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提出了一种基于ARMA时间序列算法的电动汽车充电站运行状态预测模型及充电功率需求计算方法。首先定义了充电桩的五种状态来描述电动汽车充电站的运行规律,并利用ARMA算法理论基础建立充电站运行状态预测模型。其次以实际充电站运行数据为例,基于ARMA时间序列模型进行参数估计和建模,对预测过程作出了详细说明,并对预测模型进行误差分析和模型评价,以此验证模型的可靠性。最后,利用正在充电状态时间序列及充电桩的额定充电功率计算得到了充电站预测的充电功率曲线,与实际充电功率曲线进行了对比分析,证明了模型的有效性和适应性。
An ARMA time series algorithm based on the EVMA charging station operating status prediction model and charging power demand calculation method. First of all, five states of charging pile are defined to describe the operation rules of EV charging station, and the operating status prediction model of charging station is established based on ARMA algorithm theory. Secondly, taking the actual charging station operation data as an example, the ARMA time series model is used to estimate and model the parameters. The forecasting process is described in detail. The error analysis and model evaluation of the forecasting model are carried out to verify the reliability of the model. Finally, the predicted charging power curve of the charging station is calculated by using the time series of charging status and the rated charging power of the charging pile, and compared with the actual charging power curve, the validity and adaptability of the model are proved.