• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2005년도 제17회 워크샵 및 추계학술대회
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• pp.575-578
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• 2005

The optimum design and the performance analysis software called POSEIDON for the HAWT (Horizontal Axis Wind Turbine) was developed by use of BEMT. The Prandtl's tip loss theory was adopted to consider the blade tip loss. The lift and the drag coefficient of S-809 airfoil were predicted via X-FOIL and also the post stall characteristics of S-809 were estimated by the Viterna's equations. All the predicted aerodynamic characteristics are fairly well agreed with the wind tunnel test results, performed by Sommers in Delft university of technology. The rated power of the testing rotor is 20kW(FIL-20) at design conditions. The experimental aerodynamic parameters and the X-FOIL data were used for the power prediction of the FIL-20 respectively. The comparison results shows good agreement in power prediction.

• 신재생에너지
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• 제1권4호
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• pp.38-42
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• 2005

The optimum design and the performance analysis software called POSEIDON for the HAWT [Horizontal Axis Wind Turbine] was developed by use of BEMT. The Prandtl's tip loss theory was adopted to consider the blade tip loss. The lift and the drag coefficient of S-809 airfoil were predicted via X-FOIL and also the post stall characteristics of S-809 were estimated by the Viterna's equations. All the predicted aerodynamic characteristics are fairly well agreed with the wind tunnel test results, performed by Sommers in Delft university of technology. The rated power of the testing rotor is 20kW[FIL-20] at design conditions. The experimental aerodynamic parameters and the X-FOIL data were used for the power prediction of the FIL-20 respectively. The comparison results shows good agreement in power prediction.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.689-700
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• 2017

This paper presents an effective approach for wind turbine (WT) condition assessment based on the data collected from wind farm supervisory control and data acquisition (SCADA) system. Three types of assessment indices are determined based on the monitoring parameters obtained from the SCADA system. Neural Networks (NNs) are used to establish prediction models for the assessment indices that are dependent on environmental conditions such as ambient temperature and wind speed. An abnormal level index (ALI) is defined to quantify the abnormal level of the proposed indices. Prediction errors of the prediction models follow a normal distribution. Thus, the ALIs can be calculated based on the probability density function of normal distribution. For other assessment indices, the ALIs are calculated by the nonparametric estimation based cumulative probability density function. A Back-Propagation NN (BPNN) algorithm is used for the overall WT condition assessment. The inputs to the BPNN are the ALIs of the proposed indices. The network structure and the number of nodes in the hidden layer are carefully chosen when the BPNN model is being trained. The condition assessment method has been used for real 1.5 MW WTs with doubly fed induction generators. Results show that the proposed assessment method could effectively predict the change of operating conditions prior to fault occurrences and provide early alarming of the developing faults of WTs.

• Wind and Structures
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• 제22권2호
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• pp.235-252
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• 2016

A wind velocity power spectrum (WVPS) with high fidelity is extremely important for accurate prediction of structural buffeting response. WVPS heavily depends on the geographical locations, local terrains and topographies. Hence, field measurement of wind characteristics may be the unique way to obtain the accurate WVPS for a specific region. In this paper, a systematic analysis and discussions of existing WVPSs were performed. Six recorded strong wind data from the structural health monitoring systems (SHMS) of Runyang Suspension Bridge (RSB) and Sutong Cable-stayed Bridge (SCB) in Jiangsu Province of China were selected for analysis. The measured and pre-processed wind velocity data was first transformed from time domain to frequency domain to obtain the measured spectrum. The spectrum for each strong wind was then fitted using the nonlinear least square method and compared with both the fitted spectrum from statistical analysis and the recommended spectrum in specifications. The modified Kaimal spectrum was proved to be the "best" choice for the coastal area of East Jiangsu Province. Finally, a suitable WVPS formula fit for the coastal area of East Jiangsu Province was presented based on the modified Kaimal spectrum. Results in this study provide a more accurate and reliable WVPS for wind-resistant design of engineering structures in the coastal area of East Jiangsu Province.

• Journal of Power Electronics
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• 제17권1호
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• pp.232-241
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• 2017

Advanced control algorithms must be used to make wind power generation truly cost effective and reliable. In this study, we develop a new and simple control scheme that employs model predictive control (MPC), which is used in permanent magnet synchronous generators and grid-connected inverters. The proposed control law is based on two points, namely, MPC-based torque-current control loop is used for the generator-side converter to reach the maximum power point of the wind turbine, and MPC-based direct power control loop is used for the grid-side converter to satisfy the grid code and help improve system stability. Moreover, a simple prediction scheme is developed for the direct-drive wind energy conversion system (WECS) to reduce the computation burden for real-time applications. A small-scale WECS laboratory prototype is built and evaluated to verify the validity of the developed control methods. Acceptable results are obtained from the real-time implementation of the proposed MPC methods for WECS.

• 한국지구과학회지
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• 제38권1호
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• pp.11-23
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• 2017

풍력 자원의 단기 예측 가능성은 풍력 발전 단지의 경제적 타당성을 평가하는 중요한 요소이다. 본 연구에서는 풍력 자원의 단기 예측 가능성을 향상시키는 방법의 하나로 베이지안 칼만 필터를 후처리 과정으로 적용하였다. 이때 추정된 모델과 관측 데이터의 상관관계를 평가하기 위하여 일정 시간 동안 베이지안 칼만 훈련 기간이 요구된다. 본 연구는 여러 훈련 기간에 따라 예측 특성을 정량적으로 분석하였다. 태백 지역에서는 3일 단기 베이지안 칼만 훈련으로 기온과 풍속을 예측하는 것이 다른 훈련 기간을 적용할 때보다 우수한 예측 성능을 보였다. 반면 이어도는 6일 이상의 베이지안 칼만 필터의 훈련 기간을 적용한 경우 가장 좋은 예측 성능을 나타낸다. WRF 예측 성능이 떨어지는 사례에서 베이지안 칼만 필터의 예측 성능향상이 뚜렷하게 나타나며, 반대로 WRF 예측이 정확한 지점에서는 필터적용에 따른 성능향상 정도가 약한 경향을 가진다.

• 한국항행학회논문지
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• 제22권5호
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• pp.478-484
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• 2018

본 연구는 기온, 강수량, 풍향, 풍속, 습도, 운량, 일조, 일사 등 시간별 기상 데이터를 이용하여, 일사 및 일조 그리고 태양광 발전예측을 하였다. 지도학습에서 입출력패턴은 예측에서 가장 중요한 요소이지만 인간이 직접 결정해야하기 때문에, 반복적인 실험에 의해 결정해야 한다. 본 연구는 일사 및 일조 예측을 위하여 4가지 모델의 입출력 패턴을 제안하였다. 또한, 예측된 일조 및 일사 데이터와 전라남도 영암 태양광 발전소의 발전량 데이터를 사용하여 태양광 발전량을 예측하였다. 실험결과 일조 및 일사 예측에서 모델 4가 가장 예측결과가 우수했으며, 모델 1에 비해 일조의 RMSE는 1.5배 정도 그리고 일사의 RMSE는 3배 정도 오차가 줄었다. 태양광 발전예측 실험결과 일조 및 일사와 마찬가지로 모델 4가 가장 예측결과가 좋았으며, 모델 1 보다 RMSE가 2.7배 정도 오차가 줄었다.

• 대한기계학회논문집B
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• 제32권7호
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• pp.549-557
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• 2008

Despite of the laminar-turbulent transition region co-exist with fully turbulence region around the leading edge of an airfoil, still lots of researchers apply to fully turbulence models to predict aerodynamic characteristics. It is well known that fully turbulent model such as standard k-model couldn't predict the complex stall and the separation behavior on an airfoil accurately, it usually leads to over prediction of the aerodynamic characteristics such as lift and drag forces. So, we apply correlation based transition model to predict aerodynamic performance of the NREL (National Renewable Energy Laboratory) Phase IV wind turbine. And also, compare the computed results from transition model with experimental measurement and fully turbulence results. Results are presented for a range of wind speed, for a NREL Phase IV wind turbine rotor. Low speed shaft torque, power, root bending moment, aerodynamic coefficients of 2D airfoil and several flow field figures results included in this study. As a result, the low speed shaft torque predicted by transitional turbulence model is very good agree with the experimental measurement in whole operating conditions but fully turbulent model(${\kappa}-\;{\varepsilon}$) over predict the shaft torque after 7m/s. Root bending moment is also good agreement between the prediction and experiments for most of the operating conditions, especially with the transition model.

• KEPCO Journal on Electric Power and Energy
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• 제5권3호
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• pp.223-228
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• 2019

In order to integrate large amounts of variable generation resources such as wind and solar reliably into power grids, accurate renewable energy forecasting is necessary. Since renewable energy generation output is heavily influenced by environmental variables, accurate forecasting of power generation requires meteorological data at the point where the plant is located. Therefore, a spatial approach is required to predict the meteorological variables at the interesting points. In this paper, we propose the meteorological variable prediction model for enhancing renewable generation output forecasting model. The proposed model is implemented by three geostatistical techniques: Ordinary kriging, Universal kriging and Co-kriging.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2011년도 추계학술대회 초록집
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• pp.40.2-40.2
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• 2011

A Counter-rotating wind turbine is one of the new concepts that are proposed to increase the performance of a wind turbine. It has two rotors rotating in the same axis, and it is known that its power coefficient can reach to 0.64 in the ideal case. While the BEMT is widely used to analyze the aerodynamic performance of wind turbines, the analysis of the counter-rotating wind turbine by using it is limited due to the aerodynamic interaction between the two rotors. In this study, the vortex lattice method is used to consider the effect of the front rotor on the rear rotor of the counter-rotating wind turbine and calculate the aerodynamic performance of it. The power and thrust sharing in the two rotors of the counter-rotating wind turbine are predicted and the total power and thrust are compared with that of a single rotor. Moreover, the wake convection and expansion rate is also compared with that of a single rotor.