• Journal of the Korean Solar Energy Society
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• v.40 no.4
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• pp.35-44
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• 2020

Currently, various policies regarding ecofriendly vehicles are being proposed to reduce carbon emissions. In this study, the required areas for charging electric vehicle (EV) batteries using electricity produced by photovoltaic (PV) power plants were estimated. First, approximately 2.4 million battery EVs, which represented 10% of the total number of vehicles, consume approximately 404 GWh. Second, the power required for charging batteries is approximately 0.3 GW, and the site area of the PV power plant is 4.62 ㎢, which accounts for 0.005% of the national territory. Third, from the available sites of buildings based on the region, Jeju alone consumes approximately 0.2%, while the rest of the region requires approximately 0.1%. Fourth, Seoul, which has the smallest available area of mountains and farmlands, utilizes 0.34% of the site for PV power plants, while the other parts of the region use less than 0.1%. The results of this study confirmed that the area of the PV power plant site for producing battery-charging power generated through the supply of EVs is very small. Therefore, it is desirable to analyze and implement more specific plans, such as efficient land use, forest damage minimization, and safe maintenance, to expand renewable energy, including PV power.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.502-508
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• 2012

Heliostat, as a concentrator to reflect the incident solar energy to the receiver, is the most important system in the tower-type solar thermal power plant since it determines the efficiency and ultimately the overall performance of solar thermal power plant. Thus, a good sun tracking ability as well as a good optical property of it are required. Heliostat sun tracking system uses usually an open loop control system. Thus the sun tracking error caused by heliostat's geometrical error, optical error and computational error cannot be compensated. Recently use of sun tracking error model to compensate the sun tracking error has been proposed, where the error model is obtained from the measured ones. This work is a development of heliostat sun tracking error measurement and compensation method using BCS (Beam Characterization System). We first developed an image processing system to measure the sun tracking error optically. Then the measured error is modeled in linear polynomial form and neural network form trained by the extended Kalman filter respectively. Finally error models are used to compensate the sun tracking error. We also developed the necessary image processing algorithms so that the heliostat optical properties such as maximum heat flux intensity, heat flux distribution and total reflected heat energy could be analyzed. Experimentally obtained data shows that the heliostat sun tracking accuracy could be dramatically improved using either linear polynomial type error model or neural network type error model. Neural network type error model is somewhat better in improving the sun tracking performance. Nevertheless, since the difference between two error models in compensation of sun tracking error is small, a linear error model is preferred in actual implementation due to its simplicity.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.10
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• pp.1423-1427
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• 2014

Quantity of the solar power generation is heavily influenced by weather. In other words, due to difference in insolation, different quantity may be generated. However, it does not mean all areas with identical insolation produces same quantity because of various environmental aspects. Additionally, geographic factors such as altitude, height of plant may have an impact on the quantity. Hence, through this research, we designed a system to predict efficiency of the solar power generation system by applying insolation, weather factor such as duration of sunshine, cloudiness parameter and location. By applying insolation, weather data that are collected from various places, we established a system that fits with our nation. Apart from, we produced a geographic model equation through utilizing generated data installed nationwide. To design a prediction model that integrates two factors, we apply fuzzy algorithm, and validate the performance of system by establishing simulation system.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.34 no.2
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• pp.145-151
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• 2010

In this study, an absorption power cycle, which can be used for a low-temperature heat source driven power cycle such as geothermal power generation, was investigated and optimized in terms of power by the simulation method. A steady-state simulation model was adopted to analyze and optimize its performance. Simulations were carried out for the given heat source and sink inlet temperatures, and the given flow rates were based on the typical power plant thermal-capacitance-rate ratio. The cycle performance was evaluated for two independent variables: the ammonia fraction at the separator inlet and the maximum cycle pressure. Results showed that the absorption power cycle can generate electricity up to about 14 kW per 1 kg/s of heat source when the heat source temperature, heat sink temperature, and thermal-capacitance-rate ratio are $100^{\circ}C$, $20^{\circ}C$, and 5, respectively.

• Journal of the Korean Solar Energy Society
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• v.31 no.2
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• pp.37-46
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• 2011

The GWNU (Gangnung-Wonju national university) solar radiation model was developed with radiative transfer theory by Iqbal and it is applied the NREL (National Research Energy Laboratory). Input data were collected and accomplished from the model prediction data from RDAPS (Regional Data Assimilated Prediction Model), satellite data and ground observations. And GWNU solar model calculates not only horizontal surface but also complicated terrain surface. Also, We collected the statistical data related on photovoltaic power generation of the Korean Peninsula and analyzed about photovoltaic power efficiency of the Gangwon region. Finally, the solar energy resource and photovoltaic generation possibility map established up with 4 km, 1 km and 180 m resolution on Gangwon region based on actual equipment from Shinan solar plant,statistical data for photovoltaic and complicated topographical effect.

• Advances in environmental research
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• v.1 no.2
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• pp.125-142
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• 2012

Clean development mechanism (CDM) validity study was conducted to suggest better and more adaptable CDM scenario on water treatment plant (WTP). Potential four scenarios for CDM project; improvement of intake pumping efficiency, hydro power plant construction, solar panel construction and system optimization of mechanical mixing process were evaluated on S-WTP in Korea. Net present value (NPV) of each scenario was estimated based on sensitivity analysis with the variable factors to investigate the CDM validity percentile. Hydro power plant construction was the best option for CDM business with 97.76% validity and $1,127,069 mean profit by 9,813 $tonsCO_2e$/yr reduction. CDM validity on improvement of intake pumping efficiency was 90.2% with $124,305 mean profit by huge amount of $CO_2$ mitigation (10,347 $tonsCO_2e$/yr). System optimization of mechanical mixing process reduced 15% of energy consumption (3,184 $tonsCO_2e$/yr) and its CDM validity and mean profit was 77.25% and $23,942, respectively. Solar panel construction could make the effect of 14,094 $tonsCO_2$ mitigation annually and its CDM validity and mean profit was 64.68% and $228,487, respectively.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.2
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• pp.164-171
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• 2011

The objectives of this study are to propose a suitable treatment facility for waste energy recovery after analyzing the waste generation and disposal situation in Jejudo, to establish the plan to install the solar photovoltaics and wind power plant considering the site conditions and finally to establish the environmental energy town plan in conjunction with the existing facilities. The food waste biogas plant is selected as the treatment capacity of 200 ton/day. It is estimated that the biogas plant will produce the electricity of 7,594 MWh per year, which will reduce the greenhouse gas of 4,177 $tCO_2$ per year. The solar photovoltaics and wind power plant will produce the electricity of 13,410 MWh per year, which will reduce the greenhouse gas of 7,375 $tCO_2$ per year. Environmental energy town will give us the reduction of operating cost by centralized treatment of residues and byproducts, and by efficient utilization of produced energy.

• Journal of Institute of Convergence Technology
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• v.3 no.1
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• pp.37-40
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• 2013

Plant factory industry as a new agriculture is in the spotlight. In this paper, we experimented plant factory applied photovoltaic system and LED lighting. For growing the plant, red, blue and white LED were placed into 1:4:3. Electric power generated by the photovoltaic system was supplied on DC power supply instead of AC. The designed and experimented power generation amount per day of photovoltaic system were 2,860 Wh and 2,272 Wh respectively. Plant has not been grown at the dead space of LED lighting so it is required to array LED lighting.

• Journal of Environmental Science International
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• v.28 no.2
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• pp.219-224
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• 2019

In this study, we evaluated the energy production from plant-microbial fuel cells using representative indoor plants, such as Scindapsus aureus and Clatha minor. The maximum power density of microbial fuel cell (MFC) using S. aureus ($3.36mW/m^2$) was about 2 times higher than that of the MFC using C. minor ($1.43mW/m^2$). It was confirmed that energy recovery is possible using plant-MFCs without fuel. However, further research is needed to improve the performance of plant-MFCs. Nevertheless, plant-MFCs have proved their potential as a novel energy source to overcome the limitations of the conventional renewable energy sources such as wind power and solar cells, and could be employed to a power source for the sensor in charge of the fourth industrial revolution.

• Journal of Appropriate Technology
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• v.5 no.2
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• pp.62-69
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• 2019

Supplying stable electric power is one of the important objectives of the Official Development Assistance (ODA) because it is strongly related with improving living standards and income levels in the region. However, rural areas in many developing countries are not properly connected to national power grids, and even areas connected to national power grids are frequently blacked out due to limitations in power capacity. These lack of electric power is a major obstacle to improving income levels and improving living standards in those areas. The Korea-Tanzania Innovative and Energy Center (iTEC), which was established by Seoul National University in cooperation with the Nelson-Mandela Africa Institute of Science and Technology and Technology (NM-AIST) try to build a small solar power plant using a smart-off grid in rural area of Tanzania, where there is no electricity. 10 kW and 7 kW solar power plants are built in Mkalama Village in Kilimanajaro Region and Ngurdoto Village in Arusha Region to provide power to about 50 households each. In addition, smart monitoring systems were installed to collect data about status of power system and power consumption of each house. iTEC seeks for sustainable improvement the income level and quality of life of rural residents in developing countries through the construction of small solar power plants using smart-off grid, and the implementation of various connected projects.