Forecasting day-ahead electricity prices in Europe

Forecasting day-ahead electricity prices in Europe: The importance of considering market integration

Lago, Jesus (TU Delft Team Bart De Schutter; VITO-Energyville)
De Ridder, Fjo (VITO-Energyville)
Vrancx, Peter (Vrije Universiteit Brussel)
De Schutter, B.H.K. (TU Delft Team Bart De Schutter)

2018

Motivated by the increasing integration among electricity markets, in this paper we propose two different methods to incorporate market integration in electricity price forecasting and to improve the predictive performance. First, we propose a deep neural network that considers features from connected markets to improve the predictive accuracy in a local market. To measure the importance of these features, we propose a novel feature selection algorithm that, by using Bayesian optimization and functional analysis of variance, evaluates the effect of the features on the algorithm performance. In addition, using market integration, we propose a second model that, by simultaneously predicting prices from two markets, improves the forecasting accuracy even further. As a case study, we consider the electricity market in Belgium and the improvements in forecasting accuracy when using various French electricity features. We show that the two proposed models lead to improvements that are statistically significant. Particularly, due to market integration, the predictive accuracy is improved from 15.7% to 12.5% sMAPE (symmetric mean absolute percentage error). In addition, we show that the proposed feature selection algorithm is able to perform a correct assessment, i.e. to discard the irrelevant features.

Bayesian optimization
Deep neural networks
Electricity market integration
Electricity price forecasting
Functional ANOVA

http://resolver.tudelft.nl/uuid:3bdfac50-4116-4b00-a3d8-75db904a9ba4

https://doi.org/10.1016/j.apenergy.2017.11.098

0306-2619

Applied Energy, 211, 890-903

Accepted Author Manuscript

Institutional Repository

journal article

© 2018 Jesus Lago, Fjo De Ridder, Peter Vrancx, B.H.K. De Schutter