Low Rank Matrix Completion for Recovering Missing Load Data in Power System

The missing of measurement is a phenomenon often happens in power system. In this paper, a method based on low rank matrix completion theory is proposed to recover the missing load data. The low rank matrix is constructed based on the linear approximation principle. Then the low rank matrix completion algorithm is derived based on the linearized Bregman method. Based on the real data of power grid, the method is tested and the error is calculated. The comparison of the error of recovered load data is made between low rank matrix completion algorithm and spline interpolation and extrapolation. The result shows that the algorithm based on low rank matrix completion is more effective and has stronger adaptability.