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.
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