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Smart distribution grid with multiple renewable energy sources can experiencerandom voltage fluctuations due to variable generation, which may result involtage violations. Traditional voltage control algorithms are inadequate tohandle fast voltage variations. Therefore, new dynamic control methods arebeing developed that can significantly benefit from the knowledge of dominantvoltage influencer (DVI) nodes. DVI nodes for a particular node of interestrefer to nodes that have a relatively high impact on the voltage fluctuationsat that node. Conventional power flow-based algorithms to identify DVI nodesare computationally complex, which limits their use in real-time applications.This paper proposes a novel information theoretic voltage influencing score(VIS) that quantifies the voltage influencing capacity of nodes withDERs/active loads in a three phase unbalanced distribution system. VIS is thenemployed to rank the nodes and identify the DVI set. VIS is derivedanalytically in a computationally efficient manner and its efficacy to identifyDVI nodes is validated using the IEEE 37-node test system. It is shown throughexperiments that KL divergence and Bhattacharyya distance are effectiveindicators of DVI nodes with an identifying accuracy of more than 90%. Thecomputation burden is also reduced by an order of 5, thus providing thefoundation for efficient voltage control.

An Information Theoretic approach to identify Dominant Voltage Influencers for Unbalanced Distribution Systems