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Hygro-thermal model for estimation of demand response flexibility of closed refrigerated display cabinets

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  • Månsson, Tommie
  • Sasic Kalagasidis, Angela
  • Ostermeyer, York

Abstract

In this article we present and validate a novel methodology for estimating the temperature development and heat extraction demand of closed refrigerated display cabinets (RDCs) in operating conditions, for near-future prediction and optimisation in smart grids. The approach is based on an in-house developed hygro-thermal model of an RDC, in which the conditions in each of the three main calculation domains, representing the internal air, heat exchanger and interior, are estimated at a temporal scale of seconds. The interior air temperature, heat extraction rate and run-off condensate were validated towards experimental data with good conformity. Moreover, for demand response purposes, in this article, we provide examples of how the model can be used to evaluate the temporal flexibility in heat extraction demand of RDCs. In a hypothetical supermarket with 11 RDCs exposed to various thermal loads and customer interactions, it is estimated that the heat extraction demand could be reduced to 0 for up to 83∕127 s during opening/non-opening hours respectively. With a strategic pre-cooling, the latter time could be extended to 322 s. For the case of a demand response signal requesting the supermarket to absorb excess energy, all RDCs would be able to run at full power for up to 17∕29 s, and approximately half of them for additional 20 s during opening hours. These findings are based on a total of 44 five-minutes-ahead simulations of possible scenarios for the 11 RDCs, all calculated by the presented model in approximately 10 s. In conclusion, the model provides fast and reliable results for real-time predictions in refrigeration control systems either for the benefit of the electrical grid by demand response or for energy efficiency purposes.

Suggested Citation

  • Månsson, Tommie & Sasic Kalagasidis, Angela & Ostermeyer, York, 2021. "Hygro-thermal model for estimation of demand response flexibility of closed refrigerated display cabinets," Applied Energy, Elsevier, vol. 284(C).
  • Handle: RePEc:eee:appene:v:284:y:2021:i:c:s0306261920317554
    DOI: 10.1016/j.apenergy.2020.116381
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    References listed on IDEAS

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    1. Li, Jinghua & Fang, Jiakun & Zeng, Qing & Chen, Zhe, 2016. "Optimal operation of the integrated electrical and heating systems to accommodate the intermittent renewable sources," Applied Energy, Elsevier, vol. 167(C), pages 244-254.
    2. Spiliotis, Konstantinos & Ramos Gutierrez, Ariana Isabel & Belmans, Ronnie, 2016. "Demand flexibility versus physical network expansions in distribution grids," Applied Energy, Elsevier, vol. 182(C), pages 613-624.
    3. O׳Connell, Niamh & Pinson, Pierre & Madsen, Henrik & O׳Malley, Mark, 2014. "Benefits and challenges of electrical demand response: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 686-699.
    4. Siiri Söyrinki & Eva Heiskanen & Kaisa Matschoss, 2018. "Piloting Demand Response in Retailing: Lessons Learned in Real-Life Context," Sustainability, MDPI, vol. 10(10), pages 1-17, October.
    5. Wang, Xiaonan & Palazoglu, Ahmet & El-Farra, Nael H., 2015. "Operational optimization and demand response of hybrid renewable energy systems," Applied Energy, Elsevier, vol. 143(C), pages 324-335.
    6. Kohlhepp, Peter & Harb, Hassan & Wolisz, Henryk & Waczowicz, Simon & Müller, Dirk & Hagenmeyer, Veit, 2019. "Large-scale grid integration of residential thermal energy storages as demand-side flexibility resource: A review of international field studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 527-547.
    7. Chang, Martin K. & Eichman, Joshua D. & Mueller, Fabian & Samuelsen, Scott, 2013. "Buffering intermittent renewable power with hydroelectric generation: A case study in California," Applied Energy, Elsevier, vol. 112(C), pages 1-11.
    8. Neves, Diana & Pina, André & Silva, Carlos A., 2018. "Assessment of the potential use of demand response in DHW systems on isolated microgrids," Renewable Energy, Elsevier, vol. 115(C), pages 989-998.
    9. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    10. Zehir, Mustafa Alparslan & Batman, Alp & Bagriyanik, Mustafa, 2016. "Review and comparison of demand response options for more effective use of renewable energy at consumer level," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 631-642.
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