LAPSE:2023.9112
Published Article

LAPSE:2023.9112
Fuzzy Control Strategy Applied to an Electromagnetic Frequency Regulator in Wind Generation Systems
February 27, 2023
Abstract
This paper presents the implementation of a fuzzy control strategy for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in wind power generation. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate, and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial, and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It considers the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which have several limitations that are widely discussed in the literature. This strategy also limits the EFR’s performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.
This paper presents the implementation of a fuzzy control strategy for speed regulation of an electromagnetic frequency regulator (EFR) prototype, aiming to eliminate the dependence on knowledge of physical parameters in the most diverse operating conditions. Speed multiplication is one of the most important steps in wind power generation. Gearboxes are generally used for this purpose. However, they have a reduced lifespan and a high failure rate, and are still noise sources. The search for new ways to match the speed (and torque) between the turbine and the generator is an important research area to increase the energy, financial, and environmental efficiency of wind systems. The EFR device is an example of an alternative technology that this team of researchers has proposed. It considers the main advantages of an induction machine with the rotor in a squirrel cage positively. In the first studies, the EFR control strategy consisted of the conventional PID controllers, which have several limitations that are widely discussed in the literature. This strategy also limits the EFR’s performance, considering its entire operating range. The simulation program was developed using the Matlab/Simulink platform, while the experimental results were obtained in the laboratory emulating the EFR-based system. The EFR prototype has 2 poles, a nominal power of 2.2 kW, and a nominal frequency of 60 Hz. Experimental results were presented to validate the efficiency of the proposed control strategy.
Record ID
Keywords
electromagnetic frequency regulator, fuzzy controller, photovoltaics, speed control, wind energy
Subject
Suggested Citation
Crisóstomo DCC, do Nascimento TF, Nunes EADF, Villarreal E, Pinheiro R, Salazar A. Fuzzy Control Strategy Applied to an Electromagnetic Frequency Regulator in Wind Generation Systems. (2023). LAPSE:2023.9112
Author Affiliations
Crisóstomo DCC: Department of Sciences and Technology, Federal Rural University of Semi-Arid (DCT-UFERSA), Caraúbas 59780-000, Brazil [ORCID]
do Nascimento TF: Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte (DCA-UFRN), Natal 59072-970, Brazil [ORCID]
Nunes EADF: The Federal Institute of Education, Science and Technology of Bahia (IFBA), Salvador 40301-015, Brazil [ORCID]
Villarreal E: Department of Natural Sciences, Mathematics and Statistics, Federal Rural University of Semi-Arid (DCME-UFERSA), Mossoró 59625-900, Brazil [ORCID]
Pinheiro R: Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte (DCA-UFRN), Natal 59072-970, Brazil [ORCID]
Salazar A: Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte (DCA-UFRN), Natal 59072-970, Brazil [ORCID]
do Nascimento TF: Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte (DCA-UFRN), Natal 59072-970, Brazil [ORCID]
Nunes EADF: The Federal Institute of Education, Science and Technology of Bahia (IFBA), Salvador 40301-015, Brazil [ORCID]
Villarreal E: Department of Natural Sciences, Mathematics and Statistics, Federal Rural University of Semi-Arid (DCME-UFERSA), Mossoró 59625-900, Brazil [ORCID]
Pinheiro R: Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte (DCA-UFRN), Natal 59072-970, Brazil [ORCID]
Salazar A: Department of Computer Engineering and Automation, Federal University of Rio Grande do Norte (DCA-UFRN), Natal 59072-970, Brazil [ORCID]
Journal Name
Energies
Volume
15
Issue
19
First Page
7011
Year
2022
Publication Date
2022-09-24
ISSN
1996-1073
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Original Submission
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PII: en15197011, Publication Type: Journal Article
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LAPSE:2023.9112
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https://doi.org/10.3390/en15197011
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