• Journal of Korea Technology Innovation Society
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• v.12 no.4
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• pp.788-818
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• 2009

Renewable energy refers to solar energy, biomass energy, hydrogen energy, wind power, fuel cell, coal liquefaction and vaporization, marine energy, waste energy, and liquidity fuel made out of byproduct of geothermal heat, hydrogen and coal; it excludes energy based on coal, oil, nuclear energy and natural gas. Developed countries have recognized the importance of these energies and thus have set the mid to long term plans to develop and commercialize the technology and supported them with drastic political and financial measures. Considering the growing recognition to the field, it is necessary to analysis up-to-now achievement of the government's related projects, in the standards of type of renewable energy, management of sectional goals, and its commercialization. Korean government is chiefly following suit the USA and British policies of developing and distributing renewable energy. However, unlike Japan which is in the lead role in solar rays industry, it still lacks in state-directed support, participation of enterprises and social recognition. The research regarding renewable energy has mainly examinedthe state of supply of each technology and suitability of specific region for applying the technology. The evaluation shows that the research has been focused on supply and demand of renewable as well as general energy and solution for the enhancement of supply capacity in certain area. However, in-depth study for commercialization and the increase of capacity in industry followed by development of the technology is still inadequate. 'Cost-benefit model for each energy source' is used in analysis of technology development of renewable energy and quantitative and macro economical effects of its commercialization in order to foresee following expand in related industries and increase in added value. First, Investment on the renewable energy technology development is in direct proportion both to the product and growth, but product shows slightly higher index under the same amount of R&D investment than growth. It indicates that advance in technology greatly influences the final product, the energy growth. Moreover, while R&D investment on renewable energy product as well as the government funds included in the investment have proportionate influence on the renewable energy growth, private investment in the total amount invested has reciprocal influence. This statistic shows that research and development is mainly driven by government funds rather than private investment. Finally, while R&D investment on renewable energy growth affects proportionately, government funds and private investment shows no direct relations, which indicates that the effects of research and development on renewable energy do not affect government funds or private investment. All of the results signify that although it is important to have government policy in technology development and commercialization, private investment and active participation of enterprises are the key to the success in the industry.

• Journal of the Korean Solar Energy Society
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• v.34 no.1
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• pp.8-18
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• 2014

Building simulation is used in a variety of sectors. In its early years, building simulation was mainly used in the design phase of a building for basic functions. Recently, however, it has become increasingly important during the operating phase, for commissioning and facility management. Most building simulation tools are used to estimate the thermal environment and energy consumption performance, and hence, they require the inputting of hourly weather data. A building simulation used for prediction should take into account the use of standard weather data. Weather data, which is used as input for a building simulation, plays a crucial role in the prediction performance, and hence, the selection of appropriate weather data is considered highly important. The present study proposed a technique for generating real-time weather data files, as opposed to the standard weather data files, which are required for running the building simulation. The forecasted weather elements provided by the Korea Meteorological Administration (KMA), the elements produced by the calculations, those utilizing the built-in functions of Energy Plus, and those that use standard values are combined for hourly input. The real-time weather data files generated using the technique proposed in the present study have been validated to compare with measured data and simulated data via EnergyPlus. The results of the present study are expected to increase the prediction accuracy of building control simulation results in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.626-628
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• 2018

In this paper, we compare the performances of SVM (Support Vector Machine) and ANN (Artificial Neural Network) machine learning models for predicting solar energy by using meteorological data. Two machine learning models were built by using fifteen kinds of weather data such as long and short wave radiation average, precipitation and temperature. Then the RBF (Radial Basis Function) parameters in the SVM model and the number of hidden layers/nodes and the regularization parameter in the ANN model were found by experimental studies. MAPE (Mean Absolute Percentage Error) and MAE (Mean Absolute Error) were considered as metrics for evaluating the performances of the SVM and ANN models. Sjoem Simulation results showed that the SVM model achieved the performances of MAPE=21.11 and MAE=2281417.65, and the ANN model did the performances of MAPE=19.54 and MAE=2155345.10776.

• Journal of the Korean Solar Energy Society
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• v.30 no.6
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• pp.66-72
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• 2010

In this study, we analyzed the characteristics of wind speed and wind direction at different locations in Jeju area using past 10 years observed data and used them in our wind power forecasting model. Generally the strongest hourly wind speeds were observed during daytime(13KST~15KST) whilst the strongest monthly wind speeds were measured during January and February. The analysis with regards to the available wind speeds for power generation gave percentages of 83%, 67%, 65% and 59% of wind speeds over 4m/s for the locations Gosan, Sungsan, Jeju site and Seogwipo site, respectively. Consequently the most favorable periods for power generation in Jeju area are in the winter season and generally during daytime. The predicted wind speed from the forecast model was in average lower(0.7m/s) than the observed wind speed and the correlation coefficient was decreasing with longer prediction times(0.84 for 1h, 0.77 for 12h, 0.72 for 24h and 0.67 for 48h). For the 12hour prediction horizon prediction errors were about 22~23%, increased gradually up to 25~29% for 48 hours predictions.

• Journal of the Korean Solar Energy Society
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• v.30 no.2
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• pp.72-80
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• 2010

The main thrust of this paper is to investigate a practical way of generating the monthly averaged daily horizontal solar radiation in Korea. For estimating the horizontal solar radiation, the clearness index($K_T$) and the clearness number($C_N$) which are required for the use of Liu and Jordan's model and ASHRAE Clear Sky model were derived based on the measured weather data. Third-order polynomials returning $K_T$ and��$C_N$ for a given location were derived as a function of cloud amount, month, date, latitude and longitude. The predicted monthly averaged daily horizontal solar radiation values were compared with those acquired from the established design weather data. The MBE(Mean Bias Error) and RMSE (Root Mean Squares for Error) between the predicted values and the measured data were near zero. It means that the suggested third-order polynomials for $K_T$ and $C_N$ have good applicability to Liu and Jordan's model and ASHRAE Clear Sky model.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.7
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• pp.464-471
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• 2013

In this study, the resource efficiency and future metal resource requirement in photovoltaic (PV) production system were evaluated by using material balance data and life cycle assesment (LCA) method. As a result, in the resource efficiency of ferrous and non-ferrous metal, lead and tin had higher resource efficiency than other materials in all PV systems (SC-Si, MC-Si, CI(G)S, CdTe). In the resource efficiency of rare metals, gallium and rhenium in silicon system and rhenium and rhodium in thin-film system ranked as the first and second high resource efficiency. In case of rare earth metal, gadolinium and samarium took higher resource efficiency. The results of the future metal resource requirement in PV systems showed that 2,545,670 ton of aluminium, 92,069 ton of zinc, 22,044 ton of copper, 1,695 ton of tin and 31 ton of nickel will be needed by 2030 in South Korea, except resource recycling supplement.

• Journal of the Korean Solar Energy Society
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• v.34 no.2
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• pp.82-90
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• 2014

The MERRA reanalysis data provided online by NASA was applied to predict the annual energy productions of two largest wind farms in Korea. The two wind farms, Gangwon wind farm and Yeongyang wind farm, are located on complex terrain. For the prediction, a commercial CFD program, WindSim, was used. The annual energy productions of the two wind farms were obtained for three separate years of MERRA data from June 2007 to May 2012, and the results were compared with the measured values listed in the CDM reports of the two wind farms. As the result, the prediction errors of six comparisons were within 9 percent when the availabilities of the wind farms were assumed to be 100 percent. Although further investigations are necessary, the MERRA reanalysis data seem useful tentatively to predict adjacent wind resources when measurement data are not available.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1183-1194
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• 2021

Traditionally, electric power systems have been known as the centralized structures, which is organized into placing customers at the end of the supply chain. However, recent decades have witnessed the emergence of distributed energy resources(:DERs) such as rooftop solar, farming PV system, small wind turbines, battery energy storage systems and smart home appliances. With the emergence of distributed energy resources, the role of distributed system operators(:DSOs) will expand. The increasing penetration of DERs could lead to a less predictable and reverse flow of power in the system, which can affect the traditional planning and operation of distribution and transmission networks. This raises the need for a change in the role of the DSOs that have conventionally planned, maintained and managed networks and supply outages. The objective of this research is to designed the future distribution operation system with multi-DERs and the proposed distribution system model is implemented by hardware-in-the-loop simulation(HILS). The test results show the normal operation domain and reduction of distribution line loss.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.782-785
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• 2011

Needs for MG(Microgrid) development are increasing all over the world as a solution to the problems including the depletion problem of energy resources, the growing demand for electric power and the climatic and environmental change. Especially Photovoltaic power is one of the most general renewable energy resources. However there is a problem of the uniformity of power quality because the power generated from solar light is very sensitive to climate fluctuation (variation of insolation and duration of sunshine, etc). As a solution to the above problem, ESS(Energy Storage System) is considered generally, but it has some limitations. To solve this problem this paper suggests a hybrid estimation method of photovoltaic power generation according to two climatic factors, i.e. insolation and sunshine. This result seems to help design the appropriate capacity of ESS and estimate the proper switching time between DC and AC power in the premises power system and thus maintain the uniformity of power quality.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.977-983
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• 2013

Based on the consideration of the hourly patterns of the electricity power consumption, this study predicted the effectiveness of hybrid power generation system, which is composed with wind power generator and photovoltaic generator. And this case study is performed at Konrido, which is a affiliated island of Kyeongsangnam-do. As the results, it is obvious that it is not efficient to cover the whole electricity power consumption only with any single power generating system, because the hourly patterns of electricity power consumption, wind power generation and photovoltaic generation are quite different. And because the wind is being through almost 24 hours, it is also found out that wind power generating system with storage battery is the most efficient combination for this case study.