Publications Scientifiques

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Author: search.filters.author.Recioui, AbdelmadjidSubject: search.filters.subject.Genetic algorithms

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    Optimal Placement of Fault Passage Indicators in Distribution Networks using Genetic Algorithms
    (Université M'hamed Bougara de Boumerdès, 2021) Recioui, Abdelmadjid; Merdj, Mounir; Anouar, Kamli
    Fault Passage Indicators (FPIs); also named Faulted Circuit Indicators (FCIs), have been under development for the last 70 years including new capabilities to satisfy the needs of the distribution network operators. In order to improve system stability, these devices can be deployed along the feeder to reduce, or even eliminate, the uncertainty about the fault location. The number and location of FPIs affects the network reliability that can lead to extra charge on the distribution companies as well as the consumers. In this work, the optimal number and location of fault passage indicators in Power Distribution Networks (PDN) are determined. The problem is cast as an optimization task with a special economical combined objective function and solved using the genetic algorithms. The work has been tested on the two case studies, IEEE 9 bus and IEEE 33 bus systems.
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    Use of genetic algorithms in linear and planar antenna array synthesis based on Schelkunoff method
    (2007) Recioui, Abdelmadjid; Azrar, A.
    Genetic algorithms coupled with the Schelkunoff synthesis method are used to synthesize equispaced linear and planar arrays. The purpose is to find the different excitation amplitudes and phases to achieve good matching between the desired and calculated radiation patterns. Examples which demonstrate the versatility of the approach presented in this article are considered for various patterns including the steered pattern case. The planar array is treated as a set of two separate linear arrays upon which Schelkunoff method is applied separately
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    Synthesis of linear arrays with sidelobe level reduction constraint using genetic algorithm
    (2008) Recioui, Abdelmadjid; Azrar, Arab; Bentarzi, Hamid; Dehmas, Mokrane; Chalal, Mouloud
    The synthesis of uniformly spaced linear array geometries with minimum sidelobe level and beamforming capability using genetic algorithms is presented. The iterative process aims not only at matching the desired pattern to the desired one but minimizing the sidelobe level as well; through optimizing the element excitations. Various examples are included to demonstrate the design effectiveness and flexibility namely for switched smart antenna systems applications
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    Genetic algorithm based MIMO capacity enhancement In spatially correlated channels including mutual coupling
    (Springer, 2012) Recioui, Abdelmadjid; Bentarzi, Hamid
    Higher system capacities can be achieved if multiple antennas are used on both sides of the wireless link, thus creating a multiple-input-multiple-output (MIMO) system. In this work, the maximization of MIMO system capacity in Rayleigh fading, spatially correlated channels involving practical antenna arrays is challenged through inter-element spacing optimization. The system capacity is evaluated using a proposed formula that takes into account both antenna mutual coupling and signal correlation. Capacity values turn out to outperform the ones obtained considering the conventional antenna array geometries