A missing sequence interpolation algorithm for power grid dispatching data under multisource data fusion

Abstract

To solve the problem of missing values in dispatching data in power system, so as to improve the security and stability of power system. This article proposes a missing sequence interpolation algorithm for power grid dispatch data based on multi-source data fusion. Firstly, preprocess the multi-source power grid dispatch data, including data normalization, data serialization, etc. Then, construct an LSTM long-term and short-term memory network model, and train the model using existing data to learn the features and patterns in the original data. Next, tensor PARAFAC decomposition is implemented through first-order partial derivatives to interpolate sequence data containing missing values. Finally, the effectiveness of the evaluation algorithm is verified through experiments. The experimental results show that the algorithm proposed in this paper has high interpolation accuracy and real-time performance, and can effectively interpolate missing values in power grid dispatch data.