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Optimisation de la conception de systèmes à énergie renouvelable dans des immeubles à énergie faible ou nulle utilisant des méthodes d'optimisation à objectifs uniques et multiples.

Design optimization of renewable energy systems in low/zero energy buildings using single and multi objective optimization methods.

Numéro : pap. 3484

Auteurs : LU Y., WANG S., ZHAO Y.

Résumé

Low energy buildings and zero energy buildings have attracted increasing attention in both academic and professional fields following the ambitions of many governments in reducing building energy consumption and carbon emission. This paper presents an investigation on the optimal design of renewable energy systems in two types of buildings: low energy buildings and zero energy buildings. The first zero energy building in Hong Kong, namely Hong Kong Zero Carbon Building, is taken as a reference building in this study. The TRNSYS building model is used to generate the annual cooling load profile of the building. Simplified models are developed to simulate the building energy systems including the air-conditioning systems and the renewable energy systems in Matlab while the building annual cooling load profile is taken as the input. Genetic Algorithm method and Non-dominated Sorting Genetic Algorithm(NSGA-II) approach are implemented for single objective optimization and multi-objectives optimization respectively. Three most important design parameters, i.e., sizes of photovoltaic, wind turbine and bio-diesel generator, are chosen as the variables tobe optimized. The performances of buildings, each with different combinations of renewable system sizes, are compared and evaluated.

Documents disponibles

Format PDF

Pages : 10 p.

Disponible

  • Prix public

    20 €

  • Prix membre*

    15 €

* meilleur tarif applicable selon le type d'adhésion (voir le détail des avantages des adhésions individuelles et collectives)

Détails

  • Titre original : Design optimization of renewable energy systems in low/zero energy buildings using single and multi objective optimization methods.
  • Identifiant de la fiche : 30013772
  • Langues : Anglais
  • Sujet : Environnement
  • Source : 2014 Purdue Conferences. 3rd International High Performance Buildings Conference at Purdue.
  • Date d'édition : 14/07/2014

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