SOLAR SITE SELECTOR

About This Tool

This solar site selection tool was created to demonstrate how utility scale solar energy production can be increased by optimizing site location. The tool considers three factors: Global Horizontal Irradiance (otherwise abbreviated as GHI, the amount of electromagnetic energy a horizontal surface receives from the sun), land cover (which determines areas unacceptable for solar installations due to the material at the Earth's surface), and locations of the grid's electrical transmission lines (such that a site should be within one (1) to fifty (50) kilometers of a transmission line to be considered optimal for practical connection to the grid).

Data Sources:

• NREL National Solar Radiation Database - to compare the annual GHI of different locations
• U.S. Geological Survey's National Land Cover Database from 2024 - for land cover data
• Geospatial Management Office's transmission line data - showing the location of current transmission lines

The tool overlays these three datasets, eliminates unsuitable areas, and ranks sites from most to least optimal based on their GHI and distance from the nearest transmission line. This ranking system uses the following formula:

The equation calculating annual energy generation at a suggested site (which assumes a solar installation capacity of 5 MWp) is: Energy (in GWh per year) = Capacity (in GWh) × PR × GHI/1000

How to Use: Select a state within the contiguous United States below. The number of top sites recommended, PR, maximum distance from transmission lines, and map resolution can also be modified below.

Demonstrated by this tool, solar production potential can vary greatly by site, even within one (1) state. Given the continually growing demand for electricity in the United States, optimizing solar energy production becomes even more critically important to sustainable energy supply.

Acknowledgements:

I would like to thank Dr. Chad Zanocco, Dr. June Flora, and Dr. Tao Sun for their mentorship on this project and the support of Professor Ram Rajagopal's Stanford Sustainable Systems Lab and DYEL program.