In order to effectively solve the problem of consumption loss in the electric energy information acquisition system,a method of filling missing data based on regular self- encoders is proposed. Firstly, the energy data according to the characteristics learned by the regular autoencoder is reconstructed, and the repair of the missing data is realized. Then, regularization by adding the L21- norm is realized and orthogonal constraints to the loss function, the generalization ability of the model and uses Optuna to realize the automatic optimization of hyperparameters is improved. Finally, the test results of the actual data set show that compared with other autoencoders, the regular autoencoder can accurately fill in the missing data.