Conference Year

July 2018


Dynamic Modeling, Modelica, Comfort, Thermosiphon, Heat Pump


Buildings consume about two-fifths of the primary energy in the United States with space heating and cooling taking up one-third of that fraction. Global warming and the associated climate changes have necessitated a rethinking of our energy consumption patterns. Roving Comforter (RoCo) is one such technology being developed with this objective. It enables buildings to save 10-30% of HVAC (Heating, Ventilating, and Air Conditioning) loads by enabling elevation of temperature set-points without compromising occupant comfort. The cooling operation involves an R134a vapor compression cycle operation, which stores the condenser heat into a phase change material (PCM) based thermal storage. Previous studies focused on enhancing the PCM to reduce the recharge time by thermosiphon operation by 40% without a significant increase in the weight of the thermal storage. This enhanced PCM storage needs to be recharged before the next cooling operation, which may be conducted in two different ways. A gravity-assisted two-phase thermosiphon operation consumes very less power but takes a longer recharge time (6 hours) in comparison to a reverse heat pump operation which consumes more power in a much shorter operation time (2.5 hours). The current article uses a validated dynamic models of thermosiphon and heat pump in Modelica to evaluate the overall coefficient of performance for combined cooling and recharge operations. Reduced recharge time from the heat pump recharge leads to increased frequency of the cooling operation enabling savings on building HVAC energy. All these factors are considered in making design recommendations for future prototypes of RoCo, which will save additional energy and provide longer cooling operation to the current prototypes. The modeling framework discussed in the article being generic may be used by researchers investigating vapor compression cycle integration strategies with PCM thermal storages. The article provides interesting insights and quantification of benefits obtained from various strategies adopted for improvement over the first prototype.