2017/08/18 by Mang Liao, Di Shi, Liao, Mang +9
Computer Science · Engineering · #Computational Physics and Python Applications #FOS: Mathematics #High-Voltage Power Transmission Systems #Numerical Analysis (math.NA) #Power System Optimization and Stability
paper · pdf · doi:10.48550/arxiv.1708.07733
openalex publication_date 2017/08/18 · openalex created_date 2017/08/31 · openalex updated_date 2026/08/01
This paper presents a novel algorithm for recovering missing data of phasor measurement units (PMUs). Due to the low-rank property of PMU data, missing measurement recovery can be formulated as a low-rank matrix-completion problem. Based on maximum-margin matrix factorization, we propose an efficient algorithm based on alternating direction method of multipliers (ADMM) for solving the matrix completion problem. Comparing to existing approaches, the proposed ADMM based algorithm does not need to estimate the rank of the target data matrix and provides better performance in computation complexity. In addition, we consider the case of measurements missing from all PMU channels and provide a strategy of reshaping the matrix which contains the received PMU data for recovery. Numerical results using PMU measurements from IEEE 68-bus power system model illustrate the effectiveness and efficiency of the proposed approaches.