Optimal reactive power dispatch problem solved by symbiotic organism search algorithm

TLDR: The proposed symbiotic organism search algorithm is realized for IEEE-14 bus and 30-bus systems and is compared with Evolutionary programming, Differential evolutionary algorithm, dynamic particle swarm optimization, self-adaptive real coded genetic algorithm and modified Gaussian bare bones teaching learning based optimization.

Abstract: This paper introduces a newly developed symbiotic organism search algorithm for deal with ORPD problem. The reactive power optimization problem is essential for suitable operation and regulation in power system network. It helps operators to control the voltage limits, to curtail the real power loss in transmission lines, enhances the strength of the electrical power system to withstand and counteract voltage collapse during load variations in an electrical power system. The symbiotic organism search algorithm is one of the assuring, latest developments in the tract of Meta heuristic algorithms. The texture — animated philosophy of symbiotic organism search algorithm resembles the interactive nature among organisms in feature. Organisms in the real cosmos infrequently live in isolation due to their dependence on other organisms for livelihood and longevity. This ORPD problem is formulated by generator output voltages (continuous variable), regulating transformers and switchable VAR devices (discrete variables). The proposed symbiotic organism search algorithm is realized for IEEE-14 bus and 30-bus systems. The improved result values are compared with Evolutionary programming, Differential evolutionary algorithm, dynamic particle swarm optimization, self-adaptive real coded genetic algorithm and modified Gaussian bare bones teaching learning based optimization.