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Élément Dublin Core | Valeur | Langue |
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dc.contributor.author | Souhil, MOUASSA | - |
dc.date.accessioned | 2022-03-01T10:04:18Z | - |
dc.date.available | 2022-03-01T10:04:18Z | - |
dc.date.issued | 2021-10-17 | - |
dc.identifier.citation | Neural Computing and Applications | en_US |
dc.identifier.uri | http://dspace.univ-bouira.dz:8080/jspui/handle/123456789/12359 | - |
dc.description.abstract | Optimization of reactive power dispatch (ORPD) problem is a key factor for stable and secure operation of the electric power systems. In this paper, a newly explored nature-inspired optimization through artificial ecosystem optimization (AEO) algorithm is proposed to cope with ORPD problem in large-scale and practical power systems. ORPD is a well-known highly complex combinatorial optimization task with nonlinear characteristics, and its complexity increases as a number of decision variables increase, which makes it hard to be solved using conventional optimization techniques. However, it can be efficiently resolved by using nature-inspired optimization algorithms. AEO algorithm is a recently invented optimizer inspired by the energy flocking behavior in a natural ecosystem including non-living elements such as sunlight, water, and air. The main merit of this optimizer is its high flexibility that leads to … | en_US |
dc.language.iso | en | en_US |
dc.publisher | university bouira | en_US |
dc.title | Novel design of artificial ecosystem optimizer for large-scale optimal reactive power dispatch problem with application to Algerian electricity grid | en_US |
dc.type | Article | en_US |
Collection(s) : | Articles |
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MouassaV1.R_Proof_NCAA-with-cover-page-v2.pdf | 2,66 MB | Adobe PDF | Voir/Ouvrir |
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