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Renewable Energy Potential Model: Geothermal Supply Curves
The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies.
To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. The included paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure.
Our preliminary supply curves and levelized cost of electricity (LCOE) results provided here should be considered with care due to the high uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for three scenarios: two hydrothermal (3.5km depth, USGS heat flow & SMU temperatures respectively) and one EGS (4.5km depth, SMU temperatures). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| bureauCode |
[
"019:20"
]
|
| contactPoint |
{
"fn": "Whitney Trainor-Guitton",
"@type": "vcard:Contact",
"hasEmail": "mailto:wtrainor@nrel.gov"
}
|
| dataQuality |
true
|
| description | The Renewable Energy Potential (reV) model is a geospatial platform for estimating technical potential and developing renewable energy supply curves, initially developed for wind and solar technologies. The model evaluates deployment constraints, considering land use, environmental, and cultural factors, and estimates the distance to existing grid features to connect future plants (Maclaurin et al., 2021). A pressing deficiency in the reV model, however, is representation of geothermal electricity generation technologies. To address this gap, we developed a novel geothermal generation module for reV that allows for representation and analysis at the same level of detail as other renewable technologies. The included paper describes our process for evaluating data sources for the modeling, and presents five preliminary reV geothermal results. More specifically, we present two sets of resource data that represent upper and lower bounds for geothermal potential. We then present several sensitivity runs using the upper bound resource data; the results are encouraging that levelized cost of electricity (LCOE) can be reduced by optimizing the location and estimated capacity of the spatially diverse geothermal resource while considering the distance to existing grid infrastructure. Our preliminary supply curves and levelized cost of electricity (LCOE) results provided here should be considered with care due to the high uncertainty in geothermal resource potential data. We present median LCOE values for the conterminous U.S. for three scenarios: two hydrothermal (3.5km depth, USGS heat flow & SMU temperatures respectively) and one EGS (4.5km depth, SMU temperatures). The capital and operating costs for each respective technology are modeled. We also compare results using two different resource data sources. |
| distribution |
[
{
"@type": "dcat:Distribution",
"title": "Supply Curves.zip",
"format": "zip",
"accessURL": "https://gdr.openei.org/files/1549/csvs.zip",
"mediaType": "application/zip",
"description": "Supply curve csv's of contiguous United States Great Basin for 3 scenarios: two hydrothermal and one EGS.
The columns are:
Latitude,
Longitude,
Area (square km),
Capacity (MW),
Generation (TWh),
Resource LCOE ($/MWh),
LCOT ($/MWh),
Total LCOE ($/MWh),
Trans distance (km),
Trans cost ($/MW),
Reinforcement distance (km),
and Reinforcement cost ($/MW)"
},
{
"@type": "dcat:Distribution",
"title": "Development of a Geothermal Module in reV.pdf",
"format": "pdf",
"accessURL": "https://gdr.openei.org/files/1549/reV_Geothermal_GRC2023.pdf",
"mediaType": "application/pdf",
"description": "This paper includes the detailed methodology used to produce the supply curves. The complete title reads: "Development of a Geothermal Module in reV: Quantifying the Geothermal Potential while Accounting for the Geospatial Intersection of the Grid Infrastructure and Land Use Characteristics". "
},
{
"@type": "dcat:Distribution",
"title": "reV Model",
"format": "html",
"accessURL": "https://www.nrel.gov/gis/renewable-energy-potential.html",
"mediaType": "text/html",
"description": "This is NREL's reV Model website which includes all information on how to understand, access, and use the reV Model."
}
]
|
| DOI | 10.15121/2008490 |
| identifier | https://data.openei.org/submissions/7636 |
| issued | 2023-08-21T06:00:00Z |
| keyword |
[
"EGS",
"SMU temperatures",
"capital costs",
"energy",
"exclusions",
"feasibility",
"geospatial",
"geothermal",
"geothermal location",
"grid infrastructure",
"hydrothermal",
"levelized cost of electricity",
"model",
"operating costs",
"reV",
"supply curve"
]
|
| landingPage | https://gdr.openei.org/submissions/1549 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2023-10-12T22:55:46Z |
| programCode |
[
"019:006"
]
|
| projectLead | Sean Porse |
| projectNumber | FY23 AOP 5.4.2.3 |
| projectTitle | Development of a Geothermal Module in reV |
| publisher |
{
"name": "National Renewable Energy Laboratory",
"@type": "org:Organization"
}
|
| spatial |
"{"type":"Polygon","coordinates":[[[-123.60566875,23.785599816589716],[-66.48785000000002,23.785599816589716],[-66.48785000000002,48.91835223012614],[-123.60566875,48.91835223012614],[-123.60566875,23.785599816589716]]]}"
|
| title | Renewable Energy Potential Model: Geothermal Supply Curves |
