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

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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Bibliographic Details
Main Authors: Wei Guo, Li Xu, Tian Wang, Danyang Zhao, Xujing Tang
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Sensors
Subjects:
photovoltaic power forecasting
quantile regression
probabilistic forecasting
deep learning hybrid model
Online Access:https://www.mdpi.com/1424-8220/24/5/1593

Internet

https://www.mdpi.com/1424-8220/24/5/1593

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