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Modélisation stochastique de l’occupation à court terme de bâtiments éco-énergétiques.

Stochastic modeling of short-term occupancy for energy efficient buildings.

Numéro : pap. 3542

Auteurs : DONG J., WINSTEAD C., DJOUADI S. M., et al.

Résumé

In this paper, we present a simple yet effective algorithm to automatically assign reference temperature set-points based on the occupancy information. Both the binary and detailed occupancy estimation cases are considered. In the first case study, we assume the schedule involves only binary states (occupied or not occupied),i.e. the room is in variant. With long-term observations occupancy levels can be estimated using statistical tools. In the second case study, two techniques are introduced. Firstly, we propose an identification-based approaches. More precisely, we identify the models via Expectation Maximization (EM) approach. The statistical state space model is built in linear form for the mapping between the occupancy measurements and real occupancy states with noise considered. Secondly, we introduce a novel finite state automata (FSA) which is successfully reconstructed by general systems problem solver (GSPS).As far as we know, no studies have used the finite state machine or general system theory to estimate occupancy in buildings. All above estimates can be used to adaptively update the temperature set-points for Heating, Ventilation, and Air-Conditioning (HVAC) control strategy.

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 : Stochastic modeling of short-term occupancy for energy efficient buildings.
  • Identifiant de la fiche : 30019286
  • Langues : Anglais
  • Sujet : Environnement
  • Source : 2016 Purdue Conferences. 4th International High Performance Buildings Conference at Purdue.
  • Date d'édition : 11/07/2016

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