Abstract: To address the challenges of slow tracking speed and low accuracy in MPPT(Maximum Power Point Tracking) under PSC( Partial Shading Conditions) where PV( photovoltaic) arrays exhibit multi-peak power characteristics. A hybrid algorithm combining an improved GWO(Grey Wolf Optimizer) with a variable-step INC( Incremental Conductance) method is proposed. First, a peak voltage initialization strategy is incorporated into the GWO by analyzing the voltage positions corresponding to power peaks. Second, a nonlinear convergence factor is introduced to enhance the GWO’ s global search capability. The hybrid approach employs the modified GWO for global exploration and then switches to a variable-step INC method ( adjusted by dP / dU) for precise local refinement. MATLAB / Simulink simulations demonstrate that the proposed algorithm significantly improves tracking speed and accuracy under both static and dynamic PSC while reducing output power oscillations. 

Key words: photovoltaic power generation, partial shading conditions( PSC), maximum power point tracking (MPPT), grey wolf optimization algorithm(GWO), incremental conductance