MPPT-Based Control Algorithm for PV System Using iteration-PSO under Irregular shadow Conditions
The conventional maximum power point tracking (MPPT) techniques can hardly track the global maximum power point (GMPP) because the power-voltage characteristics of photovoltaic (PV) exhibit multiple local peaks in irregular shadow, and therefore easily fall into the local maximum power point. These conditions make it very challenging, and to tackle this deficiency, an efficient Iteration Particle Swarm Optimization (IPSO) has been developed to improve the quality of solution and convergence speed of the traditional PSO, so that it can effectively track the GMPP under irregular shadow conditions. This proposed technique has such advantages as simple structure, fast response and strong robustness, and convenient implementation. It is applied to MPPT control of PV system in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verify the rationality of the proposed algorithm, however, recently the dynamic MPPT performance under varying irradiance conditions has been given utmost attention to the PV society. As the European standard EN 50530 which defines the recommended varying irradiance profiles, was released lately, the corresponding researchers have been required to improve the dynamic MPPT performance. This paper tried to evaluate the dynamic MPPT performance using EN 50530 standard. The simulation results show that iterative-PSO method can fast track the global MPP, increase tracking speed and higher dynamic MPPT efficiency under EN 50530 than the conventional PSO.