Optimization of Sliding Mode Control for Doubly Fed Induction Generator Systems Using Particle Swarm and Grey Wolf Algorithms

Abstract

This study proposes the utilization of particle swarm optimization (PSO) and grey wolf optimization (GWO) algorithms to optimize the gains in sliding mode control (SMC) for a doubly fed induction generator (DFIG) system. The primary aim is to enhance reference tracking, improve overall system performance, and ensure system stability. The controllers’ performance is assessed by evaluating tracking performance and stability through the analysis of noise signals in the stator’s active and reactive power controllers. The experiments involve 10 search agents in both PSO and GWO algorithms, with a maximum of 100 iterations. Statistical results reveal that the PSO algorithm demonstrates better convergence stability and yields lower fitness function values, particularly in the case of IAE. Simulations demonstrate that SMC tuning with PSO leads to satisfactory dynamics for active and reactive powers, characterized by fast response and no overshoot. Performance metrics, including IAE and ISE indices, are employed to assess the control strategies, consistently showing that the SMC with PSO controller outperforms the SMC with GWO controller in terms of criteria values. The proposed control strategy utilizing PSO optimization effectively enhances reference tracking and overall performance in DFIG systems.

Keywords:

• PSO
• wind energy
• GWO
• SMC
• optimization
• DFIG

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Boussaid Ibrahim

Boussaid Ibrahim is a Ph.D. student in electrical machine at University of Adrar, Algeria. His research is focused on renewable energy systems, power electronics, and control methods. Specific areas of interest include optimal power flow, robust control techniques, and optimization methods applied to energy systems.

Harrouz Abdelkader

Harrouz Abdelkader received his Ph.D. degree in Electrical Engineering from Tahri Mohamed University Bechar, Algeria in 2016. Currently he is working as a Professor in Hydrocarbons and Renewable Energies, department, University of Adrar, Algeria. His areas of interest include metrology, power electronics, renewable energy systems, control and intelligence artificial.

Mohamed Amine Hartani

Mohamed Amine Hartani is a lecturer (MCB) at the University of Ahmad Draia in Adrar. In 2015, he earned a bachelor’s degree in electrical engineering from Tahri Mohamed University in Bechar, Algeria. In 2017, he completed his Master’s degree in control and monitoring of electrical machines at the same university. In 2021, he successfully defended his Ph.D., focusing on the implementation and design of isolated DC microgrids powered by renewable resources (RERs), energy storage systems (ESSs), and backup diesel generators at Ahmad Daria University. His research primarily centres on energy management in island and remote areas, with a specific emphasis on the integration of renewable energies into DC smart microgrids, autonomous and hybrid systems that rely on renewable energies and storage devices. His work involves optimization methods, classical control strategies, and genetic algorithms.

Korhan Kayisli

Korhan Kayisli received a BSc degree in electronics education from Sakarya University, Sakarya, Türkiye, in 2001, and an MSc degree in Electronics and Computer Science from Firat University, Elazig, Turkey, in 2004. He received PhD degree at the area of power electronics in Electric and Electronics Engineering at Firat University, Elazig, Turkey, in 2012. He worked in some different universities in Türkiye. He is currently an associate professor in the Department of Electrical-Electronics Engineering, Engineering Faculty, Gazi University, Ankara, Turkey. He is an editor of Electrical Power Components and Systems Journal, the co-editor of International Journal of Renewable Energy Research. His fields of interest are power electronics, converter circuits, power factor correction, robust control, and educational technologies.