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Abdelkader Chaker
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.

Journal article
Published: 01 January 2011 in Serbian Journal of Electrical Engineering
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Nowadays the electric vehicle motorization control takes a great interest of industrials for commercialized electric vehicles. This paper is one example of the proposed control methods that ensure both safety and stability the electric vehicle by the means of Direct Torque Control (DTC). For motion of the vehicle the electric drive consists of four wheels: two front ones for steering and two rear ones for propulsion equipped with two induction motors, due to their lightweight simplicity and high performance. Acceleration and steering are ensured by the electronic differential, permitting safe and reliable steering at any curve. The direct torque control ensures efficiently controlled vehicle. Electric vehicle direct torque control is simulated in MATLAB SIMULINK environment. Electric vehicle (EV) demonstrated satisfactory results in all type of roads constraints: straight, ramp, downhill and bends.

ACS Style

Brahim Gasbaoui; Abdelkader Chaker; Abdellah Laoufi; Boumediène Allaoua; Abdelfatah Nasri. The efficiency of direct torque control for electric vehicle behavior improvement. Serbian Journal of Electrical Engineering 2011, 8, 127 -146.

AMA Style

Brahim Gasbaoui, Abdelkader Chaker, Abdellah Laoufi, Boumediène Allaoua, Abdelfatah Nasri. The efficiency of direct torque control for electric vehicle behavior improvement. Serbian Journal of Electrical Engineering. 2011; 8 (2):127-146.

Chicago/Turabian Style

Brahim Gasbaoui; Abdelkader Chaker; Abdellah Laoufi; Boumediène Allaoua; Abdelfatah Nasri. 2011. "The efficiency of direct torque control for electric vehicle behavior improvement." Serbian Journal of Electrical Engineering 8, no. 2: 127-146.