Modeling and optimization of hybrid ground source heat pump with district heating and cooling

Hybrid heating systems with ground source heat pumps (GSHP) and district heating and cooling offer flexibility in operation to both building owners and energy providers. The flexibility can be used to make the heating system more economical and environmentally friendly. However, due to the lack of suitable models that can accurately predict the long-term performance of the GSHP, there is uncertainty in their performance and concerns about the long-term stability of the ground temperature, which has limited the utilization of such hybrid heating systems. This work presents a hybrid model of a GSHP system that uses analytical and artificial neural network models to accurately represent a GSHP system's long-term behavior. A method to improve the operation of a hybrid GSHP is also presented. The method was applied to hospital buildings in northern Sweden. It was shown that in the improved case, the cost of providing heating to the building can be reduced by 64 t euro , and the CO2 emissions can be reduced by 92 tons while maintaining a stable ground temperature. (c) 2022 The Author(s). Published by Elsevier B.V.

Automated summary

This paper introduces a hybrid model that accurately represents the long-term behavior of a GSHP system using analytical and artificial neural network models, as well as a method to improve the operation of a hybrid GSHP. The study on hospital buildings in northern Sweden shows that in the improved scenario, heating costs can be reduced, CO2 emissions can be decreased, while maintaining stable ground temperature.