Identification Technology of Relationship Between User Meter and Transformer Based on Spatial-Temporal Correlation of Data

Abstract Due to the inability to accurately gain the changes of transformer archives, there are often problems such as confusion and loss of control of the station area archives in the electricity consumption information collection system, which seriously affects the work of line loss management and fault operation and maintenance, and it is difficult to achieve refined management. Existing manual identification methods are time-consuming and labor-intensive, while the dedicated device identification method is costly and requires a device-independent identification technology. Aiming at the above problems, a data analysis method based on temporal and spatial correlation is studied to analyze the temporal and spatial correlation of the voltage data of the power collection equipment. On this basis, use the classification method in data mining to divide collection equipment of each station area into one category, and calculate the probability that the acquisition equipment to be identified belongs to each category, to determine the belonging relationship of its station area. By simulating the user situation of the real station area, the simulation verifies the effectiveness of the intelligent station area identification method based on the spatial and temporal correlation of data, which can not only ensure the accuracy and efficiency of station area identification, but also does not depend on equipment and labor, and can meet the application requirements.