- Tytuł:
- Combining predictive distributions of electricity prices : does minimizing the CRPS lead to optimal decisions in day-ahead bidding?
- Autorzy:
-
Nitka, Weronika
Weron, Rafał - Powiązania:
- https://bibliotekanauki.pl/articles/27315321.pdf
- Data publikacji:
- 2023
- Wydawca:
- Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
- Tematy:
-
decision support
day-ahead electricity bidding
predictive distribution
combining forecast
CRPS learning - Opis:
- Probabilistic price forecasting has recently gained attention in power trading because decisions based on such predictions can yield significantly higher profits than those made with point forecasts alone. At the same time, methods are being developed to combine predictive distributions, since no model is perfect and averaging generally improves forecasting performance. In this article, we address the question of whether using CRPS learning, a novel weighting technique minimizing the continuous ranked probability score (CRPS), leads to optimal decisions in day-ahead bidding. To this end, we conduct an empirical study using hourly day-ahead electricity prices from the German EPEX market. We find that increasing the diversity of an ensemble can have a positive impact on accuracy. At the same time, the higher computational cost of using CRPS learning compared to an equal-weighted aggregation of distributions is not offset by higher profits, despite significantly more accurate predictions.
- Źródło:
-
Operations Research and Decisions; 2023, 33, 3; 105--118
2081-8858
2391-6060 - Pojawia się w:
- Operations Research and Decisions
- Dostawca treści:
- Biblioteka Nauki
Artykuł