ASHRAE 4697-2004 An Air-Conditioning Model Validation and Implementation into a Building Energy Analysis Software《一个建筑能耗分析软件 空气调节模型验证和实施》.pdf
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1、4697 An Air-Conditioning Model Validation and Implementation into a Building Energy Analysis Software Kamel H. Haddad, Ph.D. ABSTRACT An empirical model for a split air-conditioning system with an air-cooled condensing unit and an indoor evaporator unit is presented. The model is intended for hourly
2、 building energy simulations. Major inputs to the model are the cooling capaciq, coeficient ofperformance, andsensible heat ratio at rating conditions. Performance degradation at part-load conditions is accounted for The model is implemented in the ESP-r/H3Ksimulation engine. Model implementation in
3、 ESP- rH3K is validated through comparison to spreadsheet calcu- lations. In addition. model predictions from ESP-r/H3K are compared to results from other simulation programs and analytical solutions contained in an International Energy Agency set of test cases (HVAC BESTEST). The agreement between
4、the results from the simulation model in ESP-r/H3K and those from the HVAC BESTEST is very good. Results also show the importance of software testing and validation in increasing the confidence in simulation results. INTRODUCTION New simulation algorithms are implemented on a regular basis within ne
5、w and existing building energy simulation engines. The accuracy of the results obtained using these new algorithms depends, on the one hand, on the quality of the experimental data, assumptions, and derivations used to deduce the equations describing the model. On the other hand, the accuracy of the
6、 results also depends on the correct imple- mentation of the model into the simulation engine. During the model development and model implementa- tion phases, errors can occur that can lead to inaccurate results when using the simulation tool. As a result, validation of the model and its implementat
7、ion into a building energy simula- tion engine is very important. One validation method is to compare model predictions to experimental results. Another method is to compare results from the model to those from an analytical solution. Model validation can also be done through comparisons to results
8、from other simulation engines. In this paper, a simulation model for a simple split air- conditioning system is developed. The model is then imple- mented into the simulation engine ESPdH3K. The model implementation is validated by comparisons to spreadsheet calculations. In addition, results from t
9、he model implemented into ESP-dH3K are compared to results from other simulation engines and analytical solutions contained in the IEA HVAC BESTEST (Neymark and Judkoff 2002). AIR-CONDITIONING MODEL The model applies to a unitary split air-conditioning system consisting of an air-cooled condensing u
10、nit and an indoor evaporator unit. Mixed air from the conditioned zones and the outdoors flows on the outside of the evaporator coil by an indoor circulation fan. This fan can be placed either upstream or downstream of the evaporator coil. Figure 1 shows the various processes on the psychrometric ch
11、art for the case when the circulation fan is upstream of the coil: 1-2 2-4 4-0 5-4 Sensible cooling through coil 2-5 Latent cooling through coil Sensible heating through circulation fan Sensible + latent cooling through the coil Heating and humidification of the air inside the space State 3 is the a
12、pparatus dew-point temperature. State 1 is the result of mixing return air (state O) from the conditioned Kamel Haddad is a building energy simulation researcher, CANMET Energy Technology Centre, Ottawa, Ontario, Canada. 46 02004 ASHRAE. Table 1. Comparison of Capacity Predictions from Correlation t
13、o Manufacturers Equipment Data 19.4 Figure 1 Representation of the air-conditioning process through the coil on the psychrometric chart. 7.21 7.17 0.55 zones and outdoor air (state O). The figure also shows the line 0-0 for the mixing of return air with outdoor air. Input variables, listed in the “N
14、omenclature” section, to the model are Tdb, wl, Tdbo, SHRAR, VI, QARI, COPA, Qfan and Qtoai, load. 21.7 Correlation for Air-Conditioner Capacity model is at the following AR1 rating conditions: The steady-state cooling capacity QARI input to the Tdbl= 26.7OC Tdbo 35.0C Twb, = 19.4”C This capacity is
15、 the gross cooling capacity of the equip- ment. This is the total cooling capacity at the evaporator coil without correcting for any heat from the circulation fan. The cooling capacity Qc at other operating conditions is given by GC = OAR, XfCAp(TWb2, TdbO) . (1) 7.71 7.73 -0.25 The correction funct
16、ion is based on the correlation used in DOE2.1E (1994) for system RESYS: fCAP(Twb2, Tdb,) = 0.6003404 + 0.0022873 x Twb2 - 0.0000128 x Twbi + 0.0013898 x Tdb, - 0.0000806 x Tdbt + 0.0001412 x Twb, x Tdb, (2) The temperatures in this equation are in OF. The International Energy Agency series of test
17、cases for HVAC models by Neymark and Judkoff (2002) contains manufacturers performance data for an air-conditioning system. The data list values for the total cooling capacity of the equipment at various inlet wet-bulb temperatures and outdoor dry-bulb temperatures. Table 1 lists some of the manufac
18、- turers data contained in the IEA document and the predictions I 17.2 I 6.72 1 6.62 I 1.48 I I I I I 1 obtained using Equations 1 and 2. The percentage difference between the manufacturers data and the predictions from Equation 1 and 2 can be as high as 4.30%. Overall though there is good agreement
19、, indicating that the correlation described by Equations 1 and 2 is acceptable for predicting the capacity of the equipment at off-rating conditions. Correlation for Coefficient of Performance The input CPARItO the model is also at ARI rating condi- tions mentioned previously. The COP, at other oper
20、ating conditions is given by where the correction function is also based on a correlation for system RESYS in DOE2.1E (1994): f:;I:;) . Effectiveness is defined by It is assumed in this equation that the apparatus dew-point temperature T3 is a good estimate for the temperature of the refrigerant. Th
21、is is deemed a good assumption given the low thermal resistance associated with the tube walls of the evap- orator coil. Therefore, we have, Using the bypass factor at rating conditions BFARI, it is possible to estimate the ratio hConJ1IJCp of the heat exchanger. This ratio is then used to find BF a
22、t the new flow rate from Equation 26. Coil Bypass Factor at Rating Conditions As mentioned in the previous section, the quantity hCon_ JiiJCp is to be estimated from the value of the bypass factor at rating conditions BFARI, which is not an input to the model. However, BFARI can be deduced knowing t
23、he sensible heat ratio at rating conditions SHRARI, which is an input to the model. The procedure for deducing BFAMfrom SHRARIis very similar to that outlined previously for deducing SHR knowing BF. Cutoff Inlet Wet-Bulb Temperature for Dry Coil Conditions As mentioned previously, for every inlet dr
24、y-bulb temper- ature to the coil, there is a wet-bulb temperature Twb, above 49 which the coil surface is always wet. The wet-bulb tempera- ture Twb, needs to be determined to decide whether the coil is dry or wet. Given the inlet dry-bulb temperature to the coil, an inlet wet-bulb temperature and t
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