• NEWSLETTER 전기공업
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• no.98-23 s.216
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• pp.18-30
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• 1998

• NEWSLETTER 전기공업
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• no.98-18 s.211
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• pp.24-40
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• 1998

• 전기산업
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• v.8 no.3
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• pp.90-97
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• 1997

• Proceedings of the Korea Technology Innovation Society Conference
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• 2010.05a
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• pp.15-23
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• 2010

• Electric Engineers Magazine
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• s.335
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• pp.14-15
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• 2010

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1373-1383
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• 2016

The wind energy industry and wind power generation have increased; consequently, the stable supply of the wind power has become an important issue. It is important to accurately predict the wind power with short-term basis in order to make a reliable planning for the power supply and demand of wind power. In this paper, we first analyzed the speed, power and the directions of the wind. The neural network and the time series models (ARMA, ARMAX, ARMA-GARCH, Holt Winters) for wind power generation forecasting were compared based on mean absolute error (MAE). For one to three hour-ahead forecast, ARMA-GARCH model was outperformed, and the neural network method showed a better performance in the six hour-ahead forecast.

• Journal of Digital Convergence
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• v.11 no.2
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• pp.137-148
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• 2013

This paper aims to presents a systematic procedure for the development of construction technology roadmap, which can consider the offshore wind farm on port. Then the weight among the large/medium/small classified construction technology has identified through the AHP(Analytical Hierarchy Process) approach using FGI(Focus Group Interview) and questionnaire study. Based on the priority for classified construction technology a construction technology roadmap for port offshore wind farm was also developed. The technology roadmap suggests the time frame(20 years, from 2016 to 2036) to complete R&D work for the classified construction technology of port offshore wind farm. Such construction technology roadmap can be utilized as a milestone in setting up the R&D strategy in the green port construction industry.

• Journal of Wind Energy
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• v.9 no.4
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• pp.32-39
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• 2018

In this study, the annual power production of a wind farm according to obstacles and wind data was predicted for the Garyeok-do wind farm in the Saemangeum area. The Saemangeum Garyeok-do wind farm was built in December 2014 by the Korea Rural Community Corporation. Currently, two 1.5 MW wind turbines manufactured by Hyundai Heavy Industries are installed and operated. Automatic weather station data from 2015 to 2017 was used as wind data to predict the annual power production of the wind farm for three consecutive years. For prediction, a commercial computational fluid dynamics tool known to be suitable for wind energy prediction in complex terrain was used. Predictions were made for three cases with or without considering obstacles and wind direction errors. The study found that by considering both obstacles and wind direction errors, prediction errors could be substantially reduced. The prediction errors were within 2.5 % or less for all three years.

• 어항어장
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• s.97_98
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• pp.23-28
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• 2012

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.374-382
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• 2021

The scour risk assessment was conducted for ultimate limit state of newly developed penta pod suction bucket support structures for a 5.5 MW offshore wind turbine. The hazard was found by using an empirical formula for scour depth suitable for considering marine environmental conditions such as significant wave height, significant wave period, and current velocity. The scour fragility curve was calculated by using allowable bearing capacity criteria of suction foundation. The scour risk was assessed by combining the scour hazard and the scour fragility.