Research on data missing filling of smart watt-hour meter based on variational self-encoder

Abstract

The data of smart watt-hour meter has high-dimensional characteristics, and it is difficult to represent, so it is impossible to ensure high-precision filling of missing data. Therefore, the research on missing data filling of smart watt-hour meter based on variational self-encoder is proposed. Firstly, a filling model based on variational self-encoder is constructed to denoise the measurement data of smart watt-hour meter, then the denoised smart watt-hour meter data is input into the model, and the data missing filling result of smart watt-hour meter is output. Finally, the data missing filling of smart watt-hour meter is realized according to the result. The experimental results show that, after filling, the proposed method is coincident with the original data, and the final filling operation efficiency can reach more than 90%.