• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.557-560
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• 2021

In the face of the COVID-19 pandemic, the Korean Government announced the Korean New Deal as a national development strategy to overcome the economic recession from the pandemic crisis and lead the global action aginst sturctural changes. The Green New Deal related with the energy aims to achieve net-zero emissions and accelerates the transition towards a low-carbon and green economy. To this end, the government plans to promete an increased use of renewable energy in the the society at large. This paper introduces a compact-binary power plant using unused thermal energy and a control system based on Neural Network in order to accelerate the transition towards a low-carbon and green economy. It is expected that he compact-binary power plant accelerate introduction of renewable energy along with solar and wind power.

• 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.

• Nuclear Engineering and Technology
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• v.47 no.1
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• pp.59-65
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• 2015

Background: After the Fukushima accident, the importance of hazard analysis for extreme external events was raised. Methods: To analyze typhoon-induced hazards, which are one of the significant disasters of East Asian countries, a statistical analysis using the extreme value theory, which is a method for estimating the annual exceedance frequency of a rare event, was conducted for an estimation of the occurrence intervals or hazard levels. For the four meteorological variables, maximum wind speed, instantaneous wind speed, hourly precipitation, and daily precipitation, the parameters of the predictive extreme value theory models were estimated. Results: The 100-year return levels for each variable were predicted using the developed models and compared with previously reported values. It was also found that there exist significant long-term climate changes of wind speed and precipitation. Conclusion: A fragility analysis should be conducted to ensure the safety levels of a nuclear power plant for high levels of wind speed and precipitation, which exceed the results of a previous analysis.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.404-405
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• 2011

In this paper, we present basic modeling of Juju power system using PSCAD/EMTDC. In detail, models of bipolar HVDC system, power transmission line, basic thermal power plant, load, and wind farm have been developed for Jeju power system. For evaluating basic dynamic behavior, we tested the system with a simple scenario and the test result showed acceptable response.

• Wind and Structures
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• v.30 no.4
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• pp.433-450
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• 2020

The strong turbulence characteristic of typhoon not only will significantly change flow field characteristics surrounding the large-scale wind turbine and aerodynamic force distribution on surface, but also may cause morphological evolution of coast dune and thereby form sand storms. A 5MW horizontal-axis wind turbine in a wind power plant of southeastern coastal areas in China was chosen to investigate the distribution law of additional loads caused by wind-sand coupling movement of coast dune at landing of strong typhoons. Firstly, a mesoscale Weather Research and Forecasting (WRF) mode was introduced in for high spatial resolution simulation of typhoon "Megi". Wind speed profile on the boundary layer of typhoon was gained through fitting based on nonlinear least squares and then it was integrated into the user-defined function (UDF) as an entry condition of small-scaled CFD numerical simulation. On this basis, a synchronous iterative modeling of wind field and sand particle combination was carried out by using a continuous phase and discrete phase. Influencing laws of typhoon and normal wind on moving characteristics of sand particles, equivalent pressure distribution mode of structural surface and characteristics of lift resistance coefficient were compared. Results demonstrated that: Compared with normal wind, mesoscale typhoon intensifies the 3D aerodynamic distribution mode on structural surface of wind turbine significantly. Different from wind loads, sand loads mainly impact on 30° ranges at two sides of the lower windward region on the tower. The ratio between sand loads and wind load reaches 3.937% and the maximum sand pressure coefficient is 0.09. The coupling impact effect of strong typhoon and large sand particles is more significant, in which the resistance coefficient of tower is increased by 9.80% to the maximum extent. The maximum resistance coefficient in typhoon field is 13.79% higher than that in the normal wind field.

• Advances in Energy Research
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• v.5 no.2
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• pp.179-205
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• 2017

This research presents an in-depth analysis of location planning of the solar-hydrogen power plants for electricity production in different cities situated in Kerman province of Iran. Ten cities were analyzed in order to select the most suitable location for the construction of a solar-hydrogen power plant utilizing photovoltaic panels. Data envelopment analysis (DEA) methodology was applied to prioritize cities for installing the solar-hydrogen power plant so that one candidate location was selected for each city. Different criteria including population, distance to main road, flood risk, wind speed, sunshine hours, air temperature, humidity, horizontal solar irradiation, dust, and land costare used for the analysis. From the analysis, it is found that among the candidates' cities, the site of Lalezar is ranked as the first priority for the solar-hydrogen system development. A measure of validity is obtained when results of the DEA method are compared with the results of the technique for ordering preference by similarity to ideal solution (TOPSIS). Applying TOPSIS model, it was found that city of Lalezar ranked first, and Rafsanjan gained last priority for installing the solar-hydrogen power plants. Cities of Baft, Sirjan, Kerman, Shahrbabak, Kahnouj, Shahdad, Bam, and Jiroft ranked second to ninth, respectively. The validity of the DEA model is compared with the results of TOPSIS and it is demonstrated that the two methods produced similar results. The solar-hydrogen power plant is considered for installation in the city of Lalezar. It is demonstrated that installation of the proposed solar-hydrogen system in Lalezar can lead to yearly yield of 129 ton-H2 which covers 4.3% of total annual energy demands of the city.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.409-414
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• 2009

I have not seen each of the existing technology, RFID/USN technology combined with the wireless communication channel for the state of nuclear safety in real-time remote monitoring and operation system technology CARE existing radioactive accident information collected by the nuclear power and nuclear power status, 10-20 second intervals to monitor the safety network (SIDS), and nuclear power plants located on the site within 40 ㎞ radius around the 13~15 of the wind speed from the automatic weather network weather information such as rainfall and temperature every 10 minutes to collect as automatic weather network (REMDAS), Evaluation of atmospheric radiation and radiation of the bomb radiation impact assessment system to calculate the goodness (FADAS) and thicken the radiation-related information consists of real-time web technology to collect, the last robot on behalf of the human will to manage the nuclear power plant accident of the technology to prevent the concrete from the following narrative about to have.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.16-18
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• 2001

Recently, a study on operation in parallel between Distributed Generation(DG) unit and power distribution system has been growing interest in power distribution system. But, introducing the DG unit causes the problem due to rising the voltage variation on power distribution system. So, This paper presents the effect of introducing DG unit on distribution system. For this simulation, KEPCO distribution system is used.

• STI Policy Review
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• v.4 no.1
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• pp.135-161
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• 2013

This paper examines Japan's Science and Technology (S&T) Basic Plans in accordance with its S&T Basic Law. The Basic Plans promote two major innovation (Green Innovation and Life Innovation) towards the creation of new markets and jobs, specifically under the Fourth S&T Basic Plan enacted on August 2011. Successful smart community demonstration projects at four urban localities were launched under plans to promote Green Innovation research and development of renewable energy technologies. However, the expectation that renewable energy such as solar or wind power can replace nuclear power is not backed by sufficient evidence. Furthermore, the electricity produced by these sources is expensive and unstable owing to its reliance on weather conditions. The Fukushima nuclear power plant accident on March 2011 has also seriously affected Japan's future energy plans. According to a government estimate, electricity charges would double if nuclear power generation were abandoned, imposing a heavy burden on the Japanese economy. Japan is in need of energy policies designed on the basis of more far-sighted initiatives.

• Journal of Radiation Protection and Research
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• v.41 no.4
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• pp.315-327
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• 2016

Background: This study evaluated the atmospheric dispersion of radioactive material according to local weather conditions and emission conditions. Materials and Methods: Local weather conditions were defined as 8 patterns that frequently occur around the Kori Nuclear Power Plant and emission conditions were defined as 6 patterns from a combination of emission rates and the total number of particles of the $^{137}Cs$, using the WRF/HYSPLIT modeling system. Results and Discussion: The highest mean concentration of $^{137}Cs$ occurred at 0900 LST under the ME4_1 (main wind direction: SSW, daily average wind speed: $2.8ms^{-1}$), with a wide region of its high concentration due to the continuous wind changes between 0000 and 0900 LST; under the ME3 (NE, $4.1ms^{-1}$), the highest mean concentration of $^{137}Cs$ occurred at 1500 and 2100 LST with a narrow dispersion along a strong northeasterly wind. In the case of ME4_4 (S, $2.7ms^{-1}$), the highest mean concentration of $^{137}Cs$ occurred at 0300 LST because $^{137}Cs$ stayed around the KNPP under low wind speed and low boundary layer height. As for the emission conditions, EM1_3 and EM2_3 that had the maximum total number of particles showed the widest dispersion of $^{137}Cs$, while its highest mean concentration was estimated under the EM1_1 considering the relatively narrow dispersion and high emission rate. Conclusion: This study showed that even though an area may be located within the same radius around the Kori Nuclear Power Plant, the distribution and levels of $^{137}Cs$ concentration vary according to the change in time and space of weather conditions (the altitude of the atmospheric boundary layer, the horizontal and vertical distribution of the local winds, and the precipitation levels), the topography of the regions where $^{137}Cs$ is dispersed, the emission rate of $^{137}Cs$, and the number of emitted particles.