Comparison of metaheuristic optimization techniques including Equilibrium optimizer algorithm in power distribution network reconfiguration

Abstract

Equilibrium Optimizer (EO) is a new search algorithm inspired by the balance state of a simple and dynamic mass that is well-mixed on the region of the control volume. In this study, the EO algorithm is applied to the power distribution network reconfiguration (PDNR) for reducing active power loss, enhancing the voltage magnitude, and improving the reliability indices. The main contribution of this study is to provide a broad perspective on solving the reconfiguration problem by statistically comparing popular algorithms in the literature. The other contribution is a new algorithm has been developed for reliability index calculation, and the results are compared with the commercial software Etap. The performance of the EO algorithm has been discussed in four different distribution test systems and compared to ten meta-heuristic search algorithms studied in the literature. According to the statistical results of the analyses, the EO algorithm has provided the best performance in the solution of the reconfiguration problem in terms of several aspects such as having a lower error rate and attempting to reach the global optima successfully more than the other ten algorithms. The standard deviations of EO are calculated as 0, 3, 2.7, and 25.6 for 16-bus, 33-bus, 69-bus, and 118-bus test systems, respectively. To sum up, the proposed algorithm shows a competent, efficient and promising solution in PDNR. (C) 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University.