A Resilient Sequential Service Restoration Framework for Unbalanced Active Distribution Networks under System Uncertainties

The resilience of an active distribution network (ADN) is continuously threatened by extreme weather, natural disaster, and cyber-physical incidents. An automatic restoration framework is thus desired to optimally integrate the emerging smart-grid technologies with the grid-edge flexibility to self-heal the ADNs. This paper proposes a framework for sequential ADN restoration by coordinating different distributed energy resources (DERs) on the grid-edge. The uncertainty of the renewable DERs is, however, a challenge. Therefore, the proposed framework is formulated as a chance-constrained optimization problem (CCOP). The chance-constraints use a parametrized response policy for the control during fluctuations and are reformulated for an efficient solution. The proposed CCOP's solution provides a sequence of control actions at each time-step that coordinates the network switches and DERs to form multiple islanded microgrids. Its effectiveness is evaluated on IEEE 123 node ADN.