Forecasting PV energy generation using transformer-based architectures: A comparative study of Lag-Llama, TFT, and DeepAR
author
statement of authorship
Furqan Amjad, Tarmo Korotko, Argo Rosin
publisher
year of publication
pages
6 p
conference name, date
2024 IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), 10-12 October 2024
conference location
Riga, Latvia
ISBN
979-8-3503-6576-4
notes
Bibliogr.: 19 ref
scientific publication
teaduspublikatsioon
TTÜ department
language
inglise
subject term
keyword
photovoltaic energy forecasting
transformer-based models
temporal fusion transformer
Lag-Llama
DeepAR
classifier
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.