Mr. Pan Zhang Profile

Pan Zhang

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Proceedings Article | 25 September 2023 Paper

Repair method for abnormal loss of electrical low voltage measurement data

Yi Ding, Fei Teng, Chao Pang, Pan Zhang, Pei Chen, Xianxu Huo

Proceedings Volume 12788, 127882D (2023) https://doi.org/10.1117/12.3004409

KEYWORDS: Matrices, Data modeling, Power consumption, Interpolation, Data acquisition, Power grids, Mathematical optimization, Error analysis, Chemical elements, Evolutionary algorithms

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At present, the transmission of information from the terminals in the low-voltage station area is generally through power line carrier communication, and the working environment of the collection terminals is complicated, which is prone to missing data due to interference in the channel and abnormal collection equipment. In this paper, we propose a method to repair the abnormal missing data of distribution and low-voltage measurement data for the service middle station, which constructs the electricity consumption data matrix through the massive user data in the data middle station and records the set of missing data in the electricity consumption data matrix; constructs a pre-population model with the objective function of minimizing the kernel parametrization of the matrix, and applies the singular value threshold algorithm to pre-populate the missing data in the middle electricity consumption data matrix; clusters the pre-populated The pre-populated electricity consumption data matrix is clustered, and a low-rank repair model of electricity consumption data with joint optimization of matrix kernel parametrization and L1 parametrization is established; by solving the low-rank repair model of electricity consumption data with joint optimization of matrix kernel parametrization and L1 parametrization, the secondary repaired electricity consumption data matrix is obtained. Finally, comparing this method with the traditional interpolation restoration method, this method can obtain higher accuracy restored data by low-rank matrix restoration and effectively improve the data quality of the information collection system in the distribution business middle station.

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