Because genGEO is first-of-its-kind, we provide multiple contributions in this paper. First, in Section 2 and in the Supplemental Information (SI), we provide a detailed description of genGEO, which we implemented in python to release as open-source software concurrently with this publication. Second, we validate genGEO using publicly available data from the Tungsten Mountain geothermal power plant in Nevada, U.S. This validation is part of a larger comparison between genGEO, GETEM, and GEOPHIRES that we conduct to display the improvements that genGEO makes to the field of geothermal techno-economic assessment (Section 3.1). Third, we use genGEO to compare using CO 2 versus water as a heat extraction fluid in sedimentary basin geothermal power plants from an electricity generation and cost perspective over a large geologic parameter space (Section 3.2). Fourth, we use these large parameter space cost and generation results along with publicly available sedimentary basin data to produce supply curves for sedimentary basins geothermal power plants in the U.S. (Section 3.2). Finally, we provide the conclusions from this study (Section 4). While this study is not a review paper, we uncovered findings that have not yet been clearly documented within the geothermal energy community during the literature review that we conducted to create genGEO. As a result, we also include these literature review findings at the end of our conclusion section.