Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Modeling and optimization of hybrid ground source heat pump with district heating and cooling
https://orcid.org/0000-0001-7349-1873
https://orcid.org/0000-0002-8704-8538
Highlights A hybrid analytical ANN model for a GSHP. The model was validated using four years of monitored data. Operation of a heating system with GSHP and district heating and cooling optimized. Optimal operation reduces cost by 64 t€ and CO2 by 92 tons per year, while maintaining stable ground temperature.
Abstract 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€, and the CO2 emissions can be reduced by 92 tons while maintaining a stable ground temperature.
Modeling and optimization of hybrid ground source heat pump with district heating and cooling
https://orcid.org/0000-0001-7349-1873
https://orcid.org/0000-0002-8704-8538
Highlights A hybrid analytical ANN model for a GSHP. The model was validated using four years of monitored data. Operation of a heating system with GSHP and district heating and cooling optimized. Optimal operation reduces cost by 64 t€ and CO2 by 92 tons per year, while maintaining stable ground temperature.
Abstract 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€, and the CO2 emissions can be reduced by 92 tons while maintaining a stable ground temperature.
Modeling and optimization of hybrid ground source heat pump with district heating and cooling
https://orcid.org/0000-0001-7349-1873
https://orcid.org/0000-0002-8704-8538
Highlights A hybrid analytical ANN model for a GSHP. The model was validated using four years of monitored data. Operation of a heating system with GSHP and district heating and cooling optimized. Optimal operation reduces cost by 64 t€ and CO2 by 92 tons per year, while maintaining stable ground temperature.
Abstract 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€, and the CO2 emissions can be reduced by 92 tons while maintaining a stable ground temperature.
Modeling and optimization of hybrid ground source heat pump with district heating and cooling
Puttige, Anjan Rao (Autor:in) / Andersson, Staffan (Autor:in) / Östin, Ronny (Autor:in) / Olofsson, Thomas (Autor:in)
Energy and Buildings ; 264
26.03.2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Cost-Effective Control of Hybrid Ground Source Heat Pump (GSHP) System Coupled with District Heating
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