Real-time monitoring method of mountain active distribution network based on digital twin

In order to obtain better monitoring results of the operation status of active distribution networks in mountainous areas, a real-time monitoring method for the operation status of active distribution networks in mountainous areas based on digital twins is designed and proposed in this study. This method first completes the design of the digital twin architecture of the active distribution network from the aspects of physical entities, virtual entities, and data. Then, based on the wavelet coefficient threshold denoising method, signal denoising processing is completed. Finally, combined with attention mechanism, a real-time monitoring model for the operation status of the active distribution network is constructed based on Convolutional Neural Network (CNN) and Deep Bidirectional Gated Recurrent Unit (Bi GRU). The experimental results show that based on the evaluation of the twin device model, it can be concluded that when using the method proposed in this paper, the weighted average accuracy is about 97.80%, and the monitoring speed is about 0.48s. Compared with the comparison methods, both methods have improved performance and the application effect is better.