scholarly journals Hybrid Genetic Algorithm and Particle Swarm Optimization Algorithm for Optimal Power Flow in Power System

2019 ◽  
Vol 2 (2) ◽  
pp. 31-37
Author(s):  
Gayathri Devi K.S
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Power System ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Particle Swarm Optimization Algorithm ◽  
Hybrid Genetic Algorithm ◽  
Swarm Optimization ◽  
Optimal Power

A Chaos Particle Swarm Optimization Algorithm for Optimal Power Flow

2014 ◽  
Vol 1008-1009 ◽  
pp. 466-472
Author(s):  
Cheng Jun Xia ◽  
Yun Zhou ◽  
Hao Yu Huang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Power Flow ◽  
Optimal Power Flow ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Premature Convergence ◽  
Swarm Optimization ◽  
Optimal Power ◽  
Performance Of Algorithm

The chaos particle swarm optimization algorithm was presented to solving optimal power flow. The proposed OPF considers the total cost of generators as the objective functions. To enhance the performance of algorithm, a premature convergence strategy was proposed. The strategy can be divided into two parts. In the first part, a method is introduced to judge premature convergence, while another part provides an advance method to improve the performance of algorithm with searching the solution in total feasible region. The control strategy used to prevent premature convergence will obtain starting values for initial particle before program iterating, so it can provide bitter probability of detecting global optimum solution. The simulation results on standard IEEE 30-bus system minimizing fuel cost of generator show the effectiveness of the chaos particle swarm optimization algorithm, and can obtain a good solution.

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