الفهرس 
INTRODUCTION AND LITERATURE REVIEWOnly 14 pages are availabe for public view
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Abstract
Natural disasters damage transmission lines and power generating systems, which have created numerous issues with supplying electricity to consumers. In such situations, power outages have an impact on important loads like hospitals, gas stations, and other critical loads. Improving the distribution system resiliency is the best solution for critical loads (CLs) recovery because it enables the system to withstand sudden changes and return to its nor-mal state. Hence, the resiliency strategy tends to find ways for restoring local or CLs or both. Dividing the main network into microgrids, each is supplied by a distributed energy resource (DER), is considered as one of these required techniques to restore the unserved loads. The natural disaster is causing the massive damage, so the methods used so far to restore the loads were unable to recover all of the loads, which represents a main issue. This thesis proposes a method for restoring the maximum number of important loads in the distribution network in order to increase system resiliency, when the main supply is out of service. The system is divided into microgrids that are supplied by DERs to perform the recovery. The methodology used for optimization in the microgrid formation is the Mixed Integer Linear Programming (MILP) method. If there are still unserved CLs or non-critical loads (Non-CLs), the system is reconfigured to obtain new topology for re-duce power losses while attempting to locate other paths to restore the unserved loads. The proposed method is to merge the MILP method with the Dragonfly algorithm (DA) for reconfiguration. Using the combined method is enabling the network to recover the unrestored CLs and Non-CLs which are not supplied in the MILP restoration method. Using MATLAB and CPLEX software, the proposed method is tested on the IEEE 123-node feeder with 5 DERs and 11 CLs and 8 Non- CLs. The simulation results show that applying the combined approach of the critical loads restoration while considering recon-figurations is better than applying the microgrids formation without reconfiguration. The combined strategy improves the resiliency metric for one of the formed microgrids from 0.65 to 1.15, a 76.923% increase in percentage. Resiliency for the overall system has increased from 2.8 to 3.29.