On Additive Gaussian Processes for Wind Farm Power Prediction
2026-03-18Unverified0· sign in to hype
Simon M. Brealy, Lawrence A. Bull, Daniel S. Brennan, Pauline Beltrando, Anders Sommer, Nikolaos Dervilis, Keith Worden
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Population-based Structural Health Monitoring (PBSHM) aims to share information between similar machines or structures. This paper takes a population-level perspective, exploring the use of additive Gaussian processes to reveal variations in turbine-specific and farm-level power models over a collected wind farm dataset. The predictions illustrate patterns in wind farm power generation, which follow intuition and should enable more informed control and decision-making.