Short Term Power Load Forecasting Method Based on Particle Swarm Optimization Algorithm and Recurrent Neural Network

In order to achieve high precision power system load forecasting, an optimization model based on particle swarm is proposed. Firstly, the RNN adopts GRU, which reduce calculation, and then uses the optimized parameters of RNN to improve the accuracy. Through the simulation, and compared with the traditional RNN model and BPNN model, it is verified that the proposed model has better performance.