This paper addresses a control mechanism to strengthen the cross-sector resilience of dynamic energy and mobility systems. To realize electrification towards decarbonizing smart cities and early recovery in emergencies, the real-time management of electric vehicles (EVs) is essential. EVs cannot achieve both the energy management function and the mobility function depending on user behavior in parallel. To minimize the physical costs and the enforced human behavior change, the dynamic optimization problem of cross-sector energy and mobility systems is proposed. Through simulations imitating the central Tokyo area, the effectiveness, economic cost, and environmental impact of the proposed algorithm are also numerically evaluated.
