Application of Metaheuristic Algorithms for Optimization of Recloser Placement in a Power Supply System with Distributed Generation

Abstract

Efficiency and reliability optimization of distribution networks is an important task in the design of power supply systems, and its complexity increases with the development of new technologies such as distributed generation. One way to improve network reliability is through the installation and optimal placement of automatic circuit reclosers. The presence of distributed generation units and reclosers significantly increases the dimensionality of the optimization problem, thus necessitating the use of alternative approaches to solve it. The goal of the research is to analyze the effectiveness of metaheuristic algorithms in the recloser quantity and allocation optimization problem in a distribution network. The scientific novelty of the study lies in simultaneously considering the failure rate of network elements and changes in operating condition in case of contingencies. The practical significance of the work is demonstrated through the effectiveness of using metaheuristic methods when selecting the optimal equipment configuration in electrical networks. To solve the optimization problem of recloser placement in a 24-bus 10 kV network, the genetic algorithm, evolutionary strategy, and adaptive particle swarm optimization were considered. Computational experiments showed that the genetic algorithm is the most efficient in this case. The results can be further used in the development of methodological guidelines for designing distribution networks of various voltage classes.