Generative AI for Energy: Multi-Horizon Power Consumption Forecasting using Large Language Models
We leverage generative NLP-based models, specifically Transformer-Based models, for multi-horizon univariate and multivariate power consumption forecasting. We apply our approach to various datasets, focusing on short-term (1 day) and long-term (1 week) forecasts. We test several lag configurations with and without additional contextual information and achieve promising results. We evaluate the forecasts' effectiveness using a range of metrics, and aggregate the results on a monthly basis for a comprehensive understanding of the performance throughout the year.
Authors
- Stefano Mizzaro (ORCID: https://orcid.org/0000-0002-2852-168X)
- Vincenzo Della Mea (ORCID: https://orcid.org/0000-0002-0144-3802)
- Kevin Roitero (ORCID: https://orcid.org/0000-0002-9191-3280)
- Gianluca D'Abrosca
- Andrea Zancola
Institutions
- University of Udine (IT)
Publication Details
- Published
- 2024-10-20
- DOI
- https://doi.org/10.1145/3627673.3679933
- Citations
- 2
- Primary Topic
- Energy Load and Power Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.42