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Energy analysis and optimization of a food defrosting system

Authors :
Cédric Damour
Merouane Hamdi
Lionel Boillereaux
C. Josset
Bruno Auvity
Laboratoire d'Energétique, d'Electronique et Procédés (LE2P)
Université de La Réunion (UR)
Laboratoire de thermocinétique [Nantes] (LTN)
Centre National de la Recherche Scientifique (CNRS)-Université de Nantes (UN)
Laboratoire de génie des procédés - environnement - agroalimentaire (GEPEA)
Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST)
Université de Nantes (UN)-Université de Nantes (UN)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)
Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS)-Ecole Polytechnique de l'Université de Nantes (EPUN)
Université de Nantes (UN)-Université de Nantes (UN)-Institut Universitaire de Technologie - Nantes (IUT Nantes)
Université de Nantes (UN)-Institut Universitaire de Technologie Saint-Nazaire (IUT Saint-Nazaire)
Université de Nantes (UN)-Institut Universitaire de Technologie - La Roche-sur-Yon (IUT La Roche-sur-Yon)
Université de Nantes (UN)-Ecole Nationale Vétérinaire, Agroalimentaire et de l'alimentation Nantes-Atlantique (ONIRIS)-Université Bretagne Loire (UBL)
Source :
Energy, Energy, Elsevier, 2012, 37 (1), pp.562--570. ⟨10.1016/j.energy.2011.10.048⟩
Publication Year :
2012
Publisher :
HAL CCSD, 2012.

Abstract

International audience; This paper illustrates the benefits of two energy optimization strategies to improve the overall process efficiency of a food defrosting system. First, an off-line energy analysis, including both the effects of the refrigeration cycle and the fan used to control the cooling air temperature and speed, is carried-out. This first approach puts on display an optimal running point of the process for a specific cooling air temperature value, which leads to an optimization of the overall energy consumption. Second, an on-line energy optimization approach, based on a nonlinear model-based predictive control strategy, is developed. This second approach takes simultaneously into account the expected thawing time, the highest temperature accepted and above all an energetic cost. Simulation results show the benefits of this on-line energy optimization to significantly increase the overall process efficiency. Indeed, this strategy leads to an optimization of the overall energy consumption whatever the expected thawing time and the inlet air temperature.

Details

Language :
English
ISSN :
03605442
Database :
OpenAIRE
Journal :
Energy, Energy, Elsevier, 2012, 37 (1), pp.562--570. ⟨10.1016/j.energy.2011.10.048⟩
Accession number :
edsair.doi.dedup.....a8af27410c5a38beeedc7ecb03d741a5
Full Text :
https://doi.org/10.1016/j.energy.2011.10.048⟩