不同适配度条件下的园区电动汽车负荷统计方法

Method for Electric Vehicle Load Statistics in Parks Under Different Adaptation Conditions

电动汽车因其绿色、低碳和节能减排的特性,有助于减少人类对化石能源的依赖,因此被视为实现“双碳”目标的重要手段。根据中国汽车工业协会的统计数据,到2022年,我国电动汽车的市场渗透率从2020年的6%增长到了26%,成为全球最大的电动汽车市场。随着大量电动汽车接入电网,电网的运行安全性和稳定性可能会受到影响。因此,对电动汽车负荷进行准确的建模显得尤为重要。本文在常规电动汽车负荷统计的基础上,进一步考虑了车-桩适配度和供-需适配度,以及两者的综合影响因素,提出了一种在不同适配度下的园区电动汽车负荷统计方法。通过模拟园区的实际情况,对所提出的方法进行了验证和对比分析,证明了该方法的准确性、合理性和有效性。

Electric vehicles(EVs),known for their green,low-carbon,and emission-reducing features,contribute to reducing human dependence on fossil fuels and are seen as a vital means to achieve China's"dual carbon"goals.According to statistics from the China Association of Automobile Manufacturers,by 2022,China's EV market penetration increased from 6%in 2020 to 26%,making it the largest EV market globally.With a large number of EVs connecting to the grid,there may be impacts on the safety and stability of the grid operation.Therefore,accurate modeling of EV loads is particularly important.This paper builds on conventional EV load statistics and further considers car-to-pile adaptation,supply-demand adaptation,and their combined influencing factors.It proposes a method for EV load statistics in parks under different adaptation conditions.The method is validated and comparatively analyzed by simulating real scenarios in parks,proving its accuracy,rationality,and effectiveness.