Direct use of geothermal energy can present challenges of financial feasibility in a low-enthalpy setting. The average temperature gradients in sedimentary basins make it necessary to reach larger depths for meaningful heat production, thus increasing the drilling cost. Therefore, full realization of geothermal projects in low-enthalpy environments has been difficult and not widely deployed. The concept of harvesting the positive temperature anomalies caused by the increased heat conductivity of salt bodies could enable access to higher temperatures at a shallower depth, thus reducing the necessary depth of drilling. In a potential site in NE Netherlands, temperature differences of up to 25 °C close to the top of a salt body are modeled. Substantiating this concept we show that the energetic benefits can result to up to 40% more energy extracted, while the temperature recovery of the field is only prolonged by 13%. This opens up new possibilities for geothermal applications in sedimentary basins.

This paper presents a techno-economic analysis of a deep, direct use geothermal heat system in a conductive geological setting (Groningen, NE Netherlands). The model integrates the previously discussed uncertainties of the initial reservoir state, geological and operational conditions with the economic uncertainties. These uncertainties are incorporated in the form of probability distributions and 20,000 iterations of the model are performed over a project lifetime of 40 years. A combination of Ex-Ante and Ex-Post criteria are used to evaluate the economic performance of the system based on the Net Present Value (NPV), Levelised Cost of Heat (LCOH) and Expected Monetary Value (EMV). The sensitivity analysis highlights the load factor (effective flowrate) as the most important parameter for the economic performance and energy costs. However, the differences between the NPV and LCOH sensitivities highlight the importance of using both metrics for the economic performance of such systems. The presented project remains economically challenging, exhibiting a 50% probability of marginal revenues over its lifetime. Systematic insights are drawn with regard to potential improvements of technical and economic aspects of such geothermal heat systems.

This paper outlines a method in which the heat production of a geothermal system is controlled in relation to the demand from a district-heating network. A model predictive control strategy is designed, which uses volume measurements in the storage tank, and predictions of the demand, to regulate the production of the geothermal system in real time. The implications of such time-varying production for the reservoir are investigated using a 2D reactive transport reservoir model. As a case study, the Groningen geothermal project is considered. The numerical data generated by the controller, in closed loop with a modelled district-heating network, are used as inputs for the reservoir simulations. The latter make use of discrete parameter analyses to evaluate the effect of pressure depletion, reservoir permeability, flow rate, re-injection temperature and injection pH on the geothermal reservoir, and also mitigate possible risks during development. Using a model predictive control does not create adverse geochemical effects in the reservoir; instead, the controller is able to improve the efficiency of the geothermal heat extraction. The findings pave the way for stronger integration between elements of heat networks and a more sustainable development of geothermal resources.

Geothermal exploitation is subject to several uncertainties, even in settings with high data availability, adding to project risk. Uncertainty can stem from the reservoir's initial state, as well as from the geological and operational parameters. The interplay between these aspects entails irreducible risk prior to exploration drilling. Consequently it is difficult to construct an indicative qualitative and quantitative depiction of the most prominent facets (e.g. pressure, permeability). This paper shows the classification of known unknowns to risks, while also providing numerical results. Starting from seismic data and arriving at a reservoir model using a discrete parameter analysis we assess the risks and uncertainties of a geothermal project near the city of Groningen (NE Netherlands). By simulating all combinations of the considered parameters, their relative importance can be mapped out. Findings suggest that the unique regime of possible pressure depletion due to neighbouring gas production can highly impact the feasibility of the project. Results demonstrate how an in depth analysis at the exploration phase can direct future efforts towards the most significant elements. Although the numerical results are field specific, the methodology can be readily applied to different locations.

Energy is released when feed waters with different salinity mix. This energy can be captured in reverse electrodialysis (RED). This paper examines experimentally the effect of varying feed water concentrations on a RED system in terms of permselectivity of the membrane, energy efficiency, power density and electrical resistance. Salt concentrations ranging from 0.01M to 5M were used simultaneously in two stacks with identical specifications, providing an overview of potential applications. Results show a decrease of both permselectivity and energy efficiency with higher salt concentrations and higher gradients. Conversely, power density increases when higher gradients are used. The resistance contribution of concentration change in the bulk solution, spacers and the boundary layer is more significant for lower concentrations and gradients, while membrane resistance is dominant for high concentrations. Increasing temperature has a negative effect on permselectivity and energy efficiency, but is beneficial for power density. A power density of 6.7W/m² is achieved using 0.01M against 5M at 60°C. The results suggest that there is no single way to improve the performance of a RED system for all concentrations. Improvements are therefore subject to the specific priorities of the application and the salt concentration levels used. Regarding ion exchange membranes, higher salinity gradients would benefit most from a higher fixed charge density to reduce co-ion transport, while lower salinity gradients benefit from a thicker membrane to decrease the osmotic flux.

Energy can be produced from mixing waters with different salinity in reverse electrodialysis (RED). Technological improvements make RED gaining momentum as a technically viable option for baseload renewable energy generation. In this paper a model is presented for three different RED applications in terms of upscale potential based on experimental data in the probabilistic software GoldSim. For a project life of 30years (including a 5year pilot phase), the economics and avoided CO₂ emissions of such a power plant for three different price scenarios and three different feed solutions are examined. Subsequently an evaluation is carried out of the upscale potential, the economic break-even membrane price of a large scale RED power plant is quantified, identifying the most influential inputs through a sensitivity analysis. Furthermore, future performance and price developments are incorporated in the model and a comparison is made of a RED power plant with other conventional and renewable energy sources in terms of the Levelised Cost Of Electricity (LCOE) index. Brine applications seem to be closer to economic viability with the present state of technology and an optimistic membrane pricing scenario, but can only be upscaled to the order of 1MW. River and seawater are not yet economically attractive but have an upscale potential close to 290MW for the Dutch context. However, considering future development in membrane performance and price, the LCOE for electricity generation with river and seawater using RED is competitive to other renewable energy sources such as biomass and wind.