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A Cooperative Planning Method for Multi-Type Charging Pile Station Based on Vehicle-Road-Network Coupling
XU Tingting, LONG Yi, HU Xiaorui, LI Shun, QIN Tianxi, ZHANG Qian
Electric Power Construction ›› 2025, Vol. 46 ›› Issue (7) : 95-107.
PDF(2425 KB)
PDF(2425 KB)
A Cooperative Planning Method for Multi-Type Charging Pile Station Based on Vehicle-Road-Network Coupling
[Objective] In response to the increasingly diversified charging demands arising from the rapid development of electric vehicles （EVs）， this study investigates a planning method for charging stations based on the collaboration of multiple types of charging posts.[Methods] From the perspective of EVs， transportation networks， and power grids， a siting and sizing planning method for charging stations under vehicle-road-grid coupling is first established based on the graph theory. The charging behavior characteristics of EV users are then explicitly modeled， and four types of charging posts are selected as the main facilities： slow charging post （SCP）， fast charging post （FCP）， mobile charging post （MCP）， and ultrafast charging post （UCP）. A planning model is constructed with the objective of minimizing the annualized total social cost， incorporating constraints from multiple scenario conditions and multiple charging post types. The planning problem is then reformulated as a mixed-integer second-order cone programming （MISOCP） problem via scenario transformation and the second-order cone relaxation techniques and solved using the Gurobi optimizer.[Results] The simulation results demonstrated the high efficiency and effectiveness of the proposed model. The results indicated that the planning solution considering SCP， FCP， UCP， and MCP was optimal. Notably， the integration of MCPs provided an effective emergency response during peak charging demand periods and reduced the overall planning cost by 17.82%.[Conclusions] In the proposed planning model， EV users can select among multiple types of charging posts based on specific principles. The coordinated configuration of diverse charging posts offers greater flexibility than single-type configurations， enabling the satisfaction of charging demands while reducing the annualized total social cost.
vehicle-road-network coupling / charging station planning / multi-category charging piles / multi-conditional scenario constraints / conditional scene transformation / second-order cone relaxation
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电动汽车具备交通运输和移动负荷的双重特性，其大规模的集中充电过程会对交通网和电网同时造成冲击。利用电动汽车的移动属性和车辆到电网（V2G）技术，能够在时空层面优化其充电需求，不仅可以抑制上述冲击，还可以为电网提供额外的储能容量，协助电网削峰填谷和促进新能源消纳。以电网投资建设的充电站为例，提出一种同时考虑交通网和电网因素的充电站选址定容策略，在满足电动汽车充电需求的前提下，优化电动汽车的充电需求以最大化可用储能容量。首先，建立动态交通网模型，结合Floyd算法与区域特性精确模拟电动汽车的行驶路径，预测电动汽车充电负荷的时空特性。其次，基于电动汽车的充电负荷预测结果，以最大化储能容量、充电负荷平均分布、车辆驻车时间最长3个指标初步确定电站选址，然后再根据全时段的统计结果确定充电站的最优选址与容量。最后，以某市主城区的部分实际道路为例，预测充电负荷的时空分布，以最大储能容量为目标完成充电站的选址定容，并分析了优化结果对交通网和电网的影响，结果证明了所提方法的有效性。
Electric vehicles are both transportation means and mobile loads. Their large-scale and intensive charging will impact the transportation network and the power grid at the same time. In view of EVs' mobile attribute，their charging demands can be optimized in time and space dimensions through the vehicle-to-grid（V2G） technology. The technology can not only alleviate the aforementioned impact， but also provide energy storage capacity to the power grid，so as to promote the accommodation of renewable energy resources and peak load regulation of the power grid. Taking a charging station invested by State Grid Corporation as the example， a siting and sizing strategy for the charging station that considers transportation and power networks is proposed. On the premise of satisfying the charging demands of electric vehicles， the strategy optimizes the charging demand to maximize the energy storage capacity of the station. Firstly， based on the dynamic traffic network model， the driving paths of electric vehicles are accurately simulated by Floyd algorithm and regional characteristics，to predict the spatial and temporal characteristics of electric vehicle charging loads. Secondly，based on the prediction results， the preliminary station location is determined by three goals，maximizing the energy storage capacity，smoothing the charging load， and the extending the parking time in the station. Then， the optimal location and capacity of the charging station are adjusted according to the statistical results from the whole period. Taking the roads in a main urban area as an example， the spatial and temporal characteristics of the charging load are predicted， and the optimal location and capacity of the charging station aiming at maximizing its energy storage capacity is designed. The influence of this design on the transportation network and power grid is analyzed，which proves the effectiveness of the proposed strategy. |
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