Real-Time Optimal Charging Strategy for Battery Swapping Stations Under Time-of-Use Pricing

IF 6.7 2区计算机科学 Q1 ENGINEERING, MULTIDISCIPLINARY

IEEE Transactions on Network Science and Engineering Pub Date : 2025-02-18 DOI:10.1109/TNSE.2025.3543449

Huanyu Yan;Chenxi Sun;Huanxin Liao;Xiaoying Tang

{"title":"Real-Time Optimal Charging Strategy for Battery Swapping Stations Under Time-of-Use Pricing","authors":"Huanyu Yan;Chenxi Sun;Huanxin Liao;Xiaoying Tang","doi":"10.1109/TNSE.2025.3543449","DOIUrl":null,"url":null,"abstract":"Battery Swapping Stations (BSSs), the emerging infrastructure for electric vehicles (EVs), are swiftly proliferating facilities bridging energy and transportation networks. As the power grid's demand-side-management approach evolves, the optimal charging strategy for competitive BSSs needs further investigation. This paper proposes a real-time optimal charging strategy for each non-cooperative BSS operating under a unified power grid that implements Time-of-use (TOU) pricing. We construct a non-cooperative game model to encapsulate the competition among BSSs under the EV reservation mechanism. To resolve the game, we prove the existence of a unique Nash Equilibrium under any number of players and swapping prices, and design an algorithm to solve the equilibrium. Additionally, we suggest strategies for EVs without reservations. Specifically, we demonstrate the conditions under which the BSS profit diminishes when serving directly drive-in EVs. We also establish that the potential cost arising from no-show reserved EVs is limited by a constant. Simulations validate that our proposed battery charging strategy significantly enhances the profits of a 12-station BSS system. Moreover, the real-time optimal charging strategy also accomplishes peak-shaving over multiple time periods.","PeriodicalId":54229,"journal":{"name":"IEEE Transactions on Network Science and Engineering","volume":"12 3","pages":"2043-2056"},"PeriodicalIF":6.7000,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Network Science and Engineering","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10892049/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}

引用次数: 0

Abstract

Battery Swapping Stations (BSSs), the emerging infrastructure for electric vehicles (EVs), are swiftly proliferating facilities bridging energy and transportation networks. As the power grid's demand-side-management approach evolves, the optimal charging strategy for competitive BSSs needs further investigation. This paper proposes a real-time optimal charging strategy for each non-cooperative BSS operating under a unified power grid that implements Time-of-use (TOU) pricing. We construct a non-cooperative game model to encapsulate the competition among BSSs under the EV reservation mechanism. To resolve the game, we prove the existence of a unique Nash Equilibrium under any number of players and swapping prices, and design an algorithm to solve the equilibrium. Additionally, we suggest strategies for EVs without reservations. Specifically, we demonstrate the conditions under which the BSS profit diminishes when serving directly drive-in EVs. We also establish that the potential cost arising from no-show reserved EVs is limited by a constant. Simulations validate that our proposed battery charging strategy significantly enhances the profits of a 12-station BSS system. Moreover, the real-time optimal charging strategy also accomplishes peak-shaving over multiple time periods.

查看原文本刊更多论文

基于分时电价的换电站实时最优充电策略

电池交换站（bss）是新兴的电动汽车基础设施，正在迅速扩大连接能源和交通网络的设施。随着电网需求侧管理方法的发展，竞争性bss的最优充电策略需要进一步研究。本文提出了在统一电网下运行的各非合作BSS的实时最优充电策略，该策略采用分时电价（Time-of-use， TOU）定价。我们构建了一个非合作博弈模型来封装EV保留机制下的bss之间的竞争。为了解决这个博弈，我们证明了在任意数量的参与者和交换价格下存在一个唯一的纳什均衡，并设计了一个求解该均衡的算法。此外，我们还提出了无保留地电动汽车策略。具体来说，我们证明了当直接服务于电动汽车时，BSS利润减少的条件。我们还建立了由未显示预留的电动汽车引起的潜在成本受到常数的限制。仿真验证了我们提出的电池充电策略显著提高了12站BSS系统的利润。此外，实时最优充电策略还实现了多个时间段的调峰。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

IEEE Transactions on Network Science and Engineering Engineering-Control and Systems Engineering

CiteScore

12.60

自引率

9.10%

发文量

393

期刊介绍： The proposed journal, called the IEEE Transactions on Network Science and Engineering (TNSE), is committed to timely publishing of peer-reviewed technical articles that deal with the theory and applications of network science and the interconnections among the elements in a system that form a network. In particular, the IEEE Transactions on Network Science and Engineering publishes articles on understanding, prediction, and control of structures and behaviors of networks at the fundamental level. The types of networks covered include physical or engineered networks, information networks, biological networks, semantic networks, economic networks, social networks, and ecological networks. Aimed at discovering common principles that govern network structures, network functionalities and behaviors of networks, the journal seeks articles on understanding, prediction, and control of structures and behaviors of networks. Another trans-disciplinary focus of the IEEE Transactions on Network Science and Engineering is the interactions between and co-evolution of different genres of networks.