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Imene Cherki
SCAMRE Laboratory, ENPO-MA National Polytechnic School of Oran Maurice Audin, Oran 31000, Algeria

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Journal article
Published: 16 July 2019 in Sustainability
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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.

ACS Style

Imene Cherki; Abdelkader Chaker; Zohra Djidar; Naima Khalfallah; FadelA Benzergua. A Sequential Hybridization of Genetic Algorithm and Particle Swarm Optimization for the Optimal Reactive Power Flow. Sustainability 2019, 11, 3862 .

AMA Style

Imene Cherki, Abdelkader Chaker, Zohra Djidar, Naima Khalfallah, FadelA Benzergua. A Sequential Hybridization of Genetic Algorithm and Particle Swarm Optimization for the Optimal Reactive Power Flow. Sustainability. 2019; 11 (14):3862.

Chicago/Turabian Style

Imene Cherki; Abdelkader Chaker; Zohra Djidar; Naima Khalfallah; FadelA Benzergua. 2019. "A Sequential Hybridization of Genetic Algorithm and Particle Swarm Optimization for the Optimal Reactive Power Flow." Sustainability 11, no. 14: 3862.

Conference paper
Published: 21 June 2019 in Blockchain Technology and Innovations in Business Processes
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In this study, we attempt to solve the problem of the optimal flow of the reactive power (ORPF) by the sequential hybridization of methaheuristics based on the combination of the two techniques on populations that are the genetic algorithm GA and the Particles Swarms Optimization PSO. The aim of this optimization is the minimization of the power losses while keeping the voltage, the generated power and the transformation ratio of the transformers within their limits.

ACS Style

I. Cherki; A. Chaker; Z. Djidar; N. Khalfellah; F. Benzergua. Sequential Hybridization of GA and PSO to Solve the Problem of the Optimal Reactive Power Flow ORPF in the Algerian Western Network (102nodes). Blockchain Technology and Innovations in Business Processes 2019, 338 -346.

AMA Style

I. Cherki, A. Chaker, Z. Djidar, N. Khalfellah, F. Benzergua. Sequential Hybridization of GA and PSO to Solve the Problem of the Optimal Reactive Power Flow ORPF in the Algerian Western Network (102nodes). Blockchain Technology and Innovations in Business Processes. 2019; ():338-346.

Chicago/Turabian Style

I. Cherki; A. Chaker; Z. Djidar; N. Khalfellah; F. Benzergua. 2019. "Sequential Hybridization of GA and PSO to Solve the Problem of the Optimal Reactive Power Flow ORPF in the Algerian Western Network (102nodes)." Blockchain Technology and Innovations in Business Processes , no. : 338-346.