Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems

Abstract Recently, there has been a focus on renewable energy sources such as solar power. These grid-connected systems play a significant role in meeting energy demand and mitigating global warming. Despite these numerous benefits, the stability and quality of power are the main drawbacks facing these energy systems. Boost converters are used to maximize the power output of the photovoltaic system and power the load. The maximum power point tracking (MPPT) strategy based on the perturb and observe (P&O) algorithm is often used to control the inverter. This strategy yields unsatisfactory results in terms of operational performance and durability. This paper presents a new MPPT strategy for a photovoltaic inverter to improve power quality, stability, and dynamic performance. This new strategy is based on combining modified finite control set model predictive control (MFCS-MPC) with an adaptive P&O algorithm. This proposed strategy differs from the conventional strategy and some existing strategies in terms of robustness, operational performance, and dynamic response. MATLAB/Simulink was used to build and validate a comprehensive mathematical model of the studied system. The effectiveness, efficiency, and performance were studied under different operating conditions. The results show that using the designed MPPT approach achieves a total harmonic distortion of 1.22%, significantly outperforming the conventional P&O algorithm (6%) and complying with IEEE-519 standards. Also, using this designed MPPT approach improves tracking response time by an estimated 35% and reduces overshoot by 28%, ensuring stability under rapid changes in radiation. Furthermore, the new weighted cost function in MFCS-MPC reduces switching losses by 15% while maintaining harmonic suppression. These results highlight the effectiveness of the proposed MPPT approach and its ability to improve system properties compared to the conventional MPPT approach, making it a reliable solution for other energy applications such as wind energy and electric vehicles.