Open Access

ARTICLE

Research on Robustness of Charging Station Networks under Multiple Recommended Charging Methods for Electric Vehicles

Lei Feng¹, Miao Liu¹, Yexun Yuan¹, Chi Zhang², Peng Geng^1,*

1 School of Information and Communication Engineering, Nanjing Institute of Technology, Nanjing, 211167, China
2 School of Automation, Nanjing Institute of Technology, Nanjing, 211167, China

* Corresponding Author: Peng Geng. Email:

Journal on Internet of Things 2024, 6, 1-16. https://doi.org/10.32604/jiot.2024.053584

Received 05 May 2024; Accepted 20 June 2024; Issue published 24 July 2024

Abstract

With the rapid development of electric vehicles, the requirements for charging stations are getting higher and higher. In this study, we constructed a charging station topology network in Nanjing through the Space-L method, mapping charging stations as network nodes and constructing edges through road relationships. The experiment introduced five EV charging recommendation strategies (based on distance, number of fast charging piles, user preference, price, and overall rating) used to simulate disordered charging caused by different user preferences, and the impact of the network dynamic robustness in case of node failure is explored by simulating the load-capacity cascade failure model. In this paper, two important metrics for evaluating network robustness are selected: the relative size of the maximum connected subgraph and the network efficiency. The experimental results point out that in the price recommendation strategy, the network stability significantly decreases when the node failure ratio reaches 75.4%, while the fast charging quantity recommendation strategy significantly decreases when the node failure ratio is 62.3%. Therefore, the robustness of the charging station network is best under the price recommendation, while the network robustness is poor under the fast charging quantity recommendation.While the network robustness is poor under preference recommendation. Based on this finding, this study particularly emphasizes that in the process of improving the robustness of the charging station network, it is necessary to comprehensively consider the market demand and guide users to charge in an orderly manner by reasonably adjusting the price strategy. This strategy not only effectively prevents network stability problems that may result from disorderly charging behavior, but also enhances the ability of the charging network to resist node failure and improves the overall dynamic robustness of the network.

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Keywords

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