There is a vast range of approaches for modeling a microclimate in a greenhouse from simple static models to more complex dynamic models. A list of these models has been reviewed by Sethi et al (Sethi et al. 2013). Simple models consist of only sizing the heating and ventilation of the greenhouse while complex dynamic models might consider energy and mass balance over the various component of the system from soil and air to structural parts. Typically, dynamic models are much more accurate since they utilize more precision in predicting the energy model of the system which results in a closer comparison to the actual demands of the system and also a better simulation of climate change inside of the greenhouse which may improve the crop yield by leading decision-making variables to their optimum solution.
Greenhouses need to preserve an acceptable change in their climate throughout the day which may include both cooling and heating demand. Cooling demand is required mostly during the noontide where sun irradiance meets its maximum peak. To avoid this heat load, greenhouses commonly deploy shades to prevent overheating and exceeding the allowable temperature range. With advancements in semitransparent organic solar cells and the Commercialization of this technology, these solar cells could be used as semitransparent ceiling panels which not only reduce solar radiation during noon but also reduce the total energy demand of the system by producing electricity.
This study focuses on modeling the microclimate and energy demand of a greenhouse with different structural shape and compare the total energy demand for two cases, where semitransparent organic solar cells have been used as ceiling versus commonly used materials. Figure 1 shows the conceptual model of the proposed system.
There exist many commercial software packages capable of dynamically modeling a greenhouse environment (such as Energy Plus, ESP-r, etc.). For this study, The Design Builder software has been used to model the proposed system. The Design-Builder software is capable of integrating many types of solar panels, including the semitransparent type which is used in this study, into the greenhouse structure to model the energy demand (for cooling, heating, and ventilation) and electricity production. This software provides the possibility of defining custom OPV specifications to match the requirements.
The energy balance of the system was simulated in five different locations to consider different types of climates and solar radiation. The mean monthly outdoor temperature and humidity over the years for each location were used to visualize an accurate climate over the year. Figure 2 shows the model structure and procedure flow diagram for the greenhouse structure selection.
The present model aims to solely assess the overall balance of energy and investigate the percentage of energy-saving and whether or not this semitransparent organic solar cell integrated greenhouse could achieve a zero-energy demand. However, usage of any type of solar cell will inevitably reduce the crop yield due to diminishing solar radiation which is delivered to the plants. This modified solar radiation may affect the plant's growth rate but due to the inability to model these changes, the impact could only be assessed indirectly. Since photosynthetically active radiation (PAR) spectrum in 400–700 nm is not absorbed by semitransparent organic solar cells, effects on crop yield should be minimal; However, it should be noted that plants are also able to absorb some UV and far red spectrum in 320–400 nm and 650–730 nm, respectively (Ravishankar et al. 2020, Runkle &Fisher 2004).
2.1 Simulated Model
To compare the energy consumption and system loads of an OPV integrated greenhouse with a typical greenhouse, multiple models with different geometrical structures have been developed with the aid of the Design-Builder software which is used to simulate the energy usage, cooling/heating loads of the system and the electricity generation of the OPV panels.
The main energy flows in the proposed model as shown in Fig. 3 include energy transfer to/from: (1) air by ventilation, (2) ambient by radiation from greenhouse structure, (3) ambient by radiation from plants, (4) ambient by convection from greenhouse structure, (5) soil by conduction, (6) internal heater or cooler. There are other ways for energy to transfer between the greenhouse and the environment but due to their small values compared to the above-mentioned ones, they can be omitted.
The heat transfer to the greenhouse can be based on two sensible and latent sections. For heavy plant rooms with 24hr low-medium internal gains from equipment and transient occupancy the latent load is considered to be based on 4 sections: (1) Gains: the lumped gains into space from people, equipment, lights, etc. The coefficient of 50 watts per square meter is considered for the greenhouses. This coefficient is referred to as power density. (2) Occupancy: this section includes occupancy levels and times and metabolic activities and sets the metabolic rate according to the level of activity within the space. The metabolic factor accounts for people of various sizes. It is considered 1 for men, 0.85 for women, and 0.75 for children. In the greenhouses, this coefficient is considered to be 0.9. The density of the population is considered to be 10.39 people/m2 for greenhouses. The greenhouse working profile is 5 days a week from 9 am to 5 pm. (3) Other gains: there are also some other loads including computers, office equipment, catering, process, and miscellaneous equipment. The main load in this section includes greenhouse equipment with a 24hr workday profile and general lighting with a workday profile from 9 am to 5 pm and considering the latent load of agricultural products, this coefficient is considered to be 50 W/m2. (4) Environmental control: the data related to the environmental and comfort requirements of greenhouses is as follows; Heating set-point temperature is considered to be 22 ˚C; Cooling set-point temperature is considered to be 26 ˚C; Fresh air levels required per person, defines mechanical ventilation air change rates that considered to be 10 l/s-person; Humidity in the zone at the time of maximum Sensible load that is considered to be 60%.
Sensible heating is the heating effect of the HVAC system action on the heat balance, in particular the heating effect of introducing air that is warmer than the zone air. Likewise, sensible cooling is the cooling effect of the HVAC system on the zone. Note that these are not always directly related to heating and cooling coil energy delivery, especially because of the effect of free cooling from the outside air. So, for example, even if there is no cooling coil operational at a particular time, the sensible cooling output on the heat balance can be high due to the introduction of relatively cooler outside air into space through mechanical ventilation. These Sensible Heating/Cooling outputs will also include a component due to fans (if operational) which will tend to warm air that moves through it.
The material and other parameters used for the model simulation (e.g. OPV panel type, building structure material, etc.) are shown in Table 1.
Table 1
Simulated model properties
Item | Type / Value |
OPV panel efficiency | 8% |
Glazing properties | 2 layer Polycarbonate (3.5mm) with air (3mm) |
Structure material | Light weight metallic cladding |
Dimensions | 10m × 4m × 3m |
Temperature range (occupancy) | 22°C < T < 26°C |
Temperature range (unoccupancy) | 17°C < T < 28°C |
Relative Humidity range | 70% < RH < 90% |
Mechanical ventilation | 1 ac/h |
Cooling/Heating system type | Electrical from grid |
Heating system COP | 0.83 |
Cooling system COP | 1.67 |
2.2 Climate Condition
Assuming tomatoes as the target crop of the greenhouse (which is one of the largest greenhouse crops globally (Heuvelink 2018)) indoor conditions are set to 22°C < T < 26°C and 17°C < T < 28°C for occupancy and unoccupancy, respectively; while relative humidity is kept within the range of 70%-90% (Ahamed et al. 2018, Schwarz et al. 2014).
Ventilation is provided by two fans located on the north and south end walls, providing 1 air change per hour (ACH) (ASHRAE 2015, Ravishankar et al. 2020). Air infiltration is considered to be 1 ACH (ASHRAE 2015). Cooling and heating systems are both electrical with COP of 0.83 and 1.67, respectively.
To obtain a comprehensive model, energy demand for both cooling and heating loads, also, greenhouse microclimate conditions in five different locations based on the five different climates have been simulated. These are the most known climates on the earth that covers almost all of the globe. We have selected a representative city for each of these climates to compare the results in different climates and to be able to select the best geometrical structure for each climate. Table 2 lists the different climate conditions and their representative cities.
Table 2
Different climate conditions and their representative cities for the simulation
Climate type | City |
Tropical | Miami, United States |
Dry (desert and semi-arid) | Tehran, Iran |
Cold semi-arid | Phoenix, United States |
Temperate/mesothermal | Barcelona, Spain |
Continental/microthermal | Toronto, Canada |
It should be noted that there is also a polar climate, however, due to unpracticality and not being suitable for establishing a greenhouse (due to not having proper sunlight), we omitted this type of climate.
2.3 System Geometry
To compare energy balance, as illustrated in Fig. 4, eight different geometry for the greenhouse structure have been compared. These shapes consist of the gable, flat arch, tunnel, Ridge & furrow, sawtooth, skillion, uneven, and A-frame roof shapes. While solely comparing the energy balance of these geometries may not be a wise comparison due to the different internal volumes of these geometries, since the ultimate goal of the greenhouse is to grow plants, it is meaningful to fix plant area as the main variable and presume different internal volume as an inevitable choice, because wall height cannot be changed since it will result in different radiation absorption from sun and environment. Except for flat arch and tunnel shape geometries, the height for all shapes is equal. For reducing structural shadow, the greenhouse is orientated north-south. Walls are made up of 2 layers of polycarbonate with a thickness of 3.5mm with 3mm of air between them. Angle for slope-shaped Roof is typically 27˚to 30˚ (ASHRAE 2015) which is applied to gable shape roof; For other roof shapes, equal height regarding gable shape roof is considered for purpose of equaling internal volume of the greenhouse.
2.4 Solar Radiation and Lighting
Obtaining detailed information on solar radiation has significant importance for not only calculating the thermal load of the greenhouse but also the power generation of solar cells.
For calculating the solar cell's power generation, sun radiation on the roof area should be calculated. The Design-Builder program is capable of reporting the electricity generation by defining the OPV specification in the software. For greenhouse applications, spectrally engineered semitransparent organic solar cells (ST-OSCs) have been developed. A quaternary OSC with 17.71% power conversion efficiency is achieved with the use of newly designed multi-component blends. It is particularly noteworthy that ST-OSCs with 13.08% PCE and a plant growth factor of 24.7% were developed through non-halogenated solvent fabrication, demonstrating promise as an eco-friendly greenhouse photovoltaic (Wang et al. 2021). In this research, we considered an efficiency of 8% for simulation. As a result, we are not only close to advances in organic solar cell efficiency but also close to industry efficiency.