This overview evaluates the energy prediction bias in the wind resource assessment process, and the overprediction bias is decreasing over time. We examine the estimated and observed losses and uncertainties in energy production from the literature, according to the proposed framework in the International Electrotechnical Commission 61400-15 standard. The considerable uncertainties calls for further improvements on the prediction methodologies and more observations for validation.

A previously published wind sensing method is applied to an experimental dataset obtained on a 3.5 MW turbine and a nearby hub-tall met-mast. The method uses blade load harmonics to estimate rotor-equivalent shears and wind directions at the rotor disk. Results indicate a good quality of the estimated shear, both in terms of 10-min averages and of resolved time histories, and a reasonable accuracy in the estimation of the yaw misalignment.

In this paper a 3-dimensional steady-state solver for flow through a wind farm is developed and validated. The computational cost of the solver is on the order of seconds for large wind farms. The model is validated using high-fidelity simulations and SCADA.

This paper describes the design and field testing of a controller for reducing wake interactions on a wind farm. Reducing the power of some turbines weakens their wakes, allowing other turbines to produce more power, so that the total wind farm power may increase. There have been doubts that this is feasible, but these field tests on a full-scale wind farm have demonstrated that this goal has been achieved, also providing convincing validation of the model used for designing the controller.