Method based on t-sne reduction and K-means clustering to identify the household-transformer relationship in low-voltage distribution network

Aiming at the current problems of low-voltage distribution network (LVDN) at present due to the untimely updating of the account in the early stage, which leads to the unclear relationship between customers and affects the operation, management and fault research and judgment of distribution network, this paper presents an automatic identification method of distribution network topology on the basis of clustering of historical voltage data and its fluctuation characteristics. Firstly, the three-phase voltage data and user terminal voltage of the adjacent substation in the research object station area are collected through the distribution intelligent terminal, and the multi-dimensional fluctuation characteristic parameters of the voltage at both ends are defined and calculated, and the global fluctuation characteristics and local fluctuation characteristics of the voltage series are mainly analyzed; Then, the dimension of the target data is then reduced using the t ⁃ sne algorithm; Finally, based on the characteristics of voltage fluctuation after dimensionality reduction, the correct relationship between substation transformers and users was obtained by using an improved K ⁃ means clustering algorithm for clustering substation transformers and users. The result of the example shows that the subordinate relationship between the user and the transformer in the topology of the target station area can be identified through the detailed analysis of the voltage measurement data at both ends of the target station area.