SRA-E Lisbon 2017

In 2015, approximately 67% of total electricity generated in the United States came from fossil fuel sources, while less than 1% came from solar photovoltaic (PV) systems. In the same year, electricity generation accounted for approximately 40% of total U.S. carbon dioxide (CO₂) emissions. Solar PV can significantly reduce emissions of CO₂ and other harmful pollutants, which have asymmetric negative effects for at-risk populations such as asthmatics, the elderly, and low-income families. Although there is a significant literature on the diffusion of solar PV throughout the residential sector, little is known regarding solar PV’s potential among educational institutions. Therefore, our research identifies the technical and financial feasibility of installing PV on higher education facilities throughout the U.S. with a particular focus on the societal benefits associated with offsetting traditional electricity generation methods. The primary output of this model is a cost-benefit analysis for each higher education institution in the U.S. aggregated at the county level. To determine building locations and counts, we rely on a comprehensive list of higher education facilities in the U.S. developed in a previous Carnegie Mellon University project that detailed campus sustainability strategies and assessments. We combine this building dataset with hourly solar irradiance data available from the National Solar Radiation Data Base. Next, we estimate PV technical potential at the building-level using our combined building/solar dataset and other standard assumptions for such inputs as PV specifications. To assess the financial feasibility, we estimate the average prices of electricity from Open EI and obtain incentive information from DSIRE and North Carolina State’s 50 States of Solar. Project costs include installation, operation, maintenance and financing costs where applicable; costs are estimated using the NREL OpenPV dataset. Quantified benefits include savings from avoided electricity costs and regional environmental and health benefits, estimated with our own existing model that incorporates emissions and damages data from such sources as the EPA’s Continuous Emissions Monitoring System and the Air Pollution Emissions Experiments and Policy analysis (AP2) model. We also identify which schools in our model are located near low-income communities and have a unique opportunity to promote clean energy generation for at-risk populations. Finally, we validate the technical and cost savings potential outputs of our model with Google’s Project Sunroof and PVWatts. Our research identifies regions that can benefit the most from solar PV on higher education institutions, which stand to be leaders of sustainability in their communities.