Offshore meteorological characteristics set specific conditions for the operation of offshore wind farms. One specific feature is low turbulence intensity which on the one hand reduces loads on turbines but on the other hand is the reason for much longer turbine and farm wakes than over land. The German Government is presently funding a research project called WIPAFF (Wind PArk Far Field) which heads for the analysis of properties and impacts of offshore wind park far fields. The focus is on the analysis of wind farm wakes, their interaction among each other and their regional climate impact. This is done by in-situ, extensive aircraft and satellite measurements and by operating meso-scale wind field models and an analytical wind farm model.
Large offshore wind farms are usually clustered around transmission grids to minimize the expense of transmission and due to space military zones, pipelines and constrains due to other uses such as nature preserves. However, this close proximity can undermine power production in downwind wind farms due to wakes from upwind wind farms. Therefore, the wind energy industry has great interest in determining the spatial dimensions of offshore wind farm wakes to assess the economical potential of planned wind farms. In this work we use wake measurements conducted by a research aircraft to evaluate the performance of a wind farm parameterization (WFP) in a mesoscale model during stably-stratified atmospheric conditions, in which the wake is expected to be the strongest. The observations were conducted on the 10 September 2016 within the project WIPAFF (Wind PArk Far Field) at the North Sea. The observations allow evaluation of both the horizontal and the vertical dimensions of the wake. The model simulates the length and most of the time the spatial dimensions of the wake. Further, we show that the largest potential for improving the performance of the WFP is rooted in an improvement of the background flow. This is due to the fact that the mesoscale model has problems representing the atmospheric boundary layer in the transition between land to open sea.
The Coastal Observing System for Northern and Arctic Seas (COSYNA) was established in order to better understand the complex interdisciplinary processes of northern seas and the Arctic coasts in a changing environment. Particular focus is given to the German Bight in the North Sea as a prime example of a heavily used coastal area, and Svalbard as an example of an Arctic coast that is under strong pressure due to global change. The COSYNA automated observing and modelling system is designed to monitor real-time conditions and provide short-term forecasts, data, and data products to help assess the impact of anthropogenically induced change. Observations are carried out by combining satellite and radar remote sensing with various in situ platforms. Novel sensors, instruments, and algorithms are developed to further improve the understanding of the interdisciplinary interactions between physics, biogeochemistry, and the ecology of coastal seas. New modelling and data assimilation techniques are used to integrate observations and models in a quasi-operational system providing descriptions and forecasts of key hydrographic variables. Data and data products are publicly available free of charge and in real time. They are used by multiple interest groups in science, agencies, politics, industry, and the public.
