基于电力大数据和天牛群算法的直流电能数字化计量方法  

Digital Metering of DC EnergyBased on Power Big Data and Beetle Swarm Algorithm

作　　者：张岚 卫一民 赵鹏鸽 刘鹏 彭振飞 ZHANG Lan;WEI Yimin;ZHAO Pengge;LIU Peng;PENG Zhenfei(State Grid Henan Marketing Service Centre,Zhengzhou 450000,China;Henan Jiuyu Tenglong Information Engineering Co.,Ltd.,Zhengzhou 450000,China)

机构地区：[1]国网河南省电力公司营销服务中心,河南郑州450000 [2]河南九域腾龙信息工程有限公司,河南郑州450000

出　　处：《微型电脑应用》2024年第8期138-141,共4页Microcomputer Applications

摘　　要：为了提高直流电能计量的准确性,基于电力大数据和天牛群算法提出一种直流电能数字化计量方法。利用多周期滤波算法对电力大数据进行处理,提取电压和电流的基波分量。通过谐波计量分析技术识别和分析电力信号中的谐波分量。设计直流电能计量流程,结合自适应梳状滤波器和天牛群算法,实现对电能的精确计量和修正。测试结果表明,采用提出的方法对直流电能进行计量处理时,电能计量相对误差值多数在10 W以下,最低误差值为6.6 W,能够提高直流电能计量的准确性,具备较为理想的计量效果。In order to improve the accuracy of DC power metering,a digital DC energy measurement method based on power big data and beetle swarm algorithm is proposed.This paper uses multi period filtering algorithm to process power big data and extract fundamental components of voltage and current,and identify and analyze harmonic components in power signals through harmonic metrology analysis technology.This paper designs a DC power metering process that combines adaptive comb filters and beetle swarm algorithm to achieve accurate measurement and correction of electrical energy.The test results show that when using the proposed method for measuring and processing direct current electricity,the relative error value of electricity metering is mostly below 10 W,with a minimum error value of 6.6 W.This can improve the accuracy of direct current electricity metering and has a relatively ideal metering effect.

关 键 词：电力大数据 天牛群算法 电能计量 计量误差 

分 类 号：TM933.4[电气工程—电力电子与电力传动]