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A simulation environment for performance analysis of HVAC systems

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Abstract

Due to the lack of a building simulation program that can simulate in details the combined heat, vapor, and liquid transfer in porous elements and the HVAC (heating, ventilation and air-conditioning) systems, a flexible computational algorithm has been elaborated in order to integrate models for both HVAC systems and multizone hygrothermal building model. In the algorithm, models for the primary system-composed of chiller, cooling tower, primary pumps, and condensation pumps—have been described. For the secondary system, models for the cooling and dehumidifying coil, humidifier, fan, and mixing box have been considered. Those mathematical models have been integrated into the whole-building PowerDomus simulation environment. The simulation environment is presented, and results show the usability aspects of the proposed computer environment by comparing air- and water-cooled equipment.

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Abbreviations

a, b, c, ..., f :

curve coefficients

CAPFT :

chiller capacity as a function of temperatures (dimensionless)

C 0, ..., C 3 :

curve coefficients

C p :

specific heat (J/kg·K)

EIRFT :

chiller efficiency as a function of temperatures

EIRFPLR :

chiller efficiency as a function of the part-load ratio

FFLP :

polynomial as a function of the part-load ratio

PLR :

part-load ratio

Pot comp (PLR):

compressor chiller electric power at part-load conditions (W)

Pot comp,max :

chiller compressor electric power at full load conditions (W)

Pot comp,rat :

chiller compressor electric power at rating conditions (W)

Pot ref :

the power consumption at the reference chilled and condenser water temperatures (W)

Q ev,available :

chiller cooling capacity available in full load conditions (W)

Q ev,rat :

chiller cooling capacity at rating conditions (W)

R :

thermal resistance (m2·K/W)

T ev,out :

outlet evaporator water temperature (°C)

T cd,in :

inlet condenser temperature (external air or condensing water) (°C)

T set :

outlet water set point temperature (°C)

T wout,off :

outlet water temperature with tower fan off (°C)

T wout,on :

outlet water temperature with tower fan on (°C)

U :

overall heat transfer coefficient (W/m2·K)

W t :

actual pump/motor power at part-load conditions (W)

W t,rat :

pump/motor power at rating conditions (W)

λ:

thermal conductivity (W/m·EK)

λ :

time fraction

References

  • Barbosa RM, Mendes N (2003). Dynamic simulation of fan-coil systems. Paper presented at the 17th International Congress of Mechanical Engineering (COBEM’f2003), Sao Paulo, Brazil.

  • Barbosa RM, Mendes N (2008). Combined simulation of central HVAC systems with a whole-building hygrothermal model. Energy and Buildings. 40(3): 276–288.

    Article  Google Scholar 

  • Bourdouxhe JP, Grodent M, Lebrun J (1999). HVAC 1 toolkit: a toolkit for primary HVAC system energy calculation. Atlanta, GA: American Society of Heating, Refrigerating and Air Conditioning Engineers.

    Google Scholar 

  • Bourdouxhe JP, André P (1997). Simulation of a centralized cooling plant under different control strategies. In: Proceedings of the 5th International Building Performance Simulation Association Conference and Exhibition, Prague, Czech Republic, Vol. 1, pp. 95–102.

    Google Scholar 

  • Brandemuehl MJ, Gabel S, Andrésen I (1993). HVAC 2 toolkit: a toolkit for secondary HVAC system energy calculation. AAtlanta, GA: American Society of Heating, Refrigerating and Air Conditioning Engineers.

    Google Scholar 

  • Cherem-Pereira GC (2003). Room air conditionners modelling. Master Dissertation, Mechanical Engineering Department, Pontifical Catholic University of Paraná. (in Portuguese)

  • Cherem-Pereira GC, Mendes N (2003a). Development of empirical models for predicting heat exchangers performance of a window-type air conditioner. Paper presented at the Fourth European Thermal Sciences Conference, Valencia-Spain.

  • Cherem-Pereira GC, Mendes N (2003b). Room air conditioners: determination of empirical correlations for predicting building energy consumption. In: Proceedings of the 8th International Building Performance Simulation Association Conference and Exhibition, Eindhoven, Netherlands, pp. 1017–1024.

  • Chow TT, Clarke JA, Dunn A (1997). Primitive parts: an approach to air-conditioning component modeling. Energy and Buildings, 26: 165–173.

    Article  Google Scholar 

  • Corrêa J M (1998). Dynamic analysis of the integrated behaviour of buildings and HVAC systems. PhD Thesis, Federal University of Santa Catarina, Florianópolis. (in Portuguese)

    Google Scholar 

  • Cui J, Watanabe T, Ryu Y, Akashi Y, Nishiyama N (1999). Numerical simulation on simultaneous control process of indoor air temperature and humidity. In: Proceedings of the 6th International Building Performance Simulation Association Conference and Exhibition, Kyoto, Japan. Vol. 2, pp. 1005–1012.

    Google Scholar 

  • EnergyPlus 2004. EnergyPlus engineering document. University of Illinois and the Ernest Orlando Lawrence Berkeley National Laboratory.

  • Ghiaus C, Chicinas A, Inard C (2007). Grey-box identification of air-handling unit elements. Control Engineering Practice, 15: 421–433.

    Article  Google Scholar 

  • Hensen JLM (1991). On the thermal interaction of building structure and heating and ventilating system. PhD Thesis, Eindhoven University of Technology.

  • Hens H (2003). Proposal for a new annex. Whole building heat, air and moisture response (MOIST-ENG). Katholieke Universiteit Leuven, Belgium.

    Google Scholar 

  • Holm A, Künzel H, Radon J (2002). Uncertainty approaches for hygrothermal building simulations—Drying of AAC in hot and humid climates. Buildings VIII Conference.

  • Knabe G, Le H (2001). Building simulation by application of a HVAC system considering the thermal and moisture behaviors of the perimeter walls, In: Proceedings of the 6th International Building Performance Simulation Association Conference and Exhibition, Rio de Janeiro, Brazil, pp. 965–972.

  • Lam CL, Hui SCM, Chan ALS (1997). Regression analysis of high-rise fully air-conditioned office buildings. Energy and Buildings, 26: 189–197.

    Article  Google Scholar 

  • Mendes N (1997). Models for predicting heat and moisture transfer through porous building elements. PhD Thesis, Federal University of Santa Catarina, Floriańopolis. (in Portuguese)

    Google Scholar 

  • Mendes N, Ridley I, Lamberts R, Philippi PC, Budag K (1999). Umidus: A PC program for the prediction of heat and moisture transfer in porous building elements. In: Proceedings of the 6th International Building Performance Simulation Association Conference and Exhibition, Kyoto, Japan.

  • Mendes N, Philippi PC, Lamberts R (2002). A new mathematical method to solve highly coupled equations of heat and mass transfer in porous media. International Journal of Heat and Mass Transfer, 45: 509–518.

    Article  MATH  Google Scholar 

  • Mendes N, Winkelmann FC, Lamberts R, Philippi PC (2003a). Moisture effects on conduction loads. Energy and Buildings, 35: 631–644.

    Google Scholar 

  • Mendes N, Oliveira GHC, Araújo HX De, Coelho LS (2003b). A MATLAB—based simulation tool for building thermal performance analysis. In: Proceedings of the 8th International Building Performance Simulation Association Conference and Exhibition, Eindhoven, Netherlands, Vol. 1, pp. 855–862.

    Google Scholar 

  • Nassif N, Kajl S, Sabourin R (2003). Components modeling of an existing HVAC system, VI Colloque Interuniversitaire Franco-Québécois, Thermique des systèmes, Québec. (in French)

  • Novak PR, Mendes N, Oliveira GHC (2004). Simulation and analysis of a secondary HVAC system using MATLAB/SIMULINK platform. Paper presented at the International Mechanical Engineering Congress, USA.

  • Pacific Gas and Electric (1996). Chiller plant performance curves. In: Proceedings from the PG&E energy center DOE-2 lunch series, San Francisco, CA.

  • Philip JR, De Vries DA (1957). Moisture movement in porous materials under temperature gradients. Transactions of the American Geophysical Union, 38(2): 222–232.

    Google Scholar 

  • Rode C, Holm A, Padfield T (2004). A review of humidity buffering in the interior spaces. Journal of Thermal Envelope and Building Science. 27: 221–226.

    Google Scholar 

  • Simonson C, Salonvaara M, Ojanen T (2002). The effect of structures on indoor humidity—possibilities to improve comfort and perceived air quality. Indoor Air, 12: 243–251.

    Article  Google Scholar 

  • Wang YW, Cai WJ, Soh YC, Li SJ, Lu L, Xie L (2004). A simplified modeling of cooling coils for control and optimization of HVAC systems. Energy Conversion and Management, 45 (18–19): 2915–2930.

    Article  Google Scholar 

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Authors and Affiliations

  1. Thermal Systems Laboratory-LST, Pontifical Catholic University of Paraná-PUCPR/CCET, Rua Imaculada Conceição, 1155, Curitiba-PR, 80215-901, Brazil

    Nathan Mendes & Roberto Zanetti Freire

Authors
  1. Nathan Mendes
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  2. Rogério M. Barbosa
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  3. Roberto Zanetti Freire
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  4. Ricardo C. L. F. Oliveira
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Correspondence to Nathan Mendes.

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Mendes, N., Barbosa, R.M., Freire, R.Z. et al. A simulation environment for performance analysis of HVAC systems. Build. Simul. 1, 129–143 (2008). https://doi.org/10.1007/s12273-008-8216-7

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  • DOI: https://doi.org/10.1007/s12273-008-8216-7

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