Abstract: Error verification of the smart meter in low-voltage station areas is of great significance for maintaining the state of meters and saving operating costs. The error analysis method based on big data only relies on electricity measurement data in the advanced metering system， which is of high coverage， fast and convenient， and avoids the heavy work of on-site verification， thereby saving a lot of manpower and material resources. However， because of the ill-condition of the model， the accuracy of the measurement data cannot be guaranteed. Aiming at this problem， this paper uses data preprocessing and regularization algorithm to effectively solve the ill-posed state of verification model of the smart meter error. Finally， taking the electricity data of an actual low-voltage station area as an example， analysis result shows that the method proposed in this paper can effectively improve the calculation accuracy of operation error verification algorithm of the smart meters， and provide scientific reference for the maintenance work of on-site meter verification.

Key words:  smart meter, measurement error, ill-conditioned problem, data selection, regularization algorithm