Large Scale Power System Stability Detection Based on Linear Regression Department of electrical power and machines

The aim of this study is to introduce a statistical tool to detect large scale power system stability. The proposed tool in this paper is a linear regression which computed by using synchrophasor measurement for voltage, angle and frequency. Phasor measurement units (PMU) are used to measuring the data synchronizing from large scale power system networks, the measured data are analyzed using statistical tools to compute linear regression (LR), the generated regression equation is used to determine the stability of the system, if LR value is bounded between -1 and 1 the system will be stable, and if this value is less than -1 or more than 1 the system will be unstable, this methodology taken the effect of changing in voltage, angle and frequency simultaneously and it is a simple in the detected instability conditions, to validate the suggested tool. The MATLAB software is used to simulate three networks: - Kunder two-area system, IEEE 39 bus system and a part of the Egyptian grid which connected with Zafarana wind farm. The simulation results show that this method is effective and efficient to detect large scale power system stability.