The continued use of fossil fuels is contributing to severe environmental pollution and the establishment of an abnormal climate; consequently, alternative renewable energy sources are being actively investigated worldwide. Further, following global trends, numerous countermeasures aimed at improving carbon neutrality, promoting sustainable agriculture, and reducing fossil fuel dependence are being implemented in the Republic of Korea. Therefore, this study was conducted to investigate the application of renewable energies for greenhouse heating in the Republic of Korea. Three hybrid systems, numbered 1–3, were constructed using a pellet boiler, hydrothermal heat pump, and solar heat collection system, respectively. Thereafter, the heating performance, combined heat efficiency, energy consumption per temperature lifting, and energy cost per temperature lifting of the systems were compared. The combined thermal efficiency results showed no significant differences. However, in terms of energy consumption and cost, hybrid system 1 demonstrated 25.7 and 24.1% savings, respectively, compared with the other systems. Moreover, based on economic analysis via the net present value and life cycle cost analysis methods, the system reduced costs by 29.2 and 27.7%, respectively, compared with conventional fossil fuel boilers. Thus, hybrid system 1 was identified as the most economical system.

This study considers the possibility of utilizing agri-byproducts as energy sources via pelletization and torrefaction. Pellets were placed in a capsule and torrefied in an electrical furnace. Subsequently, they were cooled for 30 min, and their mass loss was measured. To investigate the resulting changes in fuel characteristics, ultimate and proximate analyses were performed, and calorific values were measured. To estimate the water absorption of the pellets, hygroscopicity evaluations were conducted. Based on the experimental results, the energy yield, lower heating value, and exergy were calculated to determine the optimum conditions for torrefaction. The calculation was performed by utilizing the useful exergy and standards applied to biomass power plants. We determined that torrefaction for agro-pellets should be conducted under low-to-intermediate temperatures (210–250 °C) within a period of 50 min. Under these conditions, 7–55% mass reductions were observed, the higher heating value increased from 4110 to 6880 kcal kg⁻¹, and the lower heating value changed from 3780 to 6520 kcal kg⁻¹ owing to reduced hygroscopicity. So, Agro-byproducts can contribute to the practical application by improving the heating value through torrefaction as an alternative to wood pellets.

Accurate classification of multilayered plants is vital to understanding the interaction of each canopy in a greenhouse environment and designing plant models based on the irradiation, canopy temperature, transpiration, and heat flux by the leaf area index (LAI). Based on the measurements from a greenhouse in operation, plant models for each LAI are discussed in this study. If the heat flux between plants and air can be accurately predicted through plant models using LAI, the heating and cooling load in various virtual greenhouses with densely planted crops can be predicted. To enhance the measurement accuracy, a temperature and humidity sensor with an aspirated shield, an infrared canopy sensor, and CO₂ sensor were installed. The plant environment was measured with a portable pyranometer, porometer, ceptometer, and anemometer. The measurements were inputted to the plant models, and the canopy temperature was calculated. The canopy temperature from the models was evaluated for reliability by comparing it with field measurements (R² = 0.98 and RMSE = 0.46). The results indicated that the big leaf model is suitable when the air circulation layer is larger than the canopy size, but when physical properties of the plant change band affect the LAI, as in a greenhouse, a multi-layer model should be considered.

Although smart farms are considered an alternative to traditional agriculture, they require large amounts of energy and high investment costs, hindering their efficient implementation. In the Republic of Korea, the energy supply is primarily for heating rather than cooling, necessitating the accurate prediction of the greenhouse internal temperature to determine the feasibility of agricultural management while using renewable energy. This study developed a model (TRNSYS) for predicting the internal temperature of a greenhouse using building energy simulation. A greenhouse heating experiment was conducted using a hybrid heating system simulated by TRNSYS to analyze the prediction model. The regression analysis of the experimental and simulation results revealed an R² and RMSE of 0.8834 and 3.61, respectively. A comparative analysis was conducted with the existing hot air heating system to evaluate the heating performance and economic feasibility of the hybrid system. Overall, the heating performance exhibited satisfactory results, whereas the economic analysis, based on life cycle cost, revealed a cost reduction effect of 9.45%. Hence, greenhouse heating using renewable energy can replace conventional fossil fuels with economic advantages. Moreover, the prediction of the internal temperature of the greenhouse will facilitate the design of a systematic smart farm business to prevent duplicate investment.

Global warming is accelerating due to the increase in greenhouse gas emissions. Accordingly, research on the use of biomass as energy sources, is being actively conducted worldwide to reduce CO₂ emissions. Although the production of agro-byproducts is vast, their utilization for energy production has not been fully investigated. This study suggests an optimal torrefaction process condition for agro-byproducts, such as grape branch and perilla, that have moisture content but low calorific values. To determine whether these agro-byproducts can be used for energy sources as substituents of fossil fuels, a mass reduction model was established and validated via experimental results. Thermogravimetric analysis was conducted for different heating rates, and the activation energy and frequency factor were derived through the analysis. The model was developed by changes in rate constants, moisture content, ash content, and lignocellulose content in biomass. To ascertain the optimal torrefaction conditions, fuel characteristic analysis and changes in energy yield of torrefied grape branch and perilla were investigated. The optimal torrefaction conditions for grape branch and perilla were 200 °C for 40 min and 230 °C for 30 min, respectively. The comparison result of the experiment and simulation at the optimum conditions of mass reduction were 1.42%p and 1.51%p, and 15 °C/min and 7.5 °C/min at heating rate, respectively.