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Une méthode fonctionnant grâce aux données pour déterminer les trajectoires de la température de la zone minimisant la demande électrique en période de pointe.

A data-driven method for determining zone temperature trajectories that minimize peak electrical demand.

Auteurs : LEE K. H., BRAUN J. E.

Résumé

Lee and Braun (2008b) developed a simple approach, termed the weighted-averaging method, that estimates building zone temperature set-point variations that minimize peak cooling demand during critical demand periods. This paper extends this approach to air-conditioning power demand and presents the results of a field evaluation for a small commercial building. The weighted-averaging method uses data from two or more test days to determine a near-optimal setpoint trajectory for minimizing peak demand during a demand-limiting period. Evaluation of the method was performed over a two-week test period at a small bank building located in Palm Desert, California. The first week of testing was used to collect baseline data for conventional control and data for estimating the optimal setpoint trajectory. The second week of testing was used to evaluate demand reduction and energy savings for application of trajectories determined using the WA method.

Détails

  • Titre original : A data-driven method for determining zone temperature trajectories that minimize peak electrical demand.
  • Identifiant de la fiche : 2009-1204
  • Langues : Anglais
  • Source : ASHRAE Transactions. 2008 Annual Meeting, Salt Lake City, UT. Volume 114, part 2 + CD-ROM.
  • Date d'édition : 21/06/2008

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