This research develops a co-design optimization framework for microgrids that simultaneously designs physical infrastructure and control systems. By improving both reliability and cost-effectiveness, it enables more resilient renewable energy networks, supports upgrades to existing microgrids, and helps communities maintain electricity during extreme weather events and grid failures.

This research uses functional regression to forecast how climate change will affect electricity demand across California. By modeling complete demand patterns rather than isolated data points, it aims to help design smarter, more resilient, and more equitable power grids that reduce outages during increasingly frequent heatwaves and extreme weather.