Coordinated optimization model for solar PV systems integrated into DC distribution networks

Eleonora Achiluzzi, B. Venkatesh
{"title":"Coordinated optimization model for solar PV systems integrated into DC distribution networks","authors":"Eleonora Achiluzzi, B. Venkatesh","doi":"10.1049/tje2.12295","DOIUrl":null,"url":null,"abstract":"Solar photovoltaic (PV) systems will drive deep electrification of energy systems leading to clean energy 2050. However, connecting large amounts of solar PV systems on direct current (DC) networks, like solar farms and potential future DC distribution systems, would lead to over voltages and loss of solar PV power output due to voltage issues. Further, current PV integration within distribution networks operate exclusively to maximize output using maximum power point tracking algorithms, without network coordination, which may lead to reduced solar output due to voltage issues. Here, a coordinated optimization model for solar PV systems and distribution network voltage regulators is presented. The proposed model optimally controls the settings of voltage controllers (DC‐DC converters), placed at the outputs of solar PV units and selected distribution lines, while maximizing solar power output and minimizing substation power (i.e. system losses). The solar PV systems are modelled using a trained neural network. Testing various systems against uncoordinated situations revealed that the proposed model yielded an increase in solar power of up to 60.06%, in the 28‐bus case. The proposed method will be an excellent tool enabling deep electrification using solar PV system and it overcomes limitations of uncoordinated systems used in practice today.","PeriodicalId":22858,"journal":{"name":"The Journal of Engineering","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/tje2.12295","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Solar photovoltaic (PV) systems will drive deep electrification of energy systems leading to clean energy 2050. However, connecting large amounts of solar PV systems on direct current (DC) networks, like solar farms and potential future DC distribution systems, would lead to over voltages and loss of solar PV power output due to voltage issues. Further, current PV integration within distribution networks operate exclusively to maximize output using maximum power point tracking algorithms, without network coordination, which may lead to reduced solar output due to voltage issues. Here, a coordinated optimization model for solar PV systems and distribution network voltage regulators is presented. The proposed model optimally controls the settings of voltage controllers (DC‐DC converters), placed at the outputs of solar PV units and selected distribution lines, while maximizing solar power output and minimizing substation power (i.e. system losses). The solar PV systems are modelled using a trained neural network. Testing various systems against uncoordinated situations revealed that the proposed model yielded an increase in solar power of up to 60.06%, in the 28‐bus case. The proposed method will be an excellent tool enabling deep electrification using solar PV system and it overcomes limitations of uncoordinated systems used in practice today.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
太阳能光伏系统与直流配电网的协调优化模型
太阳能光伏(PV)系统将推动能源系统的深度电气化,从而实现2050年的清洁能源。然而,将大量太阳能光伏系统连接到直流电(DC)网络上,如太阳能发电场和潜在的未来直流配电系统,将导致电压问题导致过电压和太阳能光伏发电输出的损失。此外,目前配电网内的光伏集成仅使用最大功率点跟踪算法来最大化输出,而没有网络协调,这可能导致由于电压问题而导致太阳能输出减少。本文提出了太阳能光伏系统与配电网调压器的协调优化模型。所提出的模型对电压控制器(DC - DC转换器)的设置进行了最佳控制,该控制器放置在太阳能光伏发电单元和选定的配电线路的输出端,同时最大化太阳能输出并最小化变电站功率(即系统损耗)。太阳能光伏系统使用训练好的神经网络建模。对各种系统在不协调情况下的测试表明,在28总线的情况下,所提出的模型产生了高达60.06%的太阳能增加。所提出的方法将是利用太阳能光伏系统实现深度电气化的一个很好的工具,它克服了目前实践中使用的不协调系统的局限性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
A novel jittered‐carrier phase‐shifted sine pulse width modulation for cascaded H‐bridge converter An improved hybrid network‐on‐chip with flexible topology and frugal routing Magnetic sensors for contactless and non‐intrusive measurement of current in AC power systems Regulation of mixed convective flow in a horizontal channel with multiple slots using P, PI, and PID controllers BrutNet: A novel approach for violence detection and classification using DCNN with GRU
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1