Consumer-feeder relationship identification method for low-voltage distribution station area considering feature fusion of voltage variation and spatial distribution

Abstract

Consumer-feeder relationship is an important basis for the fault location, outage management, load adjustment and power quality management in low-voltage distribution station area (LVDSA). The current identification method of the consumer-feeder relationship based on electrical characteristics analysis is single and lack of reliability. Besides, the consumers of different feeders which locate near the bus at the low voltage side of distribution transformer have high voltage variation similarity, which makes it difficult to distinguish reliably. The spatial distribution of consumers can directly reflects the feeder trend. Therefore, a consumer-feeder relationship identification method for LVDSA considering feature fusion of voltage variation and spatial distribution is proposed in this paper. Firstly, the electrical characteristics based on voltage variation and spatial distribution characteristics based on geographical location are analyzed, and the correlation between the characteristics above and consumer-feeder relationship is explained. Secondly, a semi-supervised spectral clustering (SSC) algorithm based on the feature of voltage variation and spatial distribution is proposed to identify the consumer-feeder relationship. Finally, the proposed method is tested with the real data of LVDSAs in China. The results indicate that the feature fusion of voltage variation and spatial distribution can effectively improve the identification accuracy of consumer-feeder relationship.