Bidding Strategies in Energy and Reserve Markets for an Aggregator of Multiple EV Fast Charging Stations With Battery Storage

Adopting extreme fast charging for electric vehicles will significantly reduce the charging time for electric vehicle owners, which will improve the public acceptance of electric vehicle. However, under the conditions of wide spread fast charging stations, large charging power of fast charging stations will bring nonnegligible impacts to the power system. For an aggregator that owns multiple fast charging stations, installing battery storage systems within the fast charging stations can reduce the impacts and give more flexibility. It will bring extra benefit if the aggregator participates in electricity markets by utilizing the flexibility of the storage. In order to deal with the operation and market participation problem for EV fast charging stations, this paper proposes bidding strategies in both energy and reserve markets for an aggregator of multiple fast charging stations with energy storage systems. Conditional Value at Risk (CVaR) based mixed integer quadratic programming formulation is built to hedge the risks of random charging demands and volatile market prices. The proposed formulation is converted into a linear programming problem and an iterative solution method is designed to reduce the computation time. Case studies based on the trajectory data of taxis in Beijing have been carried out. Simulation results show that the aggregator can achieve higher economic benefits while satisfying the fast charging demand of electric vehicles.