Vol 1 Issue 1 April 2014-June 2014
K. Lenin, Dr. B.Ravindranath Reddy, Dr. M.Surya Kalavathi
Abstract: This paper presents hybrid particle swarm algorithm for solving the multi-objective reactive power dispatch problem. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. Evolutionary algorithm and Swarm Intelligence algorithm (EA, SI), a part of Bio inspired optimization algorithm, have been widely used to solve numerous optimization problem in various science and engineering domains. In this paper, a framework of hybrid particle swarm optimization algorithm, called Hybrid quantum genetic particle swarm optimization (HQGPSO), is proposed by reasonably combining the Q-bit evolutionary search of quantum particle swarm optimization (QPSO) algorithm and binary bit evolutionary search of genetic particle swarm optimization (GPSO) in order to achieve better optimization performances. The proposed HQGPSO also can be viewed as a kind of hybridization of micro-space based search and macro-space based search, which enriches the searching behavior to enhance and balance the exploration and exploitation abilities in the whole searching space. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.
Keywords: quantum particle swarm optimization, genetic particle swarm optimization, hybrid algorithm Optimization, Swarm Intelligence, optimal reactive power, Transmission loss.
Title: Hybrid Quantum Genetic Particle Swarm Optimization Algorithm For Solving Optimal Reactive Power Dispatch Problem
Author: K. Lenin, Dr.B.Ravindranath Reddy, Dr.M.Surya Kalavathi
International Journal of Recent Research in Electrical and Electronics Engineering (IJRREEE)
Paper Publications