Veuillez utiliser cette adresse pour citer ce document :
http://dspace.univ-bouira.dz:8080/jspui/handle/123456789/12359
Titre: | Novel design of artificial ecosystem optimizer for large-scale optimal reactive power dispatch problem with application to Algerian electricity grid |
Auteur(s): | Souhil, MOUASSA |
Date de publication: | 17-oct-2021 |
Editeur: | university bouira |
Référence bibliographique: | Neural Computing and Applications |
Résumé: | 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 … |
URI/URL: | http://dspace.univ-bouira.dz:8080/jspui/handle/123456789/12359 |
Collection(s) : | Articles |
Fichier(s) constituant ce document :
Fichier | Description | Taille | Format | |
---|---|---|---|---|
MouassaV1.R_Proof_NCAA-with-cover-page-v2.pdf | 2,66 MB | Adobe PDF | Voir/Ouvrir |
Tous les documents dans DSpace sont protégés par copyright, avec tous droits réservés.