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Volume 16
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10.3390/en16196982
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Article

Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization

by
Xinghua Tao
1,
Nan Mo
2,
Jianbo Qin
1,
Xiaozhe Yang
1,
Linfei Yin
2,* and
Likun Hu
2
1
School of Intelligent Manufacturing, Nanning University, Nanning 530100, China
2
School of Electrical Engineering, Guangxi University, Nanning 530004, China
*
Author to whom correspondence should be addressed.
Energies 2023, 16(19), 6982; https://doi.org/10.3390/en16196982
Submission received: 1 September 2023 / Revised: 2 October 2023 / Accepted: 6 October 2023 / Published: 7 October 2023
(This article belongs to the Section A3: Wind, Wave and Tidal Energy)
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Abstract

This work proposes a parallel multi-layer Monte Carlo optimization algorithm (PMMCOA) that optimizes proportional–integral parameters for a doubly fed induction generator-based wind turbine controller. The PMMCOA, an improved form of the Monte Carlo algorithm, realizes the optimization process via a parallel multi-layer structure. The PMMCOA includes rough search layers, precise search layers, and re-precise search layers. Each layer of the PMMCOA adopts a multi-region and multi-granularity approach to increase the diversity and randomness of the search samples. The PMMCOA is employed to tune the controller parameters for achieving maximum power point tracking and improving generation efficiency. The controller fitness function reflects the sum of the rotor angular velocity error and the reactive power error. Compared with the five metaheuristic algorithms, the PMMCOA has a higher global convergence and more accurate power tracking ability.
Keywords: Monte Carlo algorithm; doubly fed induction generator; maximum power point tracking Monte Carlo algorithm; doubly fed induction generator; maximum power point tracking

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MDPI and ACS Style

Tao, X.; Mo, N.; Qin, J.; Yang, X.; Yin, L.; Hu, L. Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization. Energies 2023, 16, 6982. https://doi.org/10.3390/en16196982

AMA Style

Tao X, Mo N, Qin J, Yang X, Yin L, Hu L. Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization. Energies. 2023; 16(19):6982. https://doi.org/10.3390/en16196982

Chicago/Turabian Style

Tao, Xinghua, Nan Mo, Jianbo Qin, Xiaozhe Yang, Linfei Yin, and Likun Hu. 2023. "Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization" Energies 16, no. 19: 6982. https://doi.org/10.3390/en16196982

APA Style

Tao, X., Mo, N., Qin, J., Yang, X., Yin, L., & Hu, L. (2023). Parallel Multi-Layer Monte Carlo Optimization Algorithm for Doubly Fed Induction Generator Controller Parameters Optimization. Energies, 16(19), 6982. https://doi.org/10.3390/en16196982

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