Josh Kolenbrander ’23
Operations Research and Financial Engineering
Analysis of Global Energy Infrastructure Trends
My internship focused on cleaning and summarizing large data sets of energy-system transition models. I analyzed the Shared Socioeconomic Pathways database and the Energy Technology Perspectives scenario, which describe energy-system transitions for a variety of climate and socioeconomic contexts. I extracted from these data carbon capture and storage usage information across various regions, scenarios, energy sectors and time ranges. I primarily used Python’s pandas, numPy, Matplotlib and seaborn libraries to tabulate, clean and visualize the data. An important part of my internship was creating code that is modular and flexible so that the user can extract many different types of visualizations about the data they want. Additionally, I contributed to a project that aims to cluster power plants in India by similar characteristics. My role was to create a code base in Python that extracts plant information from large spreadsheets and stores it in a SQLite database structure. Through this internship, I gained an appreciation for energy-sector modeling and a familiarity with relevant technologies for data analysis and visualization within data science, a career path I would like to explore further.
Innovation and a New Energy Future
Lane Group, Princeton Institute for International and Regional Studies (PIIRS), Princeton University
Joe Lane, Associate Research Scholar and Lecturer, PIIRS