Impact of Large-Scale Mobile Electric Vehicle Charging in Smart Grids: A Reliability Perspective

• Main Authors: Ping Xue, Yue Xiang, Jing Gou, Weiting Xu, Wei Sun, Zhuozhen Jiang, Shafqat Jawad, Huangjiang Zhao, Junyong Liu
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-06-01
• Series: Frontiers in Energy Research
• Subjects: electric vehicle integration; electricity system reliability; transportation network; distributed generation; electric vehicle charging service reliability
• Online Access: https://www.frontiersin.org/articles/10.3389/fenrg.2021.688034/full

The charging load of electric vehicles (EVs) is characterized by uncertainty and flexibility, which burdens the distribution network, especially when there is a high penetration of distributed generation (DG) in smart grids. Large-scale EV mobility integration not only affects smart grid operation reliability but also the reliability of EV charging services. This paper aims at estimating the comprehensive impacts caused by spatial-temporal EV charging from the perspective of both electricity system reliability and EV charging service reliability. First, a comprehensive reliability index system, including two novel indexes quantifying EV charging service reliability, is proposed. Then, considering traffic constraints and users’ charging willingness, a spatial-temporal charging load model is introduced. In the coupled transportation and grid framework, the reliability impacts from plenty of operation factors are analyzed. Moreover, the electricity system reliability and EV charging service reliability correlated with DG integration are discussed. A coupled transportation grid system is adopted to demonstrate the effectiveness and practicability of the proposed method. The numerical results analyze reliability impacts from EV penetration level, trip chain, EV battery capacity, DG installation location, and capacity. The proposed studies reveal that when the EV capacity ratio to DG capacity is 3:1, the system reliability reaches the maximum level.