• Journal of Bio-Environment Control
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• v.26 no.4
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• pp.317-323
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• 2017

In this study, the heating performance and the energy saving effect of the heat pump system using hot waste water(waste heat) of the thermal power plant discharged from a thermal power plant to the sea were analyzed. The greenhouse area was $5,280m^2$ and scale of the heat pump system was 120 RT(Refrigeration Ton), which was divided into 30 RT, 40 RT and 50 RT. The heat pump system consisted of the roll type heat exchangers, hot waste water transfer pipes, heat pumps(30, 40, 50 RT), a heat storage tank and fan coil units. The roll type heat exchangers was made of PE(Poly Ethylene) pipes in consideration of low cost and durability against corrosion, because hot waste water(sea water) is highly corrosive. And the heating period was 5 months from October to February. During the heating performance test(12 hours), the inlet water temperature of evaporator was changed from $32^{\circ}C$ to $26^{\circ}C$, and heat absorption of he evaporator was changed from 175 kW to 120 kW. The inlet water temperature of the condenser rose linearly from $15^{\circ}C$ to $50^{\circ}C$, and the heat release of condenser was reduced by 40 kW from 200 kW to 160 kW. And the power consumption of the heat pump system increased from 30 kW to 42 kW. When the inlet water temperature of condenser was $15^{\circ}C$, the heating COP(Coefficient Of Performance) was over 7.0. When it was $30^{\circ}C$, it dropped to 5.0, and when it was above $40^{\circ}C$, it decreased to less than 4.0. It was analyzed that the reduction of heating energy cost was 87% when compared to the duty free diesel that the carbon dioxide emission reduction effect was 62% by recycling the waste heat of the thermal power plant as a heat source of the heat pump system.

• Smart Media Journal
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• v.12 no.10
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• pp.63-70
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• 2023

Recently, energy consumption for heating costs, which is 35% of smart farm energy costs, has increased, requiring energy consumption efficiency, and the importance of new and renewable energy is increasing due to concerns about the realization of electricity bills. Renewable energy belongs to hydropower, wind, and solar power, of which solar energy is a power generation technology that converts it into electrical energy, and this technology has less impact on the environment and is simple to maintain. In this study, based on the greenhouse heat storage tank and heat pump data, the factors that affect the heat storage tank are selected and a heat storage tank supply temperature prediction model is developed. It is predicted using Long Short-Term Memory (LSTM), which is effective for time series data analysis and prediction, and XGBoost model, which is superior to other ensemble learning techniques. By predicting the temperature of the heat pump heat storage tank, energy consumption may be optimized and system operation may be optimized. In addition, we intend to link it to the smart farm energy integrated operation system, such as reducing heating and cooling costs and improving the energy independence of farmers due to the use of solar power. By managing the supply of waste heat energy through the platform and deriving the maximum heating load and energy values required for crop growth by season and time, an optimal energy management plan is derived based on this.