Explore the vast range of titles available.

A power distribution network is a critical infrastructure in any society and any disruption has an enormous impact on the economy and daily lives. Therefore, the objective of this study is to transform the conventional power distribution systems into resilient autonomous microgrid networks by optimally sizing and siting the distributed generators (DGs). First, N main DGs are placed to transform an existing network into an autonomous microgrid network. Second, all the possible combinations of the initially deployed DGs are made and then the outage of 1 to N  − 1 DGs is considered. Considering the outage of DGs in each combination (one at a time), the resiliency of the network is analysed. Amount of load shedding, total power loss in the network, and voltage limits are analysed in this step. Finally, based on the resiliency analysis, additional DGs are placed to enhance the resiliency of the transformed network. Heuristic methods (particle swarm optimisation and genetic algorithm) are used for both sizing and siting of DGs during the first and the second steps. The objective of the formulation is to minimise load shedding, total power loss (active and reactive), and voltage deviations in the network during DG outages.

In this paper a new methodology is used to reconfigure the topology of distribution system and placement of Distributed generators (DG) optimally. This methodology is adopted from the three optimization techniques which are Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Blue Whale Optimization (BWO). The basic principles of the GA is used the optimal switching, the foundation for the swarm searching techniques, PSO is used to find the optimal placement and latest optimization technique, BWO is used to find the size of the type-III DG. The major objective of the paper is to minimize the losses through optimal reconfiguration and optimal placement of DG in balanced radial distribution system.