Focus of the text
The text describes a new solution with the potential to reduce the cost and CO2 production of energy companies. This is made possible operating existing ground source heat pump of buildings connected to the district heating and cooling network.
New study shows that a connection between buildings with ground source heat pump and district heating and cooling networks minimizes the energy cost for energy companies and building owners while maintaining a stable ground temperature. The study indicates that energy costs can be reduced by 644 tSEK per year and CO2 emissions reduced by 92 tons per year.
District heating and cooling networks and ground source heat pumps are popular sustainable heating options in Sweden. Ground source heat pumps are often seen as a competitor by district heating networks. However, this study shows that integrating the two solutions and operating the ground source heat pumps in cooperation with the district heating and cooling networks can benefit both the district heating and cooling company and the building owners. This is demonstrated in a case study of a hospital area in Umeå, Sweden, using a validated model of the heating and cooling system. It was shown that the operation energy cost of Umeå Energi can be reduced by 644 tSEK per year while reducing the CO2 emissions by 92 tons per year.
Space heating and cooling accounts for more than 25% of the total energy use in Europe. An efficient sustainable heating and cooling will help to increase energy security, cut costs and reduce greenhouse gas emissions. Two thirds of Sweden’s heating and cooling comes from renewable sources, which is the highest among the EU member states. The use of district heating and heat pumps has enabled Sweden to achieve a high percentage of renewable heating and cooling.
District networks distribute heat generated at central production units. Large central production units can utilize of renewable heat sources that individual heating system cannot. For example, District heating networks can use waste heat from industries. Heat pumps are also a sustainable heating option as a part of the heat provided by the heat pump comes from low temperature heat sources like air, ground, etc.
District heating and cooling is dominant in multi-family buildings and service sector buildings, while heat pumps are commonly used in single-family houses. In recent years, due to increasing building efficiency and improvements in heat pumps, heat pumps are being used in multi-family and service sector buildings, especially ground source heat pumps (GSHP). Hence, GSHP’s are considered as a competitor for district heating and cooling networks. Due to the high investment cost of GSHP they are often used in combination with other heat sources. In urban and suburban areas district heating and cooling is a good choice for a supplementary heat for GSHP. GSHP’s connects the electrical, heating and cooling networks hence if the energy companies cooperates with the GSHP operator the GSHP can increase the flexibility of the energy system.
However, a few concerns must be addressed to operate the system with GSHP and DHC to operate beneficially. A non-optimal distribution of load between the GHSP and the district heating and cooling network might increase the cost of the energy company and/or the building owner. An additional concern for the building owner is the long-term stability of the GSHP. The GSHP extracts and/or injects heat into the ground, which can accumulate over the years and change the temperature of the ground, which reduces the efficiency of the GSHP.
In this study, these concerns were addressed by developing accurate models for the GSHP, using a combination of data driven and analytical models. The main components of a GSHP are borehole heat exchangers and heat pumps. A hybrid analytical-artificial neural network model was developed to represent borehole heat exchangers and an artificial neural network model to represent heat pumps. The models were used to determine the distribution of heating and cooling loads between the GSHP and DHC network. The study demonstrates how to distribute the load to minimize the energy cost from the perspective of the energy company while maintaining a stable ground temperature.
The models and methods developed in this study were demonstrated for a case study of a hospital area in Umeå, Sweden. The hospital buildings have a large GSHP and are connected to the district heating and cooling network. The GSHP supplies around 92% of the cooling and 15% of the heating to the hospital. The GSHP consists of 125 boreholes and 3 heat pumps. The boreholes are used to store excess cold from the heat pumps in winter and for free cooling and storing excess heat from the heat pumps in the summer. The model of the GSHP was developed and validated using 4 years of field measurements from the GSHP. The validated model was then used to optimize the hourly distribution of heating and cooling load between the GSHP and district heating and cooling network. The results showed that changing the distribution of load will reduce the operating cost of Umeå Energi by 64 t€ and the annual CO2 will reduce by 92 tons. Moreover, the model predicted that temperature of the ground would increase by 120C if the current operation was continued for 50 years, while the temperature of the ground will remain stable using the load distribution suggested in the study.
The results of the study shows that the cost and CO2 production of the energy company can be reduced using customers with GSHP and district heating and cooling. Therefore, the energy company should consider cooperating with the building owner to benefit from it. The building owners can also benefit from the cooperation by ensuring the sustainability of the GSHP and by developing a prosumer relationship with the energy company. This study also contributed to the field of GSHPs and district heating and cooling by developing methods to determine the optimal operation of such systems.
- Heating and cooling
- Technical solutions
Article with the main results: https://doi.org/10.1016/j.enbuild.2022.112065