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This paper formulates a chance-constrained optimal distribution networkpartitioning (ODNP) problem addressing uncertainties in load and renewableenergy generation; and presents a solution methodology using sample averageapproximation (SAA). The objective is to identify potential sub-networks in theexisting distribution grid; that are likely to survive as self-adequate islandsif supply from the main grid is lost. {This constitutes a planning problem.}Practical constraints like ensuring network radiality and availability ofgrid-forming generators are considered. Quality of the obtained solution isevaluated by comparison with: a) an upper bound on the probability that theidentified islands are supply-deficient, and b) a lower bound on the optimalvalue of the true problem. Performance of the ODNP formulation is illustratedon a modified IEEE 37-bus feeder. It is shown that the network flexibility iswell utilized; the partitioning changes with risk budget; and that the SAAmethod is able to yield good quality solutions with modest computation cost.

Chance-Constrained Optimal Distribution Network Partitioning to Enhance Grid Resilience