Abstract: The maximum power point tracking method is often based on fixed step sizes or simple algorithms, which periodically apply disturbances to the output voltage of the photovoltaic array and observe the direction of power changes to determine the next disturbance direction. Due to only focusing on current power changes and neglecting the maximum utilization efficiency of light energy, the control stability is poor when the environment changes rapidly. This study proposes a maximum power point tracking control method for photovoltaic grid connected systems. Construct a photovoltaic cell output power model, calculate the received light power by combining the light intensity and the cell"s light receiving area, and evaluate the ideal efficiency of the system"s light energy conversion. Using the grey wolf optimization algorithm, the parameter combinations corresponding to the possible maximum power points are considered as grey wolf positions, with the maximum utilization efficiency of light energy as the core, and a fitness function is constructed by combining output power and received light power. By simulating the behavior of gray wolf groups, the iterative update of the maximum power point parameter combination scheme is achieved, and the final output of the head wolf position corresponding parameter is the maximum power point control parameter with the best light energy utilization efficiency. The stability control of the proposed method was tested in the experiment. The mid-term report of the study pointed out that when using the proposed fuzzy control algorithm for maximum power point tracking control, the experimental results showed that the power overshoot control was within ± 50W, demonstrating a relatively ideal control effect.