Research on Power Grid Natural Disaster Data Processing and Analysis Methods Based on Deep Learning

In today’s society, the power grid, as one of the key infrastructure, plays a vital role in modern life and economic operation. However, with the continuous intensification of climate change, frequent natural disasters have become a major challenge for the stable operation of power grids. To address these challenges more effectively, this study is titled “Exploring Deep Learning Techniques for Processing and Analyzing Power Grid Natural Disaster Data.” The objective is to investigate the application of deep learning technology in handling and analyzing the extensive data generated by power grids during natural disaster events. This research aims to enhance the disaster response capabilities and operational stability of power grids.This study first focuses on the large amount of data generated by power grids when natural disasters occur. However, traditional data processing methods are often difficult to effectively mine valuable information from these data. Hence, this study introduces a data processing approach that relies on deep learning techniques. By building a neural network model with strong adaptability and high automatic learning ability, potential patterns and rules can be extracted from complex power grid data to realize intelligent data analysis and mining. This paper first introduces the theory of data deletion, including deletion mechanism and deletion mode; Secondly, the relevant methods of missing data filling are introduced, including GAN model and GAIN model. Then, the theory of intertemporal sequence correlation is introduced. Lastly, the missing data is imputed using the model proposed in this paper, and the obtained results are analyzed to validate the effectiveness of the model.In short, this study aims to use deep learning technology to mine useful information about power load and equipment status from power grid natural disaster data, so as to improve the power grid’s natural disaster response ability and operation stability. By developing intelligent data processing and analysis methods, this study anticipates offering novel ideas and solutions for power grid response during natural disasters. Consequently, it aims to enhance the overall social reliability and resilience of power supply, thereby promoting its improvement.