Greenfielding Colorado: A GIS Methods Approach to Renewable Siting

Presenter: Brandon Brown, CU-Boulder

Presenter’s Bio:

I am Brandon Brown, an undergraduate dual major at CU-Boulder, with an independent focus on applied GIS for sustainable development planning. Geography’s interdisciplinary nature sets it apart from other majors due to the flexibility with which a student can dual major, minor, or pursue a certificate. I transferred from Colorado Mountain College in Fall 2022 with a major in Environmental Studies, swiftly adding a Geography dual major after taking Intro to Mapping. Open to early career opportunities in GIS, renewable consulting, or the intersection of both.

Session Time:

May 10, 2024, from 8:30 AM to 9:00 AM

Location:

Shively room

Session Abstract:

This is a presentation put together for my undergraduate Honors thesis at CU-Boulder. In this thesis, I examine geospatial data of renewable energy potentials, degraded environments, and community boundaries within the state of Colorado. The data is used to create maps for the entire state of Colorado and three subsequent site recommendations. I evaluate the effectiveness of geographic information systems (GIS) for siting utility-scale clean energy projects. I am presenting 10 figures throughout this writing as maps which detail multivariate criteria visualizing renewable energy potentials through a framework of ethical considerations, economic policy, and environmental conditions. Ethically, I consider community self-determination for environmental justice including Indigenous sovereignty and localized community involvement. Indigenous territories and county lines are visualized equally in the maps as community boundaries. EPA REPower and Energy Communities are economic policy instruments visualized. Three EPA REPower sites are identified for further investigation of planning clean energy projects within Colorado. Two datasets from NREL are merged spatially to create a statewide bivariate visualization of both wind and solar potentials in combination ranging from highest to lowest values. These maps demonstrate a geospatial method which can derive ideal locations for clean energy projects, from manufacturing to development, with a focus on REPower sites.