Coordinated Optimization of Coupled Power–Traffic Networks: A Hierarchical SUE Method Considering Behavioral Preferences and Uncertainty

The rapid proliferation of electric vehicles intensifies the interdependence between transportation and power networks, posing operational challenges due to stochastic routing decisions and the spatiotemporal heterogeneity of charging demand. This paper proposes a hybrid decision-making framework that integrates user behavioral modeling with system-level optimization for coupled power-traffic networks. First, we develop network models that incorporate integrated energy stations (ESs) and heterogeneous vehicle classifications grouped by charging requirements and grid-response capabilities. Second, we formulate a hierarchical nested logit-based stochastic user equilibrium model to characterize multi-level user decisions under uncertainty. Furthermore, a collaborative power-traffic dispatch model is constructed to minimize generalized user costs, encompassing travel, charging, ES attributes, and power distribution network operation. A two-stage distributed solution algorithm is further developed to ensure computational tractability. Case studies on two test systems demonstrate the method's efficacy in characterizing user behavioral uncertainties and coordinating integrated power-traffic flows.