A Hybrid Incentive Program for Managing Electric Vehicle Charging Flexibility
Abstract
With the mass roll-out of electric vehicles (EVs) and rapid progress in battery technology, utilizing EV charging flexibility has become a promising solution for supporting economic and secured power system operations. This work proposes a novel hybrid incentive program, which encourages EV owners to sell their charging flexibility to a charging station (CS) and achieve a win-win situation for both EV owners and the CS. Unlike existing approaches, the proposed hybrid incentive program is simultaneously featured with simplicity, consistency, and controllability. To determine the incentive payment parameters, an optimal incentive price selection model is developed. In the solution methodology, we first linearize the original problem, then develop an adaptive ADMM algorithm to efficiently solve the formulated problem. Case studies confirm the superiority of the proposed hybrid incentive program over the state-of-the-arts, achieving 22.51% of EV owners’ cost reduction, 31.18% of energy market bill reduction, and 64.13% of potential charging flexibility utilization.
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The EUDW incentive model enhances the accuracy of EUDW decisions by accounting for the contextual variability of decision factors.
“Compared with existing incentive frameworks that typically employ single-factor approaches [23], [27], this approach enhances the accuracy of EUDW decisions by accounting for the contextual variability of decision factors.”
From Flexibility Region Quantification and Optimal Scheduling of Fast Charging Stations Considering EV User Discharge Willingness (2025) · cites this paper as [23]
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Zhang, X., Zhao, Q., Guo, L., & Wang, S. (2025) · IEEE Transactions on Transportation Electrification · doi:10.1109/tte.2025.3594615 · Cited by 1 · see citing works
- Authors
- Wang, H., Jia, Y., Shi, M., Xie, P., Lai, C. S., & Li, K.
- Affiliations
- University of Leeds (GB)
- Southern University of Science and Technology (CN)
- Brunel University of London (GB)
- Venue
- IEEE Transactions on Smart Grid
- Published
- 2023-01
- Volume
- 14
- Issue
- 1
- Pages
- 476-488
- ISSN
- 1949-3053 (ISSN-L)
- 1949-3061
- OpenAlex
- W4291805252
- Cited by
- 59
- References
- 0
- Citations by year
- 2026: 10 · 2025: 25 · 2024: 12 · 2023: 11 · 2022: 1
- FWCI
- 3.36
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Transactions on Smart Grid (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- Brunel University Research Archive (BURA) (Brunel University London) (submittedVersion)
- Funders
- National Natural Science Foundation of China (72071100)
- Shenzhen Basic Research Program (JCYJ20210324104410030)
- Young Elite Scientist Sponsorship Program by CSEE (CSEE-YESS-2020027)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Vehicles and Infrastructure
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Smart Grid Energy Management
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Power System Optimization
- Keywords
- charging stations, linearization, power system operation
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