Forecasting PV energy generation using transformer-based architectures: A comparative study of Lag-Llama, TFT, and DeepAR
autor
vastutusandmed
Furqan Amjad, Tarmo Korotko, Argo Rosin
kirjastus/väljaandja
ilmumisaasta
leheküljed
6 p
konverentsi nimetus, aeg
2024 IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), 10-12 October 2024
konverentsi toimumispaik
Riga, Latvia
ISBN
979-8-3503-6576-4
märkused
Bibliogr.: 19 ref
teaduspublikatsioon
teaduspublikatsioon
TTÜ struktuuriüksus
keel
inglise
võtmesõna
photovoltaic energy forecasting
transformer-based models
temporal fusion transformer
Lag-Llama
DeepAR
klassifikaator
Amjad, F., Korõtko, T., Rosin, A. Forecasting PV energy generation using transformer-based architectures: A comparative study of Lag-Llama, TFT, and DeepAR // 2024 IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON). : IEEE, 2024. 6 p. https://doi.org/10.1109/RTUCON62997.2024.10830763