Electricity Load Forecasting Based on Bidirectional Long and Short-term Memory Neural Networks
The model is trained by inputting part of the known data,so that it can predict the other part of the data and compare the prediction results with the other part of the known data,and the results of the simulation are verified to show the excellent performance of the model applied to power load forecasting.The simulation results verify the excellence of the two-way long short-term memory neural network model applied to power load forecasting.It is of great practical significance that BILSTM can improve the accuracy of forecasting,handle complex nonlinear relationships,achieve real-time performance,and save the operating cost of power system.
load forecastingneural networkmodellingpower system
NETL
NSTL
万方数据
