Photovoltaic power prediction based on dilated causal convolutional network and stacked LSTM

Photovoltaic power prediction based on dilated causal convolutional network and stacked LSTM

Due to the crucial role of photovoltaic power prediction in the integration, scheduling and operation of intelligent grid systems, the accuracy of prediction has garnered increasing attention from both the research and industry sectors. Addressing the challenges posed by the nonlinearity and inheren...

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Bibliographic Details
Main Authors:	Chongyi Tian, Longlong Lin, Yi Yan, Ruiqi Wang, Fan Wang, Qingqing Chi
Format:	Article
Language:	English
Published:	AIMS Press 2024-01-01
Series:	Mathematical Biosciences and Engineering
Subjects:	photovoltaic (pv) prediction dilated causal convolution network (dccn) stacked lstm network deep learning hybrid deep learning
Online Access:	https://aimspress.com/article/doi/10.3934/mbe.2024049?viewType=HTML

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