| 引用本文: | 李春燕,赖伟彬,刘杨,易德荣,杨坤,张谦.计及实时交通流的电动汽车灵活性多速率联合优化[J].电力自动化设备,2025,45(1):200-207 |
| LI Chunyan,LAI Weibin,LIU Yang,YI Derong,YANG Kun,ZHANG Qian.Multi-rate co-optimization of electric vehicle flexibility considering real-time traffic flow[J].Electric Power Automation Equipment,2025,45(1):200-207 |
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| 摘要: |
| 由于交通网-电网之间的耦合愈加紧密，电动汽车(EV)作为灵活性资源参与调度的潜力愈加明显。针对现阶段交通网-电网耦合网络对交通流实时性考虑不足的现状，提出一种计及实时交通流的EV灵活性多速率联合优化(MRCO)策略。构建考虑交通拥堵的动态交通模型，基于速度-流量实用模型建立道路实时车流量与等效道路邻接矩阵的关系，提出考虑拥堵的等效最优路径搜索算法；建立以电网侧为主体的EV灵活性实时调度模型，针对交通网-电网的EV调度时间尺度不同的问题，提出基于MRCO的实时滚动优化算法，以适应交通路况实时多变的要求。基于某区域路网及IEEE 33节点系统对所提模型进行有效性验证，结果表明，所提策略能在满足用户出行需求的前提下，提高EV灵活性，促进可再生能源消纳。 |
| 关键词: 电动汽车 灵活性 交通拥堵 实时调度 多速率联合优化 |
| DOI：10.16081/j.epae.202409014 |
| 分类号:U469.72 |
| 基金项目:国家自然科学基金资助项目(52177073) |
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| Multi-rate co-optimization of electric vehicle flexibility considering real-time traffic flow |
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LI Chunyan, LAI Weibin, LIU Yang, YI Derong, YANG Kun, ZHANG Qian
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State Key Laboratory of Power Transmission Equipment Technology, Chongqing University, Chongqing 400044, China
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| Abstract: |
| As the coupling between the traffic network and the power grid becomes tighter, the potential of electric vehicles(EVs) to participate in scheduling as a flexible resource becomes more obvious. Aiming at the current situation that the real-time traffic flow is not considered enough in the coupling network of traffic network and power grid, a multi-rate co-optimization(MRCO) of EV flexibility considering real-time traffic flow is proposed. A dynamic traffic model considering traffic congestion is constructed, the relationship between real-time traffic flow and equivalent road adjacency matrix is established based on the speed-flow practical model, and then an equivalent optimal path search algorithm considering congestion is proposed. A real-time flexibility scheduling model of EVs is established with the power grid side as the main body. Aiming at the different time scales of EV scheduling between the traffic network and the power grid, a real-time rolling optimization algorithm based on MRCO is proposed to adapt to the real-time variable requirements of traffic conditions. Based on a regional road network and IEEE 33-bus system, the effectiveness of the proposed model is verified. The results show that the proposed strategy can improve EV flexibility and promote the consumption of renewable energy while meeting the travel needs of users. |
| Key words: electric vehicles flexibility traffic congestion real-time scheduling multi-rate co-optimization |
