• Journal of the Korean Solar Energy Society
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• v.32 no.6
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• pp.37-43
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• 2012

Long-term variations in wind speed and capacity factor(CF) on Seongsan wind farm of Jeju Island, South Korea were derived statistically. The selected areas for this study were Subji, having a year wind data at 30m above ground level, Sinsan, having 30-year wind data at 10m above ground level and Seongsan wind farm, where long-term CF was predicted. The Measure-Correlate-Predict module of WindPRO was used to predict long-tem wind characteristics at Seongsan wind farm. Eachyear's CF was derived from the estimated 30-year time series wind data by running WAsP module. As a result, for the 30-year CFs, Seongsan wind farm was estimated to have 8.3% for the coefficien to fvariation, CV, and-16.5% ~ 13.2% for the range of variation, RV. It was predicted that the annual CF at Seongsan wind farm varied within about ${\pm}4%$.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.504-511
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• 2010

After facing the fact such as fossil-fuel depletion, global warming, the Kyoto Protocol coming into force of mandatory reductions of carbon dioxide, the world is actively promoting the spread of the solar, wind, tidal, geothermal and other clean renewable energy technology development. Among them, wind power is the only alternative energy to secure a comparable price competition with fossil fuels because cheaper price power generation than other renewable energy when creating large-scale wind farm, thus wind power is the fastest growing industries in the world in the renewable energy field. Especially the offshore wind power is showing rapid growth as most of the wind power sector because of less changes of wind speed, no restrictions of land use, and large-scale development of offshore wind power. In this paper, the field of site selection and spatial location analysis techniques for development of large-scale offshore wind farm are discussed primarily. This paper shows overview of offshore wind power and establishment procedure for development of offshore wind farm.

• 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.

• Journal of Advanced Marine Engineering and Technology
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• v.35 no.8
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• pp.1063-1069
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• 2011

This paper presents aerodynamic power outputs of wind turbine of 6 MW wind farm composed of 3 sets of 2 MW wind turbine according to the separation distance by using CFD. Layout design including offshore wind farm and onshore wind farm is key factor for the initial investment cost, annual energy production and maintenance cost. For each wind turbine rotor, not actuator disc model with momentum source but full 3-dimensional model is used for CFD and it has a great technical meaning. The results of this study can be applied to the offshore wind farm layout design effectively.

• Journal of Wind Energy
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• v.14 no.2
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• pp.14-25
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• 2023

This study focuses on proposing measures for the reasonable development of offshore wind farms using the case of Norway, which was the first nation in the world to build a floating offshore wind farm of 80 MW or more. Norwegian authorities conducted a strategic environment assessment in 2012 to select offshore wind farm sites, discovered 15 potential sites, and finally decided on two designated sites in 2020. Based on various survey data such as seabirds, marine environment, and fishing activities, scientific-based spatial analysis was conducted to select additional offshore wind farm sites in line with future development plans. In addition, a government-led steering committee and advisory group have established marine spatial plans since 2002. Therefore, it will be possible to listen to and coordinate the opinions of stakeholders by using the steering committee and advisory group for offshore wind power development. By examining the case of Norway, we suggest the following policy points that can achieve carbon neutrality and develop sustainable offshore wind farms: 1. Establish a government-led steering committee and advisory group that can select potential sites for offshore wind farms by coordinating the opinions of stakeholders 2. Induce efficient and sequential offshore wind farm development by using various survey data and scientific-based spatial analysis.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.439-442
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• 2009

As a result of increasing environmental concern, the penetration of renewable power on power systems is now increasing. Wind energy can be considered as the most economical energy sources to generate electricity without depletion of fossil fuel. The penetration of wind energy from wind farm is getting larger and larger, so we need adequate control strategies for wind farm. To devise adequate control strategies for wind farm, time domain simulation analysis needs to be performed. This presents a Simultaneous Implicit-based time domain simulation algorithm for wind farm with DFAG (Doubly Fed Asynchronous generator) connected to the external power systems. This paper shows an illustrative example with a 5-bus test system.

• Journal of the Korean earth science society
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• v.34 no.7
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• pp.633-644
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• 2013

This study evaluates wind farm efficiency at Haengwon in Jeju Island. The actual energy production at Haengwon wind farm is compared with the estimated energy production based on Korean wind map which is developed at the National Institute of Meteorological Research/KMA. The validation of wind map at Gujwa located near the Haengwon wind farm shows that the wind speed is overestimated. The diurnal variation of wind speed shows a maximum value in the afternoon due to the effect of sea-land breeze. The ratio of the actual energy production at Haengwon wind farm and the estimated energy production based on the Korean wind map is 24.8%, while the distribution of energy frequency is similar each other. The difference of energy production is caused by mechanical error of the turbine and the overestimation of the simulated wind map. This study will contribute to the repowering of turbines for improving the efficiency of wind farm in the future.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.22-28
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• 2014

This paper proposes the fuzzy modeling and robust stability analysis of wind farm based on prediction model for wind speed. Owing to the sensitivity of wind speed, it is necessary to study the dynamic equation of the variable speed wind turbine. In this paper, based on the least-square method, the wind speed prediction model which is varied by the surrounding environment is proposed so that it is possible to evaluate the practicability of our model. And, we propose the composition of intelligent wind farm and use the fuzzy model which is suitable for the design of fuzzy controller. Finally, simulation results for wind farm which is modeled mathematically are demonstrated to visualize the feasibility of the proposed method.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.13-24
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• 2017

Finding promising wind farm sites in islands of Korea is performed in this study. Total ten islands that have been measuring wind speed and direction using automatic weather stations for at least ten years were subjects of this study. Conditions for finding suitable wind farm sites including wind resource and various exclusion factors were applied and two islands that were found not to be suitable for wind farms were excluded. Micositing of a single wind turbine for the remaining eight islands was performed to estimate the annual energy production and the capacity factor.. Based on the simulation results, the wind farm sites selected within the eight islands were found to be suitable for wind power. The capacity factors were varied between 22.3% and 33.0% for a 100 kW wind turbine having a hub height of 30 m.

• 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.