  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.
