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Electrified transportation and power systems are mutually coupled networks.In this paper, a novel framework is developed for interdependent power andtransportation networks. Our approach constitutes solving an iterative leastcost vehicle routing process, which utilizes the communication of electrifiedvehicles (EVs) with competing charging stations to exchange data, such aselectricity price, energy demand, and time of arrival. EV routing problem issolved to minimize the total cost of travel using the Dijkstra algorithm withthe input from EVs battery management system, electricity price from chargingstations, powertrain component efficiencies, and transportation network trafficconditions. Through the bidirectional communication of EVs with competingcharging stations, EVs charging demand estimation is done much more accurately.Then, the optimal power flow problem is solved for the power system, to findthe locational marginal price at load buses where charging stations areconnected. Finally, the electricity prices are communicated from the chargingstations to the EVs, and the loop is closed. Locational electricity price actsas the shared parameter between the two optimization problems, i.e. optimalpower flow and optimal routing problem. Electricity price depends on the powerdemand, which is affected by the charging of EVs. On the other hand, locationof EV charging stations and their different pricing strategies might affect therouting decisions of the EVs. Our novel approach that combines the electrifiedtransportation with power system operation, holds tremendous potential forsolving electrified transportation issues and reducing energy costs. Theeffectiveness of the proposed approach is demonstrated using Shanghaitransportation network and IEEE 9-bus test system. The results verify thecost-savings for both power system and transportation networks.

Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks