Abstract
This paper presents Improved Frog Leaping (IFL) algorithm for solving optimal reactive power problem. Comprehensive exploration capability of Particle Swarm Optimization (PSO) and good local search ability of Frog Leaping Algorithm (FLA) has been hybridized to solve the reactive power problem and it overcomes the shortcomings of premature convergence. In order to evaluate the validity of the proposed Improved Frog Leaping (IFL) algorithm, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard algorithms. Simulation results show that proposed Improved Frog Leaping (IFL) algorithm has reduced the real power loss considerably and voltage profiles are within the limits.
Highlights
Different numerical methods have been implemented to solve this optimal reactive power dispatch problem
In order to evaluate the validity of the proposed Improved Frog Leaping (IFL) algorithm, it has been tested in Standard IEEE 57,118 bus systems and compared to other standard algorithms
At first Improved Frog Leaping (IFL) algorithm has been tested in standard IEEE-57 bus power system
Summary
Different numerical methods have been implemented to solve this optimal reactive power dispatch problem. In recent times Global Optimization techniques such as genetic algorithms have been proposed to solve the reactive power flow problem [8.9]. This paper presents Improved Frog Leaping (IFL) algorithm for solving optimal reactive power problem. Global exploration capability of Particle Swarm Optimization (PSO) and good local search capability of Frog Leaping Algorithm (FLA) has been hybridized to solve the reactive power problem and it overcomes the shortcomings of premature convergence. Simulation results show that proposed Improved Frog Leaping (IFL) algorithm has reduced the real power loss considerably and voltage profiles are within the limits
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