Phase-user Relationship Identification Method in Low-voltage Distribution Area Based on FSC-DTW Distance and Clustering Analysis

Aiming at the problem of identifying the topological relationship between the distribution transformer phase sequence and the users in the low-voltage distribution area under the scenario of incomplete data, this paper proposes a method based on fuzzy shape context-dynamic time warping (FSC-DTW) distance and clustering analysis. Firstly, the FSC histogram at each point of each voltage sequence is calculated as the shape descriptor at this point. Secondly, the shape matching cost matrix between each voltage sequence is constructed and used instead of the distance matrix in the classical DTW algorithm to measure the similarity between each voltage sequence. Then, Searching for the alignment path with the minimum cost of regularization. Finally, based on the FCM algorithm, the phase sequence of the distribution transformer and the users are clustered to obtain the phase of the area users. In this paper, the fuzzy membership function is constructed to improve the expression ability of the classical shape context shape descriptor, and the ill-conditioned alignment problem of the classical DTW algorithm is solved by the FSC descriptor. This method can realize the identification of the relationship between the distribution transformer phase sequence and the users in the case of incomplete data or unequal time intervals in the voltage sequence. The simulation results verify the effectiveness and correctness of the proposed method.