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Une étude à base de simulation d'un modèle de régulation prévisionnel dans un bâtiment commercial de taille moyenne.

A simulation-based study of model predictive control in a medium-sized commercial building.

Numéro : pap. 3598

Auteurs : LI P., BARIC M., NARAYANAN S., et al.

Résumé

This paper presents a computationally efficient model predictive control (MPC) algorithm to optimize the energy use of the heating ventilation, and air-conditioning (HVAC) system in a multi-zone building and demonstrates the benefits using whole building energy simulations. High-fidelity models are often not well suited for optimization-based controller design and implementation. In this paper, we present an MPC algorithm using data-driven models to optimize the energy consumption of a multi-zone building served by multiple air handling units (AHUs) and a central chiller plant. The simulation results show promising benefits of applying the MPC algorithm with an average energy saving of 15% for cooling season. The computational efficiency of the MPC algorithm demonstrated makes it suitable for real-time implementation planned in the near future.

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 : A simulation-based study of model predictive control in a medium-sized commercial building.
  • Identifiant de la fiche : 30006855
  • Langues : Anglais
  • Sujet : Environnement
  • Source : 2012 Purdue Conferences. 2nd International High Performance Buildings Conference at Purdue.
  • Date d'édition : 16/07/2012

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