Abstract: With the continued deployment of synchronized
Phasor Measurement Units (PMUs), high sample rate data are
rapidly increasing the real time observability of power systems.
Prior research has shown that the statistics of these data can
provide useful information regarding network stability, but it is
not yet known how this statistical information can be actionably
used to improve power system stability. To address this issue, this
paper presents a method that gauges and improves the voltage
stability of a system using the statistics present in PMU data
streams. Leveraging an analytical solver to determine a range of
“critical” bus voltage variances, the presented methods monitor
raw statistical data in an observable load pocket to determine
when control actions are needed to mitigate the risk of voltage
collapse. A simple reactive power controller is then implemented,
which acts dynamically to maintain an acceptable voltage stability
margin within the system. Time domain simulations on 3-bus
and 39-bus test cases demonstrate that the resulting statistical
controller can out-perform more conventional feedback control
systems by maintaining voltage stability margins while loads
simultaneously increase and fluctuate.
Abstract: Prior research has shown that spectral decomposition of the reduced power flow Jacobian (RPFJ) can yield participation factors that describe the extent to which particular buses contribute to particular spectral components of a power system. Research has also shown that both variance and autocorrelation of time series voltage data tend to increase as a power system with stochastically fluctuating loads approaches certain critical transitions. 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 filter, weight, and combine real time PMU data from various locations dispersed throughout a power network in order to develop coherent measures of global voltage stability. This paper first describes the method of computing the participation factors. Next, two potential uses of the participation factors are given: (1) predicting the relative bus voltage variance magnitudes, and (2) locating generators at which the autocorrelation of voltage measurements clearly indicate proximity to critical transitions. The methods are tested using both analytical and numerical results from a dynamic model of a 2383-bus test case.