Agent-Based Simulation of Price-Demand Dynamics in Multi-Service Charging Station

Conference · Thu Jan 01 00:00:00 EST 2026

DOI:https://doi.org/10.1109/WSC68292.2025.11339092· OSTI ID:3019943

Wang, Xudong ^[1]; Chen, Yang ^[2]; Skipper, Brody ^[1]; Omitaomu, Femi ^[2]; Li, Xueping ^[1]

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1. University of Tennessee, Knoxville (UTK)
2. ORNL

As the adoption of electric vehicles and hydrogen fuel-cell vehicles grows, understanding how dynamic pricing strategies influence charging and refueling behaviors becomes crucial for optimizing local energy markets. This paper proposes a simulation-based analysis of a hydrogen-electricity integrated charging station that serves both types of vehicles. A multi-agent simulation framework is developed to model the interactions between vehicles and the station, incorporating price- and delay-sensitive behaviors in decision-making. The station can dynamically adjust energy prices, while vehicles optimize their charging or refueling choices based on their utility values. A series of sensitivity analyses are conducted to evaluate how electricity pricing, infrastructure capacity, and waiting behavior impact station performance. Results highlight that moderate electricity prices maximize user participation without sacrificing profit, infrastructure should be right-sized to demand to avoid over- or underutilization, and delay-toleration also affects service outcomes, which may reach the maximum service coverage at the threshold of 45 minutes.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 3019943
• Resource Type: Conference paper/presentation
• Conference Information: 2025 Winter Simulation Conference (WSC) - Seattle, Washington, United States of America - 12/7/2025-12/10/2025
• Country of Publication: United States
• Language: English