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Modeling Supermarket Refrigeration Systems for Demand-Side Management

Author

Listed:
  • S. Ehsan Shafiei

    () (Department of Electronic Systems, Automation and Control, Aalborg University, Aalborg, Denmark)

  • Henrik Rasmussen

    () (Department of Electronic Systems, Automation and Control, Aalborg University, Aalborg, Denmark)

  • Jakob Stoustrup

    () (Department of Electronic Systems, Automation and Control, Aalborg University, Aalborg, Denmark)

Abstract

Modeling of supermarket refrigeration systems for supervisory control in the smart grid is presented in this paper. A modular modeling approach is proposed in which each module is modeled and identified separately. The focus of the work is on estimating the power consumption of the system while estimating the cold reservoir temperatures as well. The models developed for each module as well as for the overall integrated system are validated by real data collected from a supermarket in Denmark. The results show that the model is able to estimate the actual electrical power consumption with a high fidelity. Moreover a simulation benchmark is introduced based on the produced model for demand-side management in smart grid. Finally, a potential application of the proposed benchmark in direct control of the power/energy consumption is presented by a simple simulation example.

Suggested Citation

  • S. Ehsan Shafiei & Henrik Rasmussen & Jakob Stoustrup, 2013. "Modeling Supermarket Refrigeration Systems for Demand-Side Management," Energies, MDPI, Open Access Journal, vol. 6(2), pages 1-21, February.
  • Handle: RePEc:gam:jeners:v:6:y:2013:i:2:p:900-920:d:23546
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    Citations

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    Cited by:

    1. Rasmussen, Lisa Buth & Bacher, Peder & Madsen, Henrik & Nielsen, Henrik Aalborg & Heerup, Christian & Green, Torben, 2016. "Load forecasting of supermarket refrigeration," Applied Energy, Elsevier, vol. 163(C), pages 32-40.
    2. Postnikov, A. & Albayati, I.M. & Pearson, S. & Bingham, C. & Bickerton, R. & Zolotas, A., 2019. "Facilitating static firm frequency response with aggregated networks of commercial food refrigeration systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    3. Biegel, Benjamin & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Value of flexible consumption in the electricity markets," Energy, Elsevier, vol. 66(C), pages 354-362.
    4. Rubén De Diego & José-Fernán Martínez & Jesús Rodríguez-Molina & Alexandra Cuerva, 2014. "A Semantic Middleware Architecture Focused on Data and Heterogeneity Management within the Smart Grid," Energies, MDPI, Open Access Journal, vol. 7(9), pages 1-42, September.
    5. Frank Bruno & Martin Belusko & Edward Halawa, 2019. "CO 2 Refrigeration and Heat Pump Systems—A Comprehensive Review," Energies, MDPI, Open Access Journal, vol. 12(15), pages 1-39, August.
    6. Biegel, Benjamin & Westenholz, Mikkel & Hansen, Lars Henrik & Stoustrup, Jakob & Andersen, Palle & Harbo, Silas, 2014. "Integration of flexible consumers in the ancillary service markets," Energy, Elsevier, vol. 67(C), pages 479-489.

    More about this item

    Keywords

    refrigeration systems; modeling; smart grid; supervisory control;

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q41 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Demand and Supply; Prices
    • Q42 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Alternative Energy Sources
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q48 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Government Policy
    • Q49 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Other

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