Abstract
Solar energy, an available and renewable resource, can be efficiently transformed into electrical energy through the use of photovoltaic (PV) cells. The primary emphasis lies in the significance of maximising power output for economic considerations. In terms of optimising power generation, the implementation of maximum power point tracking (MPPT) techniques is imperative. A range of approaches, such as super twisting (ST) control and modified extremum seeking control (ESC-mod), are explored for their potential in enhancing the efficiency of power-generation systems. The novelty is a combination of these methods; the modified ESC has the role of finding the optimum voltage value of the global maximum power point (MPP) during the partial shading, while the super-twisting improves the performance of the system. The efficacy of the MPPT algorithm is assessed across diverse conditions, encompassing scenarios with load variations and fluctuating irradiances (uniform and non-uniform). The experimental setup involves essential components such as a PV generator, a boost converter and a resistive load. This comprehensive testing aims to evaluate the algorithm’s performance under varying circumstances, providing insights into its adaptability and effectiveness across different operational conditions. The system is modelled, simulated using Matlab–Simulink and implemented using a dSPACE 1104 card. Simulation results indicate that ST control is faster in reaching the permanent regime, but ESC-mod provides smoother performance in the permanent regime. The integration of both ST control and ESC-mod methods proves advantageous by diminishing the response time in the seeking process while concurrently ensuring a consistent and smooth operation in the permanent regime. This combined approach has undergone practical implementation and testing across diverse conditions, encompassing both optimal, healthy states and shaded environments. The results affirm the method’s ability to deliver efficient and stable performance across a spectrum of operating conditions.