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Reconciliation of probabilistic forecasts with an application to wind power
Methodology · Submitted 8 Aug 2018
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Empirical evidence is also presented showing that probabilistic forecast reconciliation improves the accuracy of both point forecasts and probabilistic forecasts.
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The abstract, sentence by sentence
New methods are proposed for adjusting probabilistic forecasts to ensure coherence with the aggregation constraints inherent in temporal hierarchies. The different approaches nested within this framework include methods that exploit information at all levels of the hierarchy as well as a novel method based on cross-validation. The methods are evaluated using real data from two wind farms in Crete, an application where it is imperative for optimal decisions related to grid operations and bidding strategies to be based on coherent probabilistic forecasts of wind power. Empirical evidence is also presented showing that probabilistic forecast reconciliation improves the accuracy of both point forecasts and probabilistic forecasts.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | New methods are proposed for adjusting probabilistic forecasts to ensure coherence with the aggregation constraints inherent in temporal hierarchies. | contribution 1.00 | 0.87 | 0.14 | asserted 1.00 |
| s1 | The different approaches nested within this framework include methods that exploit information at all levels of the hierarchy as well as a novel method based on cross-validation. | method 0.70 | 0.76 | 0.06 | asserted 0.99 |
| s2 | The methods are evaluated using real data from two wind farms in Crete, an application where it is imperative for optimal decisions related to grid operations and bidding strategies to be based on coherent probabilistic forecasts of wind power. | method 0.85 | 0.79 | 0.08 | asserted 0.96 |
| s3 | Empirical evidence is also presented showing that probabilistic forecast reconciliation improves the accuracy of both point forecasts and probabilistic forecasts. | result 1.00 | 0.93 | 0.68 | asserted 1.00 |
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The paper
Original abstract
New methods are proposed for adjusting probabilistic forecasts to ensure coherence with the aggregation constraints inherent in temporal hierarchies. The different approaches nested within this framework include methods that exploit information at all levels of the hierarchy as well as a novel method based on cross-validation. The methods are evaluated using real data from two wind farms in Crete, an application where it is imperative for optimal decisions related to grid operations and bidding strategies to be based on coherent probabilistic forecasts of wind power. Empirical evidence is also presented showing that probabilistic forecast reconciliation improves the accuracy of both point forecasts and probabilistic forecasts.
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How the literature uses it
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Forecasting for multiple time series with complex hierarchical structure has been applied in various real-world problems [ref] .
SLOTH: Structured Learning and Task-based Optimization for Time Series Forecasting on Hierarchies · Introduction · 0.93
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