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Optimal operation of grid-friendly megawatt-level ultra-fast EV charging stations: A review on constraints, objectives and algorithms for grid-interactive operation

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  • Li, Jing
  • Lin, Xueru
  • Huang, Hao
  • Wang, Rui
  • Zhong, Wei
  • Lin, Xiaojie
  • Wei, Wei

Abstract

The rapid adoption of electric vehicles is driving an increasing demand for advanced charging infrastructure. High-voltage, megawatt-level ultra-fast charging technologies can significantly reduce charging time, offering a promising solution to alleviate range anxiety. This emerging field benefits from advancements in charger technology, site planning techniques, and energy management strategies. In this review, we comprehensively examine the distinctions between ultra-fast charging stations and conventional charging stations, highlighting the core challenges across grid integration, user experience, economic viability, and environmental sustainability. We explore the constraints, objectives, variables, and algorithms involved in site selection and capacity planning, and then discuss the impact of integrating renewable energy and energy storage, as well as demand uncertainty on system planning. We analyze the operational strategies of charging stations under deterministic, uncertain, and intelligent control paradigms. This review also presents emerging trends in multi-energy integrated charging stations, the integration of artificial intelligence techniques such as spatiotemporal modeling, reinforcement learning, and multi-agent coordination for modeling and control, and potential development roadmaps. This review aims to provide valuable insights to support the sustainable and low-carbon development of future transportation and energy systems.

Suggested Citation

  • Li, Jing & Lin, Xueru & Huang, Hao & Wang, Rui & Zhong, Wei & Lin, Xiaojie & Wei, Wei, 2026. "Optimal operation of grid-friendly megawatt-level ultra-fast EV charging stations: A review on constraints, objectives and algorithms for grid-interactive operation," Applied Energy, Elsevier, vol. 405(C).
    • Handle: RePEc:eee:appene:v:405:y:2026:i:c:s0306261925019324
    DOI: 10.1016/j.apenergy.2025.127202
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