Empowering the grid: A comprehensive review of vehicle-to-grid technology, digital twins, and intelligent energy systems

IF 2.6 Q4 ENERGY & FUELS
Global Energy Interconnection Pub Date : 2026-04-01 Epub Date: 2026-03-12 DOI:10.1016/j.gloei.2026.01.002
Nagarajan Munusamy, Indragandhi Vairavasundaram
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引用次数: 0

Abstract

The market for electric vehicles is booming. This surge poses challenges for power systems as the simultaneous charging of electric vehicles occurs without enough organization. This situation may slow our transition to clean energy. An innovative approach in Electric Vehicles (EVs) is Vehicle-to-Grid (V2G) technology, which allows EVs to interact with the power grid and become active participants in the energy system rather than passive consumers. By transferring unused battery power from vehicles to the grid, this technology can help balance electricity supply and demand, particularly during peak periods. This review examines the functionality of V2G systems, including their architecture, communication protocols, converter technology, battery performance and degradation rates, and various control methods (from traditional techniques to machine learning approaches), as well as security issues. Digital twins are highly significant. They are utilized for virtual replicas, real-time observation, estimating battery health, and assessing feasibility within Distributed Energy Resource Management Systems (DERMS). This assessment contrasts traditional methods with emerging technologies such as machine learning for predictive analytics, IoT, and blockchain, considering current offerings and anticipated market introductions by 2026. These viewpoints offer crucial guidance to stakeholders in building sustainable, intelligent energy systems.
赋予电网力量:对车辆到电网技术、数字孪生和智能能源系统的全面回顾
电动汽车市场正在蓬勃发展。这种激增给电力系统带来了挑战,因为电动汽车的同时充电没有足够的组织。这种情况可能会减缓我们向清洁能源的过渡。汽车到电网(V2G)技术是电动汽车(ev)的一种创新方法,该技术允许电动汽车与电网互动,成为能源系统的积极参与者,而不是被动的消费者。通过将未使用的电池电力从车辆转移到电网,这项技术可以帮助平衡电力供应和需求,特别是在高峰时期。本文研究了V2G系统的功能,包括其架构、通信协议、转换器技术、电池性能和退化率、各种控制方法(从传统技术到机器学习方法)以及安全问题。数字孪生非常重要。它们被用于分布式能源管理系统(DERMS)中的虚拟副本、实时观察、评估电池健康状况和评估可行性。该评估将传统方法与用于预测分析的机器学习、物联网和区块链等新兴技术进行了对比,并考虑了目前的产品和到2026年预计的市场介绍。这些观点为利益相关者建立可持续的智能能源系统提供了至关重要的指导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Global Energy Interconnection
Global Energy Interconnection Engineering-Automotive Engineering
CiteScore
5.70
自引率
0.00%
发文量
985
审稿时长
15 weeks
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