CTM-Based Collaborative Optimization of Power Distribution Network and Urban Traffic Network with Electric Vehicles

With the increased penetration of electric vehicles, wireless charging electric vehicle (WCEV) is more popular than ever before, which results in a tight spatial-temporal coupling of Power Distribution Network (PDN) and Urban Traffic Network (UTN). Under the dynamic wireless charging mode, a large amount of charging power of WCEV would be shifted during the commuting period and possibly coincides with the original peak load of PDN and thus lead to the congestions of PDN and UTN. To solve this problem, in this paper a traffic network dynamic assignment model is firstly set up based on a cell-transmission model (CTM) with an optimal power flow model of PDN presented by a mixed integer second-order cone programming, afterward a collaborative optimization model of PDN and UTN is established to simulate the spatial-temporal distribution of WCEVs’ charging load, the congestion of PDN and UTN during a traffic jam is well alleviated by optimally determining the electricity charging price. Through the joint simulation of PDN and UTN, the congestion propagation mechanism of PDN and UTN is revealed, and the effectiveness of the proposed model is verified. Furthermore, a coordinated optimization scheme of PTN is proposed to study the impact of rational allocation of active and reactive power resources on congestion in the PTN-UTN coupling model.