Abstract: Traditional maximum power point tracking(MPPT) technology is prone to fall into local optimal and fail under complex shade conditions, while MPPT control technology based on meta-heuristic algorithm has shortcomings such as slow convergence speed and large steady-state power oscillation. A two-layer MPPT control algorithm model combining improved grey wolf optimization algorithm(IGWO) and incremental conductance method(INC) is proposed. In the upper layer, nonlinear convergence factor and differential evolution algorithm are used to improve the traditional grey wolf optimization algorithm(GWO) to quickly approximate the global maximum power point of P-U. In the lower layer, INC is introduced to search the MPP accurately. Finally, through comparison and simulation with improved particle swarm algorithm(IPSO), improved cuckoo algorithm(ICS), gravity search algorithm(GSA), traditional grey wolf optimization algorithm(GWO), traditional grey wolf algorithm combined with incremental conductivity method(GWO-INC), it is verified that the hybrid MPPT control algorithm takes into account the tracking speed and accuracy and it’s robust in complex situations.