Open Access

ARTICLE

Bi-Level Optimization of Dynamic Pricing and Frequency Regulation Scheduling for Electric Heavy-Duty Truck Battery Swapping Stations Considering Heterogeneous User Response

Jianli Li¹, Xiaofeng Jin¹, Chen Li¹, Chi Zhang¹, Maosen Cao², Wentao Chang², Xin Cao², Youbo Liu³, Hang Yin^3,*, Meirui Deng³, Shurui Ding³
1 State Grid Sichuan Electric Power Company, Chengdu, China
2 Marketing Service Center (Metering Center), State Grid Sichuan Electric Power Company, Chengdu, China
3 School of Electrical Engineering, Sichuan University, Chengdu, China
* Corresponding Author: Hang Yin. Email:
(This article belongs to the Special Issue: Multi-Energy Complementarity and Source-Grid-Load-Storage Coordinated Dispatch in Integrated Energy Systems)

Energy Engineering https://doi.org/10.32604/ee.2026.089775

Received 24 July 2026; Accepted 15 September 2026; Published online 22 September 2026

Abstract

Electric heavy-duty truck battery swapping stations (EHDT-BSSs) centrally manage a large number of power batteries, enabling vehicle energy replenishment services to be provided while also offering energy storage regulation capability for participation in grid frequency regulation. However, the temporal distribution of battery swapping demand affects battery states and the available frequency regulation capacity within the station. Conventional fixed pricing cannot effectively coordinate battery swapping services with frequency regulation services. To improve the demand response (DR) capability of EHDT-BSSs and utilize the available frequency regulation capacity of EHDT-BSSs, a coordinated optimization method for dynamic pricing and frequency regulation is proposed in this paper, considering battery swapping demand response. First, the in-station batteries are classified by state of charge (SOC). Based on this classification, the upward and downward frequency regulation capacity models and the power regulation mechanism of the EHDT-BSS are established. Second, for two heterogeneous user groups, namely urban engineering trucks and logistics trucks, a response model is developed based on consumer psychology. In this model, the service cost difference ratio between charging and battery swapping is linked to user participation, with time costs taken into account. Finally, a bilevel optimization model is established. The upper level maximizes the revenue of the EHDT-BSS, while the lower level minimizes the users’ generalized cost. The case study results show that the proposed method can effectively guide users to shift their battery swapping periods and improve the distribution of battery states within the station. While satisfying battery swapping service requirements, the proposed method increases the available frequency regulation capacity of the EHDT-BSS and its overall operational revenue. In the 24 h scheduling case, compared with the fixed-pricing scenario, the integrated net revenue of the EHDT-BSS increased by 35.86%.

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Keywords

Battery swapping station; dynamic pricing; frequency regulation; demand response; bilevel optimization

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