Distributed scheduling model of multi-network coupled energy system considering dynamic charging price mechanism and multiple utilization of hydrogen energy

Driven by policies for deep decarbonization, this paper proposes the distributed scheduling model of multi-network coupled energy system considering dynamic charging price mechanism and the multiple utilization of hydrogen energy, with the goal of fully tapping the potential of coordinated operation among transportation network (TN), virtual power plant (VPP), gas distribution network (GDN), and power distribution network (PDN). First, based on the unique spatiotemporal flexibility of electric vehicle, the dynamic charging price mechanism integrating the TN-VPP operating status is proposed. Plug-in electric vehicle (PEV) and hydrogen fuel cell vehicle (HFV) are orderly guided according to road congestion, charging station saturation, and energy availability, achieving the triple benefits of alleviating traffic congestion and improving power quality and system economics. Second, the VPP distributionally robust optimization model based on the multiple utilization of hydrogen energy is constructed to achieve coordinated scheduling of hydrogen production, storage, and utilization. Third, the hydrogen-doped GDN model considering the physical properties of gas was constructed from three aspects: pressurization energy consumption, permeation loss and pipeline maintenance. Finally, the distributed solution framework based on the TM-ADMM-AOP algorithm is established to improve model convergence performance. The effectiveness of the proposed model is verified through case studies. • The distributed scheduling model of multi-network coupled energy system is proposed. • Dynamic charging price mechanism is formulated to guide the charging order of EV. • Multiple utilization mode of hydrogen energy improves energy efficiency. • Hydrogen-doped GDN transportation cost is constructed based on the physical property. • The TM-ADMM-AOP distributed algorithm is proposed to improve the convergence.