Skip to main content
Duke University Libraries
DukeSpace Scholarship by Duke Authors
  • Login
  • Ask
  • Menu
  • Login
  • Ask a Librarian
  • Search & Find
  • Using the Library
  • Research Support
  • Course Support
  • Libraries
  • About
View Item 
  •   DukeSpace
  • Theses and Dissertations
  • Nicholas School of the Environment
  • View Item
  •   DukeSpace
  • Theses and Dissertations
  • Nicholas School of the Environment
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Maximum Entropy Modeling for Photovoltaic Optimization: A Spatial Analysis of California

Thumbnail
View / Download
10.6 Mb
Date
2012-04-26
Author
Schrager, Samuel
Advisor
Golden, Jay
Repository Usage Stats
240
views
281
downloads
Abstract
Adoption of renewable energy for electricity generation holds significant potential to produce emission reduced power, in addition to other benefits. Great promise has been expected for solar energy, specifically photovoltaic (PV) solar panels, which harness the photoelectric effect to produce electricity. Over the past 20 years, the average number of PV facilities in the United States have increased nearly 40% per year. Even with this growth, as of 2011, PV provided only .2% of all national electric generating capacity. However, if historical growth trends can continue, solar energy may stand on the threshold of much larger adoption rates. Within this context, a holistic understanding of the social, environmental and economic elements that play a role in aiding PV growth may prove fruitful. Questions, which have remained unanswered, include what parties adopt, what kind of sites are most common, where development most frequent and what are the drivers of PV adoption? In this paper, a literature review of quantitative and social studies, related to PV adoption is conducted. The output of the literature review is used to select environmental, economic and social variables, which guide a spatial model building process. The model goal is to predict PV adoption hotspots. The spatial boundary of this study is limited to California, chosen due to a national dominance of the PV market. A maximum entropy based model, Maxent, was selected due to its high regard within the field of species distribution modeling, its ability to predict unoccupied habitat, the complex relationships it fits between indicator variables, and the ease at which it integrates and visualizes spatial data. Verification is conducted by comparing model output with historical adoption trends and remote sensing. Model results are analyzed for potential PV utilization market segment and policy implications. The study concludes with suggestions for further research.
Type
Master's project
Department
Nicholas School of the Environment and Earth Sciences
Subject
GIS
Maxent
Solar Energy
Permalink
https://hdl.handle.net/10161/5258
Citation
Schrager, Samuel (2012). Maximum Entropy Modeling for Photovoltaic Optimization: A Spatial Analysis of California. Master's project, Duke University. Retrieved from https://hdl.handle.net/10161/5258.
Collections
  • Nicholas School of the Environment
More Info
Show full item record
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 United States License.

Rights for Collection: Nicholas School of the Environment


Works are deposited here by their authors, and represent their research and opinions, not that of Duke University. Some materials and descriptions may include offensive content. More info

Make Your Work Available Here

How to Deposit

Browse

All of DukeSpaceCommunities & CollectionsAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit DateThis CollectionAuthorsTitlesTypesBy Issue DateDepartmentsAffiliations of Duke Author(s)SubjectsBy Submit Date

My Account

LoginRegister

Statistics

View Usage Statistics
Duke University Libraries

Contact Us

411 Chapel Drive
Durham, NC 27708
(919) 660-5870
Perkins Library Service Desk

Digital Repositories at Duke

  • Report a problem with the repositories
  • About digital repositories at Duke
  • Accessibility Policy
  • Deaccession and DMCA Takedown Policy

TwitterFacebookYouTubeFlickrInstagramBlogs

Sign Up for Our Newsletter
  • Re-use & Attribution / Privacy
  • Harmful Language Statement
  • Support the Libraries
Duke University