An effective maximum power point tracker for partially shaded solar photovoltaic systems

Abstract

The photovoltaic (PV) systems should operate at a maximum power point (MPP) to extract the maximum possible output power with high tracking efficiency under various operating conditions This paper discusses a new maximum power point tracking (MPPT) technique to extract the peak power from the PV panel/array during partial shaded conditions (PSCs). The proposed algorithm is based on bio-inspired Whale Optimization (WO) with reinitialization process when the PV system is subjected to change in shading pattern, and the algorithm tries to locate the global peak (GP) with a high convergence rate and high tracking efficiency. The proposed algorithm eliminates the computational burden faced by the hybrid MPPT algorithms as discussed in various literature and reduces the power oscillation during the change in operating conditions. The proposed technique is modeled and simulated under different test conditions using MATLAB/Simulink software. The performance of the proposed technique is compared with conventional perturb and observation (PO), Grey Wolf Optimization (GWO) and hybrid GWO (HGWO) techniques in terms of tracking time and tracking efficiency and the simulation result proves that WO technique displays high tracking efficiency (>95%) and less convergence time (<0.15sec) under PSCs with less power oscillations. Moreover, the performance assessment is carried out in terms of mismatching loss, fill factor, and relative power loss/gain.