A hierarchical optimization model for a network of electric vehicle charging stations

Cuiyu Kong, Raka Jovanovic, Islam Safak Bayram, Michael Devetsikiotis

Research output: Contribution to journalArticle

13 Citations (Scopus)

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.

Original languageEnglish
Article number675
JournalEnergies
Volume10
Issue number5
DOIs
Publication statusPublished - 1 Jan 2017

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Keywords

  • Charging stations
  • Electric vehicles
  • Hierarchical model
  • Optimization
  • Resource allocation

ASJC Scopus subject areas

  • Computer Science(all)
  • Renewable Energy, Sustainability and the Environment
  • Energy Engineering and Power Technology
  • Energy (miscellaneous)

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