A robust optimization scheduling strategy for "vehicle-road-network" systems considering dual uncertainty

Abstract

With the increasing number of electric vehicles (EVs), the "vehicle road network" system will face operational uncertainties in both the road network and the power grid. This article considers the uncertainty of the operation status of "vehicle road network". And a robust optimization scheduling strategy for "vehicle road network" considering dual uncertainty is proposed. Firstly, based on the Stackelberg game theory, a "vehicle road network" system optimization scheduling architecture is proposed. Secondly, in response to the optimization problem of operating costs for upper level leaders in the distribution network (DN), a robust optimization model for DN is constructed considering the uncertainty of photovoltaic power generation to achieve optimization of operating costs for the distribution network. On the basis of considering the uncertainty of travel time caused by road network, lower level followers of EVs participate in demand response based on the charging prices which are set by the distribution network. The simulation results show that the proposed optimization scheduling strategy can effectively reduce the operating costs of DN. The traffic pressure is alleviated. And the operational efficiency of fast charging stations is improved.