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Volume 14
Issue 2
10.3390/pr14020324
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Optimal Operation of EVs, EBs and BESS Considering EBs-Charging Piles Matching Problem Using a Novel Pricing Strategy Based on ICDLBPM

by
Jincheng Liu
1,
Biyu Wang
1,
Hongyu Wang
2,
Taoyong Li
1,
Kai Wu
3,
Yimin Zhao
3 and
Jing Liu
3,*
1
China Electric Power Research Institute, Beijing 100192, China
2
Daqing Power Supply Company of State Grid Heilongjiang Electric Power Co., Ltd., Daqing 163458, China
3
School of Mechanical and Electrical Engineering, China University of Mining & Technology-Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Processes 2026, 14(2), 324; https://doi.org/10.3390/pr14020324
Submission received: 21 November 2025 / Revised: 14 January 2026 / Accepted: 14 January 2026 / Published: 16 January 2026
(This article belongs to the Section Energy Systems)
Versions Notes

Abstract

Electric vehicles (EVs), electric buses (EBs), and battery energy storage system (BESS), as both controllable power sources and load, play a great role in providing flexibility for the power grid, especially with the increased renewable energy penetration. However, there is still a lack of studies on EVs’ pricing strategy as well as the EBs-charging piles matching problem. To address these issues, a multi-objective optimal operation model is presented to achieve the lowest load fluctuation level, minimum electricity cost, and maximum discharging benefit. An improved load boundary prediction method (ICDLBPM) and a novel pricing strategy are proposed. In addition, reduction in the number of EBs charging piles would not only impact normal operation of EBs, but also even lead to load flexibility decline. Thus a handling method of the EBs-charging piles matching problem is presented. Several case studies were conducted on a regional distribution network comprising 100 EVs, 30 EBs, and 20 BESS units. The developed model and methodology demonstrate superior performance, improving load smoothness by 45.78% and reducing electricity costs by 19.73%. Furthermore, its effectiveness is also validated in a large-scale system, where it achieves additional reductions of 39.31% in load fluctuation and 62.45% in total electricity cost.
Keywords: flexible load; electric vehicles (EVs); electric buses (EBs); battery energy storage system (BESS); ancillary service; multi-objective optimization flexible load; electric vehicles (EVs); electric buses (EBs); battery energy storage system (BESS); ancillary service; multi-objective optimization

Share and Cite

MDPI and ACS Style

Liu, J.; Wang, B.; Wang, H.; Li, T.; Wu, K.; Zhao, Y.; Liu, J. Optimal Operation of EVs, EBs and BESS Considering EBs-Charging Piles Matching Problem Using a Novel Pricing Strategy Based on ICDLBPM. Processes 2026, 14, 324. https://doi.org/10.3390/pr14020324

AMA Style

Liu J, Wang B, Wang H, Li T, Wu K, Zhao Y, Liu J. Optimal Operation of EVs, EBs and BESS Considering EBs-Charging Piles Matching Problem Using a Novel Pricing Strategy Based on ICDLBPM. Processes. 2026; 14(2):324. https://doi.org/10.3390/pr14020324

Chicago/Turabian Style

Liu, Jincheng, Biyu Wang, Hongyu Wang, Taoyong Li, Kai Wu, Yimin Zhao, and Jing Liu. 2026. "Optimal Operation of EVs, EBs and BESS Considering EBs-Charging Piles Matching Problem Using a Novel Pricing Strategy Based on ICDLBPM" Processes 14, no. 2: 324. https://doi.org/10.3390/pr14020324

APA Style

Liu, J., Wang, B., Wang, H., Li, T., Wu, K., Zhao, Y., & Liu, J. (2026). Optimal Operation of EVs, EBs and BESS Considering EBs-Charging Piles Matching Problem Using a Novel Pricing Strategy Based on ICDLBPM. Processes, 14(2), 324. https://doi.org/10.3390/pr14020324

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