Empirical Validation and Numerical Predictions of an Industrial Borehole Thermal Energy Storage System

Emil Nilsson and Patrik Rohdin
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Emil Nilsson: Department of Management and Engineering, Division of Energy Systems, Linköping University, SE 581 83 Linköping, Sweden
Patrik Rohdin: Department of Management and Engineering, Division of Energy Systems, Linköping University, SE 581 83 Linköping, Sweden

Energies, 2019, vol. 12, issue 12, 1-20

Abstract: To generate performance predictions of borehole thermal energy storage (BTES) systems for both seasonal and short-term storage of industrial excess heat, e.g., from high to low production hours, models are needed that can handle the short-term effects. In this study, the first and largest industrial BTES in Sweden, applying intermittent heat injection and extraction down to half-day intervals, was modelled in the IDA ICE 4.8 environment and compared to three years of measured storage performance. The model was then used in a parametric study to investigate the change in performance of the storage from e.g., borehole spacing and storage supply flow characteristics at heat injection. For the three-year comparison, predicted and measured values for total injected and extracted energy differed by less than 1% and 3%, respectively and the mean relative difference for the storage temperatures was 4%, showing that the performance of large-scale BTES with intermittent heat injection and extraction can be predicted with high accuracy. At the actual temperature of the supply flow during heat injection, 40 °C, heat extraction would not exceed approximately 100 MWh/year for any investigated borehole spacing, 1–8 m. However, when the temperature of the supply flow was increased to 60–80 °C, 1400–3100 MWh/year, also dependent on the flow rate, could be extracted at the spacing yielding the highest heat extraction, which in all cases was 3–4 m.

Keywords: borehole thermal energy storage; industrial excess heat; model validation; performance predictions; IDA ICE (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: 2019
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