• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.1
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• pp.62-69
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• 2023

Recently, renewable energy has been increasing in Korea to reduce greenhouse gas, and solar power generation, which accounts for the largest proportion of renewable energy, is noteworthy. The government policy will further increase solar power generation. In order to implement the policy, it is important to understand the current status of domestic solar power generation facilities. Therefore, the current status of solar power generation facilities in Jinju city close to the south coast and Jeonju city close to the west coast was investigated and compared. By 2020, 618 solar power plants had been installed in Jeonju city and 269 in Jinju city. However, there is not much difference in the amount of solar power generation for business at 9 GWh. The reason is that Jinju city has a lower population density than Jeonju city, so there are enough places to install a large-scale solar power facilities with a large power generation capacity. Monthly solar power generation was the highest in April in both Jeonju city and Jinju city and the lowest in January. In particular, in December, Jinju city showed more solar power generation than Jeonju city because of the large amount of insolation, long sunshine hours, and few clouds.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.412-415
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• 2005

Solar thermal power generation is one of promising and well-proven ways to convert solar energy to electricity. Though it requires high initial cost for system construction and continuous efforts for maintainment. it is more positive in terms of efficiency than other solar power generation technologies. Moreover, solar thermal power generation allows additional benefits of cheap thermal storage and easy hybridization with other fossil fuel-driven power generation. Owing to these benefits, large scale solar thermal power generation technology is expected to be competitive to other commercial technologies in the near future. In this paper an overview on the solar thermal hybrid power generation technology and the state of the art in Korea were briefly introduced.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.2
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• pp.249-258
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• 2023

Solar power has the largest proportion of power generation and facility capacity among renewable energy in South Korea. Floating solar power plant is a new way to resolve weakness of land solar power plant. This study analyzes the power generation of the 18.7 MW floating solar power project located in Saemangeum, Gunsan-si. Since the solar power generation has a characteristic that is greatly affected by the climate, various methods have been applied to predict solar power generation. In general, variables necessary for predicting power generation are solar insolation on inclined surfaces, solar generation efficiency, and panel installation area. This study analyzed solar power generation using the monthly solar insolation data from the KMA (Korea Meteorological Administration) over the past 10 years. Monte Carlo simulation (MCS) was applied to predict the solar power generation with the variables including solar panel efficiency and insolation. In the case of Saemangeum solar power project, the most solar power generation was in May, the least was in December, the average solar power generation simulated on MCS is 2.1 GWh per month, the minimum monthly power generation is 0.3 GWh, and the maximum is 5.0 GWh.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.359-361
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• 2010

This research is thing about location choice of solar power generation equipment to increase efficiency of solar power generation equipment. In the case of current solar power generation equipment, location of large scale solar power generation equipment facilities choice or, have localized in small scale equipment by individual. This research uses various climatic elements of small scale area for efficient location choice of solar power generation facilities and quantity of solar radiation did back-tracking.

• Journal of Advanced Navigation Technology
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• v.22 no.3
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• pp.233-239
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• 2018

Since solar power generation is intermittent depending on weather conditions, it is necessary to predict the accurate generation amount of solar power to improve the efficiency and economical efficiency of solar power generation. This study proposes a short - term deep learning prediction model of solar power generation using meteorological data from Mokpo meteorological agency and generation data of Yeongam solar power plant. The meteorological agency forecasts weather factors such as temperature, precipitation, wind direction, wind speed, humidity, and cloudiness for three days. However, sunshine and solar radiation, the most important meteorological factors for forecasting solar power generation, are not predicted. The proposed model predicts solar radiation and solar radiation using forecast meteorological factors. The power generation was also forecasted by adding the forecasted solar and solar factors to the meteorological factors. The forecasted power generation of the proposed model is that the average RMSE and MAE of DNN are 0.177 and 0.095, and RNN is 0.116 and 0.067. Also, LSTM is the best result of 0.100 and 0.054. It is expected that this study will lead to better prediction results by combining various input.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.9
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• pp.1721-1726
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• 2011

Recently, interest in renewable energy is increased due to exhaustion of fossil fuel and environmental pollution all over the world, therefore the solar power generation using solar energy is many researched. The solar power generation is required solar tracking control and high concentration solar thermal collector because generation performance is depended on concentrator efficiency. This paper proposes high efficiency solar power generation with two-axis tracking control using dish-type solar thermal collector that has excellent thermal collector performance and tracking algorithm that can be accurately tracked solar position. This paper proves validity through analysis with accuracy of tracking algorithm and generating efficiency.

• Journal of Korea Multimedia Society
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• v.25 no.11
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• pp.1572-1581
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• 2022

Energy conversion to renewable energy is being promoted to solve the recently serious environmental pollution problem. Solar energy is one of the promising natural renewable energy sources. Compared to other energy sources, it is receiving great attention because it has less ecological impact and is sustainable. It is important to predict power generation at a future time in order to maximize the output of solar energy and ensure the stability and variability of power. In this paper, solar power generation data and sensor data were used. Using the PCC(Pearson Correlation Coefficient) analysis method, factors with a large correlation with power generation were derived and applied to the GAM(Generalized Additive Model). And the prediction accuracy of the power generation prediction model was judged. It aims to derive efficient solar power generation in the future and improve power generation performance.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.658-661
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• 2007

KIER have been developing high-temperature solar technology, especially the solar thermal power generation system, since the early of 1990s. In 1994, the first research on high temperature solar technology started with PTC technology. At the moment the most advanced 10kW dish system is under demonstration for 10kW solar thermal power generation. Test results showed about 19.2% solar to electricity average efficiency. Another research activities of KIER is hybrid power generation. For hybridization, solar and LFG(landfill gas) are used. Another hybrid solar system is with solar chemical reaction. In this system, power unit is gas turbine, and the heat content of fuel(like natual gas) is upgraded by solar energy through chemical reaction. The latest project on solar thermal power generation is for 1 MW power tower system. This is the Korea-China Joint project.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.10
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• pp.353-360
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• 2016

Recently, solar photovoltaic(PV) power generation which generates electrical power from solar panels composed of multiple solar cells, showed the most prominent growth in the renewable energy sector worldwide. However, in spite of increased demand and need for a photovoltaic power generation, it is difficult to early detect defects of solar panels and equipments due to wide and irregular distribution of power generation. In this paper, we choose an optimal machine learning algorithm for estimating the generation amount of solar power by considering several panel information and climate information and develop a defect detection system by using the chosen algorithm generation. Also we apply the algorithm to a domestic solar photovoltaic power plant as a case study.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.688-692
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• 2007

Solar thermal power generation allows additional benefits of cheap thermal storage and easy hybridization with other fossil fuel-driven power generation. KIER has been performing the project for solar thermal chemical reaction hybrid power generation. The project is to build and operate the first solar thermal chemical reaction hybrid power generation system in Korea. For concentrating solar thermal energy $m^2$ dish type concentrator was adapted and a heliostat is installed for reflecting horizontal insolation to the dish concentrator. At the moment building the dish concentrator including mirror and heliostat with sun tracking system was completed and it's performance are being closely evaluated. This paper will introduce some detailed designs and construction procedures which we have experienced so far.