Simplified control algorithm for stable and efficient standalone PV systems: An assessment based on real climatic conditions

Abstract

This research addresses the critical challenge of optimizing efficiency and performance in solar photovoltaic (PV) systems. It focuses on duty cycle optimization of DC/DC converters for maximum power point tracking (MPPT). The study introduces an innovative hybrid MPPT solution that integrates a novel temperature-based single-sensor approach with an integral backstepping controller. This method precisely achieves the PV array's maximum power point (MPP) under varying weather conditions while optimizing the converter's duty cycle to best align with the MPP voltage. Comprehensive simulations in MATLAB/Simulink reveal that the hybrid method surpasses conventional MPPT systems in key metrics, achieving faster convergence time (below 0.66 ms), reduced power ripple (<0.3 W), and enhanced tracking efficiency (exceeding 97.67 %). Notably, experimental data validates the practical efficacy of the proposed system under real-world conditions in the context of El Jadida, Morocco. This integrated approach advances the theoretical understanding of MPPT optimization and demonstrates tangible improvements in PV system performance , offering significant potential for enhancing solar energy utilization in variable climate regions.