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The topological structure of distribution network system is complex, and the operation state changes frequently, so the obtained distribution network topological information has a high error. Therefore, this article proposes a clustering feature extraction method of load curve based on singular value decomposition. The load curve is given by the invariance of singular vectors to improve the generalization ability of feature processing. On the basis of considering the weight of load feature, the data integrity is ensured by singular value curve, and the clustering accuracy is high, which makes the load feature have practical physical significance. The experimental results show that this method can achieve good clustering effect, reduce the clustering time, improve the reliability of data transmission and communication coverage, and meet the communication access requirements of the power Internet of Things sensing layer.

Automatic Identification Method of HPLC Platform Topology Based on Characteristic Data Extraction