scholarly journals A Hybrid Genetic Algorithm–Interior Point Method for Optimal Reactive Power Flow

2006 ◽  
Vol 21 (3) ◽  
pp. 1163-1169 ◽  
Author(s):  
W. Yan ◽  
F. Liu ◽  
C.Y. Chung ◽  
K.P. Wong
Keyword(s):  
Genetic Algorithm ◽  
Interior Point ◽  
Interior Point Method ◽  
Power Flow ◽  
Reactive Power ◽  
Hybrid Genetic Algorithm ◽  
Point Method ◽  
Reactive Power Flow ◽  
Optimal Reactive Power Flow

scholarly journals A Sequential Hybridization of Genetic Algorithm and Particle Swarm Optimization for the Optimal Reactive Power Flow

2019 ◽  
Vol 11 (14) ◽  
pp. 3862 ◽  
Author(s):  
Imene Cherki ◽  
Abdelkader Chaker ◽  
Zohra Djidar ◽  
Naima Khalfallah ◽  
Fadela Benzergua
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Power Flow ◽  
Reactive Power ◽  
Particle Swarm ◽  
Power Losses ◽  
Swarm Optimization ◽  
Transformation Ratio ◽  
Reactive Power Flow ◽  
Optimal Reactive Power Flow

In this paper, the problem of the Optimal Reactive Power Flow (ORPF) in the Algerian Western Network with 102 nodes is solved by the sequential hybridization of metaheuristics methods, which consists of the combination of both the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO). The aim of this optimization appears in the minimization of the power losses while keeping the voltage, the generated power, and the transformation ratio of the transformers within their real limits. The results obtained from this method are compared to those obtained from the two methods on populations used separately. It seems that the hybridization method gives good minimizations of the power losses in comparison to those obtained from GA and PSO, individually, considered. However, the hybrid method seems to be faster than the PSO but slower than GA.

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