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Recherches sur la pression de refoulement optimale dans les pompes à chaleur au CO2 à l’aide de réseaux de neurones de type GMDH et PSO-BP—Partie B: Étude expérimentale.

Investigations on optimal discharge pressure in CO2 heat pumps using the GMDH and PSO-BP type neural network—part B: Experimental study.

Auteurs : SONG Y., YANG D., LI M., et al.

Type d'article : Article, Article de la RIF

Résumé

In this second part of a two-part article, the Particle Swarm Optimization (PSO) based Back-Propagation Neural-Network (BP) based algorithm for the discharge pressure controlling was experimentally achieved based on a subcooler-based transcritical CO2 rig, for further developing an acceptable real-time control approach. The detail of the control strategy in practice was clearly shown including the recirculating water PID control, the PSO-BP based discharge pressure optimization and the electronic expansion valve regulatory mechanism. Besides, the optimal discharge pressure sought by PSO-BP and corresponding system performances were compared with the results from Wang/Liao’s predictions and the tested values, which validated the prominent effectiveness of the PSO-BP method due to its satisfactory consistency with the tested data. Additionally, the subcooler-based rig under the discharge pressure from PSO-BP control had more than 15 and 25% improvements over the baseline cycle under floor heating and radiator conditions, respectively, which provided an innovative and appropriate idea for developers and manufacturers.

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Format PDF

Pages : 248-257

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    20 €

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Détails

  • Titre original : Investigations on optimal discharge pressure in CO2 heat pumps using the GMDH and PSO-BP type neural network—part B: Experimental study.
  • Identifiant de la fiche : 30026839
  • Langues : Anglais
  • Source : International Journal of Refrigeration - Revue Internationale du Froid - vol. 106
  • Date d'édition : 10/2019
  • DOI : http://dx.doi.org/10.1016/j.ijrefrig.2019.06.008

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