• Journal of Biosystems Engineering
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• v.37 no.1
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• pp.19-27
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• 2012

Purpose: Utilizing air thermal energy during over-heated time in the greenhouse is a necessary component to save greenhouse heating costs for nighttime. However, there is no practical way to implement the related principles. Methods: In this study, a heating and cooling system which utilizes the surplus air thermal energy in a greenhouse was developed. Available air thermal energy and heating load for this experimental glasshouse were estimated based on temperature conditions of the plant growth and weather data. Results: Estimated values were 400 MJ/day for maximum surplus air thermal energy and 340 MJ/day for maximum heating energy which were target values of the design as well. The system consists of a heat pump, fan-coil units and heat storage tanks which are divided into low and high temperature tanks. Moreover, a new control logic was developed for surplus air thermal energy utilization. Conclusions: This paper explains the details of conceptual design process of the system. Results of test operations showed that the developed system performed the recovery and supply of the thermal energy according to design purposes.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11c
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• pp.639-646
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• 2000

Hot air heater with light oil combustion is the most common heater for greenhouse heating in the winter season in Korea. However, since the heat efficiency of the heater is about 80%, considerable unused heat in the form of exhaust gas heat discharges to atmosphere. In order to capture this exhaust gas heat a heat recovery system for plant bed heating in the greenhouse was built and tested in the hot air heating system of greenhouse. The system consists of a heat exchanger made of copper pipes, ${\phi}\;12.7{\times}0.7t$ located inside the rectangular column of $330{\times}330{\times}900mm$, a water circulation pump, circulation plastic pipe and a water tame The total heat exchanger area is $1.5m^2$, calculated considering the heat exchange amount between flue gas and water circulated in the copper pipes. The system was attached to the exhaust gas path. The heat recovery system was designed as to even recapture the latent heat of flue gas when exposing to low temperature water in the heat exchanger. According to performance test it can recover 45,200 to 51,000kJ/hr depending on the water circulation rates of 330 to $690{\ell}$/hr from the waste heat discharged. The exhaust gas temperature left from the heat exchanger dropped to $100^{circ}C$ from $270^{circ}C$ by the heat exchange between the water and the flue gas, while water gained the difference and temperature increased to $38^{circ}C$ from $21^{circ}C$ at the water flow rate of $690{\ell}$/hr. And, the condensed water amount varies from 16 to $43m{\ell}$ at the same water circulation rates. This condensing heat recovery system can reduce boiler fuel consumption amount in a day by 34% according to the feasibility study of the actual mimitomato greenhouse. No combustion load was observed in the hot air heater.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.61-64
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• 2002

We constructed climagraphs for 16 regions of Korea by using the average monthly minimum air temperature, maximum air temperature and global radiation. We characterized the outside climate requirements corresponding to the climate requirements of crops in greenhouses. The climagraphs allow to decide the appropriate climate periods for greenhouse cultivation without heating and cooling equipment. These graphs may be used for analyzing climatic characteristic of a given area, selecting the suitable region and greenhouse and making a rational plan for greenhouse cropping in Korea. We found difficulty in deciding the beginning and end of greenhouse heating and cooling period due to insufficient references.

• Journal of Energy Engineering
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• v.15 no.3 s.47
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• pp.194-201
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• 2006

Greenhouses should be heated during nights and cold days in order to fit growth conditions in greenhouses. Ground source heat pump (GSHP) systems are recognized to be outstanding heating and cooling systems. A horizontal GSHP system with thermal storage tank was installed in greenhouse and investigated the performance characteristics. The reasons for using thermal storage tank were discussed in detail. Thermal storage tank can provide heat for heating load that is larger than GSHP system heating capacity. The results of study showed that the heating coefficient of performance of the heat pump system was 2.69.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.447-452
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• 2007

Greenhouses should be heated during nights and cold days in order to fit growth conditions in greenhouses. Ground source heat pump(GSHP) or geothermal heat pump system(GHPs) is recognized to be outstanding heating and cooling system. Horizontal GSHP system is typically less expensive than vertical GSHP system but requires wide ground area to bury ground heat exchanger(GHE). In this study, a horizontal GSHP system with thermal storage tank was installed in greenhouse and investigated as performance characteristics. In the daytime, heating load of greenhouse is very small or needless because solar radiation increases inner air temperature. The results of study showed that the heating coefficient of performance of the heat pump ($COP_h$) was 2.9 and the overall heating coefficient of performance of the system($COP_{sys}$) was 2.4. Heating energy cost was saved 76% using the horizontal GSHP system with thermal storage tank.

• Journal of Hydrogen and New Energy
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• v.34 no.6
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• pp.667-672
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• 2023

This study proposes polymer electrolyte membrane fuel cell (PEMFC) based cogeneration system for greenhouse heating and cooling. The main scope of this study is to examine the proposed cogeneration system's suitability for the 660 m²-class greenhouse. A 25 kW PEMFC system generates electricity for two identical air-cooled heat pumps, each with a nominal heating capacity of 70 kW and a cooling capacity of 65 kW. Heat recovered from the fuel cell supports the heat pump, supplying hot water to the greenhouse. In cooling mode, the adsorption system provides cold water to the greenhouse using recovered heat from the fuel cell. As a result, the cogeneration system satisfies both heating and cooling capability, performing 175 and 145 kW, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.6
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• pp.1-8
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• 2017

The purpose of this study was to provide basic data for development of environmental design technology for greenhouses constructed in reclaimed lands. We analyzed the climatic conditions around seven major reclaimed land areas in Korea, which have a plan to install advanced horticultural complexes. The characteristics of heating load through the thermal environment measurement of the greenhouse in Saemangeum were analyzed. The part to be applied to the environmental design of the greenhouses in reclaimed lands were reviewed. The overall heat transfer coefficient of the experimental greenhouse with the aluminum screen and multi-layer thermal curtain averaged $3.79W/m^2^{\circ}C$. It represents a 44 % heat savings rate compared with plastic greenhouses with a single covering, which was significantly lower than that of the common greenhouses with 2-layer thermal curtains. This is because the experimental greenhouse was installed on reclaimed land and wind was stronger than the inland area. Among the total heating load, the transmission heat loss accounted for 96.4~99.9 %, and the infiltration loss and the ground heat exchange were low. Therefore, it is necessary to take countermeasures to minimize the transmission heat loss for greenhouses constructed in reclaimed lands. As the reclaimed land is located on the seaside, the wind is stronger than the inland area, and the fog is frequent. Especially, Saemangeum area has 2.6 times stronger wind speed and 3.4 times longer fog duration than the inland area. In designing the heating systems for greenhouses in reclaimed lands, it is considered that the maximum heating load should be calculated by applying the wind coefficient larger than the inland area. It is reasonable to estimate the operation cost of the heating system by applying the adjustment factor 10 % larger than the average in calculating the seasonal heating load.

• Journal of Practical Agriculture & Fisheries Research
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• v.6 no.1
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• pp.143-154
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• 2004

The value of daily heating degree hour(described as DH hereafter) is essential for calculating the heating load of a greenhouse during the winter months. Many researchers have so for proposed different models for estimating DH value. Models for estimating DH have been investigated DH(unit, ℃·h·year^-1) in this paper. The comparisons of standard and existed DH values were made to know the estimation error of each model proposed so far. The standard DH values and other proposed DH values have were obtained for the inside setpoint temperatures of 9, 13, 16 and 20℃ in greenhouse, estimated based on meterological data from 1961 to 2000 according to locals, and standard DH values were independent and existed DH values were dependent. Among the various model, the one developed theoretically by Mihara modified to author was the best fitting for standard DH values. The DH values were obtained for the inside setpoint temperature of 9, 13, 16 and 20℃ by Modified Mihara's model. A new DH contour line graph was proposed using Modified Mihara's model. Using the DH contour line graph, the DH values can be obtained easily for any setpoint according to local.

• Journal of Bio-Environment Control
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• v.20 no.2
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• pp.83-92
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• 2011

This study is about an analysis of surplus solar energy by important greenhouse type using Typical Meteorological Year (TMY) data which was secured in order to provide basic data for designing an optimum thermal storage system to accumulate surplus solar energy generated in greenhouses during the daytime. The 07-auto-1 and 08-auto-1 types showed similar heat budget tendencies regardless of greenhouse types. In other words, the ratios of surplus solar energy were about 20.0~29.0% regardless of greenhouse type. About 54.0~225.0% and 53.0~218.0% of required heating energy will be able to be supplemented respectively according to the greenhouse types. The 07-mono-1 and 07-mono-3 types also showed similar heat budget tendencies regardless of greenhouse types. In other words, the ratios of surplus solar energy were about 20.0~26.0% and 21.0~27.0% respectively by greenhouse type. About 57.0~211.0% and 62.0~228.0% of required heating energy will be able to be supplemented by greenhouse type. Except for Daegwallyeong and Suwon area, other regions can cover heating energy only by surplus solar energy, according to the study.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.4
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• pp.129-134
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• 2018

Recently, the artificial neural network (ANN) model is a promising technique in the prediction, numerical control, robot control and pattern recognition. We predicted the outside temperature of greenhouse using ANN and utilized the model in greenhouse control. The performance of ANN model was evaluated and compared with multiple regression model(MRM) and support vector machine (SVM) model. The 10-fold cross validation was used as the evaluation method. In order to improve the prediction performance, the data reduction was performed by correlation analysis and new factor were extracted from measured data to improve the reliability of training data. The backpropagation algorithm was used for constructing ANN, multiple regression model was constructed by M5 method. And SVM model was constructed by epsilon-SVM method. As the result showed that the RMSE (Root Mean Squared Error) value of ANN, MRM and SVM were 0.9256, 1.8503 and 7.5521 respectively. In addition, by applying the prediction model to greenhouse heating load calculation, it can increase the income by reducing the energy cost in the greenhouse. The heating load of the experimented greenhouse was 3326.4kcal/h and the fuel consumption was estimated to be 453.8L as the total heating time is $10000^{\circ}C/h$. Therefore, data mining technology of ANN can be applied to various agricultural fields such as precise greenhouse control, cultivation techniques, and harvest prediction, thereby contributing to the development of smart agriculture.