In response to the global transition towards carbon neutrality, there's an increasing emphasis on sustainable energy solutions, with offshore wind power playing a crucial role, especially in South Korea. This study presents an AI-based safety management system specifically designed for offshore wind operators. At the heart of this system is a machine learning algorithm that processes sensor data to automatically recognize human behavior and improve the accuracy of predicting worker actions and conditions. Such predictive analytics not only refines the analysis of behavioral patterns, but also increases the effectiveness of accident prevention. The results of this research are expected to significantly improve safety measures in offshore wind facilities and further sustainable energy initiatives.

Offshore wind power development has been promoted in countries around the world to cope with global warming. Despite its many advantages, offshore wind power affects the marine environment during construction and operation. As a result, the reduction of fishing areas, changes in the habitat of marine animals, damage to fishing gear, and impeding the safety of fishing activities are occurring. If the offshore wind power generation project is carried out, a fishing damage investigation is nescssary. There are only four fishing damage investigations related to offshore wind power, which are being conducted similarly to the existing fishing damage investigation related to offshore construction. Therefore, this study reviewed and analyzed the report on fisheries damage investigation related to offshore wind power conducted in Korea and suggested problems and improvement measures accordingly.

This study is to propose ways to improve the system for rational procedures for offshore wind power generation projects. The results of this study are summarized as follows. In order to quickly distribute and develop offshore wind power projects, the permitting period should be shortened through special laws, the government actively intervenes to support the formation and operation of privat-public councils to ensure residents' acceptance. In this way, it can be competitive in the future energy market. Above all, a special law (proposal) related to offshore wind power currently pending in the National Assembly should be passed as soon as possible. Finally, the government and local governments that manage public waters should provide active administrative support based on system improvement measures in consideration of these permits, and the project’s main body should minimize damage to the marine environment and ecosystem. Through these subject-specific roles, offshore wind power generation will be able to reduce carbon emissions and help establish a sustainable energy production system.

고리 원자력발전소 1호기 폐쇄 후 잉여 계통접속 용량을 활용한 해상풍력단지를 개발함에 있어서, 본 논문은 해안 단기간 라이다 측정자료를 이용한 해상 풍력자원평가 방법을 제시하였다. 이를 위해 전산유체역학을 이용한 복잡지형에서의 라이다 측정오차 보정, 제3세대 재해석자료를 이용한 장기간 보정, 그리고 후류모델에 따른 발전량 예측오차를 분석하였다. 해안 평탄지형에서 라이다 측정이 수행되었기 때문에 복잡지형 보정오차는 풍속 MAE로 0.03m/s에 불과하였으나 최종 연간에너지생산량은 미보정시에 비해 10% 의 차이가 발생하였다. 특히 장기간 보정과 해안 기상자료를 해상 기상자료로 전달하는 과정의 불확도가 큰 것으로 평가되었다. 풍력 터빈 이격거리가 충분할 경우 기존 육상풍력용 후류모델은 후류손실이 없다고 예측한 반면 심층배열 후류모델은 6%의 후류손실을 예 측하였다. 정리하자면 해상풍력사업의 불확도 최소화를 위해서는 해상기상탑을 설치하고 장기간 측정을 수행하는 것이 필수적임을 재확인하였다.

An FRP(fiber reinforced polymer)-concrete hybrid hollow offshore wind power tower was proposed. To design this new-type wind tower, a design program was developed. It can design optimized sections automatically with the consideration of material nonlinearities. When the outer diameter and requested capacities of the hybrid tower are given, the developed program performs axial force-bending moment interaction analyses for one thousand sections of the tower and suggests ten economically optimized designs. The analysis considers material nonlinearities of concrete and FRP, and the confining effect of concrete. By using the developed program, example design processes were performed for a 5.0MW turbine and a 3.6MW turbine. The designing process was performed for the loads of wind power turbine and wind load. The designed section and analysis results showed the developed program suggested rational and satisfactory section designs.

The transition piece of the offshore wind power support structure transmits the load of the tower stably to the support structure on the lower side. The transition piece of the offshore wind power support structure should solve the stress concentration problem in design. In this paper, in order to solve the stress concentration problem occurring at the transition piece of the offshore wind power support structure, the location and the mitigation of the stress concentration have been studied.

In this study, the effect of electromagnetic wave from an electronic device on electric sensor system and optic sensor were analyzed to verify the reduction effect of a optic sensor and applicability to marin structure. Test revealed that optic sensor system was not occurred the noise by electromagnetic waves also had the low range of fluctuation.

In this study, the effect of electromagnetic wave from an electronic device on electric sensor system and optic sensor were analyzed to verify the reduction effect of a optic sensor and applicability to marin structure. Test revealed that optic sensor system was not occurred the noise by electromagnetic waves also had the low range of fluctuation.

In This Study, it was intended to performance of the joint grout for offshore wind power substructure. The flow, setting time, compressive strength, flexural strength, tensile strength of basic property and resistance to rapid freezing and thawing, ability to resist chloride ion penetration were carried out as the performance test. Also, on the grout by adding fiber checked flexural toughness, cracking tendency test.

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.

A long-term wind resource map was made to provide the key design data for the 2.5 GW Korean West-South Offshore Wind Project, and its reliability was validated. A one-way dynamic downscaling of the MERRA reanalysis meteorological data of the Yeongwang-Gochang offshore was carried out using WindSim, a Computational Fluid Dynamics based wind resource mapping software, to establish a 33-year time series wind resource map of 100 m x 100 m spatial resolution and 1-hour interval temporal resolution from 1979 to 2012. The simulated wind resource map was validated by comparison with wind measurement data from the HeMOSU offshore meteorological tower, the Wangdeungdo Island meteorological tower, and the Gochang transmission tower on the nearby coastline, and the uncertainty due to long-term variability was analyzed. The long-term variability of the wind power was investigated in inter-annual, monthly, and daily units while the short-term variability was examined as the pattern of the coefficient of variation in hourly units. The results showed that the inter-annual variability had a maximum wind index variance of 22.3% while the short-term variability, i.e., the annual standard deviation of the hourly average wind power, was 0.041±0.001, indicating steady variability.