• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2134-2141
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• 2014

This paper addresses on a wind power system with BESS(Battery Energy Storage System). The concerned system consists of four parts: the wind speed production model, the wind turbine model, configure capacity of the battery energy storage, battery model and control of the BESS. First of all, we produce wind speed by 4-component composite wind speed model. Secondly, the maximum available wind power is determined by analyzing the produced wind speed and the characteristic curve of wind power. Thirdly, we configure capacity of the BESS according to wind speed and characteristic curve of wind speed-power. Then, we propose a control strategy to track the power reference. Finally, some simulations have been demonstrated to visualize the feasibility of the proposed methodology.

• Journal of the Korean Solar Energy Society
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• v.35 no.3
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• pp.17-25
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• 2015

The main objective of this study is to predict the wind power generation at the wind farm using various wake models. Modeling of wind farm is a prerequisite for prediction of annual energy production at the wind farm. In this study, we modeled 20 MW class Seongsan wind farm which has 10 wind turbines located at the eastern part of Jeju Island. WindSim based on the computational fluid dynamics was adopted for the estimation of power generation. The power curve and thrust coefficient with meteorology file were prepared for wind farm modelling. The meteorology file was produced based on the measured data of the Korea Wind Atlas provided by Korea Institute of Energy Research. Three types of wake models such as Jensen, Larsen, and Ishihara et al. wake models were applied to investigate the wake effects. From the result, Jensen and Ishihara wake models show nearly the same value of power generation whereas the Larsen wake model shows the largest value. New positions of wind turbines are proposed to reduce the wake loss, and to increase the annual energy production of the wind farm.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.108-112
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• 2012

A sustainable production of electricity is essential for low carbon green growth in South Korea. The generation of wind power as renewable energy has been rapidly growing around the world. Undoubtedly wind energy is unlimited in potential. However, due to its own intermittency and volatility, there are difficulties in the effective harvesting of wind energy and the integration of wind power into the current electric power grid. To cope with this, many works have been done for wind speed and power forecasting. It is reported that, compared with physical persistent models, statistical techniques and computational methods are more useful for short-term forecasting of wind power. Among them, support vector regression (SVR) has much attention in the literature. This paper proposes an SVR based wind speed forecasting. To improve the forecasting accuracy, a fuzzy clustering is adopted in the process of SVR modeling. An illustrative example is also given by using real-world wind farm dataset. According to the experimental results, it is shown that the proposed method provides better forecasts of wind power.

• 한국신재생에너지학회:학술대회논문집
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• 2009.06a
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• pp.525-528
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• 2009

Power generation of wind turbine which is installed in wind farm should be measured to predict economic feasibility of wind farm. Also electric power company want to verify wind turbine performance which is stated by manufacturer. The International Electrotechnical Commission(IEC) published 61400-12-1 "Power performance measurements of electricity producing wind turbines" for test of wind turbine power performance. In this paper, measurable sector of wind speed is analysed based on IEC 61400-12-1 to verify power curve of wind turbine with various wind turbine in wind farm.

• Journal of Environmental Science International
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• v.23 no.9
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• pp.1551-1562
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• 2014

To clarify the characteristics of TKE (Turbulence Kinetic Energy) variation for offshore wind power development, several numerical experiments using WRF were carried out in three different coastal area of the Korean Peninsula. Buoyancy, mechanical and shear production term of the TKE budget are fundamental elements in the production or dissipation of turbulence. Turbulent kinetic energy of the south coast region was higher than in other sea areas due to the higher sea surface temperature and strong wind speed. In south coast region, strong wind passing through the Korea Strait is caused by channelling effect of the terrain of the Geoje Island. Although wind speed is weak in east coast, because of large difference in wind speed between the upper and lower layer, the development of mechanical turbulence tend to be predominant. Since lower sea surface temperature and smaller wind shear were detected in west coastal region, the possibility of turbulence production not so great in comparison with other regions. The understanding of the characteristics of turbulence in three different coastal region can be reduced the uncertainty of offshore wind construction.

• Journal of Power System Engineering
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• v.20 no.4
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• pp.44-51
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• 2016

An investigation on reliability of reanalysis wind data was conducted using the met mast wind data at four coastal regions, Jeju Island. Shinchang, Handong, Udo and Gangjeong sites were chosen for the met mast sites, and ERA-Interim and MERRA reanalysis data at two points on the sea around Jeju Island were analyzed for creating Wind Statistics of WindPRO software. Reliability of reanalysis wind data was assessed by comparing the statistics from the met mast wind data with those from Wind Statistics of WindPRO software. The relative error was calculated for annual average wind speed, wind power density and annual energy production. In addition, Weibull wind speed distribution and monthly energy production were analyzed in detail. As a result, ERA-Interim reanalysis data was more suitable for wind resource assessment than MERRA reanalysis data.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.211-212
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• 2008

As a result of environmental concerns, the production of electricity through renewable energy resources is rapidly increasing. Wind energy is among the fastest growing renewable energy resources now being integrated in the power system, and the penetration rate of wind generation has been gradually increased. For power flow analysis of the recent systems, thus, steady-state modeling of wind turbines and their application are of great importance. This paper presents the procedure we applied for implementation of a steady-state wind turbine model in power flow.

• New & Renewable Energy
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• v.5 no.2
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• pp.31-38
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• 2009

The performance test of a wind turbine in a wind farm is generally carried out by the owner to verify the power curve of the wind turbine given by the turbine manufacturer. The international electro-technical commission provides the IEC 61400-12-1 standard on "Power performance measurements of electricity producing wind turbines". By using this code, one can easily find the suitable met-mast (meteorological mast) location for the wind data whether a wind farm is potential or already built. In this paper, the valid sectors for wind turbines installed in the HanKyoung wind farm, south-west in Jeju island are analyzed on the basis of the code by considering the wind farm layout. Among these sectors, the optimal met-mast location is presented for the power curve verification of the wind farm.

• 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.

• 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.