Abstract

In this study, seven of the most commonly applied covering materials in smart farms are selected as the representative samples for analysis, namely, glass, soft film (polyethylene, PE), soft film (polyolefin, PO), rigid plastic film (ethylene tetra fluoro ethylene, ETFE), rigid plastic sheet (poly methyl methacrylate, PMMA), rigid plastic sheet (polycarbonate, PC double layer), and woven film. For each covering material, visible light transmittance and reflectivity, solar radiation transmittance and reflectivity, thickness, solar heat gain coefficient, and the coefficient of heat transmission are measured according to the test methods in the Korean Industrial Standards (KS) to derive input data for the respective materials. In addition, using the optical and thermal input data as derived above, simulations are performed on the cooling load and daylight characteristics of smart farms to derive basic reference data for the selection of adequate covering materials for the design. Based on the analysis result of the daylight characteristics for each covering material, for a shading rate of 60%, the average values of indoor illuminance were 19,879 lux, 20,012 lux, 19,393 lux, 19,555 lux, 16,560 lux, 16,228 lux, and 11,173 lux for glass, PE film, PO film, ETFE, woven film, PMMA, and PC double layer, respectively, between 6 a.m. and 8 p.m., which correspond to the hours when daylight enters indoor spaces. Considering the target light intensity for strawberry growth at 10,000–40,000 lux, the above results confirm that all the sample covering materials had an indoor illuminance level above the lower limit range of the target light intensity. For the cooling load evaluation, the PC double layer had the lowest value of 482.8 W/m2, and PO film had the highest value of 633.8 W/m2. The difference between the cooling loads of the PC double layer and the PO film is 151 W/m2, which amounts to 23.8%, thus indicating that the selected covering material significantly impacts the cooling load. The cooling load exhibited a pattern similar to that of the coefficient of heat transmission and solar heat gain coefficient, which are key influencing factors for most of the sample materials. However, for PMMA, the cooling load was low because it had a higher coefficient of heat transmission than other materials, but its solar heat gain coefficient was relatively low. Another possible reason for the difference is that the solar heat gain coefficient impacts the cooling load. When the cooling set temperature was controlled from Case 1-1 to Case 1-2, the cooling load decreased by 10.7% on average. In addition, when the cooling set temperature changed from Case 1-1 to Case 1-3, the cooling load decreased by 26.1% on average. For cooling set temperature control, maintaining the temperature around the lower temperature range of the optimal growth temperature of the plants increases the yield, but it also incurs increased cooling load and cost. In terms of cost only, while maintaining the cooling temperature for 24 h at 30 °C, which is the upper limit of the optimal growth temperature, would be advantageous, it will lead to a deterioration of the quality and reductions in yield. Therefore, as follow-up studies for further investigation of the findings of this research, there is the need for an evaluation of the yield and quality with respect to the range of cooling set temperatures. When the internal shading rate was increased to 40% (Case 2-2) with reference to Case 2-1, which was a greenhouse without the application of internal shading, the cooling load decreased by 27.4% on average. Furthermore, when the internal shading rate increased to 50% (Case 2-3) with reference to Case 2-1, the cooling load decreased by 29.3% on average. When the internal shading rate increased to 60% (Case 2-4), the cooling load decreased by 31.5% on average.

Highlights

  • ObjectivesThe projected growth of the global market in the smart farm sector is expected to be approximately USD 4.08 billion in 2022, indicating an annual average growth rate of16.4% since 2016

  • When the internal shading rate increased to 60% (Case 2-4), the cooling load decreased by 31.5% on average

  • The results of the visible transmittance, visible reflectivity, solar radiation transmittance, solar radiation reflectivity and thickness tests are shown in Table 7 to examine the daylight performance of seven samples, and triplicate tests of visible transmittance and visible reflectivity were conducted for wavelengths of light ranging from 300 nm to 2500 nm; the values are presented in Figures 12 and 13, respectively

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Summary

Background and Study Objectives

The projected growth of the global market in the smart farm sector is expected to be approximately USD 4.08 billion in 2022, indicating an annual average growth rate of. In the greenhouse design phase, the selection of the covering material is a critical factor when calculating the heating and cooling loads. The distinct contribution of this research is that to achieve improved accuracy in the simulation results, the transmittance, reflectivity, coefficient of heat transmission and thickness, etc., which are key influencing factors, were measured according to the test methods in the Korean Industrial Standards (KS) to derive input data for each covering material, whereas most of the existing works performed simulation analysis using the input data from manufacturers or the previous literature. Based on the derived optical and thermal input data obtained for each covering material, the cooling load and daylight characteristics of smart farms were simulated to obtain basic reference information for selecting covering materials in the design of greenhouses.

Types of Covering Materials for Smart Farms
Test Standards and Methods for Single-Component Covering Material
Test Standard and Methods of Composite Covering Material
International Standards of Greenhouse Design
Light Saturation and Light Compensation Level
Overview of Simulation Program and Algorithm for Light Environment Analysis
Experimental Setup
Overview of the Study Building
Simulation Conditions
Simulation Variables
Result of Transmittance and Reflectivity Test Obtained by Covering Material
Result
Result of Coefficient of Heat Transmission Test by Covering Material
Result of Daylight Characteristics Simulation for Covering Material
Result of Cooling Load Simulation by Covering Material
Conclusions
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