海鸥优化算法

Mohammad Hanif, N. Mohammad, K. Biswas, Bijoy Harun
{"title":"求解经济负荷调度问题的海鸥优化算法","authors":"Mohammad Hanif, N. Mohammad, K. Biswas, Bijoy Harun","doi":"10.1109/ECCE57851.2023.10101516","DOIUrl":null,"url":null,"abstract":"To solve the optimization problem of Economic Load Dispatch (ELD), a number of metaheuristic approaches have already been implemented, exhibiting substantial improvement over the conventional technique. Despite this, due to the global energy crisis, research in ELD still continues to garner considerable interest. In this study, the Seagull Optimization Algorithm (SOA), a recently developed swarm intelligence technique, is applied in ELD. As the SOA algorithm has never been utilized in the ELD, it is important to investigate its efficacy and validity in this domain. Here, two case studies of ELD incorporating 6 and 10 generator units are implemented employing SOA. What's more, the performance of SOA in ELD is compared with respect to three other previously applied metaheuristics algorithms. Results indicate that SOA is a potential algorithm capable of handling the practical optimization challenge of ELD problem more effectively, especially in large power plants having more than 6 units.","PeriodicalId":131537,"journal":{"name":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Seagull Optimization Algorithm for Solving Economic Load Dispatch Problem\",\"authors\":\"Mohammad Hanif, N. Mohammad, K. Biswas, Bijoy Harun\",\"doi\":\"10.1109/ECCE57851.2023.10101516\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To solve the optimization problem of Economic Load Dispatch (ELD), a number of metaheuristic approaches have already been implemented, exhibiting substantial improvement over the conventional technique. Despite this, due to the global energy crisis, research in ELD still continues to garner considerable interest. In this study, the Seagull Optimization Algorithm (SOA), a recently developed swarm intelligence technique, is applied in ELD. As the SOA algorithm has never been utilized in the ELD, it is important to investigate its efficacy and validity in this domain. Here, two case studies of ELD incorporating 6 and 10 generator units are implemented employing SOA. What's more, the performance of SOA in ELD is compared with respect to three other previously applied metaheuristics algorithms. Results indicate that SOA is a potential algorithm capable of handling the practical optimization challenge of ELD problem more effectively, especially in large power plants having more than 6 units.\",\"PeriodicalId\":131537,\"journal\":{\"name\":\"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)\",\"volume\":\"2014 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECCE57851.2023.10101516\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Electrical, Computer and Communication Engineering (ECCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECCE57851.2023.10101516","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

为了解决经济负荷调度(ELD)的优化问题,许多元启发式方法已经被应用,比传统的方法有了很大的改进。尽管如此,由于全球能源危机,对ELD的研究仍然获得了相当大的兴趣。在本研究中,海鸥优化算法(SOA)是一种新兴的群体智能技术。由于SOA算法尚未应用于实际应用领域,因此研究其在实际应用领域的有效性和有效性具有重要意义。在这里,使用SOA实现了包含6个和10个发电机组的ELD的两个案例研究。此外,还将SOA在ELD中的性能与之前应用的其他三种元启发式算法进行了比较。结果表明,SOA是一种有潜力的算法,能够更有效地处理ELD问题的实际优化挑战,特别是在6台以上的大型发电厂。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Seagull Optimization Algorithm for Solving Economic Load Dispatch Problem
To solve the optimization problem of Economic Load Dispatch (ELD), a number of metaheuristic approaches have already been implemented, exhibiting substantial improvement over the conventional technique. Despite this, due to the global energy crisis, research in ELD still continues to garner considerable interest. In this study, the Seagull Optimization Algorithm (SOA), a recently developed swarm intelligence technique, is applied in ELD. As the SOA algorithm has never been utilized in the ELD, it is important to investigate its efficacy and validity in this domain. Here, two case studies of ELD incorporating 6 and 10 generator units are implemented employing SOA. What's more, the performance of SOA in ELD is compared with respect to three other previously applied metaheuristics algorithms. Results indicate that SOA is a potential algorithm capable of handling the practical optimization challenge of ELD problem more effectively, especially in large power plants having more than 6 units.
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
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