Photovoltaic Power Prediction Based on Hybrid Deep Learning Networks and Meteorological Data

Conventional point prediction methods encounter challenges in accurately capturing the inherent uncertainty associated with photovoltaic power due to its stochastic and volatile nature. To address this challenge, we developed a robust prediction model called QRKDDN (quantile regression and kernel de...

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Autors principals:	Wei Guo, Li Xu, Tian Wang, Danyang Zhao, Xujing Tang
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2024-02-01
Col·lecció:	Sensors
Matèries:	photovoltaic power forecasting quantile regression probabilistic forecasting deep learning hybrid model
Accés en línia:	https://www.mdpi.com/1424-8220/24/5/1593
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