Potential Analysis of the Attention-Based LSTM Model in Ultra-Short-Term Forecasting of Building HVAC Energy Consumption

Potential Analysis of the Attention-Based LSTM Model in Ultra-Short-Term Forecasting of Building HVAC Energy Consumption

Predicting system energy consumption accurately and adjusting dynamic operating parameters of the HVAC system in advance is the basis of realizing the model predictive control (MPC). In recent years, the LSTM network had made remarkable achievements in the field of load forecasting. This paper aimed...

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Bibliographic Details
Main Authors:	Yang Xu, Weijun Gao, Fanyue Qian, Yanxue Li
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2021-08-01
Series:	Frontiers in Energy Research
Subjects:	energy consumption prediction ultra-short-term forecast deep learning LSTM network attention mechanism
Online Access:	https://www.frontiersin.org/articles/10.3389/fenrg.2021.730640/full

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