Investigating state-of-the-art planning strategies for electric vehicle charging infrastructures in coupled transport and power networks: a comprehensive review

步伐 背景(考古学) 电动汽车 网格 计算机科学 电信 业务 运输工程 风险分析(工程) 功率(物理) 工程类 物理 地理 古生物学 几何学 生物 量子力学 数学 大地测量学
作者
Jinhao Li,Arlena Chew,Hao Wang
出处
期刊:Progress in energy [IOP Publishing]
卷期号:6 (4): 042004-042004 被引量:3
标识
DOI:10.1088/2516-1083/ad6be1
摘要

Abstract Electric vehicles (EVs) have emerged as a pivotal solution to reduce greenhouse gas emissions paving a pathway to net zero. As the adoption of EVs continues to grow, countries are proactively formulating systematic plans for nationwide EV charging infrastructure (EVCI) to keep pace with the accelerating shift towards EVs. This comprehensive review aims to thoroughly examine current global practices in EVCI planning and explore state-of-the-art methodologies for designing EVCI planning strategies. Despite remarkable efforts by influential players in the global EV market, such as China, the United States, and the European Union, the progress in EVCI rollout has been notably slower than anticipated in the rest of the world. This delay can be attributable to three major impediments: inadequate EVCI charging services, low utilization rates of public EVCI facilities, and the non-trivial integration of EVCI into the electric grid. These challenges are intricately linked to key stakeholders in the EVCI planning problem within the context of coupled traffic and grid networks. These stakeholders include EV drivers, transport system operators, and electric grid operators. In addition, various applicable charging technologies further complicate this planning task. This review dissects the interests of these stakeholders, clarifying their respective roles and expectations in the context of EVCI planning. This review also provides insights into level 1, 2, and 3 chargers with explorations of their applications in different geographical locations for diverse EV charging patterns. Finally, a thorough review of node-based and flow-based approaches to EV planning is presented. The modeling of placing charging stations is broadly categorized into set coverage, maximum coverage, flow-capturing, and flow-refueling location models. In conclusion, this review identifies several research gaps, including the dynamic modeling of EV charging demand and the coordination of vehicle electrification with grid decarbonization. This paper calls for further contributions to bridge these gaps and drive the advancement of EVCI planning.
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