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Indoor and Built Environment

Original Paper

Performance of a dry cooling and dedicated ventilation system under different operating conditions

Indoor and Built Environment 0(0) 1–8 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/ journalsPermissions.nav DOI: 10.1177/1420326X15574122 ibe.sagepub.com

Hua Chen1, Wai Ling Lee2 and Ai-Xia Wu1

Abstract Effectiveness of dry cooling and dedicated ventilation (DCDV) system for decoupling dehumidification from cooling to achieve the desired indoor condition and condensate-free objectives for air-conditioning of office environments in Hong Kong has been confirmed in previous simulation and experimental studies by the authors. However, our previous studies assumed a constant outdoor air and chilled water flow rates, and this is not always the case in practice. Whether this assumption could affect the effectiveness of DCDV system is the subject of present investigation. A prototype that could enable the variation of outdoor air and chilled water flow rates, as well as indoor and outdoor conditions, was set up for laboratory experiments. Our results have illustrated the effectiveness of DCDV system in achieving the intended condensate-free objective which was most affected by the spacesensible heat ratio and chilled water flow rate. Little influence was found to be introduced by the outdoor air flow rate and outdoor air conditions. The results, through sensitivity and statistical analysis, were found consistent with results of our previous studies.

Keywords Dry cooling, Dedicated ventilation, Variable outdoor air flow rate, Variable chilled water flow rate, Performance analysis Accepted: 27 January 2015

Introduction Recent research advocates the use of dry cooling (DC) and dedicated ventilation (DV) air-conditioning systems for decoupling dehumidiﬁcation from cooling to achieve a condensate-free indoor environment for a better indoor environmental quality and energy eﬃciency in buildings. Condensate-free is achieved by the use of a DV coil to produce dry and cooled outdoor air which deals with the latent load and some of the space-sensible load, and a DC coil to treat the remaining space-sensible load. Energy saving is derived from chiller energy and pumping energy reductions. The eﬀectiveness of a DCDV system for air-conditioning of oﬃce environments in Hong Kong has been investigated by means of simulation and experimental studies by the authors.1–5 The results revealed that the use of DCDV system has led to attainment of desirable indoor relative humidities (between 50% and 60%). The

annual energy use could be reduced by 54% in comparison with constant air volume (CAV) systems with reheat.1 Condensation on the DC coil, however, can occur under some circumstances. To minimize condensation risk during the design of DCDV systems, parametric studies were performed to identify the factors aﬀecting the annualized cumulative frequency of condensation occurrences (ConHR). A simpliﬁed model 1 Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of commerce, Tianjin, China 2 Department of Building Services Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Corresponding author: Wai Ling Lee, Department of Building Services Engineering, The Hong Kong Polytechnic University, PolyU, Hong Kong, Hong Kong. Email: [email protected]

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relating ConHR to four inﬂuential factors was formulated, oﬀering a convenient way to determine the design conditions in minimizing condensation risk.2,3 To consider whether or not the beneﬁts of DCDV systems could be realized in practice, experimental veriﬁcations were also undertaken.4 In the experimental study, a prototype which could be switched between DCDV system mode and the conventional system mode was constructed. Two sets of identical experiments under various cooling load conditions revealed that DCDV system was slightly better in achieving the desired indoor condition and the condensate-free objective. As for the overall system coeﬃcient of performance (COP), the DCDV system was illustrated to be 5.6% to 7.2% more eﬃcient. To further achieve a completely condensate-free indoor environment, diﬀerent system operation strategies were then investigated. The results indicated that a completely condensate-free DC coil could only be achieved if the DCDV system was either continuously or semi-continuously operated.5 The above no doubt revealed that DCDV system is more energy-eﬃcient than the conventional air-conditioning system. These studies assumed a constant outdoor air ﬂow rate (moa) and chilled water ﬂow rate (mcw), which is not always the case due to a change in cooling demand6 or the incorporation of variable ﬂow constant temperature control system.7 Whether DCDV system is still eﬀective in achieving a condensate-free indoor environment under constant chilled water temperature condition is subject to further experimental investigations. Besides variable moa and mcw conditions, the eﬀectiveness of DCDV system in achieving the condensatefree objective is also aﬀected by the indoor and outdoor conditions but their inﬂuence are always considered in isolation. Therefore, their interactive inﬂuence with variable ﬂow conditions has not been addressed. In this study, Pearson correlation analysis8 was used to evaluate the interactive inﬂuences amongst diﬀerent operating parameters, and regression analysis was employed to identify the most inﬂuential operating parameter.9 Given that the characteristics of the DCDV system, the experimental setup, the experimental conditions, and the measurement details have been described in the earlier studies,4 to avoid duplication, only contents that are essential for illustrating the details of this study are presented in this paper.

System descriptions and experimental set-up Figure 1 shows the system conﬁguration of the DCDV system, illustrating that a primary air-handling unit (PAU), serving as a DV coil, was used to cool and

dehumidify the outdoor air from state 0 to state 2. The treated outdoor air was subsequently mixed with the re-circulated air sensibly cooled by the air-handling unit (AHU) (state 3) serving as a DC coil to become the supply air (state 4). In this system, the treated dried and cooled outdoor air was used to oﬀset all the latent load and part of the space-sensible load, whilst the re-circulated air of variable temperature was used to treat only the remaining space-sensible load to achieve the desired indoor condition (state 1). On the water side, to avoid condensation, the DV and DC coils were connected in series such that chilled water leaving the DV coil can successively enter the DC coil, resulting in a higher chilled water temperature diﬀerential of 9 C and a proportionally lower chilled water ﬂow rate. Figure 2 shows the air-side schematic of the experimental setup. There are two chambers. Each chamber was provided with a built-in system that consists of a water-cooled variable speed chiller and a sensible heat and moisture load generation units (LGUs). A proportional-integral-derivative (PID) control system was used to adjust the outputs of the LGUs for maintaining the temperature and humidity in each chamber at a preset condition. The PAU and AHU fans were separately provided with a variable speed drive (VSD) to enable variation of outdoor and re-circulated air ﬂow rate ratios. Figure 3 shows the water-side schematic of the experimental setup. An air-cooled constant temperature water chiller was used to generate chilled water at constant temperature (7 C) to the PAU and successively to the AHU. Chilled water ﬂow rate was modulated by the use of a variable speed circulation pump.

Experimental conditions and procedures The experimental conditions are summarized in Table 1. These were set identical to our previous works1–5 as far as possible to enable direct comparison, except for moa and mcw. Two diﬀerent sets of values were assumed. They were determined based on an outdoor air ﬂow rate of 0.007 m3/s per person and 0.01 m3/s per person according to diﬀerent design recommendations.10,11 The two chilled water ﬂow rates were determined based on the corresponding cooling demands. The indoor chamber was assumed at full load condition but with variable space-sensible heat ratio (SHR); whilst for the outdoor chamber, diﬀerent temperatures and relative humidities were assumed to simulate the varying outdoor conditions. The range of outdoor temperatures (to ¼ 25 to 33 C) was the outdoor temperature range in Hong Kong during the season when air-conditioning was used (April to October).12

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Figure 1. Configuration and psychrometric process of the dry cooling and dedicated ventilation (DCDV) system. (a) System configuration (PAU: primary air-handling unit; AHU: air handling unit). (b) Psychrometric process.

Table 1 indicates that there were altogether 24 sets of experimental conditions for the two moa values but were reduced to 16 sets for the two mcw values. Smaller number of experimental conditions for variable mcw was due to the fact that higher mcw was needed only for extreme outdoor conditions (to ¼ 33 C).

For each experimental condition, the indoor and outdoor chambers were ﬁrst conditioned to the design conditions (Table 1) by the built-in air-conditioning system. Upon the achievement of the design conditions, the DCDV system was operated to remove sensible heat and moisture generated by the LGUs inside the

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Figure 2. Air-side system of the experimental setup (T1: dry bulb temperature sensor; H1: wet bulb temperature sensor; SP: static pressure transducer; F1: thermal anemometer; VSD: variable speed drive; DP: differential pressure transducer; SD: sampling device; PDM: pressure control damper; LGUs: load generation units).

Figure 3. Water-side system of the experimental setup (T2: temperature sensor; F2: turbine flow meter).

indoor chamber. The outputs of the LGUs were adjusted according to the pre-determined space SHRs. During the experiments, all temperature and ﬂow rate measurements were automatically taken every 5 seconds and

averaged every 1 minute until the thermal condition in the indoor chamber had reached a steady state condition. Table 2 summarizes details and accuracies of the measuring instruments and devices.

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Table 1. System design parameters and experimental conditions. Conditions

Abbrev

Controlled range

No. of cases (remarks)

Constant parameters

Temperature Relative humidity Space cooling load Supply air flow rate Entering chilled water temperature

ti ’i Qsp msa tcwe

24 C 50% 2.1 kW (full load) 600 m3/h 7 C

1

Varied parameters

Outdoor chamber Sensible heat ratio Outdoor air flow rate

to ’o SHR moa

25 C; 29 C; 33 C 50%; 65% 0.7; 0.85 100 m3/h; 143 m3/h

Chilled water flow rate

mcw

0.09 kg/s; 0.135 kg/s

3 2 2 2 (mcw at 20.09 kg/s) 2 (moa at 100 m3/h and to at 33 C)

Indoor chamber

Temperature Relative humidity

Table 2. Accuracy and performance standard of major instruments. Measured Parameter

Instrument

Range

Accuracy and performance standard

Dry bulb temperature

Platinum resistance thermometer (RTD)

50 to 100 C

0.1 C

Wet bulb temperature Average space air temperature

Tree and aspirating psychrometer

50 to 100 C

Supply air flow rate Outdoor air flow rate

Thermal anemometer Air flow rate measuring apparatus

0 to 5 m/s

Chilled water flow rate

Turbine flow meter

0 to 3 m3/h

0.1 C ASHRAE 41.1 [14] 2% 0.1 C ISO 5151 [15] ASHRAE 41.2 [16] 2%

Air humidities (relative humidity and moisture content), which cannot be directly measured, were calculated based on the measured dry bulb and wet bulb temperatures by equations (1) to (4) w¼

ð2501 2:326t Þws 1:006ðt t Þ 2501 þ 1:86t 4:186t

ð1Þ

pa w 0:622 þ w

ð2Þ

pw ¼

temperature; ws* is the saturation moisture content at t*; pw is the partial pressure of water vapour; pa is the atmospheric pressure; pw,s is the saturation pressure of water vapour; T is the dry bulb temperature in Kelvin and ’ is the relative humidity. The uncertainty due to measurement errors in the calculation of relative humidity (equations (1) to (4)) was estimated to be 1.32%. The estimation was based on the single-sample uncertainty analysis method.13

ln pw,s ¼ ð5:800E þ 03Þ=T þ ð1:391E þ 00Þ þ ð4:864E 02ÞT þ ð4:176E 05ÞT2

Results and discussions

þ ð1:445E 08ÞT3 þ ð6:546E þ 00Þln T ð3Þ pw ’¼ p

ð4Þ

w,s t,p

where w is the moisture content; t is the measured dry bulb temperature; t* is the measured wet bulb

The essential characteristics of DCDV system are (1) to achieve the desired indoor condition and (2) to provide a condensate-free indoor environment, thus the focus of this study is to evaluate the resultant indoor condition and the condensation risk under the interactive inﬂuence of variable moa and mcw at diﬀerent SHR and outdoor conditions.

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However, in view of the vast amount of experimental data collected, the average values for each experimental condition (Table 3) were calculated for the analysis.

Resultant indoor condition As the indoor temperature was controlled and thus the desired indoor temperature can basically be achieved; the focus was therefore on the resultant indoor relative humidity (’i).

Influence of moa. Pearson correlation analysis was adopted to examine the correlations of the resultant ’i with moa, SHR, and outdoor air condition. The outdoor air condition is represented by the outdoor air enthalpy (Eo, kJ/kg), which was calculated based on the air condition (Table 1, temperature and relative humidity) at the outdoor chamber. The results show that the resultant ’i relates strongly with SHR (correlation coefﬁcient ¼ 0.911), but not with Eo and moa. Results are summarized in Table 4. The results are considered reasonable because relative humidity is subject to the extent of space latent load (Ql). Ql can be represented by other parameters as shown in equation (5) Ql ¼ ðQo þ Qsp Þ ð1 SHRÞ

ð5Þ

where Ql is the space latent load; Qo is the outdoor air total load subject to changes in Eo and moa (average for all experimental conditions ¼ 0.55 kW); and Qsp the space total load which is maintained constant (¼2.1 kW). By conducting partial derivatives of equation (5) with respect to Qo and SHR, the change in Ql with respect to changes in Qo, SHR, and mcw can be determined by equations (6) and (7) @Ql ¼ 1 SHR @Qo

ð6Þ

@Ql ¼ ðQo þ Qsp Þ @SHR

ð7Þ

Considering that to achieve little change in Ql so as to maintain a fairly constant ’i, equations (6) and (7) should tend to become zero as shown in equation (8) @Ql @Ql 0 and @Qo @SHR

Table 3. Experimental results. Eo (kJ/kg)

’i (%)

SHR air flow 0.85 0.85 0.85 0.85 0.85 0.85 0.7 0.7 0.7 0.7 0.7 0.7 0.85 0.85 0.85 0.85 0.85 0.85 0.7 0.7 0.7 0.7 0.7 0.7 0.7

moa (m3/h) rate (moa) 100 100 100 100 100 100 100 100 100 100 100 100 143 143 143 143 143 143 143 143 143 143 143 143 100

(a) Variation 87.15 74.41 71.72 61.73 58.51 50.71 87.15 74.41 71.72 61.73 58.51 50.71 87.15 74.41 71.72 61.73 58.51 50.71 87.15 74.41 71.72 61.73 58.51 50.71 74.41

of outdoor 53.9 54.4 54.8 54.2 54.6 54.2 62.9 62.3 63 62 63.4 62.7 58.5 55.3 53.9 49.5 52.6 50.4 65.5 63.5 65.7 59.6 64 61.9 62.3

(b) Variation 74.41 74.41 74.41 74.41 74.41 74.41 74.41 87.15 87.15 87.15 87.15 87.15 87.15 87.15 87.15

of chilled water flow rate (mcw) 60.7 0.7 100 63.5 0.7 143 62.6 0.7 143 54.4 0.85 100 53.4 0.85 100 55.3 0.85 143 51.3 0.85 143 62.9 0.7 100 60.2 0.7 100 65.5 0.7 143 61.1 0.7 143 53.9 0.85 100 53 0.85 100 58.5 0.85 143 48.9 0.85 143

mcw (kg/s) 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135

ð8Þ

To solve equation (8), the SHR should tend to become 1. The resultant ’i is dominated by a change in SHR but not Eo and moa can thus be wellexplained.

SHR: space-sensible heat ratio.

Influence of mcw. The root-mean-square error (RMSE) was used to quantify the deviation of the resultant ’i from the desired value (50%) under the two mcw values. A higher level of deviation can be

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Most influential parameter. Both SHR and

Table 4. Correlations of the studied parameters. Eo Eo Pearson correlation 1 Sig. (2-tailed) N 24

’i

SHR

moa

0.095 0.561 24

0.000 1.000 24

0.000 1.000 24

’i Pearson correlation 0.095 Sig. (2-tailed) 0.561 N 24

1

0.911** 0.020 0.000 0.904 24 24

24

SHR Pearson correlation 0.000 0.911** Sig. (2-tailed) 1.000 0.000 N 24 24

24

moa Pearson correlation 0.000 Sig. (2-tailed) 1.000 N 24

0.000 1.000 24

0.020 0.904 24

1

0.000 1.000 24

’i ¼ 109:942 60:1 SHR 51:597 mcw

1 24

N: the number of test samples; SHR: space-sensible heat ratio. Notes: Sig. (2-tailed) – those flagged with two asterisks (**) are of significant correlations at 0.01 significance level (2- tailed is the top 5% or bottom 5% of its probability distribution).

reﬂected by a larger RMSE. RMSE is calculated by equation (9)

RMSE ¼

ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ sX n ð’x ’d Þ2 x¼1 n

mcw can exert a certain level of inﬂuence on the resultant ’i as was outlined by discussion of equation (10) above. For identifying the more inﬂuential parameter, regression analysis was conducted. The two parameters aﬀecting the resultant ’i were assumed to be independent variables for inclusion into a regression model. Linear regression analysis was conducted using the statistical package SPSS.9 The standardized coeﬃcients are used to reﬂect the level of signiﬁcance. A higher value indicates an increase in signiﬁcance. A negative coeﬃcient indicates that the resultant ’i decreases with an increase in the variable, and vice versa. The model constructed by regression analysis can be represented by equation (11)

ð9Þ

where the ’x is the resultant indoor relative humidity for xth experimental condition and ’d is the design indoor relative humidity equal to 50%. The calculated RMSE indicates that regardless of changes in moa, SHR and Eo, RMSE is smaller for a higher mcw (2.86% as opposed to 3.70%). This is considered reasonable because dehumidiﬁcation is responsible by the DV coil, which is subject to its performance as shown in equation (10) ðQo þ Qsp,dv Þ ¼ mcw ðtcwr,dv tcwe Þ ð1 SHRdv Þ ð10Þ where Qo is the outdoor air total load; Qsp,dv is the space-sensible load handled by the DV coil, tcwr,dv is the return chilled water temperature at the DV coil which is a variable; tcwe is the entering chilled water temperature which is maintained at 7 C, and SHRdv is the sensible heat ratio of the DV coil. From equation (10), with an increase in mcw, tcw,dv would tend to decrease to enhance the dehumidiﬁcation performance of the DV coil and thus can better maintain the desired ’i.

ð11Þ

It has a coeﬃcient of determination (r2) of 0.866 to conﬁrm the inﬂuence of the two parameters on the resultant ’i.14 The standardized coeﬃcients determined by regression analysis indicate that SHR would introduce a higher inﬂuence on the resultant ’i than mcw. Their coeﬃcients are 0.911 and 0.188, respectively. The negative signs are judged to be reasonable.

Condensation risk Based on the experimental results, whether there was condensation on the DC coil was determined by checking the discrepancy in moisture content between the recirculated air (Figure 2: state 1) and treated DC air (Figure 2: state 3). Upon ascertaining the presence or absence of condensation as dependent variable for each experimental condition, other studied parameters including moa, mcw, SHR and Eo, aﬀecting the condensation risk (ConR) on the DC coil were assumed to be independent variables for inclusion into a regression model. Linear regression analysis was again used to determine the standardized coeﬃcients. The presence or absence of condensation is a qualitative variable. To deal with this, the dummy variable method was adopted to assign the value 0 or 1 to indicate the presence or absence of condensation on the DC coil. The model constructed by regression analysis is as represented by equation (12) below ConR ¼ 5:175 5:556 SHR 2:803 mcw þ 0:00001 Eo ð12Þ A coeﬃcient of determination (r2) of 0.729 would conﬁrm the inﬂuence of the studied parameters on ConR. Among all studied parameters, SHR has the

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highest standardized coeﬃcient of 0.845, followed by mcw (0.121) and Eo (0.003). moa would pose no inﬂuence on the condensation risk. The negative sign for SHR and mcw, and the positive sign for Eo, as discussed in the previous sections, are again judged to be reasonable. The previous study5 has identiﬁed that the condensation risk on the DC coil is strongly related to the indoor t and t* (represented by ’ as t is a constant), Pearson correlation analysis was again employed to review the correlation between the resultant ’i and the presence or absence of condensation for each experimental condition. The correlation coeﬃcient was found to be 0.808; therefore indicating that the correlation was signiﬁcant at the 0.01 level (2-tailed test as explained in Table 4) and thus conﬁrming consistent result has been achieved in comparison with our previous study.5

Conclusions In order to evaluate the performance of DCDV system when applied under diﬀerent outdoor air ﬂow rate (moa) and chilled water ﬂow rate conditions (mcw), as well as variable SHR and outdoor air enthalpy (Eo) conditions, a prototype was set-up for experimental studies. The experimental results showed that the eﬀectiveness of DCDV system in achieving the desired indoor condition, and providing a condensate-free indoor environment, was most aﬀected by the space SHR and mcw. The parameters, moa and Eo, were found to pose no or little inﬂuence. The results, through sensitivity and statistical analysis, were found consistent with results of previous studies based on simulations and experimental studies. Authors’ contribution All authors contributed equally in the preparation of this manuscript.

Declaration of conflicting interests

Funding This work was supported by Hong Kong Research Grants Council General Research Fund No. 522709.

References 1. Lee WL, Chen H, Leung YC and Zhang Y. Decoupling dehumidification and cooling for energy saving and desirable space air conditions in hot and humid Hong Kong. Energ Convers Manage 2012; 53: 230–239. 2. Chen Hua and Lee WL. Application of condensate-free dry coils for energy-saving and analysis on indoor air quality in Hong Kong. Building Sci 2011; 27: Apr No. 4. 3. Jia Jie and Lee WL. Energy performance and condensation risk of DCDV system in subtropical Hong Kong. Trans Tianjin Univ 2014; 20: 042–047. 4. Jia Jie and Lee WL. Experimental study of performance of a dry cooling and dedicated ventilation (DCDV) system under different space cooling load conditions. Energ Convers Manage 2013; 3: 158–166. 5. Jia Jia and Lee WL. Condensation risk of DCDV system for hot and humid Hong Kong. Indoor Built Environ 2014; 23(6): 814–822. 6. Huang WZ, Zaheeruddin M and Cho SH. Dynamic simulation of energy management control functions for HVAC systems in buildings. Energ Convers Manage 2006; 47: 926–943. 7. Yu FW and Chan KT. Improved energy performance of air cooled centrifugal chillers with variable chilled water flow. Energ Convers Manage 2008; 49: 1595–1611. 8. Anonymous. Pearson product-moment correlation coefficient. Wikipedia 2014, http://en.wikipedia.org/wiki/Pearson_productmoment_correlation_coefficient (accessed 27 January 2015). 9. SPSS: IBM SPSS Statistics. Version 22. IBM Corp USA; 2013. 10. EMSD. Code of practice for energy efficiency of building services installations in building. 2012 ed. Hong Kong: Electrical & Mechanical Services Department, 2012. 11. ANSI: ASHRAE Standard 62.1-2013.Ventilation Standard for acceptable indoor air quality. Atlanta: American Society of Heating Refrigerating and Air-Conditioning Engineers, 2013. 12. Lam JC, Tsang CL and Li DHW. Long term ambient temperature analysis and energy use implications in Hong Kong. Energ Convers Manage 2004; 45: 315–327. 13. Moffat RJ. Describing uncertainties in experimental results. Exp Therm Fluid Sci 1988; 1: 3–17. 14. Milton JS and Arnold SC. Probability and statistics in the engineering and computing sciences. Singapore: McGraw-Hill International Editions, 1987.

The authors declared no potential conﬂicts of interest with respect to the research, authorship, and/or publication of this article.

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Indoor and Built Environment

Original Paper

Performance of a dry cooling and dedicated ventilation system under different operating conditions

Indoor and Built Environment 0(0) 1–8 ! The Author(s) 2015 Reprints and permissions: sagepub.co.uk/ journalsPermissions.nav DOI: 10.1177/1420326X15574122 ibe.sagepub.com

Hua Chen1, Wai Ling Lee2 and Ai-Xia Wu1

Abstract Effectiveness of dry cooling and dedicated ventilation (DCDV) system for decoupling dehumidification from cooling to achieve the desired indoor condition and condensate-free objectives for air-conditioning of office environments in Hong Kong has been confirmed in previous simulation and experimental studies by the authors. However, our previous studies assumed a constant outdoor air and chilled water flow rates, and this is not always the case in practice. Whether this assumption could affect the effectiveness of DCDV system is the subject of present investigation. A prototype that could enable the variation of outdoor air and chilled water flow rates, as well as indoor and outdoor conditions, was set up for laboratory experiments. Our results have illustrated the effectiveness of DCDV system in achieving the intended condensate-free objective which was most affected by the spacesensible heat ratio and chilled water flow rate. Little influence was found to be introduced by the outdoor air flow rate and outdoor air conditions. The results, through sensitivity and statistical analysis, were found consistent with results of our previous studies.

Keywords Dry cooling, Dedicated ventilation, Variable outdoor air flow rate, Variable chilled water flow rate, Performance analysis Accepted: 27 January 2015

Introduction Recent research advocates the use of dry cooling (DC) and dedicated ventilation (DV) air-conditioning systems for decoupling dehumidiﬁcation from cooling to achieve a condensate-free indoor environment for a better indoor environmental quality and energy eﬃciency in buildings. Condensate-free is achieved by the use of a DV coil to produce dry and cooled outdoor air which deals with the latent load and some of the space-sensible load, and a DC coil to treat the remaining space-sensible load. Energy saving is derived from chiller energy and pumping energy reductions. The eﬀectiveness of a DCDV system for air-conditioning of oﬃce environments in Hong Kong has been investigated by means of simulation and experimental studies by the authors.1–5 The results revealed that the use of DCDV system has led to attainment of desirable indoor relative humidities (between 50% and 60%). The

annual energy use could be reduced by 54% in comparison with constant air volume (CAV) systems with reheat.1 Condensation on the DC coil, however, can occur under some circumstances. To minimize condensation risk during the design of DCDV systems, parametric studies were performed to identify the factors aﬀecting the annualized cumulative frequency of condensation occurrences (ConHR). A simpliﬁed model 1 Tianjin Key Laboratory of Refrigeration Technology, Tianjin University of commerce, Tianjin, China 2 Department of Building Services Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Corresponding author: Wai Ling Lee, Department of Building Services Engineering, The Hong Kong Polytechnic University, PolyU, Hong Kong, Hong Kong. Email: [email protected]

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relating ConHR to four inﬂuential factors was formulated, oﬀering a convenient way to determine the design conditions in minimizing condensation risk.2,3 To consider whether or not the beneﬁts of DCDV systems could be realized in practice, experimental veriﬁcations were also undertaken.4 In the experimental study, a prototype which could be switched between DCDV system mode and the conventional system mode was constructed. Two sets of identical experiments under various cooling load conditions revealed that DCDV system was slightly better in achieving the desired indoor condition and the condensate-free objective. As for the overall system coeﬃcient of performance (COP), the DCDV system was illustrated to be 5.6% to 7.2% more eﬃcient. To further achieve a completely condensate-free indoor environment, diﬀerent system operation strategies were then investigated. The results indicated that a completely condensate-free DC coil could only be achieved if the DCDV system was either continuously or semi-continuously operated.5 The above no doubt revealed that DCDV system is more energy-eﬃcient than the conventional air-conditioning system. These studies assumed a constant outdoor air ﬂow rate (moa) and chilled water ﬂow rate (mcw), which is not always the case due to a change in cooling demand6 or the incorporation of variable ﬂow constant temperature control system.7 Whether DCDV system is still eﬀective in achieving a condensate-free indoor environment under constant chilled water temperature condition is subject to further experimental investigations. Besides variable moa and mcw conditions, the eﬀectiveness of DCDV system in achieving the condensatefree objective is also aﬀected by the indoor and outdoor conditions but their inﬂuence are always considered in isolation. Therefore, their interactive inﬂuence with variable ﬂow conditions has not been addressed. In this study, Pearson correlation analysis8 was used to evaluate the interactive inﬂuences amongst diﬀerent operating parameters, and regression analysis was employed to identify the most inﬂuential operating parameter.9 Given that the characteristics of the DCDV system, the experimental setup, the experimental conditions, and the measurement details have been described in the earlier studies,4 to avoid duplication, only contents that are essential for illustrating the details of this study are presented in this paper.

System descriptions and experimental set-up Figure 1 shows the system conﬁguration of the DCDV system, illustrating that a primary air-handling unit (PAU), serving as a DV coil, was used to cool and

dehumidify the outdoor air from state 0 to state 2. The treated outdoor air was subsequently mixed with the re-circulated air sensibly cooled by the air-handling unit (AHU) (state 3) serving as a DC coil to become the supply air (state 4). In this system, the treated dried and cooled outdoor air was used to oﬀset all the latent load and part of the space-sensible load, whilst the re-circulated air of variable temperature was used to treat only the remaining space-sensible load to achieve the desired indoor condition (state 1). On the water side, to avoid condensation, the DV and DC coils were connected in series such that chilled water leaving the DV coil can successively enter the DC coil, resulting in a higher chilled water temperature diﬀerential of 9 C and a proportionally lower chilled water ﬂow rate. Figure 2 shows the air-side schematic of the experimental setup. There are two chambers. Each chamber was provided with a built-in system that consists of a water-cooled variable speed chiller and a sensible heat and moisture load generation units (LGUs). A proportional-integral-derivative (PID) control system was used to adjust the outputs of the LGUs for maintaining the temperature and humidity in each chamber at a preset condition. The PAU and AHU fans were separately provided with a variable speed drive (VSD) to enable variation of outdoor and re-circulated air ﬂow rate ratios. Figure 3 shows the water-side schematic of the experimental setup. An air-cooled constant temperature water chiller was used to generate chilled water at constant temperature (7 C) to the PAU and successively to the AHU. Chilled water ﬂow rate was modulated by the use of a variable speed circulation pump.

Experimental conditions and procedures The experimental conditions are summarized in Table 1. These were set identical to our previous works1–5 as far as possible to enable direct comparison, except for moa and mcw. Two diﬀerent sets of values were assumed. They were determined based on an outdoor air ﬂow rate of 0.007 m3/s per person and 0.01 m3/s per person according to diﬀerent design recommendations.10,11 The two chilled water ﬂow rates were determined based on the corresponding cooling demands. The indoor chamber was assumed at full load condition but with variable space-sensible heat ratio (SHR); whilst for the outdoor chamber, diﬀerent temperatures and relative humidities were assumed to simulate the varying outdoor conditions. The range of outdoor temperatures (to ¼ 25 to 33 C) was the outdoor temperature range in Hong Kong during the season when air-conditioning was used (April to October).12

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Figure 1. Configuration and psychrometric process of the dry cooling and dedicated ventilation (DCDV) system. (a) System configuration (PAU: primary air-handling unit; AHU: air handling unit). (b) Psychrometric process.

Table 1 indicates that there were altogether 24 sets of experimental conditions for the two moa values but were reduced to 16 sets for the two mcw values. Smaller number of experimental conditions for variable mcw was due to the fact that higher mcw was needed only for extreme outdoor conditions (to ¼ 33 C).

For each experimental condition, the indoor and outdoor chambers were ﬁrst conditioned to the design conditions (Table 1) by the built-in air-conditioning system. Upon the achievement of the design conditions, the DCDV system was operated to remove sensible heat and moisture generated by the LGUs inside the

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Figure 2. Air-side system of the experimental setup (T1: dry bulb temperature sensor; H1: wet bulb temperature sensor; SP: static pressure transducer; F1: thermal anemometer; VSD: variable speed drive; DP: differential pressure transducer; SD: sampling device; PDM: pressure control damper; LGUs: load generation units).

Figure 3. Water-side system of the experimental setup (T2: temperature sensor; F2: turbine flow meter).

indoor chamber. The outputs of the LGUs were adjusted according to the pre-determined space SHRs. During the experiments, all temperature and ﬂow rate measurements were automatically taken every 5 seconds and

averaged every 1 minute until the thermal condition in the indoor chamber had reached a steady state condition. Table 2 summarizes details and accuracies of the measuring instruments and devices.

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Table 1. System design parameters and experimental conditions. Conditions

Abbrev

Controlled range

No. of cases (remarks)

Constant parameters

Temperature Relative humidity Space cooling load Supply air flow rate Entering chilled water temperature

ti ’i Qsp msa tcwe

24 C 50% 2.1 kW (full load) 600 m3/h 7 C

1

Varied parameters

Outdoor chamber Sensible heat ratio Outdoor air flow rate

to ’o SHR moa

25 C; 29 C; 33 C 50%; 65% 0.7; 0.85 100 m3/h; 143 m3/h

Chilled water flow rate

mcw

0.09 kg/s; 0.135 kg/s

3 2 2 2 (mcw at 20.09 kg/s) 2 (moa at 100 m3/h and to at 33 C)

Indoor chamber

Temperature Relative humidity

Table 2. Accuracy and performance standard of major instruments. Measured Parameter

Instrument

Range

Accuracy and performance standard

Dry bulb temperature

Platinum resistance thermometer (RTD)

50 to 100 C

0.1 C

Wet bulb temperature Average space air temperature

Tree and aspirating psychrometer

50 to 100 C

Supply air flow rate Outdoor air flow rate

Thermal anemometer Air flow rate measuring apparatus

0 to 5 m/s

Chilled water flow rate

Turbine flow meter

0 to 3 m3/h

0.1 C ASHRAE 41.1 [14] 2% 0.1 C ISO 5151 [15] ASHRAE 41.2 [16] 2%

Air humidities (relative humidity and moisture content), which cannot be directly measured, were calculated based on the measured dry bulb and wet bulb temperatures by equations (1) to (4) w¼

ð2501 2:326t Þws 1:006ðt t Þ 2501 þ 1:86t 4:186t

ð1Þ

pa w 0:622 þ w

ð2Þ

pw ¼

temperature; ws* is the saturation moisture content at t*; pw is the partial pressure of water vapour; pa is the atmospheric pressure; pw,s is the saturation pressure of water vapour; T is the dry bulb temperature in Kelvin and ’ is the relative humidity. The uncertainty due to measurement errors in the calculation of relative humidity (equations (1) to (4)) was estimated to be 1.32%. The estimation was based on the single-sample uncertainty analysis method.13

ln pw,s ¼ ð5:800E þ 03Þ=T þ ð1:391E þ 00Þ þ ð4:864E 02ÞT þ ð4:176E 05ÞT2

Results and discussions

þ ð1:445E 08ÞT3 þ ð6:546E þ 00Þln T ð3Þ pw ’¼ p

ð4Þ

w,s t,p

where w is the moisture content; t is the measured dry bulb temperature; t* is the measured wet bulb

The essential characteristics of DCDV system are (1) to achieve the desired indoor condition and (2) to provide a condensate-free indoor environment, thus the focus of this study is to evaluate the resultant indoor condition and the condensation risk under the interactive inﬂuence of variable moa and mcw at diﬀerent SHR and outdoor conditions.

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However, in view of the vast amount of experimental data collected, the average values for each experimental condition (Table 3) were calculated for the analysis.

Resultant indoor condition As the indoor temperature was controlled and thus the desired indoor temperature can basically be achieved; the focus was therefore on the resultant indoor relative humidity (’i).

Influence of moa. Pearson correlation analysis was adopted to examine the correlations of the resultant ’i with moa, SHR, and outdoor air condition. The outdoor air condition is represented by the outdoor air enthalpy (Eo, kJ/kg), which was calculated based on the air condition (Table 1, temperature and relative humidity) at the outdoor chamber. The results show that the resultant ’i relates strongly with SHR (correlation coefﬁcient ¼ 0.911), but not with Eo and moa. Results are summarized in Table 4. The results are considered reasonable because relative humidity is subject to the extent of space latent load (Ql). Ql can be represented by other parameters as shown in equation (5) Ql ¼ ðQo þ Qsp Þ ð1 SHRÞ

ð5Þ

where Ql is the space latent load; Qo is the outdoor air total load subject to changes in Eo and moa (average for all experimental conditions ¼ 0.55 kW); and Qsp the space total load which is maintained constant (¼2.1 kW). By conducting partial derivatives of equation (5) with respect to Qo and SHR, the change in Ql with respect to changes in Qo, SHR, and mcw can be determined by equations (6) and (7) @Ql ¼ 1 SHR @Qo

ð6Þ

@Ql ¼ ðQo þ Qsp Þ @SHR

ð7Þ

Considering that to achieve little change in Ql so as to maintain a fairly constant ’i, equations (6) and (7) should tend to become zero as shown in equation (8) @Ql @Ql 0 and @Qo @SHR

Table 3. Experimental results. Eo (kJ/kg)

’i (%)

SHR air flow 0.85 0.85 0.85 0.85 0.85 0.85 0.7 0.7 0.7 0.7 0.7 0.7 0.85 0.85 0.85 0.85 0.85 0.85 0.7 0.7 0.7 0.7 0.7 0.7 0.7

moa (m3/h) rate (moa) 100 100 100 100 100 100 100 100 100 100 100 100 143 143 143 143 143 143 143 143 143 143 143 143 100

(a) Variation 87.15 74.41 71.72 61.73 58.51 50.71 87.15 74.41 71.72 61.73 58.51 50.71 87.15 74.41 71.72 61.73 58.51 50.71 87.15 74.41 71.72 61.73 58.51 50.71 74.41

of outdoor 53.9 54.4 54.8 54.2 54.6 54.2 62.9 62.3 63 62 63.4 62.7 58.5 55.3 53.9 49.5 52.6 50.4 65.5 63.5 65.7 59.6 64 61.9 62.3

(b) Variation 74.41 74.41 74.41 74.41 74.41 74.41 74.41 87.15 87.15 87.15 87.15 87.15 87.15 87.15 87.15

of chilled water flow rate (mcw) 60.7 0.7 100 63.5 0.7 143 62.6 0.7 143 54.4 0.85 100 53.4 0.85 100 55.3 0.85 143 51.3 0.85 143 62.9 0.7 100 60.2 0.7 100 65.5 0.7 143 61.1 0.7 143 53.9 0.85 100 53 0.85 100 58.5 0.85 143 48.9 0.85 143

mcw (kg/s) 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135 0.09 0.135

ð8Þ

To solve equation (8), the SHR should tend to become 1. The resultant ’i is dominated by a change in SHR but not Eo and moa can thus be wellexplained.

SHR: space-sensible heat ratio.

Influence of mcw. The root-mean-square error (RMSE) was used to quantify the deviation of the resultant ’i from the desired value (50%) under the two mcw values. A higher level of deviation can be

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Most influential parameter. Both SHR and

Table 4. Correlations of the studied parameters. Eo Eo Pearson correlation 1 Sig. (2-tailed) N 24

’i

SHR

moa

0.095 0.561 24

0.000 1.000 24

0.000 1.000 24

’i Pearson correlation 0.095 Sig. (2-tailed) 0.561 N 24

1

0.911** 0.020 0.000 0.904 24 24

24

SHR Pearson correlation 0.000 0.911** Sig. (2-tailed) 1.000 0.000 N 24 24

24

moa Pearson correlation 0.000 Sig. (2-tailed) 1.000 N 24

0.000 1.000 24

0.020 0.904 24

1

0.000 1.000 24

’i ¼ 109:942 60:1 SHR 51:597 mcw

1 24

N: the number of test samples; SHR: space-sensible heat ratio. Notes: Sig. (2-tailed) – those flagged with two asterisks (**) are of significant correlations at 0.01 significance level (2- tailed is the top 5% or bottom 5% of its probability distribution).

reﬂected by a larger RMSE. RMSE is calculated by equation (9)

RMSE ¼

ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ sX n ð’x ’d Þ2 x¼1 n

mcw can exert a certain level of inﬂuence on the resultant ’i as was outlined by discussion of equation (10) above. For identifying the more inﬂuential parameter, regression analysis was conducted. The two parameters aﬀecting the resultant ’i were assumed to be independent variables for inclusion into a regression model. Linear regression analysis was conducted using the statistical package SPSS.9 The standardized coeﬃcients are used to reﬂect the level of signiﬁcance. A higher value indicates an increase in signiﬁcance. A negative coeﬃcient indicates that the resultant ’i decreases with an increase in the variable, and vice versa. The model constructed by regression analysis can be represented by equation (11)

ð9Þ

where the ’x is the resultant indoor relative humidity for xth experimental condition and ’d is the design indoor relative humidity equal to 50%. The calculated RMSE indicates that regardless of changes in moa, SHR and Eo, RMSE is smaller for a higher mcw (2.86% as opposed to 3.70%). This is considered reasonable because dehumidiﬁcation is responsible by the DV coil, which is subject to its performance as shown in equation (10) ðQo þ Qsp,dv Þ ¼ mcw ðtcwr,dv tcwe Þ ð1 SHRdv Þ ð10Þ where Qo is the outdoor air total load; Qsp,dv is the space-sensible load handled by the DV coil, tcwr,dv is the return chilled water temperature at the DV coil which is a variable; tcwe is the entering chilled water temperature which is maintained at 7 C, and SHRdv is the sensible heat ratio of the DV coil. From equation (10), with an increase in mcw, tcw,dv would tend to decrease to enhance the dehumidiﬁcation performance of the DV coil and thus can better maintain the desired ’i.

ð11Þ

It has a coeﬃcient of determination (r2) of 0.866 to conﬁrm the inﬂuence of the two parameters on the resultant ’i.14 The standardized coeﬃcients determined by regression analysis indicate that SHR would introduce a higher inﬂuence on the resultant ’i than mcw. Their coeﬃcients are 0.911 and 0.188, respectively. The negative signs are judged to be reasonable.

Condensation risk Based on the experimental results, whether there was condensation on the DC coil was determined by checking the discrepancy in moisture content between the recirculated air (Figure 2: state 1) and treated DC air (Figure 2: state 3). Upon ascertaining the presence or absence of condensation as dependent variable for each experimental condition, other studied parameters including moa, mcw, SHR and Eo, aﬀecting the condensation risk (ConR) on the DC coil were assumed to be independent variables for inclusion into a regression model. Linear regression analysis was again used to determine the standardized coeﬃcients. The presence or absence of condensation is a qualitative variable. To deal with this, the dummy variable method was adopted to assign the value 0 or 1 to indicate the presence or absence of condensation on the DC coil. The model constructed by regression analysis is as represented by equation (12) below ConR ¼ 5:175 5:556 SHR 2:803 mcw þ 0:00001 Eo ð12Þ A coeﬃcient of determination (r2) of 0.729 would conﬁrm the inﬂuence of the studied parameters on ConR. Among all studied parameters, SHR has the

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highest standardized coeﬃcient of 0.845, followed by mcw (0.121) and Eo (0.003). moa would pose no inﬂuence on the condensation risk. The negative sign for SHR and mcw, and the positive sign for Eo, as discussed in the previous sections, are again judged to be reasonable. The previous study5 has identiﬁed that the condensation risk on the DC coil is strongly related to the indoor t and t* (represented by ’ as t is a constant), Pearson correlation analysis was again employed to review the correlation between the resultant ’i and the presence or absence of condensation for each experimental condition. The correlation coeﬃcient was found to be 0.808; therefore indicating that the correlation was signiﬁcant at the 0.01 level (2-tailed test as explained in Table 4) and thus conﬁrming consistent result has been achieved in comparison with our previous study.5

Conclusions In order to evaluate the performance of DCDV system when applied under diﬀerent outdoor air ﬂow rate (moa) and chilled water ﬂow rate conditions (mcw), as well as variable SHR and outdoor air enthalpy (Eo) conditions, a prototype was set-up for experimental studies. The experimental results showed that the eﬀectiveness of DCDV system in achieving the desired indoor condition, and providing a condensate-free indoor environment, was most aﬀected by the space SHR and mcw. The parameters, moa and Eo, were found to pose no or little inﬂuence. The results, through sensitivity and statistical analysis, were found consistent with results of previous studies based on simulations and experimental studies. Authors’ contribution All authors contributed equally in the preparation of this manuscript.

Declaration of conflicting interests

Funding This work was supported by Hong Kong Research Grants Council General Research Fund No. 522709.

References 1. Lee WL, Chen H, Leung YC and Zhang Y. Decoupling dehumidification and cooling for energy saving and desirable space air conditions in hot and humid Hong Kong. Energ Convers Manage 2012; 53: 230–239. 2. Chen Hua and Lee WL. Application of condensate-free dry coils for energy-saving and analysis on indoor air quality in Hong Kong. Building Sci 2011; 27: Apr No. 4. 3. Jia Jie and Lee WL. Energy performance and condensation risk of DCDV system in subtropical Hong Kong. Trans Tianjin Univ 2014; 20: 042–047. 4. Jia Jie and Lee WL. Experimental study of performance of a dry cooling and dedicated ventilation (DCDV) system under different space cooling load conditions. Energ Convers Manage 2013; 3: 158–166. 5. Jia Jia and Lee WL. Condensation risk of DCDV system for hot and humid Hong Kong. Indoor Built Environ 2014; 23(6): 814–822. 6. Huang WZ, Zaheeruddin M and Cho SH. Dynamic simulation of energy management control functions for HVAC systems in buildings. Energ Convers Manage 2006; 47: 926–943. 7. Yu FW and Chan KT. Improved energy performance of air cooled centrifugal chillers with variable chilled water flow. Energ Convers Manage 2008; 49: 1595–1611. 8. Anonymous. Pearson product-moment correlation coefficient. Wikipedia 2014, http://en.wikipedia.org/wiki/Pearson_productmoment_correlation_coefficient (accessed 27 January 2015). 9. SPSS: IBM SPSS Statistics. Version 22. IBM Corp USA; 2013. 10. EMSD. Code of practice for energy efficiency of building services installations in building. 2012 ed. Hong Kong: Electrical & Mechanical Services Department, 2012. 11. ANSI: ASHRAE Standard 62.1-2013.Ventilation Standard for acceptable indoor air quality. Atlanta: American Society of Heating Refrigerating and Air-Conditioning Engineers, 2013. 12. Lam JC, Tsang CL and Li DHW. Long term ambient temperature analysis and energy use implications in Hong Kong. Energ Convers Manage 2004; 45: 315–327. 13. Moffat RJ. Describing uncertainties in experimental results. Exp Therm Fluid Sci 1988; 1: 3–17. 14. Milton JS and Arnold SC. Probability and statistics in the engineering and computing sciences. Singapore: McGraw-Hill International Editions, 1987.

The authors declared no potential conﬂicts of interest with respect to the research, authorship, and/or publication of this article.

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