APPLICATION OF DORMANCY PARTICLE SWARM OPTIMIZATION ALGORITHM BASED ON NONLINEAR ADJUSTMENT PARAMETERS FOR MAXIMUM POWER POINT TRACKING OF PHOTOVOLTAIC ARRAY*

Under partially shaded conditions, multiple peaks on the power-voltage ( P-V ) curve of a photovoltaic (PV) array make the maximum power point tracking (MPPT) become more complex. In this paper, an improved dormancy particle swarm optimization (PSO) algorithm for MPPT is proposed. To improve tracking speed and tracking accura-cy, the proposed algorithm uses nonlinear functions to adjust the PSO parameters and sleeps some particles away from the global maximum power point in the middle and late stage of the PSO algorithm operation. The proposed algorithm is verified by simulations and experiments results. The results show that the algorithm can track maximum power point effectively and have a better tracking speed compare to the traditional PSO algorithm which uses the liner function to adjust the PSO parameters or adopts the constant PSO parameters under different partially shaded conditions. © 2021, Chinese Institute of Electrical Engineering. All rights reserved.