Utilization of Surplus Air Thermal Energy by a Water Cycle System in a Chinese-Type Solar Greenhouse

Abstract

Solar greenhouses are commonly overheated during the day, and the remaining air heat can only be dissipated through ventilation, which is a severe energy waste problem. In order to improve the energy utilization of the greenhouse, this study proposes a water cycle system using surplus air thermal energy, which consists of an air-water heat exchanger, supply and return pipes, a submersible pump, a water tank, and an automatic control system. The proposed system stores the surplus air thermal energy in the greenhouse in the water tank. It releases it into the greenhouse using water circulation, and experimental analyses were carried out using a solar greenhouse in the Shenyang area. The effects of different air and water flow rates on the performance of the surplus air thermal energy water recycling system and the environment inside the greenhouse were analyzed by establishing a CFD model and model validation, and the average difference between the experimental data and the simulated data was 6.98%. The results show that the circulating air flow rate significantly affects the system performance and the environment inside the greenhouse. In the heat collection stage, the water circulation system with an airflow rate of 9 m/s has a minor average temperature difference in the vertical plane of the greenhouse. The water circulation system with an airflow rate of 6.0 m/s collects and releases the most significant heat. The temperature cloud between the vertical and horizontal planes is more uniform. This research provides new ideas for efficient energy use in solar greenhouses.

1. Introduction

The area of greenhouses is increasing worldwide [1]. According to statistics, as of 2019, the CSG area in China reached 570,000 ha [2]. Greenhouses provide better environmental conditions for plant growth than most agricultural production systems [3,4]. It protects against climatic changes to extend the season for growing crops [5]. In order to improve the quality and yield of greenhouse crops and adjust the crop’s maximum yield cycle, greenhouse production technology has been driven by continuous progress. These requirements have led to constant advances in greenhouse technology. The greenhouse is widely used to create a suitable environment for crop growth [6]. In the north of China, solar greenhouses solve the problem of people not being able to get fresh vegetables in the winter. The growth of the crop depends on the balance between various environmental factors, including temperature, solar radiation, carbon dioxide concentration, relative humidity, and so on. In particular, the greenhouse’s thermal environment is essential for crop growth [7]. As a unique horticultural facility in northern China, the solar greenhouse has been known for its high efficiency, energy savings, and low cost [8,9]. However, the greenhouse structure alone is insufficient to keep crops growing year-round. All kinds of measures for crop growth are accompanied by energy consumption [10,11]. Especially in winter, to maintain the normal growth of crops, the greenhouse needs to be heated to maintain the optimal temperature. Heating costs account for about 65% to 85% of the total energy consumption of greenhouses [12,13]. The primary energy sources used in heating equipment include traditional fossil energy sources (e.g., coal, natural gas, etc.) and renewable energy sources (e.g., solar, geothermal, biomass, etc.) [14]. Because of the high cost and low environmental benefits, the former is gradually being phased out and replaced by the latter [15]. Surplus air thermal energy (SATE) is one of the renewable energy sources. Suppose a greenhouse in the temperate and subtropical regions is maintained in a closed condition. In that case, the indoor temperature commonly exceeds that required for optimal plant growth, even in the cold season. This excess energy is then considered SATE, which can be recovered, stored, and used when heat is needed [16,17,18].

SATE is the heat energy stored in the atmosphere and is renewable [19,20,21]. There are few types of research on the development and use of SATE in greenhouses, which has great potential value. In the past, the SATE inside the greenhouse was generally discharged as residual heat. In recent years, many researchers have conducted much research on this [22,23,24,25]. By monitoring the environmental data of the closed greenhouse and calculating the energy consumption of the greenhouse, it was concluded that the surplus air thermal energy stored in the summer is fully sufficient to meet the heating needs of the solar greenhouse in the winter [26]. Some researchers have argued that the utilization of SATE presupposes the calculation of the value of surplus heat [27]. Some researchers have also evaluated the cost-effectiveness of relevant surplus air thermal energy storage systems regarding the direction of economic viability [28,29,30]. Soil, rock beds, water, and phase change materials can all be used as thermal storage media to effectively absorb heat and passively store and release heat to improve the indoor thermal environment and ensure normal crop growth [31,32]. Most of these studies do not apply to Chinese solar greenhouses, and the installation costs of the heating systems in these studies are high; the cost of the heating equipment itself is also high. These studies focus on the analysis of the internal environment after the installation of the heating system and do not pay much attention to the performance of the system itself. Therefore, this paper proposes a water cycle system using surplus air thermal energy in a greenhouse and analyzes the system’s performance and the greenhouse’s internal thermal environment using a combination of numerical simulation and experimentation.

In order to design a water cycle surplus thermal energy utilization system scientifically and rationally, the system’s feasibility needs to be verified, and the performance effects of the system need to be further defined. Constrained by factors such as materials, construction, cost, type of greenhouse, and heating effects, operational parameters need to be measured, and water cycle surplus thermal energy utilization system patterns need to be systematically investigated. In recent years, Computational Fluid Dynamics (CFDs) have proven to be the most useful tool for modeling the interaction of liquids and gases with complex surfaces [31,33,34]. CFD techniques provide a better, faster, and more reliable understanding of flow fields with less labor and cost. Therefore, this study takes an energy-efficient solar greenhouse as the research object and combines simulation and experimental validation to systematically investigate the effects of greenhouse water cycle surplus thermal energy utilization system, on the internal environment of greenhouses and to specify the operating parameters of the system in order to provide a reference for the design, application, and research of solar greenhouse heat storage and energy-saving strategies in China.

2. Materials and Methods

2.1. Experimental Environment and Equipment

In this study, the sliding-over solar greenhouse was located in the experimental field of Shenyang Agricultural University (41.8° N, 123.4° E) with a typical temperate continental monsoon climate. The minimum temperature is −20 °C, and the maximum is 31 °C throughout the year. The greenhouse is 66 m long, spanning 10.4 m, facing east-west, and has a total construction area of about 2355 m². The skeleton structure of the slide-covered greenhouse is a semi-circular arc, with rock wool-filled steel flat as the insulation covering material, and the east-west wall is replaced by a slide-covered steel flat with a height of 5.2 m. The outer insulation covering part, east and west walls, and ventilation windows at the top and bottom can be opened and closed automatically, increasing the light rate on both sides and improving the problem of shading due to the traditional earth walls on both sides. Long-term use led to the external insulation covering not automatically opening and closing. Now the south roof is covered with a 0.04 m thick cotton blanket at night for insulation. The CSG structure is shown in Figure 1a,b. The insulation quilt was rolled up at 8:30 during the day to allow sunlight to enter the solar greenhouse and lowered at 4:30 p.m. to reduce heat dissipation from the south roof.

The ambient temperature was monitored from the beginning of November, and the indoor and outdoor temperature data during the test period are shown in Figure 2. During the experimental data collection period, the greenhouse’s back wall water heat storage equipment was not operating. The daily maximum outdoor temperature fluctuated around 6 °C. The average minimum outdoor temperature was below 0 °C, the average temperature difference between outdoor temperatures was 13.7 °C, and the maximum temperature was 22.2 °C. December 16 was the coldest day, with a minimum temperature of −19.9 °C, and the maximum outdoor daily temperature fluctuated around 6 °C. As there was no crop growth indoors, no heating or insulation equipment was started except for the insulation quilt. The lowest average indoor temperature was 8.3 °C, and the lowest was 2 °C; the highest average indoor temperature was over 35 °C; and the highest was 48.4 °C, which fully satisfied the system operating conditions.

The experimental greenhouse was divided into two identical parts with insulated panels; one was used for plant cultivation, and the other was an empty greenhouse. To exclude the influence of plants, the water cycle surplus thermal energy utilization system was installed in the east compartment without plants. Components of the water cycle surplus thermal energy utilization system are shown in Figure 3a and

Table 1. Component equipment and related functions of the water cycle surplus thermal energy utilization system.

Equipment	Material	Function
Air-water heat exchanger	Consists of an axial flow fan, aluminum fins, and copper tubes.	Exchange of heat
Water supply and return pipes	Polypropylene-Random	Water supply and return
Submersible pump	-	Maintenance of water cycle dynamics
Tank	Polyvinyl chloride	Thermal energy storage
Automatic control system	-	Control of equipment start/stop
Flowmeter	-	Measurement of water flow

. The air-water heat exchanger consists of an axial flow fan, aluminum fins, and copper tubes in 3 rows of 18 tubes, each with a diameter of 18 mm. Moreover, the water in the pipes flows from the bottom up, which can flow wholly and evenly to exhaust the air inside. The submersible pump is placed inside a tank wrapped in a layer of insulation, and a flow meter is mounted on the water supply line to monitor the water flow. When the system starts running, air and water pass through the air-water heat exchanger at the same time, exchanging heat through heat convection and heat conduction to achieve the effect of heat exchange. In the heat collection phase, cold water and hot air are exchanged for heat through an air-water heat exchanger, and the exchanged heat is taken to a water tank for conservation. In the exothermic phase, the heat is released through the air-water heat exchanger.

2.2. Experimental Equipment and Methodology

The experiment was carried out on 11 November 2022. Before the system was started, basic parameters such as soil, back wall, indoor air temperature, and humidity inside the greenhouse were continuously monitored for one month to derive a pattern of changes in each parameter. 12 December saw the start of operation of the system, with a minimum outdoor temperature of −19.9 °C and a maximum outdoor temperature of 6.3 °C during the experiment. During the experiment, the greenhouse compartment was kept sealed to meet the experimental requirements. Based on the basic parameters, the system was operated between 10:30 and 15:30, from 10:00 p.m. to 8:00 a.m. the following day. From 12 December to 27 December, all equipment was operated, and the difference in performance between the system on sunny and cloudy days was observed. The experiments verified that the water cycle surplus heat utilization system has better heat collection performance in cold weather.

In order to determine the thermal environment inside the CSG, a total of 14 monitoring points were set up inside and outside the greenhouse to obtain quantitative data on internal air temperature, soil temperature, and wall temperature using a temperature logger (RC-4, Elitech, Xuzhou, China, Precision: ±0.1 °C, temperature range from −30 °C to 80 °C) to record data every 10 min. All sensors were installed in the greenhouse’s middle cross-section, and the measurement points’ locations were distributed, as shown in Figure 3b. In order to determine the changes in parameters during the operation of the system, temperature monitoring was carried out in the experimental tank, the control tank, and the return water outlet. To determine the solar radiation values during the experiment, solar radiation was measured using a corona meter (HD2302, Delta Ohm, Selvazzano Dentro, Italy, Precision: ±15 W/m²) mounted on the north wall of the greenhouse. Individual data loggers automatically collected data during the measurements.

2.3. Heat Load of the Greenhouse

The energy gained and lost by the greenhouse is in energy balance [18] (Equations (1)–(4)). The greenhouse energy mainly comes from solar radiation (${\phi }_{solar}$), equipment operation (${\phi }_{equipment}$), heating systems (${\phi }_{heat}$), and plant respiration (${\phi }_{respiration}$). The heat inside the greenhouse is dissipated to the outside environment mainly through the greenhouse structure (${\phi }_{wall}$), soil (${\phi }_{ground}$), and ventilation (${\phi }_{ventlatent}$ and ${\phi }_{ventsensible}$).

$${\phi }_{solar}+{\phi }_{equipment}+{\phi }_{heat}+{\phi }_{respiration}={\phi }_{wall}+{\phi }_{ground}+{\phi }_{ventsensible}+{\phi }_{ventlatent}$$

(1)

In this experiment, the heat energy provided by the heating system at night is the only heat load the greenhouse receives. Moreover, the solar radiation at night is zero, and the empty greenhouse involves no other equipment or crops. The soil temperature is usually higher than the air temperature at night, and the greenhouse vents are closed. Therefore, the above heat balance equation is simplified: The calculation method for heat transfer through the greenhouse structure is as follows:

$${\phi }_{heat}={\phi }_{wall}+{\phi }_{ventsensible}$$

(2)

The calculation method for heat transfer through the greenhouse structure is as follows:

$${\phi }_{wall}={\displaystyle \sum _j{k}_j{A}_j(t_a-t_{oa})}$$

(3)

where $k_j$ is the heat transfer coefficient of different parts of the greenhouse structure (W·m⁻²·°C⁻¹), $A_j$ is the area of each part of the greenhouse structure (m²), $t_a$ is the indoor air temperature (°C), and $t_{oa}$ is the outdoor air temperature (°C).

The heat loss by infiltration can be estimated as follows:

$${\phi }_{ventsensible}=L{V}_a{\rho }_a{c}_a(t_a-t_{oa})$$

(4)

where $L$ is the infiltration rate (s⁻¹), $V_a$ is the volume of the greenhouse (m³), ${\rho }_a$ is density of the indoor air (kg·m⁻³), $c_a$ is specific heat of the indoor air (J·kg⁻¹·°C⁻¹).

2.4. CFD Models Simulation

2.4.1. CFD Models’ Assumptions

Several assumptions were made about the greenhouse and the water cycle surplus heat utilization system in the CFD simulations. (1) The greenhouse is uniformly translucent, shaded, and sealed. (2) Ideal gases are used for greenhouse gases. (3) The wet air in the greenhouse consists of dry air and water vapor only. The temperature and RH distribution in the greenhouse before cooling are uniform. (4) The greenhouse subsoil temperature remains constant during the operation of the installation, and the outdoor boundary conditions (e.g., outdoor irradiance, humidity, and temperature) remain stable.

2.4.2. Calculation Domain and Mesh Settings

CFD simulations were conducted with Ansys 18.0 to model the spatial distribution of greenhouse air temperatures. A physical model measuring 3 m in height and 5 m in length was constructed for experimental validation, using the same parameters as the greenhouse in the experimental data collection. Grid independence tests were performed with five different grid numbers, and discrete coordinate models were employed to simulate solar radiation. The solar calculator was set up with latitude and longitude, date, and time according to the experiment, with a sunshine factor of 0.9 for weather conditions. The geometry and meshes used for the numerical analysis were designed using Solidworks 2018 and Fluent 18.0 Meshing software tools. The average temperature in the greenhouse was monitored and checked to reach a stable value. As shown in Figure 4, the initial number of cells was 2.2 million, eventually reaching 3.4 million in four grid refinement steps. The average air temperature in the greenhouse associated with the second level of grid refinement (approximately 2.8 million cells) showed satisfactory accuracy compared with the third and fourth levels (3.4 million cells). Increasing the number of cells to 3.4 million did not show a significant increase in the accuracy of the results. Therefore, considering the computational burden and the guarantee of simulation accuracy, the same grid division method was used for the other comparison cases in the parametric study, with a total grid size of approximately 2,800,000.

The boundaries in the grid calculation domain are divided into six parts: the south roof (membrane), the east and west side walls, the north wall, the soil, and the water cycle surplus heat utilization system. The physical properties of the materials in the simulation are shown in

Table 2. Thermo-physical properties of materials used in simulation.

Physical Properties	Internal Air	Soil	Polyolefin Film	Polystyrene Board
Density/kg·m−3	ideal-gas	1700	950	30
Transmittance/%	–	–	70	20
Reflectance/%	–	–	15	–
Specific heat Capacity/J·kg−1·K−1	1006.43	1010	1600	2414.8
Thermal conductivity/W·m2·K−1	0.024	0.85	0.19	0.041

. Outdoor humidity, temperature, and solar radiation are used as boundary conditions, and the experimental greenhouse is airtight and unventilated, with the whole installation forming an internal loop in the greenhouse. The minimum grid size of 0.012 m and the maximum grid size of 0.099 m were used in drawing the grid of the CFD model. The system of equations was solved based on the finite volume method using the commercial solver software ANSYS 18.0. An implicit method was used to simplify the pressure and velocity. The discrete form of the control equations was set as follows: (i) gradient as a least squares-based cell; (ii) pressure as second order; (iii) momentum and energy as second-order inverse flow. Other variables, such as turbulent kinetic energy and dissipation rate, are in first-order upwind form. Considering the computational cost, an acceptable simulation time step and a maximum number of iterations per time step of 30 s and 20 iterations, respectively, were chosen for CFD model screening and water cycle surplus thermal energy utilization system selection in this study.

2.4.3. Mathematical Model

The following are the three basic conservation equations in the CFD model: mass, momentum, and energy [35] (Equations (5)–(7)).

$$\frac{\partial \rho }{\partial t}+\nabla .\left(\rho \overrightarrow{V}\right)=0$$

(5)

$$\frac{\partial \left(\rho \overrightarrow{u}\right)}{\partial t}+\nabla .\left(\rho \overrightarrow{u}\overrightarrow{V}\right)=-\nabla P+\nabla .\left({\tau }_{eff}\right)+\rho \overrightarrow{f}+S_i$$

(6)

$$\frac{\partial \left(\rho E\right)}{\partial t}+\nabla .\left[\overrightarrow{V}\left(\rho E+p\right)\right]=\nabla .\left[k_{eff}\nabla T-{\displaystyle \sum _j{h}_j{\overrightarrow{J}}_j+\left({\tau }_{eff}.\overrightarrow{V}\right)}\right]+S_h$$

(7)

The standard k-ε model (Equations (8) and (9)) is applied to the model [36].

$$\frac{\partial }{\partial t}\left(\rho k\right)+\frac{\partial }{\partial x_i}\left(\rho k{u}_i\right)=\frac{\partial }{\partial x_j}\left(a_k{\mu }_{eff}\frac{\partial k}{\partial x_j}\right)+G_k+G_b-\rho \epsilon -Y_M$$

(8)

$$\frac{\partial }{\partial t}\left(\rho \epsilon \right)+\frac{\partial }{\partial x_i}\left(\rho \epsilon u_i\right)=\frac{\partial }{\partial x_j}\left(a_{\epsilon }{\mu }_{eff}\frac{\partial \epsilon }{\partial x_j}\right)+C_{1\epsilon }\frac{\epsilon }{k}\left(G_k+G_{3\epsilon }{G}_b\right)-G_{2\epsilon }\rho \frac{{\epsilon }^2}{k}+S_{\epsilon }$$

(9)

The solar radiation was applied to the model using the Discrete Ordinates (DO) model as follows:

$$\nabla \cdot \left(I\left(\overrightarrow{r},\overrightarrow{s}\right)\overrightarrow{s}\right)+\left(a+{\sigma }_s\right)I\left(\overrightarrow{r},\overrightarrow{s}\right)=a{n}^2\frac{\sigma T^4}{\pi }+\frac{{\sigma }_s}{4\pi }{\displaystyle {\int }_0^{4\pi }I}\left(\overrightarrow{r},\overrightarrow{s}\right)\Phi \left(\overrightarrow{r},{\overrightarrow{s}}^{\prime }\right)d{\Omega }^{\prime }$$

(10)

The greenhouse’s geographical position and the time in which the models were solved were applied for the calculation of global solar radiation.

2.4.4. Energy Migration System Energy Efficiency and Cooling Heating Efficiency Assessment [33]

$${\eta }_{ce}=\frac{\left(T_{ie}-T_{ii}\right)\cdot V}{P_A\cdot t}$$

(11)

$$P_{ca}=\frac{P_A\cdot t}{A}$$

(12)

3. Results and Discussion

3.1. Validation of Numerical Simulations

To verify the accuracy of the CFD numerical model, the simulated greenhouse temperatures were compared with the experimental greenhouse under the same environmental conditions. The average air temperature inside the greenhouse was measured and compared with the simulated average air temperature. Figure 5 illustrates that the average internal air temperature variation values closely aligned with the simulated results of the experimental data, with an average difference of 1.1 °C and an average absolute difference of 6.98%. This demonstrates that the proposed mathematical model describes the processes occurring in the greenhouse with high accuracy. Under the conditions of the model, the single variable method was used to solve the model for different variable conditions and accurately predict the system operation and the effect on the microclimate in the greenhouse for different air flows, different water flows, and different weather conditions.

3.2. Performance of the System

The heat collection efficiency of the system depends on the indoor air temperature and is related to the solar radiation received inside the greenhouse. In order to systematically evaluate the system’s heat storage and discharge performance, three typical days were selected for comparative analysis, as shown in Figure 6, with significant differences in performance between different weather conditions. Sunny days caused significantly higher water temperature increases than cloudy days, with a sharp increase in water temperature when solar radiation increased significantly between 10:00 a.m. and 12:00 p.m., especially on sunny days. The average rate of warming on a sunny day was 6.01 °C/h, 1.52 times higher than on a cloudy day. On cloudy days, water temperatures can still rise to meet system operating conditions, with the maximum average water temperature exceeding 25 °C. This is mainly because residual air thermal energy was utilized in this study and did not rely entirely on solar radiation.

In Figure 7, the daily heat release is lower than the heat collected, and, in addition, due to the experimental conditions, the heat collected on that day was not sufficient to heat the system in one night. The amount of heat collected exceeded 8 MJ per day for the system’s operation, with a maximum of 16 December. The energy collected is related to several factors, such as the initial water temperature, the amount of water stored, etc., and to the operating parameters of the system, such as the speed of the water passing through the copper tubes of the air-water heat exchanger and the airflow that circulates the hot air inside the greenhouse, which have a more significant influence on the environmental parameters.

Using the experimental data curve from a typical sunny day as a reference (Figure 8), the tank water temperature used as a control slightly varied, with a fluctuation value of less than 1 °C compared with the initial water temperature of 9.8 °C. At 10 a.m., the system started, and the tank water temperature rose rapidly, reaching a peak of 32.5 °C at 13:45, and began to fall until 15:30 (when the system stopped running), when the water temperature began to fall gradually until the night-time system operation time, which is an unavoidable heat loss process in the experiment, and improving the insulation capacity of the water storage tank can reduce this loss, with a temperature difference of 2.8 °C during this time. When running at night, the water temperature drops sharply. The water tank peak stops running during this period of temperature decline because the greenhouse daytime indoor maximum value is around 2 p.m.; after the peak, the indoor temperature is difficult to support the water temperature rise and cannot maintain the indoor peak when the water temperature value produces the phenomenon of decline. The phenomenon of a sharp drop in nighttime operation is due to the small number of experimental equipment, the extensive experimental greenhouse, and the poor insulation and heating measures for it due to the absence of crop growth, resulting in the greenhouse being so cold at night that the experimental water tank water temperature is lower than the control tank water temperature.

In summary, we demonstrated that the water cycle surplus heat utilization system can effectively capture and utilize surplus air thermal energy in the solar greenhouse. Compared with the heat transfer between the greenhouse’s air and the storage medium, the energy migration system loses less heat during heat collection and discharge and has a higher transfer efficiency.

3.3. Simulation of the Heat Storage and Release Effects of Water Cycle Surplus Heat Utilization System at Different Water Flows

The temperature distribution of the internal air, soil, and north wall should be carefully monitored during the winter growth of crops. The air environment directly affects the growth of the crop, while the soil environment directly affects the growth of the crop roots. The north wall is the most essential part of the CSG for storing and releasing heat and directly affects the temperature stability of the air inside.

Figure 9 describes the temperature distribution program in the horizontal and vertical planes of the greenhouse model of the water cycle surplus heat utilization system at different water flows. Two typical periods were selected for observation to analyze the water cycle surplus heat utilization system’s effect on the greenhouse microenvironment. In order to better observe the pattern of air temperature changes within the greenhouse, the scale of the cloud map is set separately for different periods in the ambient greenhouse. The insulation is rolled up at 8:30 a.m., and the temperature inside rises as the solar radiation from outside increases, reaching a maximum at 2:00 p.m., when the internal surface temperature of the walls and soil rises, mainly due to the simultaneous radiative heat transfer from the air inside. Due to the colder winter months, the cotton blanket must be deployed around 4:00 p.m. to maintain the ambient temperature adequate for crop growth when the external temperature drops. At 10:50 a.m., 20 min into the system’s operation, the indoor temperature constantly increases due to the more significant influence of the external environment on the internal environment. The size of the water flows affects the adequacy of the water medium in contact with the hot air; the faster the water speed, the less efficient the absorption of heat; therefore, from left to right, the greater the increase in water speed, the higher the indoor temperature is at this time. At 2:00 p.m., the indoor temperature is significantly lower than at 10:50 a.m., and the system’s operation reduces the original temperature difference so that the extreme temperatures seen in the previous ambient measurements disappear, maintaining an overall temperature of 26 °C or less. The cloud chart at 10:50 and 14:00 shows that the air temperature near the back wall part is higher than the temperature near the film. Due to the different thermal parameters of the back wall and the film, the back wall has a certain ability to store and release heat, and the outdoor environment has less influence on the indoor air temperature on the north side than on the south side due to the difference in volume and location, so the air temperature near the north side is obviously higher than near the film side.

During the nighttime exothermic phase (Figure 10), the tank temperature was significantly higher than the air temperature inside the greenhouse at 22:20, 20 min after the system was run. At 24:00, after 2 h of system operation, the air temperature inside is more evenly distributed. From the observations on the cloud diagram, it can be concluded that the rate of circulating water during the heat storage and exothermic phases can affect the indoor environment, but not significantly.

Six CFD models simulated air temperature variations at different heights in the greenhouse at the same water circulation flow during the heat storage phase (Figure 11). The temperatures simulated by the six CFD models exhibit a relatively consistent spatial pattern throughout the daytime heat storage period. This means the temperature gradually decreases from the ground to the roof, with the highest temperature at ground level being 29.39 °C and the lowest at the roof. This is because the soil is a good heat storage body, and the roof is in contact with the outdoors and is more influenced by the outside temperature. The further away from the ground, the less significant the temperature fluctuations. The temperature stratification on the vertical plane in the greenhouse was not obvious, with the temperature profile inside fluctuating around 20 °C up and down in the 0.5~2.5 m range, with 2.5 m being slightly warmer than the other horizontal heights simulated, with a temperature difference of about 0.5 °C. With the change in time, the indoor temperature should have gradually increased during the day as the insulation was uncovered and the greenhouse was exposed to sunlight. The indoor high-temperature fluctuations were reduced due to the operation of the system, which transferred heat from the air in the greenhouse to the water storage tank for storage.

Changes in the heat in the greenhouse lead to temperature fluctuations, and the heat is stored through the operation of the system. Figure 12 shows the change in indoor air temperature during the heat storage phase for different water circulation rates at the same height. The trend is all downward with time, and the average temperature difference between the horizontal surfaces at different heights (0 m, 0.5 m, 1.0 m, 1.5 m, 2.0 m, 2.5 m, 3.0 m) before and after the heat storage period is 7.90 °C, 7.41 °C, 7.50 °C, 7.61 °C, 7.63 °C, 4.06 °C, and 2.31 °C. Therefore, the histograms in Figure 11f, reflect much more minor differences at different flow rates; the temperature at the same height for different variables is less than 0.15 °C. As shown in the figure, there is little difference in temperature between each variable during the heat collection phase.

The most effective gauge for assessing the system’s thermal performance is the change in water temperature compared with the air temperature. The water temperature variation versus the greenhouse temperature during the nighttime heat release phase is depicted below. Figure 13 shows the trend of the average air temperature (Figure 13a) versus the temperature of the thermal storage tank (Figure 13b) for six variables during the heat dissipation phase. The greenhouse temperature continued to drop until the water cycle surplus heat utilization system was operated at 10 p.m., with the average indoor temperature at 10 p.m. being around 10 °C, according to previous ambient monitoring data. The system operated from 10 p.m. until 8 a.m. the following morning, during which the indoor temperature reached its maximum within an hour and a half and then began to fall continuously. The water temperature cooled at a rate of 7.08 °C·h⁻¹ during this phase, followed by a cooling rate of 0.43 °C·h⁻¹ until it stopped, with the difference between each curve maintained at 0.5 °C. At the start of the system’s operation, the temperature difference between the greenhouse’s interior and the water storage tank is so significant that, at the beginning, the exothermic efficiency of the system is at its maximum. In contrast, the heat demand of the greenhouse was high, and during the second half of the night, the heat from the system struggled to support the increase in greenhouse temperature, and the greenhouse temperature began to drop. In the case of winter production in greenhouses, the greenhouses will be better insulated and will not have such significant temperature differences as in the experimental period.

3.4. Simulation of the Heat Storage and Release Effects of Water Cycle Surplus Heat Utilization System at Different Air Flows

Inside the greenhouse, the air temperature rises progressively with increasing height from ground level upwards. The airflow directly affects the rate of air circulation within the greenhouse, influencing the airflow’s mass, momentum, and energy transfer properties, and thus the cooling results in both the spatial and temporal dimensions. The average indoor air velocities measured by the model for six parameters (1.5 m/s, 3.0 m/s, 4.5 m/s, 6.0 m/s, 7.5 m/s, and 9.0 m/s) were 0.26 ± 0.0031 and 0.42 ± 0.0029. The average indoor temperatures for the six models with different air flows decreased significantly after 20 min of system operation (Figure 14) and decreased in the following operation. At the beginning of the operation, the indoor temperature was high, and the temperature difference between air and water was significant. Hence, the heat collection efficiency of the system was highest at this time. Similarly, the exothermic phase is also the same.

The temperature distribution clouds provide a better view of the greenhouse structure and the temperature changes in the greenhouse interior environment. Figure 15 depicts the temperature distribution clouds on the horizontal and vertical surfaces inside the greenhouse for different air flows of the water cycle surplus heat utilization system. Two typical periods were selected for observation to analyze the effect of the system on the microenvironment inside the greenhouse. At 10:50 a.m., 20 min into the system’s operation, the temperature on horizontal and vertical surfaces decreased, and the overall uniformity increased as the airflow rate increased. Airflow volume impacts the overall performance of airflow throughout the entire area; the higher the airflow, the greater the distance the system affects horizontally and vertically. As a result, the indoor air temperature continues to decrease with increasing airflow during the period the system is operating while also increasing the uniformity of the environment. At 2:00 p.m., the indoor temperature is significantly lower than at 10:50 a.m. The greenhouse section temperature fluctuates much less, and the overall temperature remains around 25 °C, meeting the needs of growing crops indoors.

The temperature clouds for the nighttime exothermic phase (Figure 16) are shown below. At 20 min of system operation, the horizontal and vertical surface temperature clouds with air flows of 1.5 m/s and 3.0 m/s show an average greenhouse temperature below 10 °C. By 24:00 p.m., the overall temperature is higher than by 10:20 p.m. The higher the airflow, the faster and more evenly the heat stored in the system can be distributed throughout the greenhouse. Thus, when the system has just been running for 2 h, the greenhouse air temperature increases as the airflow increases. It can be seen that temperature clouds with air flows of 4.5 m/s, 6.0 m/s, 7.5 m/s, and 9.0 m/s had average greenhouse temperatures above 15 °C.

During the exothermic phase, under consistent airflow, the temperature within the greenhouse varies over time at different heights from the ground, as illustrated in Figure 17. The highest temperature occurs at ground level, while the lowest temperature is 12 °C, at 0.5 m above ground, with a decrease of 1.38–1.79 °C compared with ground level. At 1.0 m, the temperature decreases, being 0.1–0.3 °C lower than at 0.5 m. Subsequently, the temperature gradually rises between 1.5 m and 2.5 m, with the lowest temperature occurring at the simulated point at 3 m, coinciding with the roof. Because 0.5 m and 1.0 m are closer to the ground and are subject to greater soil temperatures, the closer you are to the soil, the higher the temperature; from 1.5 m to the roof, because the density of hot air is lower than that of cold air, the air temperature increases as the height increases. The increase in airflow brought forward the time at which maximum temperatures were reached at night, with maximum temperatures at each altitude occurring approximately 2 h and 20 min after the system was operated at 1.5 m/s and 1 h and 40 min after the system was operated at 9 m/s. As mentioned earlier, due to the structure of the greenhouse itself and the cold winter months, the difference between indoor and outdoor temperatures is so great that it is difficult to maintain the system at a certain temperature inside. The higher the air flow rate, the earlier the time to reach the maximum temperature produced by the night heating, and due to the lack of heat storage, the faster the rate of fall in the later stages of system operation than other air flows. The higher the airspeed, the lower the temperature at 8 a.m., with the 9 m/s system being on average 1.35 °C lower than the 1.5 m/s system.

The water cycle surplus heat utilization systems with different air flow rates showed consistent temperature trends during the heat collection phase (Figure 18). At ground level, the average temperatures at the same height for the different speeds (1.5 m/s, 3.0 m/s, 4.5 m/s, 6.0 m/s, 7.5 m/s, and 9.0 m/s) were 25.39 °C, 24.46 °C, 24.55 °C, 24.49 °C, 24.39 °C, and 24.35 °C. At 0.5 m from the ground, the 1.5 m/s model was, on average, 1.67 °C higher than the other airflow models. As height increases, the 3 m/s curve gets closer to the 1.5 m/s curve, and the temperature values for the different air flows are closest at 2.5 m. In Figure 18g, the curve with an airflow of 1.5 m/s has the lowest temperature. During the heat storage phase of the day, when the ground is furthest from the fan, the lowest airflow produces a minor effect on the ground and, therefore, the highest temperature at ground level; the same can be explained in Figure 18b. As the height above the ground increases and the distance from the fan decreases, the curves begin to differ; as can be seen from the graph, the four curves of 4.5 m/s, 6.0 m/s, 7.5 m/s, and 9.0 m/s are relatively close to each other, and the difference between the variables is less than 0.15 °C; at the closest point of 2.5 m from the fan, the values of the variables have the slightest difference in this range; the simulation point at the roof is subjected to external influences, which has the lowest temperature. The airflow of 1.5 m/s is too tiny and has a negligible effect on the temperature field of the upper greenhouse. In comparison, the airflow of 9.0 m/s is too high, and the air circulation rate is too high and significantly affects the upper greenhouse’s temperature field.

As shown in

Table 3. Thermal performance of a water cycle surplus heat utilization system with different water flows.

Water Flow (m/s)		0.5	1.0	1.5	2.0	2.5	3.0
Thermal performance (MJ)	Collected heat	10.18 ± 0.0063	10.19 ± 0.0048	10.20 ± 0.0050	10.20 ± 0.0013	10.19 ± 0.0040	10.19 ± 0.0032
	Released heat	9.87 ± 0.0024	9.95 ± 0.0037	9.87 ± 0.0018	9.79 ± 0.0041	9.86 ± 0.0021	9.74 ± 0.0011

and

Table 4. Thermal performance of a water cycle surplus heat utilization system with different air flows.

Air Flow (m/s)		1.5	3.0	4.5	6.0	7.5	9.0
Thermal performance (MJ)	Collected heat	8.91 ± 0.0017	10.06 ± 0.0020	12.21 ± 0.0025	13.02 ± 0.0018	12.91 ± 0.0041	12.43 ± 0.0039
	Released heat	8.36 ± 0.0030	9.62 ± 0.0041	10.04 ± 0.0036	11.07 ± 0.0033	10.14 ± 0.0014	10.34 ± 0.0028

, the difference in heat collection of the system at different water flows is no more than 0.02 MJ, and the difference in heat dissipation is no more than 0.1 MJ. Water flow has a negligible effect on the water cycle surplus heat utilization system in this experiment. The difference between the heat collection and dissipation of the system at different air flows is significant. With the increased airflow, the heat collection and dissipation show a parabolic trend, with 6.0 m/s as the peak point.

3.5. Economic Analysis

The economic acceptability of the system is directly related to its application, so it is crucial to evaluate the financial cost as shown in

Table 5. Investment cost list of the system.

Items	Quantity	Value (USD/Year)
Air-water heat exchanger	1	83.7
Water supply and return pipes	3	8.4
Submersible pump	1	21.76
Tank	1	13.9
Automatic control system	1	4.5
Flowmeter	1	18.1
Installation cost	1	27.9
Total		178.26

and

Table 6. The heating costs of the water cycle surplus thermal energy utilization system.

Items	Proposed System	Coal Heating	Natural Gas Heating
Daily heating value	24.1 MJ/day	24.1 MJ/day	24.1 MJ/day
Annual heating period	150 day	150 day	150 day
Annual energy consumption	462.6 kwh	0.3 ton	112.9 m3
Unit price	0.07 USD/kwh	144 USD/ton	0.39 USD/m3
Annual heating cost	32.4 USD	43.2 USD	44.0 USD

. In the Shenyang area, the heating period of the CSG is usually five months, from the end of October to March of the following year. Under the experimental conditions, the annual heating costs of the system were reduced by 25 percent and 26 percent compared with coal-fired heating and natural gas heating, respectively.

4. Conclusions

In order to improve the efficiency of greenhouse energy use, a water cycle surplus thermal energy utilization system is proposed. Through a combination of experimental and simulation methods, changes in the temperature field in the greenhouse are studied under different wind and water flow rates, and the relevant operating parameters of the system are clarified. The results show that the heat collection and release of the system with different water flow rates is less than 0.1 MJ under a single variable control study, and the heat collection and release of the system with different wind flow rates is more than 2.0 MJ, which shows a parabolic trend with the increasing wind flow rate. In the daytime heat collection stage, the system can maintain the average indoor temperature fluctuations in the upper and lower 25 °C; in the night exothermic stage, it can maintain the average indoor temperature fluctuations in the upper and lower 12 °C. The average warming rate of the water cycle surplus thermal energy utilization system on a sunny day is 6.01 °C/h, 1.52 times higher than on a cloudy day. However, on a cloudy day, the system heat collection can also reach about 61% of the heat collection on a sunny day.

Therefore, in the choice of pump power, according to the actual situation, choosing to meet the head requirements of the pump power can be. From the airflow, choosing the air-water heat exchanger with an airflow of 6.0 m/s is recommended. The water cycle surplus thermal energy utilization system has a simple structure, is easy to install, and is easy to use. The system capacity can be increased by adjusting the size of the water tank, the number of heat exchangers, and so on, and the system can be used in combination with other heating equipment. However, under weather conditions such as persistent cloudy days, the stored energy supply during the day will not be able to meet the heating needs of the greenhouse, so more research is needed on heat transfer fluids, energy storage materials, and system structure to improve the efficiency of the system. Future research will also be integrated with greenhouse crops to study greenhouse heat demand and optimal system design in the presence of crops.