Intelligent approach for optimal energy management of chiller plant using fuzzy and PSO techniques

E. A. H. Abdalla, P. Nallagownden, N. M. Nor, M. Romlie, M. Abdalsalam, M. S. Muthuvalu
{"title":"Intelligent approach for optimal energy management of chiller plant using fuzzy and PSO techniques","authors":"E. A. H. Abdalla, P. Nallagownden, N. M. Nor, M. Romlie, M. Abdalsalam, M. S. Muthuvalu","doi":"10.1109/ICIAS.2016.7824050","DOIUrl":null,"url":null,"abstract":"This paper discusses the optimal energy management of chiller plant. Two intelligent approaches have been employed. Fuzzy is used to adjust the set-point and, while PSO is utilized to optimize the objective function after setting by Fuzzy. Moreover, Fuzzy is also utilized to adjust weighting factors in order to find the best values for the PSO local and global. This will improve PSO performance. The proposed method was combined two levels as Fuzzified PSO, and the model has been simulated and validated by a real case study which consists of 5 electric-driven chillers. The results have shown that the effectiveness of the proposed method compared to the conventional one, and it also has demonstrated a better power saving.","PeriodicalId":247287,"journal":{"name":"2016 6th International Conference on Intelligent and Advanced Systems (ICIAS)","volume":"356 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 6th International Conference on Intelligent and Advanced Systems (ICIAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAS.2016.7824050","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

This paper discusses the optimal energy management of chiller plant. Two intelligent approaches have been employed. Fuzzy is used to adjust the set-point and, while PSO is utilized to optimize the objective function after setting by Fuzzy. Moreover, Fuzzy is also utilized to adjust weighting factors in order to find the best values for the PSO local and global. This will improve PSO performance. The proposed method was combined two levels as Fuzzified PSO, and the model has been simulated and validated by a real case study which consists of 5 electric-driven chillers. The results have shown that the effectiveness of the proposed method compared to the conventional one, and it also has demonstrated a better power saving.
基于模糊和粒子群算法的冷水机组能量优化管理智能方法
讨论了冷水机组的能量优化管理问题。采用了两种明智的方法。利用模糊对设定点和进行调整,利用粒子群算法对模糊定值后的目标函数进行优化。此外,还利用模糊方法对权重因子进行调整,以寻找局部和全局粒子群的最优值。这将提高粒子群的性能。将所提出的方法结合两层作为模糊粒子群,并通过5台电驱动制冷机的实际算例进行了仿真验证。结果表明,与传统方法相比,所提出的方法是有效的,并且具有更好的节能效果。
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:604180095
Book学术官方微信