Electric vehicles (EVs) are recognized as a promising remedy for the environmental crisis and fuel shortage faced by modern metropolises. But meanwhile, with the popularization of EVs, the unordered charging of EVs will have negative impacts on both the power distribution network (DN) and the traffic network (TN). The well scheduled EV charging/discharging behaviors could participate in the coordinated operation of TN and DN to significantly enhance the energy utilization efficiency of both networks. With an assumption that an entity like State Grid capable of dispatching distributed generators (DGs) and adjusting charging prices of fast charging stations (FCSs), a traffic-distribution coordination (TDC) model is proposed to minimize the travel cost of TN and energy service cost of DN, which simultaneously considers the economic operation of DN by alternating current dynamic optimal power flow (AC DOPF) and the traffic flow assignment of TN by EVs dynamic user equilibrium (DUE) respectively. And afterward the augmented Lagrangian alternating direction inexact Newton (ALADIN) method is adopted to solve the TDC model. Finally, the necessity of coordinated operation of TN and DN and the effectiveness of TDC model are validated in an integrated system of modified Nguyen-Dupius TN and IEEE 33-bus DN.

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To achieve the "carbon peak" and "carbon neutrality" goals, the power industry is the main battlefield and main force. Compared with the long carbon reduction path after natural peak in major European and American countries, the carbon peak, plateau period, and transformation path under the "dual carbon" goal in China will be completely different. This article establishes a multi-scenario analysis framework for the transformation path of the power industry under the "dual carbon" goal, and constructs three major scenarios. It analyses the low-carbon transformation path of power system including power source structure and carbon emissions under different scenarios and proposes policy recommendations.