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Energies 2017, 10(5), 675; doi:10.3390/en10050675

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

1
Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA
2
Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Education City, P.O. Box 5825, Doha, Qatar
3
College of Science and Technology, Hamad Bin Khalifa University, Education City, P.O. Box 5825, Doha, Qatar
4
Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Pierluigi Siano and Miadreza Shafie-khah
Received: 22 March 2017 / Revised: 25 April 2017 / Accepted: 8 May 2017 / Published: 11 May 2017
(This article belongs to the Special Issue Innovative Methods for Smart Grids Planning and Management)
View Full-Text   |   Download PDF [2678 KB, uploaded 11 May 2017]   |  

Abstract

Charging station location decisions are a critical element in mainstream adoption of electric vehicles (EVs). The consumer confidence in EVs can be boosted with the deployment of carefully-planned charging infrastructure that can fuel a fair number of trips. The charging station (CS) location problem is complex and differs considerably from the classical facility location literature, as the decision parameters are additionally linked to a relatively longer charging period, battery parameters, and available grid resources. In this study, we propose a three-layered system model of fast charging stations (FCSs). In the first layer, we solve the flow capturing location problem to identify the locations of the charging stations. In the second layer, we use a queuing model and introduce a resource allocation framework to optimally provision the limited grid resources. In the third layer, we consider the battery charging dynamics and develop a station policy to maximize the profit by setting maximum charging levels. The model is evaluated on the Arizona state highway system and North Dakota state network with a gravity data model, and on the City of Raleigh, North Carolina, using real traffic data. The results show that the proposed hierarchical model improves the system performance, as well as the quality of service (QoS), provided to the customers. The proposed model can efficiently assist city planners for CS location selection and system design. View Full-Text
Keywords: electric vehicles; charging stations; optimization; hierarchical model; resource allocation electric vehicles; charging stations; optimization; hierarchical model; resource allocation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Kong, C.; Jovanovic, R.; Bayram, I.S.; Devetsikiotis, M. A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations. Energies 2017, 10, 675.

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