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Optimisation du chargement des refroidisseurs basée sur un algorithme génétique permettant des économies d'énergie.

Genetic algorithm based optimal chiller loading for energy conservation.

Auteurs : CHANG Y. C.

Type d'article : Article

Résumé

This study employs a genetic algorithm to solve optimal chiller loading problem. The genetic algorithm overcomes the flaw that Lagrangian method is not suitable as there is non-convex kW-PLR function in a system. This study uses the part load ratios (PLR) of chiller units to binary code chromosomes, and execute reproduction, crossover and mutation operation. Since the semiconductor plant is the largest a/c load for power consumption, it is used as an example in the paper. After analysis and comparison of the case study, the author is confident to say that this method not only solves the problem of the Lagrangian method, but also produces results with high accuracy within a rapid timeframe. It can be perfectly applied to the operation of air conditioning systems.

Détails

  • Titre original : Genetic algorithm based optimal chiller loading for energy conservation.
  • Identifiant de la fiche : 2006-0875
  • Langues : Anglais
  • Source : Applied Thermal Engineering - vol. 25 - n. 17-18
  • Date d'édition : 12/2005

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