Congestion Balanced Green Charging Networks for Electric Vehicles in Smart Grid

Qiang Tang, Kezhi Wang, Yuan Sheng Luo, Kun Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

In this paper, a congestion balanced green charging networks is proposed for the electric vehicles (EVs) in smart grid. Firstly, a problem about the congestion probability balance among the charging stations (CSs) is analyzed and formulated, and then a two-layer optimization model is established based on the profit functions of power plant (PP), CSs and EVs. In the first layer, the optimal generation capacities as well as the charging capacities of CSs are determined, while in the second layer, the sum of each CS's profit and that of the EVs which want to charge at the CS is formulated as a profit maximization problem. The two-layer optimization model solves the congestion probability balance problem in the iterative manner, and finally the congestion balanced smart charging algorithm (CBSCA) is obtained. By comparing with other benchmarks, the results show that CBSCA is converged in an acceptable time, and the congestion probabilities among the CSs are balanced.

Original languageEnglish
Title of host publication2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PublisherIEEE
Pages1-6
Number of pages6
ISBN (Electronic)9781509050192
ISBN (Print)978-1-5090-5020-8
DOIs
Publication statusPublished - 15 Jan 2018
Event2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore
Duration: 4 Dec 20178 Dec 2017

Conference

Conference2017 IEEE Global Communications Conference, GLOBECOM 2017
Country/TerritorySingapore
CitySingapore
Period4/12/178/12/17

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