Operation Optimization And Bidding Strategy Of The Electric Vehicle Aggregator Participating In Day-ahead Electricity Markets

Under the background of the new round of electric industry reform in China,the spot markets construction has been put on the agenda,among which day-ahead markets are suitable for prior development,where demand-side resources will also play an important role.Demand-side large-scale electric vehicle resources supported by vehicle to grid(V2G)technology will have superior adjustability.The introduction of electric vehicle aggregators will help realize their friendly interaction with the power system.In this context,this paper focuses on the operation optimization and bidding strategy of the electric vehicle aggregator participating in day-ahead electricity markets.Firstly,the V2G technology is introduced and the characteristics of the electric vehicle resources are analyzed.Since individual electric vehicles are not suitable for independent participation in the wholesale market,the electric vehicle aggregator is introduced as a commercial middleman between electric vehicles and the market in order to use the economies of scale to achieve market entry thresholds,reduce costs and improve the availability and reliability of ancillary service provision.The electric vehicle aggregator has the potential to benefit from participating in energy market and ancillary service markets.Their businesses include trading in wholesale markets and service for electric vehicle owners,among which voluntary-charging consumers and flexible-charging consumers are suitable for time-variant retail rate programs and charge and discharge management respectively under contracts.Then,the electric vehicle aggregator is regarded as a price-maker for decision-making issues in the day-ahead energy market.A bi-level model representing its day-ahead operation optimization as well as day-ahead market clearing is established.The proposed nonlinear mixed integer bi-level programming problem is transformed into a single-level mixed integer linear programming problem based on the complementarity theory and linearization methods.Simulation results show that the aggregator's net cost is the lowest under the price-maker strategy,while implementing the price-taker strategy deviates its decision from the optimal solution,verifying the necessity for considering the impact of demand-side resources' strategic bidding behavior on market clearing results;gains from discharging electric vehicles are not significant.The economy of arbitrage behavior by discharging would be further weakened if the resulting battery extra degradation cost is taken into account.For the decision-making issues of participating in both the day-ahead energy market and ancillary service markets,the objective function terms and constraints related to regulation and reserve services provision are further taken into account in the operation optimization model of the electric vehicle aggregator.A joint optimization model for the aggregator to participate in day-ahead energy and ancillary service markets is proposed for the optimization of aggregator's bidding strategy and flexible allocation of its electric vehicle resources.Simulation results show that participation in the ancillary service markets could significantly reduce the aggregator's total cost.Participating in both the regulation market and the reserve market brings more profits than those brought by only participating in one of them.The ancillary service market revenues mainly come from the capacity revenue.The regulation market net revenue is obviously reduced because of battery extra degradation cost that is resulted from regulation service provision.The electric vehicle's ability to discharge power is critical for increasing profits in the ancillary service markets.