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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Bibliografische Detailangaben

Hauptverfasser:	Ava Mohammadi, Gonzalo Napoles, Yamisleydi Salgueiro
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	IEEE 2025-01-01
Schriftenreihe:	IEEE Access
Schlagworte:	Deep learning explainable AI interpretability short-term load forecasting time series forecasting
Online-Zugang:	https://ieeexplore.ieee.org/document/11005580/
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