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A Survey on Model Predictive Control of DFIGs in Wind Energy Conversion Systems
Yan, Shuo1; Chen, Junyu2; Wang, Minghao3; Yang, Yongheng4; Rodriguez, Jose M.5
2024-05-01
Source PublicationCSEE Journal of Power and Energy Systems
ISSN2096-0042
Volume10Issue:3Pages:1085-1104
Abstract

This paper presents a comprehensive study on the model predictive control (MPC) of doubly fed induction generators (DFIG) in wind energy conversion systems (WECS); in particular the MPC of the rotor side converter. The general principle of prevalent MPC strategies is discussed to introduce the theoretical framework in the first place. Furthermore, mainstream and high-performance MPC methods of DFIGs have been identified as model predictive current control (MPCC), model predictive torque control (MPTC), and model predictive power control (MPPC). Starting from analyzing dynamic models, these MPC strategies are investigated in terms of operating principles and technical developments. The paper further investigates implementation of MPC strategies in unbalanced grids. Based on the quantitative and qualitative analysis of several case studies, performance of various MPC schemes is compared and their special features are identified. Guidelines for designing MPC strategies of DFIGs in WECS are provided.

KeywordDoubly Fed Induction Generator (Dfig) Model Predictive Control (Mpc) Wind Energy
DOI10.17775/CSEEJPES.2022.08500
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEnergy & Fuels ; Engineering
WOS SubjectEnergy & Fuels ; Engineering, Electrical & Electronic
WOS IDWOS:001252836800015
PublisherCHINA ELECTRIC POWER RESEARCH INST15, QINGHE XIAOYING DONG LU, HAIDIAN-QU, BEIJING 100192, PEOPLES R CHINA
Scopus ID2-s2.0-85196673808
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Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
THE STATE KEY LABORATORY OF INTERNET OF THINGS FOR SMART CITY (UNIVERSITY OF MACAU)
Corresponding AuthorWang, Minghao
Affiliation1.STEM College, RMIT University, Melbourne, Australia
2.Hong Kong Polytechnic University, Hong Kong, Hong Kong
3.University of Macau, State Key Laboratory of Internet of Things for Smart City (UM), Department of Electrical and Computer Engineering, Macao
4.College of Electrical Engineering, Zhejiang University, Hangzhou, 310027, China
5.Universidad San Sebastin, Santiago de Chile, 000000, Chile
Corresponding Author AffilicationUniversity of Macau
Recommended Citation
GB/T 7714
Yan, Shuo,Chen, Junyu,Wang, Minghao,et al. A Survey on Model Predictive Control of DFIGs in Wind Energy Conversion Systems[J]. CSEE Journal of Power and Energy Systems, 2024, 10(3), 1085-1104.
APA Yan, Shuo., Chen, Junyu., Wang, Minghao., Yang, Yongheng., & Rodriguez, Jose M. (2024). A Survey on Model Predictive Control of DFIGs in Wind Energy Conversion Systems. CSEE Journal of Power and Energy Systems, 10(3), 1085-1104.
MLA Yan, Shuo,et al."A Survey on Model Predictive Control of DFIGs in Wind Energy Conversion Systems".CSEE Journal of Power and Energy Systems 10.3(2024):1085-1104.
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