| Title | Probabilistic Analysis of Failure Risk in the Primary Geothermal Cycle |
|---|---|
| Authors | C. Fichter, G. Falcone, K. M. Reinicke, C. Teodoriu |
| Year | 2011 |
| Conference | Stanford Geothermal Workshop |
| Keywords | Deep Geothermal Systems, Monte Carlo Simulation, Probabilistic Evaluation, Decision Tree |
| Abstract | The implementation of renewable energy sources, and geothermal energy in particular, is becoming increasingly important in Germany. However, geothermal power generation is a high risk, capital intensive technology and its future use will depend on how successfully it can be integrated within the German power grid infrastructure. For this to happen, its inherent operational risks must be reduced to a level that will guarantee a safe, available and affordable geothermal energy production over a plant’s lifetime. To operate successfully in the deep, hot, saline conditions that are associated with the Northern German Basin, a geothermal power plant will need to incorporate an Enhanced Geothermal System (EGS). The objective of this study is to identify and statistically model the main causes of failure in the primary cycle of an EGS and how likely they were to occur. In so doing, it is hoped to reduce the probability of downtime in such geothermal power systems in order to achieve higher plant online availability. |