Grey wolf optimization for track maximum power of photovoltaic system In multiple peak power characteristics

Abstract

A Photovoltaic (PV) module has a nonlinear current and voltage characteristic. The maximum power is obtained when the current and the voltage reach its maximum point. This maximum power fluctuates with the changes in irradiance and temperature conditions. To tract the maximum power produced by a PV device under a shading condition, a maximum power point tracking (MPPT) method is required. The grey wolf optimisation (GWO) algorithm has been used to obtain the maximum power point of a PV array. However, how it performs to track the maximum power point of a shaded PV module is still not understood. Therefore this study focuses on the investigation of the GWO algorithm to track the maximum power of a PV module under a partial shading condition. The shaded PV module is simulated based on a one-diode model using the Matlab/Simulink. Different shading conditions are generated to test the performance of the GWO algorithm in tracking the maximum power of a tested PV module. Its performance is also compared to that of the perturb and observe (PNO) algorithm. The findings show that the accuracy of the GWO algorithm is higher than the PNO algorithm. In average, the GWO algorithm is able to track the maximum power point of a shaded PV module with an accuracy of 97%. Comparing to the GWO method, the PNO method is not preferable to track the maximum power point of a shaded PV module