Abstract
With the rapid growth of electric vehicles (EVs), the shortage and uneven distribution of charging infrastructure have become major issues. This paper proposes a method for public charging infrastructure planning based on a hybrid EV charging model. It estimates EV flow between locations with a gravity model, applies a congestion game model to determine demand distribution across charging stations, and then optimizes charger deployment at each location. The method is demonstrated through a case study in the Sydney metropolitan area.
| Original language | English |
|---|---|
| Title of host publication | PRICAI 2024: Trends in Artificial Intelligence, 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, Kyoto, Japan, November 18-24, 2024, Proceedings, Part V |
| Editors | Rafik Hadfi, Patricia Anthony, Alok Sharma, Takayuki Ito, Quan Bai |
| Place of Publication | Singapore |
| Publisher | Springer |
| Pages | 111-117 |
| Number of pages | 7 |
| ISBN (Electronic) | 9789819601288 |
| ISBN (Print) | 9789819601271 |
| DOIs | |
| Publication status | Published - 2025 |
Publication series
| Name | Lecture Notes in Computer Science |
|---|---|
| Publisher | Springer |
| Volume | 15285 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 7 Affordable and Clean Energy -
SDG 9 Industry, Innovation, and Infrastructure
Keywords
- congestion game
- electric vehicles
- gravity model
Fingerprint
Dive into the research topics of 'A hybrid model for public electric vehicle charging infrastructure planning'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver