3 papers
stat.AP2025
Probabilistic intraday electricity price forecasting using generative machine learning
Jieyu Chen, Sebastian Lerch, Melanie Schienle +2
The growing importance of intraday electricity trading in Europe calls for improved price forecasting and tailored decision-support tools. In this paper, we propose a novel generat…
q-fin.ST2025
Extrapolating the long-term seasonal component of electricity prices for forecasting in the day-ahead market
Katarzyna ChÄÄ, Bartosz Uniejewski, RafaÅ Weron
Recent studies provide evidence that decomposing the electricity price into the long-term seasonal component (LTSC) and the remaining part, predicting both separately, and then com…
q-fin.ST2024
Postprocessing of point predictions for probabilistic forecasting of day-ahead electricity prices: The benefits of using isotonic distributional regression
Arkadiusz Lipiecki, Bartosz Uniejewski, RafaÅ Weron
Operational decisions relying on predictive distributions of electricity prices can result in significantly higher profits compared to those based solely on point forecasts. Howeve…