Abstract
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 benchmark the P10-P90 calculations.
Original language | American English |
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Number of pages | 10 |
State | Published - 2024 |
Event | Stanford Geothermal Workshop - Stanford, CA Duration: 12 Feb 2024 → 14 Feb 2024 |
Conference
Conference | Stanford Geothermal Workshop |
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City | Stanford, CA |
Period | 12/02/24 → 14/02/24 |
NREL Publication Number
- NREL/CP-5700-88560
Keywords
- exclusions
- geospatial
- geothermal resource data
- grid infrastructure
- uncertainty