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Predictive Control Strategies based on Weather Forecast in Buildings with Energy Storage System: A Review of the State-of-the Art

Title:

Predictive Control Strategies based on Weather Forecast in Buildings with Energy Storage System: A Review of the State-of-the Art

Thieblemont, Hélène, Haghighat, Fariborz, Ooka, Ryozo and Moreau, Alain (2017) Predictive Control Strategies based on Weather Forecast in Buildings with Energy Storage System: A Review of the State-of-the Art. Energy and Buildings . ISSN 03787788 (In Press)

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Official URL: http://dx.doi.org/10.1016/j.enbuild.2017.08.010

Abstract

Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expanding the use of renewable energies in buildings and communities. To have a high system performance, the energy storage system has to be properly controlled while maintaining a comfortable thermal environment for the occupants. However, defining the optimal charging period for a storage system may be difficult since storage systems address issues with conflicting needs between cost saving and thermal comfort. Moreover, with the increase of the use of renewable energies, the complexity increases with the consideration of the renewable energy production. As a result, the decision process should be able to predict both loads and renewable energy production in order to increase the storage system efficiency. This necessity explains the increasing interest during the last decade for predictive control, i.e., control system considering the forecasting.

This paper reviews the recent advancements in building predictive control with energy storage system. Special attention is paid to its limitations and abilities.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Building, Civil and Environmental Engineering
Item Type:Article
Refereed:Yes
Authors:Thieblemont, Hélène and Haghighat, Fariborz and Ooka, Ryozo and Moreau, Alain
Journal or Publication:Energy and Buildings
Date:10 August 2017
Funders:
  • Natural Sciences and Engineering Research Council Canada (NSERC)
Digital Object Identifier (DOI):10.1016/j.enbuild.2017.08.010
Keywords:Storage; Predictive Control; Model Predictive Control; Weather Forecasting
ID Code:982794
Deposited By: DANIELLE DENNIE
Deposited On:17 Aug 2017 19:37
Last Modified:01 Aug 2018 00:00
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