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Energy analysis and optimization of a food defrosting system

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  • Damour, C.
  • Hamdi, M.
  • Josset, C.
  • Auvity, B.
  • Boillereaux, L.

Abstract

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.

Suggested Citation

  • Damour, C. & Hamdi, M. & Josset, C. & Auvity, B. & Boillereaux, L., 2012. "Energy analysis and optimization of a food defrosting system," Energy, Elsevier, vol. 37(1), pages 562-570.
    • Handle: RePEc:eee:energy:v:37:y:2012:i:1:p:562-570
    DOI: 10.1016/j.energy.2011.10.048
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    References listed on IDEAS

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    1. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Improving energy use efficiency of canola production using data envelopment analysis (DEA) approach," Energy, Elsevier, vol. 36(5), pages 2765-2772.
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    4. Mousavi-Avval, Seyed Hashem & Rafiee, Shahin & Jafari, Ali & Mohammadi, Ali, 2011. "Optimization of energy consumption for soybean production using Data Envelopment Analysis (DEA) approach," Applied Energy, Elsevier, vol. 88(11), pages 3765-3772.
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    Cited by:

    1. Papasidero, Davide & Pierucci, Sauro & Manenti, Flavio, 2016. "Energy optimization of bread baking process undergoing quality constraints," Energy, Elsevier, vol. 116(P2), pages 1417-1422.
    2. Bhattacharya, Madhuchhanda & Basak, Tanmay, 2013. "A theoretical study on the use of microwaves in reducing energy consumption for an endothermic reaction: Role of metal coated bounding surface," Energy, Elsevier, vol. 55(C), pages 278-294.
    3. Qi Siah & Haslinda Zabiri, 2022. "Modeling and Optimization of Water–Food–Energy Nexus for Malaysia’s Agricultural Sector," Sustainability, MDPI, vol. 14(3), pages 1-31, February.
    4. Bhattacharya, Madhuchhanda & Basak, Tanmay, 2016. "A review on the susceptor assisted microwave processing of materials," Energy, Elsevier, vol. 97(C), pages 306-338.
    5. Alamir, M. & Witrant, E. & Della Valle, G. & Rouaud, O. & Josset, Ch. & Boillereaux, L., 2013. "Estimation of energy saving thanks to a reduced-model-based approach: Example of bread baking by jet impingement," Energy, Elsevier, vol. 53(C), pages 74-82.

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