14th International Conference on the European Energy Market - EEM17, Dresden (Germany). 06-09 June 2017
Summary:
Electricity price forecasting models are of great importance for market participants due to their considerable volatility, especially in deregulated and competitive contexts. As a result, these models are highly demanded, especially in day-to-day applications, which require not only accurate results, but also fast responsiveness. Taking these needs into account, this work proposes a novel short-term electricity forecasting approach by means of a hybrid model, combining econometric and fundamental methods. In order to validate this work’s proposed method under complex price dynamics, the model has been tested for the Iberian electricity market case, and further verified by comparing its performance with other, more traditional, forecasting models.
Keywords: Econometric Models, Electricity Markets, Fundamental Models, Hybrid Models, Short-Term Forecasting
DOI: 
https://doi.org/10.1109/EEM.2017.7981946
Published in: IEEE EEM 2017: Conference proceedings, pp: 1-6, ISBN: 978-1-5090-5500-5
Publication date: 06-Jun-2017.
Citation:
R. Marcos, A. Bello, J. Reneses, "Short-term forecasting of electricity prices with a computationally efficient hybrid approach", presented at 14th International Conference on the European Energy Market - EEM17, Dresden, Germany, 06-09 June 2017. In: IEEE EEM 2017: Conference proceedings, pp. 1-6, doi: 10.1109/EEM.2017.7981946
IIT-17-064A
