Distributionally Robust Coordinated Scheduling of Power-Transportation Systems Considering Bounded Rationality and Flexible Swapping of Electric Vehicles

Large-scale electric vehicles (EVs) integration demand coordinated power-transportation systems to optimise charging loads and grid flexibility, whereas existing strategies inadequately address range anxiety, peak demands and photovoltaic (PV) operational uncertainties. To address these issues, this work proposes a power-transportation coordination model integrating flexible swapping. The model strategically guides EV users towards swapping stations by embedding bounded rationality parameters within a stochastic user equilibrium framework, mitigating anxiety while balancing charging-swapping loads. This work also develops a distributionally robust optimisation framework to address PV uncertainty, enhancing resilience against generation fluctuations. Numerical simulations demonstrate that battery swapping integration significantly reduces distribution network peak loads and shortens user waiting times compared to charging-only approaches. The proposed method outperforms deterministic models by reducing conservativeness and aligning more closely with real-world operational dynamics, validating its efficacy in harmonising user behaviour and grid constraints under uncertainty.