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With increasing penetration of renewable energy and active consumers, controland management of power distribution networks has become challenging. Renewableenergy sources can cause random voltage fluctuations as their output powerdepends on weather conditions. Conventional voltage control schemes such as tapchangers and capacitor banks lack the foresight required to quickly alleviatevoltage violations. Thus, there is an urgent need for effective approaches forpredicting and mitigating voltage violations as a result of random fluctuationsin power injections. This work proposes a novel voltage monitoring approachbased on low-complexity, data-driven probabilistic voltage sensitivityanalysis. The usefulness of this work is not only in predicting voltageviolations in unbalanced distribution grids, but also in opening up the doorfor optimal voltage control. Using system data and forecasts, the proposedapproach predicts the distribution of system node voltages which is then usedto to identify nodes that may violate the nominal operational limits with highprobability. The method is tested on the IEEE 37 node distribution systemconsidering integrated distributed solar energy sources. The method isvalidated against the classic load flow based method and offers over 95\%accuracy in predicting voltage violations.

Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks