车用终端综合能源站关键技术与系统优化发展动态分析

Development trends of key technologies and system optimization of vehicle terminal integrated energy stations

  • 摘要:
    目的 随着交通能源低碳化与数字化转型的加速推进,车用终端综合能源站(Vehicle Terminal-Integrated Energy Station,VT-IES)作为支撑绿色交通和能源智能化的重要枢纽,正逐渐成为学界和产业界关注的焦点。系统梳理该领域的研究脉络与技术演进特征,有助于揭示研究路径间的内在联系,提炼核心技术,并探索可持续优化方向。
    方法 运用CiteSpace,以2015—2024年间国内外VT-IES相关研究文献为数据来源,采用关键词共现、聚类与时间线演化分析方法,对该领域的研究热点、前沿主题与发展趋势进行了可视化与细致总结。
    结果 对国内外研究成果进行对比分析发现,国际研究在VT-IES领域更强调系统建模与多目标优化,形成了较为成熟的技术体系,尤其在鲁棒控制、随机优化与深度强化学习等前沿方法方面积累了丰富经验,能够较好地应对复杂不确定环境下的系统调度问题;而国内研究则更多以应用场景为驱动,重点关注充电桩布局、电动汽车充放电过程与需求响应协同调度,推动了VT-IES在城市交通与区域能源系统中的实际应用。此外,从演进趋势来看,该领域技术体系正呈现多维发展特征:①多能协同调度成为核心议题;②交通场景与能源系统深度融合;③智能化调控手段逐步渗透。
    结论 VT-IES的相关研究已在国际与国内形成了差异化发展格局。国际研究的优势在于方法论与理论体系的完备性,国内研究的特色则在于紧密贴合本土应用场景。未来应吸收国际先进经验,结合国内交通能源转型的实际需求,构建面向多能互补与智能优化的研究框架,从而推动交通能源系统的高效、清洁与创新发展。

     

    Abstract:
    Objective With the rapid advancement of low-carbon transportation energy and digital transformation, the Vehicle Terminal Integrated Energy Station (VTIES), a vital hub for green transportation and intelligent energy, is increasingly attracting attention in the academia and industry. Systematically reviewing the research landscape and technological evolution in this field will help clarify the connections between research directions, refine core technologies, and identify sustainable optimization pathways.
    Methods The research literature on VTIES from 2015 to 2024, both domestic and international, was used as the data source through CiteSpace. Key word co-occurrence, clustering, and timeline evolution analyses were applied to visualize and systematically summarize the research hotspots, cutting-edge topics, and development trends in this field.
    Results A comparative analysis of domestic and international research revealed that international studies on VTIES prioritized system modeling and multi-objective optimization, resulting in a relatively mature technical framework. In particular, rich experience had been accumulated in advanced methods such as robust control, stochastic optimization, and deep reinforcement learning, enabling improved system scheduling in complex and uncertain environments. In contrast, domestic research was more application-driven, concentrating on charging pile deployment, coordinated scheduling of electric vehicle charging-discharging processes and demand response, thereby advancing the practical implementation of VTIES in urban transportation and regional energy systems. Additionally, the technical system in this field was evolving along multiple dimensions: (1) multi-energy coordinated scheduling had become a core issue; (2) transportation scenarios and energy systems were increasingly integrated; (3) intelligent control methods were progressively adopted.
    Conclusion A differentiated development pattern has emerged in VTIES research internationally and domestically. International studies excel in methodological rigor and theoretical completeness, while domestic research is distinguished by its strong alignment with local application scenarios. Moving forward, integrating advanced international expertise with domestic transportation energy transition needs will be essential to establish a research framework focused on multi-energy complementarity and intelligent optimization, thereby advancing an efficient, clean, and innovative transportation energy system.

     

/

返回文章
返回