摘要
目前电动汽车充电过程中电力测量准确度较低,对此研究对电动汽车充电负载特性进行分析,提出了一种结合小波变换与自适应卡尔曼滤波的电力计量模型。此外,实验还构建了电力计量评估模型对电力计量精度进行评价。实验结果显示,所提方法将电力计量的准确度提高了0.172 3%,相对准确度提高了68.12%。此外,该方法具有较强的抗谐波干扰性,在谐波变化的情况下可减少60.23%以上的变化量。由此,实验构建的电力计量模型具有较强的可操作性和应用潜力。
Aiming at the problem of low power metering accuracy in electric vehicle charging process,a power metering model combining wavelet transform and adaptive Kalman filter was proposed after analyzing the characteristics of electric vehicle charging load.In addition,an electric power measurement evaluation model is constructed to evaluate the accuracy of electric power measurement.Experimental results show that the proposed method improves the accuracy of power measurement by 0.1723%and the relative accuracy by 68.12%.In addition,the method has strong anti-harmonic interference,and can reduce the amount of harmonic change by more than 60.23%.Therefore,the electric power metering model constructed in the experiment has strong operability and application potential.
作者
王嘉明
任雪娇
赵君
WANG Jiaming;REN Xuejiao;ZHAO Jun(Shaanxi Institute of Industry and Technology,Xianyang Shaanxi 712000,China)
出处
《自动化与仪器仪表》
2024年第1期175-178,183,共5页
Automation & Instrumentation
基金
陕西工业职业技术学院2022校级科研项目(2022YKYB-005)。
关键词
充电负载
电力计量
小波变换
自适应卡尔曼滤波
评估模型
charging load
electric power measurement
wavelet transform
adaptive Kalman filtering
evaluation model
