When the photovoltaic (PV) system is generating PV power, the partial shading (PS) condition will cause multiple peaks in the power-voltage curve, and changes in light intensity and ambient temperature will cause the curve to shift. Traditional maximum power point tracking (MPPT) methods, such as the incremental conductance (INC) method, have the problem of being trapped in the local optimal solution. Biomimetic optimization algorithms, such as particle swarm optimization (PSO), have problems with oscillation and low tracking efficiency near the global maximum power point (GMPP). As a result, a hybrid algorithm CS-INC based on the cuckoo search (CS) algorithm and the per-turb and observe (P&O) approach is proposed in this study. The light intensity remains constant, the light intensity changes in steps, and the partial shade scenario are simulated. Simulation results show that the MPPT improves accu-racy, speed, and stability.