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Variable refrigerant flow heat pump model with estimated parameters and emulated controller based on manufacturer data

Aziz Mbaye et Massimo Cimmino

Communication écrite (2022)

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Abstract

A new physics-based and modular variable refrigerant flow (VRF) heat pump model aimed toward multi-year simulations is presented. The model allows the simulation of any number of indoor units (IU), outdoor units (OU) and compressors. A parameter-estimation procedure and a control strategy both using available manufacturer data is proposed. The model is validated against data collected from a VRF system that services the first floor of the former ASHRAE Headquarters Building in Atlanta (USA), comprised of 22 IU, 2 OU, and 8 compressors. Results show that the model accurately predicts the total energy consumption over a two-month cooling period, with a relative error, normalized mean bias error, and coefficient of variation of the root mean square error of 1%, 1.6%, and 16.7%, respectively.

Département: Département de génie mécanique
Organismes subventionnaires: CRSNG/NSERC
Numéro de subvention: RGPIN-2018-04471
URL de PolyPublie: https://publications.polymtl.ca/57209/
Nom de la conférence: 5th Building Performance Analysis Conference and SimBuild (2022)
Lieu de la conférence: Chicago, Illinois
Date(s) de la conférence: 2022-09-14 - 2022-09-16
Titre de la revue: Science and Technology for the Built Environment (vol. 30, no 4)
Maison d'édition: Taylor and Francis
DOI: 10.1080/23744731.2023.2279469
URL officielle: https://doi.org/10.1080/23744731.2023.2279469
Date du dépôt: 29 janv. 2024 14:38
Dernière modification: 23 mars 2025 16:02
Citer en APA 7: Mbaye, A., & Cimmino, M. (septembre 2022). Variable refrigerant flow heat pump model with estimated parameters and emulated controller based on manufacturer data [Communication écrite]. 5th Building Performance Analysis Conference and SimBuild (2022), Chicago, Illinois (18 pages). Publié dans Science and Technology for the Built Environment, 30(4). https://doi.org/10.1080/23744731.2023.2279469

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