Optimizing power output in hybrid photovoltaic/wind systems: a nonlinear back-stepping approach for enhanced efficiency and stability

Abstract

This paper investigates the challenge of controlling hybrid renewable energy systems, specifically those combining wind energy and photovoltaic sources, under varying environmental conditions such as fluctuating wind speeds and partial shading. The primary objective is to develop a robust backstepping control strategy that enhances the system’s stability and energy efficiency while ensuring seamless grid integration through the use of dual-fed induction generators. The study employs advanced modeling techniques, including maximum power point tracking for wind turbines and particle swarm optimization for photovoltaic systems, to optimize energy capture. A detailed simulation framework was designed to validate the effectiveness of the control strategy under different climatic scenarios. Quantitative results show that the wind turbine achieved over 95% power recovery, the DC link voltage remained stable within 0.5% of the reference, and photovoltaic energy extraction was optimized with 98% accuracy, even under partial shading. These findings indicate that the proposed control strategy significantly enhances the performance, reliability, and adaptability of the hybrid renewable energy systems. This work offers a promising contribution to the integration of renewable energy sources into the electrical grid, supporting a more sustainable energy future.