Bi-Level Optimization Dispatching of Hydrogen-Containing Integrated Energy System Considering Electric Vehicles and Demand Response

The rapid proliferation of electric vehicles (EVs) has introduced significant challenges to the efficient operation of hydrogen-containing integrated energy systems (H-IESs). To cope with these challenges, this paper develops a bi-level optimal scheduling strategy for H-IESs that simultaneously incorporates a ladder-type carbon emission trading mechanism, demand response, and the operational characteristics of EVs. A demand response model is formulated by considering the coupling characteristics of electric and thermal loads. Price-based incentive signals are further designed to coordinate the interactions between the H-IES operator and EV users, enabling flexible resources to actively participate in system scheduling. In the proposed bi-level framework, the upper-level problem aims to minimize the total operating cost of the H-IES, while the lower-level problem seeks to reduce the charging cost of EV users. The resulting bi-level optimization problem is reformulated and solved using the Karush–Kuhn–Tucker (KKT) conditions. Case study results demonstrate that, compared with the single-level benchmark, the proposed bi-level strategy reduces the total operating cost by 34.79% and lowers the EV charging cost by 4.50%.