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Generative AI for Energy: Multi-Horizon Power Consumption Forecasting using Large Language Models

Published: 21 October 2024 Publication History

Abstract

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.

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    cover image ACM Conferences
    CIKM '24: Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
    October 2024
    5705 pages
    ISBN:9798400704369
    DOI:10.1145/3627673
    This work is licensed under a Creative Commons Attribution International 4.0 License.

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    Published: 21 October 2024

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    Author Tags

    1. power consumption forecasting
    2. time series
    3. transformers

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    • REACT-EU project, PON 2014-2020 AZIONE IV.6 GREEN

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