Hygro-thermal model for estimation of demand response flexibility of closed refrigerated display cabinets. (15th February 2021)

• Record Type: Journal Article
• Authors: Månsson, Tommie; Sasic Kalagasidis, Angela; Ostermeyer, York
• Is Part Of: Applied energy. Volume 284(2021)
• Publication Date: 2021-02-15
• Subjects: Refrigerated display cabinet -- Supermarket -- Thermal modelling -- Food retail -- Energy efficiency -- Demand response -- Demand-side management -- Renewable energy -- Smart grid; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2020.116381
• Languages: English
• ISSNs: 0306-2619

Abstract

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. Highlights: Computationally efficient hygrothermal model of a refrigerated display cabinet. Predicts 5 min ahead temperature and heat extraction per RDC in less than 0.5 s. Can be run in two modes, for near-future demand predictions or for load shifting. Validation shows good conformity between measured and calculated results. The demand response flexibility of 11 hypothetical RDCs is between 17–322 s.