Scheduling and performance analysis under a stochastic model for electric vehicle charging stations
- Authors
- Kim, Jerim; Son, Sung-Yong; Lee, Jung-Min; Ha, 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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Collections - 사회과학대학 > 응용통계학과 > 1. Journal Articles
- IT융합대학 > 전기공학과 > 1. Journal Articles
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