• Title/Summary/Keyword: Onshore wind farm

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The Study of Onshore Wind Farm Suitability Analysis Process (육상풍력 적지분석 프로세스에 대한 연구)

  • Ko, Jung-Woo;Lee, Byung-Gul
    • Journal of Environmental Science International
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    • v.25 no.3
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    • pp.457-464
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    • 2016
  • The most wind farm development process in Korea still have not been defined since the history of the wind farm development experiences are very short compared to EU and other developed countries. Therefore, most wind farm development company and researchers have a lot of trouble to implement the wind farm development and need a guideline for the process. Establishing the wind farm needs a complex processes such as transportation system, construction conditions, natural environment and wind conditions etc. Specially, for the restricted development area, the social negotiation and legal minds are necessary. In the case, the decision making process of suitable wind farm area using GIS tool is very useful. However, before using GIS technique, we should understand the development processes and the items for surveying tools. Recently, suitability analysis of selecting Onshore Wind Farm has been studied to consider exclusion analysis to solve the limited develop condition problem. This paper proposed the onshore wind farm development process which can suitable to Korea wind farm environment based on European guideline with GIS tool. To estimate the processes, the processes are divided into two parts, the basic design and wind farm planning. Next, the planning stages are classified into five stages in which the factors for each step were considered.

Wind Turbine Wake Model by Porous Disk CFD Model (다공 원반 CFD 모델을 이용한 풍력발전기 후류 해석 연구)

  • Shin, Hyungki;Jang, Moonseok;Bang, Hyungjun;Kim, Soohyun
    • Journal of Wind Energy
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    • v.4 no.1
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    • pp.68-74
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    • 2013
  • Offshore wind farm is being increased since there are much trouble to develop onshore wind farm. But in the offshore, wind turbine wake does not dissipate less than onshore wind turbine because of low turbulence level. Thus this remained wake interacted to other wind turbine. This interaction reduces energy production in wind farm and have a bad influence on fatigue load of wind turbine. In this research, CFD model was constructed to analyze wake effect in offshore wind farm. A method that wind turbine rotor region was modelled in porous media was devised to reduce computation load and validated by comparison with Horns Rev measurement. Then wake interaction between two wind turbine was analyzed by devised porous model.

Changes in insect diversity and composition after construction of an onshore wind farm (육상풍력발전단지 조성에 따른 곤충군집 변화에 관한 연구)

  • Jin Lee;Sung-Soo Kim;Moon-Jeong Jang
    • Korean Journal of Environmental Biology
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    • v.40 no.4
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    • pp.591-603
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    • 2022
  • This study was conducted to identify changes of insect compositions and diversity after construction of an onshore wind farm. We investigated insect fauna and compositions between a grassland deforested by the construction and a forest located at Yeongdeok and Yeongyang, Gyeongsangbuk-do, Korea. Insects were collected using a sweeping net and light trap. A total of 11 orders, 50 families, and 246 species, and 1,076 individuals were collected at study sites. By taxonomic group, Lepidoptera species were the most frequently found with 141 species, 417 individuals (38.8%), followed by Hymenoptera (20.6%), Hemiptera (16.2%), and Orthoptera (12.3%). There were also significant differences in insect species and community compositions between sites. Creating open-field deforested forests are beneficial for some insect groups such as Hymenoptera and Orthoptera. Our results suggest that deforesting by the construction of an onshore wind farm might affect the composition and diversity of insects. Results of this study provide basic data for research on onshore wind farms.

A Study on the Power Loss Cost of Inner-Grid in the Offshore Wind Farm (해상풍력단지 내부그리드의 전력손실비용에 관한 연구)

  • Shin, Je-Seok;Kim, Sung-Yul;Bae, In-Su
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.3
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    • pp.72-77
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    • 2014
  • The cross-section area of cable in the Offshore Wind Farm (OWF) is smaller than that in the onshore wind farm. Because the power loss in OWF is large relatively, the power loss is a key element for the economic evaluation of OWF design. The availability of wind turbine in OWF and the size of OWF are larger than those of onshore wind farm. If the economic evaluation of OWF ignores the availability of wind turbines, the power loss cost of OWF is overpriced. Since there are so many wind turbines, also, the calculation of power loss should be more accurate. In this paper, a method to calculate power loss is proposed for the design of big and complex inner-grid in OWF. The 99.5MW OWF is used for case study to see what effect the proposed method have on the power loss cost.

Analysis of LCOE for Korean Onshore Wind Farm Considering Social Discount Rate (사회적 할인율을 고려한 국내육상풍력발전 단지의 LCOE 분석)

  • Lee, Keon-Woo;Ko, Kyung-Nam
    • Journal of the Korean Solar Energy Society
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    • v.40 no.1
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    • pp.1-13
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    • 2020
  • A study on estimation of the Levelized Cost of Energy (LCOE) was conducted for the Korean onshore wind farms. The LCOE was estimated on the basis of the actual wind farm data from Data Analysis, Retrieval Transfer system (DART) run by Financial Supervisory Service. Recently, social discount rate of Korea dropped from 5.5% to 4.5%, which was taken into account for this study. The onshore wind farms studied accounted for 42% of all the onshore wind farms of South Korea. Capital Expenditure (CapEx) and Operation Expenditure (OpEx) were calculated from the actual data, while Capacity Factors (CFs) were obtained from the wind farms of five provinces. Their distributions were estimated using Maximum Likelihood Estimation method, and then Monte Carlo Simulation (MCS) was performed for estimating LCOE, Levelized Fixed Cost (LFC), and Levelized Variable Cost (LVC). As a result, the LCOEs at the two discount rates, 4.5 and 5.5%, were 142 and 152 $/MWh, respectively, which were lower than that of financially viable onshore wind project of Korea. The 1% drop of social discount rate was estimated to result in a 10 $/MWh decrease in LCOE and a 4 $/MWh in LFC, which can be an advantage for wind project investors.

Evaluation of Onshore Wind Resource Potential According to Environmental Conservation Value Assessment (국토환경성평가에 의한 육상 풍력자원 잠재량 산정)

  • Kim, Hyun-Goo;Hwang, Hyo-Jung;Kang, Young-Heaok
    • Journal of Environmental Science International
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    • v.22 no.6
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    • pp.717-721
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    • 2013
  • In order to analyze the effect of environmental protection on wind energy dissemination quantitatively, the onshore wind resource potential is estimated using Environmental Conservation Value Assessment Map and Korea Wind Resource Map. The onshore wind resource potential of 11 GW is calculated if wind farm development is prohibited within Class 1 area of Environmental Conservation Value Assessment plus 500 m buffer area. Therefore it is worried that environmental protection would be a practical barrier of accomplishing 4,155 thousand TOE target of wind energy dissemination until 2030.

Economic Assessments of LFAC and HVDC Transmissions for Large Offshore Wind Farms

  • Park, Taesik;Kwak, Nohong;Moon, Chaeju;Cha, Seungtae;Kwon, Seongchul
    • KEPCO Journal on Electric Power and Energy
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    • v.1 no.1
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    • pp.73-77
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    • 2015
  • Offshore wind farms extend a distance from an onshore grid to increase their generating power, but long distance and high power transmissions raise a lot of cost challenges. LFAC (Low Frequency AC) transmission is a new promising technology in high power and low cost power transmission fields against HVDC (High Voltage DC) and HVAC (High Voltage AC) transmissions. This paper presents an economic comparison of LFAC and HVDC transmissions for large offshore wind farms. The economic assessments of two different transmission technologies are analyzed and compared in terms of wind farm capacities (600 MW and 900 MW) and distances (from 25 km to 100 km) from the onshore grid. Based on this comparison, the economic feasibility of LFAC is verified as a most economical solution for remote offshore wind farms.

Suitability Analysis of Onshore Wind Farm using GIS Program and Digital maps (GIS 및 수치지도를 활용한 육상풍력발전단지 적지분석)

  • Park, Jae-Hyeong;Lee, Hwa-Woon;Kim, Dong-Hyuk;Kim, Hyun-Goo;Kim, Tae-Wook
    • Journal of Environmental Science International
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    • v.23 no.11
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    • pp.1919-1927
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    • 2014
  • In order to decide the location of appropriate onshore wind farm with higher potential wind energy, several decision processes using Geographic Information System (GIS) including Digital Elevation Map (DEM) were proposed and we also estimated the wind resources through the proposed decision process. Decision process consists with three steps. First step is excluding inappropriate location geographically using DEM data including SRTM (Shuttle Radar Topography Mission) terrain data, landslide, land-use, roadway, and forest road data. And the second step of decision process is consideration of the difficulty caused by the natural environmental problem. This step is carried out using ECVAM (Environmental Conservation Value Assessment Map) data. And final step is determination of the most suitable location through the Moving Suitability Identification Method (MSIM) based on the moving potentially estimated wind resources area. Proposed decision process was applied over the Korean Peninsula. Wind resource potential estimated by the first and the second step is cases shows 35.09 GW and 7.17 GW, respectively, and the total evaluated energy from the all proposed step were 0.43 GW and 1.87 GW for the 3 km and 1.5 km geographical grid size, respectively.

Evaluation of Onshore Wind Resource Potential According to the Road Proximity (도로인접성에 따른 육상 풍력자원 잠재량 평가)

  • Kim, Hyun-Goo;Hwang, Hyo-Jung;Kang, Yong-Heack;Yun, Chang-Yeol
    • New & Renewable Energy
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    • v.9 no.4
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    • pp.13-18
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    • 2013
  • Wind turbines should generally be installed at a certain distance from a road to ensure passengers' safety. In Korea, there is no clear guidance as the Ministry of Environment first proposed a road setback distance of 400 m in the Onshore Wind Farm Siting Guidelines draft proposed in July 2012, and then modified it to 1.5 times the height of the wind turbine in October of the same year. This study analyzed the dynamic range of onshore wind resource potential according to how the road setback distance is set using the Korea Wind Atlas with 100m spatial resolution made by the Korea Institute of Energy Research, the transportation network of the Ministry of Construction and Transportation, and the forest road network of the Korea Forestry Service. Owing to the geographical characteristics of Korea, where mountainous terrain accounts for 70% of the total territory, the wind resource potential within 1 km from forest roads are estimated to be 14.3 GW, 14% of Korea's total wind resource potential. In addition, the construction distance of new road for transporting wind turbines from the existing road to a wind farm site is estimated as less than 2 km. Given the limited wind resource potential and geographical constraints, an assessment system that can maximize wind resource utilization and ensure road safety at the same time, and which takes into account the regional characteristics instead of applying the fixed road setback distance across-the-road, is required.

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.