• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.723-734
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• 2021

Wind energy is one of the rapidly developing renewable energies which is being developed and invested in response to climate change. As renewable energy policies and power plant installations are promoted, the supply of wind power in Korea is gradually expanding and attempts to accurately predict demand are expanding. In this paper, the ARIMA and ARIMAX models which are Time series techniques and the SVR, Random Forest and XGBoost models which are machine learning models were compared and analyzed to predict wind power generation in the Jeonnam and Gyeongbuk regions. Mean absolute error (MAE) and mean absolute percentage error (MAPE) were used as indicators to compare the predicted results of the model. After subtracting the hourly raw data from January 1, 2018 to October 24, 2020, the model was trained to predict wind power generation for 168 hours from October 25, 2020 to October 31, 2020. As a result of comparing the predictive power of the models, the Random Forest and XGBoost models showed the best performance in the order of Jeonnam and Gyeongbuk. In future research, we will try not only machine learning models but also forecasting wind power generation based on data mining techniques that have been actively researched recently.

• Journal of the Korean Solar Energy Society
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• v.27 no.3
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• pp.117-125
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• 2007

This study proposes a CFD(Computational Fluid Dynamics) analysis as a method of verification of the designed-data and a supplement of the insufficient experiences in geothermal system, which shows a rapid growth among the renewable energies. The followings are the results. FLUENT 6.2.12 is used as a CFD tool on this study, with the equations of continuity, motion, energy for unsteady flow through pipes and k-epsilon turbulent model. S-type model which has one borehole with diameter 12m by depth 206m and T-type model which has 3 boreholes with $12m{\times}20m{\times}206m$ are proposed, and also the boundary conditions are described. The temperature differences between temperatures by CFD analysis and by on-site measurement are less than 1.5%, this shows a high reliability of CFD analysis process which this study proposes. After 11 days simulation operated 12 hours interval On/Off mode, it is clearly predicted that the outlet temperatures of geothermal pipes are increased by $1.2^{\circ}C$, and $2.2^{\circ}C$ after 4 months. And the outlet temperatures of geothermal pipes increased with increase of the mass flow rates through the pipes. T-type model shows that the 4m distance between boreholes are reasonable because the temperatures at 2m and 6m from boreholes are nearly same.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.2
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• pp.146-156
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• 2010

The objective of this study was to improve the accuracy of calculation and estimation of solar radiation and duration of sunshine, which are the most important variables of photovoltaic power generation in deciding the location of photovoltaic facilities efficiently. With increasing interest in new and renewable energies, research on solar energy is also being conducted actively, but there have not been many studies on the location of photovoltaic facilities. Thus, this study calculated solar duration and solar radiation based on geographical factors, which have the most significant effect on solar energy in GIS environment, and corrected the results of analysis using diffuse radiation. Moreover, we performed ordinary kriging, a spatial statistical analysis method, for estimating values for parts deviating from the spatial resolution of input data, and used variogram, which can determine the spatial interrelation and continuity of data, in order to estimate accurate values. In the course, we compared the values of variogram factors and estimates from applicable variogram models, and selected the model with the lowest error rate. This method is considered helpful to accurate decision making on the location of photovoltaic facilities.

• 한국신재생에너지학회:학술대회논문집
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• 2010.11a
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• pp.113.2-113.2
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• 2010

We report that the novel covalent organic frameworks (COFs) are capable of reversibly providing an extremely high uptake capacity of carbon dioxide and hydrogen at room temperature. These COFs are designed based on the multiscale simulations approach via the combination of ab initio calculations and force-field calculations. For this goal, we explore the adsorption sites of carbon dioxide and hydrogen on COFs, their porosity, as well as carbon dioxide adsorption isotherms. We identify the binding sites and energies of $CO_2$ on COFs using ab initio calculations and obtain the carbon dioxide adsorption isotherms using grand canonical ensemble Monte Carlo calculations. Moreover, the calculated adsorption isotherms are compared with the experimental values in order to build the reference model in describing the interactions between the $CO_2/H_2$ and the COFs and in predicting the $CO_2$ and $H_2$ adsorption isotherms of COFs. Finally, we design three new COFs, 2D COF-05, 3D COF-05 (ctn), and 3D COF-05 (bor), for the high capacity $CO_2/H_2$ and $H_2$ storage.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.3
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• pp.469-475
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• 2016

As we are facing the shortage of oil energy, studies on renewable energy, wind energy research has been naturally getting attention. Among wind energies, ocean wind energy is relatively abundant compared to land wind energy and therefore, is getting much attention in terms of its efficiency. However, the problem is the cost. Generally, the cost ratio of the supporting structure is over 25% of the total installation cost of a offshore wind turbine system. Thus, it is very important to reduce the total installation cost of the offshore wind turbine and develop accurate analysis methodology for various offshore wind turbine foundations. In this study, nonlinear structure-soil interaction analyses have been proposed and conducted for the typical suction bucket model of an offshore wind turbine foundation, and the results were compared with experimental test data for numerical validations.

• Journal of Hydrogen and New Energy
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• v.25 no.6
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• pp.636-642
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• 2014

As environment problem became a worldwide issue, countries are tightening regulations regarding greenhouse gas reduction and improvement of air pollution problems. With these circumstances, one of the renewable energies produced from biomass is getting attention. Bio-ethanol, which is applicable to SI engine, showed a positive effect on the PFI (Port Fuel Injection) type. However, Ethanol has a problem in homogeneous mixture formation because it has high latent heat of vaporization characteristics and in the GDI (Gasoline Direct Injection) type, mixture formation is required quickly after fuel injection. Particularly, South Korea is one of the countries with great temperature variation among seasons. With this reason, South Korea supply fuel additive for smooth engine operation during winter. Therefore, experimental study and investigation about application possibility of blending fuel is necessary. This paper demonstrates the spray characteristics by using the CVC direct injection and setting the bio-ethanol blending fuel temperature close to the temperature during each seasons: -7, 25, $35^{\circ}C$. The diameter and the width of the CVC are 86mm and 39mm. High-pressure fuel supply system was used for target injection pressure. High-speed camera was used for spray visualization. The experiment was conducted by setting the injection pressure and ambient pressure according to each temperature of bio-ethanol blending fuel as a parameter. The result of spray visualization experiment demonstrates that as the temperature of the fuel is lower, the atomization quality is lower, and this increase spray penetration and make mixture formation difficult. Injection strategy according to fuel temperature and bio-ethanol blending rate is needed for improving characteristics.

• Journal of Environmental Science International
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• v.19 no.8
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• pp.983-999
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• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.8
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• pp.1504-1511
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• 2009

By development of renewable energies and high-efficient facilities and deregulated electricity market, the operation cost of distributed generation(DG) becomes more competitive. The amount of distributed resource is considerably increasing in the distribution network consequently. Also, international environmental regulations of the leaking carbon become effective to keep pace with the global efforts for low-carbon paradigm. It contributes to spread out the business of DG. Therefore, the operator of DG is able to supply electric power to customers who are connected directly to DG as well as loads that are connected to entire network. In this situation, community energy system(CES) having DGs is recently a new participant in the energy market. DG's purchase price from the market is different from the DG's sales price to the market due to the transmission service charges and etc. Therefore, CES who owns DGs has to control the produced electric power per hourly period in order to maximize the profit. If there is no regulation for carbon emission(CE), the generators which get higher production than generation cost will hold a prominent position in a competitive price. However, considering the international environment regulation, CE newly will be an important element to decide the marginal cost of generators as well as the classified fuel unit cost and unit's efficiency. This paper will introduce the optimal operation of CES's DG connected to the distribution network considering CE. The purpose of optimization is to maximize the profit of CES and Particle Swarm Optimization (PSO) will be used to solve this problem. The optimal operation of DG represented in this paper is to be resource to CES and system operator for determining the decision making criteria.

• Journal of the Korean Applied Science and Technology
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• v.29 no.3
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• pp.516-530
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• 2012

Gasohol which is the mixture of gasoline and ethanol, is used to gasoline vehicles worldwide currently. This study is performed by the methods of the review of references, and includes the background introduced, manufacturing processes, amounts produced, original properties, specifications, ways of applied currently, regulations and policies as a fuel for gasoline vehicles on individual countries through the scope of worldwide, especially focused on bioethanol and gasoline. By the reason above, it is prepared by focused on multiple angles for the person who want to getting information and searching desired ways in the future regarding to bioethanol and gasohol. It is concluded that gasohol is one of the useful renewable energies, and must to take a step forward by the approaching of multiple points, and finally showed some directions by the way of comparing of the situations and references nowaday.

• Journal of the Korean Solar Energy Society
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• v.32 no.3
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• pp.138-145
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• 2012

Because of the climate changes and the development of building technologies, the cooling loads have been increased. Among the various renewable energies, geothermal energy is known as very useful and stable energy for heating and cooling of building. This study proposes a road snow-melting system of which heat is supplied from GSHP(Ground source heat pump) in viewpoint of the initial investment and annual running performance, which is also operating as a main facility of heating and cooling for common spaces. The results of this study is as followings. From the site measurement, it is found out that the road surface temperature above the geothermal heating pipe rose up to $5^{\circ}C$, which is the design temperature of road snow-melting, after 2 hours' operation and average COP(Coefficient of performance) was estimated as 3.5. The reliability of CFD has confirmed, because the temperature difference between results of CFD analysis and site measurement is only ${\pm}0.4^{\circ}C$ and the trend of temperature variation is quite similar. CFD analysis on the effect of pavement materials clearly show that more than 2 hours is needed for snow-melting, if the road is paved by ascon or concrete. But the road paved by brick is not reached to $5^{\circ}C$ at all. To evaluate the feasibility of snow-melting system operated by a geothermal circulation which has not GSHP, the surface temperature of concrete-paved road rise up to $0^{\circ}C$ after 2 hour and 40 minutes, and it does never increase to $5^{\circ}C$. And the roads paved by ascon and brick is maintained as below $0^{\circ}C$ after 12 hours geothermal circulation.