Spatial–temporal QoS assessment of the EV charging network considering power outages

Frontiers in Energy Research

Energy Research

Tianyang Zhao¹  Qi Wang²  Difei Tang²  Xiaofeng Liu² 

[1] Department of Electronic and Electrical Engineering, University of Bath, Bath, United Kingdom;NARI School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, China;Jiangsu International Joint Laboratory for Integrated Energy Equipment and Integration, Nanjing Normal University, Nanjing, China;

关键词: electric vehicle;    charging network;    power outage;    Quality-of-service;    Markov decision process;    queuing theory;   

DOI  :  10.3389/fenrg.2023.1112169

 received in 2022-11-30, accepted in 2023-03-01,  发布年份 2023

来源: Frontiers

【 摘 要 】

The rapid expansion of electric vehicle charging networks (EVCNs) makes them critical infrastructures bridging power and traffic systems. The EVCN could be vulnerable during power outages at fast charging stations (FCSs), which are induced by planned maintenance or emergency load shedding. This paper proposes an approach to assess the impact of power outages on the Quality-of-service of the EVCN. The Markov decision process is utilized to model the spatial–temporal randomness of EV movement in a graph-based EVCN. The decision of charging by EV drivers is estimated by a fuzzy logic inference system. The spatial–temporal EV charging load at FCSs is formulated by a queuing-based non-linear optimization problem. Yen’s algorithm is adopted to simulate the EV redistribution phenomenon of searching adjacent healthy FCSs in response to the power outage. Quality-of-service (QoS) indices are derived to assess the potential congestions in the adjacent healthy FCSs. The case studies demonstrate that power outages may cause congestion at peripheral FCSs, exacerbating the QoS of the EVCN. Partial charging may alleviate the QoS deterioration in the event of FCS outages.

【 授权许可】

Unknown   
Copyright © 2023 Tang, Liu, Zhao and Wang.