A Novel Chaotic Rao-2 Algorithm for Optimal Power Flow Solution

Abstract

This article suggests a novel chaotic Rao-2 algorithm to solve various optimal power flow (OPF) problems. The basic Rao-2 solver is a newly developed metaphor-less optimization tool. The novel optimization course of the basic Rao-2 algorithm relies on the finest and inferior solutions within the population and the indiscriminate interrelations among the nominee individuals. This tactic allows superior directions to scrutinize the exploration space. In this work, a novel chaotic Rao-2 algorithm-inspired scheme for handling the OPF problem is offered. In the offered solver, a chaotic tactic is amalgamated into the movement formula of the basic Rao-2 algorithm to enhance the variety of solutions and enhance both its global and local search capabilities. This novel scheme, which incorporates the features of the basic Rao-2 algorithm and chaotic dynamics, is then utilized to solve various OPF problems. For the OPF solution, five situations are investigated. The offered solver is examined on two standard IEEE test grids and the emulation outcomes are evaluated with the outcomes offered in the other publications and deemed competitive in terms of the features of the solution. The offered chaotic Rao-2 algorithm outperforms the basic Rao-2 algorithm regarding convergence velocity and solution competence. Furthermore, a test is performed to validate the statistical worth of the offered chaotic Rao-2-inspired solver. The offered chaotic Rao-2 algorithm presents a vigorous and simple solution for the OPF framework under various objectives.