Remote Estimation Method for Running Error of Smart Meters Based on Genetic Optimization LM Algorithm

Authors

  • Liang Chen, Youpeng Huang, Tao Lu, Sanlei Dang, Zhengmin Kong

Abstract

To solve the problems of high work intensity, long verification cycle and low management efficiency in the current way of smart meter verification, a remote estimation method for the running error of smart meters based on the genetic optimization LM algorithm is proposed in this paper. Firstly, the relationship between the running error of smart meters and the electricity consumption is deeply analyzed based on the measurement data of various users. Then, the genetic optimization LM algorithm is applied to estimate the running error of smart meters. Finally, the performance of the proposed algorithm is tested with the real measurement data of a power grid. The results show that an accurate estimation for the running error of smart meters can be achieved when the measurement data is sufficient.

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Published

2020-08-01

Issue

Section

Articles