论文标题

考虑到城市交通网络状况的电动汽车充电站多目标计划的研究

Research on Multi-Objective Planning of Electric Vehicle Charging Stations Considering the Condition of Urban Traffic Network

论文作者

Wang, Limeng, Yang, Chao, Zhang, Yi, Bu, Fanjin

论文摘要

作为电动汽车的重要支持设施,充电站的合理规划和布局对电动汽车的开发具有重要意义。但是,充电站的计划和布局受到各种复杂因素的影响,例如政策经济,收费需求,用户充电舒适性和道路交通状况。如何权衡各种因素来构建一个合理的充电站位置和容量模型已成为电动汽车充电设施计划领域的主要困难。首先,本文构建了充电站的位置和容量优化模型,目的是最大化运营商的收入并最大程度地减少用户的收费额外成本。同时,引入了道路耗时的指数,以量化道路拥堵对用户充电额外费用的影响,以有效地提高用户在充电过程中的满意度。然后,提出了针对基于混乱初始化和算术交叉操作员的精英策略(NSGA-II)的非主导分类遗传算法(NSGA-II)的非主导分类遗传算法。最后,以北京的海德区为模拟对象,结果表明,与未考虑的城市交通网络的情况相比,本文提出的模型将用户的损失时间降低了11.4%,用户收费的额外费用增加了7.6%。它不仅可以确保系统的经济性,而且可以有效地提高用户的充电满意度,从而进一步验证了模型的可行性和有效性,并可以为未来的充电站计划和布局提供参考。

As an important supporting facility for electric vehicles, the reasonable planning and layout of charging stations are of great significance to the development of electric vehicles. However, the planning and layout of charging stations is affected by various complex factors such as policy economy, charging demand, user charging comfort, and road traffic conditions. How to weigh various factors to construct a reasonable model of charging station location and capacity has become a major difficulty in the field of electric vehicle charging facility planning. Firstly, this paper constructs the location and capacity optimization model of the charging station with the goal of maximizing the revenue of operators and minimizing the user's charging additional cost. At the same time, the road time-consuming index is introduced to quantify the impact of road congestion on the user's charging additional cost, so as to effectively improve the user's satisfaction during charging. Then, aiming at the charging station planning model, a non-dominated sorting genetic algorithm with an elite strategy (NSGA-II) based on chaos initialization and arithmetic crossover operator is proposed. Finally, taking the Haidian District of Beijing as the simulation object, the results show that compared with the situation of urban traffic networks not considered, the model proposed in this paper significantly reduces the cost of lost time of users by 11.4% and the total additional cost of users' charging by 7.6%. It not only ensures the economy of the system, but also effectively improves the charging satisfaction of users, which further verifies the feasibility and effectiveness of the model, and can provide a reference for the planning and layout of charging stations in the future.

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