Affiliations: [a] State Grid Baoding Power Supply Company, Baoding, Hebei, China
| [b] School of Foreign Languages, Henan University, Kaifeng, Henan, China
Correspondence:
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Corresponding authors. Liang Guo, State Grid Baoding Power Supply Company, Baoding, Hebei, China. E-mail: gl_9521@163.com and Wenhui Li, School of Foreign Languages, Henan University, Kaifeng, Henan, 475001, China. E-mail: lwh_241@163.com.
Abstract: To solve the problem of inaccurate user phase identification, the paper proposes a new algorithm based on improved cloud model and adaptive segmented voltage algorithm. Firstly, the new algorithm uses improved cloud model to calculate the digital features of station area and users’ voltage sequences quickly. Secondly, the paper uses the adaptive segmentation voltage algorithm to divide the full voltage sequences into three parts automatically to add local features into phase identification. Finally, the paper calculates cosine similarity between each segmented voltage cloud model to identify users’ voltage phase. The analysis based on station data and field verification shows that the new algorithm has not only improved the calculation efficiency by 41% compared with traditional user phase identification algorithm, but also increased the difference in identification results between different phases by 1000 times. In the final result, the accuracy of the new algorithm is 95%. The new algorithm has more obvious differentiation and higher accuracy. The analysis results based on the actual engineering data also prove the feasibility and effectiveness of the new user phase identification algorithm.
