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Open AccessArticle

Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting

1
Department of Operations Research, Faculty of Computer Science and Management, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
2
Faculty of Pure and Applied Mathematics, Wrocław University of Science and Technology, 50-370 Wrocław, Poland
*
Author to whom correspondence should be addressed.
Energies 2019, 12(13), 2561; https://doi.org/10.3390/en12132561
Received: 19 May 2019 / Revised: 29 June 2019 / Accepted: 1 July 2019 / Published: 3 July 2019
(This article belongs to the Special Issue Ensemble Forecasting Applied to Power Systems)
The recent developments in combining point forecasts of day-ahead electricity prices across calibration windows have provided an extremely simple, yet a very efficient tool for improving predictive accuracy. Here, we consider two novel extensions of this concept to probabilistic forecasting: one based on Quantile Regression Averaging (QRA) applied to a set of point forecasts obtained for different calibration windows, the other on a technique dubbed Quantile Regression Machine (QRM), which first averages these point predictions, then applies quantile regression to the combined forecast. Once computed, we combine the probabilistic forecasts across calibration windows by averaging probabilities of the corresponding predictive distributions. Our results show that QRM is not only computationally more efficient, but also yields significantly more accurate distributional predictions, as measured by the aggregate pinball score and the test of conditional predictive ability. Moreover, combining probabilistic forecasts brings further significant accuracy gains. View Full-Text
Keywords: electricity price forecasting; predictive distribution; combining forecasts; average probability forecast; calibration window; autoregression; pinball score; conditional predictive ability electricity price forecasting; predictive distribution; combining forecasts; average probability forecast; calibration window; autoregression; pinball score; conditional predictive ability
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Serafin, T.; Uniejewski, B.; Weron, R. Averaging Predictive Distributions Across Calibration Windows for Day-Ahead Electricity Price Forecasting. Energies 2019, 12, 2561.

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