• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.263-265
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• 2008

자원 재활용 및 에너지 생산관점에서 폐유지로부터 환경친화적인 연료인 바이오디젤에 대한 연구가 활발히 진행되고 있다. 특히 폐유지내 함유된 유리지방산 및 수분에 의해 효율적인 에스테르화 반응이 어렵기 때문에 이를 전처리 단계에서 제거되어야 한다. 본 연구에서는 폐유지내 유리지방산을 효과적으로 제거하기 위하여 회분식 반응기에서 제올라이트 촉매의 종류에 의한 세공구조와 산성도 변화에 따른 유리지방산 전환반응에 미치는 영향을 조사해 보았다. 제올라이트 촉매의 유리지방산 전환율은 세공구조와 산성도에 따라 큰 차이를 나타내었다. 유리지방산 전환율은 FAU < MOR < MFI < BEA의 순으로 높았다. 제올라이트의 세공구조는 1차원적인 구조를 가질 경우 탄소침적이 일어나지만 3차원적인 세공구조를 가지는 경우 탄소침적에 의한 촉매의 활성저하가 감소된다. 또한 제올라이트의 산성도에 따른 특성으로는 유리지방산의 전환반응에는 중간정도의 산세기를 가진 촉매가 유리함을 확인하였다. 그러므로 폐유지로부터 유리지방산을 제거하기 위한 우수한 제올라이트 촉매로는 BEA 제올라이트 촉매임을 확인하였다.

• New & Renewable Energy
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• v.10 no.2
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• pp.29-39
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• 2014

This study examines the future variability of surface wind speed and solar radiation based on climate change scenario over the Korean Peninsula. Climate change scenarios used in this study are RCP 4.5 and 8.5 with a 12.5 km horizontal resolution. Climate change scenario RCP 4.5 and 8.5 reproduce the general features of wind speed over the Korean Peninsula, such as strong wind speed during spring and winter and weak wind speed during summer. When compared with the values of wind speed and solar radiation of the future, they are expected to decrease current wind and solar resource map. Comparing the resource maps using RCP 4.5 and 8.5 scenarios, wind speed and solar radiation decrease with increasing greenhouse gas concentration. Meteorological resource maps of future wind and solar radiation should be improved with high resolution for the industrial application.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.307-308
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• 2006

The national goal of wind energy dissemination has to be determined rationally based on technically available wind resource potential. For a reliable and scientific estimation or wind resource potential, a wind map is requisite. This paper presents the national wind map of Korea established by numerical wind simulation. Prediction accuracy of the low-resolution wind map is Improved by nudging QuikSCAT data and is validated by comparing with marine buoy beacon and met-mast measurements. Therefore, quantification of national wind resource potential is now possible and is anticipating to be utilized as a core index for policy and strategy building of wind energy dissemination and technology development.

• 한국신재생에너지학회:학술대회논문집
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• 2008.10a
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• pp.332-333
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• 2008

This paper presents an estimation method of national wind resource potential using a national and GIS(Geographical Information System). The wind resource potential is classified into theoretical, geographical and technical potentials and each category narrows down the previous definition by excluding impossible area to be developed as a wind farm using GIS datasets for onshore and offshore. As a basic unit of wind energy potential at a certain area, API(Average Power Intercepted) is calculated from WPD(Wind Power Density) given by a national wind map which is established by numerical wind simulation, so that a logical and relatively accurate potential estimation is possible comparing with other methods based on a field measurement interpolation which is inevitable to avoid critical assumptions.

• Journal of Convergence Society for SMB
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• v.1 no.1
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• pp.39-44
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• 2011

Recently, due to people's incontinent use all over the world, fossil fuels such as coal, oil, and natural gas were nearly to be exhausted and also causes serious environment pollutions. Therefore, there is a strong need to develop solar, wind, hydro, biomass, geothermal to replace fossil fuels to prevent suffering from above problems. Wish advances in sensor technology, such data is collected as a kind of stream data which arrives in an online manner so that it is characterized as high- speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. Therefore, the traditional data processing techniques are not fit to deal with stream data. In this paper, we propose a kalman filter-based algorithm to process renewable stream data.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.39-44
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• 2023

Renewable energy such as solar and wind power is a resource that is sensitive to weather conditions and environmental changes. Since the amount of power generated by a facility can vary depending on the installation location and structure, it is important to accurately predict the amount of power generation. Using meteorological data, a data preprocessing process based on principal component analysis was conducted to monitor the relationship between features that affect energy production prediction. In addition, in this study, the prediction was tested by reconstructing the dataset according to the sensitivity and applying it to the machine learning model. Using the proposed model, the performance of energy production prediction using random forest regression was confirmed by predicting energy production according to the meteorological environment for new and renewable energy, and comparing it with the actual production value at that time.

• New & Renewable Energy
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• v.20 no.1
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• pp.88-94
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• 2024

This study explored the potential and implementation of renewable energy sources in Sri Lanka, focusing on the theoretical potential of solar and wind energy to develop self-reliant energy models. Using advanced climate data from the European Centre for Medium-Range Weather Forecasts and Global Solar/Wind Atlas provided by the World Bank, we assessed the renewable energy potential across Sri Lanka. This study proposes off-grid and minigrid systems as viable solutions for addressing energy poverty in rural regions. Rural villages were classified based on solar and wind resources, via which we proposed four distinct energy self-reliance models: Renewable-Dominant, Solar-Dominant, Wind-Dominant, and Diesel-Dominant. This study evaluates the economic viability of these models considering Sri Lanka's current energy market and technological environment. The outcomes highlight the necessity for employing diversified energy strategies to enhance the efficiency of the national power supply system and maximize the utilization of renewable resources, contributing to Sri Lanka's sustainable development and energy security.

• 한국신재생에너지학회:학술대회논문집
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• 2007.06a
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• pp.404-408
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• 2007

현재 국내에서 운용중인 풍력발전시스템은 국내 풍력자원에 대한 정확한 정보의 부재와 국내 풍황에 맞지 않는 국외 모델을 그대로 운용하는 등의 몇 가지 문제를 드러내었다. 본 연구의 목적은 국내 연안의 해상에서 한국형 해상풍력터빈을 설치하기 위한 잠재적 최적위치와 풍황자료 산출 최적화 알고리즘을 구현하는 것이다. 최적화 알고리즘은 얕은 수심 분포와 연안에서의 거리를 제약조건으로 하고 최대 에너지밀도를 가진 지점을 구하는 것으로 정식화하였다. 풍황자료 산출을 위해서 국내 연안의 해상 풍황자료를 포함하는 기상풍황자료를 통계적 모델로 분석하여 바람지도를 작성하였다. 이 바람지도를 이용하여 지질 통계학 분야의 관측기법인 크리깅 모델을 구성하고, 전역최적화기법인 유전자알고리즘을 이용하여 제약조건을 만족하는 최대에너지밀도값과 그 위치를 도출하였다. 수치최적화 결과 우리나라 풍력 자원의 대략적인 잠재량과 현황파악이 가능하였고, 해상풍력발전단지가 조성 가능한 개략적인 위치를 예측할 수 있었다.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.300-302
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• 2008

For the evaluation of wind resources, numerical simulation was carried out as a tool for establishing wind map around the korean peninsula. Initial and boundary condition are given by 3 hourly RDAPS(Regional Data Assimilation and Prediction System) data of KMA(Korea Meteorology Administration) and high resolution terrain elevation land cover(30 seconds) data from USGS(United States Geological Survey). Furthermore, Data assimilation was adopted to improve initial meteorological data with buoy and QuikSCAT seawinds data. The simulation was performed from 2003 to 2006 year. To understand wind data correctly in complex terrain as the korean peninsula, at this research, Wind map was classified 4 categories by distance from coastline and elevation.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.331-332
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• 2008

Wind energy issued as most spotlight general energy by excellence of actuality as well as economical efficiency, solving environmental problem which caused by creating the energy and possibility of eternal production. Accordingly, government is at the stage of corresponding level by requesting development of new technology to the developed countries as a part of national key industries. The grievous situation from such a rapid movement is meteorological comprehension and assessment as well as the problem of estimation exactness about the wind. In this study, we use the regional meteorological station data, automatic weather station data and QuikSCAT SeaWinds data.