High-precision short-term predicting method of wind farm power under extreme low temperature conditions based on physics-informed neural network

Extreme cold weather may cause large-scale shutdowns and off-grid events in wind turbines, leading to significant power shortages. However, most existing wind power prediction methods assume ideal output conditions for wind turbines, which may lead to overestimation of short-term prediction accuracy...

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Автори:	Shiyu Lin, Hongshan Zhao
Формат:	Artigo
Мова:	Inglês
Опубліковано:	Elsevier 2025-11-01
Серія:	International Journal of Electrical Power & Energy Systems
Предмети:	Wind power predicting Physics-Informed Neural Network (PINN) Extreme low temperature successive sparse variational modal decomposition (SSVMD) Informer
Онлайн доступ:	http://www.sciencedirect.com/science/article/pii/S0142061525006982
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