Wednesday, December 12, 2018 - 3:00pm to 4:00pm
Event Calendar Category
LIDS & Stats Tea
MIT Energy Initiative
Building and Room Number
The stochastic future can be reduced to a cost-to-go value function of the system state variable for fast and optimal real-time decision making, following the concept of dynamic programming, this serves as a potential solution to the ongoing real-time energy storage dispatch problem, however finding the optimal cost-to-go function for the complex power system remains a challenge. This study provides an algorithmic insight into constructing a piece-wise linear cost-to-go function for energy storage state-of-charge through scenario-based numerical simulations. The proposed method has much lower computation complexity and can be implemented in parallel, allowing the power system economic dispatch to adapt to the newest forecast at the earliest possibility.
Bolun Xu is a postdoctoral associate at the MIT Energy Initiative working with Dr. Frank O'Sullivan and Dr. Audun Botterud. He is also a member of the electric energy systems group at LIDS. He received his PhD degree in Electrical Engineering from University of Washington, Seattle in 2018 and his research interests are on power system economics and energy storage.