A personalized network-aware price design for electric vehicle charging using a sequential Stackelberg game

This study develops a personalized network-aware price design for electric vehicle (EV) charging in an unbalanced distribution network to achieve the social welfare maximization while respecting distribution network constraints. Under this price design, the independent distribution system operator (IDSO), as the leader, and aggregators, as followers, engage in a sequential Stackelberg game to determine the personalized network-aware retail price profiles and the EV charging schedules for customers. This design integrates not only network-level constraints, including peak demand limits, voltage limits, and line congestion limits, into the personalized network-aware retail price profiles, but also customer-level personalized preference, attribute and locational information, leading to an informative structure of those retail price profiles. Finally, the convergence and optimality properties of this design, based on the fast dual decomposition algorithm, are established.