[论文解读] Placement of EV Charging Stations --- Balancing Benefits among Multiple Entities

Chao Luo, Yih-Fang Huang+1 more|RePEc: Research Papers in Economics|Jan 7, 2018

Electric Vehicles and Infrastructure被引用 41

一句话总结

该论文在寡头市场中开发了一个多阶段框架，用于放置电动汽车充电站，使用嵌套逻辑斯蒂模型预测需求，并使用贝叶斯博弈在 QoS 与电网影响约束下推导最优布置。

ABSTRACT

This paper studies the problem of multi-stage placement of electric vehicle (EV) charging stations with incremental EV penetration rates. A nested logit model is employed to analyze the charging preference of the individual consumer (EV owner), and predict the aggregated charging demand at the charging stations. The EV charging industry is modeled as an oligopoly where the entire market is dominated by a few charging service providers (oligopolists). At the beginning of each planning stage, an optimal placement policy for each service provider is obtained through analyzing strategic interactions in a Bayesian game. To derive the optimal placement policy, we consider both the transportation network graph and the electric power network graph. A simulation software --- The EV Virtual City 1.0 --- is developed using Java to investigate the interactions among the consumers (EV owner), the transportation network graph, the electric power network graph, and the charging stations. Through a series of experiments using the geographic and demographic data from the city of San Pedro District of Los Angeles, we show that the charging station placement is highly consistent with the heatmap of the traffic flow. In addition, we observe a spatial economic phenomenon that service providers prefer clustering instead of separation in the EV charging market.

研究动机与目标

• 在 EV 充电扩张中平衡多家充电服务提供商的利润、消费者满意度与电网可靠性。
• 用嵌套逻辑斯蒂预测候选充电站的级别需求，以建模 EV 车主充电选择。
• 通过贝叶斯博弈分析提供商之间在充电站布置与定价方面的策略互动，以确定最优布置与定价。

提出的方法

• 将 EV 充电市场建模为 Level 1、Level 2、Level 3 充电服务的三方寡头。
• 使用嵌套逻辑斯蒂框架预测候选充电站的聚合需求。
• 在提供商效用函数中加入电网影响度量与电网压力惩罚。
• 将充电站布置与定价表述为贝叶斯博弈，以获得均衡策略。
• 开发 EV Virtual City 1.0 模拟器，用于研究 EV 车主、交通网络、电力系统和充电站之间的相互作用。

Figure 1: The Architecture of The EV Virtual City 1.0

实验结果

研究问题

• RQ1 在满足 QoS 约束并尽量减少电网干扰的前提下，规划的充电地点如何最大化提供商利润？
• RQ2 如何用嵌套逻辑斯蒂模型从出行与站点属性预测 EV 车主的充电需求？
• RQ3 在信息不完全的情形下，服务提供商在充电站布置与定价中的战略互动的本质是什么？
• RQ4 移动性、道路网络与电网的相互依赖性如何影响最优充电站部署？
• RQ5 在贝叶斯博弈框架下，提供商的聚集或分散是否会成为均衡特征？

主要发现

• 充电站布置与交通热力图相吻合，显示需求与交通流模式之间的一致性。
• 在贝叶斯博弈下，提供商在 EV 充电市场中倾向于聚集而非分散。
• 模型展示了利润与电网扰动之间的权衡，该权衡由效用中的可调权重 w 控制。
• 嵌套逻辑斯蒂模型使站点级别的需求估计成为可能，并为定价与布置决策提供信息。
• EV Virtual City 1.0 模拟器有助于分析用户、道路、电网与充电基础设施之间的相互作用。

Figure 2: Roads and Buildings of San Pedro District