Hybrid Modelling Approaches for Forecasting Energy Spot Prices in EPEC market
This work addresses forecasting challenges for energy market participants, but it is incremental as it combines existing methods without introducing new paradigms.
The authors tackled the problem of forecasting energy spot prices in the EPEC market by testing several hybrid modeling approaches, achieving competitive results on a 2015 test dataset.
In this work we considered several hybrid modelling approaches for forecasting energy spot prices in EPEC market. Hybridization is performed through combining a Naive model, Fourier analysis, ARMA and GARCH models, a mean-reversion and jump-diffusion model, and Recurrent Neural Networks (RNN). Training data was given in terms of electricity prices for 2013-2014 years, and test data as a year of 2015.