Hourly Reconfiguration of Large-scale Networks in the Presence of Dispersed generations Based on Changes in Load and Generation Levels with Teaching-Learning Based Optimization Algorithm

Abstract

Reconfiguration of distribution networks is a problem related to exploitation that, due to changes in the mode of switches, causes changes in configuration of distributed feeders to achieve optimal topology in order to minimize network losses. In addition, dispersed generation units play an important role in distribution networks. The present study aims to examine the reconfiguration of distribution networks by considering the effect of changes in generation level of dispersed generation units and also in load levels with Teaching-Learning Based Optimization (TLBO) Algorithm in order to reduce network power losses. Given the fact that presence of dispersed generation units has a significant effect on reducing network losses, it is necessary to extract optimal topologies in the presence of, in the absence of, and based on the changes in the generation level of these units. In this study, analysis of performance is presented on a standard 69-bus distribution network and effectiveness of the proposed method is proven. Also, some part of the real network of Ardabil with two sub-transmission posts and 5 medium-pressure feeders is analyzed as a large-scale network. The simulation results show that reduction of power losses and improvement of the voltage profile in distribution networks are achieved with the presence of dispersed generation units and also reconfiguration of the distribution network