Design and Parametric Investigation of an Efficient Heating System, an Effort to Obtain a Higher Seasonal Performance Factor

Abstract

The present work introduces an innovative yet feasible heating system consisting of a ground source heat pump, borehole thermal energy storage, an auxiliary heater, radiators, and ventilation coils. The concept is developed by designing a new piping configuration monitored by a smart control system to reduce the return flow temperature and increase the temperature differential between the supply and return flows. The radiators and ventilation heating circuits are connected in series to provide the heat loads with the same demand. The investigation of the proposed model is performed through developed Python code considering a case study hospital located in Norway. The article presents, after validation of the primary heating system installed in the hospital, a parametric investigation to evaluate the effect of main operational parameters on the performance metrics of both the heat pump and the total system. According to the results, the evaporator temperature is a significant parameter that considerably impacts the system performance. The parametric study findings show that the heat pumps with a thermal capacity of 400 kW and 600 kW lead to the highest heat pump and total seasonal performance factors, respectively. It is also observed that increasing the heat pump capacity does not affect the performance indicators when the condensation temperature is 40 °C and the heat recovery is 50%. Moreover, choosing a heat pump with a smaller capacity at the heat recovery of 75% (or higher) would be an appropriate option because the seasonal performance values are not varied by changing the heat pump capacity. The results reveal that reducing return temperature under a proper parameters selection results in substantially higher seasonal performance factors of the heat pump and total system. These outcomes are in-line with the United Nations sustainable development goals including Sustainable Cities and Communities.

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“…Harsem et al [25] proposed a heating system for a hospital consisting of a ground source heat pump, gas boiler, borehole thermal energy storage, hydronic radiators, and an air handling unit. Calculations, performed in a developed simulation tool, allowed the selection of thermal capacity of heat pumps for their highest seasonal performance effectiveness.…”

Using Artificial Neural Networks to Gather Intelligence on a Fully Operational Heat Pump System in an Existing Building Cluster

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