ASHRAE 4689-2004 Thermodynamic Modeling and Experimental Validation of Screw Liquid Chillers《液体螺杆冷水机组的热力学建模及实验验证》.pdf
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1、4689 Thermodynamic Modeling and Experimental Validation of Screw Liquid Chillers Tzong-Shing Lee, Ph.D., P.E. Member ASHRAE ABSTRACT This study presents an empirically based model, involving the first and second laws of thermodynamics and the NTU-E method of heat exchanger, to predict the coeficient
2、 ofperfor- mance (COP) of screw liquid chillers under various operating conditions, especially for capacity control by return chilled water sensing. A series of experiments wereperformed to verifi this model. The input operating parameters of the model are readily measured data from the water side o
3、f liquid chillers; they include the chilled water inlet temperature, the cooling water inlet temperature, and the cooling capacity. By incor- porating the experimental data and the theoreticalpredictions, an empirical correlation form can be obtained to predict the performance of a screw liquid chil
4、ler: The result indicates that comparison between the predicted value and the measured data yields an R2 (explained fraction of variance) of around 98.87%, an RMSE (absolute root-mean-square error) of about O. 0524, and an R-RMSE (relative root-mean-square-error) of about 1.43%. The results of this
5、workshould be appliedfor the purposes ofperformance prediction, evaluation of energy-efi- ciency improvements, fault detection, and other diagnoses of screw liquid chillers. INTRODUCTION Vapor-compression liquid chillers have been extensively used as cooling equipment to cool water, brine, or other
6、secondary coolant for air conditioning or refrigeration in the field of commerce and industry. The main components of a vapor-compression liquid chiller unit include a compressor and its driver, a condenser, a throttling device, a liquid cooler (evaporator), accessories, and a control system. The mo
7、st often used types of compressors are reciprocating, screw, and centrifugal. Liquid chillers with screw compressors are often applicable at a cooling capacity of 90 kW (25.6 tons) to about 3,500 kW (995.2 tons) (ASHRAE 2002). Although screw chillers are made up to 3,500 kW (995.2 tons) in capacity,
8、 they are most cost-effective up to 1,000 kW (284.3 tons). Above that size, they are not cost competitive with centrifugal chill- ers. Screw chillers provide continuous capacity modulation from 100% capacity down to 10% or less. For continuous capacity modulation, the leaving chilled liquid temperat
9、ure is sensed for capacity control, while for the step capacity modu- lation, return chilled liquid temperature sensing is normally used by units to help provide good temperature control. The performance of chillers, specified by cooling capac- ity, compressor power consumption, and COP, is commonly
10、 given by the refrigerant-side data, such as condensing temper- ature, evaporating temperature, degrees of superheating, and degrees of subcooling. Practically, especially for the purposes of performance prediction, evaluation of energy-efficiency improvements, fault detection, and other diagnosis o
11、f screw liquid chillers, expressing chiller performance in terms of readily measured water-side data rather than the refrigerant- side data is more convenient. These measurable water-side data include cooling water inlet temperature, chilled water inlet or outlet temperature, and cooling capacity. A
12、ccordingly, the modeling of liquid chillers for these purposes has been the subject of many studies over the last decade. Gorden et al. (1995) successfully developed an empiri- cally based thermodynamic model of centrifugal chillers and validated it experimentally using cooling plant data. As well a
13、s predicting the chiller performance over a broad range of oper- ating conditions, this model can be used as a diagnostic tool to analyze the fouling effect of heat exchangers on chiller perfor- Tzong-Shing Lee is an associate professor in the Department of Air-conditioning and Refrigerating Enginee
14、ring, National Taipei University of Technology, Taiwan. 206 02004 ASHRAE. mance. Ng et al. (1 997) developed a simple thermodynamic analytic method for diagnosing reciprocating chillers. The use of this model to establish optimal operating conditions and evaluate potential improvements to reciprocat
15、ing chillers was demonstrated. After reviewing more than 60 research papers on both steady-state and transient models, Browne and Bansal(l998a) described the philosophy and challenges of developing simu- lation models of vapor-compression refrigeration chillers. Only steady-state simulations were fo
16、und, which, in itself, indicates the need for transient models. Additionally, the surveyed literature exhibited a distinct lack of simulation models associated particularly with vapor-compression liquid chillers. Brown and Bansal (1 998b) presented a steady-state model of vapor-compression-type cent
17、rifugal liquid. They validated the model using experimental data on the perfor- mance under part to full loading of three different chillers, and the agreement was found to be within *lo%. Brown and Bansal (2001) utilized NTU-E methods to develop a steady- state model for predicting the performance
18、of vapor-compres- sion liquid chillers over a wide range of operating conditions. This model extends their previously developed model (Brown and Bansal 1998b). In addition to the readily measured data, the extended model also requires data concerning the heat exchanger, including the geometrical par
19、ameters of the tube bundle and the knowledge of the heat transfer coefficient on both the water and the refrigerant sides. The model was vali- dated with data from two liquid chillers, and the agreement was within %lo%. Swider et al. (2001) and Bechtler et al. (2001) proposed approaches to predict t
20、he performance of a chiller without using any physical or thermodynamic model. Swider et al. (2001) used a generalized radial basis function (GRBF) neural network to predict the chiller performance in the steady state. The input parameters were the chilled water outlet tempera- ture from the evapora
21、tor, the cooling water inlet temperature to the condenser, and the evaporator capacity. Applied to two different chillers, this model predicted the compressor work input and the COP to within *5%. Bechtler et al. (2001) presented a dynamic neural network model of the dynamic processes in vapor-compr
22、ession liquid refrigeration systems. This model was validated by application to two chiller units in different transient operating regimes; the results imply that the trends in any given data set were satisfactorily predicted. Recently, Swider (2003) presented a comparison of empiri- cally based mod
23、els for steady-state modeling of vapor- compression liquid chillers. The models he considered in his work included regression and thermodynamic models, a radial basis function neural network model, and a multilayer percep- tron neural network model. The results showed that the radial basis function
24、neural network model is preferred for predict- ing a chillers performance. The models developed in the literature mentioned above are used for the case of capacity control by the leaving chilled liquid temperature. Models and simulations of the perfor- mance of screw chillers using an empirically ba
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