• New & Renewable Energy
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• v.2 no.3
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• pp.23-30
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• 2006

Need developments of substitute energy to solve problem of global warming by excess use of fossil energy, excess discharge of carbon dioxide. wind power generation system is all-important energy in next generation as clean energy. Environmental pollution of wind power generation system is not exhausted entirely. And, electric-power generation system cost is cheap than other energy. Wind Generation system that is supplied much present is most horizontality style blade structure. But, Horizontal style structure is serious noise and there is problem in stability of blade. We designed special blade solve to this problem. And, manufactured vertical axis wind power generation system because using blade. Also, developed assistance power generator to increase driving efficiency ago wind power generation. We expect this devices that is such cover shortcoming of wind power generation system.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.

• 한국신재생에너지학회:학술대회논문집
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• 2007.11a
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• pp.244-244
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• 2007

• Journal of Energy Engineering
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• v.26 no.3
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• pp.51-63
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• 2017

Paris Agreement on Climate Change(2015) requires to reduce the greenhouse gas emission. One of the responses to the requirement is to change the proportion of power generation, which is summarized to the decrease in thermal power and the increase in new and renewable power. This article conducts a comparative analysis on the economic effects between thermal- and new and renewable- power generations, using the Input-Output Table from The Bank of Korea. The results of this analysis show that the new and renewable power generation has got the larger effects in production-inducing, value-added-inducing, employment-inducing, and supply-shortage scopes, while the smaller effect in price-pervasive scope than the thermal power generation. According to these results, the complex consideration should be taken into when the changes in power generation mix are tried. Especially, the political efforts to reduce the supply-shortage effect of new and renewable power and the price-pervasive effect of thermal power will be important.

• New & Renewable Energy
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• v.18 no.2
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• pp.18-25
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• 2022

In this study, we propose a wind power generation prediction system that applies machine learning and data mining to predict wind power generation. This system increases the utilization rate of new and renewable energy sources. For time-series data, the data set was established by measuring wind speed, wind generation, and environmental factors influencing the wind speed. The data set was pre-processed so that it could be applied appropriately to the model. The prediction system applied the CNN (Convolutional Neural Network) to the data mining process and then used the LSTM (Long Short-Term Memory) to learn and make predictions. The preciseness of the proposed system is verified by comparing the prediction data with the actual data, according to the presence or absence of data mining in the model of the prediction system.

• Journal of the Korean Solar Energy Society
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• v.39 no.3
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• pp.59-66
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• 2019

New and renewable energy forecasts are key technology to reduce the annual operating cost of new and renewable facilities, and accuracy of forecasts is paramount. In this study, we intend to build a model for the prediction of short-term solar power generation for 1 hour to 3 hours. To this end, this study applied two time series technique, ARIMA model without considering seasonality and SARIMA model with considering seasonality, comparing which technique has better predictive accuracy. Comparing predicted errors by MAE measures of solar power generation for 1 hour to 3 hours at four locations, the solar power forecast model using ARIMA was better in terms of predictive accuracy than the solar power forecast model using SARIMA. On the other hand, a comparison of predicted error by RMSE measures resulted in a solar power forecast model using SARIMA being better in terms of predictive accuracy than a solar power forecast model using ARIMA.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.806-812
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• 2009

Availability of reliable and affordable energy supply is a prerequisite for economic growth. Renewables are the third largest contributor to global electricity production after coal and natural gas and account for a share of 18%. Power generating capacity from renewables has increased to around 900GW by the year 2007. Today biodiesel fuels have been in commercial use in many countries and recently the world-wide biodiesel market has experienced considerable growth, which is partly due to various tax concession programs and other financial incentives. In Korea, biodiesel has already been used for transportation fuel, but not used for power generation fuel yet. Korean government has a strategy for renewable energy propagation, especially the goal of power generation amount by renewable energy is 3% of total power production by 2012. This paper focuses on the feasibility study for adaptability and strategy of using biodiesel as power generation fuel. The study also has the plan to replace the fuel of thermal power plant, gas turbine and distributed power system. As the increase of biodiesel fuel, I look forward to environment-friendly power generation and the strategy of Renewable Portfolio Standards(RPS).

• New & Renewable Energy
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• v.18 no.2
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• pp.50-59
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• 2022

The Korean government announced the "1st Basic Plan for the Transition to Hydrogen Economy" in 2021 and declared the establishment of a hydrogen industry ecosystem by 2040. To build a low-carbon power system, resources that can efficiently accommodate renewable energy are required, and green hydrogen is considered a potential solution. This study analyzed the economic feasibility of green hydrogen-based sector coupling to reduce curtailment of renewable generation in the Jeju power system by 2025 under the scenario of with or without HVDC#3. The result showed that HVDC#3 significantly reduced the frequency of curtailment from 16.1% to 3.0%. In addition, green hydrogen-based sector coupling was an economically feasible option as result showed an IRR of 4.86% when HVDC#3 was connected and 11.45% when it was not under the condition of achieving 50% curtailment reduction. This study shows that the higher the level of renewable energy deployment, the more delayed the HVDC connection between Jeju and the main land, and the lower the SMP, the more economically feasible the green hydrogen-based sector coupling is. Furthermore, this study suggests that the policy goal of completely reducing curtailment is not economically efficient.

• New & Renewable Energy
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• v.17 no.1
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• pp.61-75
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• 2021

Power generation using solar PV and wind power are more feasible to compete with fossil fuel power generation. However, residential acceptance is still a big challenge in the deployment of renewable energy. The Korean government has implemented various policies to support the development of renewable energy in which communities invest. However, there are very few cases of the commercial operation of community-invested renewable energy power plants. Renewable energy has attracted attention in the reduction of greenhouse gasses (GHG) effects and economic feasibility. However, it is also necessary to focus on socio-economic effects to overcome the economic recession while reducing greenhouse emissions. Community-invested renewable energy development projects can positively revitalize the local economy in many aspects, such as resident income, job creation, and the growth of local businesses. This study analyzes the local economic impact of renewable energy development projects on residents' income and job creation. It increased local companies' sales through community-invested development projects in Korea.

• New & Renewable Energy
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• v.2 no.3
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• pp.15-22
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• 2006

As the distributed generation becomes more reliable and economically feasible, it is expected that a higher application of the distributed generation units would be interconnected to the existing grids. This new market penetration using the distributed generation technology is linked to a large number of factors like economics and performance, safety and reliability, market regulations, environmental issues, or grid connection standards. KEPCO, a government company in Korea, has performed the project to identify and evaluate the performance of Micro Gas Turbine(MGT) technologies focused on 30, 60kW-class grid-connected optimization and combined Heat & Power performance. This paper describes the results for the mechanical, electrical, and environmental tests of MGT on actual grid-connection under Korean regulations. As one of the achievements, the simulation model of Exhaust-gas Absorption Chiller was developed, so that it will be able to analyze or propose new distributed generation system using MGT. In addition, KEPCO carried out the field testing of the MGT Cogeneration system at the R&D Center Building, KEPCO. The field test was conducted in order to respond to a wide variety of needs for heat recovery and utilization. The suggested method and experience for the evaluation of the distributed generation will be used for the introduction of other distributed generation technologies into the grid in the future.