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dc.contributor.authorFrancis, Karol*
dc.date.accessioned2016-08-26T23:39:33Z
dc.date.available2016-08-26T23:39:33Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10150/618974
dc.description.abstractPhotovoltaic (PV) solar electricity generation has the potential to reduce the demand for more traditional fossil and nuclear power generation. Community PV solar installations allow energy users to share the electricity generated by these plants. Optimal siting of community solar installations will allow for maximum electricity generation while avoiding environmental conflicts, as well as, minimizing construction costs. This study identifies opportunities for community solar plants in Maricopa and Pinal Counties, Arizona, of ¼-acre in size. Input parameters fall into economic, physical, and environmental categories. Each of the input parameters were classified from 1 (not suitable) to 9 (highly suitable). Next, the classified rasters in each category were weighed according to importance, and Esri’s Weighted Sum tool was used to generate a combined raster for the category. The three resulting environmental, economic, and physical characteristic rasters were weighed again, and the Weighted Sum tool was used to generate a raster of community solar suitability scores. Next, a mask of locations inappropriate for community-scale solar development was created, including lakes, rivers, streams, and residential rooftops, which are too small to accommodate ¼-acre community solar installations. The masked areas were removed from the suitability raster, and the suitability raster was reclassified using standard deviations to generate a preference map with values ranging from 1 (low preference) to 3 (high preference). The model output reveals 68 percent of the study area is of medium or high preference for community solar installations. Maricopa and Pinal counties provide many opportunities for community solar installations.
dc.language.isoen_USen
dc.publisherThe University of Arizona.en
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en
dc.subjectCommunity Solaren
dc.subjectLUCISen
dc.subjectMaricopa County (Ariz)en
dc.subjectPinal County (Ariz)en
dc.subjectWeighted sumen
dc.subjectMultiple criteria decision analysisen
dc.subjectSuitabilityen
dc.subjectPreferenceen
dc.titleIdentifying Opportunities for Community Solar: A Study of Maricopa and Pinal Countiesen_US
dc.typeThesisen
thesis.degree.grantorUniversity of Arizonaen
thesis.degree.levelmastersen
thesis.degree.disciplineGeographic Information Systems Technologyen
thesis.degree.nameM.S.en
dc.description.collectioninformationThis item is part of the MS-GIST Master's Reports collection. For more information about items in this collection, please contact the UA Campus Repository at repository@u.library.arizona.edu.en
refterms.dateFOA2018-08-15T15:33:11Z
html.description.abstractPhotovoltaic (PV) solar electricity generation has the potential to reduce the demand for more traditional fossil and nuclear power generation. Community PV solar installations allow energy users to share the electricity generated by these plants. Optimal siting of community solar installations will allow for maximum electricity generation while avoiding environmental conflicts, as well as, minimizing construction costs. This study identifies opportunities for community solar plants in Maricopa and Pinal Counties, Arizona, of ¼-acre in size. Input parameters fall into economic, physical, and environmental categories. Each of the input parameters were classified from 1 (not suitable) to 9 (highly suitable). Next, the classified rasters in each category were weighed according to importance, and Esri’s Weighted Sum tool was used to generate a combined raster for the category. The three resulting environmental, economic, and physical characteristic rasters were weighed again, and the Weighted Sum tool was used to generate a raster of community solar suitability scores. Next, a mask of locations inappropriate for community-scale solar development was created, including lakes, rivers, streams, and residential rooftops, which are too small to accommodate ¼-acre community solar installations. The masked areas were removed from the suitability raster, and the suitability raster was reclassified using standard deviations to generate a preference map with values ranging from 1 (low preference) to 3 (high preference). The model output reveals 68 percent of the study area is of medium or high preference for community solar installations. Maricopa and Pinal counties provide many opportunities for community solar installations.


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