An Adaptive Gradient Descent Method for Error Estimation of Electric Meters

  • Liang Chen , Youpeng Huang , Tao Lu , Sanlei Dang , Jie Zhang , Wen Zhao , Zhengmin Kong

Abstract

Error verification of electric meters in the power industry is usually manually
conducted through standard meters. With the continuous improvement of real-time
data collection technology, data of power systems available for analysis is becoming
more abundant. In this paper, we propose an adaptive gradient descent method for error
estimation of electric meters based on large amount of data. In order to improve the
accuracy of estimation results, we first adopt a clustering algorithm for light load data
detection and elimination. Then we provide a detailed description of the remote
estimation model for the running error of electric meters. According to the simulation
experiments, results obtained by the proposed method can well match the true value of
electric meter's running error. This method can effectively reduce the maintenance cost
of on-site calibration of electric meters, and can also provide a reference for the service
of electric meters.

Published
2020-07-25
Section
Articles