Optimal Day-Ahead Charging and Frequency Reserve Scheduling of Electric Vehicles Considering the Regulation Signal Uncertainty
Yan Cui, Zechun Hu, Haocheng Luo
Abstract
With large-scale integration of intermittent renewable energy sources (RESs), power systems need more ancillary services to guarantee system stability and security. When properly managed, large-scale electric vehicles (EVs), whose markets have been growing rapidly in recently years, can provide frequency regulation service for power systems, benefiting both EVs and the grid. However, interests balance between different parties and regulation signals uncertainty are not well considered when deploying EVs to provide regulation services in previous studies. In this article, a leader-follower game is proposed for individual EVs and their aggregator to determine optimal day-ahead charging and frequency reserve scheduling considering regulation signals uncertainty. Acting as the leader in the game, the EV aggregator prices for its charging service and offers for regulation service to encourage EVs' participation. EVs act as price-takers and aim at achieving a tradeoff between costs from electricity consumption and revenues from providing regulation service through an aggregative game. The proposed leader-follower game is then converted to a bilevel optimization problem, which can be solved by introducing an aggregate EV model. Furthermore, for the sake of privacy protection, a distributed approach is designed for EVs to optimize their scheduling. Case studies with the proposed scheduling model are carried out to demonstrate its effectiveness.