| 引用本文: | 孙亮,朱童生,党翠,王奕霏,石鸿福,张儒峰.考虑用户选择偏好行为的电动汽车充电站扩容与新建规划[J].电力自动化设备,2026,46(2):128-136. |
| SUN Liang,ZHU Tongsheng,DANG Cui,WANG Yifei,SHI Hongfu,ZHANG Rufeng.Capacity expansion and new construction planning of electric vehicle charging stations considering users’ preference behaviors[J].Electric Power Automation Equipment,2026,46(2):128-136. |
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| 摘要: |
| 针对现有充电站难以满足当前不断增长的电动汽车(EV)充电需求的问题，提出一种考虑用户充电选择偏好行为的EV充电站扩容与新建规划方法。利用蒙特卡罗算法模拟规划区域内的充电需求，并基于距离分配至最近的现有充电站，获取充电需求时空分布的同时估计供需差额，确定后续扩容与新建的容量；提出基于改进Huff模型的用户充电选择偏好模型，以描述用户产生充电需求后对充电站的选择偏好行为；建立双层规划模型，上层规划综合考虑多方成本，下层规划考虑用户的相对偏好。以29节点交通网与IEEE 33节点配电网的耦合网络为算例，采用遗传算法和CPLEX求解器对双层模型进行耦合求解。算例分析结果表明所提方法具有可行性与有效性。 |
| 关键词: 电动汽车 充电站 扩容 新建规划 改进Huff模型 选择偏好 双层规划 |
| DOI：10.16081/j.epae.202507011 |
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| 基金项目:国家自然科学基金资助项目(52377080) |
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| Capacity expansion and new construction planning of electric vehicle charging stations considering users’ preference behaviors |
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SUN Liang1, ZHU Tongsheng1, DANG Cui2, WANG Yifei1, SHI Hongfu1, ZHANG Rufeng1
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1.School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China;2.State Grid Nanchang Power Supply Company, Nanchang 330096, China
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| Abstract: |
| In response to the problem that the existing charging stations are difficult to meet the current continuously increasing charging demand of electric vehicles(EVs),a capacity expansion and new construction planning method of EV charging stations considering users’ charging preference behaviors is proposed. The charging demand within the planned area is simulated by using Monte Carlo algorithm and is then allocated to the nearest existing charging station based on distance, so as to capture the spatiotemporal distribution of charging demand and estimate the supply-demand gap, and determine the capacity expansion and new construction of charging stations. A user’s charging preference model based on the modified Huff model is proposed to characterize users’ station-selection preference behaviors after the generation of charging demands. A bi-level planning model is established, where the upper-level planning comprehensively considers multi-stakeholder costs, and the lower-level planning considers users’ relative preference. Taking the coupled network of a 29-node transportation network and an IEEE 33-node distribution network as a case study, the genetic algorithm and CPLEX solver are adopted to solve the bi-level model in a coupled manner. The results demonstrate the feasibility and effectiveness of the proposed method. |
| Key words: electric vehicles charging station capacity expansion new construction planning modified Huff model selection preference bi-level planning |
