Research on Electric Vehicle Fleet Behavior based on Data- and Model-Driven Simulation Method

Expand
  • (1. State Grid Fujian Electric Power Co., Ltd. Economic and Technological Research Institute, Fuzhou, 350012, China;2. School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China)

Online published: 2024-10-25

Abstract

To address issues like lack of actual electric vehicle (EV) charging load data, significant regional differences, and complex simulation methods, we propose an EV behavior simulation method consisting of trip chains, energy consumption chains, and charging chains. Initially, to tackle the scarcity of charging data, we derive a vehicle trip chain construction method using a data-driven approach, leveraging similarities between EV and conventional vehicle trips to understand EV travel patterns. Subsequently, we summarize energy consumption models, creating energy consumption chains based on trip chains. Lastly, considering factors like charging anxiety, queueing, and charging time, we develop the EV charging chain. Simulations of common charging strategies demonstrate their impact on user charging costs and the power grid.

Cite this article

LIU Lin1 , YANG Siyu1 , HUANG Xianan1 , CHEN Yantao1 , XU Huashuai2 , WANG Lingling2 , JIANG Chuanwen2 . Research on Electric Vehicle Fleet Behavior based on Data- and Model-Driven Simulation Method[J]. Journal of Shanghai Jiaotong University, 0 : 0 . DOI: 10.16183/j.cnki.jsjtu.2024.082

Outlines

/