This paper investigates the treatment of tropical-cyclone-generated waves in metocean models and in statistical evaluation for offshore wind design. It provides recommendations for ensuring the accurate representation of extreme waves for the design and operation of offshore projects on the Atlantic coast of the United States.

Three recent wind resource datasets are assessed for their skills in representing annual average wind speeds and seasonal, diurnal, and interannual trends in the wind resource in coastal locations to support customers interested in small and midsize wind energy.

Our study explores how frontal low-level jets (FLLJs) impact wind power production by causing ramp-down events. Using the Weather Research and Forecasting model, we analyzed various modeling configurations and found that initial and boundary conditions, domain configuration, and wind farm parameterization significantly influence simulations. Our findings show such extreme events can be forecasted 1 d in advance, helping manage wind power more efficiently for a stable, reliable energy supply.

Maritime authorities often impose turbine alignment constraints on developers to secure the navigation of boats within the wind farm, potentially creating substantial wake losses. The proposed contribution is a new wind farm layout optimization (WFLO) algorithm that considers these constraints. The proposed method optimizes the grid-alignment parameters and the turbines' location on this grid. We illustrate the algorithm's performances on a challenging example.

Drivetrain efficiency is a wind turbine’s fundamental behaviour in the energy conversion. To determine the efficiency, input and output powers need to be measured with sufficient accuracy. However, this is a very challenging task due to high complexity and lack of properly calibrated torque measurements. In cooperation with the German and Swiss national metrology institutes, the efficiency determination with state-of-the-art instrumentations is demonstrated here with test processes and results.

Wind turbines organized in wind farms are an important electric power source. Thereby, each wind turbine causes a so-called wake with a reduced wind speed. This can influence wind turbines that follow and is an opportunity to optimize the operation of the complete wind farm; i.e., we steer the wakes to increase the total power output of the wind farm. In order to do this efficiently, we exploit repetitive structures within a wind farm.

Current offshore wind farms have been designed to maximize their production of electricity at all times and not to keep a reserve of power in case of unexpected events on the grid. We present a new formulation for designing wind farms to maximize revenues from both energy and reserve markets. We apply it to a real-life wind farm and show that profits are expected to increase in a significant way for wind farms designed and operated for reserve, with less energy supplied.

This study is the first to use real-world atmospheric measurements to show that large wind plants can increase the height of the planetary boundary layer, the part of the atmosphere near the surface where life takes place. The planetary boundary layer height governs processes like pollutant transport and cloud formation and is a key parameter for modeling the atmosphere. The results of this study provide important insights into interactions between wind plants and their local environment.

The study presents a critical analysis using wind tunnel experiments and large-eddy simulations aimed at quantifying to what extent turbulence affects the wake structures of a floating turbine undergoing large motions. Analyses show that, whenever realistic turbulence comes into play, only small gains in terms of wake recovery are noticed in comparison to bottom-fixed turbines, suggesting the absence of hypothesized superposition effects between inflow and platform motion.