Abstract
The increasing penetration of electric vehicles (EVs) in the power system has raised concerns regarding the management of charging sessions to prevent systems from overloading. This paper proposes a distributed control method of EV clusters that enables controllers to make decisions independently, using only commonly broadcasted signals. Additionally, the method also includes a user-based power scheduling mechanism that prioritizes EVs based on their respective energy needs and time availability. A power-constrained system is considered for the case studies, where the system is only capable of charging one EV with maximum power. Simulation results demonstrate that the system effectively accommodates and schedules multiple EVs to charge simultaneously in a restricted environment without compromising user satisfaction. In instances of communication loss, the system demonstrates the capability to sustain the charging process through resource reallocation. The method is characterized by its distributed and autonomous nature, which ensures both robustness and effective operation.
Original language | English |
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Title of host publication | Proceedings of 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific (ITEC-AP 2023) |
Number of pages | 6 |
Publisher | IEEE |
Publication date | 2024 |
ISBN (Electronic) | 979-8-3503-1427-4 |
DOIs | |
Publication status | Published - 2024 |
Event | 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific - Chiang Mai, Thailand Duration: 28 Nov 2023 → 1 Dec 2023 |
Conference
Conference | 2023 IEEE Transportation Electrification Conference and Expo, Asia-Pacific |
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Country/Territory | Thailand |
City | Chiang Mai |
Period | 28/11/2023 → 01/12/2023 |
Keywords
- Electric vehicles
- Distributed charging
- Power management