Research on Phase Identification Technology of Power Supply District Based on High Frequency Collection Data

At present, the HPLC (High-speed Power Line Carrier)-based power supply district identification technology is not mature and the unreliable, which is far from meeting the practical needs of power supply companies. Therefore, this paper takes an power-supplied area as an example, and establishes a feature extraction algorithm through analysis of high frequency acquisition data. Through K-Means clustering algorithm, we analyze the relationship between households in the power supply district and build up a model for analyzing the relationship between households in the power supply district; through deep data mining, we combine the longitudinal conduction characteristics of the current in the power supply district and build up a model for analyzing the phase of power supply in the power supply district. By running the above models, the power supply phase identification of smart energy meter is realized, which meets the business requirements of power supply company.