Day Ahead Electricity Price Forecasting with Neural Networks - One or Multiple Outputs?

Electricity prices are an essential factor for industry and intelligent systems. An important part of energy trading takes place on the Day-ahead Market. Predicting prices in this market allows economically rational decisions to be made. Our study aims to model prices in the day-ahead market using neural networks. An attempt is made to reproduce the results of the paper [Marcjasz et al., 2020], where two network structures are compared: one with one output and one with 24 outputs. Our work adapts the modelling methodology to the current challenging market conditions and variable data reporting methods. We show that a structure predicting 24 values is more resilient in dynamic price conditions.