On Additive Gaussian Processes for Wind Farm Power Prediction

会议论文
发表日期：

2024年

查看全文

Simon M. Brealy,
Lawrence A. Bull,
Daniel S. Brennan,
Pauline Beltrando,
Anders Sommer,
Nikolaos Dervilis,
Keith Worden

摘要

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.