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Cited 24 time in webofscience Cited 27 time in scopus
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Scheduling and performance analysis under a stochastic model for electric vehicle charging stations

Authors
Kim, JerimSon, Sung-YongLee, Jung-MinHa, Hyung-Tae
Issue Date
Jan-2017
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
Electric vehicles; Battery charging station; Stochastic modeling; Charge scheduling; Markov-modulated Poisson process; Performance measures
Citation
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE, v.66, pp.278 - 289
Journal Title
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
Volume
66
Start Page
278
End Page
289
URI
https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/6553
DOI
10.1016/j.omega.2015.11.010
ISSN
0305-0483
Abstract
Wide-spread infrastructures for electric vehicle battery charging stations are essential in order to significantly increase the implementation of electric vehicles (EVs) in the foreseeable future. Therefore, we propose a stochastic model and charge scheduling methods for an EV battery charging system. We utilize a flexible Poisson process with a hidden Markov chain for modeling the complexity of the time-varying behavior of the EV stream into the system. Relevant random factors and constraints, which include parking times, requested amounts of electricity, the number of parking lots (charging facilities), and maximal demand level, are considered within the proposed stochastic model. Performance measures for the proposed charge scheduling are analytically derived by obtaining stationary distributions of states concerning the number of inbound EVs, waiting time distributions, and the joint distributions of parking time and electricity charged during random parking times. (C) 2016 Elsevier Ltd. All rights reserved.
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사회과학대학 > 응용통계학과 > 1. Journal Articles
IT융합대학 > 전기공학과 > 1. Journal Articles

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Son, Sung Yong
Graduate School (Dept. of Next Generation Smart Energy System Convergence)
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