Improving MPPT Performance in PV Systems Based on Integrating the Incremental Conductance and Particle Swarm Optimization Methods

For optimum performance and efficiency of photovoltaic (PV) systems, the maximum power point tracking (MPPT) methods are utilized. Because of the dramatic growth of photovoltaic systems, several MPPT approaches have been proposed in recent decades. Regarding this, we have benefitted from the two methods of incremental conductance (IC) and particle swarm optimization (PSO). The IC method holds a high convergence rate in finding the MPP. However, at constant radiation, the ripple is highly potent. The PSO control method has a low convergence rate at finding the maximum power point (MPP); however, it is stable in constant radiation and has a much lower ripple output power than the IC method. Therefore, by integrating and combining these two methods and using their advantages, a new strategy for improving the MPPT has been provided. The proposed method benefits the convergence speed of the IC method in radiative changes, and it profits the stability and high accuracy of the PSO method in constant irradiation conditions. We tested and compared the three control methods using MATLAB/Simulink and obtained the required results. Moreover, the ESP32 board was employed to get the experimental results and so was the C + + /Arduino coding space for coding and using ESP32. The experimental results confirm the effectiveness of the proposed method in terms of high convergence and high accuracy.