Our project tackles the challenge of managing power flow in microgrids, especially with the increasing use of renewable energy. We’re creating a new solution using a differential-dynamic programming solver within the SUGAR-3 framework. This approach is unique for microgrids with dynamic renewable energy and battery storage. We’re also building a simple web interface for experts to design and simulate microgrids, showcasing optimal control settings and grid states. Additionally, we’re incorporating machine learning to predict renewable energy output and load usage. Overall, our project aims to make microgrid management more efficient and user-friendly for everyone.
A Visual and Intuitive Microgrid Energy Management System