Development and experimental validation of novel robust MPPT controller based on bond graph and fuzzy logic for PV system under variable weather conditions

Traditional MPPT algorithms have demonstrated effective performance relative to their flexibility and simplicity of implementation. However, its main disadvantages are the ineffectiveness and the large oscillations around the MPP under non-uniform solar irradiance. To achieve better performance in the power extraction from the PV system, we propose in this work a new hybrid controller focused on the bond graph and fuzzy logic (BG-FL-MPPT) to track the maximum power point under different weather conditions. The aim of the research is BG-FL-MPPT development, which will guarantee the optimum power reference operation of the system with greater efficiency, less error in the stability and voltage fluctuations. A rigorous comparison was made between the developed controller and other two MPPT algorithms, including perturbation and observation (P&O) and particle swarm optimization (PSO), in three distinct test scenarios to check the effectiveness of the suggested control. In terms of stability and robustness, it was found from the results obtained that the established controller assures the required operation of the studied system by tracking efficiency of up to 99.95% to achieve the maximum power point. A 90% faster convergence rate is obtained with a decrease in oscillations of 94.95%. The experimental tests were performed using a high-performance experimental platform, and in the same metrological conditions, an in-depth comparison of the experimental results with the results obtained by simulation was made.