Focusing on the problem of accuracy reduction due to error accumulation in multi-moment missing measurement data reparation of the power distribution system

this paper proposes a multi-moment missing measurement data repair method based on multi-step long-short term memory(MLSTM)and covariance intersection(CI)for the power distribution system.Firstly

the historical data of current

power

and other quantity measurements of power distribution system are downscaled to construct the input vector matrix and feature label matrix with different dimensions as model inputs and then trained to obtain multiple long-short term memory(LSTM)measurement data repair models with different time steps.On this basis

the CI algorithm is utilized to fuse the above LSTM repair models with different time steps to obtain a multi-moment missing measurement data repair model for the power distribution system.Example analysis shows that the proposed method can effectively suppress the error accumulation in repairing multi-moment measurement data and improve the reparation accuracy of multi-moment missing data.