Universities and higher education institutions across the country are often seen at the forefront of social and environmental change, the catalysts for the rest of the country. Universities such as Stanford and Cornell are the leaders of this environmental change, making solid and proven steps toward carbon neutrality. The University of Virginia has also made steps toward net zero emissions, but still have some work to do. Both of my projects focused on what methods these universities are using to reach their emission goals, and how these strategies can be implemented at the University of Virginia. For the technical project, my team and I used the Tools for Energy Modeling Optimization and Analysis (TEMOA) to predict when peak energy demands occur at UVA and to understand how interventions, such as heat recovery chillers and thermal storage tanks, might be used to balance load and also scaled these strategies to the whole state of Virginia. In my STS research, I go in depth into my finding when studying the strategies of decarbonization for Stanford University and Cornell University. I chose these two universities because from they are rated in the top three institutions across the country that lead the way in carbon neutrality, according to the sustainability tracking, assessment and rating system (STARS) produced by the Association for the Advancement of Sustainability in Higher Education (AASHE). For both Stanford and Cornell, I study their sustainability offices’ climate action plans and compare their emission goals and how they are achieving those goals. I also take into account the cost effectiveness of the methods and study how they could be applied to the University of Virginia. The technical portion of my thesis analyzed how energy load-shifting technologies could be scaled to larger universities such as UVA by focusing on the Fontaine Research Park. Using the predictive TEMOA model along with institutional energy data, my team studied how application of distributed energy technologies in the state of Virginia and at UVA could have an effect on the grid’s ability to apply these methods. Our research and models showed that on a state-scale level, balancing energy loads had a minimal effect. However, for individual institutional use, it could prove to be a helpful resource in lowering energy use and demand as well as reducing cost. My research and work with my team inspired my STS research to continue to study other ways universities and institutions of higher education can lower carbon emissions in an efficient and cost effective way.