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Amélioration de la qualité des solutions dans l'optimisation de la charge des refroidisseurs.

Solution quality improvement in chiller loading optimization.

Auteurs : GEEM Z. W.

Type d'article : Article

Résumé

In order to reduce greenhouse gas emission, we can energy-efficiently operate a multiple chiller system using optimization techniques. So far, various optimization techniques have been proposed to the optimal chiller loading problem. Most of those techniques are meta-heuristic algorithms such as genetic algorithm, simulated annealing, and particle swarm optimization. However, this study applied a gradient-based method, named generalized reduced gradient, and then obtains better results when compared with other approaches. When two additional approaches (hybridization between metaheuristic algorithm and gradient-based algorithm; and reformulation of optimization structure by adding a binary variable which denotes chiller’s operating status) were introduced, generalized reduced gradient found even better solutions. [Reprinted with permission from Elsevier. Copyright, 2011].

Détails

  • Titre original : Solution quality improvement in chiller loading optimization.
  • Identifiant de la fiche : 30004062
  • Langues : Anglais
  • Source : Applied Thermal Engineering - vol. 31 - n. 10
  • Date d'édition : 07/2011
  • DOI : http://dx.doi.org/10.1016/j.applthermaleng.2011.02.030

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