  With increasing penetration of renewable energy and active consumers, control
and management of power distribution networks has become challenging. Renewable
energy sources can cause random voltage fluctuations as their output power
depends on weather conditions. Conventional voltage control schemes such as tap
changers and capacitor banks lack the foresight required to quickly alleviate
voltage violations. Thus, there is an urgent need for effective approaches for
predicting and mitigating voltage violations as a result of random fluctuations
in power injections. This work proposes a novel voltage monitoring approach
based on low-complexity, data-driven probabilistic voltage sensitivity
analysis. The usefulness of this work is not only in predicting voltage
violations in unbalanced distribution grids, but also in opening up the door
for optimal voltage control. Using system data and forecasts, the proposed
approach predicts the distribution of system node voltages which is then used
to to identify nodes that may violate the nominal operational limits with high
probability. The method is tested on the IEEE 37 node distribution system
considering integrated distributed solar energy sources. The method is
validated against the classic load flow based method and offers over 95\%
accuracy in predicting voltage violations.
