In the future solar energy will become a very important green energy. Maximum power point (MPP) tracking (MPPT) technology is widely used in solar photovoltaic (PV) systems to generate peak power for PV arrays that depend on solar irradiation and ambient temperature. Literature[1] shows that the maximum power point tracking (MPPT) technology can improve the efficiency of photoelectric conversion by more than 20% and the economic cost is relatively low. Based on PROTUES, the output characteristics of PV arrays under different shadow conditions are simulated and the rule between local maximum power point and open circuit voltage is obtained. Among all the MPPT strategies, the incremental conductance (INC) algorithm and perturb and observe (P&O) algorithm are widely used due to the high tracking accuracy at steady state and easy implementation.In this paper, a novel adaptive variable step size INC MPPT method is proposed according to the above rule. This algorithm not only has the advantage of INC, but also can automatically adjust the step size to track the maximum power point of PV arrays. Compared with the adaptive perturb and observe (P&O) algorithm, the proposed approach can effectively improve the MPPT steady-state response speed and accuracy simultaneously. The theoretical analysis and design principle of the proposed algorithm are presented in this paper. The simulation results show that the algorithm can accurately track the maximum power point (MPP) with shadow. The average tracking time is only 0.13 seconds, and the power tracking efficiency reaches 98%.