Research On The Assistant Decision System Of Electric Vehicle Users Participating In Frequency Regulation Market Quotation

With the rapid increase in installed capacity and continuous expansion of the scale of renewable energy such as wind power and photovoltaics,new demands are being put forward for frequency regulation in the new power system.The number of electric vehicles is increasing and the Vehicle-to-Grid technology is becoming increasingly successful.Under the background of the above,it has become a new research idea to use electric vehicles to solve the frequency fluctuation problem of the power system.Existing studies mostly use aggregators to manage electric vehicle clusters and participate in the frequency regulation ancillary services market.However,they fail to fully consider user preference and maximize the interests from the perspective of users.In practice,it will be difficult to attract enough electric vehicle users to sign up with aggregators.When electric vehicles,especially electric private cars,express user preferences through their day-ahead quotation schemes,the main reasons affecting electric vehicles participating in the frequency regulation ancillary services market are as follows:1)The quotation mechanism is not friendly to users.Users need to quote almost every day,and the workload is very large.2)Users lack relevant knowledge and may not be able to submit the optimal quotation schemes and estimate the corresponding interests and costs.Therefore,further research is needed to develop a convenient and efficient quotation model to assist users in completing quotation schemes.The quotation model will help address the difficulties users face in the quotation and increase the willingness of electric vehicles to participate in the frequency regulation ancillary services market.Expected utility theory describes individual decision-making behavior based on the assumption of perfectly rational person.It is important for describing individuals’long-term decision-making behavior.But in reality,people are bounded rationality.It is closer to reality by using prospect theory to describe individual decision-making behavior under uncertain conditions.The two theories are complementary and provide a comprehensive explanation of individual decision-making behavior.Therefore,this paper takes a single private electric vehicle as the research object.The decision aid model(DAM)based on expected utility theory is established and the decision model(DM)based on prospect theory is also established.Given that energy flows are bidirectional between electric vehicles and the grid,this paper presents three frequency regulation participation modes through reasonable simplification of user preferences.They are base mode(BM),unidirectional charging Mode(UCM),and bidirectional charging/discharging mode(BCDM).Based on three participating modes,DAM and DM use bidding policy and response control policy to optimize the process of day-ahead quotation.The quotation schemes with the maximum expected revenue and the maximum combined prospect value are generated for users to choose from.With the help of DAM or DM,users can participate in the frequency regulation ancillary services market by inputting basic travel information.It will help users to reduce the difficulty of participating in the frequency regulation ancillary services market independently.Moreover,the quotation models under the two theories fully consider user preferences and maximize their interests from the perspective of users.This could help attract more electric vehicle users to participate in the frequency regulation ancillary services market.And more and better frequency regulation resources will be fully utilized.The feasibility and validity of the quotation model under the two assumptions are verified by the simulation results.