Achieving Consensus in Self-Organizing Electric Vehicles for Implementing V2G-Based Ancillary Services

The integration of Electric Vehicles (EVs) equipped with Vehicle-to-Grid (V2G) technology has been recognized as a promising solution to enhance the flexibility of modern power distribution systems. However, to make this a reality, there is a need for flexible, reliable, and highly scalable computing architectures that can coordinate the charging and discharging process of EV fleets while identifying the best trade-offs between the vehicle charging expectations and the grid requirements. This challenging problem has been formalized in this paper as a welfare maximization problem, by defining proper utility functions to quantify the marginal cost/benefits of the charging and discharging process. Then, a self-organizing solution scheme is proposed in the task of enabling the EVs fleet to solve the welfare maximization problem by only exchanging local non-sensitive information. The insight is to define a formal connection between the charging/discharging scheduling problem and the economic dispatch of thermal generators, hence exploiting all the vast literature on the theory of the marginal cost for the decentralized solution of the scheduling problem, which is one of the main contributions of this paper. Simulation results obtained on two case studies are presented and discussed in order to assess the effectiveness of the proposed technique in solving complex scheduling problems in realistic operation scenarios.