1887

Abstract

Summary

Aquifer thermal energy storage (ATES) systems are designed to recover in winter the heat stored in the aquifer during summer. In practice however, spatial heterogeneity or non-favorable hydrogeological conditions reduces the energy efficiency. In many cases, a deterministic approach is used to calibrate the subsurface component of those systems, neglecting the quantification of uncertainty. In this contribution, we propose to use the recently-developed prediction-focused approach to forecast the heat storage capacity of an alluvial aquifer. We compare the ability of two different push/pull tests to make this prediction. We first analyze the performance of the method using synthetic cases and validate the approach using field data. For both, we show that the method is able to forecast the posterior distribution with realistic uncertainty. We also identify the experiment which has the highest information content for the desired prediction. Then we forecast the long-term heat storage capacity of the aquifer and assess its uncertainty. This final result can be used to design properly the heat pump associated with the system.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201702136
2017-09-03
2024-03-29
Loading full text...

Full text loading...

References

  1. Blum, P., Campillo, G., & Kölbel, T.
    [2011]. Techno-economic and spatial analysis of vertical ground source heat pump systems in Germany. Energy, 36, 3002–3011.
    [Google Scholar]
  2. Hermans, T., Oware, E.K., & Caers, J.
    [2016]. Direct prediction of spatially and temporally varying physical properties from time-lapse electrical resistance data. Water Resources Research, 52, 7262–7283.
    [Google Scholar]
  3. Park, B.-H., Bae, G.-O., & Lee, K.-K.
    [2015]. Importance of thermal dispersivity in designing groundwater heat pump (GWHP) system: Field and numerical study. Renewable Energy, 83, 270–279.
    [Google Scholar]
  4. Possemiers, M., Huysmans, M., & Batelaan, O.
    [2015]. Application of multiple-point geostatistics to simulate the effect of small-scale aquifer heterogeneity on the efficiency of aquifer thermal energy storage. Hydrogeology Journal, 23, 971–981.
    [Google Scholar]
  5. Vandenbohede, A., Hermans, T., Nguyen, F.
    [2011]. Shallow heat injection and storage experiment: heat transport simulation and sensitivity analysis. Journal of Hydrology, 409, 262–272.
    [Google Scholar]
  6. Wildemeersch, S., Jamin, P., Orban, P., Hermans, T., Klepikova, M., Nguyen, F., Brouyère, S., & Dassargues, A., Lebbe, L.
    [2014]. Coupling heat and chemical tracer experiments for estimating heat transfer parameters in shallow alluvial aquifers. Journal of Contaminant Hydrology, 169, 90–99.
    [Google Scholar]
  7. Yapparova, A., Matthäi, S., & Driesner, T.
    [2014]. Realistic simulation of an aquifer thermal energy storage: Effects of injection temperature, well placement and groundwater flow. Energy, 76, 1011–1018.
    [Google Scholar]
  8. Zhou, H., Gómez-Hernández, J.J., & Li, L.
    [2014]. Inverse methods in hydrogeology: Evolution and recent trends. Advances in Water Resources, 63, 22–37.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201702136
Loading
/content/papers/10.3997/2214-4609.201702136
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error