A Modelica Toolbox for the Simulation of Borehole Thermal Energy Storage Systems

Julian Formhals, Hoofar Hemmatabady, Bastian Welsch, Daniel Otto Schulte and Ingo Sass
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Julian Formhals: Geothermal Science and Technology, Technical University of Darmstadt, Schnittspahnstraße 9, 64287 Darmstadt, Germany
Hoofar Hemmatabady: Geothermal Science and Technology, Technical University of Darmstadt, Schnittspahnstraße 9, 64287 Darmstadt, Germany
Bastian Welsch: Geothermal Science and Technology, Technical University of Darmstadt, Schnittspahnstraße 9, 64287 Darmstadt, Germany
Daniel Otto Schulte: Geothermal Science and Technology, Technical University of Darmstadt, Schnittspahnstraße 9, 64287 Darmstadt, Germany
Ingo Sass: Geothermal Science and Technology, Technical University of Darmstadt, Schnittspahnstraße 9, 64287 Darmstadt, Germany

Energies, 2020, vol. 13, issue 9, 1-23

Abstract: 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.

Keywords: borehole thermal energy storage; Modelica; district heating; borehole heat exchanger; thermal resistance capacity model; model reduction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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