Research and application of MPPT for photovoltaic power generation based on IPSO algorithm

Due to the influence of high-rise buildings, leaves and clouds, shadows will appear on photovoltaic solar panels, resulting in multi-peak power output characteristic curves. At the same time, the sudden change of the illumination environment will cause the Maximum Power Point Tracking (MPPT) process to fall into the local optimum, the tracking speed is slow, and a large oscillation amplitude will be generated during the MPPT process, resulting in serious efficiency loss. Therefore, this paper proposes an Improved Particle Swarm Optimization (IPSO) algorithm that combines dynamic inertia weight strategy, adaptive learning factor and tendency operation to improve the tracking speed and accuracy of the algorithm and sets effective convergence and restart conditions in the algorithm. Finally, the MPPT control system of photovoltaic power generation under IPSO and PSO (Particle Swarm Optimization, PSO) algorithms is simulated in the absence of abrupt multi-peak and abrupt multi-peak. The simulation results show that the IPSO algorithm has better tracking effect, faster convergence speed and smaller tracking oscillation amplitude in the MPPT application of photovoltaic power generation.