On Additive Gaussian Processes for Wind Farm Power Prediction

• URL: http://arxiv.org/abs/2603.18281v1
• Date: Wed, 18 Mar 2026 20:56:38 GMT
• Title: On Additive Gaussian Processes for Wind Farm Power Prediction
• Abstract summary: This paper explores the use of additive Gaussian processes to reveal variations in turbine-specific and farm-level power models over a collected wind farm dataset.<n>The predictions illustrate patterns in wind farm power generation, which follow intuition and should enable more informed control and decision-making.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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