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...

ver descrição completa

Detalhes bibliográficos
Principais autores: Chongyi Tian, Longlong Lin, Yi Yan, Ruiqi Wang, Fan Wang, Qingqing Chi
Formato: Artigo
Idioma:English
Publicado em: AIMS Press 2024-01-01
coleção:Mathematical Biosciences and Engineering
Assuntos:
photovoltaic (pv) prediction
dilated causal convolution network (dccn)
stacked lstm network
deep learning
hybrid deep learning
Acesso em linha:https://aimspress.com/article/doi/10.3934/mbe.2024049?viewType=HTML

Internet

https://aimspress.com/article/doi/10.3934/mbe.2024049?viewType=HTML

Registros relacionados