STATOR ACTIVE AND REACTIVE POWER RIPPLES MINIMIZATION FOR DVC CONTROL OF DFIG BY USING FIVE-LEVEL NEURAL SPACE VECTOR MODULATION

H. Benbouhenni, Oran Algeria Ecole Nationale Polytechnique d’Oran Maurice Audin
{"title":"STATOR ACTIVE AND REACTIVE POWER RIPPLES MINIMIZATION FOR DVC CONTROL OF DFIG BY USING FIVE-LEVEL NEURAL SPACE VECTOR MODULATION","authors":"H. Benbouhenni, Oran Algeria Ecole Nationale Polytechnique d’Oran Maurice Audin","doi":"10.15546/AEEI-2019-0010","DOIUrl":null,"url":null,"abstract":"ABSTRACT This paper presents a direct vector control (DVC) strategy for the doubly fed induction generator (DFIG)based wind turbine systems. The major disadvantages that are usually associated with DVC control scheme are the electromagnetic torque, reactive power and active power ripples. To overcome these disadvantages an advanced five-level space vector modulation (5L-SVM) strategy based on neural networks (NNs) controller is proposed. The proposed controller is shown to be able to reduce the reactive and active powers ripples and to improve the performances of the DVC control. Simulation results are shown by using Matlab/Simulink.","PeriodicalId":31657,"journal":{"name":"Acta Electrotechnica et Informatica","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Electrotechnica et Informatica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15546/AEEI-2019-0010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

ABSTRACT This paper presents a direct vector control (DVC) strategy for the doubly fed induction generator (DFIG)based wind turbine systems. The major disadvantages that are usually associated with DVC control scheme are the electromagnetic torque, reactive power and active power ripples. To overcome these disadvantages an advanced five-level space vector modulation (5L-SVM) strategy based on neural networks (NNs) controller is proposed. The proposed controller is shown to be able to reduce the reactive and active powers ripples and to improve the performances of the DVC control. Simulation results are shown by using Matlab/Simulink.
基于五级神经空间矢量调制的dfig定子有功和无功波纹最小化控制
针对双馈感应发电机(DFIG)风力发电系统,提出了一种直接矢量控制(DVC)策略。通常与DVC控制方案相关的主要缺点是电磁转矩、无功功率和有功功率波动。为了克服这些缺点,提出了一种基于神经网络控制器的五能级空间矢量调制(5L-SVM)策略。实验结果表明,所提出的控制器能够有效地减小无功和有功功率波动,提高DVC控制的性能。利用Matlab/Simulink给出了仿真结果。
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
审稿时长
8 weeks
×
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:604180095
Book学术官方微信
小红书