Enhancing Electric Vehicle Charging Schedules: A Surrogate-Assisted Approach
Pages 183 - 186
Abstract
This paper addresses the pressing issue of efficiently scheduling electric vehicle (EV) charging at public stations to alleviate strain on the electrical grid. EV drivers provide their charging needs beforehand, and the scheduler optimizes charger allocation and power distribution to minimize discrepancies in state-of-charge levels at departure. To tackle the complexity of this NP-hard problem, this study proposes a solution framework combining a genetic algorithm with linear programming. Surrogate models are also investigated to expedite problem-solving. Simulation results demonstrate the effectiveness of these approaches in managing the complexities of EV charging scheduling.
References
[1]
Syed Abdullah-Al-Nahid, Tafsir Ahmed Khan, Md Abu Taseen, Taskin Jamal, and Tareq Aziz. 2022. A novel consumer-friendly electric vehicle charging scheme with vehicle to grid provision supported by genetic algorithm based optimization. Journal of Energy Storage 50 (2022), 104655.
[2]
Jerome H Friedman. 2001. Greedy function approximation: a gradient boosting machine. Annals of statistics (2001), 1189--1232.
[3]
Guang-Bin Huang, Qin-Yu Zhu, and Chee-Kheong Siew. 2006. Extreme learning machine: theory and applications. Neurocomputing 70, 1--3 (2006), 489--501.
[4]
Lars Kotthoff. 2016. Algorithm selection for combinatorial search problems: A survey. Data mining and constraint programming: Foundations of a cross-disciplinary approach (2016), 149--190.
[5]
Jiayan Liu, Gang Lin, Sunhua Huang, Yang Zhou, Yong Li, and Christian Rehtanz. 2020. Optimal EV charging scheduling by considering the limited number of chargers. IEEE Transactions on Transportation Electrification 7, 3 (2020), 1112--1122.
[6]
Lizi Luo, Wei Gu, Suyang Zhou, He Huang, Song Gao, Jun Han, Zhi Wu, and Xiaobo Dou. 2018. Optimal planning of electric vehicle charging stations comprising multi-types of charging facilities. Applied energy 226 (2018), 1087--1099.
[7]
Muhammad Sulaman, Mahmoud Golabi, Mokhtar Essaid, Julien Lepagnot, Mathieu Brévilliers, and Lhassane Idoumghar. 2024. Surrogate-assisted metaheuristics for the facility location problem with distributed demands on network edges. Computers & Industrial Engineering 188 (2024), 109931.
[8]
Muhammad Sulaman, Mahmoud Golabi, Mokhtar Essaid, Julien Lepagnot, Mathieu Brévilliers, and Lhassane Idoumghar. 2024. Surrogate-assisted metaheuristics for the facility location problem with distributed demands on network edges. Computers & Industrial Engineering (2024), 109931.
[9]
Weitiao Wu, Yue Lin, Ronghui Liu, Yaohui Li, Yi Zhang, and Changxi Ma. 2020. Online EV charge scheduling based on time-of-use pricing and peak load minimization: Properties and efficient algorithms. IEEE Transactions on Intelligent Transportation Systems 23, 1 (2020), 572--586.
[10]
Imene Zaidi, Ammar Oulamara, Lhassane Idoumghar, and Michel Basset. 2023. Electric Vehicle Charging Scheduling Problem: Heuristics and Metaheuristic Approaches. SN Computer Science 4, 3 (2023), 283.
[11]
Zongzhao Zhou, Yew Soon Ong, My Hanh Nguyen, and Dudy Lim. 2005. A study on polynomial regression and Gaussian process global surrogate model in hierarchical surrogate-assisted evolutionary algorithm. In 2005 IEEE congress on evolutionary computation, Vol. 3. IEEE, 2832--2839.
Index Terms
- Enhancing Electric Vehicle Charging Schedules: A Surrogate-Assisted Approach
Recommendations
Vehicle-to-grid communication system for electric vehicle charging
Anniversary Volume: Celebrating 20 Years of ExcellenceRecently, the attention on electric vehicle EV/plug-in hybrid electric vehicle PHEV has been growing. The EV/PHEV will be one of important electric loads from the viewpoint of smart grid in near future. It is anticipated that the EV/PHEV will affect the ...
Interurban Electric Vehicle Charging Stations Through Genetic Algorithms
Hybrid Artificial Intelligent SystemsAbstractElectric vehicles are one of the strongest ways for society to stop contributing to greenhouse gas emissions. However, for their use to become regular, a good infrastructure of charging stations is needed, allowing a similar convenience to that ...
Electric Vehicle Charging Scheduling Problem: Heuristics and Metaheuristic Approaches
AbstractAdopting electric vehicles is essential to reducing greenhouse gas emissions and achieving climate goals. However, the existing electrical grid can easily be overloaded with more electric vehicles on the road. For this reason, many researchers are ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
July 2024
2187 pages
Copyright © 2024 Copyright held by the owner/author(s).
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 01 August 2024
Check for updates
Author Tags
Qualifiers
- Poster
Conference
GECCO '24 Companion
Sponsor:
GECCO '24 Companion: Genetic and Evolutionary Computation Conference Companion
July 14 - 18, 2024
VIC, Melbourne, Australia
Acceptance Rates
Overall Acceptance Rate 1,669 of 4,410 submissions, 38%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 26Total Downloads
- Downloads (Last 12 months)26
- Downloads (Last 6 weeks)4
Reflects downloads up to 21 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in