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Electronics
Volume 14
Issue 19
10.3390/electronics14193940
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Article

Day-Ahead Coordinated Scheduling of Distribution Networks Considering 5G Base Stations and Electric Vehicles

by
Lin Peng
1,
Aihua Zhou
1,
Junfeng Qiao
1,*,
Qinghe Sun
1,
Zhonghao Qian
2,
Min Xu
1 and
Sen Pan
1
1
China Electric Power Research Institute, Nanjing 210003, China
2
State Grid Jiangsu Electric Power Co., Ltd., Nantong 226006, China
*
Author to whom correspondence should be addressed.
Electronics 2025, 14(19), 3940; https://doi.org/10.3390/electronics14193940 (registering DOI)
Submission received: 4 September 2025 / Revised: 1 October 2025 / Accepted: 2 October 2025 / Published: 4 October 2025
Versions Notes

Abstract

The rapid growth of 5G base stations (BSs) and electric vehicles (EVs) introduces significant challenges for distribution network operation due to high energy consumption and variable loads. This paper proposes a coordinated day-ahead scheduling framework that integrates 5G BS task migration, storage utilization, and EV charging or discharging with mobility constraints. A mixed-integer second-order cone programming (MISOCP) model is formulated to optimize network efficiency while ensuring reliable power supply and maintaining service quality. The proposed approach enables dynamic load adjustment via 5G computing task migration and coordinated operation between 5G BSs and EVs. Case studies demonstrate that the proposed method can effectively generate an optimal day-ahead scheduling strategy for the distribution network. By employing the task migration strategy, the computational workloads of heavily loaded 5G BSs are dynamically redistributed to neighboring stations, thereby alleviating computational stress and reducing their associated power consumption. These results highlight the potential of leveraging the joint flexibility of 5G infrastructures and EVs to support more efficient and reliable distribution network operation.
Keywords: 5G base stations; electric vehicles; coordinated scheduling; task migration; distribution network; day-ahead optimization; energy management 5G base stations; electric vehicles; coordinated scheduling; task migration; distribution network; day-ahead optimization; energy management

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MDPI and ACS Style

Peng, L.; Zhou, A.; Qiao, J.; Sun, Q.; Qian, Z.; Xu, M.; Pan, S. Day-Ahead Coordinated Scheduling of Distribution Networks Considering 5G Base Stations and Electric Vehicles. Electronics 2025, 14, 3940. https://doi.org/10.3390/electronics14193940

AMA Style

Peng L, Zhou A, Qiao J, Sun Q, Qian Z, Xu M, Pan S. Day-Ahead Coordinated Scheduling of Distribution Networks Considering 5G Base Stations and Electric Vehicles. Electronics. 2025; 14(19):3940. https://doi.org/10.3390/electronics14193940

Chicago/Turabian Style

Peng, Lin, Aihua Zhou, Junfeng Qiao, Qinghe Sun, Zhonghao Qian, Min Xu, and Sen Pan. 2025. "Day-Ahead Coordinated Scheduling of Distribution Networks Considering 5G Base Stations and Electric Vehicles" Electronics 14, no. 19: 3940. https://doi.org/10.3390/electronics14193940

APA Style

Peng, L., Zhou, A., Qiao, J., Sun, Q., Qian, Z., Xu, M., & Pan, S. (2025). Day-Ahead Coordinated Scheduling of Distribution Networks Considering 5G Base Stations and Electric Vehicles. Electronics, 14(19), 3940. https://doi.org/10.3390/electronics14193940

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