Simulation and performance research of absorption heat pump unit based on R134a-DMF working fluid pair

Abstract

R134a-DMF absorption heat pump unit is an energy-saving heat pump unit that can utilize renewable energy, and has great potential in the refrigeration and heating fields of urban and rural areas. The purpose of this article is to conduct in-depth research on the dynamic characteristics of absorption heat pump units based on R134a-DMF, a new working fluid pair. A mathematical model of the thermophysical properties of the R134a-DMF working fluid pair and the mathematical models of various components of the heat pump unit are constructed. This paper constructs a simulation program, and uses the Control variates to study the change trend of the Coefficient of performance of R134a-DMF absorption heat pump unit affected by the generator outlet concentrated solution temperature, condenser air volume and temperature rise, and chilled water outlet temperature. The results indicate that the established mathematical model for thermophysical properties and the unit model are both accurate models, which can provide guidance for the actual operation and optimization of R134a-DMF absorption heat pump units. Through simulation, it can be concluded that for the three combined forms of R134a DMF (3:2), R134a DMF (1:1), and R134a DMF (2:3), the average increase in COP and refrigeration capacity is 0.85 %, 0.39 96, and 0.42 % for each 1 °C increase in the outlet solution of the generator, and the growth rate is relatively slow. The larger the proportion of refrigerant in the binary solution, the greater the COP of the unit under the same operating conditions.

Headnote

ABSTRACT

R134a-DMF absorption heat pump unit is an energy-saving heat pump unit that can utilize renewable energy, and has great potential in the refrigeration and heating fields of urban and rural areas. The purpose of this article is to conduct in-depth research on the dynamic characteristics of absorption heat pump units based on R134a-DMF, a new working fluid pair. A mathematical model of the thermophysical properties of the R134a-DMF working fluid pair and the mathematical models of various components of the heat pump unit are constructed. This paper constructs a simulation program, and uses the Control variates to study the change trend of the Coefficient of performance of R134a-DMF absorption heat pump unit affected by the generator outlet concentrated solution temperature, condenser air volume and temperature rise, and chilled water outlet temperature. The results indicate that the established mathematical model for thermophysical properties and the unit model are both accurate models, which can provide guidance for the actual operation and optimization of R134a-DMF absorption heat pump units. Through simulation, it can be concluded that for the three combined forms of R134a DMF (3:2), R134a DMF (1:1), and R134a DMF (2:3), the average increase in COP and refrigeration capacity is 0.85 %, 0.39 96, and 0.42 % for each 1 °C increase in the outlet solution of the generator, and the growth rate is relatively slow. The larger the proportion of refrigerant in the binary solution, the greater the COP of the unit under the same operating conditions.

ARTICLE INFO

Keywords: R134a-DMF Mathematical model Numerical simulation Coefficient of performance

1. Introduction

Since China's reform and opening up, the rapid development of energy industry has provided a strong support for economic development, but the single energy structure and inefficient energy efficiency ratio have made environmental problems increasingly severe [1]. Since the beginning of this century, with the rapid development of China's economy, by 2020, China's total energy consumption has increased by 6.3 % compared with 2000, from 1.47 billion standard coal in 2000 to 4.98 billion standard coal in 2020 [2]. Among them, building energy consumption accounts for 20 % of the country's total energy consumption, and carbon emissions account for 51.2 % of the country's energy carbon emissions [3,4]. The energy consumption of air conditioning in buildings accounts for about 50 % of the total energy consumption of buildings [5]. Therefore, saving building air conditioning energy consumption is the top priority of current energy conservation and emission reduction work. It is also very important to study the performance of the absorption heat pump unit of the new working medium pair.

As an heat pump can use industrial waste heat waste heat, solar energy and other lowgrade heat sources as the driving force to achieve the functions of heating and cooling [6,7]. Compared with the compression heat pump technology, the absorption heat pump has many advantages such as low power consumption and friendly to the environment. Therefore, in the field of energy conservation and emission reduction, absorption heat pump technology combined with regional and environmental advantages can significantly accelerate the pace of energy conservation and emission reduction [8]. The absorption heat pump using R134a-DMF as the working fluid pair has more advantages compared to traditional working fluid pairs. Refrigerant R134a is less ozone destructive and more environmentally friendly compared to R22, R141b, and R142b [9]. The GWP of R134a is 1200, which is 43 % lower than R12, and the GWP of DMF is 156 [10,11]. Compared with NH, refrigerant, the corrosiveness of absorption heat pump units is less. At the same time, it can also realize the switching operation of absorption heat pump and electric energy driven compression heat pump. Nezu et al. [12] examined the possibility of testing R134a as a refrigerant in vapor absorption refrigeration systems (VARS) with various organic solvents and showed that the R134a-DMA and the R134a-DMF systems are considered attractive as the working-fluid pairs for the absorption refrigeration system than other R134a/absorbent systems. Yokozeki [13] studied the theoretical performance of various refrigerant-absorbent pairs in a VARS cycle employing the equations of state. R134a-DMF and R134a-DMA systems exhibit better performance, compared to other R134a-absorbent systems. The circulation ratio is less and COP is more for the R134a-DMF system compared to the R134a-DMA system. The use of R134a-DMF absorption heat pump unit can achieve peak cutting and valley filling, reduce the power supply shortage in towns and rural areas, and has great potential economic value.

At present, there are many ways to simulate the absorption heat pump. Youliang et al. [14] established a small single-effect lithium bromide absorption refrigeration system driven by solar energy through TRNSYS software. Mengjin et al. [15] established a lithium bromide refrigeration system driven by industrial waste heat through Aspen Plus software. Qiang et al. [16] systematically analyzed the design and operation of an absorption air source heat pump system using gas as the heat source, based on a heat source substitution project in a residential area and a cluster in Zhengzhou. Penghui [17] used FORTRAN language to compile the thermal physical property model of lithium bromide aqueous solution and the dynamic operation program of dualeffect lithium bromide absorption refrigeration unit. There are few researches on model building entirely through Matlab platform in China. Foreign scholars Kohlenbach and Ziegler [18] systematically proposed the model description method of single-effect lithium bromide absorption refrigerator for the first time. Ochoa [19] is committed to the dynamic simulation research of lithium bromide absorption refrigerating

machine, and proposes the q of refrigerating machine by using characteristic equation method. The thermal and physical property parameters of lithium bromide and hydrochemical pair are used in the model construction of the unit. Ceviz et al. [20] studied the importance of Heat source temperature of Water-to-Air

Heat Pumps and its influence on system and state. Afshari et al. [21] studied the influence of HFCS on compressor working conditions and system performance through experimental tests under different working conditions. Khanlari et al. [22] proposed the use of wastewater as a heat source for heat pump systems, and designed а heat recovery system to utilize the available energy in the discharged shower water. Xiaoyang [23] used Aspen Plus software to build an absorption refrigeration unit using three working medium pairs of R134aDMF, H,0-LiBr and NHz-Hz0, and explored the feasibility of the operation of the absorption refrigeration unit under the condition of low grade heat source.

Therefore, to establish the simulation model of R134a-DMF absorption heat pump unit, we must first complete the thermal physical property mathematical model of R134a-DMF working medium pair. Then the mathematical model of the absorption heat pump unit can be built and the performance of the unit can be studied.

In this paper, the heat exchanger model built by Aspen Plus software is used to obtain the thermal physical property data of R134a-DMF binary solution, and Matlab software is used to fit. At the same time, the mathematical model of absorption heat pump is established on Matlab platform. By the si data with the data, a more accurate mathematical model of the unit is obtained. On this basis, the changes of COP and cooling capacity of the unit with the concentrated solution temperature at the generator outlet, the air temperature difference at the inlet and outlet of the air-cooled condenser, the air volume and the chilled water temperature at the outlet are analyzed, and the performance of the unit is explored.

2. Working principle of R134a-DMF absorption heat pump

Absorption heat pump is a device driven by thermal energy, consisting of an evaporator, condenser, throttling device, and thermal compressor. The thermal compressor includes devices such as a generator, absorber, and solution heat exchanger. They form two circular loops, and their principle is shown in Fig. 1. One of the cycles is the refrigerant cycle (1-2-3-7-8-9-10), which is a reverse cycle. The other cycle is the absorption cycle (1-2-3-4-5-6), which is a positive cycle. Fig. 2 shows the enthalpy concentration (h- ) diagram, where the concentration represents the mass concentration of DMF in the binary solution. Fig. 3 shows the pressure enthalpy diagram, and the process corresponds to Fig. 1.

In the cycle, the high and high-pi R134a refrigerant vapor from the generator condenses in the condenser. The refrigerant vapor condenses into a high-temperature and highpressure R134a refrigerant liquid, which flows to the electronic expansion valve. After being throttled and depressurized by the expansion valve, a | and low-p R134a liquid is formed. Subsequently, it enters the evaporator, where the R134a refrigerant liquid absorbs heat and vaporizes into a low-pressure R134a refrigerant gas. Finally, the R134a refrigerant gas enters the thermal compressor for heating and pressurization to achieve circulation.

The R134a DMF binary solution only circulates between the generator and absorber. The R134a refrigerant vapor (10) at the evaporator outlet enters the absorber and is absorbed by the R134a DMF binary solution, which is then transported to the generator through a solution pump. Preheat through a solution heat exchanger. The binary solution of R134a DMF is heated and boiled by an external heat source in the generator, and R134a gas escapes (7). The escaping high-temperature and high-pressure R134a gas enters the condenser to continue refrigerant circulation. The remaining binary solution (4) flows through the solution heat exchanger and is pre cooled. After being throttled and depressurized, it returns to the absorber to continue absorbing R134a refrigerant gas from the thus the absorbent cycle.

Absorption heat pumps can not only save power consumption, but also make full use of natural energy. The main difference between it and is that the type of energy supplied is changed from electrical energy to thermal energy. At the same time, two kinds

of working medium with large difference in boiling point are used to realize the pressure raising process.

3. Mathematical model of thermal properties of R134a-DMF working medium pair

The thermophysical properties of working medium pairs are the basis of simulation and calculation of R134a-DMF absorption heat pump system. Aspen Plus 15 the most popular large-scale general process simulation system internationally. It has a wide coverage of physical property databases, including nearly 6000 pure component physical property data. And it can be applied to industrial design and scientific research processes. Using Aspen Plus software can achieve preliminary process simulation using a simple device model. Using detailed models for process balance calculations and online optimization of process flow [24]. After determining the simulation purpose, follow the following steps to establish the model and collect data:

(1) Select the units for input and output;

(2) Select chemical components;

(3) Select a method for calculating physical properties;

(4) Select appropriate components to build process models;

(5) Determine the state parameters and component composition of the input stream;

(6) Set the variables of the unit module and run the software for simulation;

(7) Output Results.

The traditional method of finding thermophysical properties is to look up the graph. However, in the face of a huge amount of data, there will be some problems such as complicated chart search process, large calculation amount and poor calculation accuracy, which is not conducive to the mathematical simulation of the system. Therefore, it is necessary to establish mathematical models for the thermal properties of R134a-DMF mixed solution, R134a gas phase and liquid phase.

3.1. Mathematical model of thermal properties of R134a-DMF binary solution

The data in this section is derived from Aspen Plus software. Because the heat exchange component used in this simulation model generator is a plate heat exchanger, Aspen Plus is used to build a simple plate heat exchanger model as shown in Fig. 4. At the same time, the heat exchange temperature of the plate heat exchanger is set to 324.15K to 358.15K, and the working condition of the plate heat exchanger is adjusted with 1K as the step length. The material parameter data of R134a-DMF mixture solution at different temperatures were collected from the output stream strand, analyzed and nonlinearly fitted using Matlab software.

In terms of Aspen Plus physical property calculation method selection, Xin [25,26] used the VLE experimental data determined by Zehioua Raouf to analyze the results of R134a-DMF binary solution. Based on the analysis results, the regression errors of RENG-ROB, NRTL and PRMHV2 thermodynamic models are compared. The average relative error of NRTL thermodynamic model is 0.276 % at 30°C. At 80°C, the mean relative error of regression pressure is 0.66 %. Therefore, NTRL is chosen as the basic calculation method of physical properties in this model. R134a-DMF binary solution fitting takes temperature as variable and 1K as step size, and selects data in the temperature range from 324.15K to 358.15K for nonlinear fitting. This paper needs to explore the effect of R134a-DMF binary solution with different ratio of R134a solution and DMF solution on the performance of the generator. Therefore, a thermophysical property model of mass flow rate, density, kinematic viscosity, enthalpy value and thermal conductivity of R134a solution and DMF solution with different proportions on saturated liquid phase was established in this section. When the ratio of R134a solution and DME solution is 3:2, the thermal properties of binary solution are fitted by rational imation and i imatis i

Use Aspen Plus to collect data on various thermophysical parameters of the working fluid in steps of 1K and collect them in Excel. Import it into Matlab for fitting.

(1) The three thermal properties of mass flow rate m = f (T), density p = f (T) and enthalpy value h = f (T) were fitted using rational approximation. Where the numerator order and denominator order are set as first order, and the fitting function is of the following form:

... (1)

where: T - Kelvin temperature, К;

f(T) - All fitted thermal properties;

P1,P2,q; - Fitting parameter.

(1) Kinematic viscosity v = f (T), dynamic viscosity и = f (7), thermal conductivity à = f (T) three thermal properties using polynomial correlation fitting, fitting function is in the following form:

where: T - Kelvin temperature, К;

f(T) - The thermal and physical parameters of refrigerant;

dı, a, a; -Fitting parameter.

3.1.1. The ratio of R134a solution to DMF solution is 3:2

Set the initial state at flow $3, set the temperature to 50°C, set the pressure to 9 bar, set the mass flow rate of refrigerant R134a to 300kg/h, and set the mass flow rate of absorbent DMF to 200kg/h. Through the simulation data of Aspen Plus, it was found that the binary solution of R134a-DMF began to appear the state of gas-liquid coexistence at 65°C. With 1K as the step size, the thermal physical property data at 20°C after gas-liquid separation, that is, the thermal physical property data between 65°C and 85°C, was used for correlation fitting. The following simulation results are obtained (Tables 1 and 2).

The liguid-phase thermophysical properties fitting data of R134aDMF binary solution in the gas-liquid separation state were compared with the original data in Aspen Plus for error analysis. The analysis results show that the average relative error of the mathematical model of thermal physical property parameters of R134a-DMF working medium pair is less than 1 %, and the maximum relative error is less than 1.5 %. Therefore, the correlation fitting in the liquid phase of R134a-DMF meets the simulation requirements.

3.1.2. The ratio of R134a solution to DMF solution is 1:1

The temperature and pressure Settings of Streaming $3 are the same as those in the previous section. Change the mass flow rate of refrigerant R134a to 250kg/h and the mass flow rate of absorbent DMF to 250kg/h. The simulation data of Aspen Plus under this condition were studied, and it was found that R134a-DMF binary solution began to appear gas-liquid coexistence at 76°C. With 1K as the step size, the thermophysical property data of 24 steps after gas-liquid separation, that is, the thermophysical property data between 76°C and 100°C, was selected for correlation fitting. Among them, the three items of mass flow, density and enthalpy value are fitted by correlation using formula (1). Kinematic viscosity, dynamic viscosity and thermal conductivity were correlated by formula (2). The following simulation results are obtained (Tables 3 and 4).

The error analysis of the liquid phase thermal properties of R134aDMF binary solution in the gas-liquid separation state was carried out. The results show that the average relative error of the mathematical model of thermal physical property parameters of R134a-DMF working medium pair is less than 0.5 %, and the maximum relative error is less than 0.55 %.

3.1.3. The ratio of R134a solution to DMF solution is 2:3

The temperature and pressure Settings of streaming S3 remain unchanged. Change the mass flow rate of refrigerant R134a to 200kg/h and the mass flow rate of absorbent DMF to 300kg/h. The simulation data of Aspen Plus under this condition were studied, and it was found that R134a-DMF binary solution began to coexist at 88°C. With the step size of 1K, the thermophysical property data of 27 steps after gas-liquid separation, that is, the thermophysical property data between 88°C and 115°C, was selected for correlation fitting. Among them, the mass flow rate and density were fitted by correlation using formula (1). Kinematic viscosity, dynamic viscosity, enthalpy value, thermal conductivity and specific heat at constant pressure were fitted using formula (2). The following simulation results are obtained (Tables 5 and 6).

The error analysis of the liquid phase thermal properties of R134aDMF binary solution in the gas-liquid separation state was carried out. The results show that the average relative error of the mathematical model of each thermal property parameter of R134a-DMF working medium pair is less than 1.3 %, and the maximum relative error is less than 2.2 %.

3.2. Mathematical model of thermal properties of refrigerant R134a

The temperature range for R134a fitting was selected for saturation temperatures from 170K to 370K. With 5K as step size, 41 groups of data in saturated gas phase and saturated liquid phase were selected for correlation fitting. For the saturated gas phase and saturated liquid phase of R134a, the thermal physical property models of pressure p, density p, enthalpy value h, specific heat capacity c, at constant volume, specific heat capacity c, at constant pressure, thermal conductivity 4, kinematic viscosity у and thermal diffusivity a were established, respectively, with temperature as the independent variable.

3.2.1. Mathematical model of thermal properties of R134a saturated gas phase

In this paper, cftool toolbox of Matlab is used to establish the mathematical model of R134a saturated gas phase thermal property parameters. The fitting association is obtained by using the least square approximation method through the function of the toolbox.

(1) In addition to the enthalpy value h = f (T), the mathematical model of the residual heat physical property parameters is fitted by using the Gaussian function of three terms. The fitting function is of the following form:

... (3)

Where: T - Kelvin temperature, К;

a,-a; - fitting parameter;

b;ı-bz - fitting parameter;

,-c3 - fitting parameter;

f(T) - the thermal and physical parameters of refrigerant .

(1) Enthalpy value h = f (T), correlation fitting using exponential function. The fitting function is of the following form:

Where: T - Kelvin temperature, K;

a,b, с, d - fitting parameter; f(T) - the thermal and physical parameters of refrigerant.

The error analysis of the fitting results of R134a on the saturated gas phase line is carried out. The results show that the average relative error of the mathematical model of each thermal property parameter is less than 3.6 % and the maximum relative error is less than 8.9 % in the saturated gas phase of R134a (Tables 7 and 8).

3.2.2. Mathematical model of thermal properties of R134a saturated liquid phase

Using the same fitting method for saturated gas phase of R134a, the correlation fitting of thermal properties of R134a solution in saturated liquid phase was carried out.

(1) Pressure р = f (T), enthalpy value h= f (T), specific heat capacity at constant volume c, = f (T), specific heat capacity at constant pressure ср= f (T) and thermal conductivity i= f (T) were fitted using the fitting form of formula (3). The fitting results are as follows:

(2) The density p = f (T), kinematic viscosity v = f (T) and thermal diffusivity a = f (T) were fitted using the form of formula (4). The fitting results are as follows (Tables 9 and 10):

The error analysis of the fitting results of R134a on the saturated liquid phase line was carried out. The results show that the average relative error of the mathematical model of each thermal physical property parameter in R134a saturated liquid phase is less than 1.7 %, and the maximum relative error is less than 6.2 %.

3.3. Mathematical model of thermal physical property parameters of saturated aqueous solution

Select sufficient data from REFPROP 9.0 for aqueous solutions from saturation temperature 275.15K to 373.15K. Taking 2K as step length, the correlation equations between thermal physical properties of liquid water and temperature are fitted. By using 1Stops software, the polynomial fitting of the association is carried out through the general global optimization algorithm. The density p, specific heat capacity cp at constant pressure, thermal conductivity 4 and thermal diffusion coefficient « were respectively fitted by polynomial (Table 11).

... (5) where: T - Kelvin temperature, К;

ay, ay A3, a; - Fitting parameter;

f(T) - The thermal and physical parameters of refrigerant .

The error analysis of the fitting results was carried out. The results show that the average relative error of the mathematical model of each thermal property parameter of saturated aqueous solution is less than 0.45 %, and the maximum relative error is less than 0.11 %.

4. Mathematical model of main components of R134a-DMF absorption heat pump unit

The model of R134a-DMF heat pump unit is composed of five parts: generator, absorber, condenser, evaporator and solution heat exchanger using the principle of mass conservation and energy conservation. The mathematical models of the five components of the absorption heat pump system were established [27-29].

4.1. Mathematical model of generator

Generator mass balance:

... (6)

... (7)

From the principle of conservation of mass, it can be deduced that the ratio of solution is:

... (8)

... (9)

Heat transfer calculation:

... (10)

where, Ozen is the generator heat load, ??/;?, 15 the mass flow rate of R134a-DMF dilute solution at the generator inlet, kg/s;m,sis the mass flow rate of R134a-DMF concentrated solution at the generator outlet, kg/s;m Is the mass flow rate of refrigerant R134a steam at the generator outlet, kg/s; ??, is the mass flow rate of hot water, kg/s; cp is the specific heat capacity of hot water at constant pressure, kJ/(kg); Kye is the heat transfer coefficient of the generator plate heat exchanger, W/(m2:K); Fyen is the heat exchange area of the generator plate heat the exchanger, temperature, m?; At, °C, and his the enthalpy, mean kJ/kg. The subscript difference,'C; is shown t is in the system circulation diagram in Fig. 5, where w represents the state point of hot water from the heat source, s represents the state point of solution circulation, and r represents the state point of refrigeration cycle.

The ic mean difference is by the following formula:

... (11)

In order to simplify the calculation, in the actual calculation process, the temperature of the refrigerant at the outlet of the generator is usually replaced by the average value of the concentrated solution temperature at the outlet of the generator and the temperature at which the solution begins to boil in the generator [30].

... (12)

tpg is the temperature at which the solution begins to boil in the generator, °C.

4.2. Mathematical model of absorber

Absorber mass balance:

... (13)

... (14)

Heat transfer calculation:

... (15)

Where, Que is the heat load of the absorber, KWo, is the mass flow. - rate of R134a-DME dilute solution at the absorber outlet, kg/simi,çis the mass flow rate of R134a-DMF concentrated solution at the absorber inlet, bes, ofthe absorb fan, kg/s Cp is the specific heat capacity of ai at constant pressure, so õ WIA Es i the heat exchange area of the absorber air cooler, mês die omic per amos euro e or re, °C, and h is the enthalpy, kJ/kg. The subscript is shown in the System eireulation diegram in Fig. 6, Where represents ihe state plot ofthe absorber cooling fan, represents the state pont tes circulation, and r represents the state point of the refrigeration cycle.

The logarithmic mean temperature difference is approximated by the following formula:

Because the absorber the experimental formal he R134 DMT absorption heat pump unit sp

cycle rate is 0 for this form of system. that is, the mass flow rate after the mixture of refrigerant vapor and absorbent concentrated solution is the mass flow rate of dilute solution initially measured at the measurement point sl.

4.3. Mathematical model of condenser, evaporator and solution heat EXChanger

In the Fig 7, tr2,tr3 - condenser import and export refigerant R134a temperature, ·C,

tr5,tr4 - evaporator import and export refrigerant R134a temperature, ·C:

tw3, tw4 - chilled water intel and outlet temperature, ·C; t, 1, t·3, tg5, tg6 - the temperature of the binary mbature in and out of the solution heat exchange,·C.

4.4. Performance cont and simplfled Aypothests of heat pump system

Refrigeration performance coefficient of absorption heat pump system [31];

... (17)

Where: Qeva - The evaporator absorbs heat, kW;

Qabs - The generator absorbs heat, kW.

In order to simplify the process, the following assumptions are made [32-34]:

(1) Ignore the heat loss of generator and absorber tank wall, connecting pipe wall and external environment;

(2) Generators, absorbers and other parts with gas-liquid two phases, the gas-liquid two phases are in equilibrium;

(3) Ignoring heat loss and pressure loss during solution circulatio

(4) The outlet solution of the generator and absorber is saturated;

(5) The throttling process is adiabatic;

(6) Ignore the pump work of each circulating pump.

Based on the above assumptions, the mathematical model of R134aDMEF absorption heat pump unit is established.

5. Simulation calculation and result analysis of absorption heat pump unit

Using Matlab software to compile the program for simulation, it can be more convenient to solve the difficult problems caused by the calculation equations of each component and the many parameters involved in the solution cycle. The effects of concentrated solution temperature at generator outlet, air volume and supply air temperature difference of condenser fan, chilled water outlet temperature, R134a-DMF binary solution ratio on system performance were simulated and analyzed. Based on the thermodynamic calculation sub-modules of generator, absorber, solution heat exchanger, condenser and evaporator, the performance

analysis flow of R134a-DMF absorption heat pump unit is established

Thermal property is the basis of analysis of R134a-DMF absorption heat pump unit. According to the requirements of pe analysis, the ical properties correlation equations of R134a-DMF binary solution, R134a vapor phase, R134a liquid phase and saturated water fitted in the above section were respectively input. The input parameters are heat source hot water inlet temperature t,,1, chilled water outlet temperature £,,4, air cooled condenser inlet temperature tg, chilled water mass flow m,, air cooled air of air-cooled condenser my, air cooled air of absorber ту» and mass flow of heat source hot water my. The output parameters are the parameters, heat load and COP of each state point of each component of the R134a-DMF absorption heat pump unit. In this paper, the concentrated solution temperature at the generator outlet, the air volume of the condenser and the temperature rise of the inlet and outlet air, and the temperature of the chilled water outlet are changed to calculate the COP changes of the R134a-DMF absorption heat pump unit under different operating conditions, so as to analyze the reasons for the influence of changing input parameters on the unit performance.

5.1. Stability verification of R134a-DMF absorption heat pump simulation model

The reliability of mathematical model is the basis of simulation. After converting the physical model of the R134a-DMF absorption heat pump unit into a mathematical model, whether the conclusion obtained by running the simulation system can reflect the authenticity of the heat pump unit is the key point in the modeling and simulation process [35]. In order to ensure the correctness of the designed R134a-DMF absorption heat pump simulation system, it is necessary to check the R134aDMF absorption heat pump simulation system.

The R134a-DMF absorption heat pump unit system test bench was established in the information building of Shandong Jianzhu University. The main equipment of the system is shown in Fig. 9. In this paper, the model of each of the heat pump unit is built on the basis of the equipment structure parameters of the test bench.

By the key point data of the same experimental platform with the simulation process and calculating the key point temperature value, the same operating conditions are set. The specific operating condition is 85°C heat source, and the temperature t;; of the concentrated solution at the outlet of the generator is 74.5°C. The absorber fan and condenser fan are running at full load. The air capacity of the absorber fan and the condenser fan are 3800kg/h and 3768kg/h, respectively. The hot water circulation pump and chilled water circulation pump run at full load, and the hot water circulation volume and chilled water circulation volume are 2.84m·/h and 2.55m°/h, respectively. The key point temperature is shown in Table 12.

By comparing the temperature of the key point measurement point of the experimental platform with the temperature of the key point calculated by the ion of the si ion system, the results show that the simulation system meets the design requirements. At the same time, the systematic error of the platform measuring point and the location of the ing point are consi The si system of the heat pump is regarded as a stable state, and the simulation data can be used as the real value for performance analysis.

5.2. Performance analysis of R134a-DMF absorption heat pump unit

5.2.1. Effect of temperature of concentrated solution at generator outlet on system performance

R134a-DMF absorption heat pump generator outlet concentrated solution temperature reflects the performance of the generator heat exchange equipment on the performance of the unit. In this paper, the heat source temperature is defined as the average temperature of the hot water electric heater to the R134a-DMF binary solution through the generator brazed plate heat exchanger. Among them, the heat source temperature of R134a-DMF (3:2), R134a-DMF (1:1) and R134a-DMF (2:3) are set at 120°C. The temperature of the heat source is controlled unchanged, and it is assumed that the solution in the generator is heated by 10°C after the analysis, and this state is the initial state of the outlet concentrated solution. The COP and cooling capacity of R134a-DMF absorption heat pump unit are obtained by changing the temperature of the concentrated solution at the outlet of the generator on the basis of the initial state.

Fig. 10 shows the variation curve of COP and cooling capacity of the unit with the temperature of the concentrated solution at the generator outlet. It can be seen from the figure that with the increase of the concentrated solution temperature at the generator outlet, the COP and cooling capacity of the unit increase approximately linearly. This is because in the case of constant solution circulation, as the temperature of the concentrated solution at the outlet of the generator increases, the steam of the precipitated refrigerant R134a increases. At this time, the mass fraction of R134a-DMF concentrated solution increases, the condensation

increases, the decreases, and the heat transfer temperature difference of the evaporator increases. The mass fraction of the dilute solution at the outlet of the absorber grows more slowly than that at the outlet of the generator, and the bleed range increases, resulting in the increase of COP and cooling capacity of the unit.

According to the data analysis, for the binary solution of R134a-DMF (3:2), R134a-DMF (1:1) and R134a-DMF (2:3), the average increase of COP and cooling capacity is 0.85 %, 0.39 % and 0.42 %, respectively, when the temperature of the concentrated solution at the generator ot let increases by 1°C. The growth rate is slow. Through comparison, it is found that under the same design conditions, that is, the heat source is 120°C and the is 10°C, the ratio of R134a to DMF is 3:2, and the ratio of R134a to DMF is 2:

5.2.2. Effect of condenser cooling effect on system performance

The COP and cooling capacity of the unit vary with the cooling air temperature of the condenser. There are two factors that affect the change of wind temperature: fan air volume and ambient temperature.

The influence of air volume of condenser fan on unit performance was studied. Under the condition that the heat source temperature, hot water flow rate, chilled water inlet and outlet temperature, chilled water flow rate and the parameters of the absorber cooling fan are unchanged, the cooling air volume is changed to study the changes of the unit cooling capacity and COP. Figs. 11 and 12 show the COP and cooling capacity of the R134a-DMF(3:2) absorption heat pump system changing trend with cooling air volume, respectively. With the increase of cooling air volume, the i and i decrease, and the COP and cooling capacity of the unit increase. When the cooling air volume is less than the set value of 3765kg/h, the COP and cooling capacity of the unit are greatly affected with the increase of condensing air volume. When the condensing air volume is greater than the set value of 3765kg/h, with the increase of the condensing air volume, the influence on the COP and cooling capacity of the unit gradually becomes stable.

The effect of ambient temperature on unit performance is studied by changing the temperature rise of the air at the inlet and outlet of the fan. Under the design cooling air volume of 3765kg/h, with the inlet and outlet air temperature difference of the condenser fan increasing from 5°C to 7°C, the COP increases from 0.3956 to 0.5436, and the cooling capacity increases from 6.3kW to 8.7kW, and the cooling capacity increases by 38 %. COP and cooling capacity have similar variation trend with cooling air volume under different temperature difference between inlet and outlet. When it is below the set value, it is between 5.5-6.0 %, and when it is above the set value, it is between 3.5-5.0 %, and the growth rate of both shows a slowing trend, as shown in Fig. 13. Fig. 14 shows the change of COP of R134a-DMF in three ratio states of 1:1 and 2:3 with cooling air volume under the same working condition. COP increased with the increase of cooling air volume, and COP also increased with the increase of refrigerant R134a content in the working medium.

5.2.3. Impact of chilled water outlet on system

The change curve of COP of R134a-DMF absorption heat pump system with the temperature of chilled water outlet is shown in Fig. 15. Control the other parameters of the heat pump unit unchanged, set the temperature of the heat source 120°C, the air volume of the condensing. fan 3768kg/h, the temperature of the concentrated solution at the generator outlet 100.5°C, adjust the temperature of the chilled water outlet from 10°C to 20°C, and then observe the change of the COP of the unit. As can be seen in Fig. 15, the system COP increases as the chilled water outlet temperature increases. And the greater the proportion of refrigerant in binary solution, the greater the COP of the unit at the same temperature. According to the data analysis, the COP of R134a-DMF(3:2), R134a-DMF(1:1) and R134a-DMF(2:3) increased at an average rate of 1.36 %, 3.06 % and 3.1 % i when the outlet of chilled water increased from 10°C to 20°C. The COP growth rate of the system slowed down, and the COP growth rate of the system with 3:2 working mass ratio decreased from 1.68 % to 1.05 %. The COP growth rate of the system with 1:1 working mass ratio decreased from 3.64 % to 2.53 %. The COP growth rate of the system with 2:3 working mass ratio decreased from 3.57 % to 2.65 %, and the heat pump unit tended to be stable. When the amount of work mass to solution circulation in the system is a fixed value, with the increase of chilled water outlet temperature, and ion pressure increases, the concentrated solution in the absorber absorbs energy enhancement. The mass fraction of dilute solution decreases, the gas discharge range increases, the refrigeration dose increases, and the cooling capacity and COP of the heat pump unit increase.

6. Conclusion

In this paper, according to the requirement of simulation of R134aDMF absorption heat pump unit, a mathematical model is established for the thermal physical property parameters of R134a-DMF binary solution, refrigerant R134a and saturated water. At the same time, on the basis of mass conservation and energy conservation, the mathematical models of R134a-DMF absorption heat pump generator, absorber, evaporator, condenser and solution heat exchanger are established. And the five parts are connected in series to form a complete mathematical model of the unit. The accuracy of the model is verified by the experimental data, which ensures the feasibility of the simulation. On the basis of this, the influences of concentrated solution temperature at generator outlet, cooling capacity of condenser and chilled water outlet temperature on COP and cooling capacity of unit are analyzed by simulation. The following conclusions are drawn:

(1) For R134a-DMF (3:2), R134a-DMF (1:1) and R134a-DMF (2:3), the average COP and cooling capacity increase are 0.85 %, 0.39 % and 0.42 %, respectively, when the generator outlet concentrated solution temperature increases by 1°C, and the growth is relatively slow. Among them, the strongest cooling capacity is the R134a: DMF 3:2, and the worst is the R134a: DMF 2:3.

(2) The COP of the heat pump unit increases with the increase of the air volume of the condenser fan. In addition, with the increase of condensing fan air volume, the COP growth rate of the unit slows down, and the greater the temperature difference between the inlet and outlet of the condenser fan, the better the cooling effect, and the larger the COP of the unit.

(3) The COP of heat pump unit increases with the increase of chilled water outlet temperature. The larger the proportion of refrigerant in R134a-DMF binary solution, the larger the COP of the unit at the same temperature, but the growth rate gradually slows down and tends to be stable.

However, the thermophysical parameter equations and accuracy of R134a-DMF binary solution are limited. In further research on R134a DMEF absorption heat pump units, it is of great significance to establish a detailed database of R134a DMF thermophysical parameters. This article simplifies the process of establishing mathematical models and

various It is necessary to establish a more accurate mathematical model and adopt assumptions that are more in line with the actual situation to make the research on heat pump units more accurate.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests ог personal relationships that could have appeared to influence the work reported in this paper.

CRediT authorship contribution statement

Zhaoyi Zhuang: Methodology, Validation, Formal analysis, Writing - original draft, Writing - review & editing. Jin Zhao: Software, Writing - original draft, Writing - review & editing, Visualization. Jiapeng Ра! Project administration, Investigation, Resources. Teng Zhang: Invest gation, Data curation. Qiang Han: Supervision, Project administration.

Acknowledgements

In this paper: the research was sponsored by the Natural Science Foundation of Shandong Province (Grant No. ZR2022ME102), the Plan of Introduction and Cultivation for Young Innovative Talents in Colleges and Universities of Shandong Province (2021), and the Scientific and Technological Innovation Project for Youth of Shandong Provincial Colleges and Universities (Grant No. 2019KJH012) and the Research on Energy and Built Environment 6 (2025) 307-319

the Development of Intelligent Management System and Energy Saving Technology for Public Hospital Building Energy Use (Grant No. and GYZ2022HQ44) Medium and Shandong Province bility Science and Technology Project (Grant Small No. 2023TSGC0052, 2023TSGC0074).

Sidebar

Received 21 August 2023; Received in revised form 11 November 2023; Accepted 19 November 2023

Available online 2 December 2023

Footnote

* Corresponding author. E-mail address: [email protected] (Z. Zhuang).

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