ASHRAE OR-16-C010-2016 Energy Performance Assessment of Radiant Cooling System through Modeling and Calibration at Component Level.pdf

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1、 Jyotirmay Mathur is a Professor in the Department of Mechanical Engineering, MNIT, Jaipur, RAJASTHAN (India). Mahabir Bhandari is a scientist at Oak Ridge National Laboratory, Oak Ridge, TN, and Yasin Khan is a Project Engineer at MNIT, Jaipur, RAJASTHAN (India). Energy Performance Assessment of Ra

2、diant Cooling System through Modeling and Calibration at Component Level Jyotirmay Mathur, PhD Mahabir Bhandari, PhD Yasin Khan Member ASHRAE Member ASHRAE ABSTRACT The paper describes a case study of an information technology office building with a radiant cooling system and a conventional variable

3、 air volume (VAV) system installed side by side so that performance could be compared. First, an energy model of the building was developed in EnergyPlus, a simulation tool. Second, a base case model was developed to generalize energy saving potential of radiant cooling system. This paper details th

4、e calibration of the whole building energy model to the component level, including lighting, equipment, and HVAC components such as chillers, pumps, cooling towers, and fans. The error at the whole building level measured in mean bias error (MBE) is 0.2%, and the coefficient of variation of root mea

5、n square error (CvRMSE) is 3.2%. The total errors in HVAC at the hourly are MBE = 8.7% and CvRMSE = 23.9%, which meet the criteria of ASHRAE Guideline 14 (2002) for hourly calibration. A base case model was developed by using the calibrated model for quantifying the energy saving potential of the ra

6、diant cooling system. It was found that a radiant cooling system integrated with DOAS can save 28% energy compared with the conventional VAV system. INTRODUCTION Cooling of commercial buildings contributes significantly to electricity consumption and peak power demand. In buildings conditioned by co

7、nventional all-air systems, air is employed as a heat transfer medium for cooling through convection. A significant part of the electricity that is consumed is used by fan motors to transport the cool air. In a radiant cooling system, the amount of transport air is reduced, and cooling is provided b

8、y chilled water that flows through pipes embedded in the structure. Radiant cooling systems reduce the temperature of the structures which trigger the radiation heat transfer from the human body, and that heat is taken out by flowing chilled water. However, some part of the cooling load (mostly late

9、nt load) is still removed by air, which is necessary for ventilation. Thus, a radiant cooling system separates the tasks of ventilation and thermal conditioning and uses both convection and radiation heat transfer to provide thermal comfort in a space. Separating the ventilation and the thermal cond

10、itioning tasks can significantly reduces the energy consumption of a building HVAC (Feustel and Stetiu 1995). Niu et al. (2002) evaluate the system performance and energy saving potential of a radiant cooling system with desiccant cooling through energy simulation. Their results indicate that a chil

11、led ceiling combined with desiccant cooling could save up to 44% of the primary energy consumption, in comparison with a conventional system. A study by Henze et al. (2008) concluded that buildings with Thermo Active Building Systems showed better thermal comfort and about 20% less energy consumptio

12、n than all-air variable air volume (VAV) systems. Oxizidis and Papadopoulos (2013) compared radiant and convective systems with respect to energy consumption and thermal comfort in a test cell through computer simulations of a single office in a warm and humid climate; their results showed that the

13、conventional system consumed greater than 14% more primary cooling energy than the radiant system. There are very few studies which assess the energy saving potential of a radiant cooling system by comparing it with a conventional all-air system that have proper validation. Also, existing studies ar

14、e generally based on test cells or on a simple ideal zone, not on a realistic building which is operating under business as usual circumstances. Only one case study describes realistic building behavior with a radiant cooling building (Tian and Love 2009). Proper validation of a hypothetical model o

15、f a conventional air system has not been done. Proper validation of a simulation model is highly dependent on the calibration process. There are some standard criteria for considering any model to be a calibrated model (ASHRAE 2002; IPMVP 2007). These criteria are based on monthly and hourly level m

16、atching, but they do not specify which level (building level or component level) of energy consumption should be used for the calibration process. A review of previous calibration work revealed that there are very few studies available that describe calibration methodology. Pedrini et al. (2002) dev

17、eloped a methodology for building energy simulation calibration which is divided into three stages with well set default values for building input parameters. Reddy et al. (2007a, 2007b) developed a calibration procedure which involves a set of influence parameters, advanced mathematics, numerous tr

18、ials, and simulation runs. Pan et al. (2007) summarize the calibration process based on the related literatures for high-rise commercial building in Shanghai. Lam et al. (2008) conduct simulations for ten air conditioned office buildings and calibrate them at the monthly level whole using sensitivit

19、y analysis. Raftery et al. (2011a, 2011b) developed evidence-based methodology for a detailed calibration process in which verified information is used for real office building simulation and calibration. Most of the above studies focus error analysis on the whole building energy level, not on the c

20、omponents level. In whole building energy level, calibration inaccuracies at the component level can offset each other to give the results that match the measured data, but in reality there may be a chance of poor representation of the actual building performance. So a calibrated model at the whole

21、building level may give an unreliable breakdown of total energy consumption of the building. Therefore, it is necessary to validate the model at the relevant system components level, especially in cases where HVAC performance is being compared. The main objective of this work is to provide an assess

22、ment of the energy savings that can be achieved by radiant system cooling using a detailed calibrated building energy model. CASE STUDY DESCRIPTION This paper discusses the case study of one of the buildings of INFOSYS, an information technology company located in Pocharam, Hyderabad (India) which i

23、s referred to as the Software Development Block-1 (SDB-1). This case study provided an opportunity to assess the performance of a radiant cooling system. SDB-1 is not only the first large commercial building in India with a radiant cooling system, but it was also used in the worlds largest side-by-s

24、ide comparison between VAV and radiant cooling systems (Sastry and Rumsey 2014).The building consists of two symmetric parts that include two types of cooling systems. The total built-up area of the building is about 24,000 m2, which is distributed over six floors of two symmetrical parts and two fl

25、oors of center wing. The center wing floors are auditorioums with separate HVAC system. The west side of the building (the conventional side) is cooled by a VAV air conditioning system, and the east side of the building (the radiant side) is cooled by a radiant cooling system integrated with a dedic

26、ated outdoor air system (DOAS). The meeting and conference rooms in the radiant side of the building have chilled beams to cool them. The main orientation of the building is the east-west direction. The building has a typical floor layout in which the floors recede with height, so the building looks

27、 like a pyramid (Figure 1). There are two chilled water plants for each side of the wings (Figure 2). The conventional side of the wings has 272 TR (952 kW) chillers which provide chilled water for six AHUs cooling coils and one DOAS cooling coil on the radiant side known as the LT (low temperature)

28、 coil. The radiant side chilled water plant has 325 TR (1137.5 kW) chillers which providing chilled water for the radiant tubes and another DOAS cooling coil known as the HT (high temperature) coil. Figure 1 (a) The INFOSYS building in Hyderabad, India; (b) Energy model of the INFOSYS building; and

29、(c) Zoning layout of a floor of the building. Figure 2 Chilled water plant of SDB-1. Both the radiant and the conventional sides of the INFOSYS building are monitored, but in this particular case measured data alone cannot be used for the following reasons: Different part load performance. The LT co

30、il of DOAS is feed by the conventional side chiller for the dehumidification purpose. Therefore conventional side chiller is operating at a higher load than expected, and the radiant side chiller is operated on a lower load as compared to the supposed load. This affects the part load performance of

31、both the chillers. So it is necessary to have a separate chiller for the latent load on the radiant side. Different COPs. Secondly, the chillers used on the conventional and radiant sides do not have the same COP values. For example, the conventional side chiller has COP of 6.4 (rated at 7 C (44.6 F

32、) supply chilled water temperature), but for the radiant side chiller, the COP is 7.8 (rated at 12 C (53.6 F) supply chilled water temperature). For a fair comparison of both the systems a base COP recommended by standards is used for generalizing the energy saving of the radiant cooling system. Bui

33、lding Orientation. As discussed earlier, the INFOSYS building is one of the largest experimental facilities being used to compare the performance of radiant and conventional cooling systems, but still there are dissimilarities between the HVAC loads on the east and west wings because of their differ

34、ent orientations. To discount for the impact of orientation of the heating and cooling loads of the east and west wings, the performance comparison was also made by rotating the building model by 180 degrees. MODEL DEVELOPEMENT In this research work, the EnergyPlus tool version 8.0 was used because

35、of the complexity of the model. EnergyPlus allows the user to define the components in great detail. There are a total of 62 zones, of which 49 zones are conditioned. It was assumed that there is one occupant per desktop. The number of desk was taken from architectural layout of the space. The light

36、ing power density (LPD) and equipment power density (EPD) were determined as 5 W/m2 (0.46 W/ft2) and 20 W/m2 (1.86 W/ft2), respectively, from the specification document. The building is operated from 9 AM to 6 PM 5 days in a week. Rad OVERVIEW OF CALIBRATION PROCESS The calibration process consists

37、of twelve steps in which the first step is the initial simulation result. The errors in each step are shown in a pair which represents the mean bias error/coefficient of variation of root mean square error (MBE/CvRMSE). The second step deals with lighting and equipment energy consumption. The errors

38、 in lighting and equipment energy are -28%/27% and -88%/85%, respectively. After adjusting the values for LPD and EPD based on the measured lighting and equipment energy consumption, the best matches achieved for LPD and EPD were (0.37 W/ft2) and 16 W/m2 (1.49 W/ft2), respectively, which reduces the

39、 error in lighting and equipment to -0.6%/0.8% and 0.8%/3.7%, respectively. The building LPD and uninterrupted power supply) load revisions substantially reduced the MBE and CvRMSE to 10% and 11%, respectively, at the whole building energy level, which was initially 45% and 43%, respectively. Accura

40、te weather data is one of the most important factors needed to predict HVAC energy consumption; weather data is also needed in the calibration process. Bhandari et al., (2012) investigated the impact of different weather data sets on building energy consumption. In the third step, onsite weather dat

41、a including dry-bulb temperature, dew point temperature, relative humidity, and solar radiation were used instead of Typical Meteorological Year data. The error reduction in this step is just 1% at whole building, but for the HVAC level, it is around 4.5%. In the fourth step, the value of fan pressu

42、re rise is changed from the default value and taken from the manufacturing sheet of the fan. This step reduces the error in fan energy for AHUs 11%/18% and for DOAS -8%/12%. In the fifth step, the supply air setpoint temperature is changed from 14C to 15C (57.2 F to 59 F), which further reduces the

43、error in fan energy for the AHUs and brings the fan energy into the calibration limit with 1.2%/9.8%. In the sixth step, the minimum air flow rate is changed for DOAS, which is oversized with higher minimum air flow rate. This step brings the DOAS fan into the calibration limit with -1%/7.6%. In the

44、 seventh step, the radiant side condenser pump water flow was modulated according to the measured energy of the condenser pump. This step significantly reduces the error to -2.3%/9.3%. (It was initially -66%/68% for the radiant side condenser pump.) A similar improvement was made for the conventiona

45、l side condenser pump; the errors reduced from -16%/26% to -2%/8.6%. In the eighth step, the cooling tower water outlet setpoint temperature was changed according to the measured data, which reduced the error from 43%/65% to 40%/43% for the radiant side cooling tower. However, for the conventional s

46、ide cooling tower, the MBE increased from 12% to 24%, but CvRMSE reduced from 37% to 26%. In the 9th step detailed CoolTool-CrossFlow tool model which represented the current wind tower equipment more closely was used. This step brought the conventional side cooling tower into the calibration limit.

47、 The error at this stage of calibration is 0.3%/8% for the conventional cooling tower. Till this stage, the conventional side chiller has been calibrated, but the radiant side chiller still required some improvements. In the tenth step, the supply air temperature schedule of the heat recovery wheel

48、is changed according to the measured data; this change reduces the error from 21%/30% to 17%/26% for the radiant side chiller. In the next step the design supply chilled water temperature was initially 12C (53.6 F); that is changed to 16C (60.8 F) as the radiant side chiller is operated 16C (60.8 F)

49、 rather than 12C (53.6 F). This step reduces the error for the radiant side chiller significantly. In the last (twelfth) step, the throttling range of the radiant cooling system is changed from 2C to 1C (3.6 F to 1.8 F) , which moves the radiant side chiller into the calibration limit with 5.6%/13.3%. RESULTS OF THE CALIBRATION PROCESS The previously described calibration process brings all the building energy components except the chilled water supply pumps into the predefined calibration criteria. It is very difficult to calibrate these pumps because of the una