Long Short-Term Memory Autoencoder and Extreme Gradient Boosting-Based Factory Energy Management Framework for Power Consumption Forecasting

Electricity consumption prediction is crucial for the operation, strategic planning, and maintenance of power grid infrastructure. The effective management of power systems depends on accurately predicting electricity usage patterns and intensity. This study aims to enhance the operational efficienc...

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Bibliographic Details
Published in:	Energies (Basel) Vol. 17; no. 15; p. 3666
Main Authors:	Moon, Yeeun, Lee, Younjeong, Hwang, Yejin, Jeong, Jongpil
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.08.2024
Subjects:	deep learning Electric power systems electricity consumption prediction Energy consumption Energy efficiency Energy management systems Energy use extreme gradient boosting Factories factory energy management system Green technology Infrastructure (Economics) long short-term memory autoencoder Manufacturing Marketing research South Korea South Korea
ISSN:	1996-1073, 1996-1073
Online Access:	Get full text
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