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Efficient design under uncertainty of renewable power generation systems using partitioning and regression in the course of optimization / Athanasios I. Papadopoulos in Industrial & engineering chemistry research, Vol. 51 N° 39 (Octobre 2012) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 51 N° 39 (Octobre 2012) . - pp. 12862-12876 Titre : Efficient design under uncertainty of renewable power generation systems using partitioning and regression in the course of optimization Type de document : texte imprimé Auteurs : Athanasios I. Papadopoulos, Auteur ; Garyfallos Giannakoudis, Auteur ; Panos Seferlis, Auteur Année de publication : 2012 Article en page(s) : pp. 12862-12876 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Optimization  Phase  partition  Uncertainty  Design Résumé : Renewable power generation systems are significantly affected by uncertainty due to intense variability often observed in energy sources. Uncertainty should be considered during design to enable optimum performance within constantly changing conditions. However, the resulting computational complexity and effort is high, especially in view of flowsheets integrating multiple subsystems. To address this challenge, the presented work proposes the partitioning of the space representing uncertain realizations to facilitate the development and continuous update of a surrogate model in the course of optimization. A wide exploration of this strategy reveals and addresses important issues in the implementation of the partitioning and model regression layers. Formal statistical associations are examined regarding the beneficial implications of partitioning to computational efficiency and surrogate model development. The proposed strategy is presented as part of a Simulated Annealing algorithm. This is tested in terms of computational efficiency and solution robustness against an adaptation of Stochastic Annealing, which addresses computational intensity through a different approach while depending entirely on a full system model Results are illustrated through numerical examples and case studies on a stand-alone, hybrid system using renewable energy sources for power generation and storage. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26419243 [article] Efficient design under uncertainty of renewable power generation systems using partitioning and regression in the course of optimization [texte imprimé] / Athanasios I. Papadopoulos, Auteur ; Garyfallos Giannakoudis, Auteur ; Panos Seferlis, Auteur . - 2012 . - pp. 12862-12876. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 39 (Octobre 2012) . - pp. 12862-12876 Mots-clés : Optimization  Phase  partition  Uncertainty  Design Résumé : Renewable power generation systems are significantly affected by uncertainty due to intense variability often observed in energy sources. Uncertainty should be considered during design to enable optimum performance within constantly changing conditions. However, the resulting computational complexity and effort is high, especially in view of flowsheets integrating multiple subsystems. To address this challenge, the presented work proposes the partitioning of the space representing uncertain realizations to facilitate the development and continuous update of a surrogate model in the course of optimization. A wide exploration of this strategy reveals and addresses important issues in the implementation of the partitioning and model regression layers. Formal statistical associations are examined regarding the beneficial implications of partitioning to computational efficiency and surrogate model development. The proposed strategy is presented as part of a Simulated Annealing algorithm. This is tested in terms of computational efficiency and solution robustness against an adaptation of Stochastic Annealing, which addresses computational intensity through a different approach while depending entirely on a full system model Results are illustrated through numerical examples and case studies on a stand-alone, hybrid system using renewable energy sources for power generation and storage. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26419243