• 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%.

• New & Renewable Energy
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• v.10 no.1
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• pp.41-49
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• 2014

For a proper valuation of wind power project, it is necessary to consider volatilities of key parameters such as annual energy production, electricity sales price, and long term interest rate. Real option methodology allows to calculate option values of these parameters. Volatilities to be considered in wind project valuation are 1) annual energy production (AEP) estimation due to meteorological variation and estimation errors in wind speed distribution, 2) changes in system marginal price (SMP), and 3) interest rate fluctuation of project financing which provides refinancing option to be exercised during a loan tenor for commercial scale projects. Real option valuation turns out to be more than half of the sales value based on a case study for a FIT scheme wind project that was sold to a financial investor.

• Journal of Advanced Marine Engineering and Technology
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• v.41 no.3
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• pp.209-215
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• 2017

A large floating offshore wind-wave hybrid power generation system with an area of 150 m2 and four 3 MW class wind turbine generators was installed at each column top. In accordance with the wind turbine arrangement, the wake generated from upstream turbines can adversely affect the power performance and load characteristics of downstream turbines. Therefore, an optimal arrangement design, obtained through a detailed flow analysis focusing on wake interference, is necessary. In this study, to determine the power characteristics and annual energy production (AEP) of individual wind turbines, transient computational fluid dynamics, considering wind velocity variation (8 m/s, 11.7 m/s, 19 m/s, and 25 m/s), was conducted under different platform conditions ($0^{\circ}$, $22.5^{\circ}$, and $45^{\circ}$). The AEP was calculated using a Rayleigh distribution, depending on the wind turbine arrangement. In addition, we suggested an optimal arrangement design to minimize wake losses, based on the AEP.

• Journal of the Korean Solar Energy Society
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• v.32 no.6
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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.

• Korean Management Science Review
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• v.30 no.2
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.7
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• pp.469-480
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• 2017

For accurate AEP prediction in a wind farm, it is necessary to effectively calculate the wind speed reduction and the power loss due to the wake effect in each wind direction. In this study, a computer program for AEP prediction considering directional wake effect was developed. The results of the developed program were compared with the actual AEP of the wind farm and the calculation result of existing commercial software to confirm the accuracy of prediction. The applied equations are identical with those of commercial software based on existing theories, but there is a difference in the calculation process of the detection of the wake effect area in each wind direction. As a result, the developed program predicted to be less than 1% of difference to the actual capacity factor and showed more than 2% of better results compared with the existing commercial software.

• Journal of Industrial Technology
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• v.25 no.B
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• pp.149-157
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• 2005

The power performance monitoring system for a small class of wind turbine is established. The wind turbine power performance characteristics are determined by measured power curve and the estimated annual energy production (AEP). The measured power curve is determined by collecting simultaneous measurements of wind speed and power output at the test site under varying wind conditions. In order to determine the power performance characteristics of the wind turbine accurately, the data are of sufficient quantity and quality shall be corrected according to defined criteria. In this study, the 6kW wind turbine made by Germany Inventus GmbH is examined.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.21-24
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• 2005

This study explains the procedure that should be taken to develop a successful wind park project. It Provide guideline for activities and studies to be done step by step solution. This study follow a chronological flow through the development process. They cover Technical consideration, Assessment of Wind Energy Resource, Wind park siting and Energy yield calculation. It's build on the experience gained by the Youngduk Wind Park project and give the playa role in the development of wind energy projects. It is important to understand all theses issues if a new project is to be successfully completed.

• New & Renewable Energy
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• v.1 no.2 s.2
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• pp.19-25
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• 2005

This study explains ther procedure that should be taken to develp a successful wind park project. It provides a guideline for the activities and studies to be done as a step by step solution. This study follows a chronological flow throughout the whole development Process. This Paper covers technical consideration, assessment of wind energy resource, wind Park siting and energy yield calculation This presented knowledge h3s been mostly gained by the experience from Youngduk wind park project. The further comparison study will be performed between the theoretical prediction and the actual yield of the Youngduk wind park.

• Journal of Wind Energy
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• v.4 no.1
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• pp.46-52
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• 2013

The wind generally includes turbulence characteristics in nature. So the yaw errors between wind turbine direction and wind direction occur due to turbulence fluctuation. The yaw errors affect the fatigue load of wind turbine system and power reduction. The components of turbulence intensity are different from those of each site where the wind turbines are installed. We studied that the fatigue load and power efficiency are improved by controlling yaw motions. In this study, we controlled the averaged yaw error time according to site conditions by turbulence intensity.