Accurate modeling of wind conditions is vital for the efficient operation and management of wind farms. This study investigates the enhancement of weather simulations by assimilating local offshore light detection and ranging (lidar) and/or supervisory control and data acquisition (SCADA) data into a numerical weather prediction model while considering the presence of neighboring wind farms through wind farm parameterization. We focus on improving model output during storms impacting the Belgian–Dutch wind farm cluster located in the Southern Bight of the North Sea via the four-dimensional data assimilation (nudging) technique in the Weather Research and Forecasting (WRF) model. Our findings indicate that assimilating wind observations significantly reduces the relative root-mean-square error for wind speed at a wind farm located 47 km downwind from the offshore lidar platform. This leads to more accurate power production outputs. Specifically, at wind turbines experiencing wake effects, the wind speed error decreased from 10.5 % to 5.2 %, and the wind direction error was reduced by a factor of 2.4. A proposed artificial configuration, leveraging the upwind lidar measurements, showcases the potential for improving hour-ahead wind and power predictions. Moreover, we perform a thorough study to investigate the sensitivity to nudging parameters during versatile atmospheric conditions, which helps to identify the best assimilation practices for this offshore setting. These insights are expected to refine wind resource mapping and reanalysis of weather events, as well as motivate more measurement campaigns offshore.@en

Floating Modular Energy Islands (FMEIs) are modularized, interconnected floating structures that function together to produce, store, possibly convert and transport renewable energy. Recent technological advancements in the offshore energy sector indicate that the concept of floating offshore energy islands has the potential to become more cost-effective and more widespread than previously anticipated. This review is specifically meant as a basis for the development of new approaches to the sustainable exploitation of multi-energy sources in the offshore environment leveraging the know-how of existing technologies and, at the same time, exploring new solutions for the specific challenges of FMEIs. The paper critically analyzes the current state of data-driven approaches and structural health monitoring techniques in the offshore energy sector. It also covers topics such as met-ocean data, load estimation, platform dynamics, coupling actions, nonlinear dynamics of mooring lines, modelling considerations, and control of electrical subsystems. It is believed that this systematic and multidisciplinary review will facilitate synergies and further enhance research and development of offshore renewable energies.@en