Bidding Strategy Research for Aggregator of Electric Vehicles Based on Clustering Characteristics

With the opening of the power distribution side and the power sales side of the power market, and the rapid increase of the number of electric vehicles (EVs) used, more and more attention has been paid to the study of EVs which are as flexible loads participating in the bidding of power market. This paper, under a certain power market environment, carries out cluster analysis according to the driving characteristics of different EV subgroups. Aiming to minimize the charging cost of the EV aggregator, considering the market clearance constraints and EVs charging load constraints, this paper establishes a two-level optimal bidding strategy model for EVs aggregator participating in the power market. According to KKT condition and dual principle, this model is transformed into mixed integer linear programming problem. An example shows that this bidding strategy of EV aggregator based on cluster characteristics can effectively reduce the charging cost of EVs.