Enhanced power quality in grid-connected wind energy systems using PI-controlled with doubly fed induction generator optimized by hybrid differential evolution and grey wolf algorithm

Introduction. Nowadays, the most widely used wind energy conversion system in wind farms is based on a doubly fed induction generator (DFIG); it has a large speed range and can function in multiple modes. Problem. Harmonic distortion in wind energy conversion system can degrade output waveform quality, reduce power conversion efficiency. Goal. This study investigates the dynamic performance of a wind energy conversion system comprising a grid-connected load, a 13-level hybrid multilevel converter and a doubly fed induction generator (DFIG), using a PI controller. The study aims to evaluate the dynamic performance and power quality of wind energy conversion systems, and to develop a novel hybrid metaheuristic method combining differential evolution (DE) and grey wolf optimization (GWO)-based selective harmonic elimination pulse-width modulation (SHEPWM) control strategies. This method reduces total harmonic distortion (THD) and ensures compliance with IEEE 519 standards, while increasing the power transferred to the grid. Methodology. The system, which includes a grid-connected load, a 13-level converter, and a DFIG, is modeled and simulated in MATLAB/Simulink under steady-state wind conditions. Vector control via stator flow orientation was used to modify the energy quality provided by the DFIG, making the system comparable to the DC machine. Our approach was to use a PI controller in order to directly control the active and reactive DFIG power through multi-level converter then a hybrid metaheuristic algorithm combining DE and GWO is implemented to solve the SHEPWM nonlinear transcendental equations. The proposed algorithm is evaluated based on its ability to suppress lower-order harmonics and improve THD performance, these converters increase the power transmitted to the power grid by reducing harmonic content of the output voltages. Results. By using the DE-GWO hybrid method and a PI controller, lower-order harmonics were effectively removed and THD was reduced to meet IEEE 519 standards. Simulations showed an improvement in output wave quality and better energy conversion efficiency compared to conventional optimization methods. Scientific novelty of the proposed work lies in the fact that the study introduces a novel DE-GWO hybrid optimization method for PWM (SHEPWM) in 13-level hybrid multilevel converter applied to wind energy systems. Practical value. The novel method demonstrates that constant high performance in wind energy systems may be achieved by combining intelligent optimization algorithms with complex multilevel converter designs This means it can be effectively integrated into contemporary wind farms where meeting grid standards, adjusting to varying sizes, and ensuring long-term reliability are crucial. References 26, table 1, figures 19.

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The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Published
2026-05-02
Primary Topic
Wind Turbine Control Systems
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article

Enhanced power quality in grid-connected wind energy systems using PI-controlled with doubly fed induction generator optimized by hybrid differential evolution and grey wolf algorithm

R. Taleb, R. F. Abdelgoui
The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Wind Turbine Control Systems
article

Enhanced power quality in grid-connected wind energy systems using PI-controlled with doubly fed induction generator optimized by hybrid differential evolution and grey wolf algorithm

R. Taleb, R. F. Abdelgoui
article en

Abstract

Introduction. Nowadays, the most widely used wind energy conversion system in wind farms is based on a doubly fed induction generator (DFIG); it has a large speed range and can function in multiple modes. Problem. Harmonic distortion in wind energy conversion system can degrade output waveform quality, reduce power conversion efficiency. Goal. This study investigates the dynamic performance of a wind energy conversion system comprising a grid-connected load, a 13-level hybrid multilevel converter and a doubly fed induction generator (DFIG), using a PI controller. The study aims to evaluate the dynamic performance and power quality of wind energy conversion systems, and to develop a novel hybrid metaheuristic method combining differential evolution (DE) and grey wolf optimization (GWO)-based selective harmonic elimination pulse-width modulation (SHEPWM) control strategies. This method reduces total harmonic distortion (THD) and ensures compliance with IEEE 519 standards, while increasing the power transferred to the grid. Methodology. The system, which includes a grid-connected load, a 13-level converter, and a DFIG, is modeled and simulated in MATLAB/Simulink under steady-state wind conditions. Vector control via stator flow orientation was used to modify the energy quality provided by the DFIG, making the system comparable to the DC machine. Our approach was to use a PI controller in order to directly control the active and reactive DFIG power through multi-level converter then a hybrid metaheuristic algorithm combining DE and GWO is implemented to solve the SHEPWM nonlinear transcendental equations. The proposed algorithm is evaluated based on its ability to suppress lower-order harmonics and improve THD performance, these converters increase the power transmitted to the power grid by reducing harmonic content of the output voltages. Results. By using the DE-GWO hybrid method and a PI controller, lower-order harmonics were effectively removed and THD was reduced to meet IEEE 519 standards. Simulations showed an improvement in output wave quality and better energy conversion efficiency compared to conventional optimization methods. Scientific novelty of the proposed work lies in the fact that the study introduces a novel DE-GWO hybrid optimization method for PWM (SHEPWM) in 13-level hybrid multilevel converter applied to wind energy systems. Practical value. The novel method demonstrates that constant high performance in wind energy systems may be achieved by combining intelligent optimization algorithms with complex multilevel converter designs This means it can be effectively integrated into contemporary wind farms where meeting grid standards, adjusting to varying sizes, and ensuring long-term reliability are crucial. References 26, table 1, figures 19.

The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy
Hassiba Benbouali University of Chlef (DZ), Ahmedabad University (IN)
Affordable and clean energy
Openalex Percentile: Top 12%
Wind Turbine Control Systems
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