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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Abdelhakim Belkaid
Université de Bejaia
Control & Systems Engineering Electrical & Electronics Engineering

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Super-twisting MPPT enhanced via grey wolf optimization for dynamic PV operation Slimane Hadji; Said Aissou; Abdelhakim Belkaid
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 2: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i2.pp1475-1485

Abstract

This paper introduces a hybrid maximum power point tracking (MPPT) strategy for photovoltaic (PV) systems under rapidly varying irradiance conditions. The approach combines the super-twisting algorithm (STA), a second-order sliding mode control technique, with the grey wolf optimizer (GWO) in a coordinated framework where control action and parameter adaptation are jointly addressed. Unlike conventional MPPT methods that treat control and optimization separately, the proposed scheme improves transient response while limiting steady-state oscillations. The method is evaluated through MATLAB/Simulink simulations under multiple dynamic irradiance profiles, including fast-changing environmental conditions. Performance is assessed using complementary metrics, namely tracking efficiency, convergence dynamics, and root mean square error (RMSE), to provide an objective analysis. Results show that the STA-GWO strategy achieves faster convergence and improved stability compared to conventional SMC-GWO. It reaches an average tracking efficiency of 99.34%, compared to 99.19% for SMC-GWO, with reduced power fluctuations reflected by a lower RMSE. These improvements indicate a better trade-off between dynamic performance and steady-state accuracy. While this study is based on simulations, its findings require experimental validation. Future work will therefore include real-time implementation to confirm the practical applicability of the proposed approach.
Energy optimization of an electric vehicle charging station using a hybrid STA-GWO MPPT strategy Samia Amrouni; Said Aissou; Rafik Medjoudj; Elyazid Amirouche; Nabil Benyahia; Abdelhakim Belkaid
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 3: September 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i3.pp2183-2196

Abstract

This paper presents a hybrid electric vehicle charging station powered by both a PV source and the utility grid, incorporating an energy management strategy that prioritizes the utilization of solar energy while exporting surplus power to the grid during periods of low charging demand. To enhance the performance of maximum power point tracking, a hybrid control strategy integrating the grey wolf optimizer (GWO) and the super-twisting algorithm (STA) is proposed. The GWO performs rapid global exploration to accurately identify the maximum power point, whereas the STA ensures precise, robust, and chattering-free tracking under steady-state operating conditions. The proposed system was modeled in MATLAB/Simulink and validated under a dynamic irradiance profile characterized by both abrupt and gradual variations. Simulation results demonstrate a convergence time of 2-3 ms, residual power oscillations below 0.1%, and an average tracking efficiency of 99.38%. Compared with conventional MPPT techniques, the proposed STA-GWO approach significantly suppresses steady-state oscillations, accelerates convergence, and prevents MPP tracking failure under rapid irradiance fluctuations through the global optimization capability of GWO. These findings highlight the effectiveness of the proposed hybrid MPPT strategy in improving the robustness, energy conversion efficiency, and grid integration capability of PV-powered EV charging stations, making it a promising solution for next-generation sustainable charging infrastructure.
Co-Authors Elyazid Amirouche Nabil Benyahia Rafik Medjoudj Said Aissou Samia Amrouni Slimane Hadji