• 한국태양에너지학회 논문집
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• 제35권2호
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• pp.1-10
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• 2015

Promising onshore wind farm sites in Gangwon province of Korea were investigated in this study. Gangwon province was divided into twenty five simulation regions and a commercial program based on Reynolds averaged Navier-Stokes equation was used to find out wind resource maps of the regions. The national wind atlas with a period 2007-2009 developed by Korea institute of energy research was used as climatologies. The wind resource maps were combined to construct a wind resource map of Gangwon province with a horizontal spatial resolution of 100m. In addition to the wind resource, national environmental zoning map, distance from substation, residence and automobile road, Beakdudaegan mountain range, terrain slope, airport and military reservation district were considered to find out promising wind farm sites. A commercial wind farm design program was used to find out developable wind farm capacities in promising wind farm site with and without excluding environmental protection regions. The total wind farm capacities with and without excluding the protection regions were estimated to be 46MW and 598MW, respectively, when a 2MW commercial wind turbine was employed.

• 산업기술연구
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• 제31권A호
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• pp.119-122
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• 2011

AWS (Automated Weather Station) wind data was used to predict the annual energy production of Gangwon wind farm having a total capacity of 98 MW in Korea. Two common wind energy prediction programs, WAsP and WindSim were used. Predictions were made for three consecutive years of 2007, 2008 and 2009 and the results were compared with the actual annual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from both prediction programs were close to the actual energy productions and the errors were within 10%.

• 한국태양에너지학회 논문집
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• 제31권2호
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• pp.72-81
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• 2011

The wind data obtained from an AWS(Automated Weather Station) was used to predict the AEP(annual energy production) of Gangwon wind farm having a total capacity of 98 MWin Korea. A wind energy prediction program based on the Reynolds averaged Navier-Stokes equation was used. Predictions were made for three consecutive years starting from 2007 and the results were compared with the actual AEPs presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm. The results from the prediction program were close to the actual AEPs and the errors were within 7.8%.

• 한국태양에너지학회 논문집
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• 제34권2호
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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.

• 한국태양에너지학회 논문집
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• 제32권6호
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• pp.1-10
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• 2012

The annual energy production of Gangwon wind farm was predicted for three consecutive years of 2007, 2008 and 2009 using commercial programs, WindPRO and WindSim which are known to be used the most for wind resource prediction in the world. The predictions from the linear code, WindPRO, were compared with both the actual energy prediction presented in the CDM (Clean Development Mechanism) monitoring report of the wind farm and also the predictions from the CFD code, WindSim. The results from WindPRO were close to the actual energy productions and the errors were within 11.8% unlike the expectation. The reason for the low prediction errors was found to be due to the fact that although the wind farm is located in highly complex terrain, the terrain steepness was smaller than a critical angle($21.8^{\circ}$) in front of the wind farm in the main wind direction. Therefore no flow separation was found to occur within the wind farm. The flow separation of the main wind was found to occur mostly behind the wind farm.

• 대한공간정보학회지
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• 제18권1호
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• pp.31-39
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• 2010

석유파동이후 신재생에너지의 중요성이 대두되고 현재에 들어 저탄소 녹색성장으로 다시금 그 중요성은 커지고 있다. 본 논문에서는 신재생 에너지 중 가장 현실적인 대안으로 받아들여지고 있는 풍력에너지에 대하여 강원지방 기상청의 2008년 데이터 이용하여 풍속지도를 제작 하였다. 강원도 월별 평균 풍속과 최대풍속지도를 제작하였으며, 기상자료에 여러 가지 보간법을 적용하고 방법에 따른 차이를 확인하였다. 강원도 지역의 특수한 지형적, 기후적 특성이 반영된 풍속지도는 풍력 단지 입지분석에 활용성이 높을 것으로 기대된다.

• 대한공간정보학회지
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• 제22권4호
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• pp.13-19
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• 2014

한반도와 같은 산악지형에서 풍력단지를 조성할 경우, 인근 지형에 의한 차폐영향이 없기 때문에 상대적으로 풍력자원이 우수한 능선을 따라서 풍력터빈을 설치하는 것이 유리하다. 본 연구에서는 산악지형에서의 풍력단지 입지평가를 위하여 SRTM v4.1 3 arc-second 해상도의 수치고도 데이터베이스와 지형형태 분류 프로그램인 LandSerf v2.3을 이용하여 풍력터빈 설치 가능한 능선을 추출하였으며, 강원도에 건설된 강원풍력단지, 태기산풍력단지 및 매봉산풍력단지의 사례분석을 통하여 대부분의 풍력터빈이 상대적으로 풍력자원이 우수한 능선을 따라 배치되었음을 확인함으로써 이 방법의 유효성을 검증하였다.

• 한국지리정보학회지
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• 제17권4호
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• pp.86-100
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• 2014

본 연구의 목적은 산지 내 풍력발전단지 입지 적합성 분석을 통해 입지선정 가이드라인과 산지 훼손 최소화를 위한 제도적 개선방안을 도출하는 것이다. 먼저 풍력발전단지 입지 적합성 분석을 위해 국내외 사례 및 현장조사, 연구문헌 고찰을 통해 산지 내 풍력발전단지 입지선정을 위한 요인을 도출하고, 요인별 세부항목 및 가중치를 결정하여 이를 바탕으로 각 항목별 세부평가기준을 수립함으로써 입지 적합성 모델을 개발하였다. 강원도를 사례지역으로 선정하여 풍력자원 밀도 데이터, 법적 산지보전지역, 입지 기준 요인 항목별 자료를 토대로 공간 DB를 구축하여 산지 내 풍력발전 입지가능지역을 도출하였다. 일정 개수 이상의 풍력발전기가 입지할 수 있는 풍력발전단지 잠재 입지가능면적의 추정을 위해서 본 연구에서는 근린분석방법인 Block Statistics와 Focal Statistics 방법을 이용하였다. 그 결과 Block Statistics 방법에 의한 풍력발전기 잠재적 입지가능 면적은 1,261ha이며, Focal Statistics 방법에 의한 풍력발전기 잠재적 입지가능 면적은 1,411ha으로 나타났다. 본 연구의 결과를 바탕으로 대규모 절성토에 의한 산림재해 발생 우려 및 산지경관 훼손을 방지하기 위한 저감대책이 마련되어야 할 것이다.

• 한국농공학회논문집
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• 제54권6호
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• pp.45-52
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• 2012

Along with global warming, ever intensifying weather events have increased damages to agricultural farms and facilities. The objective of this study was to investigate the spatial distribution and regional characteristics of agricultural damages by extreme weather events. Agricultural disaster statistics provided by the National Emergency Management Agency were summed over for a 13-year period from 1998 to 2010 and used for the spatial analysis. Two indices of damage area ration and property damage per unit area were introduced to quantify regional agricultural damages. As the results, farm inundation accounted for the largest area primarily damaged by typhoons with heavy rainfalls. Most property damages to farm lands originated from farm erosion in the alpine regions by localized guerrilla rains. The two major causes of damages to greenhouse and livestock facilities were typhoon with strong wind and winter blizzards. Gangwon was the province of the largest property loss mostly from farm land erosion losses, followed by Gyeongnam, Jeonnam, and Chungnam where losses to greenhouse and livestock facilities were relatively greater. Property loss per unit area was also the greatest for the Gangwon province (4.91 M\/ha), followed by Gyongnam and Chungnam of 2.20 and 1.50 M\/ha, respectively. Unit loss for greenhouse and livestock facilities was 13.3 M\/ha, approximately 13 times greater than that for farm land (1.06 M\/ha). The study findings indicated the importance of reducing highland farm erosion and reinforcing farming facilities structures for agricultural disaster management.

• 농촌의학ㆍ지역보건
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• 제6권1호
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• pp.13-24
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• 1981

This study was conducted with 478 farm households located in Pyongtaek Gun of Gyonggi Do, Chongju City and Chongwon Gun of Chung Buk Do, and Hongchon Gun of Gangwon Do for the period of 10, September through 20, October 1980. It dealt with general features of the farmhouseholds, their practices of handling and using pescides, and relationship between safe use of pesticides and poisoning experiences. The results of the study are summarized as follows: 1. Of the total, 63.2% purchased pesticides mainly through the Agricultural Coops, and 95.4% transported them home separately from other goods. 2 Pesticides were sold contained mainly in glass bottles and paper bags. 3. Mixing of the respodents (87.5%) stored pesticides in sheds, warehouses and boxes. 4. Mixing containers and measuring tools were not used by the majority of the group studied. This indicates that there exist serious problems of safety and accuracy with regard to use of pesticides. 5. As to pesticide protective devices, gloves, respirators, goggles and boots were not used in general. Even in case of using them, their quality was not satisfactory. 6. Among the interviewees, 4.2% did not read pesticide label, 33.9% did not wash immediately when pesticide was spilled on the skin, 48.4% did not care the wind direction during pesticide application, and 17.0% did not wash hands when smoking a cigarette while pesticide is being handled. 7. Of the total, 40.4% were found to harvest vegetables within 10 days from the date of pesticide application, which indicates their unawareness of possible hazards by pesticide residues. 8. Empty pesticide containers or bags were not properly disposed of by majority of the respondents. Furthermore, impacts on the environment by the misuse or abuse of pesticides were not understood by 67.6% 9. Of the interviewees, 48.7% were found to have not received instructions on safe use of pesticides. 10. The rate of pesticidal poisoning experience was about 28.0% if minor symptoms excluded, and it rose to about 44.0% if included. Meanwhile, the rate of pesticidal poisoning tends to increase with the size of farm. 11. The study failed to show a statistically significant relationship between the rate of pesticidal poisoning and use of mixing container and/or measuring tools. However, use of gloves showed a statistical significance on the rate of pesticidal poisoning. 12. Among the poisoned cases, 19.0% were cared for in either hospitals or clinics.