Bedyao, Juan C.Xie, JingWang, YuboZhang, XiLiu, Chen-Ching2019-11-132019-11-132019http://hdl.handle.net/10919/95535Resiliency of distribution systems under extreme operating conditions is critical, especially when the utility is not available. With the large-scale deployment of distributed resources, it becomes possible to restore critical loads with local non-utility resources. Distribution system operators (DSOs) need to determine the critical loads to be restored, considering limited resources and distribution facilities. Several studies on resiliency have been conducted for the restoration of distribution systems. However, the inherent asynchronous characteristic of the information availability has not been incorporated. With incomplete and asynchronous information, decisions may be made that result in underutilization of generation resources. In this paper, a new distribution system restoration approach is proposed, considering uncertain devices and associated asynchronous information. It uses a two-module architecture that efficiently optimizes restoration actions using a binary linear programming model and evaluates their feasibility with unbalanced optimal power flow. Networked microgrids are included in the model. The IEEE 123-node test feeder is used for validation. The results show that asynchronous messages may affect the restoration actions significantly and the impacts can be mitigated by the proposed decision support tool for the DSOs.application/pdfenCreative Commons Attribution 4.0 InternationalBinary linear programmingdecision making with asynchronous informationdistribution systems resiliencythree-phase unbalanced optimal power flowArticle - Refereedhttps://doi.org/10.1109/ACCESS.2019.293090772169-3536