Suitability modeling and the location of utility-scale solar power plants in the southwestern United States
type: CreativeWork
description: As states and regions have begun prioritizing renewable energy at the legislative level, solar energy has started to play a noticeably larger role in the energy portfolio of certain regions in the United States. Decision making concerning the siting of new solar facilities can be complicated, and GIS-based suitability modeling is often employed to determine ideal candidate sites. These suitability models seek to evaluate a comprehensive set of relevant criteria (such as insolation values, topography, access, land designation status, etc.), often at different weights, to produce a classified map of all potential sites that will facilitate decisions of site location. This research examines the nature and reliability of this type of suitability modeling by analyzing the extent to which those regions identified as most suitable' in a GIS model actually match up with the locations of existing and planned solar facilities. A suitability model was developed in ArcGIS based on examples from similar research, and compared against the actual locations of photovoltaic and concentrating solar facilities in the southwestern part of the United States. The topic of land ownership is also investigated to determine its relationship to the spatial distribution of solar facilities. The analysis indicated that although the locations of solar facilities fell mainly within those areas identified as highly suitable, this match was more noticeable for concentrating solar facilities than it was for photovoltaic facilities, indicating a need to develop separate models for these two types of facilities. Furthermore, while a high suitability classification seemed to be a prerequisite for solar facilities, the amount of highly suitable terrain in a state did not necessarily predict how many facilities would be present. Federally owned lands were also discovered to be preferable in regard to site locations. All of these results indicate the relevance of other non-spatial criteria as an explanati…
abstract: As states and regions have begun prioritizing renewable energy at the legislative level, solar energy has started to play a noticeably larger role in the energy portfolio of certain regions in the United States. Decision making concerning the siting of new solar facilities can be complicated, and GIS-based suitability modeling is often employed to determine ideal candidate sites. These suitability models seek to evaluate a comprehensive set of relevant criteria (such as insolation values, topography, access, land designation status, etc.), often at different weights, to produce a classified map of all potential sites that will facilitate decisions of site location. This research examines the nature and reliability of this type of suitability modeling by analyzing the extent to which those regions identified as most suitable' in a GIS model actually match up with the locations of existing and planned solar facilities. A suitability model was developed in ArcGIS based on examples from similar research, and compared against the actual locations of photovoltaic and concentrating solar facilities in the southwestern part of the United States. The topic of land ownership is also investigated to determine its relationship to the spatial distribution of solar facilities. The analysis indicated that although the locations of solar facilities fell mainly within those areas identified as highly suitable, this match was more noticeable for concentrating solar facilities than it was for photovoltaic facilities, indicating a need to develop separate models for these two types of facilities. Furthermore, while a high suitability classification seemed to be a prerequisite for solar facilities, the amount of highly suitable terrain in a state did not necessarily predict how many facilities would be present. Federally owned lands were also discovered to be preferable in regard to site locations. All of these results indicate the relevance of other non-spatial criteria as an explanati…
author: Ignizio, Drew
language: English
keywords: Solar power plants--Geographic information systems--Southwest, New, Solar power plants--Location--Southwest, New--Data processing, Geospatial data
date published: 2010-06-25T07:00:00Z
date modified: 2026-07-24T05:27:31Z
provider: University of New Mexico
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of New Mexico

PropertyValue
property ID: Handle
value: http://hdl.handle.net/1928/10825