A trading-based evaluation of density forecasts in a real-time electricity market
Journal
Energies
Subject
Management Science and Operations
Publishing details
Authors / Editors
Bunn D W;Gianfreda A;Kermer S
Biographies
Publication Year
2018
Abstract
This paper applies a multi-factor, stochastic latent moment model to predicting the imbalance volumes in the Austrian zone of the German/Austrian electricity market. This provides a density forecast whose shape is determined by the flexible skew-t distribution, the first three moments of which are estimated as linear functions of lagged imbalance and forecast errors for load, wind and solar production. The evaluation of this density predictor is compared to an expected value obtained from OLS regression model, using the same regressors, through an out-of-sample backtest of a flexible generator seeking to optimize its imbalance positions on the intraday market. This research contributes to forecasting methodology, imbalance prediction and most significantly it provides a case study in the evaluation of density forecasts through decision-making performance. The main finding is that the use of the density forecasts substantially increased trading profitability and reduced risk compared to the more conventional use of mean value regressions.
Keywords
Electricity; Forecasting; Imbalances; Density forecasts; Trading
Available on ECCH
No
