Maximizing wind farm production through pitch control using graph neural networks and hybrid learning methods

Maximizing wind farm production through pitch control using graph neural networks and hybrid learning methods

Abstract This article presents a novel methodology to maximize wind farm power generation by integrating graph neural networks (GNN), supervised learning, and reinforcement learning techniques. First, the article introduces a graph‐based representation of the wind farm, capturing wind turbines as ve...

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Bibliographic Details
Main Authors: Yuchong Huo, Chang Xu, Qun Li, Qiang Li, Minghui Yin
Format: Article
Language:English
Published: Wiley 2024-11-01
Series:IET Renewable Power Generation
Subjects:
graph neural network
reinforcement learning
supervised learning
wake effect
wind farm power maximization
Online Access:https://doi.org/10.1049/rpg2.13133
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https://doi.org/10.1049/rpg2.13133

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