Joint Optimization for Coordinated Charging Control of Commercial Electric Vehicles Under Distributed Hydrogen Energy Supply.

The transition to the zero-carbon city is underway accelerating recently. Hydrogen energy and electric vehicles (EVs) are promising solutions on the supply and demand sides of zero-carbon power system. This paper presents a novel architecture that includes the hydrogen production stations (HPSs), fast charging stations (FCSs) and commercial EV fleet for passenger transportation. The proposed architecture jointly optimizes the distributed hydrogen energy dispatch and the EV charging location selection to minimize the operating cost, and is formulated by a time-varying bi-level bipartite graph (T-BBG) model for real-time operation. Based on the receding-horizon control framework, we develop a bi-level iteration optimization method combining mixed-integer linear programming (MILP) and Kuhn-Munkres (KM) algorithm to solve the joint optimization problem whose optimality is proved theoretically. The effectiveness of the proposed architecture on reducing the operating cost is verified via case studies in Shanghai. The proposed method outperforms other strategies and improves the performance by at least 13% which shows the potential economic benefits of the joint architecture. The convergence and impact of the pile number, battery capacity, EV speed and penalty factor are assessed.