For the German energy transition, offshore wind energy is a significant factor of success. The number of installed offshore wind energy turbines is steadily increasing. Currently, the subject matter of offshore wind energy turbine maintenance and its optimization is increasingly in the focus of research and development work. The present contribution examines the logistics of offshore wind energy turbine maintenance and the impact of the actual sea state and of sea state forecasts. To this end, the coordination processes between the players involved in the planning of service operations will be presented and analysed. Based on this, the impact of the quality of wave height forecasts on operation decisions and the mean time to repair will be determined as well as the availability of the turbines at different forecast quality levels. Proceeding on the basis of these results, the concept of a decision-making support system for operative logistics planning will be presented.

The competition of maintenance services in the offshore wind industry is continually increasing. The quality of the services acts as the distinguishing feature in the industry. Furthermore, there are public standards, which lead to the permanent necessity to offer further education and training programs for employees. To meet the requirements for further training in the specific field of application within the offshore wind industry, a gamified e-learning application has been developed and is introduced in this paper. It consists of a complete solution, which contains the automated analysis of service protocols to identify qualification needs, the involvement of service technicians in the generation of learning materials, the preparation, transmission as well as the further development of those materials in accordance with the principles of e-learning. Finally, the solution contains a gamified mobile application for qualification, which is designed to meet the individual learning needs of the service technicians. This concept paper follows a problem-centred approach. Based on the current state of technology and research, the problem and motivation are identified and the urgency is verified. Furthermore, a detailed specification of the solution and a first implementation approach is presented.

해상풍력발전단지 발전량의 보다 정확한 예측을 위해 발전단지 예정지 인근에서 측정된 풍속데이터가 반드시 필요하다. 풍속데이터 확보를 위해서는 해상기상탑을 설치하는 방법과 인근 해안가나 섬에 풍속계측타워를 설치하는 방법이 있다. 본 연구에서는 인근 섬에서 측정한 풍속데이터와 WAsP 방법을 이용하여 해상풍력발전단지의 발전량을 예측할 경우에 섬의 지형 및 지면조도의 변화에 따른 발전량 예측값의 민감도를 분석하여 섬의 형상의 불확실성이 발전량 예측에 미치는 영향을 정량적으로 파악하였다. 계측타워의 풍속측정 높이가 높아질수록 섬의 지형 모델링 오차가 발전량 예측에 미치는 영향이 작아졌으며, 섬의 지면조도 변화에 따른 발전량 변동은 미미한 것으로 나타났다.

In this research, we carried out design and analysis with joint of concrete supporting structure for offshore wind energy. We developed load transfer mechanism about applied load induced from steel tower to concrete foundation. Also, a commercially available finite element program, ABAQUS 6.10, is used to analyze behavior of structure.

To predict annual energy production (AEP) accurately in the wind farm where located in Seongsan, Jeju Island, Equivalent wind speed (EQ) which can consider vertical wind shear well than Hub height wind speed (HB) is calculated. AEP is produced by CFD model WindSim from National wind resource map. EQ shows a tendency to be underestimated about 2.7% (0.21 m/s) than HB. The difference becomes to be large at nighttime when wind shear is large. EQ can be also affected by atmospheric stability so that is classified by wind shear exponent (). AEP is increased by 11% when atmosphere becomes to be stabilized ( > 0.2) than it is convective ( < 0.1). However, it is found that extreme wind shear ( > 0.3) is hazardous for power generation. This results represent that AEP calculated by EQ can provide improved accuracy to short-term wind power forecast and wind resource assessment.