M.A. Thesis:

Reconfiguration of Radial Distribution Network with Presence of Distributed Generation Sources with Objective of Loss Reduction and Reliability Improvement Using Dragonfly Algorithm

In this thesis, the problem of rearrangement of radial distribution networks with distributed generation sources with the aim of reducing power losses and improving reliability (energy not provided by subscribers) of multi-objective optimization of network based on fuzzy method using multi-objective optimization method of dragonfly (DA) case Studied. The problem variables are the optimization of the status of open and network switches, which are determined by the DA method. Distributed sources of production are considered as problem-based assumptions about location and capacity. The proposed method has been implemented on IEEE standard 33 and 69 buses. Simulations have been implemented in different scenarios of the rearrangement problem with and without regard to dispersed products, both single-objective and multi-objective. The results show that multi-objective optimization results are compared with the results of a single-objective compromise between loss criteria and reliability. The results show that by performing a reassembly, the amount of losses and unprotected energy of the network subscribers has decreased dramatically. Also, the results indicate that considering dispersed outputs optimally in the network has led to a significant reduction in losses and improved reliability. Moreover, the performance of the proposed method for reducing losses through discrete learning-learning, improved gravity search algorithms, and an improved adaptive algorithm of colonial competition has been compared in previous studies, which proved the superiority of the proposed method.

Keywords: Network distribution, reassignment, loss reduction, reliability improvement, dragonfly algorithm