Les Inscriptions à la Bibliothèque sont ouvertes en
ligne via le site: https://biblio.enp.edu.dz
Les Réinscriptions se font à :
• La Bibliothèque Annexe pour les étudiants en
2ème Année CPST
• La Bibliothèque Centrale pour les étudiants en Spécialités
A partir de cette page vous pouvez :
Retourner au premier écran avec les recherches... |
Détail de l'auteur
Auteur Padilha-Feltrin, A.
Documents disponibles écrits par cet auteur
Affiner la rechercheTime-series-based maximization of distributed wind power generation integration / Ochoa, L.F. in IEEE transactions on energy conversion, Vol. 23 n°3 (Septembre 2008)
[article]
in IEEE transactions on energy conversion > Vol. 23 n°3 (Septembre 2008) . - pp. 968 - 974
Titre : Time-series-based maximization of distributed wind power generation integration Type de document : texte imprimé Auteurs : Ochoa, L.F., Auteur ; Padilha-Feltrin, A., Auteur ; Harrison, G.P., Auteur Année de publication : 2008 Article en page(s) : pp. 968 - 974 Note générale : Energy conversion Langues : Anglais (eng) Mots-clés : Pareto optimisation; distributed power generation; distribution networks; genetic algorithms; time series; wind power; wind turbines Résumé : Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of DWPG. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4556651&sortType%3Das [...] [article] Time-series-based maximization of distributed wind power generation integration [texte imprimé] / Ochoa, L.F., Auteur ; Padilha-Feltrin, A., Auteur ; Harrison, G.P., Auteur . - 2008 . - pp. 968 - 974.
Energy conversion
Langues : Anglais (eng)
in IEEE transactions on energy conversion > Vol. 23 n°3 (Septembre 2008) . - pp. 968 - 974
Mots-clés : Pareto optimisation; distributed power generation; distribution networks; genetic algorithms; time series; wind power; wind turbines Résumé : Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of DWPG. En ligne : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=4556651&sortType%3Das [...]