Model Predictive Control-Based Real-Time Optimal Charging of Electric Vehicle Aggregators
- Resource Type
- Conference
- Authors
- Gong, Liling; Guo, Ye; Sun, Hongbin; Deng, Weisi
- Source
- 2022 IEEE Power & Energy Society General Meeting (PESGM) Power & Energy Society General Meeting (PESGM), 2022 IEEE. :1-5 Jul, 2022
- Subject
- Engineering Profession
Power, Energy and Industry Applications
Uncertainty
Stochastic processes
Programming
Predictive models
Regulation
Real-time systems
Numerical models
electric vehicle aggregator
model predictive control
regulation service
electricity market
- Language
- ISSN
- 1944-9933
The optimal operation problem of electric vehicle aggregator (EVA) is considered. An EVA can participate in energy and regulation markets with its current and upcoming EVs, thus reducing its total cost of purchasing energy to fulfill EVs' charging requirements. A model predictive control (MPC) based optimization is developed to consider the future arrival of EVs as well as energy and regulation prices. The index of conditional value-at-risk (CVaR) is used to model the risk-averseness of an EVA. Simulations on the 1000-EV test system validate the effectiveness of our work in achieving a lucrative revenue while satisfying the charging requests from EV owners.