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Intermittent experimental study of a vertical ground source heat pump system
Applied Energy 136 (2014) 628–635
Contents lists available at ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
Intermittent experimental study of a vertical ground source heat pump system Yan Shang ⇑, Ming Dong, Sufen Li Key Lab. of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, PR China
h i g h l i g h t s We studied the intermittent operation of a GSHP system with experimental method. The influence of factors on geo-temperature and performance parameters is analyzed. Soil temperature transports faster when the soil thermal diffusivity is larger. Soil temperature varies quickly with larger inlet flow rate and weather temperature. Fitted formula will predict geo-temperature variations under intermittent operation.
a r t i c l e
i n f o
Article history: Received 27 May 2014 Received in revised form 11 September 2014 Accepted 22 September 2014
Keywords: Ground source heat pump system (GSHPS) Intermittent operation Soil temperature Multiple nonlinear regressions
a b s t r a c t In this paper, the intermittent experiment of a vertical ground source heat pump (GSHP) system is investigated and the corresponding geo-temperature variations are studied. The performance of the GSHP system under intermittent operation and the comparisons of different intermittent modes are presented in the paper. The parameters of soil backfill material, air temperature and inlet volume flow rate are also investigated. Experimental results suggest that, due to the recovery in ground thermal energy in intermittent time, the heat exchange rate and the operation performance coefficient (COP) of the heat pump increases, and the compressor power decreases in the successive working. But an insufficient soil recovery time leads to a rapid decline of the performance parameters and the soil temperature. The temperature transports faster under large soil thermal conductivity conditions and the soil temperature decreases more quickly and recovers more slowly with larger inlet flow rate and lower weather temperature for different soil thermal diffusivities. Through multiple nonlinear regression analysis, a curve formula can be fitted to predict the soil temperature variations under intermittent operation of the ground source heat pump in winter, Dalian. It can be found that the soil temperature increases at an exponential function with each factor. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Because of the improvement of people’s living standards, it can be predicted that the consumption of building energy will continue to increase rapidly [1]. Being environmentally friendly and requiring low levels of maintenance, ground source heat pumps (GSHPs) have become a popular choice for space conditioning in commercial and residential facilities. The actual number of installed GSHP units worldwide was around half a million in 2000, and 1.3 million in 2007, with almost 59% and 9.7% annually increase in the United States and Europe respectively [2]. Yang [3] points that the GCHP technology can be used both in cold ⇑ Corresponding author. Tel.: +86 13591326496; fax: +86 0411 84708460. E-mail address: [email protected] (Y. Shang). http://dx.doi.org/10.1016/j.apenergy.2014.09.072 0306-2619/Ó 2014 Elsevier Ltd. All rights reserved.
and hot weather areas and the energy saving potential is significant. With regard to the performance of the heat pump units, heat transfer rate decreases as the heat transfer driving potential reduces, which consequently influences the performance coefficient of heat pump (COP). The controllable intermittent performance would intensify the heat transfer in the soil, enhance the capacity of underground heat and increase the heat economy of the ground-source heat pump system. During the last decade, there were numerous interests in the energy analysis [4–12], performance [13–20] and experiments [21–30] of the GSHP systems. Michopoulos [7] pointed that a new energy tool can be more suitable for the analysis of ground source heat pump systems. Koohi-Fayegh [12] concluded that for a specific heat flux from the bore hole wall, a borehole separation distance can be calculated for the temperature of the soil to stay
Y. Shang et al. / Applied Energy 136 (2014) 628–635
629
Nomenclature COPhp Cp Gr h IC K _ m Nu Pr QE Ta Tin
performance coefficient of the heat pump specific heat capacity of water (kJ/kg K) Grashof number the convection heat transfer coefficient (W/m2 K) the current of the compressor (A) soil thermal diffusivity (m2/s) the mass flow rate of the water antifreeze solution (kg/s) Nusselt-number Prandtl number heat extracted by heat pump in the heating mode (kJ) air temperature (K) water temperature at the ground heat exchanger inlet (K)
below a desired limit. Nam [14] conducted several case studies for the optimal operation method by calculating the coefficient of performance on various groundwater and well conditions. Hepbasli [18,19] gave the primary reason with regard to why the heating coefficient of the heat pump (COP) performance and the COP of the whole system were much lower than other heat pumps operated under or near designing conditions. Esen [23,24] suggested that the average performance coefficients of the system for horizontal ground heat exchanger in the different trenches were 2.66 and 2.81 at 1 m and 2 m depth, respectively. Kyriakis [28] proved that the energy demand of the system is significantly lower than that of conventional heating and cooling systems. The seasonal COP of the system, which has not yet been stabilized as expected due to the operation of the ground heat exchanger, is gradually increasing. However, the influencing factors such as air temperature, inlet flow rate were not taken into account in their experiment, and the regression expression which can be used to predict the soil temperature variation under the intermittent operation was rarely presented in the previous studies. During the batch operation of ground source heat pump system, the performance characteristics of the unit can be improved by reasonable intermittent control, which depends on the soil temperature variation. The regression formula could forecast the temperature variation extent, and is indeed very important for the heat pump system. This paper presents an intermittent experiment of heating mode from November to March in the heating seasons of 2011–2013. Based on the experimental data, the influence of soil backfill material, U-tube inlet flow rate, air temperature on soil temperature and performance parameters is analyzed, and a curve formula is fitted through multiple nonlinear regressions by the commercial optimizing software package 1stOptÒ, which can give good predictions on soil temperature variations under the intermittent operation of heat pump system in heating mode in the Dalian city.
2. System description 2.1. Experimental set-up The ground source heat pump system was installed in Dalian University of Technology. The schematic diagram of the constructed experimental system is illustrated in Fig. 1. The system mainly consists of four components: (1) underground U tube heat exchanger, (2) heat pump unit, (3) air conditioning unit, (4) auxiliary equipment (including water collector/ separator, pumps, etc), and three separate circuits: (a) the ground
Tout Uc
v0
W
water temperature at the U tube ground heat exchanger outlet (K) the voltage of the compressor (V) the velocity of the inlet (m/s) the power input to the compressor (kJ)
Greek symbols cos u power factor Subscripts c compressor hp heat pump in inlet out outlet
heat exchanger circuit, (b) the heat pump circuit, (c) the air conditioning circuit. In the heating mode, heat is absorbed by the U-bend heat exchanger, where water solution works as the medium, from the underground soil, and transported through the U tube, water separator, cooling water pump and finally arrives at the heat pump unit. The carried heat is released to the refrigerant in the heat pump unit, and the refrigerant is subsequently evaporated. After a series of complicated refrigerant state-changes in the heat pump unit, the heat is intensified and then transported to the water solution in the air conditioning circuit side by the plate heat exchanger. Through these cycles, the heat can be finally transferred to terminal heat users at the air conditioning circuit side. It is noted that the working medium is collected and recycled within all the above flowing circuits. The type of the household heat pump unit is HSSWR-23(S), which is produced by Tsinghua Artificial Environment Co., Ltd. There are 9 underground U tubes with 7 pieces of 50 m depth, 1 piece of 75 m depth and 25 m depth respectively. 12 temperature-measuring wells are distributed around the U tube, with the depth of 70 m; the detailed arrangement of temperature measurement points is given in Fig. 2. Two of the 50 m shafts are backfilled with sandy and sandy clay respectively, others are backfilled with clay. The material of the U tube is HDPE (High-density Polyethylene). The diameter of the U tube, drill well and Temperature-measuring well is 32 mm, 110 mm and 110 mm respectively. 2.2. Measurement system In the experiment, the measurement system consists of the following parts: a. PT100 thermal resistance of copper constantan 3 is utilized for temperature measurement with the permissible error ±0.15 K. The mining control system is applied in the parametric tests, which collects and stores data by the Luban R software every 5 min. b. The voltages and amperes put into the compressor are measured with universal electric meter every 5 min. c. The mass flow rate of the water antifreeze solution is measured by ultrasonic flow meter. d. The ambient atmospheric temperature and pressure are obtained by thermometer and barometer. 2.3. Uncertainty analysis Measurements of the variables are influenced by a number of elemental error sources – such as the ambient temperatures, flow
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Fig. 1. The schematic diagram of the constructed experimental system.
Fig. 2. The distribution of the U tube and temperature measured well.
rates, pressure drops, and others. In order to prove the accuracy of the experiments, uncertainty analysis is performed using the method described by Coleman [23]. The uncertainties of wR is calculated by
" wR ¼
@R w1 @x1
2
þ
@R w2 @x2
2
þ þ
@R wn @xn
2 #1=2 ð1Þ
where, R is a given function of the independent variables x1, x2,. . ., xn, w1, w2,. . ., wn are the uncertainties of the independent variables.
The total uncertainty in the measurement of the independent variables w1 may be calculated as follows [24,25].
1=2 w1 ¼ w211 þ w212 þ þ w21n
ð2Þ
where, w11, w12,. . ., w1n are the uncertainties of the reading, system, and others. In the present study, the temperatures, flow rates, pressure drops, voltages and amperes were measured with appropriate
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Y. Shang et al. / Applied Energy 136 (2014) 628–635 Table 1 Total uncertainty of the measured parameters. Description
Unit
Total uncertainty (%)
Temperature of water antifreeze solution at ground heat exchanger inlet Temperature of water antifreeze solution at ground heat exchanger outlet Supply water temperature of heat pump unit Return water temperature of heat pump unit Outdoor air temperature Indoor air temperature Supply water temperature of plate heat exchanger Return water temperature of plate heat exchanger Soil temperature in depth and level Volumetric flow rate of water/antifreeze solution Mass flow rate of the water antifreeze solution Current of the compressor Voltage of the compressor Atmospheric pressure Power factor Heat extracted by heat pump in the heating mode Heat transfer rate The power input to the compressor The water-antifreeze circulating pump The condenser fan COP of the heat pump COP of the whole system
K K K K K K K K K m 3/h kg/s A V mbar
1.07 1.07 1.07 1.07 1.43 1.43 1.07 1.07 1.07 2.79 2.8 1.12 1.12 1.01 1 2.98 2.98 2.02 2.02 2.02 3.61 4.6
kJ kW kJ kJ kJ
instruments explained previously. All the uncertainties considered in the present study are presented in Table 1. 3. Processing of experimental results The performance coefficient of the heat pump can be calculated by the following equation.
COP hp ¼ ðQ E þ W C Þ=W C
ð3Þ
where QE is the heat extracted by heat pump in the heating mode, and WC is the power input to the compressor. QE is calculated as
_ P ðT out T in Þ Q E ¼ mC
ð4Þ
_ is the mass flow rate of the water antifreeze solution, CP is where m the specific heat capacity of water, Tout is the water temperature at the U tube ground heat exchanger outlet, and Tin is the water temperature at the ground heat exchanger inlet. The power input to the compressor WC can be defined as
W C ¼ IC U C cos u
Fig. 3. Experimental results of the heat pump performance characteristic (working conditions: v0 = 0.42 m/s, Ta = 273 K, backfill soil is clay).
ð5Þ
IC is the current of the compressor, UC is the voltage of the compressor, and cos u is the power factor.
IC ¼
pffiffiffi 3 ðIC1 þ IC2 þ IC3 Þ 9
ð6Þ
IC1, IC2, IC3 are the line currents measured by universal electric meter. 4. Results and discussions Experiments with heating mode were conducted under different working conditions for the time period from November 2011 to March 2013. The energy performance of the GSHP system and the soil temperature variations analysis are given as below. 4.1. The intermittent operation Figs. 3 and 4 show the experimental results of the heat pump characteristic and the heat exchange rate when the heat pump runs for 12 h and stops for 6 h in 4 days. The heat exchange rate points that the heat extracted by heat pump in the heating mode
Fig. 4. Experimental results of the heat exchange rate (working conditions: v0 = 0.42 m/s, Ta = 273 K, backfill soil is clay).
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Fig. 5. The soil temperature under different intermittent mode (working conditions: v0 = 0.42 m/s, Ta = 273 K, backfill soil is clay mode 1: 12 h operation, 6 h downtime, mode 2: 12 h operation, 8 h downtime, mode 3: 12 h operation, 10 h downtime and mode 4: 12 h operation, 12 h downtime).
per unit time. When the heat pump is running, the heat exchange rate and the COP of the heat pump are decreasing and the compressor power is increasing due to the reduction in ground thermal energy. Then all of the above parameters can be recovered because of the heat transfer between the nearby soil and the distant soil while the heat pump is shutdown. As is illustrated, the heat exchange rate and the COP of the heat pump are becoming smaller and the compressor power is becoming larger every time the heat pump starts up. This is because the recovery time of soil temperature may be not sufficient for the soil to reach its initial temperature, which will in turn result in the decreasing of geothermal energy around. 4.2. The intermittent operation under different intermittent mode Fig. 5 shows the soil temperature variation under different intermittent mode, and detailed mode description is given in Fig. 5 (The soil temperature in all the pictures are 35 m depth underground should no special annotation.) The GSHP system runs three times respectively under each mode. As is indicated, under the longer recovery time mode, a relatively lower soil temperature drop and a higher temperature rise could be obtained during the intermittent operation of the heat pump, which would result in a preferable operating characteristic for the heat pump system. The difference between the initial and the last recovery temperature is about 1.2 K under the first mode, 0.47 K under the second mode, 0.16 K under the third mode, and 0.12 K under the forth mode. It can be seen that the third mode gives approximately the same temperature difference as the finest forth mode, so it is the optimum intermittent time which is adequate to conduct the operation of heat pump system considering both operating characteristics and practical time cost compared with the other three modes. Therefore, it is unnecessary to have a very long time interval to reach the initial temperature when the intermittent time attains optimum, and how to obtain the optimum intermittent time is significant for the working of the ground source heat pump system. 4.3. The influencing factor 4.3.1. Backfill material The effect of backfill material on the soil temperature is provided in Fig. 6. It reveals that during the operation of the heat
Fig. 6. The soil temperature variation with different backfill material (working conditions: v0 = 0.42 m/s, Ta = 273 K).
Table 2 The physical properties of backfill soil. Material
Thermal conductivity (W/m K)
Volumetric heat capacity (J m3 K1)
Thermal diffusivity (m2/s)
Sandy clay Clay Sandy
1.08 0.86 1.16
4.35 3.31 3.34
0.0025 0.0023 0.00346
pump, the soil temperature descends most rapidly within the backfill material of clay due to its smallest heat capacity and thermal conductivity. In the first 2 h, the soil temperature decreases most slowly within the backfill material of sandy clay because of its largest heat capacity, but then it decreases more quickly than sandy backfill material, still more slowly than clay. In the ground temperature recovery process, the soil temperature within the sandy backfill material recovers more quickly than others. The main reason may be that different materials have different thermal diffusivity, which can lead to the various temperature transfer abilities, as shown in Table 2. The larger the thermal diffusivity is, the faster the temperature transports. The thermal diffusivity can be expressed as follows:
K ¼ k=C V
ð7Þ
where k is soil thermal conductivity, and CV is volumetric thermal capacity. Therefore, the optima backfill material for the ground source heat pump system is the soil with large thermal conductivity and thermal diffusivity. 4.3.2. Inlet flow rate Another important conclusion regarding the inlet flow rate is revealed in Fig. 7. As can be seen, in the first 5 h operation, the increase of the inlet flow rate from 2.7 m3/h to 4 m3/h leads to a growth of heat exchange rate, and the heat exchange rate decreased with the heat pump running afterward, especially for high flow rate cases. This is because that a improvement in inlet flow rate will result in the aggravation of flow turbulence in tube, and the heat exchange rate increases significantly as the convective heat transfer coefficient increases in the initial period. Meanwhile, the geothermal energy around the tube reduces, the heat transfer rate decreases as the temperature difference between the tube and soil decreases soon afterwards. Therefore, the soil temperature decreases more quickly and recovers more slowly
Y. Shang et al. / Applied Energy 136 (2014) 628–635
Fig. 7. The heat exchange rate with different inlet flow rate (working conditions: Ta = 273 K, backfill soil is clay).
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Fig. 9. The soil temperature variation with different weather temperature (working conditions: v0 = 0.42 m/s, backfill soil is clay).
4.4. The curve of the temperature variation
Fig. 8. The soil temperature variation with different inlet flow rate (working conditions: Ta = 273 K, backfill soil is clay).
when the inlet flow rate is larger under the intermittent operation, as shown in Fig. 8. 4.3.3. Weather temperature The effect of weather temperature on the soil temperature is illustrated in Fig. 9. It reveals that when the weather temperature is low, soil temperature decreases more quickly under the operation of the ground-source heat pump system, and recovers more slowly during the intermittent time. The main reason may be the increase of temperature difference caused by the decreased air temperature. The convection coefficient (Ignored the influence of the wind velocity) can be calculated by
hl ¼ Nu ¼ CðGrPrÞn k
ð8Þ
where Nu is Nusselt-number, C is 0.54 and 0.58 for heating and cooling, respectively [6]. Gr is Grashof number; Pr is Prandtl number, l is characteristic length, n is a coefficient that decided by the value of Gr. In this paper, the value of n is 1/3. Both of the increases lead to an increase in the heat flux. Therefore, the heat taken away by air increases, soil temperature decreases quickly and recovers slowly.
Based on the above analysis, the soil temperature variation is important to the intermittent operation of the GSHP system, which can be influenced by certain factors. In order to predict the soil temperature, seek a reasonable interval time, a regression expression of soil temperature variation under the heat pump system intermittent operation in heating mode in Dalian city based on the experimental date is presented. The date used is 1.05 m from the U-tube with the depth less than 5 m below ground under different conditions in winter. The formula is fitting through multiple nonlinear regressions by using 1stOpt. 1stOpt is commercialism software, applies to nonlinear regression, curve fitting, nonlinear model parameter estimation, the core algorithm of which is Universal Global Optimization (UGO). The effects of backfill material, flow rate and weather temperature on soil temperature are considered. It can be found that the functional relationship between soil temperature and each factor is exponential based on the experiment results. Therefore, the expressions can be fitted for two processes. When the heat pump operates, the formula can be described as
Y ¼ a1 þ a2 expða3 x1 Þ þ a4 expða5 x2 Þ þ a6 expða7 x3 Þ þ a8 expða9 x4 Þ þ a10 expða11 x5 Þ
ð9Þ
where x1 is the operation time, x2 is the soil thermal diffusivity, x3 is the inlet flow rate, x4 is the air temperature, x5 is the soil initial temperature, a1–a11 is the coefficient, and Y is the soil temperature. When the heat pump stops working, the formula can be given as
Y ¼ b1 þ b2 expðb3 z1 Þ þ b4 expðb5 z2 Þ þ b6 expðb7 z3 Þ þ b8 expðb9 z4 Þ ð10Þ where z1 is the recovery time, z2 is the soil thermal diffusivity, z3 is the air temperature, z4 is the soil initial temperature of recovery, b1–b9 is the coefficient, and Y is the soil temperature. Through a large number of multiple nonlinear regressions, the parameters value of a1–a11 and b1–b9 can be given as following Table 3. In order to verify the reliability of the expression, 120 data of operation and 120 data of recovery are selected randomly for comparison. The maximum error between the calculated value and the experimental date is 0.42 K and 0.38 K of operation and recovery process respectively, the minimum error is 0.0003 K and 0.001 K,
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Table 3 The parameters value of a1–a11 and b1–b9. Parameters
Value
Parameters
Value
a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11
1735.695 4.513 0.102 7620.326 4336.975 423.682 0.0008 1546.589 8.05E06 0.189 0.019
b1 b2 b3 b4 b5 b6 b7 b8 b9
1952.151 4.475 0.202 5.88E21 12599.086 8357460.41 7.04E02 1970.545 4.52E04
a
the effects of soil backfill material, U-tube inlet volume flow rate, air temperature on soil temperature and performance parameters are analyzed, and regression expressions of soil temperature are fitted to predict the geo-temperature distribution at each moment under the intermittent operation of ground-source heat pump system in heating mode. The following conclusions can be drawn from the experiments. (1) The optimum intermittent time is important to the intermittent operation of GSHP system, and the insufficient soil recovery time could result in the rapid decline of performance parameters and soil temperature in the follow-up working; but unusually longer recovery time could lead to waste of resources under intermittent operation. (2) The temperature transports faster when the soil thermal diffusivity is larger, therefore, the optimum backfill material for the ground source heat pump system is that with large heat capacity and thermal diffusivity. (3) The soil temperature decreases more quickly and recovers more slowly when the inlet flow rate is larger and the weather temperature is lower under the intermittent operation in heating mode, and the larger flow rate could obtain higher heat exchange rate in the first 5 h. (4) The regression formula presented in this paper can be used to predict the soil temperature variation under the intermittent operation of the ground source heat pump in winter, Dalian.
Acknowledgement It is gratefully acknowledged that this work is sponsored by Liaoning Province Education Administration of China (L2013029).
b
Fig. 10. The comparison of the experimental results and calculated results (a) operation process; and (b) recovery process.
and the average error is 0.096 K and 0.088 K separately, as is shown in Fig. 10a and b. Therefore, the regression formula can be used to predict the soil temperature variation, and to look for the optimum interval time for the intermittent operation of the GSHP system in winter, Dalian. 5. Conclusions In this paper, intermittent experiments of heating mode from November to March in heating season of 2011–2013 are presented,
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Contents lists available at ScienceDirect
Applied Energy journal homepage: www.elsevier.com/locate/apenergy
Intermittent experimental study of a vertical ground source heat pump system Yan Shang ⇑, Ming Dong, Sufen Li Key Lab. of Ocean Energy Utilization and Energy Conservation of Ministry of Education, Dalian University of Technology, Dalian 116024, PR China
h i g h l i g h t s We studied the intermittent operation of a GSHP system with experimental method. The influence of factors on geo-temperature and performance parameters is analyzed. Soil temperature transports faster when the soil thermal diffusivity is larger. Soil temperature varies quickly with larger inlet flow rate and weather temperature. Fitted formula will predict geo-temperature variations under intermittent operation.
a r t i c l e
i n f o
Article history: Received 27 May 2014 Received in revised form 11 September 2014 Accepted 22 September 2014
Keywords: Ground source heat pump system (GSHPS) Intermittent operation Soil temperature Multiple nonlinear regressions
a b s t r a c t In this paper, the intermittent experiment of a vertical ground source heat pump (GSHP) system is investigated and the corresponding geo-temperature variations are studied. The performance of the GSHP system under intermittent operation and the comparisons of different intermittent modes are presented in the paper. The parameters of soil backfill material, air temperature and inlet volume flow rate are also investigated. Experimental results suggest that, due to the recovery in ground thermal energy in intermittent time, the heat exchange rate and the operation performance coefficient (COP) of the heat pump increases, and the compressor power decreases in the successive working. But an insufficient soil recovery time leads to a rapid decline of the performance parameters and the soil temperature. The temperature transports faster under large soil thermal conductivity conditions and the soil temperature decreases more quickly and recovers more slowly with larger inlet flow rate and lower weather temperature for different soil thermal diffusivities. Through multiple nonlinear regression analysis, a curve formula can be fitted to predict the soil temperature variations under intermittent operation of the ground source heat pump in winter, Dalian. It can be found that the soil temperature increases at an exponential function with each factor. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Because of the improvement of people’s living standards, it can be predicted that the consumption of building energy will continue to increase rapidly [1]. Being environmentally friendly and requiring low levels of maintenance, ground source heat pumps (GSHPs) have become a popular choice for space conditioning in commercial and residential facilities. The actual number of installed GSHP units worldwide was around half a million in 2000, and 1.3 million in 2007, with almost 59% and 9.7% annually increase in the United States and Europe respectively [2]. Yang [3] points that the GCHP technology can be used both in cold ⇑ Corresponding author. Tel.: +86 13591326496; fax: +86 0411 84708460. E-mail address: [email protected] (Y. Shang). http://dx.doi.org/10.1016/j.apenergy.2014.09.072 0306-2619/Ó 2014 Elsevier Ltd. All rights reserved.
and hot weather areas and the energy saving potential is significant. With regard to the performance of the heat pump units, heat transfer rate decreases as the heat transfer driving potential reduces, which consequently influences the performance coefficient of heat pump (COP). The controllable intermittent performance would intensify the heat transfer in the soil, enhance the capacity of underground heat and increase the heat economy of the ground-source heat pump system. During the last decade, there were numerous interests in the energy analysis [4–12], performance [13–20] and experiments [21–30] of the GSHP systems. Michopoulos [7] pointed that a new energy tool can be more suitable for the analysis of ground source heat pump systems. Koohi-Fayegh [12] concluded that for a specific heat flux from the bore hole wall, a borehole separation distance can be calculated for the temperature of the soil to stay
Y. Shang et al. / Applied Energy 136 (2014) 628–635
629
Nomenclature COPhp Cp Gr h IC K _ m Nu Pr QE Ta Tin
performance coefficient of the heat pump specific heat capacity of water (kJ/kg K) Grashof number the convection heat transfer coefficient (W/m2 K) the current of the compressor (A) soil thermal diffusivity (m2/s) the mass flow rate of the water antifreeze solution (kg/s) Nusselt-number Prandtl number heat extracted by heat pump in the heating mode (kJ) air temperature (K) water temperature at the ground heat exchanger inlet (K)
below a desired limit. Nam [14] conducted several case studies for the optimal operation method by calculating the coefficient of performance on various groundwater and well conditions. Hepbasli [18,19] gave the primary reason with regard to why the heating coefficient of the heat pump (COP) performance and the COP of the whole system were much lower than other heat pumps operated under or near designing conditions. Esen [23,24] suggested that the average performance coefficients of the system for horizontal ground heat exchanger in the different trenches were 2.66 and 2.81 at 1 m and 2 m depth, respectively. Kyriakis [28] proved that the energy demand of the system is significantly lower than that of conventional heating and cooling systems. The seasonal COP of the system, which has not yet been stabilized as expected due to the operation of the ground heat exchanger, is gradually increasing. However, the influencing factors such as air temperature, inlet flow rate were not taken into account in their experiment, and the regression expression which can be used to predict the soil temperature variation under the intermittent operation was rarely presented in the previous studies. During the batch operation of ground source heat pump system, the performance characteristics of the unit can be improved by reasonable intermittent control, which depends on the soil temperature variation. The regression formula could forecast the temperature variation extent, and is indeed very important for the heat pump system. This paper presents an intermittent experiment of heating mode from November to March in the heating seasons of 2011–2013. Based on the experimental data, the influence of soil backfill material, U-tube inlet flow rate, air temperature on soil temperature and performance parameters is analyzed, and a curve formula is fitted through multiple nonlinear regressions by the commercial optimizing software package 1stOptÒ, which can give good predictions on soil temperature variations under the intermittent operation of heat pump system in heating mode in the Dalian city.
2. System description 2.1. Experimental set-up The ground source heat pump system was installed in Dalian University of Technology. The schematic diagram of the constructed experimental system is illustrated in Fig. 1. The system mainly consists of four components: (1) underground U tube heat exchanger, (2) heat pump unit, (3) air conditioning unit, (4) auxiliary equipment (including water collector/ separator, pumps, etc), and three separate circuits: (a) the ground
Tout Uc
v0
W
water temperature at the U tube ground heat exchanger outlet (K) the voltage of the compressor (V) the velocity of the inlet (m/s) the power input to the compressor (kJ)
Greek symbols cos u power factor Subscripts c compressor hp heat pump in inlet out outlet
heat exchanger circuit, (b) the heat pump circuit, (c) the air conditioning circuit. In the heating mode, heat is absorbed by the U-bend heat exchanger, where water solution works as the medium, from the underground soil, and transported through the U tube, water separator, cooling water pump and finally arrives at the heat pump unit. The carried heat is released to the refrigerant in the heat pump unit, and the refrigerant is subsequently evaporated. After a series of complicated refrigerant state-changes in the heat pump unit, the heat is intensified and then transported to the water solution in the air conditioning circuit side by the plate heat exchanger. Through these cycles, the heat can be finally transferred to terminal heat users at the air conditioning circuit side. It is noted that the working medium is collected and recycled within all the above flowing circuits. The type of the household heat pump unit is HSSWR-23(S), which is produced by Tsinghua Artificial Environment Co., Ltd. There are 9 underground U tubes with 7 pieces of 50 m depth, 1 piece of 75 m depth and 25 m depth respectively. 12 temperature-measuring wells are distributed around the U tube, with the depth of 70 m; the detailed arrangement of temperature measurement points is given in Fig. 2. Two of the 50 m shafts are backfilled with sandy and sandy clay respectively, others are backfilled with clay. The material of the U tube is HDPE (High-density Polyethylene). The diameter of the U tube, drill well and Temperature-measuring well is 32 mm, 110 mm and 110 mm respectively. 2.2. Measurement system In the experiment, the measurement system consists of the following parts: a. PT100 thermal resistance of copper constantan 3 is utilized for temperature measurement with the permissible error ±0.15 K. The mining control system is applied in the parametric tests, which collects and stores data by the Luban R software every 5 min. b. The voltages and amperes put into the compressor are measured with universal electric meter every 5 min. c. The mass flow rate of the water antifreeze solution is measured by ultrasonic flow meter. d. The ambient atmospheric temperature and pressure are obtained by thermometer and barometer. 2.3. Uncertainty analysis Measurements of the variables are influenced by a number of elemental error sources – such as the ambient temperatures, flow
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Fig. 1. The schematic diagram of the constructed experimental system.
Fig. 2. The distribution of the U tube and temperature measured well.
rates, pressure drops, and others. In order to prove the accuracy of the experiments, uncertainty analysis is performed using the method described by Coleman [23]. The uncertainties of wR is calculated by
" wR ¼
@R w1 @x1
2
þ
@R w2 @x2
2
þ þ
@R wn @xn
2 #1=2 ð1Þ
where, R is a given function of the independent variables x1, x2,. . ., xn, w1, w2,. . ., wn are the uncertainties of the independent variables.
The total uncertainty in the measurement of the independent variables w1 may be calculated as follows [24,25].
1=2 w1 ¼ w211 þ w212 þ þ w21n
ð2Þ
where, w11, w12,. . ., w1n are the uncertainties of the reading, system, and others. In the present study, the temperatures, flow rates, pressure drops, voltages and amperes were measured with appropriate
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Y. Shang et al. / Applied Energy 136 (2014) 628–635 Table 1 Total uncertainty of the measured parameters. Description
Unit
Total uncertainty (%)
Temperature of water antifreeze solution at ground heat exchanger inlet Temperature of water antifreeze solution at ground heat exchanger outlet Supply water temperature of heat pump unit Return water temperature of heat pump unit Outdoor air temperature Indoor air temperature Supply water temperature of plate heat exchanger Return water temperature of plate heat exchanger Soil temperature in depth and level Volumetric flow rate of water/antifreeze solution Mass flow rate of the water antifreeze solution Current of the compressor Voltage of the compressor Atmospheric pressure Power factor Heat extracted by heat pump in the heating mode Heat transfer rate The power input to the compressor The water-antifreeze circulating pump The condenser fan COP of the heat pump COP of the whole system
K K K K K K K K K m 3/h kg/s A V mbar
1.07 1.07 1.07 1.07 1.43 1.43 1.07 1.07 1.07 2.79 2.8 1.12 1.12 1.01 1 2.98 2.98 2.02 2.02 2.02 3.61 4.6
kJ kW kJ kJ kJ
instruments explained previously. All the uncertainties considered in the present study are presented in Table 1. 3. Processing of experimental results The performance coefficient of the heat pump can be calculated by the following equation.
COP hp ¼ ðQ E þ W C Þ=W C
ð3Þ
where QE is the heat extracted by heat pump in the heating mode, and WC is the power input to the compressor. QE is calculated as
_ P ðT out T in Þ Q E ¼ mC
ð4Þ
_ is the mass flow rate of the water antifreeze solution, CP is where m the specific heat capacity of water, Tout is the water temperature at the U tube ground heat exchanger outlet, and Tin is the water temperature at the ground heat exchanger inlet. The power input to the compressor WC can be defined as
W C ¼ IC U C cos u
Fig. 3. Experimental results of the heat pump performance characteristic (working conditions: v0 = 0.42 m/s, Ta = 273 K, backfill soil is clay).
ð5Þ
IC is the current of the compressor, UC is the voltage of the compressor, and cos u is the power factor.
IC ¼
pffiffiffi 3 ðIC1 þ IC2 þ IC3 Þ 9
ð6Þ
IC1, IC2, IC3 are the line currents measured by universal electric meter. 4. Results and discussions Experiments with heating mode were conducted under different working conditions for the time period from November 2011 to March 2013. The energy performance of the GSHP system and the soil temperature variations analysis are given as below. 4.1. The intermittent operation Figs. 3 and 4 show the experimental results of the heat pump characteristic and the heat exchange rate when the heat pump runs for 12 h and stops for 6 h in 4 days. The heat exchange rate points that the heat extracted by heat pump in the heating mode
Fig. 4. Experimental results of the heat exchange rate (working conditions: v0 = 0.42 m/s, Ta = 273 K, backfill soil is clay).
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Fig. 5. The soil temperature under different intermittent mode (working conditions: v0 = 0.42 m/s, Ta = 273 K, backfill soil is clay mode 1: 12 h operation, 6 h downtime, mode 2: 12 h operation, 8 h downtime, mode 3: 12 h operation, 10 h downtime and mode 4: 12 h operation, 12 h downtime).
per unit time. When the heat pump is running, the heat exchange rate and the COP of the heat pump are decreasing and the compressor power is increasing due to the reduction in ground thermal energy. Then all of the above parameters can be recovered because of the heat transfer between the nearby soil and the distant soil while the heat pump is shutdown. As is illustrated, the heat exchange rate and the COP of the heat pump are becoming smaller and the compressor power is becoming larger every time the heat pump starts up. This is because the recovery time of soil temperature may be not sufficient for the soil to reach its initial temperature, which will in turn result in the decreasing of geothermal energy around. 4.2. The intermittent operation under different intermittent mode Fig. 5 shows the soil temperature variation under different intermittent mode, and detailed mode description is given in Fig. 5 (The soil temperature in all the pictures are 35 m depth underground should no special annotation.) The GSHP system runs three times respectively under each mode. As is indicated, under the longer recovery time mode, a relatively lower soil temperature drop and a higher temperature rise could be obtained during the intermittent operation of the heat pump, which would result in a preferable operating characteristic for the heat pump system. The difference between the initial and the last recovery temperature is about 1.2 K under the first mode, 0.47 K under the second mode, 0.16 K under the third mode, and 0.12 K under the forth mode. It can be seen that the third mode gives approximately the same temperature difference as the finest forth mode, so it is the optimum intermittent time which is adequate to conduct the operation of heat pump system considering both operating characteristics and practical time cost compared with the other three modes. Therefore, it is unnecessary to have a very long time interval to reach the initial temperature when the intermittent time attains optimum, and how to obtain the optimum intermittent time is significant for the working of the ground source heat pump system. 4.3. The influencing factor 4.3.1. Backfill material The effect of backfill material on the soil temperature is provided in Fig. 6. It reveals that during the operation of the heat
Fig. 6. The soil temperature variation with different backfill material (working conditions: v0 = 0.42 m/s, Ta = 273 K).
Table 2 The physical properties of backfill soil. Material
Thermal conductivity (W/m K)
Volumetric heat capacity (J m3 K1)
Thermal diffusivity (m2/s)
Sandy clay Clay Sandy
1.08 0.86 1.16
4.35 3.31 3.34
0.0025 0.0023 0.00346
pump, the soil temperature descends most rapidly within the backfill material of clay due to its smallest heat capacity and thermal conductivity. In the first 2 h, the soil temperature decreases most slowly within the backfill material of sandy clay because of its largest heat capacity, but then it decreases more quickly than sandy backfill material, still more slowly than clay. In the ground temperature recovery process, the soil temperature within the sandy backfill material recovers more quickly than others. The main reason may be that different materials have different thermal diffusivity, which can lead to the various temperature transfer abilities, as shown in Table 2. The larger the thermal diffusivity is, the faster the temperature transports. The thermal diffusivity can be expressed as follows:
K ¼ k=C V
ð7Þ
where k is soil thermal conductivity, and CV is volumetric thermal capacity. Therefore, the optima backfill material for the ground source heat pump system is the soil with large thermal conductivity and thermal diffusivity. 4.3.2. Inlet flow rate Another important conclusion regarding the inlet flow rate is revealed in Fig. 7. As can be seen, in the first 5 h operation, the increase of the inlet flow rate from 2.7 m3/h to 4 m3/h leads to a growth of heat exchange rate, and the heat exchange rate decreased with the heat pump running afterward, especially for high flow rate cases. This is because that a improvement in inlet flow rate will result in the aggravation of flow turbulence in tube, and the heat exchange rate increases significantly as the convective heat transfer coefficient increases in the initial period. Meanwhile, the geothermal energy around the tube reduces, the heat transfer rate decreases as the temperature difference between the tube and soil decreases soon afterwards. Therefore, the soil temperature decreases more quickly and recovers more slowly
Y. Shang et al. / Applied Energy 136 (2014) 628–635
Fig. 7. The heat exchange rate with different inlet flow rate (working conditions: Ta = 273 K, backfill soil is clay).
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Fig. 9. The soil temperature variation with different weather temperature (working conditions: v0 = 0.42 m/s, backfill soil is clay).
4.4. The curve of the temperature variation
Fig. 8. The soil temperature variation with different inlet flow rate (working conditions: Ta = 273 K, backfill soil is clay).
when the inlet flow rate is larger under the intermittent operation, as shown in Fig. 8. 4.3.3. Weather temperature The effect of weather temperature on the soil temperature is illustrated in Fig. 9. It reveals that when the weather temperature is low, soil temperature decreases more quickly under the operation of the ground-source heat pump system, and recovers more slowly during the intermittent time. The main reason may be the increase of temperature difference caused by the decreased air temperature. The convection coefficient (Ignored the influence of the wind velocity) can be calculated by
hl ¼ Nu ¼ CðGrPrÞn k
ð8Þ
where Nu is Nusselt-number, C is 0.54 and 0.58 for heating and cooling, respectively [6]. Gr is Grashof number; Pr is Prandtl number, l is characteristic length, n is a coefficient that decided by the value of Gr. In this paper, the value of n is 1/3. Both of the increases lead to an increase in the heat flux. Therefore, the heat taken away by air increases, soil temperature decreases quickly and recovers slowly.
Based on the above analysis, the soil temperature variation is important to the intermittent operation of the GSHP system, which can be influenced by certain factors. In order to predict the soil temperature, seek a reasonable interval time, a regression expression of soil temperature variation under the heat pump system intermittent operation in heating mode in Dalian city based on the experimental date is presented. The date used is 1.05 m from the U-tube with the depth less than 5 m below ground under different conditions in winter. The formula is fitting through multiple nonlinear regressions by using 1stOpt. 1stOpt is commercialism software, applies to nonlinear regression, curve fitting, nonlinear model parameter estimation, the core algorithm of which is Universal Global Optimization (UGO). The effects of backfill material, flow rate and weather temperature on soil temperature are considered. It can be found that the functional relationship between soil temperature and each factor is exponential based on the experiment results. Therefore, the expressions can be fitted for two processes. When the heat pump operates, the formula can be described as
Y ¼ a1 þ a2 expða3 x1 Þ þ a4 expða5 x2 Þ þ a6 expða7 x3 Þ þ a8 expða9 x4 Þ þ a10 expða11 x5 Þ
ð9Þ
where x1 is the operation time, x2 is the soil thermal diffusivity, x3 is the inlet flow rate, x4 is the air temperature, x5 is the soil initial temperature, a1–a11 is the coefficient, and Y is the soil temperature. When the heat pump stops working, the formula can be given as
Y ¼ b1 þ b2 expðb3 z1 Þ þ b4 expðb5 z2 Þ þ b6 expðb7 z3 Þ þ b8 expðb9 z4 Þ ð10Þ where z1 is the recovery time, z2 is the soil thermal diffusivity, z3 is the air temperature, z4 is the soil initial temperature of recovery, b1–b9 is the coefficient, and Y is the soil temperature. Through a large number of multiple nonlinear regressions, the parameters value of a1–a11 and b1–b9 can be given as following Table 3. In order to verify the reliability of the expression, 120 data of operation and 120 data of recovery are selected randomly for comparison. The maximum error between the calculated value and the experimental date is 0.42 K and 0.38 K of operation and recovery process respectively, the minimum error is 0.0003 K and 0.001 K,
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Table 3 The parameters value of a1–a11 and b1–b9. Parameters
Value
Parameters
Value
a1 a2 a3 a4 a5 a6 a7 a8 a9 a10 a11
1735.695 4.513 0.102 7620.326 4336.975 423.682 0.0008 1546.589 8.05E06 0.189 0.019
b1 b2 b3 b4 b5 b6 b7 b8 b9
1952.151 4.475 0.202 5.88E21 12599.086 8357460.41 7.04E02 1970.545 4.52E04
a
the effects of soil backfill material, U-tube inlet volume flow rate, air temperature on soil temperature and performance parameters are analyzed, and regression expressions of soil temperature are fitted to predict the geo-temperature distribution at each moment under the intermittent operation of ground-source heat pump system in heating mode. The following conclusions can be drawn from the experiments. (1) The optimum intermittent time is important to the intermittent operation of GSHP system, and the insufficient soil recovery time could result in the rapid decline of performance parameters and soil temperature in the follow-up working; but unusually longer recovery time could lead to waste of resources under intermittent operation. (2) The temperature transports faster when the soil thermal diffusivity is larger, therefore, the optimum backfill material for the ground source heat pump system is that with large heat capacity and thermal diffusivity. (3) The soil temperature decreases more quickly and recovers more slowly when the inlet flow rate is larger and the weather temperature is lower under the intermittent operation in heating mode, and the larger flow rate could obtain higher heat exchange rate in the first 5 h. (4) The regression formula presented in this paper can be used to predict the soil temperature variation under the intermittent operation of the ground source heat pump in winter, Dalian.
Acknowledgement It is gratefully acknowledged that this work is sponsored by Liaoning Province Education Administration of China (L2013029).
b
Fig. 10. The comparison of the experimental results and calculated results (a) operation process; and (b) recovery process.
and the average error is 0.096 K and 0.088 K separately, as is shown in Fig. 10a and b. Therefore, the regression formula can be used to predict the soil temperature variation, and to look for the optimum interval time for the intermittent operation of the GSHP system in winter, Dalian. 5. Conclusions In this paper, intermittent experiments of heating mode from November to March in heating season of 2011–2013 are presented,
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