LAPSE:2023.16925
Published Article
LAPSE:2023.16925
Efficiency Enhancement of Switched Reluctance Generator Employing Optimized Control Associated with Tracking Technique
March 3, 2023
Abstract
This article presents studies related to the driving and control of the switched reluctance generator in order to enhance its efficiency. This type of electrical machine is an option for wind energy conversion systems, favoring the generation of electricity in distributed generation systems and contributing positively to loads without access to the main grid. The studies developed in this paper verify the possibility of controlling the output voltage of the switched reluctance generator in parallel with an efficiency tracking technique acting on the switching angles of the power converter. Simulation and experimental results are presented in order to verify the feasibility of implementing this technique to enhance the efficiency of the generator.
This article presents studies related to the driving and control of the switched reluctance generator in order to enhance its efficiency. This type of electrical machine is an option for wind energy conversion systems, favoring the generation of electricity in distributed generation systems and contributing positively to loads without access to the main grid. The studies developed in this paper verify the possibility of controlling the output voltage of the switched reluctance generator in parallel with an efficiency tracking technique acting on the switching angles of the power converter. Simulation and experimental results are presented in order to verify the feasibility of implementing this technique to enhance the efficiency of the generator.
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Keywords
efficiency, Optimization, optimized control, switched reluctance generator, tracking technique, wind energy conversion system
Subject
Suggested Citation
Araujo WRH, Reis MRC, Wainer GA, Calixto WP. Efficiency Enhancement of Switched Reluctance Generator Employing Optimized Control Associated with Tracking Technique. (2023). LAPSE:2023.16925
Author Affiliations
Araujo WRH: Systems Research and Development Group and Computational Modeling (GSiM), Federal Institute of Goias, Goiania 75250-000, Brazil; Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74690-900, Brazil; Polytechnic Scho [ORCID]
Reis MRC: Systems Research and Development Group and Computational Modeling (GSiM), Federal Institute of Goias, Goiania 75250-000, Brazil; Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74690-900, Brazil [ORCID]
Wainer GA: Visualization, Simulation and Modeling, Carleton University, Ottawa, ON 1125, Canada [ORCID]
Calixto WP: Systems Research and Development Group and Computational Modeling (GSiM), Federal Institute of Goias, Goiania 75250-000, Brazil; Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74690-900, Brazil [ORCID]
Reis MRC: Systems Research and Development Group and Computational Modeling (GSiM), Federal Institute of Goias, Goiania 75250-000, Brazil; Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74690-900, Brazil [ORCID]
Wainer GA: Visualization, Simulation and Modeling, Carleton University, Ottawa, ON 1125, Canada [ORCID]
Calixto WP: Systems Research and Development Group and Computational Modeling (GSiM), Federal Institute of Goias, Goiania 75250-000, Brazil; Electrical, Mechanical & Computer Engineering School, Federal University of Goias, Goiania 74690-900, Brazil [ORCID]
Journal Name
Energies
Volume
14
Issue
24
First Page
8388
Year
2021
Publication Date
2021-12-13
ISSN
1996-1073
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Original Submission
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PII: en14248388, Publication Type: Journal Article
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Published Article
LAPSE:2023.16925
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https://doi.org/10.3390/en14248388
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[v1] (Original Submission)
Mar 3, 2023
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Mar 3, 2023
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