Adding more renewable energy into the electric grid is a critical part of the strategy to increase energy availability. Reliable numerical weather prediction (NWP) models need to be able to predict the intrinsic nature of weather-dependent resources such as wind ramp events, as wind energy could quickly be available in abundance or temporarily cease to exist. We assess the ability of the operational High Resolution Rapid Refresh NWP model to forecast wind ramp events in the two most recent versions.

This study is an experimental exploration of the wake of the novel X-Rotor vertical-axis wind turbine. Passive blade pitch is used to favorably modify the wake topology and subsequent energy replenishment process. The results demonstrate significant increases in available power for downstream rotors and the underlying mechanisms, highlighting the potential of vertical-axis wind turbines and passive blade pitch control for high-energy-density wind farm applications.

This study demonstrates how kites used to generate wind energy can act as sensors to measure wind conditions and system behaviour. By combining data from existing sensors, such as those measuring position, speed, and forces on the tether, a sensor fusion technique accurately estimates wind conditions and kite performance. This approach can be integrated into control systems to help optimize energy generation and enhance the reliability of these systems under changing wind conditions.

Scour depths at nine British offshore wind farms (OWFs) were analysed. Site-specific scour drivers were identified, including the relative water depth, relative median grain size, Keulegan–Carpenter number, and sediment mobility. These findings improve our understanding of scour behaviour at different scales and lay the groundwork for enhancing scour prediction frameworks at future offshore wind farms, thereby supporting the expansion of sustainable energy.

It is crucial to understand the loads and power production of wind turbines under different atmospheric situations (e.g., night and day changes). Computational simulations are a widely used tool to get more knowledge of the performance and the wake of wind turbines. In this study realistic velocity profiles of the atmosphere are used as input for simulations so that these simulations become more realistic. The generated flow is used as inflow for wind turbine simulations.

With increasing wind energy in the German energy grid, it is crucial to better understand how different types of weather (including thunderstorms) can impact wind turbines and the surrounding atmosphere. We find rapid wind changes associated with the leading edge of thunderstorm outflows within the height range of wind turbines that would quickly increase wind power output, with longer-lasting changes in the near-surface atmosphere that would affect subsequent wind turbine operations.

Wake effects cause power losses that degrade wind farm efficiency. This paper presents a wind tunnel investigation of dynamic induction control (DIC), a strategy to mitigate wake losses by improving turbine–flow interactions. WindScanner lidar measurements are used to explore the wake development of model turbines in response to DIC. Our results demonstrate consistent benefits and adaptability under realistic inflow conditions, highlighting DIC’s potential to increase wind farm power production.

Airborne wind energy (AWE) systems use tethered aircraft to harness high-altitude winds, offering a cost-effective alternative to wind turbines. This study develops and tests an emulator that replicates AWE power generation, optimizing energy conversion with advanced control techniques. Our results improve system efficiency and reliability, supporting AWE's commercialization as a scalable, sustainable energy source with lower infrastructure demands.

This study improves the analysis of curved wind turbine blades, such as those with sweep or prebend. Existing methods often blend different effects on blade performance, making design optimization challenging. We developed a framework that disentangles these effects, providing clearer insights. Our findings show that the aerodynamic influences of sweep and prebend can be modeled separately and combined, simplifying modeling processes and supporting more efficient blade design.

Distributed wind (DW) faces a growing demand for skilled workers, but hiring challenges persist, and workforce development efforts lag behind other wind sectors. This project uses an equity-driven rubric and spatial mapping to identify institutions in disadvantaged areas with strong potential for wind energy training partnerships. The results highlight the rubric as a strategic tool for identifying DW workforce collaborators.

We explore how simple terrain influences spatial variations in wind speed and wind farm performance during a low-level jet. Using simulations, field observations, and turbine production data, we find that downstream turbines produce more power than upstream ones, despite being subjected to wake effects. This counterintuitive result arises because the low-level jet and winds near turbine rotors are highly sensitive to topographic features, leading to stronger winds at the downstream turbines.

For wind energy in the Arctic, a better understanding of wind characteristics is necessary. Observations from a valley in Svalbard show that local, thermally driven valley winds are frequent. They increase the average wind speed and reduce the wind variability in this valley, which is not reproduced well by common numerical model products. The wind characteristics are advantageous for wind power in valleys.