Wind‐assisted microgrid grid code compliance employing a hybrid Particle swarm optimization‐Artificial hummingbird algorithm optimizer‐tuned STATCOM

Wind Energy Pub Date : 2024-04-22 DOI:10.1002/we.2908
S. Imtiaz, Lijun Yang, Hafiz Muhammad Azib Khan, Hafiz Mudassir Munir, Mohammed Alharbi, M. Jamil
{"title":"Wind‐assisted microgrid grid code compliance employing a hybrid Particle swarm optimization‐Artificial hummingbird algorithm optimizer‐tuned STATCOM","authors":"S. Imtiaz, Lijun Yang, Hafiz Muhammad Azib Khan, Hafiz Mudassir Munir, Mohammed Alharbi, M. Jamil","doi":"10.1002/we.2908","DOIUrl":null,"url":null,"abstract":"The importance of resolving stability concerns in weak AC grid‐connected doubly fed induction generator (DFIG) wind energy systems during low‐voltage ride‐through (LVRT) events cannot be ignored, given the increasing popularity of wind power‐based microgrids. Furthermore, the emergence of generation loss and postfault oscillation within a microgrid (MG) due to grid faults has also become a significant concern. The static synchronous compensator (STATCOM) under consideration in this study is tuned using particle swarm optimization (PSO), the artificial hummingbird algorithm (AHA), and a hybrid approach incorporating both PSO and AHA. Faults of both a symmetrical and an asymmetrical nature have occurred on the power grid side. The proposed hybrid PSO‐AHA‐tuned STATCOM strategy aims to improve LVRT, minimize power generation loss during faults, and reduce oscillations after a fault by controlling the flow of reactive power between point of common coupling (PCC) and MG. The MATLAB simulation environment was used to simulate the 16 MW MG test system. The performance of the PSO‐AHA‐tuned STATCOM was assessed by comparing results with those from conventional STATCOM, PSO, and AHA optimizer‐tuned STATCOM in four fault situations. A comparison of the results shows that the proposed strategy performed better than other approaches mentioned in this paper and achieved the desired objectives.","PeriodicalId":506912,"journal":{"name":"Wind Energy","volume":"66 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Wind Energy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1002/we.2908","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

The importance of resolving stability concerns in weak AC grid‐connected doubly fed induction generator (DFIG) wind energy systems during low‐voltage ride‐through (LVRT) events cannot be ignored, given the increasing popularity of wind power‐based microgrids. Furthermore, the emergence of generation loss and postfault oscillation within a microgrid (MG) due to grid faults has also become a significant concern. The static synchronous compensator (STATCOM) under consideration in this study is tuned using particle swarm optimization (PSO), the artificial hummingbird algorithm (AHA), and a hybrid approach incorporating both PSO and AHA. Faults of both a symmetrical and an asymmetrical nature have occurred on the power grid side. The proposed hybrid PSO‐AHA‐tuned STATCOM strategy aims to improve LVRT, minimize power generation loss during faults, and reduce oscillations after a fault by controlling the flow of reactive power between point of common coupling (PCC) and MG. The MATLAB simulation environment was used to simulate the 16 MW MG test system. The performance of the PSO‐AHA‐tuned STATCOM was assessed by comparing results with those from conventional STATCOM, PSO, and AHA optimizer‐tuned STATCOM in four fault situations. A comparison of the results shows that the proposed strategy performed better than other approaches mentioned in this paper and achieved the desired objectives.
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
采用粒子群优化-人工蜂鸟算法混合优化器调整 STATCOM 的风力辅助微电网电网规范合规性
随着风力发电微电网的日益普及,在低电压穿越(LVRT)事件中解决弱交流并网双馈异步发电机(DFIG)风能系统稳定性问题的重要性不容忽视。此外,电网故障导致的微电网(MG)内发电损耗和故障后振荡的出现也已成为一个重要问题。本研究中考虑的静态同步补偿器(STATCOM)采用了粒子群优化(PSO)、人工蜂鸟算法(AHA)以及包含 PSO 和 AHA 的混合方法进行调整。电网侧出现了对称性和非对称性故障。所提出的 PSO-AHA 混合调整 STATCOM 策略旨在通过控制公共耦合点 (PCC) 和 MG 之间的无功功率流,改善低电压穿越,最大限度地减少故障期间的发电损失,并降低故障后的振荡。MATLAB 仿真环境用于模拟 16 MW MG 测试系统。通过比较传统 STATCOM、PSO 和 AHA 优化器调整的 STATCOM 在四种故障情况下的结果,评估了 PSO-AHA 调整的 STATCOM 的性能。对比结果表明,建议的策略比本文中提到的其他方法表现更好,达到了预期目标。
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 Study of the Near Wake Deformation of the X‐Rotor Vertical‐Axis Wind Turbine With Pitched Blades Evaluation of Engineering Models for Large‐Scale Cluster Wakes With the Help of In Situ Airborne Measurements A CFD Study on High‐Thrust Corrections for Blade Element Momentum Models Short‐Term Offshore Wind Power Prediction Based on Significant Weather Process Classification and Multitask Learning Considering Neighboring Powers Wind Tunnel Tests of a Thick Wind Turbine Airfoil
×
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