Master of Environmental Data Science
(2023)
Identifying Optimal Wind and Solar Co-Location Sites in the United States
Deliverables:
Description
Today’s need to phase out our reliance on fossil fuels is accelerating the demand for renewable energy like wind and solar power in the United States. However, a barrier to adding new wind and solar photovoltaic (PV) development lies in transmission and land use restraints. Co-location of renewable energy sites by adding solar PV to sites with existing wind turbines can minimize new infrastructure costs and transmission needs while maximizing power production and land use. Existing co-located wind and solar PV sites have proven successful around the world; however, these technologies have yet to emerge at scale in the U.S. This project explores how co-located wind and solar PV sites can play a role in the clean energy transition and quantifies how it can be implemented most effectively in the U.S.
This project uses socio-economic, infrastructure, and environmental data (including wind speed, solar radiation, and land use information). We will model output capacities from wind and solar PV sites, construct a simple linear optimization program, and perform geospatial analysis to determine the optimal locations and additional energy output produced by new wind and solar co-located sites in the U.S.
