Congestion Balanced Green Charging Networks for Electric Vehicles in Smart Grid

Tang, Qiang, Wang, Kezhi, Luo, Yuan-sheng and Yang, Kun (2018) Congestion Balanced Green Charging Networks for Electric Vehicles in Smart Grid. In: GLOBECOM 2017 - 2017 IEEE Global Communications Conference. IEEE, pp. 1-6. ISBN 978-1-5090-5020-8

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1109/GLOCOM.2017.8254206

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.

Item Type: Book Section
Subjects: G900 Others in Mathematical and Computing Sciences
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 24 Sep 2018 10:10
Last Modified: 24 Sep 2018 10:10
URI: http://nrl.northumbria.ac.uk/id/eprint/35873

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