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Master of Environmental Data Science

Understanding US Wind and Solar Energy Siting

Wind turbines in a field

Group Members: Paloma Cartwright, Joseph (Joe) DeCesaro, Daniel Kerstan, Desik Somasundaram

Faculty Advisors: Ranjit Deshmukh

Client: UCSB Environmental Science Department




Technical Documentation 

Final Presentation


Climate change has caused widespread adverse impacts globally. The decarbonization of energy sources is one of the proven pathways to mitigating the impacts of climate change. There is significant pressure to implement large scale renewable energy projects in an efficient and timely manner to achieve the increasingly prevalent, highly ambitious clean energy goals. However, limited knowledge exists pertaining to the determining factors for the successful siting of wind and solar energy projects. In this project, we gather data across physical, social, policy/economic, and infrastructure factors of interest for the contiguous US. Using the various datasets, we conduct geospatial analysis and use machine learning techniques to discover insights on the most important siting factors for utility-scale wind and solar. We then generate predictive maps that show the likelihood of utility-scale plants to be sited at a given location in the US based on suitable areas. 


UCSB: Grace Wu, Assistant Professor, Environmental Studies Program; Ranjit Deshmukh, Assistant Professor, Environmental Studies and Bren School

Bren School: Niklas Griessbaum, PhD Student; Allison Horst, Assistant Teaching Professor

Lawrence Berkeley National Laboratory

The Nature Conservancy

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