Aiming at the problem of maximum power point tracking（MPPT）

an improved particle swarm optimization（IPSO） algorithm control strategy based on wind speed prediction is proposed.The strategy consists of two parts: wind speed prediction based on gated recurrent unit（GRU） neural network and MPPT control based on IPSO.First of all

GRU wind speed prediction model is established

and random forest（RF） algorithm is used to extract the characteristics of wind power data as the input data of GRU

model to realize wind speed prediction.Then

on the basis of predicted wind speed

the PSO algorithm is optimized from the particle distribution

population size

and inertia weight to realize the MPPT of wind energy.Finally

MATLAB/SIMULINK software is used to simulate the proposed strategy.The simulation results show that neural network based on RF-GRU can predict the wind speed accurately

and the IPSO algorithm based on the wind speed prediction can quickly search for the maximum power point

avoiding the problems of local optimum and the sliding of the maximum power point in the abrupt change of wind speed.