Abstract
In this paper, an Ameliorated Particle Swarm Optimization (APSO) algorithm has been proposed to solve the optimal reactive power dispatch problem. Particle Swarm Optimization (PSO) is swarm intelligence-based exploration and optimization algorithm which is used to solve global optimization problems. But due to deficiency of population diversity and early convergence it is often stuck into local optima. Diversity upsurges and avoids premature convergence by using evolutionary operators in PSO. In this paper the intermingling crossover operator is used to upsurge the exploration capability of the swarm in the exploration space. Particle Swarm Optimization uses this crossover method to converge optimum solution in quick manner. Thus the intermingling crossover operator is united with particle swarm optimization to augment the performance and possess the diversity which guides the particles to the global optimum powerfully. Proposed Ameliorated Particle Swarm Optimization (APSO) algorithm has been tested in standard IEEE 30 bus test system and simulation results shows clearly the improved performance of the projected algorithm in reducing the real power loss and static voltage stability margin has been enhanced.
Highlights
IntroductionMany numerical methods [1,2,3,4,5,6,7] have been applied to solve the optimal reactive power dispatch problem
Reactive power optimization plays a key role in optimal operation of power systems
Minimization of the real power loss (Ploss) in transmission lines is mathematically stated as follows
Summary
Many numerical methods [1,2,3,4,5,6,7] have been applied to solve the optimal reactive power dispatch problem. Many Evolutionary algorithms have been already proposed to solve the reactive power flow problem [9,10,11]. To solve the optimal reactive power dispatch problem. In [16, 17] nonlinear interior point method and pattern-based algorithm has been used to solve the reactive power problem. An Ameliorated Particle Swarm Optimization (APSO) algorithm has been proposed to solve the optimal reactive power dispatch problem. Particle Swarm Optimization (PSO) [21] has been used efficaciously in solving many optimization problems, for its simplicity and fast convergence rate. The simulation results show that our proposed methodology outperforms all the entitled reported algorithms in minimization of real power loss
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