Journal
JOURNAL OF PROCESS CONTROL
Volume 24, Issue 6, Pages 750-762Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jprocont.2013.10.005
Keywords
Non-residential building; Energy consumption; Zoned HVAC system; Thermal comfort; Artificial Neural Networks; Model predictive control
Funding
- Pyrescom company
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In France, non-residential buildings account for a significant part of energy consumption. A large part of this consumption is due to HVAC (Heating, Ventilation and Air-Conditioning) systems, which are in most cases poorly handled. The present work deals with an efficient approach allowing energy consumption to be minimized while still ensuring thermal comfort. We propose a predictive control strategy for existing zoned HVAC systems and consider the PMV (Predicted Mean Vote) index as a thermal comfort indicator. In order to test this strategy, we modelled a non-residential building located in Perpignan (south of France) using the EnergyPlus software. The twofold aim is to limit the times during which the HVAC sub-systems are turned on and to ensure a satisfactory thermal comfort when people are working in the considered building. This predictive approach, computationally tractable, allows thermal comfort requirements to be met without wasting energy. (C) 2013 Elsevier Ltd. All rights reserved.
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