摘要
现有低压配网线损率自动预测方法未筛选影响线损的参数,造成其预测效果较差。为解决这一问题,提出基于改进BP神经网络的低压配网线损率自动预测方法。该方法先筛选线损率影响参数,然后建立全面反映线损电气特性的指标体系,最后建立自动检测模型,实现配网线损率自动预测。实验结果表明,应用所提方法得到的预测值与实测值之间误差小于0.001%,应用效果较好。
The existing automatic prediction method of line loss rate of low-voltage distribution network does not screen the influencing line loss parameters,resulting in its poor prediction effect.To solve this problem,an automatic prediction method of low-voltage distribution line loss rate based on improved BP neural network is proposed.This method first selects the influence parameters of line loss rate,then establishes an index system reflecting the electrical characteristics of line loss,and finally establishes an automatic detection model to realize the automatic prediction of distribution line loss rate.The experimental results show that the error between the predicted value and the measured value of the proposed method is less than 0.001%,and the application effect is good.
作者
张昆
ZHANG Kun(State Grid Xuzhou Power Supply Company,Xuzhou,Jiangsu 221005,China)
出处
《自动化应用》
2025年第6期186-188,共3页
Automation Application
关键词
改进BP神经网络
低压配网线损率
自动预测方法
improved BP neural network
line loss rate of low-voltage distribution network
automatic prediction method
