TLBO算法对分布式发电布局的新改进

Seyed Iman Taheri, M. Salles
{"title":"TLBO算法对分布式发电布局的新改进","authors":"Seyed Iman Taheri, M. Salles","doi":"10.1109/ICCEP.2019.8890101","DOIUrl":null,"url":null,"abstract":"Placement of Distributed Generators (DGs) can improve power quality characteristics of the distribution system. This paper presents a multi-objective modified-teaching-learning-based-optimization (MOTLBO) algorithm to the placement of DGs in a distribution system. Three objective functions are considered which are optimization of voltage profile and minimization of losses and cost of the distribution system. Two kinds of DGs which are photovoltaic units and fuel cell units are considered in this paper because they represent an established technology (photovoltaic) and a promising one (fuel cell). The original teaching-learning-based-optimization (TLBO) algorithm is modified in teaching and learning phases for improving the accuracy and convergence velocity of TLBO. The suggested algorithm is executed on a 70-bus-radial-distribution-system in comparison with other evolutionary methods. The superiority of the proposed algorithm is its accuracy and calculation velocity.","PeriodicalId":277718,"journal":{"name":"2019 International Conference on Clean Electrical Power (ICCEP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"A New Modification for TLBO Algorithm to Placement of Distributed Generation\",\"authors\":\"Seyed Iman Taheri, M. Salles\",\"doi\":\"10.1109/ICCEP.2019.8890101\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Placement of Distributed Generators (DGs) can improve power quality characteristics of the distribution system. This paper presents a multi-objective modified-teaching-learning-based-optimization (MOTLBO) algorithm to the placement of DGs in a distribution system. Three objective functions are considered which are optimization of voltage profile and minimization of losses and cost of the distribution system. Two kinds of DGs which are photovoltaic units and fuel cell units are considered in this paper because they represent an established technology (photovoltaic) and a promising one (fuel cell). The original teaching-learning-based-optimization (TLBO) algorithm is modified in teaching and learning phases for improving the accuracy and convergence velocity of TLBO. The suggested algorithm is executed on a 70-bus-radial-distribution-system in comparison with other evolutionary methods. The superiority of the proposed algorithm is its accuracy and calculation velocity.\",\"PeriodicalId\":277718,\"journal\":{\"name\":\"2019 International Conference on Clean Electrical Power (ICCEP)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Clean Electrical Power (ICCEP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCEP.2019.8890101\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Clean Electrical Power (ICCEP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCEP.2019.8890101","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

分布式发电机的配置可以改善配电系统的电能质量特性。提出了一种多目标修正教-学优化(MOTLBO)算法来求解配电系统中配电设备的配置问题。考虑了配电系统电压分布的优化、损耗和成本的最小化三个目标函数。本文考虑了光伏发电机组和燃料电池机组两种分布式发电机组,因为它们代表了一种成熟的技术(光伏)和一种有前途的技术(燃料电池)。为了提高TLBO算法的精度和收敛速度,在教学阶段和学习阶段对原有的基于教学的优化算法进行了改进。该算法在一个70总线的径向分布系统上运行,并与其他进化方法进行了比较。该算法的优点在于精度高、计算速度快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Modification for TLBO Algorithm to Placement of Distributed Generation
Placement of Distributed Generators (DGs) can improve power quality characteristics of the distribution system. This paper presents a multi-objective modified-teaching-learning-based-optimization (MOTLBO) algorithm to the placement of DGs in a distribution system. Three objective functions are considered which are optimization of voltage profile and minimization of losses and cost of the distribution system. Two kinds of DGs which are photovoltaic units and fuel cell units are considered in this paper because they represent an established technology (photovoltaic) and a promising one (fuel cell). The original teaching-learning-based-optimization (TLBO) algorithm is modified in teaching and learning phases for improving the accuracy and convergence velocity of TLBO. The suggested algorithm is executed on a 70-bus-radial-distribution-system in comparison with other evolutionary methods. The superiority of the proposed algorithm is its accuracy and calculation velocity.
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