Chairs / 主席:
Xiaolong Jin, Associate Professor, Tianjin University
靳小龙，天津大学副教授

Xiaohong Dong, Associate Professor, Hebei University of Technology
董晓红，河北工业大学副教授

Yunfei Mu, Professor, Tianjin University
穆云飞，天津大学教授

In recent years, China has witnessed a rapid surge in the adoption of electric vehicles (EVs), with projections indicating the fleet will exceed 100 million by 2030, accompanied by a peak charging load of approximately 100 GW. This massive scale of EV deployment poses significant challenges to several stakeholders, including the power grid, automobile manufacturers, governments, and EV owners. Effective Vehicle-to-Grid (V2G) is a key approach to addressing these challenges. However, due to multiple constraints such as the differing interests of multiple stakeholders, cross-industry data barriers, and the external market environment, large-scale V2G faces severe challenges. This special session focuses on key technologies and equipment for cross-domain data-driven V2G. The purpose of this special session is to explore and discuss cutting-edge technologies and equipment essential for enabling large-scale (V2G) interactions, particularly in the context of cross-domain, data-driven solutions.Topics of interest include: 1. AI-Driven Modeling Techniques for V2G using cross-domain big data; 2. Optimal planning techniques for charging and swapping resources with uncertainties; 3. Operational and market strategies for large-scale V2G; 4. Advanced bidirectional charging and discharging technologies and equipment for high-power charging/swapping stations with wide operational ranges.

近年来，中国电动汽车（EV）的普及迅速增长，预计到2030年，电动汽车保有量将超过1亿辆，峰值充电负荷约100GW。如此大规模的电动汽车部署给电网、汽车制造商、政府和电动汽车车主等多个利益相关方带来了重大挑战。有效的车网互动（V2G）是应对这些挑战的关键方法。然而，由于多方利益诉求不同、跨行业数据壁垒以及外部市场环境等多种制约因素，大规模V2G面临严峻挑战。本专题重点关注跨域数据驱动的V2G关键技术与装备，旨在探讨和讨论实现大规模V2G互动所必需的前沿技术和装备，特别是在跨域数据驱动解决方案的背景下。重点研究方向包括：1. 基于人工智能的跨域大数据车网互动（V2G）建模技术；2. 考虑不确定性的充换电资源优化规划方法；3. 大规模车网互动的运营与市场策略；4. 宽运行范围大功率充换电站先进双向充放电技术与装备。

• AI-Driven Modeling Techniques for V2G using cross-domain big data / 基于跨域大数据的V2G人工智能建模技术
• Optimal planning techniques for charging and swapping resources with uncertainties / 不确定性条件下充换电资源优化规划技术
• Operational and market strategies for large-scale V2G / 大规模V2G运行与市场策略
• Advanced bidirectional charging and discharging technologies and equipment for high-power charging/swapping stations with wide operational ranges / 宽运行范围大功率充换电站先进双向充放电技术与装备
• AI Technology for V2G Integrating Energy, Transportation, and Meteorological Information / 融合能源、交通与气象信息的V2G人工智能技术
• Coordinated Vehicle-Charger-Road-Grid Resource Allocation under Spatiotemporal High Uncertainty Conditions / 时空高不确定性条件下车-桩-路-网资源协同配置
• Precise Guidance for Large-Scale EV Charging/Swapping / 大规模电动汽车充换电精准引导