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ANN-LSTM based tool for photovoltaic power forecasting

author
Zahraoui, Younes
Korõtko, Tarmo
Mekhilef, Saad
Rosin, Argo
statement of authorship
Younes Zahraoui, Tarmo Korõtko, Saad Mekhilef, Argo Rosin
source
2024 4th International Conference on Smart Grid and Renewable Energy (SGRE) : proceedings
location of publication
Danvers
publisher
IEEE
year of publication
2024
pages
6 p. : ill
conference name, date
4th International Conference on Smart Grid and Renewable Energy, (SGRE 2024), 8-10 January 2024
conference location
Doha, Qatar
url
https://doi.org/10.1109/SGRE59715.2024.10428969
subject term
sügavõpe
aegridade analüüs
tehisnärvivõrgud
prognostika
fotogalvaanika
taastuvenergia
keyword
deep learning (DL)
power forecasting
time series
long-short term memory
artificial neural networks (ANN)
ISBN
9798350306262
notes
Bibliogr.: 21 ref
scientific publication
teaduspublikatsioon
classifier
3.1
TalTech department
elektroenergeetika ja mehhatroonika instituut
Targa linna tippkeskus
language
inglise
Zahraoui, Y., Korotko, T., Mekhilef, S., Rosin, A. ANN-LSTM based tool for photovoltaic power forecasting // 2024 4th International Conference on Smart Grid and Renewable Energy (SGRE) : proceedings. Danvers : IEEE, 2024. 6 p. : ill. https://doi.org/10.1109/SGRE59715.2024.10428969