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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

... to voltage fluctuation, power quality, and electrical grid stability can be avoided by performing solar irradiance forecasts. In this sense, several methodologies have been used to forecast solar irradiance for different time horizons, like numerical weather prediction (NWP) models, time series analysis...

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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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