Air management modeling of condensing units in a confined space and its impact on the chiller system performance

Air management modeling of condensing units in a confined space and its impact on the chiller system performance

Energy and Buildings 43 (2011) 2673–2677 Contents lists available at ScienceDirect Energy and Buildings journal homepage: www.elsevier.com/locate/en...

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Energy and Buildings 43 (2011) 2673–2677

Contents lists available at ScienceDirect

Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild

Air management modeling of condensing units in a confined space and its impact on the chiller system performance Yu-Ling Shi b , Liang Yang c , Chun-Lu Zhang a,∗ a

College of Mechanical Engineering, Tongji University, Shanghai 201804, China China R&D Center, Carrier Cooperation, No. 3239, Shen Jiang Road, Shanghai, China c Institute of Refrigeration and Cryogenics, Shanghai Jiaotong University, Shanghai 200240, China b

a r t i c l e

i n f o

Article history: Received 28 April 2010 Received in revised form 21 April 2011 Accepted 18 June 2011 Keywords: Confined space Air management CFD model System model Air recirculation

a b s t r a c t The small air cooled chillers that serve an apartment building or residential villa often have the outdoor condensing units installed within a confined space. The installation distance between chiller and wall or between two chillers has significant impact on the chiller performance. In this study, three CFD (Computational Fluid Dynamics) approaches to condensing unit air management modeling are proposed and compared with each other first. The predicted air flow rates are compared to the test data as well. The comparison shows that the CFD approach with fan boundary definition is the most cost-effective, easy to be implemented, and accurate. Together with the chiller system modeling, a parametric study is further conducted to investigate the effect of the wall–chiller distance and the chiller–chiller distance on the chiller performance. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Small air cooled chillers are widely used in residential buildings, small office buildings, and residential villas in Shanghai. The small air cooled chiller consists of two parts: an outdoor unit and some indoor fan coil units. In the cooling mode, the outdoor coil behaves as an air-cooled condenser. Outdoor air is drawn through the coil by a propeller fan and carries away the heat from the refrigerant condenser. For aesthetic consideration, the outdoor condensing units are usually installed behind the building in a narrowly confined space between two walls. Usually, several units installed in parallel according to the building heat load. Furthermore, such confined space has been squeezed to very limited size in recent years due to the jump of land price in Shanghai. The air side system loss of condensing units increases when the air enters this crowded space via the small opening and leaves from the top. Under some worse conditions, the recirculation of discharge air happens. The high temperature recirculating air not only causes energy waste but also brings up the equipment operation problem, which could seriously affect the performance of air conditioning system and shorten the lifecycle of the compressor. The objective of this study is to reveal heat transfer and performance consequences of poor ventilation in a confined installation space, and provide a reliable and economic

∗ Corresponding author. Tel.: +86 136 71825 133. E-mail address: [email protected] (C.-L. Zhang). 0378-7788/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2011.06.023

modeling approach to study this aspect of air-conditioning design, building service and management. There have been extensive studies on velocity and temperature distributions in room, atrium, corridors and other kinds of buildings. Chen and Srebic [1] did a comprehensive review on the CFD applications in various building structures over the last two decades. Considerable studies on condenser efficiency and oncoil temperature of condensers have been conducted. Chow et al. [2,3] used CFD code to investigate the performance of split-type air conditioners in respect to the temperature rise of the condensing units installed at both high-rise and low-rise buildings re-entrant. The fan function is treated by body force definition. Xue et al. [4] simulated the effect of re-entrant dimensions, air velocity across the condenser and heat rejection of each condenser on velocity and temperature distribution in a confined space. Avara and Daneshgar [5] investigated the effect of wall–chiller distance on entrance air temperature under two kinds of installation condition using CFD. However, most of the work on the condenser unit placement focused on the air flow distribution within the confined space. The condensing unit is modeled as a local heat source with the user defined air flow blowing toward the confined space. To our best knowledge, there is very little work on the modeling techniques study to model the installation effect on condensing unit performance. The wall near the chiller not only affects the coil air entering temperature, but also affects the condensing unit total air flow rate due to the change of the system loss.

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2. CFD model overview Nomenclature COP Cp k Prt Re S T u, U, V

coefficient of performance heat capacity (J/(kg K)) turbulent kinetic energy (J/kg) turbulent Prandtl number Reynolds number source term temperature (K) velocity (m/s)

Greek symbols ı Kronecker delta ε dissipation rate of k (m2 /s3 ) eff , t effective and turbulent viscosity (Pa s)  density (kg/m3 )

CFD software Fluent 6.3 is used for the condensing unit air management modeling. Three CFD approaches are applied to treat the axial fan function. The governing equations for continuity, momentum and energy in tensor form for the computation domain can be expressed as follows. Continuity: ∂(uj ) ∂ =0 + ∂t ∂xj

(1)

Momentum: ∂ ∂ ∂(ui ) + (ui uj ) − ∂t ∂xj ∂xj =−

∂P ∂ + ∂xi ∂xj



eff





∂uj

eff



∂xi

Energy: The objective of this work is to study the effect of the condensing unit installation condition on its performance using CFD simulation. Before we study the installation condition, a reliable and economical CFD approach will be investigated first for reducing the computational cost of further parametric study. This paper proposes three-dimensional CFD approaches for the condensing unit air management modeling and the one-dimensional approach for the small air cooled chiller system performance simulation. The total air flow rate predicted by CFD is compared to the experimental results first. Then a parametric study is conducted to elaborate the impacts of wall–chiller distance and chiller–chiller distance on the air flow rate, coil air entering temperature, and discharge air recirculation. The chiller system performance simulation is also conducted to evaluate the effects of total air flow rate and discharge air recirculation on the system COP. Fig. 1 shows typical outdoor unit of the small air cooled chiller. In this study, the outdoor condenser is the L-shape vertical coil. Air is drawn through the coil and discharged from the top of the unit by a propeller fan.

∂(Cp T ) ∂ ∂ + (uj Cp T ) − ∂t ∂xj ∂xj



∂ui ∂xj 2 3







k + eff

a +

t Prt



ul xl

 

ıij + Si

(2)



·

∂ (Cp T ) = Sheat (3) ∂xj

where eff =  + t , t = C (k2 /ε) and the source terms, Si and Sh , represent the momentum source and the volumetric heat source of coil, respectively. The high Reynolds number standard k–ε turbulence model is used with the default coefficients settings in Fluent 6.3 [6]. Three CFD approaches are applied and compared in the work. The numerical definitions of the three CFD approaches are introduced below and summarized in Table 1. 1. Full grid CFD model: Fan blades are included. To model the axial fan rotation motion, the sliding mesh approach is employed. The unsteady-state governing equations are solved. 2. Simplified model: Fan blades are ignored. Fan pressure curve is defined in the fan boundary condition panel. This CFD model can predict system air flow rate by balancing the system loss and fan pressure curve. 3. System loss model: The fan blades are not included. The mass flow rate inlet boundary condition is used to predict the system loss with a series of air flow rate conditions for the system loss curve generation. This CFD model cannot predict the system air flow rate directly. The system air flow rate is estimated by fansystem matching between the fan pressure curve and system loss curve. The second and third approaches ignore fan blade geometry, and the governing Eqs. (1)–(3) can be simplified to steady-state ones. All above approaches are modeled under the ideal installation condition, which means there is no wall nearby. The surfaces such as unit casing and frame are modeled by “thin” surfaces, the solid volumes such as compressor, motor and fan hub are subtracted from the air flow domain. The coil is simplified to porous media zone with flow resistance definition. The volumetric heat source is also defined in this porous media zone to calculate the heat transfer between the coil and the entering air. 3. Validation of CFD approaches

Fig. 1. The small air cooled chiller outdoor unit.

Fig. 2 shows the flow path-line predicted by the three CFD approaches. Table 2 summarizes the air flow rate comparison between the CFD predictions and measurement. Table 3 shows the advantages and disadvantages comparison between three approaches.

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Table 1 Boundary conditions for the three CFD approaches. Boundary

Full grid CFD model

Inlet Outlet

Simplified model

System loss model

Pressure inlet, Gauge pressure = 0 Pa Pressure outlet, Gauge pressure = 0 Pa

Fan blade Coil zone

Same in the three models Flow rate boundary condition, define different flow rates to predict system loss for system loss curve generation Ignore, apply fan BC Ignore Porous media with flow resistance and volumetric heat source definition

Included, sliding mesh

Fig. 2. Flow path-line predicted by the three CFD approaches.

Table 2 Air flow rate comparison between predictions and test. System air flow rate (m3 /h) Test CFD model Full grid CFD model Simplified model System loss model

Deviation (%)

20,710

0

20,800 20,000 20,760

0.4 −3.4 0.2

Note that the air flow rates predicted by the three CFD approaches agree very well to the test value. However, the full grid CFD model requires the fine mesh and the unsteady-state simulation for the fan rotor modeling, which results in high computational cost and implementation cost for case building. By comparison, both the simplified model and the system loss model ignore the fan blade and therefore do not need the fine blade mesh and the

unsteady-state model. But the system loss model has to simulate several cases of different air flow rates to plot the system loss curve, and then estimates the system air flow rate by fan-system matching, as shown in Fig. 3. It shows that the system loss model cannot predict the fan system interaction and requires more CFD computational cost to estimate the condensing unit air flow rate than the simplified model. Therefore, in view of the case complexity and computational cost, the simplified model is recommended for future engineering study on the condensing unit air management CFD modeling.

Table 3 Advantages and disadvantages comparisons between CFD approaches. Full grid model Accuracy Fan system interaction Computational cost Implement cost

Simplified model

System loss model

Similar, all agree well to test Active interaction Independent High Low High High Low Low

Fig. 3. Fan-system matching chart.

Table 4 Parametric study DOE list and outdoor unit performance comparison. Case

1 2 3 4

Geometry 2A (m)

D (m)

0.6 0.6 4 4

1.5 0.6 1.5 0.6

Discharge air recirculation

Coil air entering T (◦ C)

Coil air flow rate (kg/s)

System cooling capacity (kW)

System COP

No Yes No No

35.0 42.5 35.0 35.0

6.67 6.54 6.67 6.65

77.1 70.1 77.1 77.0

2.644 2.166 2.644 2.640

Note: the coil air entering temperature values in CFD modeling are reported on a surface of 20 cm upwind of the coil to avoid the diffusion effect on air temperature.

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Fig. 4. Concept parameters and boundary condition definition.

Fig. 5. Air flow path-line of cases 2 and 3.

4. System model The system consists of the incremental tube-by-tube coil model [7] for the outdoor condensing unit and indoor fan coil units, fan curves from the suppliers, and the compressor model [8]. The system uses TXV (Thermostatic Expansion Valve) to modulate the refrigerant entering the evaporators so that the suction superheat of compressor can be controlled to the set point. Therefore, the TXV model is simply replaced by the constant suction superheat equation. The system modeling logic is similar to that described in [9]. The distributions of coil air face velocity and air entering temperature from CFD modeling can be imported to the coil model [7] and therefore reflected in the system performance modeling. 5. Case study The second CFD approach, the simplified model, is employed to study the effects of the wall–chiller distance and the chiller–chiller

distance on the total air flow rate, the discharge air recirculation and the coil air entering temperature. To save the modeling time, the periodic BC (boundary condition) is applied to represent the condition that many condensing units are installed in parallel. S is the wall–chiller distance in the no coil side of the condensing unit. It is not a design parameter and is fixed as 0.6 m for the service requirement. Wall height is defined at 4.88 m and the ambient temperature is at 35 ◦ C in all CFD cases. Fig. 4 shows the conceptual parameters and boundary conditions. The CFD simulation studied the case that there are many condensing units installed in a confined space. 2A represents the distance between condensing units. D stands for the distance between the condensing unit coil and the wall, which is a conceptual parameter. S denotes the distance between the chiller frame and the wall. Since it does not affect the coil heat transfer performance a lot, it is not a conceptual parameter. To simplify the CFD model, periodic boundary condition is used to model the condition that many condensing units work together. Fig. 4 shows the surfaces where the periodic BC is defined. The chiller system’s cooling capacity and energy efficiency are simulated using 1D system per-

Fig. 6. Air temperature profile on coil surface of cases 2 and 3.

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Fig. 7. Air velocity profile on coil surface of cases 2 and 3.

formance modeling. The system COP (coefficient of performance) of the four installation conditions are found related to the condenser total air flow rate and coil air entering temperature predicted from CFD. Table 4 shows the concepts studied and the key results. It indicates that the system air flow rate is not very sensitive to the wall–chiller distance and chiller–chiller distance. There is about 2% air flow rate reduction between the best installation condition, case 3, and the worse installation condition, case 2. However, under the worst installation condition, the recirculation of discharge air happens, which results in higher air entering temperature of the coil. The system performance modeling shows that the cooling capacity and COP in the worst case are, respectively, 9.1% and 18% lower than those in the best cases. Figs. 5–7 show the air flow path-line, the air temperature profile and the velocity profile on the coil upwind surface. Note that when discharge air recirculation happens, the coil upwind surface temperature increases dramatically, the distributions of the air temperature on the coil upwind surface become more non-uniform. Discharge air recirculation brings hot air to the condensing coil, which not only seriously affects the performance of air conditioning system, but also hurts the compressor. 6. Conclusions In this paper, three CFD modeling approaches, the full grid CFD model, the simplified model and the system loss model, are presented and compared for the study of condensing unit air management. Comparison between the CFD approaches and test data shows that all three models agree well to the test. In view of the complexity, cost and capability, the simplified CFD model has been recommended for the condensing unit air management modeling. The effect of condensing unit installation condition on the coil air entering temperature, the discharge air recirculation and the total air flow rate has been investigated using CFD for 4 cases related to

different wall–chiller distances and chiller–chiller distances. The small air cooled chiller system performance modeling is conducted by the 1D system simulation to investigate the effects of the coil air entering temperature and total air flow rate on the system COP. The study shows that the condensing unit installation condition brings little effect on air flow rate, but the bad installation condition can result in the discharge air recirculation and the coil air entering temperature rise. The worst installation condition in this study results in the 7.5 ◦ C increase of air temperature entering the coil, 9.1% cooling capacity down and 18% system COP decrease. This work provides useful information for effective ventilation in confined space as well as reliable and economic modeling approach for the small air cooled chiller air management and system performance modeling. References [1] Q. Chen, J. Srebic, Application of CFD tools for indoor and outdoor enviroment design, International Journal on Architectural Science 1 (1) (2000) 14–29. [2] T.T. Chow, Z. Lin, J.P. Liu, Effect of condensing unit layout at building reentrant on split-type air-conditioner performance, Energy and Buildings 34 (2002) 237–244. [3] T.T. Chow, Z. Lin, X.Y. Yang, Placement of condensing units of split-type airconditioners at low-rise residences, Applied Thermal Engineering 22 (2002) 1431–1444. [4] H. Xue, B. Xu, J. Wu, Y. Wei, Prediction of temperature rise near cndensing units in the confined space of a high-rise building, Builing and Environment 42 (2007) 2480–2487. [5] A. Avara, E. Daneshgar, Optimum placement of condensing units of split-type air-conditioners by numberical simulation, Energy and Buildings 40 (2008) 1268–1275. [6] Fluent (Inc.), Fluent 6.3 User’s Guide, 2006. [7] J. Liu, W.J. Wei, G.L. Ding, C.L. Zhang, M. Fukaya, K.J. Wang, T. Inagaki, A general steady state mathematical model for fin-and-tube heat exchanger based on graph theory, International Journal of Refrigeration 27 (2004) 965–973. [8] L. Yang Liang, L.X. Zhao, C.L. Zhang, B. Gu, Loss-efficiency model of single and variable-speed compressors using neural networks, International Journal of Refrigeration 32 (6) (2009) 1423–1432. [9] L.X. Zhao, L.L. Shao, C.L. Zhang, Hybrid modeling of economized screw water chillers using polynomial neural network compressor model, International Journal of Refrigeration 33 (4) (2010) 729–738.