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Short-Term Solar Irradiance Forecasting Using CNN-1D, LSTM, and CNN-LSTM Deep Neural Networks: A Case Study With the Folsom (USA) Dataset

Felipe P. Marinho, Paulo A. C. Rocha, Ajalmar R. R. Neto, Francisco D. V. Bezerra

J. Sol. Energy Eng. August 2023, 145(4): 041002.

Paper No: SOL-22-1144

DOI: https://doi.org/10.1115/1.4056122

Published Online: November 25, 2022

...) were computed using deep neural networks with 1-dimensional convolutional neural network (CNN-1D), long short-term memory (LSTM), and CNN-LSTM layers on the benchmarking dataset FOLSOM, which is formed by predictors obtained by recursive functions on the clear sky index time series and statistical...

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Topics: Artificial neural networks, Errors, Molecular beam epitaxy, Solar radiation, Time series, Solar energy

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Short-Term Solar Irradiance Forecasting Using CNN-1D, LSTM, and CNN-LSTM Deep Neural Networks: A Case Study With the Folsom (USA) Dataset

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Short-Term Solar Irradiance Forecasting Using CNN-1D, LSTM, and CNN-LSTM Deep Neural Networks: A Case Study With the Folsom (USA) Dataset

Journals

Conference Proceedings

eBooks

Resources

Opportunities

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