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dc.contributor.authorSouhil, MOUASSA-
dc.date.accessioned2022-03-01T10:04:18Z-
dc.date.available2022-03-01T10:04:18Z-
dc.date.issued2021-10-17-
dc.identifier.citationNeural Computing and Applicationsen_US
dc.identifier.urihttp://dspace.univ-bouira.dz:8080/jspui/handle/123456789/12359-
dc.description.abstractOptimization 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.isoenen_US
dc.publisheruniversity bouiraen_US
dc.titleNovel design of artificial ecosystem optimizer for large-scale optimal reactive power dispatch problem with application to Algerian electricity griden_US
dc.typeArticleen_US
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