• International Journal of Fluid Machinery and Systems
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• v.4 no.1
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• pp.150-160
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• 2011

This study focuses on the Achard turbine, a vertical axis, cross-flow, marine current turbine module. Similar modules can be superposed to form towers. A marine or river hydropower farm consists of a cluster of barges, each gathering several parallel rows of towers, running in stabilized current. Two-dimensional numerical modelling is performed in a horizontal cross-section of all towers, using FLUENT and COMSOL Multiphysics. Numerical models validation with experimental results is performed through the velocity distribution, depicted by Acoustic Doppler Velocimetry, in the wake of the middle turbine within a farm model. As long as the numerical flow in the wake fits the experiments, the numerical results for the power coefficient (turbine efficiency) are trustworthy. The overall farm efficiency, with respect to the spatial arrangement of the towers, was depicted by 2D modelling of the unsteady flow inside the farm, using COMSOL Multiphysics. Rows of overlapping parallel towers ensure the increase of global efficiency of the farm.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.E
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• pp.47-54
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• 1995

Irrigation water has been mainly used for paddy rice. Irrigated paddy land tends to be recently converted to land for green house, farm house, and rural-industrial complex. Consequently, demand of water for crops, domestic & industrial, rural recreations, small-scaled hydropower, livestocks, and environment in the rural area, so called rural water, is rapidly increasing. In order to supply rural water, water in the existing irrigation reservoir could be enlarged by repairment of irrigation canal and reinforcement of irrigation reservoir, and be saved by the operation rule curve, utilization of dead water, and balanced storage management.

• 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.