LAPSE:2023.13134
Published Article

LAPSE:2023.13134
Improving the Maximum Power Extraction from Wind Turbines Using a Second-Generation CRONE Controller
February 28, 2023
Abstract
Developing precise and robust algorithms that can help in obtaining maximum power yield in a variable speed wind turbine is an important area of research in wind engineering. The present manuscript proposes a technique that utilizes a second-generation CRONE controller for the maximum power tracking technique (MPPT) to maximize power generation in a wind energy conversion system (WECS) based on a double-fed induction generator (DFIG). The authors propose this novel method because the classical controllers cannot provide adequate performance in terms of extracting the maximum energy from variable speed wind turbines when applying a real wind profile and they cannot guarantee the high stability of the WECS. Moreover, this novel controller sufficiently handles problems related to the control effort level. The performance of the second-generation CRONE method was mathematically modeled using MATLAB/Simulink and compared with four other types of MPPT control techniques, which include a proportional-integral linear controller (PI), nonlinear sliding mode controller (SMC), backstepping controller (BS), and fuzzy logic controller (FLC). Two different wind profiles, a step wind profile and a real wind profile, were considered for the comparative study. The response time, dynamic error percentage, and static error percentage were the quantitative parameters compared, and the qualitative parameters included set-point tracking and precision. This test demonstrated the superiority of the second-generation CRONE controller in terms of all of the compared parameters.
Developing precise and robust algorithms that can help in obtaining maximum power yield in a variable speed wind turbine is an important area of research in wind engineering. The present manuscript proposes a technique that utilizes a second-generation CRONE controller for the maximum power tracking technique (MPPT) to maximize power generation in a wind energy conversion system (WECS) based on a double-fed induction generator (DFIG). The authors propose this novel method because the classical controllers cannot provide adequate performance in terms of extracting the maximum energy from variable speed wind turbines when applying a real wind profile and they cannot guarantee the high stability of the WECS. Moreover, this novel controller sufficiently handles problems related to the control effort level. The performance of the second-generation CRONE method was mathematically modeled using MATLAB/Simulink and compared with four other types of MPPT control techniques, which include a proportional-integral linear controller (PI), nonlinear sliding mode controller (SMC), backstepping controller (BS), and fuzzy logic controller (FLC). Two different wind profiles, a step wind profile and a real wind profile, were considered for the comparative study. The response time, dynamic error percentage, and static error percentage were the quantitative parameters compared, and the qualitative parameters included set-point tracking and precision. This test demonstrated the superiority of the second-generation CRONE controller in terms of all of the compared parameters.
Record ID
Keywords
backstepping controller (BS), DFIG, fuzzy logic controller (FLC), MPPT, second-generation CRONE controller, sliding mode controller (SMC), WECS
Subject
Suggested Citation
Yessef M, Bossoufi B, Taoussi M, Motahhir S, Lagrioui A, Chojaa H, Lee S, Kang BG, Abouhawwash M. Improving the Maximum Power Extraction from Wind Turbines Using a Second-Generation CRONE Controller. (2023). LAPSE:2023.13134
Author Affiliations
Yessef M: Laboratory of Engineering, Modeling and Systems Analysis, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco [ORCID]
Bossoufi B: Laboratory of Engineering, Modeling and Systems Analysis, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco [ORCID]
Taoussi M: Laboratory of Technologies and Industrial Services, Higher School of Technology, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco
Motahhir S: Engineering, Systems, and Applications Laboratory, ENSA, SMBA University, Fez 30000, Morocco [ORCID]
Lagrioui A: Department of Electrical and Computer Engineering, Higher National School of Arts and Trades, Moulay Ismail University, Meknes 50050, Morocco
Chojaa H: Laboratory of Technologies and Industrial Services, Higher School of Technology, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco [ORCID]
Lee S: Department of ICT Convergence, Soonchunhyang University, Asan 31538, Korea
Kang BG: Department of ICT Convergence, Soonchunhyang University, Asan 31538, Korea
Abouhawwash M: Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt; Department of Computational Mathematics, Science, and Engineering (CMSE), College of Engineering, Michigan State University, East Lansing, MI 48824, USA [ORCID]
Bossoufi B: Laboratory of Engineering, Modeling and Systems Analysis, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco [ORCID]
Taoussi M: Laboratory of Technologies and Industrial Services, Higher School of Technology, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco
Motahhir S: Engineering, Systems, and Applications Laboratory, ENSA, SMBA University, Fez 30000, Morocco [ORCID]
Lagrioui A: Department of Electrical and Computer Engineering, Higher National School of Arts and Trades, Moulay Ismail University, Meknes 50050, Morocco
Chojaa H: Laboratory of Technologies and Industrial Services, Higher School of Technology, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco [ORCID]
Lee S: Department of ICT Convergence, Soonchunhyang University, Asan 31538, Korea
Kang BG: Department of ICT Convergence, Soonchunhyang University, Asan 31538, Korea
Abouhawwash M: Department of Mathematics, Faculty of Science, Mansoura University, Mansoura 35516, Egypt; Department of Computational Mathematics, Science, and Engineering (CMSE), College of Engineering, Michigan State University, East Lansing, MI 48824, USA [ORCID]
Journal Name
Energies
Volume
15
Issue
10
First Page
3644
Year
2022
Publication Date
2022-05-16
ISSN
1996-1073
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Original Submission
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PII: en15103644, Publication Type: Journal Article
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LAPSE:2023.13134
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