Impacts of underground climate change on urban geothermal potential: Lessons learnt from a case study in London.

While urban underground is being increasingly used for various purposes, two concerns should be addressed with respect to the urban underground climate change: i) how much energy has been stored in urban subsurface due to the heat rejection from underground heated spaces (such as tunnels and basements) and ii) how much of the thermal demand of a city or district can be supplied by harvesting this accumulative thermal energy in the ground. However, our understanding of the temperature rise in the ground and of the geothermal potential of urban subsurface is still limited. This paper quantifies the geothermal potential for a 12 km2 densely populated borough in central London by considering the spatio-temporal temperature variation in the ground owing to continuous rejection of heat into the ground, coupled with the effect of geothermal extraction capacity. A large-scale transient semi-3D geothermal subsurface model of the site is developed, and the thermal interaction between underground heated spaces, geothermal energy extraction systems and the ground and groundwater are simulated. The concurrent heat rejection and extraction processes in the subsurface are computed so that the most influencing parameters of the subsurface on its geothermal potential are identified. Results show that up to 50% of the borough's total heat demand can be supplied via geothermal installations leading to around 33% reduction in CO2 emission. The geothermal extraction efficiency in sand and gravel primarily depends on the ground conditions such as the thickness of the permeable layer and the groundwater flow regime. In impermeable ground such as clay, however, the underground built environment such as heated spaces have shown to have a significant impact on improving the geothermal extraction efficiency.

Multi-fidelity approach to Bayesian parameter estimation in subsurface heat and fluid transport models.

The increased use of the urban subsurface for competing purposes, such as anthropogenic infrastructures and geothermal energy applications, leads to an urgent need for large-scale sophisticated modelling approaches for coupled mass and heat transfer. However, such models are subject to large uncertainties in model parameters, the physical model itself and in available measured data, which is often rare. Thus, the robustness and reliability of the computer model and its outcomes largely depend on successful parameter estimation and model calibration, which are hampered by the computational burden of large-scale coupled models. To tackle this problem, we develop a novel Bayesian approach for parameter estimation, which allows us to account for different sources of uncertainty, is capable of dealing with sparse field data and makes optimal use of the output data from expensive numerical model runs. This is achieved by combining output data from different models that represent the same physical problem, but at different levels of fidelity, e.g. reflected by different spatial resolution. By applying this new approach to a 1D analytical heat transfer model and a large-scale semi-3D numerical model while using synthetic data, we show that the accuracy and precision of parameter estimation by this multi-fidelity framework by far exceeds the standard single-fidelity results. The consideration of different error terms in the Bayesian framework also allows assessment of the model bias and the discrepancy between the different fidelity levels. These are emulated by Gaussian Process models, which facilitate re-iteration of the parameter estimation without additional model runs.

Large-scale urban underground hydro-thermal modelling - A case study of the Royal Borough of Kensington and Chelsea, London.

The shallow subsurface of dense cities is increasingly exploited for various purposes due to the significant rise in urban populations. Past research has shown that underground activities have a significant impact on local subsurface temperatures. However, the resulting spatial variability of ground temperature elevations on a city-scale is not well understood due to the lack of sufficient information and modelling complexity at such large scales. Resilient and sustainable planning of underground developments and geothermal exploitation in the short and long-term necessitate more detailed, more reliable knowledge of subsurface thermal status. This paper investigates the impact of some common underground heat sources such as train tunnels and residential basements on subsurface temperature elevation on a large scale and highlights the influence of local geology, hydrogeology, density, and type and arrangement of the heat sources on ground thermal disturbance. To tackle the size issues and computational expenses of such a large-scale problem, a semi-3D hydro-thermal numerical approach is presented to capture the combined influence of underground built environment characteristics coupled with ground properties on ground temperature elevation within the Royals Borough of Kensington and Chelsea (RBKC), London. Numerical results show that the extent of ground thermal disturbance is mostly affected by geological and hydrogeological characteristics in permeable ground (River Terrace Deposits). Density and spatial distribution of heat sources, however, are critical parameters in ground temperature evaluation in highly impermeable ground such as London Clay Formation. The locality of temperature rise and potential ground energy within immediate impermeable ground surrounding heat sources versus significantly large extent of ground thermal disturbance in permeable ground, highlights the significant dependency of ground thermal state and geothermal potential at the studied site to the ground and underground built environment characteristics and necessitates a better understanding of shallow subsurface thermal state for a sustainable and resilient urban underground development.

Carrier fluid temperature data in vertical ground heat exchangers with a varying pipe separation.

The dataset in this article is related to shallow geothermal energy systems, which efficiently provide renewable heating and cooling to buildings, and specifically to the performance of the vertical ground heat exchangers (GHE) embedded in the ground. GHEs incorporate pipes with a circulating (carrier) fluid, exchanging heat between the ground and the building. The data show the average and inlet temperatures of the carrier fluid circulating in the pipes embedded in the GHEs (which directly relate to the performance of these systems). These temperatures were generated using detailed finite element modelling and comprise part of the daily output of various one-year simulations, accounting for numerous design parameters (including different pipe geometries) and ground conditions. An expanded explanation of the data as well as comprehensive analyses on how they were used can be found in the article titled "Ground-source heat pump systems: the effect of variable pipe separation in ground heat exchangers" (Makasis N, Narsilio GA, Bidarmaghz A, Johnston IW, 2018) [1].