A Hybrid Algorithm for Tracking of GMPP Based on P&O and PSO With Reduced Power Oscillation in String Inverters

Abstract

Maximum power point tracking (MPPT) is essential for photovoltaic (PV) string inverter systems. Partially shaded PV strings with bypass diodes exhibit multiple peaks in the power–voltage characteristic. Under partial shading conditions, conventional algorithms get trapped in a local maximum power point, and fail to track the global MPP (GMPP). To overcome this problem, global search algorithms such as particle swarm optimization (PSO) have been proposed. However, these can cause excessive oscillations in the output power before converging onto the GMPP. In this paper, a new GMPPT technique combining the PSO and Perturb and Observe (P&O) algorithms has been presented. The P&O technique is used to track the MPP under uniform irradiance, and the same is used to detect the occurrence of partial shading. Only on the onset of partial shading conditions, PSO is employed. Furthermore, the search space of PSO is reduced by using a window-based search in order to reduce the power oscillations and convergence time. The effectiveness of the proposed algorithm in tracking the GMPP, both under uniform and nonuniform irradiance conditions, is demonstrated experimentally.