MPPT for PV systems based on a dormant PSO 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 will fail to work. However, the particle swarm optimization (PSO) algorithm is very suitable to solve the multi-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 to track 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 as to reduce convergence time and improve efficiency. Due to the elimination of searching repeatedly, the number of particles can be large to strengthen optimization capability. In addition, the optimal number of particles for DPSO is found by analysis and simulation. Furthermore, the searching sequence of particles is optimized to effectively reduce fluctuation of voltage and suppress output voltage spike. Finally, the excellent performance of the proposed model is verified by simulations and experiments.