Artificial Intelligence Hybrid Algorithm for System Reconfiguration to Reduce Power Losses in the Distribution System

Abstract

A number of algorithms that aim to reduce power system losses and improve voltage profiles by system reconfiguration have already been proposed, but they are still subject to several limitations. Hence, new algorithms can be developed, or existing ones can be improved so that this important issue can be addressed more appropriately and effectively. To understand smart grids, distribution network, which is a key component of Distribution System Reconfiguration (DSR), is presented in this study as an accurate and effective solution. To determine the intended optimum reconfiguration and effectively rearrange the connectivity of the distribution networks, it uses a variety of heuristic optimization techniques. In this paper, a hybrid artificial intelligent method, made up of the genetic algorithm (GA) and particle swarm optimization (PSO), is developed. Using the standard IEEE 33-bus distribution network on MATLAB, the proposed method's validity and efficacy have been evaluated. The findings demonstrate the proposed approach's robustness and demonstrate that it minimizes the average power loss of independent runs while requiring less processing time. The comparison of results shows that HGAPSO has a better solution than GA and PSO.