No abstract

The objective of the paper is to present an innovative method for event detection. The data is collected using a PMU network installed to provide wide-area monitoring and analysis of Texas' bulk power system. Grid events are detected using a combination of simple statstical algorithms, singular point detection with residual modeling, short time Fourier transform and linear regression. The performance of the proposed method is shown through the results of analysis on two types of actual events.

No abstract

No abstract

The University of Texas at Austin introduced the Independent Synchrophasor Network in order to monitor events and analyze low frequency oscillations from the electric power grid through PMU measurements taken at customer level voltage (120 V). The purpose of this paper is to present validation of the quality of these distribution level measurements for power system monitoring and analysis. Three different steps are used in the validation process. In the first step, the distribution voltage phase angle measurements are plotted with and compared to the state estimated transmission level voltage phase angle. The second step is the comparison of distribution level PMU measurements to transmission level PMU measurements during a power system transient response. The frequency, voltage magnitude, and voltage phase angle are analyzed during a unit trip event. In the final step, the modal frequency and damping estimates are used to illustrate the accuracy of distribution measurements as representative of the power system's ambient response. Because of the location of the PMUs within the network, it will also be possible to measure the effects of wind power on the rest of the grid.