Benamara, Katia, Amimeur, Hocine, Hamoudi, Yanis et al. (3 more authors) (2024) Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators. Frontiers in Energy Research. 1421336. ISSN 2296-598X
Abstract
This study investigates strategies for enhancing the performance of dual-star induction generators in wind power systems by optimizing the full control algorithm. The control mechanisms involved include the PID (Proportional-Integral-Derivative) controller for speed regulation and the PI (Proportional-Integral) controller for flux, DC-link voltage, and grid connection control. The primary objective is to optimize the entire system by fine-tuning PID and PI controllers through the application of meta-heuristic algorithms, specifically Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO). These algorithms play a crucial role in estimating the optimal values of Kp, Ki, and Kd for the PID speed controller, as well as Kp and Ki for the PI controller used in the flux, DC-link voltage, and grid connection for wind energy conversion system based dual-star induction generator. This comprehensive optimization ensures accurate parameter tuning for optimal system performance. A comparative analysis of the optimization results has been conducted, focusing on the outcomes obtained with the GWO algorithm. The findings reveal a notable reduction in steady-state error, signifying improved stability, and an overall enhancement in the wind power system’s performance. This study contributes valuable insights into the effective application of meta-heuristic algorithms for optimizing dual-star induction generators in wind power systems.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 Benamara, Amimeur, Hamoudi, Abdolrasol, Cali and Ustun. |
Keywords: | dual star induction generator,field oriented control,grey wolf optimization,particle swarm optimization,wind energy |
Dates: |
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Institution: | The University of York |
Academic Units: | The University of York > Faculty of Sciences (York) > Electronic Engineering (York) |
Depositing User: | Pure (York) |
Date Deposited: | 21 Jan 2025 18:17 |
Last Modified: | 21 Jan 2025 18:17 |
Published Version: | https://doi.org/10.3389/fenrg.2024.1421336 |
Status: | Published |
Refereed: | Yes |
Identification Number: | 10.3389/fenrg.2024.1421336 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:222116 |
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Filename: fenrg-12-1421336.pdf
Description: Grey wolf optimization for enhanced performance in wind power system with dual-star induction generators
Licence: CC-BY 2.5