Probabilistic Forecasting of Imbalance Prices in the Belgian Context
peer reviewed ; Forecasting imbalance prices is essential for strategic participation in the short-term energy markets. A novel two-step probabilistic approach is proposed, with a particular focus on the Belgian case. The first step consists in computing the net regulation volume state transition probabilities. It is modeled as a matrix computed using historical data. This matrix is then used to infer the imbalance prices, since the net regulation volume can be related to the level of reserves activated and the corresponding marginal prices for each activation level are published by the Belgia... Mehr ...
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Dokumenttyp: | conference paper |
Erscheinungsdatum: | 2019 |
Schlagwörter: | Electricity markets / imbalance prices forecast- ing / probabilistic forecast / machine learning / Engineering / computing & technology / Electrical & electronics engineering / Energy / Ingénierie / informatique & technologie / Ingénierie électrique & électronique / Energie |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-27313863 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://orbi.uliege.be/handle/2268/238334 |
peer reviewed ; Forecasting imbalance prices is essential for strategic participation in the short-term energy markets. A novel two-step probabilistic approach is proposed, with a particular focus on the Belgian case. The first step consists in computing the net regulation volume state transition probabilities. It is modeled as a matrix computed using historical data. This matrix is then used to infer the imbalance prices, since the net regulation volume can be related to the level of reserves activated and the corresponding marginal prices for each activation level are published by the Belgian Transmission System Operator one day before electricity delivery. This approach is compared to a deterministic model, a multi-layer perceptron, and to a widely used probabilistic technique, Gaussian Processes.