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<p>This study presents a stochastic framework for optimizing wind-powered electric vehicle charging stations (EVCSs) using minute-by-minute wind speed data from the National Wind Technology Center’s M2 and M4 towers. The Kernel Search Optimization (KSO) algorithm is applied to identify optimal wind turbine (WT) configurations and charging capacities, ensuring reliable power output. Among the evaluated turbines, turbine 124 consistently delivers the most stable performance, improving EV accommodation by up to 83.52% (M2) and 92.73% (M4) with three-minute data averaging compared to one-minute intervals. Extended averaging periods enhance wind power stability, increasing the EVCS’s efficiency and capacity. The analysis highlights the potential of integrating real wind data and advanced optimization algorithms to design resilient EVCS infrastructure that minimizes grid dependence and supports fast charging with reduced power fluctuations. The findings encourage the adoption of renewable energy in sustainable transport systems.</p>

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Optimizing wind-powered electric vehicle charging stations: a stochastic framework utilizing real-world wind speed data

  • 期刊论文

  • 发表日期：

    2025年9月8日

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  • Jiaqi Chen

摘要

This study presents a stochastic framework for optimizing wind-powered electric vehicle charging stations (EVCSs) using minute-by-minute wind speed data from the National Wind Technology Center’s M2 and M4 towers. The Kernel Search Optimization (KSO) algorithm is applied to identify optimal wind turbine (WT) configurations and charging capacities, ensuring reliable power output. Among the evaluated turbines, turbine 124 consistently delivers the most stable performance, improving EV accommodation by up to 83.52% (M2) and 92.73% (M4) with three-minute data averaging compared to one-minute intervals. Extended averaging periods enhance wind power stability, increasing the EVCS’s efficiency and capacity. The analysis highlights the potential of integrating real wind data and advanced optimization algorithms to design resilient EVCS infrastructure that minimizes grid dependence and supports fast charging with reduced power fluctuations. The findings encourage the adoption of renewable energy in sustainable transport systems.