Project 2
Renewable Energy Economics Project - Victor Bogin
Using data from the UCLA Center for Economics and Policy, I analyzed historical power generation from hydro, wind, and solar energy sources across different regions. With Excel and R, I ran trend and regression analyses to understand what drives changes in renewable output, such as seasonal weather patterns, new project installations, and shifts in resource availability.
Based on these insights, I created a model to estimate how renewable energy systems perform over their lifetimes. The model accounts for when plants are built, how their efficiency changes over time, and when older projects are replaced or retired. I then combined this with expected growth in new installations and energy demand to forecast renewable production through 2026.
The analysis suggests that solar generation will grow by around 55% between 2022 and 2026, while wind output is expected to rise by roughly 35–40%, and hydroelectric power will stay relatively stable. These results can help guide decisions about where to invest in new energy projects, how to plan grid capacity, and when to expand clean energy infrastructure to meet future demand.