Wake effects commonly exist in offshore wind farms, which will cause a 10–20% reduction of whole power production as well as a 5–15% increase of fatigue loading on the wind turbine main structures. Obviously wake interaction between floating offshore wind turbine (FOWT) is more complicated, and needs careful assessment which is a prerequisite for active wake control (AWC). The primary objective of the present research is to investigate in detail how the wake inflow condition, streamwise spacing, turbulence intensity, and wind shear influence the power performance, platform motion dynamic and structural loading of FOWT. FAST.Farm, developed by the National Renewable Energy Laboratory (NREL), was used for simulating two tandem FOWTs in different conditions. Comparisons were made between FOWTs in different conditions on power performance and platform motion dynamic, which were presented through both time and frequency domain analysis. Damage equivalent loads change in FOWTs interference under typical working conditions were discussed and summarized. Half wake inflow would pose many challenges to the downstream FOWT. These research studies can be incorporated into further offshore wind farm wake models, providing applicable AWC strategies to reduce wake interference effects for higher energy production and for the longer life of FOWT.

Synthesis of uniform and dense metal nanostructures on the whole exposed fiber, instead of simply on the membrane surface, is necessary for controllable separation and sensitive SERS detection. Herein, uniform and dense AuNP/MoS₂ hybrids were synthesized on single 3D glass fiber (GF) surfaces, obtained by the reaction of a MoS₂ nanosheet and HAuCl₄. The chemical mechanism (CM) of the MoS₂ layers and the electromagnetic enhancement (EM) of the dense AuNPs were used to enhance the SERS sensitivity. The molecule-separation ability of the obtained GF membranes, constructed by numerous compacted fibers with dense AuNP/MoS₂ hybrids, was not destroyed, and herein, these membranes were used to separate mixed molecules. These MoS₂-based hybrid substrates show great potential for excellent paper-based separation and are sensitive SERS substrates for biological and chemical detection.

The wake management of offshore wind farms (OWFs) mainly considers the wake effect. Wake effects commonly occur in offshore wind farms, which cause a 5–10% reduction in power production. Although there have been many studies on wake management, many methods are not accurate enough; for instance, look-up table and static wake model control methods do not consider the time-varying wake state. Dynamic wake management is based on the real-time dynamic wake, so it can increase the energy of the OWFs effectively. For OWFs, dynamic wake control is the main method of dynamic wake management. In this paper, the existing wake model and control progress are discussed, mainly emphasizing the dynamic wake model and the dynamic wake control method, solving the gap of the review for dynamic wake management. This paper presents a digital twins (DT) framework for power and fatigue damage for the first time.. The structure of this paper is as follows: (1) the mechanism of wind farm wake interference is described and then the dynamic wake model is reviewed and summarized; (2) different control methods are analyzed and the dynamic wake management strategies for different control methods are reviewed; (3) in order to solve the problems of dynamic wake detection and real-time effective control, the technology of DT is applied to the dynamic wake control of OWFs. This new DT frame has a promising application prospect in improving power and reducing fatigue damage.

For the first time, the Weather Research and Forecast (WRF) model with the Wind Farm Parameterization (WFP) modeling method is utilized for a short-range wind power forecast simulation of 48 h of an offshore wind farm with 100 turbines located on the east coast of the China Yellow Sea. The effects of the horizontal multi-grid downsize method were deployed and investigated on this simulation computation. The simulation was validated with the field data from the Supervisory Control and Data Acquisition (SCADA) system, and the results showed that the horizontal mesh downsize method improved the accuracy of wind speed and then wind power forecast. Meanwhile, the wind power plant aerodynamics with turbine wake and sea–land shore effects were investigated, where the wake effects from the wind farm prolonged several miles downstream, evaluated at two wind speeds of 7 m/s and 10 m/s instances captured from the 48 h of simulation. At the same time, it was interesting to find some sea–land atmospheric effects with wind speed oscillation, especially at the higher wind speed condition. Finally, the research results show that the WRF + WFP model for the wind power forecast for production operation may not be ready at this stage; however, they show that the methodology helps to evaluate the wind power plant aerodynamics with wake effects and micrometeorology of the sea–land interconnection region. This plant aerodynamics study set the stage for a wake turbine interaction study in the future, such as one utilizing the NREL FAST.FARM tool.