Enhancing power quality in grid-connected hybrid renewable energy systems using UPQC and optimized O-FOPID

IF 2.6 4区 工程技术 Q3 ENERGY & FUELS Frontiers in Energy Research Pub Date : 2024-07-30 DOI:10.3389/fenrg.2024.1425412
R. Venkatesan, C. Kumar, C. R. Balamurugan, Tomonobu Senjyu
{"title":"Enhancing power quality in grid-connected hybrid renewable energy systems using UPQC and optimized O-FOPID","authors":"R. Venkatesan, C. Kumar, C. R. Balamurugan, Tomonobu Senjyu","doi":"10.3389/fenrg.2024.1425412","DOIUrl":null,"url":null,"abstract":"Hybrid Renewable Energy Systems (HRES) have recently been proposed as a way to improve dependability and reduce losses in grid-connected load systems. This research study suggests a novel hybrid optimization technique that regulates UPQC in order to address the Power Quality (PQ) problems in the HRES system. The load system serves as the primary link between the battery energy storage systems (BESS), wind turbine (WT), and solar photovoltaic (PV) components of the HRES system. The major objective of the study is to reduce PQ issues and make up for the load requirement inside the HRES system. The addition of an Optimized Fractional Order Proportional Integral Derivative (O-FOPID) controller improves the efficiency of the UPQC. The Crow-Tunicate Swarm Optimization Algorithm (CT-SOA), an enhanced variant of the traditional Tunicate Swarm Optimization (TSA) and Crow Search Optimization (CSO), is used to optimize the control parameters of the FOPID controller. Utilizing the MATLAB/Simulink platform, the proposed method is put into practice, and the system’s performance is assessed for sag, swell, and Total Harmonic Distortion (THD). The THD values for the PI, FOPID, and CSA techniques, respectively, are 5.9038%, 4.9592%, and 3.7027%, under the sag condition. This validates the superiority of the proposed approach over existing approaches.","PeriodicalId":12428,"journal":{"name":"Frontiers in Energy Research","volume":"96 1","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Energy Research","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3389/fenrg.2024.1425412","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0

Abstract

Hybrid Renewable Energy Systems (HRES) have recently been proposed as a way to improve dependability and reduce losses in grid-connected load systems. This research study suggests a novel hybrid optimization technique that regulates UPQC in order to address the Power Quality (PQ) problems in the HRES system. The load system serves as the primary link between the battery energy storage systems (BESS), wind turbine (WT), and solar photovoltaic (PV) components of the HRES system. The major objective of the study is to reduce PQ issues and make up for the load requirement inside the HRES system. The addition of an Optimized Fractional Order Proportional Integral Derivative (O-FOPID) controller improves the efficiency of the UPQC. The Crow-Tunicate Swarm Optimization Algorithm (CT-SOA), an enhanced variant of the traditional Tunicate Swarm Optimization (TSA) and Crow Search Optimization (CSO), is used to optimize the control parameters of the FOPID controller. Utilizing the MATLAB/Simulink platform, the proposed method is put into practice, and the system’s performance is assessed for sag, swell, and Total Harmonic Distortion (THD). The THD values for the PI, FOPID, and CSA techniques, respectively, are 5.9038%, 4.9592%, and 3.7027%, under the sag condition. This validates the superiority of the proposed approach over existing approaches.
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
利用 UPQC 和优化的 O-FOPID 提高并网混合可再生能源系统的电能质量
混合可再生能源系统(HRES)是最近提出的一种提高并网负载系统可靠性和降低损耗的方法。本研究提出了一种新型混合优化技术,通过调节 UPQC 来解决 HRES 系统中的电能质量(PQ)问题。负载系统是 HRES 系统中电池储能系统 (BESS)、风力涡轮机 (WT) 和太阳能光伏 (PV) 组件之间的主要联系。研究的主要目的是减少 PQ 问题,弥补 HRES 系统内部的负载需求。添加优化分数阶比例积分微分(O-FOPID)控制器可提高 UPQC 的效率。乌鸦-调谐群优化算法(CT-SOA)是传统调谐群优化(TSA)和乌鸦搜索优化(CSO)的增强型变体,用于优化 FOPID 控制器的控制参数。利用 MATLAB/Simulink 平台,将所提出的方法付诸实践,并评估了系统的下垂、膨胀和总谐波失真 (THD) 性能。在下陷条件下,PI、FOPID 和 CSA 技术的 THD 值分别为 5.9038%、4.9592% 和 3.7027%。这验证了拟议方法优于现有方法。
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
Frontiers in Energy Research
Frontiers in Energy Research Economics, Econometrics and Finance-Economics and Econometrics
CiteScore
3.90
自引率
11.80%
发文量
1727
审稿时长
12 weeks
期刊介绍: Frontiers in Energy Research makes use of the unique Frontiers platform for open-access publishing and research networking for scientists, which provides an equal opportunity to seek, share and create knowledge. The mission of Frontiers is to place publishing back in the hands of working scientists and to promote an interactive, fair, and efficient review process. Articles are peer-reviewed according to the Frontiers review guidelines, which evaluate manuscripts on objective editorial criteria
期刊最新文献
Grid-integrated solutions for sustainable EV charging: a comparative study of renewable energy and battery storage systems Research on the impact of digitalization on energy companies’ green transition: new insights from China Multi-objective-based economic and emission dispatch with integration of wind energy sources using different optimization algorithms Demand-side management scenario analysis for the energy-efficient future of Pakistan: Bridging the gap between market interests and national priorities Modeling and scheduling of utility-scale energy storage toward high-share renewable coordination
×
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