文章摘要
曹 舒,张 颖,魏晓莹,韦先灿.一种基于线损迭代的超差智能电能表筛查方法[J].电力需求侧管理,2022,24(4):111-116
一种基于线损迭代的超差智能电能表筛查方法
Out-of-tolerance smart meter screening based on line loss iteration
投稿时间:2022-04-07  修订日期:2022-05-11
DOI:10. 3969 / j. issn. 1009-1831. 2022. 04 . 018
中文关键词: 电能表筛查  误差估计  线损计算  数据剔除  迭代计算
英文关键词: electric energy meter screening  error estimation  line loss calculation  data culling  iterative calculation
基金项目:国家电网有限公司科技项目(5230HQ19000F)
作者单位
曹 舒 国网福建省电力有限公司 营销服务中心福州 350001 
张 颖 国网福建省电力有限公司 营销服务中心福州 350001 
魏晓莹 国网福建省电力有限公司 营销服务中心福州 350001 
韦先灿 福州大学 电气工程与自动化学院福州 350108 
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中文摘要:
      针对当前智能电能表误差检定存在人工成本高、效率差、覆盖面小等问题,提出一种基于线损迭代的超差智能电表筛查方法。首先,收集待测配电台区一段时间内的日电量数据并进行筛查,标识出轻载、空载电能表的数据。接着利用所提的误差估计模型迭代计算固定损耗、线路损耗以及电能表误差系数。在迭代中,逐步剔除线损率较高和较低的电量数据,使得有效电量数据的线损率集中于一个区间,不仅提高误差估计精度,也可防止有效的数据被误删。最后选择误差系数超出标准值且非轻载和空载的电能表,将其标定为超差表。通过3个不同规模的配电台区电能表数据验证所提方法的有效性,实验结果均证明其能准确地检测出超差电能表。与最小二乘法相比,所提方法的检测准确率明显优于前者。
英文摘要:
      Aiming at the problems of high labor cost, poor efficiency, and small coverage in the current error verification of smart meters, an out- of- tolerance smart meter screening method based on line loss iteration is proposed. Firstly, the daily electricitydata of the distribution station is collected and screened over a period of time to identify the data of light and no-load meters. Then,the fixed loss, line loss and error coefficient of meters are calculated iteratively by using the error estimation model. Through iteration, the data with high and low line loss rate are gradually eliminated, so that the line loss rate of effective data is concentrated inan interval. This not only improves the accuracy of error estimation, but also prevents valid data from being deleted by mistake. Finally, a non- light and no- load meter whose error coefficient exceeds the standard value is labeled as an out- of- difference one.The validity of the proposed method is verified by the data of electricity meters in three different sizes of distribution stations, and the experimental results show that the proposed method can detectout-of-tolerance electricity meters accurately. Comparing with the traditional least-squares method, the detection accuracy of the proposed method is obviously better than it.
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