胡梦锴,陈胜,卫志农,吕思
HU Mengkai,CHEN Sheng,WEI Zhinong,LYU Si

• 1:河海大学电气与动力工程学院
• 2:南京邮电大学自动化学院

摘要(Abstract)：

随着电动汽车规模化发展，V2G（车网互动）技术在电网峰谷调节中的协同优化价值日益显著，然而现有研究在充电负荷预测精度与V2G响应行为建模方面仍存在局限。为此，提出一种基于弹性M/M/c/N模型的充电负荷预测方法，并建立融合用户画像和SOC（荷电状态）约束的V2G参与意愿模型。首先，构建计及V2G双向能量交互的配电网优化模型，通过V2G参与意愿模型求解不同用户参与V2G的概率；其次，利用弹性M/M/c/N模型表征充电需求的时空分布，结合预测结果和V2G参与情况，实现配电网协同优化；最后，通过算例分析验证方法的有效性，为充电负荷预测和V2G调度提供参考依据。
With the large-scale development of electric vehicles(EVs), vehicle-to-grid(V2G) technology has shown increasing potential in grid peak-valley regulation through collaborative optimization. However, existing research still faces limitations in charging load forecasting accuracy and V2G response behavior modeling. To address these challenges, this paper proposes a charging load forecasting method based on an elastic M/M/c/N model and establishes a V2G participation willingness model incorporating user profiling and state-of-charge( SOC) constraints. First, a distribution network optimization model is developed, accounting for V2G bidirectional energy exchange, and the probability of user participation in V2G is derived using the willingness model. Next, the elastic M/M/c/N model is employed to characterize the spatiotemporal distribution of charging demand. By integrating the forecasting results and V2G participation scenarios, collaborative optimization of the distribution network is achieved. Finally, case studies validate the effectiveness of the proposed method, providing insights for charging load forecasting and V2G scheduling.

关键词(KeyWords)： 车网互动;用户画像;弹性M/M/c/N模型;配电网优化;充电负荷预测
V2G;user profiling;elastic M/M/c/N model;distribution network optimization;charging load forecasting

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(52377091)

作者(Author): 胡梦锴,陈胜,卫志农,吕思
HU Mengkai,CHEN Sheng,WEI Zhinong,LYU Si

DOI: 10.19585/j.zjdl.202508001

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