Research on Power Network Data Management Based on Convolutional Neural Network

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Abstract
Faced with huge business data, collecting and statistics of these data can be easily achieved through the system. However, during data analysis and result output, there is a large amount of data that cannot be intuitively accepted at a glance, resulting in disorder and inefficient work. Therefore, the grid load thermal map is scaled with cubic convolution interpolation in the paper, which requires the offset distance determination of the floating point in the horizontal and vertical directions. Moreover, based on the operating data of transformer and line, the analysis and verification of the load thermal map in power grid is realized. Besides, problem equipment can be clearly displayed on the map, which is convenient for staffs to identify and analyze.