摘要
目前由于智能电表的测量标准单位的不同,在数据测量上存在难以统计的情况。为了提高分时段用电量测量的准确性,使用BP神经网络对用单一单位电量和区域单位电量进行分时段测量,以此得出更高准确值,从而指导分时段供电功率。BP神经网络算法对用电量进行测量,可以看出单一用户在10:00~20:00用电量较高,在(16kW.h, 21kW.h)波动;区域用电量根据地区差异呈现出不同的用电量波动。因此,BP神经网络可以测量单一和区域分时段用电量并提高测量准确性,从而指导供电的合理性。
At present, due to the different measurement standard units of smart meters, it is difficult to make statistics in data measurement.In order to improve the accuracy of power consumption measurement in different time periods, BP neural network is used to measure the single unit power consumption and regional unit power consumption in different time periods, so as to get a higher accurate value and guide the power supply in different time periods.BP neural network algorithm is used to measure the power consumption.It can be seen that the power consumption of a single user is high from 10:00 to 20:00,and fluctuates at(16 kw.H,21 kw.H);the regional power consumption shows different fluctuations according to the regional differences.Therefore, BP neural network can measure single and regional power consumption in different periods and improve the accuracy of measurement, so as to guide the rationality of power supply.
作者
刘怡琳
刘怡
LIU Yilin;LIU Yi(Xuchang Power Supply Company,State Grid Henan Electric Power Company,Zhengzhou 450000,China;Maintenance Company,State Grid Henan Electric Power Company,Zhengzhou 450000,China)
出处
《自动化与仪器仪表》
2021年第5期61-64,68,共5页
Automation & Instrumentation
基金
国家自然科学基金(No.51507145)。
关键词
BP神经网络
电表
动态测量
数据
自动化分类
BP neural network
ammeter
dynamic measurement
data
automatic classification
作者简介
刘怡琳(1995-),女,河南平顶山人,硕士,主要研究方向为电力营销计量。
