Open Access

ARTICLE

Two-Stage Optimal Scheduling of Distribution Network Considering Low-Carbon Demand Response and Battery Life in Electric Vehicle Battery Swap Stations

Junmin Tang^1,*, Yi Ding², Juzheng Zhu³, Hongbo Zhong³, Yanliang Long⁴, Shuo Dong⁵
1 Department of Electrical Engineering, Northeast Electric Power University, Jilin, 132012, China
2 Zhejiang Zheneng Zhongmei Zhoushan Coal Power Co., Ltd., Zhoushan, 316131, China
3 State Grid Zhangjiajie Power Supply Company, Zhangjiajie, 427000, China
4 Dongguan Power Supply Bureau of Guangdong Power Grid Corporation, Dongguan, 530221, China
5 Guiyang Power Supply Bureau, Guizhou Power Grid Co., Ltd., Guiyang, 550004, China
* Corresponding Author: Junmin Tang. Email:

Energy Engineering https://doi.org/10.32604/ee.2025.074489

Received 12 October 2025; Accepted 03 December 2025; Published online 30 December 2025

Abstract

With the rapid growth of the electric vehicle (EV) population and the development of active distribution networks (DN), the optimal scheduling of power systems that incorporate EVs has become increasingly important. electric vehicle battery swap stations (EVBSS), leveraging their substantial battery resources and suitability for centralized scheduling, offer a new approach for enhancing DN flexibility. Accordingly, this paper proposes a two-stage optimal scheduling method for DN that considers low-carbon demand response and the battery life of EVBSS. The method employs dynamic carbon emission factors as penalty components in time-of-use electricity pricing, thereby transmitting carbon signals from the generation side to the load side and encouraging low-carbon state transitions on the user side. The carbon substitution effect generated by electric vehicles through battery swapping is incorporated into the carbon quota allocation system, constructing a reward and punishment ladder-type carbon trading mechanism. Considering the impact of battery lifespan in electric vehicle battery swap stations on scheduling, the depth of discharge is converted into equivalent cycle counts by tracking the charging and discharging processes. The planned service life of the batteries is then incorporated as a hard constraint into the optimization model, making the scheduling results more practical. Case studies verify that the proposed method can effectively curb carbon emissions of DN and mitigate load fluctuations.

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Keywords

Distribution network; electric vehicle battery swap stations; battery life; low-carbon demand response

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