Innovative PID-GA MPPT Controller for Extraction of Maximum Power From Variable Wind Turbine

Azzouz, Said; Messalti, Sabir; Harrag, Abdelghani

doi:10.15199/48.2019.08.26

Cited by 7 publications

(2 citation statements)

References 12 publications

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“…In fact, wind energy system has high nonlinearity obtained from uncertainties, wind speed turbulence, and the changes in wind system parameters (Krim et al 2018). For this reason, nonlinear controls have been developed to be not very sensitive to wind speed and parameters variation, such as sliding mode controller Benattous, 2011, 2012;Azzouz et al 2019;Bouguerra and Benfdila, 2023), fuzzy logic controller (Belaimeche et al, 2018;Cheikh et al, 2013;Djoudi et al, 2021), Artificial Neural Networks (Benbouhenni, 2020), fuzzy sliding mode control (Benmeziane et al, 2019), H ∞ Controller (Saihi et al, 2020), etc.…”

Section: Introductionmentioning

confidence: 99%

Comparative study between PI, FLC, SMC and Fuzzy sliding mode controllers of DFIG wind turbine

Bouguerra

2023

J. Ren. Energies

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In speed control, double-fed-induction generator (DFIG) has attracted attention in wind energy conversion systems (WECs). These systems can offer higher performances by controlling converters that connect the generator windings to the grid network. Therefore, different control strategies have been used. We can find the proportional integral (PI) and sliding mode control (SMC) which offer better performances. However, PI has constant gains that can’t change with the external variation and SMC has a chattering problem. Therefore, a hybrid control system that combines fuzzy logic control (FLC) and SMC to perform fuzzy sliding mode control (FSMC) is proposed. The hybrid system can improve the FLC and SMC robustness. The DFIG modeling and each of the control strategies have been detailed. To demonstrate the effectiveness of the control strategies, a comparative study of different control strategies (PI, FLC, SMC and FSMC) is described and performed using MATLAB/Simulink software. The results obtained from the present study show that FSMC is more robust and efficient than the other controllers (PI, FLC and SMC). It has high performances (low settling time, high steady state accuracy) assuring a perfect power decoupling with minimal ripples and errors.

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Section: Introductionmentioning

confidence: 99%

Comparative study between PI, FLC, SMC and Fuzzy sliding mode controllers of DFIG wind turbine

Bouguerra

2023

J. Ren. Energies

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“…The authors in (Hadji et al, 2018) also apply a GA algorithm for tuning a PID controller for an MPPT in a wind turbine. The authors in (Azzouz et al, 2019) use a GA algorithm to tune a PID controller for an MPPT in a wind turbine, comparing their proposal against the sliding mode controller. Their results show that the PID controller optimized by GA has a better response than the sliding mode controller, with a faster response.…”

Section: Solar Photovoltaicmentioning

confidence: 99%

Modelo y desarrollo de un sistema de gestión óptima para una microrred empleando algoritmos bio-inspirados

Águila León

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Quiero expresar mi profundo agradecimiento a mis directores de tesis Carlos Vargas y Elías Hurtado por todo el apoyo y la guía que me han brindado durante el proceso de mi tesis doctoral en la Universidad Politécnica de Valencia. Desde el primer día, ambos han demostrado un gran interés en mi trabajo y han estado dispuestos a dedicar su tiempo y esfuerzo para ayudarme a mejorar mis habilidades y conocimientos.En especial, quiero darle las gracias al Dr. Carlos Vargas por su amistad, paciencia y colaboración durante estos últimos siete años. Sus consejos y sugerencias han sido fundamentales para el éxito de mi tesis y no puedo agradecerle lo suficiente por su constante apoyo.

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Neural Network MPPT Control of an On-Grid Wind Energy System

Dahmane,

Boulaoutaq,

Bouachrine

et al. 2024

Proceedings of Ninth International Congress on Information and Communication Technology

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Innovative PID-GA MPPT Controller for Extraction of Maximum Power From Variable Wind Turbine

Cited by 7 publications

References 12 publications

Comparative study between PI, FLC, SMC and Fuzzy sliding mode controllers of DFIG wind turbine

Comparative study between PI, FLC, SMC and Fuzzy sliding mode controllers of DFIG wind turbine

Modelo y desarrollo de un sistema de gestión óptima para una microrred empleando algoritmos bio-inspirados

Neural Network MPPT Control of an On-Grid Wind Energy System

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