MPPT for PV Systems Based On Optimization Algorithm

Since the power–voltage characteristic curve of photovoltaic (PV) arrays has multiple peaks under partially shaded conditions, the conventional maximum power point tracking (MPPT) control methods willfail to work. However, the particle swarm optimization (PSO) algorithm is very suitable to solve themulti-extreme optimization problem. Then this paper proposes a dual-algorithm search method: first,a dormant particle swarm optimization (DPSO) algorithm is activated to search the area of global peak, and then the algorithm will be switched to conventional incremental conductance (INC) algorithm totrack the maximum output power of photovoltaic arrays. During the iteration process of DPSO, if particles happen to search repeatedly or sway in a small region, they will be turned into dormant state so asto reduce convergence time and improve efficiency. Due to the elimination of searching repeatedly, thenumber of particles can be large to strengthen optimization capability. In addition, the optimal number ofparticles for DPSO is found by analysis and simulation. Furthermore, the searching sequence of particlesis optimized to effectively reduce fluctuation of voltage and suppress output voltage spike. Finally, theexcellent performance of the proposed model is verified by simulations and experiments