Borehole thermal energy storage (BTES) systems facilitate the subsurface seasonal storage of thermal energy on district heating scales. These systems’ performances are strongly dependent on operational conditions like temperature levels or hydraulic circuitry. Preliminary numerical system simulations improve comprehension of the storage performance and its interdependencies with other system components, but require both accurate and computationally efficient models. This study presents a toolbox for the simulation of borehole thermal energy storage systems in Modelica. The storage model is divided into a borehole heat exchanger (BHE), a local, and a global sub-model. For each sub-model, different modeling approaches can be deployed. To assess the overall performance of the model, two studies are carried out: One compares the model results to those of 3D finite element method (FEM) models to investigate the model’s validity over a large range of parameters. In a second study, the accuracies of the implemented model variants are assessed by comparing their results to monitoring data from an existing BTES system. Both studies prove the validity of the modeling approaches under investigation. Although the differences in accuracy for the compared variants are small, the proper model choice can significantly reduce the computational effort.

Borehole thermal energy storage (BTES) systems are a viable option to meet the increasing cooling demand and to increase the sustainability of low-temperature district heating and cooling (DHC) grids. They are able to store the rejected heat of cooling cycles on a seasonal basis and deliver this heat during the heating season. However, their efficient practical implementation requires a thorough analysis from technical, economic and environmental points of view. In this comparative study, a dynamic exergoeconomic assessment is adopted to evaluate various options for integrating such a storage system into 4th generation DHC grids in heating dominated regions. For this purpose, different layouts are modeled and parameterized. Multi-objective optimization is conducted, varying the most important design variables in order to maximize exergetic efficiency and to minimize levelized cost of energy (LCOE). A comparison of the optimal designs of the different layouts reveals that passive cooling together with maximizing the heating temperature shift, accomplished by a heat pump, lead to optimal designs. Component-wise exergy and cost analysis of the most efficient designs highlights that heat pumps are responsible for the highest share in inefficiency while the installation of BTES has a high impact in the LCOE. BTES and buffer storage tanks have the lowest exergy destruction for all layouts and increasing the BTES volume results in more efficient DHC grids.

Space heating applications account for a high share of global greenhouse gas emissions. To increase the renewable share of heat generation, seasonal thermal energy storage (STES) can be used to make thermal energy from fluctuating renewable sources available in times of high demand. A popular STES technology is pit thermal energy storage (PTES), where heat is stored underground, using water as a storage medium. To evaluate the use of PTES in an energy system, easily adaptable, publicly accessible and tool independent models are needed. In this paper, we improve an existing PTES model developed in the Modelica modeling language. The model is cross-compared with a more detailed and previously validated COMSOL model, considering different amounts of insulation, showing a deviation of 2–13% in the observed annual charged and discharged amount of heat. The results indicate that the presented model is well suited for early design stage and an exemplary case study is performed to demonstrate its applicability in a system context. Dimensions of system components are optimized for the levelized cost of heat (LCOH), both with and without subsidies, highlighting the importance of subsidies for the transition towards climate friendly heating solutions, as the gas boiler use is reduced from 47.6% to 2.7%.

Integration of borehole heat exchangers (BHE) into district heating (DH) should be supported by numerical simulations to ensure efficient operation. Co-simulation allows for the use of dedicated software for above and below ground sub-models, facilitating the use of detailed 3D geological models. This paper presents a methodology for coupling DH models in Modelica to 3D FEM subsurface models. An interface which implements BHE models in Modelica and one with BHE models in the FEM model are compared to a benchmark model. Furthermore, an adaptive control of the communication steps reduces communication error and computational times simultaneously. A fictional solar DH system with underground thermal energy storage is co-simulated to demonstrate potential advantages of the proposed method. Overall, co-simulation of DH systems and BHE arrays facilitates accurate performance assessment of systems for which this would not be possible otherwise, but should be applied carefully, due to the increased computational effort.