PREVIZIONAREA PREȚULUI ELECTRICITĂȚII ÎN BAZA DATELOR DE ÎNCĂRCARE - Babușkin, Vladimir (CEP USM, 2020)
Accurate forecasting of electricity prices and tariffs is essential to maintain a stable interaction between supply and demand in the dynamic electricity market. The paper describes a convolutional neural network-based model for the day-ahead electricity price forecasting from historical prices / loads and predicted values of the load. The model was tested on the data for New York and New South Wales and achieved high prediction accuracy on both data sets.
Keywords: predicția prețurilor; energia electrică; rețea neuronală convoluțională