The fundamental parameter that characterizes the hydraulic state of a water pipeline and largely determines the efficiency of the water-transport process is the hydraulic resistance coefficient (HRC). The actual values of the HRC may be different from the theoretical values because of the complexity of the actual situation. A novel method-multi-goal optimization (MGO) strategy-for HRC estimation in building air conditioning systems is described in this paper. First, the basic principle of the approach is presented. Then the strategy is validated using a numerical example

Hou, Z.

Lian, Z.

Texas A&amp;M Repository

ICEBO2006, Shenzhen, China HVAC Technologies for Energy Efficiency, Vol. IV-11-2 Zhijian Hou     Identification of the Flow Resistance Coefficient and Validation  of a Building Air Conditioning System                       Zhiwei Lian                                                                           PH.D.  Lecturer School of Mechanical and Electrical Engineering,Shenzhen Polytechnic,Shenzhen, P. R. China, 518055  hzj305@163.com PH.D.  Professor Institute of Refrigeration and Cryogenics, School of Mechanical and Power Engineering, Shanghai Jiao Tong University, Shanghai,  P. R. China,200030 zwlian@sjtu.edu.cn Abstract The fundamental parameter that characterizes the hydraulic state of a water pipeline and largely determines the efficiency of the water-transport process is the hydraulic resistance coefficient (HRC). The actual values of the HRC may be different from the theoretical values because of the complexity of the actual situation. A novel method— multi-goal optimization (MGO) strategy — for HRC estimation in building air conditioning systems is described in this paper. First, the basic principle of the approach is presented. Then the strategy is validated using a numerical example. Keywords: Flow Resistance Coefficient, Parameter Identification, Air Conditioning System  1 INTRODUCTION  Loop networks have been developed and used widely in the heating, ventilation and air-conditioning (HVAC) field. The complexity of modern air conditioning system may make the balancing process quite involved. Some persons frequently are unaware of the difficulties and requirements of balancing. In the past it was often possible to get by with making a few adjustments and checking if people were comfortable. This is no longer satisfactory on large systems. Organized procedures are required to balanced system so that it will result in comfort in all reasons. Furthermore, the increased need for minimizing energy waste also requires correct balancing techniques. An improperly balanced system will almost certainly use excess energy. In addition, the variable frequency driver (VFD) is being used as a new adjustment implement. The control of variable-speed pumps on hot- and chilled-water systems must be based upon a hydraulic analysis of the water system. Hydraulic analysis enables the control manufacturer to select and program the variable-speed and pump addition and subtraction controls to achieve the maximum system efficiency [1]. Furthermore, hydraulic process faults, such as blockage in the network, may be occurred in loop networks. Many researches have been investigated about hydraulic state in HVAC field. Hydraulic process fault diagnosis and parameter identification based on resistance coefficient region contraction in district heating networks is discussed in literature [2]. Xuzhong Qin etc.[3] presented a quantitative definition of hydraulic stability and its calculating method according to the network’s structure and hydraulic condition or the measured data online. It is important to find a way to evaluate these networks, and hydraulic state is one of the basic criteria. The fundamental parameter that characterizes the hydraulic state of a water pipeline and largely determines the efficiency of the water-transport process is the hydraulic resistance coefficient (HRC). Since there are many pipe bends, manual valves, etc., of which the flow resistance performance depends on the installation or local initial regulation, the actual values of the HRC may be different from the ESL-IC-06-11-128 Proceedings of the Sixth International Conference for Enhanced Building Operations, Shenzhen, China, November 6 - 9, 2006 ICEBO2006, Shenzhen, China HVAC Technologies for Energy Efficiency, Vol. IV-11-2 theoretical values. In addition, a service engineer wishes to check if the proper flow rate is circulating in the chilled water piping on a job. All these problems would be easily solved if the HRC of piping were known. A novel method—multi-goal optimization(MGO) strategy— for HRC estimation and hydraulic process fault diagnosis in building air conditioning system is presented in this paper. First, the basic principle of the approach is presented. Then the strategy is validated using the simulation data.   2 BASIC APPROACH OF MULTI-GOAL OPTIMIZATION   2.1 The analysis of hydraulic state of chilled water system In order to have the water temperature to each air handling unit (AHU) equal to the temperature at which it is generated, two pipe arrangements are usually used in HVAC system. Figure 1 is an arrangement of central chilling water system.  Bal anci ng val veVFDCont r ol l er(n-1) 'n'nChi l l erChi l l erFl ow met erBy pass val veFMΔ Pn-12…3Regul at i on val ve12'AHU(n+1)AHUnAHU4… …3'AHU3AHU2AHU11'A B Fig.1 The schematic of chilled water system There are two mains, one for supply and one for return. Individual supply branches feed each unit. Return branches deliver water back to the return main. The hydraulic balancing problem could be resolved by throttling a balancing valve in each branch. And flow regulation valves can be used to meet the room comfort requirement with the change of cooling load. The pump is automatically controlled according to differential pressure of chilled water loop. Chilled water flow meter is available for the total water supply. For piping system, the turbulent flow exists in HVAC system and the pressure loss due to friction is given as expression (1) 2H SQ=                (1) where, S is the flow resistance coefficient of pipe,kPa.S2/ m6; Q is the flow rate, m3/s;H is pressure loss, kPa.  The S value can be assumed as independent flow rate in chilled water piping system. In addition, pressure drop of heat exchanger can be determined from equation (2) ( )mQ mBAH Bw =Δ =             (2) Where, ΔH is the water resistance of heat exchanger. B and m are coefficients obtained from experiments. A is sectional area of water pipe in heat exchanger. In practice, the value of m may be close to 2 and not be equal to 2. As a result, the pressure loss-flow relation may not be following equation (1).  2.2 The strategy of multi-goal optimization In order to illustrate the strategy of multi-goal optimization, firstly, only AHU1 and AHU2, as shown in figure 1, are considered and others are stopped flow. It is assumed that the values of HRC through 1-AHU1-1’ and 1-AHU2-1’ are S1 and S2 respectively. And let the flow resistance coefficient of through A-AHU1-1 and 1’-AHU2-B is S. Before identification, some data have to be obtained according to following procedures: 1)  Close the by-pass valve; 2) Shut off flow of AHU2; 3) Adjust the drive frequency of pump and let the value of flow meter equal to designed flow rate (Q1) of AHU1. And the pressure drop (Δh1) from A to B can be obtained; 4) Stop flow of AHU1 and make a comeback for AHU2; ESL-IC-06-11-128 Proceedings of the Sixth International Conference for Enhanced Building Operations, Shenzhen, China, November 6 - 9, 2006 ICEBO2006, Shenzhen, China HVAC Technologies for Energy Efficiency, Vol. IV-11-2 5) Adjust the drive frequency of pump and let the value of flow meter equal to the designed flow rate (Q2) of AHU2. And the pressure loss (Δh2) from A to B can be obtained; 6) Make a comeback for AHU1and AHU2.  7) Adjust the drive frequency of pump and let the value of flow meter equal to the sum of Q1 and Q2. At the same time, the corresponding pressure loss (Δh3) from A to B can be measured. According to the analysis of hydraulic state above mentioned. The pressure loss-flow relation may not be following equation (1). For this reason, expression(3)-(5) are used to identify S1,S2 and S in this paper. 11 21hMinimize S SQΔ+ −        （3） 22 22hMinimize S SQΔ+ −       （4） 31 221 21 2*2 ( )( )hS SMinimize SQ QS SΔ+ − ++  （5）  Seen from expression (3)-(5), the HRC estimation is based on multi-goal optimization (MGO) principle. “m is close to 2” is assumed for AHU1 and AHU2. Once S, S1 and S2 are estimated, the HRC of other branch and main section can be estimated based on same principle.   3 VALIDATION BY SIMULATION The strategy of MGO is validated by the simulation of AHU1 and AHU2. The parameters are shown in table 1.  Tab. 1 The parameters of AHU for simulation  AHU1 AHU2 通水断面积(m2) A1=0.00407 A2=0.00553 Water resistance of Heat exchanger(kPa) 15.48w1.97 64.68w1.854 Designed flow rate (m3/s) 0.003 0.006 Balancing is the process of proportioning the correct flow of air and water throughout the system, through mains, branches and equipment. What actually happens is that in balancing the system the contractor will throttle valves in the path of less resistance to increase the pressure drop and produce the proper flow in that circuit.                                Fig.2 Flow of balancing Tab.2 Experiment 1: The simulation results for S equal 50000 kPa.s2/m6 ΔS1 Q’2  1s ′   2s ′   s′   0.512( )ss′′  0 0.00354 927066 2073975 66031 0.669 2000000 0.00485 2927411 2074320 65686 1.188 5000000 0.00564 5935109 2082018 57987 1.689 7000000 0.00595 7940742 2087651 52354 1.950 Q1,Δh1 121hQΔ Q2,Δh2 222hQΔ Q2+Q1,Δh3 321 2( )hQ QΔ+  The calculated values of S ′、 1S ′、 2S ′  according to expression(3)-(5) '0.5 12'1 2?QSS Qε− ≤（ ）  S ′、 1S ′、 2S ′  Y N Adjusting resistance in the path of less resistance ESL-IC-06-11-128 Proceedings of the Sixth International Conference for Enhanced Building Operations, Shenzhen, China, November 6 - 9, 2006 ICEBO2006, Shenzhen, China HVAC Technologies for Energy Efficiency, Vol. IV-11-2 7500000 0.00601 8441917 2088826 51180 2.010 7650000 0.00603 8592617 2089526 50480 2.028 7800000 0.00604 8743125 2090033 49972 2.045 8000000 0.00607 8943590 2090499 49507 2.068 Figure 2 illustrates the flow of balancing.Three conditions are simulated to investigate and the data of adjusting are shown in table 2, 3 and 4 respectively. And table 5 shows the performance of identification. Tab.3 Experiment 2: The simulation results for S equal 50000 kPa.s2/m6 ΔS1 Q’2  1s ′   2s ′   s′   0.512( )ss′′  0 0.00354 17322 1640726 730269 0.103 2000000 0.00485 2927411 2074320 115686 1.188 5000000 0.00564 5935109 2082019 107987 1.688 7000000 0.00595 7940742 2087652 102354 1.950 7500000 0.00601 8441917 2088826 101180 2.010 7650000 0.00603 8592617 2089526 100480 2.028 8000000 0.00607 8943589 2090501 96901 2.068 Tab.4 Experiment 3: The simulation results  for S equal 400000 kPa.s2/m6 ΔS1 Q’2  1s ′   2s ′   s′   0.512( )ss′′  0 0.00354 927066 2073975 416031 0.670 2000000 0.00485 2927411 2074320 415686 1.188 5000000 0.00564 5935109 2082019 407987 1.688 7000000 0.00595 7940742 2087652 402354 1.950 7500000 0.00601 8441917 2088826 401180 2.010 7650000 0.00603 8592617 2089526 400480 2.028 7800000 0.00604 8743125 2090034 399972 2.045 Tab.5 The estimated values of hydraulic resistance under design flux HRC Experiment S1+ΔS S2 S Actual Value 8443097 2090006 50000 Identified Value  8441917 2088826 51180 Error 1180 1180 11780 1 Relative error 0.014% 0.056% 2.359% Actual Value 8443100 2090006 100000 2 Identified Value  8441917 2088826 101180 Error 1180 1180 1180 Relative error,% 0.014 0.056 1.18 Actual Value 8443100 2090006 400000 Identified Value 8441917 2088826 401180 Error 1180 1180 1180 3 Relative error,% 0.014 0.0564 0.295 It is seen from table 5 that the HRC by identifying are very closed to the actual values, which indicates that the strategy of MGO can be used for balancing, hydraulic process fault diagnosis and provide the base for the maximum system efficiency. 4 CONCLUSION Multi-goal optimization strategy for HRC estimation is investigated in this paper. And some conclusions can be got as follows: 1) The MGO method is applicable for S value identification. The method is based on the principle for multi goal optimization. The process can be widely used in engineering practice.  2) Traditionally, the success of balancing depends on adequate instrumentation. These instruments are used for measuring temperature, pressure, velocity, flow rate, speed, heat flow, and electrical energy. Whereas, the MGO method can be achieved by the identification of HRC, which only depends on the parameters of water flow and pressure drop. As a result, it is accord with the actual situation in HVAC system. 3) HRC is the fundamental parameter that characterizes the hydraulic state. The identification result of HRC can be used to hydraulic fault diagnosis and provide the base for the maximum efficiency of the water-transport process. REFERENCE [1] Rishel, J.B. Control of variable-speed pumps on hot- and chilled-water systems, ASHRAE Transactions Issue pt 1, 1991, Pages 746-750   [2] Yi Jiang. Xuzhong Qin. Hydraulic Process Fault Diagnosis and Parameter Identification in District Heating Networks. ASHRAE Transactions Volume 106, 2000, Pages PA/-   [3] Xuzhong Qin, Yi Jiang, Gang Liu. Evaluation of Hydraulic Stability and its Application in Hydronic Systems ESL-IC-06-11-128 Proceedings of the Sixth International Conference for Enhanced Building Operations, Shenzhen, China, November 6 - 9, 2006 

Identification of the Flow Resistance Coefficient and Validation of a Building Air Conditioning System

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Identification of the Flow Resistance Coefficient and Validation of a Building Air Conditioning System

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Identification of the Flow Resistance Coefficient and Validation of a Building Air Conditioning System

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