Deep Learning for Time-Series Forecasting With Exogenous Variables in Energy Consumption: A Performance and Interpretability Analysis

Deep Learning for Time-Series Forecasting With Exogenous Variables in Energy Consumption: A Performance and Interpretability Analysis

The rise of decentralized energy sources and renewables demands advanced grid planning, with short-term load forecasting (STLF) playing a crucial role. Energy demand in smart grids is highly variable and influenced by external factors, making accurate forecasting challenging. While deep learning mod...

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Bibliographic Details
Main Authors: Ava Mohammadi, Gonzalo Napoles, Yamisleydi Salgueiro
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Deep learning
explainable AI
interpretability
short-term load forecasting
time series forecasting
Online Access:https://ieeexplore.ieee.org/document/11005580/
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https://ieeexplore.ieee.org/document/11005580/

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