Phasor Data Compression with Principal Components Analysis in Polar Coordinates for Subsynchronous Oscillations

In the previous studies, the phasor data are processed as the amplitudes and the phases separately since existing methods are in the field of real numbers. To take advantage of the correlations between amplitudes and phases of phasors, a phasor principal components analysis (PPCA) method in polar coordinates is proposed in this paper. In PPCA, the conventional principal components analysis (PCA) is improved and extended to the field of complex numbers to process the phasors in polar coordinates. The actual PMU data measured in a subsynchronous oscillation incident are used to verify the compression performance of PPCA which is also compared with PCA. The result demonstrates that PPCA can achieve better performance by making use of the correlations between amplitudes and phases of phasors.

I. Introduction

The synchronous phasor data, also known as synchrophasors, provided by Wide-area Measurement System (WAMS) and Phasor Measurement Units (PMU) have higher reporting rate and synchronized measurement data compared with the conventional Supervisory Control And Data Acquisition (SCADA) system, Thus, synchronous measurement data, especially synchrophasors, greatly enhance the measurement and control of interconnected wide-area power grids. However, with the rapid development of WAMS, more and more PMUs are installed in power grids, which leads to a significant increase in the amount of measurement data simultaneously and then leads to tremendous pressure on data communication and storage in turn. Since synchrophasors of voltages and currents account for the vast majority of synchronous measurement data, phasor data compression techniques are highly desirable to reduce the negative impacts of massive synchronous measurement data.