System-Wide Early Warning Signs of Instability in Stochastically Forced Power Systems

Prior research has shown that spectral decomposition of the reduced power flow Jacobian can yield participation factors that describe the extent to which particular buses contribute to particular mode shapes in a power system. Research has also shown that both variance and autocorrelation of time series voltage data tend to increase as a power system approaches a critical transition. This paper presents evidence suggesting that a system’s participation factors predict the relative bus voltage variance values for all nodes in a system. As a result, these participation factors can be used to combine PMU data from various locations dispersed throughout a power network into a single, coherent measure of global stability. This paper first describes the method of computing the participation factors. Next, two methods for using these factors in conjunction with dynamic time series data are presented. The method is tested using a dynamic model of a 2383-bus test case. Results from these tests indicate that system wide cross-correlation and system wide weighted variance ratios can both be effective early warning signs of a looming transition.