• 제목/요약/키워드: Wind turbine drivetrain

검색결과 5건 처리시간 0.029초

GL 2010 기반 대형 풍력터빈 드라이브트레인 시스템 다물체 동역학 해석기법 (Multi-body Dynamic Analysis for the Drivetrain System of a Large Wind Turbine Based on GL 2010)

  • 정대하;김동현;김명환
    • 한국소음진동공학회논문집
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    • 제24권5호
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    • pp.363-373
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    • 2014
  • In this study, computational multi-body dynamic analyses for the drivetrain system of a 5 MW class offshore wind turbine have been conducted using efficient equivalent modeling technique based on the design guideline of GL 2010. The present drivetrain system is originally modeled and its related system data is adopted from the NREL 5 MW wind turbine model. Efficient computational method for the drivetrain system dynamics is proposed based on an international guideline for the certification of wind turbine. Structural dynamic behaviors of drivetrain system with blade, hub, shaft, gearbox, supports, brake disk, coupling, and electric generator have been analyzed and the results for natural frequency and equivalent torsional stiffness of the drivetrain system are presented in detail. It is finally shown that the present multi-body dynamic analysis method gives good agreement with the previous results of the 5 MW class wind turbine system.

풍력터빈 드라이브트레인의 동특성 해석을 위한 모델링 기법 (Modeling Techniques for The Dynamic Characteristics Analysis of Drivetrain in Wind Turbine)

  • 임동수;이승규;조준행;안경민
    • 한국신재생에너지학회:학술대회논문집
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    • 한국신재생에너지학회 2008년도 춘계학술대회 논문집
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    • pp.286-289
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    • 2008
  • Wind turbine industry is booming and spending a lot on research for improving the performance of its present machines and increasing their capacity. Wind turbine requires service life of about 20 years and each components of wind turbine requires high durability, because installation and maintenance costs are more expensive than generated electricity by wind-turbine. So the design of wind turbine must be verified in various condition before production step. For this work, high reliability model for analysis is required. Drivetrain model is modeled by multibody dynamic modeling method. The model constituted with rotor blades, hub, main shaft, gear box, high speed shaft and generator. Natural frequency and torsional stiffness of drivetrain are calculated and analyzed.

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풍력터빈 드라이브트레인의 동특성 해석을 위한 모델링 기법 (Modeling Techniques for The Dynamic Characteristics Analysis of Drivetrain in Wind Turbine)

  • 임동수;이승규;양보석
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2012년도 추계학술대회 논문집
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    • pp.583-586
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    • 2012
  • Wind turbine industry is booming and spending a lot on research for improving the performance of its present machines and increasing their capacity. Wind turbine requires service life of about 20 years and each canponents of wind turbine requires high durability, because installation and maintenance costs are more expensive than generated electricity by wind-turbine. So the design of wind turbine must be verified in various condition before production step. For this work, high reliability model for analysis is required. Drivetrain model is modeled by multibody dynamic modeling method. The model constituted with rotor blades, hub, main shaft, gear box, high speed shaft and generator. Natural frequency and torsional stiffness of drivetrain are calculated and analyzed.

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풍력발전기 디지털트윈 개발을 위한 드라이브트레인 시뮬레이션 모델의 기계학습 연구 (A Study on Machine Learning of the Drivetrain Simulation Model for Development of Wind Turbine Digital Twin)

  • 최요나단;김탁곤
    • 한국시뮬레이션학회논문지
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    • 제32권3호
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    • pp.33-41
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    • 2023
  • 최근 전 세계가 탄소중립에 관심이 높아지면서 재생에너지 발전량이 증가하고 있다. 하지만 재생에너지는 간헐성과 변동성이 심해 발전량 예측이 어렵고, 정확하지 않은 발전량 예측은 전력 계통에 부정적인 영향을 끼칠 수 있다. 이에 본 연구에서는 풍력발전기 발전량 예측 문제를 해결할 방법으로 디지털트윈 개념을 적용하였다. 풍력발전기의 회전이 발전량과 높은 상관관계를 갖는 부분을 반영하여 풍력발전기 드라이브트레인 회전 거동을 주로 모의하는 기계학습된 모델을 개발하였다. 회전 거동을 모의하는 드라이브트레인 시뮬레이션 모델의 기반은 잘 알려진 회전 시스템을 모의하는 시스템 상태방정식으로 설정되었다. 또한 제조사로부터 제공되지 않은 파라미터들에 대하여 시뮬레이션 기반 기계학습을 수행하였다. 기계학습된 드라이 브트레인 모델은 27개의 실제 풍력발전기 운영데이터 세트를 활용하여 검증되었다. 검증 결과, 드라이브트레인 모델은 실제 풍력발전기 운영데이터 세트와 비교하여 평균 4.41%의 오차를 보였다. 결과적으로 기계학습된 드라이브트레인 모델은 실제 풍력발전기 드라이브트레인 시스템을 잘 모사한다고 평가하였다.

상태지수의 경향성 분류에 기반한 풍력발전기 베어링 잔여수명 추정 (Estimation of Remaining Useful Life for Bearing of Wind Turbine based on Classification of Trend)

  • 서윤호;김상렬;마평식;우정한;김동준
    • 풍력에너지저널
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    • 제14권3호
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    • pp.34-42
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    • 2023
  • The reduction of operation and maintenance (O&M) costs is a critical factor in determining the competitiveness of wind energy. Predictive maintenance based on the estimation of remaining useful life (RUL) is a key technology to reduce logistic costs and increase the availability of wind turbines. Although a mechanical component usually has sudden changes during operation, most RUL estimation methods use the trend of a state index over the whole operation period. Therefore, overestimation of RUL causes confusion in O&M plans and reduces the effect of predictive maintenance. In this paper, two RUL estimation methods (load based and data driven) are proposed for the bearings of a wind turbine with the results of trend classification, which differentiates constant and increasing states of the state index. The proposed estimation method is applied to a bearing degradation test, which shows a conservative estimation of RUL.