EV Charging Station Placement Considering Traffic Flow

Abstract

Abstract.The flow refueling location model is adopted to describe the traffic network considering the shortest and the second shortest paths. Three objective functions of the electric vehicle charging station placement optimal model are defined to maximize the captured traffic flow, to minimize the investment cost, and to minimize the average voltage deviation. Then, the non-dominated sorting genetic algorithm-Ⅱ is used to solve the multi-objective model. With the example of the IEEE 33-node power distribution network and the 25-node traffic network, the basic characteristics of the presented model and solving method are illustrated. INSTRUCTIONSWith the growing prominence of energy and environmental issues in recent years and the development of related technologies, more attention has been paid on electric vehicles (EVs) for their advantages in saving the energy and protecting the environment. EV charging stations, which are both public service facilities and power load facilities, need to be carefully planned before constructing. The influence of not only the traffic network, but also the power grid should be considered.Many works have been done about EV charging station placement.[1] introduces planning of EV charging and charging station construction from macro point of view, including the factors affecting the layout of EV charging stations and overall principles of charging station planning.In [2],the objective is set to minimizetotal construction cost, subject to constraints of charging station coverage and convenience for drivers to charge their EVs. Literature [3] proposes a well-organized system architecture operational scheduling method for charging and discharging of EVs.Multiobjective framework aims at minimizing total operation cost and emissions.Benders decomposition technique is used to solve the proposed model.Influence of the traffic flow is included in the planning model [4], and the super-efficiency data envelopment analysis is employed to transfer multiobjective optimization into a single-objective one.In this paper, we adopt the flow refueling location mode considering shortest and second shortest paths, to describe effect of traffic network.Three objectives of the optimal EV charging station placement model is to maximize the captured traffic flow, as well as to minimize the investment cost and average voltage deviation. EV charging station placement model Model optimal objectivesThe optimal objectives we proposed in this paper are to maximize the traffic flow that charging stations capture, to minimize the investment cost and to minimize the power bus voltage deviation.

Despliegue óptimo georreferenciado de estaciones de carga vehicular pública considerando capacidad de flujo y distancias máximas habilitantes

“…Para la difusión he introducción de VEEs es necesario implementar IECP, puesto que, se debe garantizar la operatividad del VEE en el tiempo. En [2]- [4] se puede evidenciar la importancia de la ubicación óptima de estaciones de carga (EC) como uno de los ejes fundamentales para el desarrollo en la industria del VEE, garantizando así, la adecuada operatividad y ciclo óptimo de vida de las IECP [5]. En consecuencia, se pretende establecer directrices fundamentales para el desarrollo sostenible de IECP para VEEs reduciendo al máximo, no solo costos de infraestructura, sino que además, el costo social [6].…”