| Title | Risk Factors Within Techno-economic Evaluation of Soft-stimulation Measures |
|---|---|
| Authors | Sören REITH, Dorothee SIEFERT, Hanna MERGNER, Thomas KÖLBEL, Wolfram MÜNCH |
| Year | 2018 |
| Conference | Stanford Geothermal Workshop |
| Keywords | techno economic evaluation, stimulation, risk factors |
| Abstract | Simulation treatments are often the only means to meet economic and sustainability requirements for a geothermal project. Nevertheless, stimulation is expensive, due to varying natural conditions not always successful and sometimes coupled with negative environmental impacts. The “soft stimulation” concept applied within the DESTRESS-project aims at minimizing environmental impact and increasing success rate. Thereby social acceptance and economic efficiency shall be increased to enable market uptake of EGS. Market uptake is inseparably linked with a promising business case. Besides the application of soft stimulation measures DESTRESS therefore also puts a focus on the techno-economic evaluation including risk factors (e.g. uncertainty in technical parameters). The present paper will show the methodology and first results of expanding the techno-economic evaluation by uncertainty demonstrated on the example of geothermal projects using soft stimulation measures. Inspired by the decision analysis approach, probabilistic can improve project evaluation by supporting investment decisions through a statistical data basis. Therefore an integrated simulation model is developed that includes uncertainty caused by technical, social and environmental risk factors. The model maps the whole geothermal circuit process (production – usage – injection) technically and economically on a highly detailed level. First results will include the economic representation of soft stimulation, the integration of risk factors into the simulation as well as the representation of the technical effects of soft stimulation. The research leading to these results has received funding from the European Union’s Horizon2020 Research and Innovation Program under grant agreement No 691728 (Project DESTRESS). |