Numerous Electric Vehicle Charging Aggregation, Bidding and Management

The participation of large-scale electric vehicles (EVs) in grid interactions is hindered by factors. Firstly, the heterogeneity of their parameter information results in a high degree of complexity and inefficiency in the calculation of their dispatchable capacity. Secondly, the absence of an effective scientific bidding management strategy limits the participation of EVs in electricity markets. Considering the considerations, this paper puts forth a bidding and operation management method for EV operators, one that is based on an improved Minkowski additive dynamic aggregation. First, clustering is performed based on the characteristics of electric vehicle charging behaviors, and the power curves of each cluster of EVs are represented as a polyhedral model containing operational constraints through Minkowski addition. A scaling factor is introduced to account for individual differences, thereby establishing a dispatchable capacity assessment model for electric vehicle clusters. Furthermore, considering the operators' participation in the electricity market, a bi-level bidding model is established and transformed into a Nash equilibrium problem to simulate competitive relationships among operators. Simulation results show that the method can effectively address the impact of large-scale EV information heterogeneity on the aggregation process and significantly improve computational efficiency and accuracy. Moreover, the operation and management method reduce the operation cost and load fluctuation, assists the power system in peak and frequency regulation, and realizes the orderly interaction between large-scale EVs and the power grid.