Comparing Business Models for Optimizing Turnover in Electric Vehicle Charging Stations
Type
conference paper
Date Issued
2025-06-16
Author(s)
Abstract
This paper addresses the central question on how to optimize turnover of electric vehicle charging stations (EVCS) during peak demand. We evaluate and compare different business models (BMs), including smart pricing, release & reward, and auction-based mechanisms, that introduce dynamic pricing and negotiation strategies to reduce congestion and increase station utilization. Queuing at charging stations is a growing problem due to the increasing popularity of EVs, thus, new approaches are needed to minimize waiting times and congestion at charging stations without expanding the infrastructure. To assess the impact of different BMs, we use a data-driven agent-based simulation, modeling realistic customer behavior and charging dynamics. Our results show that negotiationbased approaches leveraging game theory and Nash equilibrium can significantly enhance station efficiency. The auction-based model increased turnover by nearly 6% compared to the baseline, demonstrating its potential as a practical solution for peakdemand management. These findings suggest that tailored BMs can play a crucial role in optimizing EVCS operations, striking a balance between provider revenue and customer incentives.
Keywords
Multiagent-based simulation
Game theory
EV charging
Turnover optimization
Business models
Publisher
IEEE
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Name
IEEE-SmartComp25-BModels-EV.pdf
Size
1.01 MB
Format
Adobe PDF
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