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

Cuiyu Kong, Raka Jovanovic, Islam Safak Bayram and Michael Devetsikiotis
Additional contact information
Cuiyu Kong: Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27695, USA
Raka Jovanovic: Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Education City, P.O. Box 5825, Doha, Qatar
Islam Safak Bayram: Qatar Environment and Energy Research Institute, Hamad Bin Khalifa University, Education City, P.O. Box 5825, Doha, Qatar
Michael Devetsikiotis: Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA

Energies, 2017, vol. 10, issue 5, 1-20

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.

Keywords: electric vehicles; charging stations; optimization; hierarchical model; resource allocation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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