Robust scheduling of electric vehicle charging stations with price-based demand response under decision-dependent uncertainty

As electric vehicles become one of the primary modes of urban transportation, the randomness in users’ charging behaviors poses notable charging service congestion risks to electric vehicle charging stations. To mitigate localized service congestion, this paper introduces a price-based demand response mechanism into charging station operational scheduling, where appropriate pricing guides orderly charging and induces load shifting. First, a demand response model is developed by incorporating both self-price and cross-price elasticities to capture the spatial transferability of charging demand among charging stations. Second, to characterize the response-deviation uncertainty caused by environmental factors and user psychological behaviors, a price decision-dependent uncertainty set is proposed. Finally, under the decision-dependent uncertainty framework, a two-stage robust scheduling optimization model is formulated and solved. Simulation results demonstrate that the proposed price-based demand response mechanism effectively guides load migration and alleviates charging service congestion. Moreover, compared with conventional decision-independent uncertainty sets, the proposed decision-dependent uncertainty set significantly reduces the conservatism of robust scheduling and yields more effective pricing incentives, thereby further reducing operating costs and improving charging load accommodation.