Aquifer thermal energy storage (ATES) combined with ground-source heat pumps (GSHP) offer an attractive technology to match supply and demand by efficiently recycling heating and cooling loads. This study analyses the integration of the ATES–GSHP system in both district heating and cooling networks of an urban district in southwestern Finland, in terms of technoeconomic feasibility, efficiency, and impact on the aquifer area. A novel mathematical modeling for GSHP operation and energy system management is proposed and demonstrated, using hourly data for heating and cooling demand. Hydrogeological and geographic data from different Finnish data sources is retrieved in order to calibrate and validate a groundwater model. Two different scenarios for ATES operation are investigated, limited by the maximum pumping flow rate of the groundwater area. The additional precooling exchanger in the second scenario resulted in an important advantage, since it increased the heating and cooling demand covered by ATES by 13% and 15%, respectively, and decreased the energy production cost by 5.2%. It is concluded that dispatching heating and cooling loads in a single operation, with annually balanced ATES management in terms of energy and pumping flows resulted in a low long-term environmental impact and is economically feasible (energy production cost below 30 €/MWh).

Aalto New Campus Complex (ANCC) is a recently inaugurated educational facility at Aalto University, located in Otaniemi (Espoo), Finland. Within over 40,000 m², it comprises two faculties, a shopping center, recreational areas, and a metro station. ANCC is also a large-scale application of Ground Source Heat Pump (GSHP)–Borehole Thermal Energy Storage (BTES) in Finland, comprising an irregular BTES field of 74 boreholes with an overall length of roughly 23 km and 4 million m³ of energy storage. Therefore, accurate monitoring of the GSHP–BTES energy system is crucial for sustainable and efficient long-term operation. Due to the fundamental issues affecting the accuracy of all thermal energy meters, a novel methodology adjusting for consistency of the measured data (in order to accomplish daily energy balance on both sides of the GSHP) is developed. The proposed methodology is used also in conjunction with reconstruction of missing relevant data before April/May 2020 by applying linear regression techniques. The developed data management is considered essential due to its capability to handle measured data with high uncertainty (thermal meters) by using highly accurate data regarding the GSHP power demand. Additionally, operational data and relevant GSHP performance indicators for the 18-month period starting from July 2019 is presented and analyzed.

Groundwater-filled boreholes are a common solution in Scandinavian installations of ground source heat pumps (GSHP) due to the particular hydro-geological conditions with existing bedrock, and groundwater levels close to the surface. Different studies have highlighted the advantage of water-filled boreholes compared with their grouted counterparts since the natural convection of water within the borehole tends to decrease the effective thermal resistance R_b*. In this study, several methods are proposed for the evaluation and modeling of the effective thermal resistance of groundwater-filled boreholes. They are based on distributed temperature sensing (DTS) measurements of six representative boreholes within the irregular 74-single-U 300 m-deep borehole field of Aalto New Campus Complex (ANCC). These methods are compared with the recently developed correlations for groundwater-filled boreholes, which are implemented within the python-based simulation toolbox Pygfunction. The results from the enhanced Pygfunction simulation with daily update of R_b* show very good agreement with the measured mean fluid temperature of the first 39 months of system operation (March 2018–May 2021). It is observed that in real operation the effective thermal resistance R_b* can vary significantly, and therefore it is concluded that the update of R_b* is crucial for a reliable long-term simulation of groundwater-filled boreholes.