M. Hadi AminiOrkun KarabasogluAmini, M. HadiKarabasoglu, Orkun2025-10-062018199610731996-107310.3390/en110101962-s2.0-85042650786https://www.scopus.com/inward/record.uri?eid=2-s2.0-85042650786&doi=10.3390%2Fen11010196&partnerID=40&md5=e997d252ce474340c72eb36b548ace6bhttps://gcris.yasar.edu.tr/handle/123456789/9634https://doi.org/10.3390/en11010196Electrified transportation and power systems are mutually coupled networks. In this paper a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process which utilizes the communication of electrified vehicles (EVs) with competing charging stations to exchange data such as electricity price energy demand and time of arrival. The EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system electricity price from charging stations powertrain component efficiencies and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations EVs' charging demand estimation is done much more accurately. Then the optimal power flow problem is solved for the power system to find the locational marginal price at load buses where charging stations are connected. Finally the electricity prices were communicated from the charging stations to the EVs and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems i.e. optimal power flow and optimal routing problem. Electricity price depends on the power demand which is affected by the charging of EVs. On the other hand location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks. © 2018 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/openAccessCharging Station, Electrified Transportation Network, Electrified Vehicle, Least Cost Route Optimization, Locational Marginal Price, Power Systems Operation, Acoustic Generators, Battery Management Systems, Charging (batteries), Electric Load Flow, Iterative Methods, Location, Vehicle Routing, Vehicle To Vehicle Communications, Vehicles, Charging Station, Electrified Vehicles, Least Cost Routes, Locational Marginal Prices, Power Systems Operation, Transportation Network, CostsAcoustic generators, Battery management systems, Charging (batteries), Electric load flow, Iterative methods, Location, Vehicle routing, Vehicle to vehicle communications, Vehicles, Charging station, Electrified vehicles, Least cost routes, Locational marginal prices, Power systems operation, Transportation network, CostsCharging StationLocational Marginal PricePower Systems OperationLeast Cost Route OptimizationElectrified Transportation NetworkElectrified VehicleArticle