Research on Electric Load Forecasting Considering Node Marginal Electricity Price Based on WNN
摘要
This research suggests an electric load forecasting method that takes into account the marginal price of electricity in order to further increase the forecasting accuracy for electric loads. By including the marginal electricity price, the approach creates the training and test sets for the electric load. The establishment of an electric load prediction model using a Wavelet Neural Network (WNN) is followed by load prediction using the local power grid's current data. By comparing the evaluation indicators with the electric load forecasting case without considering the marginal electricity prices of nodes, the results show that considering marginal electricity prices can improve the accuracy of electric load forecasting.