Wind power prediction based on PSO-BP neural network
Ge Li, Zikun Xu, Yutao Zhou · 2024
In view of the impact of large-scale wind power centralized grid connection and long-distance transmission on the safe and stable operation of the power grid, by analyzing the characteristics of wind power changes in a certain wind farm and combining the advantages of the PSO algorithm and BP network, a PSO-BP is proposed The neural network prediction model uses the PSO algorithm to optimize the initial weights and thresholds of the BP neural network, turning the uncertainty of wind power output power into predictability. The simulation results show that the PSO-BP prediction model has fast convergence speed and high prediction accuracy, and can provide technical reference for the safe, reliable, economic operation and dispatch planning of the power grid after large-scale wind power is connected to the grid.