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This paper presents a validated simulation model for heat pump-based energy recycling systems, with a focus on heat recovery applications in grocery stores. Heat is recovered through heat pumps from a subcritical CO2-based refrigeration system, with exhaust air heat recovery used on demand according to the heating demand. The model is validated through a case study on a Finnish hypermarket-sized grocery store, where the heat pump system has been operational since 2020. Multi-objective energy optimization is used to validate the model by estimating critical decision variable values and providing error estimates compared to the measured data. The calibrated energy system model has a maximum mean bias error, MBE, of ±5% and a 10–15% coefficient of variation of root mean squared error, CV(RMSE), for the heat pump-related energy balance. Energy optimizations indicate that the control algorithm of the investigated heat pump system can be enhanced to reduce district heating consumption by 12%. The study emphasizes the need for numerous input parameters tailored to a system-specific layout to accurately reproduce the heat pump system’s control algorithm. Compared to a typical transcritical CO2 booster system with heat recovery, the novel heat recovery system shows superior heat recovery potential and a high total COP for both heating and cooling.
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Söderholm et al. (2025) studied this question.
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