原文信息：
Low-carbon lithium extraction makes deep geothermal plants cost-competitive in future energy systems
原文链接：
https://www.sciencedirect.com/science/article/pii/S2666792423000276
Abstract
Lithium is a critical material for the energy transition, but conventional procurement methods have significant environmental impacts. In this study, we utilize regional energy system optimizations to investigate the techno-economic potential of the low-carbon alternative of direct lithium extraction in deep geothermal plants. We show that geothermal plants will become cost-competitive in conjunction with lithium extraction, even under unfavorable conditions and partially displace photovoltaics, wind power, and storage from future renewable energy systems. Our analysis indicates that the deployment of 33 deep geothermal plants in municipalities in the Upper Rhine Graben area in Germany could provide enough lithium to produce about 1.2 million electric vehicle battery packs per year, equivalent to 70% of today`s annual electric vehicle registrations in the European Union. As this number represents only a small fraction of the techno-economic potential in Germany, this lithium extraction process could offer significant environmental benefits. High potential for mass application also exists in other countries, such as the United States, United Kingdom, France, and Italy, highlighting the importance of further research and development of this technology.
Keywords
Municipal energy system modeling
Direct lithium extraction
Deep geothermal
Mathematical optimization
Lithium-ion batteries
Critical metals
Graphics
Graphical abstract
Fig. 1. Components of the energy system optimization model, including renewable potentials, imports, conversion, and storage technologies, as well as demand sectors. Commodities that are in demand or supplied are indicated with different colors, and only if the technology involves more than one.
Fig. 4. Overview of a few key characteristics of the 330 investigated municipalities in the Upper Rhine Graben with hydrothermal potential. The maps show the population density (a), electricity demand (b), heat demand (c), onshore wind potential (d), open field PV potential (e) and rooftop PV potential (f) in the municipalities. The population density corresponds to official statistical data [60], the energy demands were regionalized [50] using official statistical data, and the renewable potentials were determined on a site-specific basis using the TREP tool [47]. Except for the population density, there is only low spatial autocorrelation between the municipalities (a: Moran index of 0.405, z-score of 13.393, and p-value of 0.000; b: Moran index of 0.021, z-score of 4.881, and p-value of 0.000; c: Moran index of 0.106, z-score of 4.059, and p-value of 0.000; d: Moran index of 0.074, z-score of 2.616, and p-value of 0.009; e: Moran index of 0.103, z-score of 3.523, and p-value of 0.000; f: Moran index of 0.105, z-score of 3.710, and p-value of 0.000).
Fig. 5. Optimized energy system by 2045 in the worst case, baseline, optimistic, and best case scenarios for the municipality of Bruchsal. The different panels show the total annual cost (a), storage capacities (b), electricity generation (c), and heat generation (d) for the cost-optimal energy systems in the different scenarios.
Fig. 7. Cost-optimal energy systems of 330 municipalities in the Upper Rhine Graben with the option of direct lithium extraction compared to energy systems without this option. The figure panels show how the total annual cost (a), capacities of Organic Rankine Cycle (b), district heating plant (c), onshore wind turbines (d), open field (e), and rooftop (f) photovoltaics are affected if the option to install direct lithium extraction is given compared to optimal energy systems without this option.
Fig. 8. Optimized capacities of Organic Rankine Cycles and district heating plants, as well as lithium carbonate production over the share of municipalities in the Upper Rhine Graben, whereas the share of 100% corresponds to 330. The municipalities are ordered by maximum achievable wellhead temperature (i.e., highest potential), as well as Organic Rankine Cycle capacity. The latter leads to the leap in the curve of district heating plant capacity, as no Organic Rankine Cycle plants are installed in the remaining municipalities.
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