基于大数据的10kV配电线路分段线损计算方法  

Calculation Method of Sectional Line Loss of 10 kV Distribution Line Based on Big Data

作　　者：张岩 周卫峰 黄军锋 王涛 晁佳 魏璐 ZHANG Yan;ZHOU Weifeng;HUANG Junfeng;WANG Tao;CHAO Jia;WEI Lu(Tongchuan Power Supply Company of State Grid Shanxi Electric Power Co.,Ltd.,Tongchuan 727031,China)

机构地区：[1]国网陕西省电力有限公司铜川供电公司,陕西铜川727031

出　　处：《微型电脑应用》2023年第8期86-90,共5页Microcomputer Applications

摘　　要：由于配电网规模增大、支路增多,10 kV配电线路计算一直存在计算准确度不足的问题。针对上述问题,提出基于大数据的10 kV配电线路分段线损计算方法。划分待计算的配电线路,将配电线路划分为不同的区段,采集各个区段上的线路长度、配电变压器总容量、月无功功率电量、月有功功率电量以及负荷电流不平衡度等5个特征参量。以大数据分析中的RBF神经网络为基础,结合遗传算法改进RBF神经网络的隐含层中心选择、宽度以及输出权值等3个结构参数,构建10 kV配电线路分段线损计算模型,计算10 kV配电线路分段线损值。结果表明:所研究方法得出的线损计算结果与样本训练输出值之间的绝对误差和相对误差百分比均较小,由此说明所研究方法的计算准确度更高。Due to the increase of the scale of distribution network and the increase of branches,the calculation accuracy of 1o kV distribution line has been insufficient.In view of the problem,a segmented line loss calculation method of 1o kV distribution line based on big data is proposed.We divide the distribution lines into different sections,and collect five characteristic parameters on each section,such as line length,total capacity of distribution transformer,monthly reactive power and electric quantity,monthly active power and electric quantity and load current imbalance.Based on RBF neural network in big data analysis,combined with genetic algorithm,the structural parameters of RBF neural network,such as hidden layer center selection,width and output weight are determined.A calculation model of sectional line loss of 1o kV distribution line is constructed,and the sectional line loss of 1o kV distribution line is calculated.The results show that the absolute error and relative error percentage between the line loss calculation results obtained by this method and the sample training output value are small,which shows that the calculation accuracy of the studied method is higher.

关 键 词：大数据 10 kV配电线路 分段线损 计算方法 

分 类 号：TP241.3[自动化与计算机技术—检测技术与自动化装置]