With the increasing penetration of new-type loads such as electric vehicles and hydrogen fuel vehicles in urban power grids, the peak-to-valley load difference increases sharply, and a multi-energy coordination model is desirable. This article proposes a day-ahead operation model of an urban energy system considering traffic flows and peak shaving, which can positively contribute to multi-energy complement and low-carbon emission. The proposed model minimizes the total cost of electricity and gas by optimizing the charging and discharging strategies of energy storage, in which the output of the wind turbine and energy management of the energy hub are adaptively adjusted. The urban energy system is represented by a second-order cone (SOC) energy flow model, and hence, the optimization problem is modeled as a mixed integer SOC programming (MISOCP). Finally, test results on an integrated urban energy network indicate that the energy storage and multi-energy coordination can alleviate the peak load cutting and valley filling. The relationship between urban grid operation cost and peak-valley difference is also discussed. The maximum utilization of renewable energy sources using gasoline vehicles has been presented in this study to illustrate cost and emission reductions for a sustainable integrated electricity and transportation infrastructure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.