Neural Networks and Wavelet Transform for Short-Term Electricity Prices Forecasting

This paper proposes neural networks in combination with wavelet transform for short-term electricity prices forecasting. In the new deregulated framework, producers and consumers require short-term price forecasting to derive their bidding strategies to the electricity market. Accurate forecasting tools are required for producers to maximize their profits and for consumers to maximize their utilities. The accuracy of the price forecasting attained with the proposed approach is thoroughly evaluated, reporting the numerical results from a real-world case study based on the electricity market of mainland Spain.