考虑公平充电的基于Stackelberg博弈的电动汽车中途充电策略

IF 5.6 2区 工程技术 Q2 ENERGY & FUELS Sustainable Energy Grids & Networks Pub Date : 2025-03-01 Epub Date: 2024-12-13 DOI:10.1016/j.segan.2024.101590
Xiaocheng Wang , ZeLong Li , Qiaoni Han , Pengjiao Sun
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引用次数: 0

摘要

随着电动汽车产业的快速发展,电动汽车与充电站之间的充电游戏被广泛研究。针对电动汽车仍然存在的里程问题,本文研究了中途充电场景下电动汽车与CSs之间的充电交互问题。首先,在有导航系统参与的信息交换过程中,每辆电动汽车在考虑距离和路况等因素后,在CSs定价策略的影响下进行选择,使支出最小化。在获得电动汽车的充电策略后,CSs将调整充电策略,使收益最大化,同时获得最小的负载系数。然后,我们使用一个多领导者和多追随者的Stackelberg博弈模型来模拟CSs与ev之间的交互。此外,考虑到中途充电的特殊性,我们增加了公平充电来限制电动汽车的充电容量。最后,针对Stackelberg均衡问题,采用逆向归纳法,在给定CSs (leader)充电价格的情况下,推导出电动汽车(follower)的充电容量策略,并根据电动汽车的最优定价策略设计出CSs的最优定价策略。此外,还提出了一种分布式算法来迭代地获得博弈均衡。仿真结果表明,采用该策略可使电动汽车的平均充电成本降低25%,且CSs的负载均衡性较高,表明了该策略在降低成本和平衡负载方面的有效性。
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A midway charging strategy for electric vehicles based on Stackelberg game considering fair charging
With the rapid development of the electric vehicle industry, there are games about charging between electric vehicles (EVs) and charging stations (CSs) that have been extensively studied. Due to the mileage problem that EVs still have, this paper addresses the charging interactions between EVs and CSs in a midway charging scenario. Firstly, in the information exchange process with the involvement of navigation system, each EV chooses under the influence of the pricing strategy of CSs to minimize the expenditure after considering factors including distance and road conditions. After getting EVs’ strategy, CSs will adjust the charging strategy to maximize the revenue while obtaining the minimum load factor. Then, we use a Stackelberg game with multi-leader and multi-follower to model the interaction between CSs and EVs. Moreover, considering the particularity of midway charging, we add fair charging to limit the charging capacity of EVs. Lastly, to address the Stackelberg equilibrium problem, the backward induction method is adopted, that is, we derive the charging capacity strategies of EVs (i.e., followers) given the charging price of CSs (i.e., leaders), and then design the optimal pricing strategy of CSs based on the EVs’ optimal strategy. Besides, a distributed algorithm is also proposed to obtain the game equilibrium iteratively. Furthermore, the simulation results show that the average charging cost of EVs is reduced by 25% using the proposed strategy, and the load balance of CSs is relatively high, which shows the effectiveness of this strategy in reducing costs and balancing loads.
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来源期刊
Sustainable Energy Grids & Networks
Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology
CiteScore
7.90
自引率
13.00%
发文量
206
审稿时长
49 days
期刊介绍: Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.
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