1589. A Realistic MAP/PH/c Queuing Model for Electric Vehicle Charging Stations: Theoretical Development and Real-World Case Study
Invited abstract in session WB-54: Stochastic Models and Optimization I, stream Stochastic modelling.
Wednesday, 10:30-12:00Room: Liberty 1.08
Authors (first author is the speaker)
| 1. | Eman Almehdawe
|
| University of Regina |
Abstract
we develop a realistic multi-server queuing model for electric vehicle (EV) charging stations, where multiple identical connectors operate independently. The arrival of EVs follows a Markovian arrival process (MAP), while charging durations follow a phase-type (PH) distribution. This approach addresses the limitations of simpler Poisson-based models, which often do not capture the variability and dynamics of EV arrival patterns and charging durations. We validate the model through numerical examples and a case study using real-world charging session data from Saskatchewan, Canada. By adopting this advanced stochastic framework, we provide practical insights for designing and managing EV charging stations to improve efficiency and user satisfaction. This work contributes to developing a more effective EV infrastructure that can meet the growing adoption of EVs while ensuring a seamless user experience.
Keywords
- Queuing Systems
- Service Operations
- Stochastic Models
Status: accepted
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