DOI: 10.5281/zenodo.14991109
title: High-resolution analysis of power plant land requirements for GODEEEP

description: This dataset contains data associated with Mongird et al. (under review). Files include output from the following three analyses found in the paper: (1) Projected power plant siting intersections with US Disadvantaged Communities (DACs), important farmland, and natural areas; (2) onshore wind and solar photovoltaic capacity factor availability under 27 different siting restriction cases, and (3) output from an analysis that determines how many DACs are projected to see both fossil fuel generation retirement and new renewable power plant development. Each of the files associated with these components are described below. 

For more detailed information please refer to Mongird et al. (under review), "High-resolution analysis of power plant land requirements for the evolving Western United States power grid indicates coordinated land use policies will be essential"

Outputs included in this dataset are associated with two different scenarios. Summaries of each of the two scenarios included are provided below. For additional information, see Ou et al. 2023.

Scenario Descriptions



business-as-usual:



This scenario does not include any long-term federal policies requiring decarbonization.

It does include the US Inflation Reduction Act (IRA) incentives.

It assumes that CCS technologies are available.



high renewables:



This scenario includes a clean electricity grid in the U.S. by 2035 and a net-zero economy by 2050.

It does include US IRA incentives.

It assumes that CCS technologies are available.




Data Descriptions

1. Projected power plant siting intersections

Description

These files identify the intersection of projected power plant locations with three types of land: federall identified disadvantaged communities (DACs), important farmland, and land in close proximity to natural areas.

Scenario Files:




File Name
File Description


bau_dac_analysis_2050.csv
Results from analysis identifying how many projected power plant sitings through 2050 under the busines-as-usual scenario intersect with federally identified US DACs by technology type and Western US state


bau_env_analysis_2050.csv
Results from analysis identifying how many projected power plant sitings through 2050 under the busines-as-usual scenario intersect with areas within 1 km, 5 km, and 10km of environmental areas by technology type and Western US state


bau_farm_analysis_2050.csv
Results from analysis identifying how many projected power plant sitings through 2050 under the busines-as-usual scenario intersect with important farmland by technology type and Western US state


hr_dac_analysis_2050.csv
Results from analysis identifying how many projected power plant sitings through 2050 under the high renewables scenario intersect with federally identified US DACs by technology type and Western US state


hr_env_analysis_2050.csv
Results from analysis identifying how many projected power plant sitings through 2050 under the high renewables scenario intersect with areas within 1 km, 5 km, and 10km of environmental areas by technology type and Western US state


hr_farm_analysis_2050.csv
Results from analysis identifying how many projected power plant sitings through 2050 under the high renewables scenario intersect with important farmland by technology type and Western US state




 

Data Dictionary:




Column
Description
Units


state
Name of US state
N/A


technology
Power plant technology type inclusive of turbine type, presence of CCS, and cooling type (as applicable)
N/A


technology_simple
Power plant technology type excluding turbine type, presence of CCS, and cooling type (as applicable)
N/A


layer_name
Descriptive name of geospatial raster layer used for intersection analysis
N/A


layer
Name of geospatial raster layer used for intersection analysis
N/A


total_plants
Number of projected power plants of specified technology in specified state under given scenario
#


intersection
Number of projected power plant intersections of specified technology in specified state with given layer under given scenario 
#


fraction
ratio of intersection and total_plants
fraction




 

Scenario Difference Analysis Files:




difference_dac_analysis_2050.csv
Results from analysis identifying how many more projected power plant sitings through 2050 under the high renewables scenario intersect with federally identified US DACs by technology type and Western US state compared to projected power plant sitings through 2050 under the business-as-usual scenario. Negative results indicate that the business-as-usual scenario had a greater number of intersections.


difference_env_analysis_2050.csv
Results from analysis identifying how many more projected power plant sitings through 2050 under the high renewables scenario intersect with areas within 1 km, 5 km, and 10km of environmental areas by technology type and Western US state compared to projected power plant sitings through 2050 under the business-as-usual scenario. Negative results indicate that the business-as-usual scenario had a greater number of intersections.


difference_farm_analysis_2050.csv
Results from analysis identifying how many more projected power plant sitings through 2050 under the high renewables scenario intersect with important farmland by technology type and Western US state compared to projected power plant sitings through 2050 under the business-as-usual scenario. Negative results indicate that the business-as-usual scenario had a greater number of intersections.




 

Data Dictionary:




Column
Description
Units


state
Name of US state
N/A


technology
Power plant technology type
N/A


layer
Name of geospatial raster layer used for intersection analysis
N/A


hr
Number of projected power plant intersections with given layer under the high renewables scenario
#


bau
Number of projected power plant intersections with given layer under the business-as-usual scenario
#


intersection
Difference in projected power plant intersections between the high renewables scenario and the business-as-usual scenario
#




 

2. Projected onshore wind and solar photovoltaic capacity factor availability under 27 siting restriction cases

Description:

This file contains results from an analysis on the capability of reaching high renewables scenario solar and wind generation in 2050 under 27 different siting restriction cases.

Relevant File:




File Name
File Description


capacity_factor_analysis_2050.csv
Amount of solar PV or onshore wind generation projected to be available in a given state under a specified siting restriction case 




Data Dictionary:




Column
Description
Units


region_name
Name of US state
N/A


technology
Power plant technology type (either solar PV or Wind)
N/A


capacity_density_mw
Assumed MW per square-km
MW


case
Name of siting exclusion case
N/A


total_generation_mwh
Projected total generation available given remaining available land after exclusions
MWh


target_generation_mwh
Projected target annual generation in 2050 for technology type under high renewables scenario
MWh


gcam_trading_region
Name of zonal representation of electricity trading regions as defined in the capacity expansion model
N/A




 

3.  US DACs that see both fossil fuel generation retirement and new renewable power plant development by 2050

Description:

This data contains US census tract GEOIDs that see both new renewable sitings and the retirement of fossil generating resources.

Relevant File:




File Name
File Description


dac_fossil_retire_analysis_2050.csv
List of US census tracts that see both fossil fuel generation retirement and new renewable generation siting by 2050 




Data Dictionary:




Column
Description


 census_tract
 US census tract GEOID


state_name
Name of US state


county_name
Name of US county


scenario
scenario name




 

Funding statement

This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL).

PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.

 

Changelog

v1.1

 The following updates were made following manuscript revision:



"power_density_mw" variable name in `capacity_factor_analysis_2050.csv` file changed to "capacity_density_mw"

More estimates are provided in `capacity_factor_analysis_2050.csv` reflecting additional capacity density and turbine hub height assumptions.

Scenario naming adjusted to align with manuscript naming