Distributed Dynamic Tariff for Congestion Management in Distribution Networks Considering Temporal-Spatial Coordination of Electric Vehicles

A distributed dynamic tariff (DDT) method was proposed in this study for congestion management in distribution networks considering the temporal-spatial coordination of electric vehicles (EVs). First, a quadratic DT-based congestion management model was formulated considering the full travel route as well as charging and discharging (C&D) behavior of EVs in the transportation network. Second, a distributed congestion management framework based on the asynchronous distributed alternating direction method of multipliers (AD-ADMM) was introduced. Using the proposed framework, DDTs were iteratively optimized between the distribution system operator (DSO) and aggregators to achieve optimal EV routing in the transportation network and congestion management in the distribution network. Finally, case studies were conducted on two test systems, and the numerical results showed that the proposed DDT method can optimize the temporal-spatial distribution of EVs in the transportation network, minimize the travel time and C&D costs of EVs in each aggregator, and effectively avoid congestion in the distribution network. Moreover, the optimization efficiency and privacy information protection of aggregators in the DT-based congestion management method could be improved.