the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
City-scale heating and cooling with Aquifer Thermal Energy Storage (ATES)
Haegyeong Lee
Philipp Blum
Kathrin Menberg
Abstract. Sustainable and climate-friendly space heating and cooling is of great importance for the energy transition. Compared to conventional energy sources, Aquifer Thermal Energy Storage (ATES) systems can significantly reduce greenhouse gas emissions from space heating and cooling. Hence, the objective of this study is to quantify the technical potential of shallow low-temperature ATES systems in terms of reclaimable energy in the city of Freiburg im Breisgau, Germany. Based on 3D heat transport modeling, heating and cooling power densities are determined for various hydrogeological subsurface characteristics and ATES configurations. High groundwater flow velocities of up to 13 m d-1 cause high storage energy loss limiting power densities to a maximum of 3.2 W m-2. Nevertheless, comparison of these power densities with the existing thermal energy demands shows that ATES systems can achieve substantial heating and cooling supply rates. This is especially true for the cooling demand, for which a full supply by ATES is determined for 92 % of all residential buildings in the study area. For ATES heating alone, potential greenhouse gas emission savings of up to about 70,000 tCO2eq a-1 are calculated, which equals about 40 % of the current greenhouse gas emissions caused by space and water heating in the study areas’ residential building stock. The modeling approach proposed in this study can also be applied in other regions with similar hydrogeological conditions to obtain estimations of local ATES supply rates and support city-scale energy planning.
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Ruben Stemmle et al.
Status: final response (author comments only)
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RC1: 'Comment on hess-2023-62', Jannis Epting, 30 Apr 2023
Dear colleagues,
The paper "City-scale heating and cooling with Aquifer Thermal Energy Storage (ATES)" presented by Stemmle et al. represents an interesting case study that builds on previously developed methods. A new aspect is the simultaneous consideration of heating and cooling.
One major drawback is the missing information on the city-scale model (setup, parameterization, boundary conditions, calibration / validation, etc.). It is also not apparent whether this information has been published elsewhere.
The use of an “ambient temperature of 12 °C” should be justified. The use of an "ambient temperature of 12 °C" should be justified. In Freiburg, groundwater temperatures vary greatly, and the starting point will be different depending on the aquifer region.
The latter two aspects also lead me to decide that major revisions are needed.
More sepecific comments include:
p. 1, l. 13: provide information on the aquifer, unconsolidated gravel aquifer, …
p. 1, l. 13: specify «limiting power densities» aquifer
p. 2, l. 53: GWHP was already introduced, check whole text
p. 3, l. 65: “2D numerical box models” include: F. Bottcher, A. Casasso, G. Gotzl, K. Zosseder, TAP - thermal aquifer Potential: a quantitative method to assess the spatial potential for the thermal use of groundwater, Renew. Energy 142 (2019) 85e95.
p. 3, l. 76: GHG was already introduced, check whole text
p. 3, l. 94: specify “lower hydraulic conductivity”
Fig. 1a: missing scale bar (maybe zoom in, include Voges); m asl
Fig. 1b: flow direction of river Dreisam (maybe zoom in, show 10m equidistance); m asl
Fig. 1c: requires x-scaling, legend for lithologies, turn m asl 180°
Section 2.2.: Required? No new equations are developed. Reference could be sufficient.
Table 1: 4.4 E-3; 6 E-5 (reference personal communication?); References for standard values appropriate?
Fig. 2 could be merged with Fig. 1
Table 2: Value representation? Simplify & avoid repetitions.
p. 7, l. 170: Why estimated?
p. 7, l. 174.176: What is the difference between uniform and constant thickness?
p. 8, l. 193: Specify “substantial”
Fig. 4: turn labeling right axis asl 180°
p. 8, l. 211: When is thermal equilibrium reached? This measure maybe is more appropriate compared to the lifetime.
p. 10, l. 232-233: Discuss “ambient temperature of 12 °C”
p. 10, l. 249: Table 3?
p. 12, l.301: It would make sense to also calculate the SCOP as seasonal operation is investigated.
p. 13, eq. 14: see Epting et al. 2018
p. 17, l. 421-428: Compare to Epting et al. 2018 & 2020Good luck and all the best,
Jannis Epting
Citation: https://doi.org/10.5194/hess-2023-62-RC1 -
RC2: 'Comment on hess-2023-62', Anonymous Referee #2, 14 May 2023
This manuscript describes a case study in which the shallow geothermal system Aquifer Thermal Energy Storage (ATES) is analyzed for the city of Freiburg in Germany. The work is largely presented as case study, and the question is why a reader in Florence, Oklahoma City, or Nanjing should be interested in reading it. If this manuscript addresses readers who are really interested in the city of Freiburg, the German journal “Grundwasser” would be the right place to publish it, because the latter journal made for a German audience. A paper in HESS, by contrast, should present either new insights in hydrological system behavior, or new methods of general interest that can be applied at many places. I honestly don’t see that the authors have advanced our general understanding of heat transport in the subsurface, but I also have difficulties to recognize methodological breakthroughs. Using simplified box-shaped models with a uniform ambient hydraulic gradient, is not really new, and the concept of the power density has been introduced before. So what is really new and of interest to a broad readership?
I have to admit that my specialty is not in the design of shallow geothermal systems, but I understand the underlying concepts and governing equations quite well. Having said that, I am not convinced about the concept of the power density. The natural geothermal heat flux in the region is about 0.1 W/m2. If you plaster the domain with many geothermal wells, all of them extracting heat, and you insulate the top (as done by the authors), the long-term power density will equal the natural geothermal heat flux of 0.1 W/m2. The trick of ATES is of course that heat is injected into the ground in the summer and extracted in the winter, which makes even the scenario of a plastered domain with an insulated top less dependent on the natural geothermal heat flux. What the authors do, is to consider a rectangular box with a single or two geothermal well pairs or triplets, run the system for 30 years, and then outline the 0.5 K contourline of the temperature anomaly. This design is not representative if you consider a second/third/fourth row of well pairs/triplets that will interfere. This is a simple matter of superposition, which applies to linear transport. A realistic small-scale scenario representative for an entire city would use periodic boundary conditions, in which the heat flux leaving the domain at the downstream end enters at the upstream end. If you run the system until you reach dynamic steady state, you see how the geothermal systems influence each other in the middle of a periodic domain. This would make much more sense then outlining an arbitrarily chosen contourline of a lonesome geothermal system. A systematic analysis of heat fluxes (how much is recycled, what is the difference in the incoming versus the outgoing heat flux with ambient flow if you don’t assume periodicity, what is the heat flux at the non-insulated top boundary) would make more sense to me then the power density, which only gives the illusion of a practical metric.
I could imagine that the work could be converted into a methodological study, outlining how small-scale models can be used to predesign large-scale optimization of geothermal systems. But the manuscript is not written in such a way, and a real large-scale optimal design is not attempted at all.
Notwithstanding these fundamental concerns, I have a series of minor comments:
- Line 34: “thermal energy” rather than “environmental”
- Line 55: “revealed” (past tense)
- Line 89: Shouldn’t it be “alluvial fan” rather than “cone”?
- Lines 92-94: Outside of Baden-Württemberg, nobody knows the Neuenburg and Bresigau formations. Give at least their age (their both from the Pleistocene)
- Equation 3: You use a scalar dispersive thermal conductivity, but later on you use a longitudinal and a transverse dispersivity. This implies applying the Scheidegger parameterization, and it implies anisotropic dispersive heat transfer. The corresponding equations are missing.
- Equation 5, line 131: if p is supposed to be the pore pressure, you need to add gravity to Darcy’s law: u = -K*grad(p/(ρ*g)+z). Alternatively, you can define p as the total potential (pore pressure plus ρ*g*z).
- Line 132: I assume that you neglect the temperature dependence of hydraulic conductivity, which stems from the temperature dependence of viscosity. We are talking about a factor of two for 10 K temperature difference.
- Equation 6: I assume that you use the specific storativity to relate the given time derivative to the rate of change in pore pressure/potential.
- Table 1: It’s “transverse dispersivity” rather than “transversal”, and the coefficient is about two orders of magnitude too large. Stochastic theory reveals that the longitudinal dispersion coefficient (if you believe in Fickian dispersion) increases by orders of magnitude upon upscaling, whereas the transverse dispersion coefficient is hardly affected at all.
- Figure 3 and its discussion: The heat-related boundary conditions are incomplete. What is the bottom boundary? How do you treat temperature at the up- and downstream faces?
- Section 2.6: I have expressed my concerns regarding the power density above. In fact, the results of the city-scale model confirm the importance of the interference across boxes. I am not convinced.
- Lines 348-349: is the observation that ambient flow influences the thermal recovery in ATES systems new at all?
- Figure 7: This plot shows a linear dependence of TR on ln(u). It should be possible to approximate the corresponding coefficients by analytical considerations, but the authors not even do the linear regression.
- Lines 431-432: For the given simple setup with uniform ambient flow I am not convinced that numerical models truly outperform analytical expressions.
- Lines 451-454: I expressed doubts about the thermal insulation on top already further up. In fact, a large fraction of the heat in shallow geothermal systems comes from the surface. It’s still reasonable to prefer these systems over air heat pumps because you change the timing.
- Line 468 ff.: Here the discussion becomes by far too local. I value the cities of Ludwigsburg (nice baroque castle), Lausanne (Olympic museum on Lake Geneva), and Geneva (impressive fountain in the lake), but the authors simply list a couple of case studies. You need to concentrate on general principles and methods instead!
- Section 3.4: I am not convinced about the savings of greenhouse-gas emissions either. This all depends on the specific energy mix, for the existing heating systems, and for electricity production. On the long run, all heating has to be done with renewable energy. In Freiburg, deep geothermal energy would be an option. If you exclude that, you get stuck to heat pumps. The rght comparison in my opinion is to based on the electric-energy demand for heating/cooling with shallow geothermal systems versus air heat pumps. The (hopefully renewably produced) electricity saved is the long-term argument for ATES.
- Section 3.5: I am not convinced that the city-scale model is really computationally too demanding. In this model you can address the interferences of individual systems, and you don’t rely on parallel ambient flow. The goal should be to optimize the big system. If you can show how to do that in general (with the help of box models for predefine or not), you have a HESS-worthy publication.
Citation: https://doi.org/10.5194/hess-2023-62-RC2
Ruben Stemmle et al.
Ruben Stemmle et al.
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