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Smart city article details
| Title | Multi-Agent Game-Theoretic Modelling Of Electric Vehicle Charging Behavior And Pricing Optimization In Dynamic Ecosystems |
|---|---|
| ID_Doc | 38094 |
| Authors | Pok P.J.; Yeo H.; Woo S. |
| Year | 2025 |
| Published | Procedia Computer Science, 257 |
| DOI | http://dx.doi.org/10.1016/j.procs.2025.03.060 |
| Abstract | This research investigates the dynamic interactions between electric vehicles (EVs) and electric vehicle charging stations (EVCSs) through a multi-agent simulation over 30 days. The simulation models EV commuting behavior, charging decisions, and dynamic pricing strategies to analyze their impact on station utilization and energy distribution. EVs operate with unique parameters, including State of Charge (SOC), SOC thresholds, and weighted preferences for cost, wait time, and distance. Each vehicle follows a logistic urgency model and a utility function to evaluate trade-offs between charging at home or office stations. Dynamic pricing at office stations adjusts costs based on demand, encouraging cost-sensitive EVs to charge during of-peak hours, while time-sensitive EVs prioritize shorter queues despite higher costs. Vehicles with critically low SOC exhibit urgency-driven behavior, prioritizing the nearest available station to prevent depletion. The simulation models 101 EVs, distributed across three home locations (50 at Home1, 50 at Home2, and 1 at Home3), capturing diverse charging behaviors and station interactions. The results demonstrate that dynamic pricing effectively mitigates congestion at high-demand stations during peak hours while improving resource utilization. These findings emphasize the importance of personalized decision-making frameworks and flexible pricing strategies in optimizing EVCS operations. The study provides insights for integrating real-time pricing and adaptive charging infrastructure in smart cities, with future work exploring real-world traffic patterns, renewable energy integration, and vehicle-to-grid (V2G) interactions to enhance system sustainability. © 2025 Elsevier B.V.. All rights reserved. |
| Author Keywords | Charging; Electric Vehicle Charging Behaviour; Electric Vehicles; Game theory; Pricing |
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