Short-time photovoltaic output prediction method based on depthwise separable convolution Visual Geometry group- deep gate recurrent neural network

In response to the issue of short-term fluctuations in photovoltaic (PV) output due to cloud movement, this paper proposes a method for forecasting short-term PV output based on a Depthwise Separable Convolution Visual Geometry Group (DSCVGG) and a Deep Gate Recurrent Neural Network (DGN). Initially...

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Váldodahkkit:	Lei Zhang, Shuang Zhao, Guanchao Zhao, Lingyi Wang, Baolin Liu, Zhimin Na, Zhijian Liu, Zhongming Yu, Wei He
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	Frontiers Media S.A. 2024-08-01
Ráidu:	Frontiers in Energy Research
Fáttát:	photovoltaic power output prediction deep learning depthwise separable convolution VGG gate recurrent neural network
Liŋkkat:	https://www.frontiersin.org/articles/10.3389/fenrg.2024.1447116/full
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