• Title/Summary/Keyword: 강원풍력발전단지

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Feasibility Study for the Construction of Wind Farm (풍황 및 계통여건을 고려한 강원지역 풍력실증단지 적정입지 분석)

  • Lee, Jung-Eun;Cheong, Jong-Chan;Kee, Woo-Bong;Kim, Hyun-Han;Lee, Kue-Sam;Kim, Kwang-Ho;Jang,, Gil-Soo;Kang, Sang-Hee
    • Proceedings of the KIEE Conference
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    • 2007.07a
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    • pp.768-769
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    • 2007
  • 국내의 풍력자원과 계통자원을 함께 고려해 강원도 풍력발전단지의 최적입지 타당성을 검증. 국내의 풍황 자료를 조사하고 우수한 지역 5곳을 선정한 후, WASP 프로그램을 이용해 최대 에너지 생산 가능한 지역에 풍력발전기의 배치를 결정하였다.

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Prediction and Validation of Annual Energy Production of Garyeok-do Wind Farm in Saemangeum Area (새만금 가력도 풍력발전단지에 대한 연간발전량 예측 및 검증)

  • Kim, Hyungwon;Song, Yuan;Paek, Insu
    • Journal of Wind Energy
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    • v.9 no.4
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    • pp.32-39
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    • 2018
  • In this study, the annual power production of a wind farm according to obstacles and wind data was predicted for the Garyeok-do wind farm in the Saemangeum area. The Saemangeum Garyeok-do wind farm was built in December 2014 by the Korea Rural Community Corporation. Currently, two 1.5 MW wind turbines manufactured by Hyundai Heavy Industries are installed and operated. Automatic weather station data from 2015 to 2017 was used as wind data to predict the annual power production of the wind farm for three consecutive years. For prediction, a commercial computational fluid dynamics tool known to be suitable for wind energy prediction in complex terrain was used. Predictions were made for three cases with or without considering obstacles and wind direction errors. The study found that by considering both obstacles and wind direction errors, prediction errors could be substantially reduced. The prediction errors were within 2.5 % or less for all three years.

Comparison Analysis of Turbulence Intensity and Fatigue Load of Onshore Wind Farms According to Terrain (지형에 따른 육상풍력발전단지 난류강도 및 피로 하중 비교 분석)

  • Yeong-Hwi Kim;Minji Kim;Insu Paek
    • Journal of Wind Energy
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    • v.14 no.4
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    • pp.57-67
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    • 2023
  • This study aimed to investigate differences in turbulence intensity and turbine loads among onshore wind farms located in various types of terrain. To achieve this, simulations were conducted for two onshore wind farms with identical wind turbines and capacity but situated on complex and flat terrains. The simulations used meteorological data gathered over a 10-year period from automatic weather stations nearest to the wind farms. WindSim and WindPRO software tools were employed for wind field and load analysis, respectively. The simulation results revealed that wind farm A, situated on complex terrain, exhibited significantly higher effective turbulence intensity than wind farm B on flat terrain, as expected. Consequently, the load indices of several wind turbines exceeded 100 % in wind farm A, indicating that the turbines could not reach their design lifespan. From the simulation study, aimed at reducing both the effective turbulence intensity and turbine loads, it became evident that while increasing turbine spacing could decrease effective turbulence intensity to some extent, it couldn't completely resolve the issue due to the inherently high ambient turbulence intensity on complex terrain. The problem with wind turbine loads could only be completely resolved by using wind turbines with a turbine class of A+, corresponding to a reference turbulence intensity of 0.18.

Analyzing Site Characteristics and Suitability for Wind Farm Facilities in Forest Lands (산지 내 풍력발전단지 입지 특성 및 적합성 분석)

  • Kwon, Soon-Duk;Joo, Woo-Yeong;Kim, Won-Kyung;Kim, Jong-Ho;Kim, Eun-Hee
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.4
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    • pp.86-100
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    • 2014
  • The purposes of this study are to provide a guideline for the suitability of wind farm facilities in forest lands and to suggest improvement plans of policies and systems to minimize the damage of forest lands. First, we implemented a literature review and field surveys to examine and select factors for the suitability of wind farm facilities in forest lands. Spatial database for selected location factors of wind farm facilities in forest lands was constructed to develop the suitability model for locating wind farm facilities focusing on Gangwon-do. Data used in this study include wind power resource, legal mountainous preserved area, forest roads, developed areas, forest class, and other spatial data. In order to find specific-sized potential areas for a certain number of wind farm turbines, we used block statistics and focal statistics methods. As a result, the areas for potential wind farm locations were 1,261ha from a block statistics method and 1,411ha from a focal statistics method. Based on the outputs of this research, it is required to make an urgent solution for the prevention of forest disaster and to prepare reduction measures for the destruction of ridge landscape.

AEP Prediction of Gangwon Wind Farm using AWS Wind Data (AWS 풍황데이터를 이용한 강원풍력발전단지 발전량 예측)

  • Woo, Jae-Kyoon;Kim, Hyeon-Ki;Kim, Byeong-Min;Yoo, Neung-Soo
    • Journal of Industrial Technology
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    • v.31 no.A
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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%.

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Prediction of Annual Energy Production of Wind Farms in Complex Terrain using MERRA Reanalysis Data (MERRA 재해석 자료를 이용한 복잡지형 내 풍력발전단지 연간에너지발전량 예측)

  • Kim, Jin-Han;Kwon, Il-Han;Park, Ung-Sik;Yoo, Neungsoo;Paek, Insu
    • Journal of the Korean Solar Energy Society
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    • v.34 no.2
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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.

Prediction of Annual Energy Production of Gangwon Wind Farm using AWS Wind Data (AWS 풍황데이터를 이용한 강원풍력발전단지 연간에너지발전량 예측)

  • Woo, Jae-kyoon;Kim, Hyeon-Gi;Kim, Byeong-Min;Paek, In-Su;Yoo, Neung-Soo
    • Journal of the Korean Solar Energy Society
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    • v.31 no.2
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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%.

The Selection of Promising Wind Farm Sites in Gangwon Province using Multi Exclusion Analysis (다중 배제분석을 이용한 강원도 내 풍력발전단지 유망후보지 선정)

  • Park, Ung-Sik;Yoo, Neung-Soo;Kim, Jin-Han;Kim, Kwan-Soo;Min, Deok-Ho;Lee, Sang-Woo;Paek, In-Su;Kim, Hyun-Goo
    • Journal of the Korean Solar Energy Society
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    • v.35 no.2
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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.