We present a preliminary methodology for including geothermal resource uncertainty into the Renewable Energy Potential model, which estimates potential capacity and costs on a gridded surface at the national scale. The uncertainty outputs characterize the 10th, 50th and 90th percentile for geothermal resources using two energy capacity estimation equations. We then present a method and results that demonstrate how other geologic data layers, which may be indicative of permeability, can be used to inform the mean and standard deviation of the geothermal capacity. We demonstrate how the mean and standard deviation can be defined or partially informed by using collocated regression estimates and estimate errors, respectively. These regression results are from 36 observed geothermal power plants in the Great Basin region and are also used to the P10-P90 calculations.

Press the Back button in your browser, or search again.

Copyright 2024, Stanford Geothermal Program: Readers who download papers from this site should honor the copyright of the original authors and may not copy or distribute the work further without the permission of the original publisher.