Toward efficient smart management: A review of modeling and optimization approaches in electric vehicle-transportation network-grid integration

Mince Li, Yujie Wang, Pei Peng, Zonghai Chen
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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.

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实现高效智能管理:电动汽车-交通网络-电网集成中的建模和优化方法综述
电动汽车(EV)规模的不断扩大及其随机充电行为导致交通网络与电网之间的耦合日益增强。因此,对电动汽车-交通网络-电网集成系统进行有效的智能管理变得至关重要。本文全面回顾了当前系统建模和优化方法的最新进展,以实现对这一耦合系统的智能管理。我们首先介绍了通过充电行为影响交通和电网系统的电动汽车类型,并探讨了充电水平。随后,我们详细讨论了系统模型,包括电动汽车充电负荷预测模型和交通-电网耦合模型。此外,我们还从系统规划和电动汽车充电调度的角度分析了优化技术。通过全面回顾这些关键科学问题,介绍了最新的理论技术和应用成果。此外,我们还探讨了建模和优化研究面临的挑战,并对未来进行了展望,旨在为电动汽车-交通网络-电网集成系统的开发和设计提供见解和灵感。
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