Robust Coupled Power Transportation Network Equilibrium for Heterogeneous Electric Vehicles Considering Charging Station Utilization

To address the interaction and collaborative optimization issues of the coupled power transportation network (CPTN) amid the rapid development of electric vehicles (EVs), this paper proposes a robust coupled power transportation network equilibrium (NE) approach for heterogeneous EVs considering charging station (CS) utilization. First, the uncertainty of actual traffic flow is modeled via the distributionally robust chance constraint (DRCC) based on the Chebyshev inequality. Based on M/M/N queuing theory, CS average waiting time is optimized to balance utilization of CS and alleviate power congestion. Then, to reduce redundant computations, a NE iterative solution method is proposed, which solves for the NE solution without the need to enumerate all feasible routes and CSs. Route and CS location constraints are proposed to guide rational CS selection for EVs. A feasible route and CS selection matrix for EVs is proposed, which effectively addresses the NE problem of heterogeneous EVs. A linearization method is developed to reduce the computational complexity of the NE solution approach. CS prices are tied to the locational marginal prices (LMP) of the distribution network (DN) to cut DN operating costs. Finally, the effectiveness of the proposed method is verified using real EV data, the simplified Chengdu and Anaheim transportation network (TN), as well as the modified IEEE 69-bus and 141-bus systems. The results demonstrate that the proposed method can rapidly solve the robust NE for heterogeneous EVs and effectively balance CS utilization.