Error analysis method of intelligent electricity meter based on improved BP neural network

Abstract

Many smart electricity meters work in different nonideal environments. The complexity of the working environment often leads to the difference between the measurement error of electricity meters and the ideal conditions. In this paper, BP neural network is improved to make it suitable for error analysis of intelligent electricity meter. By identifying, processing, analyzing and integrating a large number of experimental data, the error model of smart electricity meter is established. Then the internal relationship between various stress factors and the error of electricity meter is revealed from the data level. This method can accurately predict the error of electricity meters under certain conditions and lay a foundation for error correction of smart electricity meters in the future. In this paper, the realization process of the method is briefly described through simulation experiments, and the feasibility, rationality and reliability of the method are verified.