Toward efficient smart management: A review of modeling and optimization approaches in electric vehicle-transportation network-grid integration
Year: 2024
Type: article
Abstract: The increasing scale of electric vehicles (EVs) and their stochastic charging behavior have resulted in a growing coupling between the transportation network and the grid. Consequently, effective smart management in the EV-transportation network-grid integration system has become paramount. This paper presents a comprehensive review of the current state of the art in system modeling and optimization approaches for the smart management of this coupled system. We begin by introducing the types of EVs that impact the transportation and grid systems through their charging behavior, along with an exploration of charging levels. Subsequently, we delve into a detailed discussion of the system model, encompassing EV charging load forecasting models and transportation-grid coupling models. Furthermore, optimization technologies are analyzed from the perspectives of system planning and EV charging scheduling. By thoroughly reviewing these key scientific issues, the latest theoretical techniques and application results are presented. Additionally, we address the challenges and provide future outlooks for research in modeling and optimization, aiming to offer insights and inspiration for the development and design of the EV-transportation network-grid integration system.
Authors: Mince Li, Yujie Wang, Pei Peng, Zonghai Chen
Institution: University of Science and Technology of China
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,950
Awards: G5395982554, G7625811032
OpenAlex ID: W4391718430
