葛乐,陆颖,王明深,邹凌岳,涂善卿
GE Le,LU Ying,WANG Mingshen,ZOU Lingyue,TU Shanqing

• 1:南京工程学院电力工程学院
• 2:国网江苏省电力有限公司电力科学研究院

摘要(Abstract)：

随着我国电动汽车应用场景的多元化，不同类型电动汽车的出行行为异质性及补电需求差异性增强，导致充换电负荷预测难度加大。鉴于此，提出一种计及用户决策更新与有限理性的多类型电动汽车充换电负荷预测方法。构建车辆出行链-能耗模型-选站策略融合机制，对电动私家车、出租车、公务车的出行特性与补电偏好差异化建模，实现异质车辆群体的充换电负荷预测。仿真结果表明：该负荷预测模型能够计算充换电负荷时空分布，且所提用户决策更新策略可有效节省用户补电成本，并减少用户行驶成本。
The diversification of electric vehicle(EV) applications in China has intensified the heterogeneity in travel behaviors and refueling demands across different EV types, significantly complicating charging/swapping load forecasting. To address this challenge, this paper proposes a novel load forecasting method for multi-type EVs that incorporates user decision updating and bounded rationality. A novel integrated framework is developed, combining travel chains, energy consumption models, and station selection strategies. Differential modeling of travel patterns and refueling preferences is implemented for private EVs, electric taxis, and electric official vehicles. Simulation results demonstrate that the model accurately capture the spatiotemporal distributions of charging/swapping loads. Furthermore, the decision-updating mechanism effectively reduces users' refueling costs and travel costs.

关键词(KeyWords)： 电动汽车;负荷预测;充换电;用户决策
EV;load forecasting;charging and battery swapping;user decision

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金(52477101)

作者(Author): 葛乐,陆颖,王明深,邹凌岳,涂善卿
GE Le,LU Ying,WANG Mingshen,ZOU Lingyue,TU Shanqing

DOI: 10.19585/j.zjdl.202510013

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