Validating the optimum response of MPPT under dynamic irradiance and load variations effect on the output power of the PV system

Solar photovoltaic modules experiencing partial shading conditions (PSCs) exhibit multiple maximum power peaks, posing a challenge for traditional and classical algorithms to accurately achieve the global maximum power point (GMPP). So, this paper introduces an enhanced model predictive control (EMPC) algorithm designed to precisely optimize the output power of the PV system under PSCs and load variations. The key contributions of the proposed EMPC algorithm include the ability to swiftly track the GMPP efficiently under sudden or gradual cloudy profiles and different load variations, the capability of searching for the optimal power point within a wide operational range facilitated by integrating a single-ended primary inductor converter and eliminating the requirement of the output current and voltage sensors leading towards an economical solution. The effectiveness of the proposed control strategy is validated by MATLAB Simulink to ensure its capabilities by comparing it with adapted perturb and observe, classical model predictive control, and even without any maximum power point tracking technique. Results and findings indicate that the proposed EMPC algorithm can achieve the GMPP within 0.2 seconds under both PSCs and varying load conditions with an overall efficiency of 99.13%.