A Method to Evaluate the Maximum Hosting Capacity of Power Systems to Electric Vehicles

M. Kamruzzaman, Xiaohu Zhang, Michael Abdelmalak, M. Benidris, Di Shi
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引用次数: 3

Abstract

This paper proposes a smart charging/discharging-based method to evaluate the expected maximum hosting capacity (EMHC) of power systems to electric vehicles (EVs). The rapid growth in the use of EVs increases the challenges to satisfy their charging demand using existing power system resources. Therefore, a method to quantify the EMHC of power systems to EVs is required to plan for system improvements and ensure maximum utilization of resources. In this work, a method to calculate the EMHC of power systems to EVs is developed based on variable charging/discharging rates. The EMHC is calculated for charging stations at both homes and workplaces. The charging/discharging rates are varied based on daily energy demand and parking durations of EVs and network constraints. The parking duration is calculated based on probability distribution functions (PDFs) of arrival and departure times. The energy required to travel each mile and PDF of daily travel distances are used to calculate the daily energy demand of EVs. The optimization problem to maximize the hosting capacity is formulated using a linearized AC power flow model. The Monte Carlo simulation is used to calculate the EMHC. The proposed method is demonstrated on the modified IEEE 33-bus system. The results show that the daily EMHC of the modified IEEE 33-bus system varies between 20-41 cars for selected nodes.
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一种评估电力系统对电动汽车最大承载能力的方法
提出了一种基于智能充放电的电力系统对电动汽车期望最大承载能力(EMHC)评估方法。电动汽车使用量的快速增长增加了利用现有电力系统资源满足其充电需求的挑战。因此,需要一种量化电力系统对电动汽车的EMHC的方法,以规划系统改进并确保资源的最大利用。本文提出了一种基于变充放电速率的电力系统对电动汽车的EMHC计算方法。EMHC是为家庭和工作场所的充电站计算的。充电/放电速率根据电动汽车的日常能源需求和停车时间以及网络限制而变化。停车时间是根据到达和离开时间的概率分布函数(pdf)计算的。使用每英里行驶所需能量和每日行驶距离PDF来计算电动汽车的每日能源需求。利用线性化的交流潮流模型,建立了最大承载容量的优化问题。采用蒙特卡罗模拟方法对EMHC进行了计算。该方法在改进的IEEE 33总线系统上得到了验证。结果表明,改进后的IEEE 33总线系统在选定节点上的日EMHC在20-41辆之间变化。
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