Investigating State-of-the-Art Planning Strategies for Electric Vehicle Charging Infrastructures in Coupled Transport and Power Networks: A Comprehensive Review

TL;DR

This comprehensive review analyzes global practices and methodologies for planning electric vehicle charging infrastructure, highlighting challenges, stakeholder roles, and research gaps to guide future advancements in integrated transport and power networks.

Contribution

It provides a detailed synthesis of current EVCI planning strategies, stakeholder interests, modeling approaches, and identifies key research gaps for future exploration.

Findings

Global EVCI rollout is slower than expected due to key impediments.

Stakeholder interests and roles are clarified in EVCI planning.

Various modeling approaches for station placement are categorized and discussed.

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 electric vehicle 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. 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.