RTU Upfrequency Reconstruction Based on Data Fusion

In order to solve the frequency compatibility problem between some node phasor measurement unit (PMU) data and remote terminal unit (RTU) measurement data, a RTU upfrequency reconstruction method based on SRResN et deep learning network was proposed. First, the time series data is converted into electrical data images. Secondly, we propose a data image super resolution residual network (SRResNet) model and use the data image to train the SRResN et model. Finally, the SRResNet model based on training reconstructs RTU low frequency data into high frequency data to realize data fusion. The effectiveness of the proposed method is verified by the simulation analysis of the load disturbance on the IEEE39-node system.