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Prior research has shown that spectral decomposition of the reduced powerflow Jacobian (RPFJ) can yield participation factors that describe the extentto which particular buses contribute to particular spectral components of apower system. Research has also shown that both variance and autocorrelation oftime series voltage data tend to increase as a power system with stochasticallyfluctuating loads approaches certain critical transitions. This paper presentsevidence suggesting that a system's participation factors predict the relativebus voltage variance values for all nodes in a system. As a result, theseparticipation factors can be used to filter, weight, and combine real time PMUdata from various locations dispersed throughout a power network in order todevelop coherent measures of global voltage stability. This paper firstdescribes the method of computing the participation factors. Next, twopotential uses of the participation factors are given: (1) predicting therelative bus voltage variance magnitudes, and (2) locating generators at whichthe autocorrelation of voltage measurements clearly indicate proximity tocritical transitions. The methods are tested using both analytical andnumerical results from a dynamic model of a 2383-bus test case.

Identifying System-Wide Early Warning Signs of Instability in Stochastic Power Systems