Abstract
This paper present’s Dimensioned Particle Swarm Optimization (DPSO) algorithm for solving Reactive power optimization (RPO) problem. Dimensioned extension is introduced to particles in the particle swarm optimization (PSO) model in order to overcome premature convergence in interactive optimization. In the performance of basic PSO often flattens out with a loss of diversity in the search space as resulting in local optimal solution. Proposed algorithm has been tested in standard IEEE 57 test bus system and compared to other standard algorithms. Simulation results reveal about the best performance of the proposed algorithm in reducing the real power loss and voltage profiles are within the limits.
Highlights
Reactive power optimization (RPO) problem is one of the difficult optimization problems in power systems
Dimensioned extension is introduced to particles in the particle swarm optimization (PSO) model in order to overcome premature convergence in interactive optimization
Proposed algorithm has been tested in standard IEEE 57 test bus system and compared to other standard algorithms
Summary
Reactive power optimization (RPO) problem is one of the difficult optimization problems in power systems. The reactive power dispatch problem involves best utilization of the existing generator bus voltage magnitudes, transformer tap setting and the output of reactive power sources so as to minimize the loss and to enhance the voltage stability of the system. It involves a non linear optimization problem. Various mathematical techniques have been adopted to solve this optimal reactive power dispatch problem These include the gradient method [1,2], Newton method [3] and linear programming [4,5,6,7].The gradient and Newton methods suffer from the difficulty in handling inequality constraints.
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