Research on the autonomous identification method of the metering error of the electronic voltage transformer based on principal component-fractal theory
Electronic voltage transformer (EVT) is composed of a large number of electronic units, which is easy to fall in fault under the influence of the complex operation environment of substation. The long-term stability of its metering error is poor. The conventional detection method is to compare and calibrate with the standard transformer regularly. It is a sampling inspection method for EVT, and it is unable to evaluate the impact of EVT metering data on node power accumulation. To solve this problem, firstly, based on the three-phase symmetrical operation characteristics of power system nodes, the metering data of three-phase EVT are analyzed by principal component analysis, and SPE statistics are established in the residual subspace to realize the self-detection of EVT metering error. Secondly, the autonomous identification of EVT measurement error degradation form is realized by calculating the fractal dimension of SPE statistics during EVT operation. The research results are helpful to promote the development of EVT state detection from regular detection to on-demand detection.