A Distributed EV Navigation Strategy Considering the Interaction Between Power System and Traffic Network

Abstract

Increasing number of drivers are switching to electric vehicles (EV) for higher efficiency, lower environmental impact and less maintenance cost. To promote the EV revolution, charging issues of EVs needs to be well addressed. Since the traffic flow of the transportation network and the operating conditions of the power systems are time-varying, it is important to implement real-time charging navigation for EV drivers. In this paper, a novel navigation approach is proposed to search the fast charging station with the lowest overall objective, which consists both of the time consumption and the financial cost. The traffic condition and distribution system loading level are reflected by the time consumption on each road section and locational marginal price (LMP) at each fast charging station, respectively. The LMP can act as a signal to divert the EV load and thus relieve the traffic and power line congestions. The proposed navigation approach is based on the multi-agent system framework utilizing the distributed min/max- consensus and the biased min consensus algorithms. Simulations demonstrate the effectiveness of the proposed navigation approach in different scales of systems.