Stochastic Energy Storage Control and Electric Vehicle Charging

The student develop custom stochastic algorithms to optimize energy storage control in price arbitrage and V2G electric vehicle charging. The student will perform a stochastic dynamic programming algorithm to calculate the value-to-go function for each storage, and design a priority queuing system to dispatch storage. 

Name of Lab: Xu Lab

Direct Supervisor: Bolun Xu

Hours per week: 20 

Position type: Hybrid (both Remote and On Site)

Qualifications: Energy storage, stochastic optimization

Eligibility: Senior, Master's 

SEAS students only: Yes