The method of manual verification of smart meters used at the current stage usually suffers from high cost, poor efficiency, and small coverage. A new method is presented to solve the error of energy meter by iteration. Firstly, the daily electricity data is collected and sifted through to classify the data for light-load and no-load meters. Then, by applying the outlier line-loss rate treatment method, it can obtain the invariable-loss & line-loss rate & the suspected out-of-tolerance meter and their initial values. After that, the meter error, invariable-loss, and line-loss rate can be calculated by the improved meter error estimation model. Based on the computed results, the data with relatively high and low line-loss rate are removed. It is to guarantee that the line-loss rate of data is within a small range. The sifted process removes the outliers and avoids the mis-deletion of the valid data, which improves the calculation accuracy. The proposed method proves to be effective in out-of-tolerance meter search by verifying the data from two different scale distribute-electricity transformer districts (DETDs) and comparing with the traditional least-squares method (LSM). The algorithm is easily applicable to small computation burdens.