Distributed Generation Allocation in Low Voltage Distribution Network Using Artificial Neural Network

Edin Semic, Tarik Hubana, M. Saric
{"title":"Distributed Generation Allocation in Low Voltage Distribution Network Using Artificial Neural Network","authors":"Edin Semic, Tarik Hubana, M. Saric","doi":"10.1109/EUROCON.2019.8861816","DOIUrl":null,"url":null,"abstract":"This paper presents a method for distributed generation (DG) allocation in low voltage distribution network based on the total annual energy loss reduction and Artificial Neural Network (ANN). The proposed method is applied to the PV solar based DG allocation problem in the low voltage distribution network using realistic network data and measurements. This research is motivated by numerous realistic issues faced by the Distribution System Operator in the area of DG planning. The main objective of this work is to develop, test and validate a robust method for DG allocation which can be used in practical problems without the need for extensive system modelling and load flow analysis. The results confirm the importance of appropriate DG planning and show that the proposed method can be used as a promising tool for efficient and effective DG allocation in low voltage distribution network.","PeriodicalId":232097,"journal":{"name":"IEEE EUROCON 2019 -18th International Conference on Smart Technologies","volume":"24 3-4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE EUROCON 2019 -18th International Conference on Smart Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EUROCON.2019.8861816","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4

Abstract

This paper presents a method for distributed generation (DG) allocation in low voltage distribution network based on the total annual energy loss reduction and Artificial Neural Network (ANN). The proposed method is applied to the PV solar based DG allocation problem in the low voltage distribution network using realistic network data and measurements. This research is motivated by numerous realistic issues faced by the Distribution System Operator in the area of DG planning. The main objective of this work is to develop, test and validate a robust method for DG allocation which can be used in practical problems without the need for extensive system modelling and load flow analysis. The results confirm the importance of appropriate DG planning and show that the proposed method can be used as a promising tool for efficient and effective DG allocation in low voltage distribution network.
基于人工神经网络的低压配电网分布式发电分配
提出了一种基于年总能量损耗减少和人工神经网络的低压配电网分布式发电分配方法。利用实际电网数据和实测数据,将该方法应用于基于光伏太阳能的低压配电网DG分配问题。本研究的动机是许多现实问题面临的配电系统运营商在DG规划领域。这项工作的主要目标是开发、测试和验证一种可靠的DG分配方法,该方法可以在实际问题中使用,而无需进行广泛的系统建模和负荷流分析。结果证实了合理的DG规划的重要性,并表明该方法可以作为低压配电网中高效分配DG的一种有前途的工具。
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:481959085
Book学术官方微信