Project 2
Renewable Energy Economics Project - Victor Bogin
I conducted an analysis of renewable energy using data and information from the UCLA department of Economic, Department of Public Policy, and publicly available data sets. I examined generation trends across regions, focusing on hydroelectric, wind, and solar resources using economics and policy research data. With Excel and R, I performed trend and regression analyses to evaluate how renewable output responds to new project installations, seasonal patterns, policy incentives, and resource availability while accounting for development lead times.
The results showed strong growth in solar and wind generation, driven primarily by capacity additions rather than efficiency gains. Estimated trends indicated annual growth of roughly 6–10% for solar and 4–7% for wind. In contrast, hydroelectric generation remained relatively stable over time and was largely dependent on precipitation, making it difficult to predict accurately without detailed hydrological information.
I then developed a lifecycle performance model that incorporated construction timelines, gradual efficiency changes, project retirements, and replacement cycles. Combining this with expected installation growth and demand trends, I forecast renewable generation through 2026. The findings highlight continued expansion in solar and wind output, while hydroelectric production remains comparatively uncertain, offering insights for renewable investment decisions and grid planning.