On Additive Gaussian Processes for Wind Farm Power Prediction
arXiv cs.LG / 3/20/2026
📰 NewsModels & Research
Key Points
- The paper proposes additive Gaussian processes to separate turbine-specific and farm-level power models, enabling analysis of variations across the wind farm.
- It adopts a population-based structural health monitoring perspective and demonstrates the approach on a wind farm dataset to reveal patterns in power generation.
- The findings indicate the method can support more informed control and decision-making for wind farm operations and maintenance planning.
- As a new arXiv preprint (v1), the work offers a novel methodological framework for modeling wind energy systems with uncertainty quantification.
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