A computer system suitable for estimating the expected change in annual energy production (AEP) of a wind turbine due to structural deterioration of blades of the wind turbine, said computer system being arranged to execute the following steps: loading a dataset representing estimated lift and drag curves at specific radial locations along the original blade of the wind turbine, building a baseline BEM model of the wind turbine based on said estimated lift and drag curves of the original blade and analysing the model to provide a baseline AEP estimation of the wind turbine with original blades, loading a dataset representing aerodynamic effects of identified structural deteriorations at specific radial locations along each of the blades of the wind turbine, using the dataset of aerodynamic effects to generate modified lift and drag curves at specific radial locations along each of the blades.

A method of operating at least one wind turbine including: receiving a first signal which is indicative of a level of a remuneration for electrical energy, which is fed currently and/or in the future into a grid to which the wind turbine is connected, producing a control signal dependent on the first signal, and controlling the wind turbine with the control signal for generating power of the wind turbine, that is dependent on the control signal. A wind turbine and a central control for carrying out such a method and a system comprising a central control and a plurality of wind turbines.

Methods for assessing the useful life that may remain for a portion of a wind turbine support structure. The methods may include identifying an overall expected useful life for the portion of the support structure and estimating an expended life from the extent of loading that has occurred to the portion of the support structure during the operative life of a wind turbine. The useful life remaining for the portion may be determined by subtracting the expended life from the overall expected useful life.

A wind turbine has a Lidar device to sense wind conditions upstream of the wind turbine. Signals from the wind turbine are processed to detect an extreme change in wind direction. The detection is performed by differentiating the rate of change of wind direction and filtering for a period of time. On detection of extreme change the system controller takes the necessary evasive action which may include shutting down the turbine, commencing an immediate yawing action, and de-rating the turbine until the yawing action is complete.

A method for predicting remaining useful life of a wind or water turbine or component determines in step 116 an EOH for the turbine or component and compares this in step 118 to an EOH limit obtained in step 114. This provides a simple approach to estimating remaining useful life, giving the turbine operator an indication of the condition of turbines or farms under management.

A method for controlling a wind turbine may generally include operating the wind turbine at an initial power output that is greater than a rated power output associated with the wind turbine. The wind turbine may have an anticipated operational life at the rated power output. In addition, the method may include decreasing a power output of the wind turbine over time in order to maintain an actual operating life of the wind turbine substantially equal to or greater than the anticipated operational life. A final power output of the wind turbine at an end of the anticipated operating life may be less than the rated power output.

A method for controlling a wind energy farm is disclosed. A wake state of the wind energy farm is determined, including determining wake chains defining wake relationships among the wind turbines of the wind farm under the current wind conditions. For at least one of the wind turbines of the wind energy farm, a lifetime usage is estimated, based on an accumulated load measure for the wind turbine. In the case that the estimated lifetime usage is below a predefined lifetime usage limit, the wind turbine is operated in an overrated state, while monitoring wake effects at each of the wind turbines. In the case that a downstream wind turbine detects wake effects above a predefined wake threshold level, at least one wind turbine having an upstream wake relationship with the downstream wind turbine is requested to decrease the generated wake, e.g. by decreasing power production.

Provided are a control method and apparatus for load reduction of a wind turbine. The control method for load reduction includes: determining a representative blade root load value of a wind turbine; determining an additional pitch rate value based on the representative blade root load value; determining a pitch rate control value based on a given pitch rate value and the additional pitch rate value: and applying the pitch rate control value to each blade of the wind turbine, to control each blade of the wind turbine to perform a pitch action.

A system and method are provided for reducing vibrations and loads in one or more rotor blades of a wind turbine when the rotor hub is locked against rotation, The method detects that the rotor blades are vibrating above a threshold limit, and determines one or more wind parameters for wind impacting the rotor blades. An initial orientation of the blades is also determined. Based on the wind parameters and initial blade orientation, a first angle of attack for the rotor blades is determined that will reduce the vibrations in the rotor blades. The method then determines if expected loads induced at one or more wind turbine components will exceed a threshold limit at the first angle of attack for the rotor blades. The first angle of attack is modified when the expected loads exceed the threshold limit to reduce the expected loads to below the threshold limit. A controller pitches the rotor blades to achieve the first angle of attack.

Determination of Wind Turbine Configuration The present invention relates to a method and computer system for determining a configuration of a wind turbine of a given wind turbine type, the method comprising the steps of: storing in a database a plurality of combinations of physical and control parameters of the wind turbine that can be varied; determining a plurality of wind flow characteristics at a target location; applying a function which defines a relationship between a performance parameter, a fatigue life estimation, the combination of physical and control parameters and the plurality of wind flow characteristics, to at least some of the plurality of combinations in the database to determine values of the performance parameter and the fatigue life estimation for those combinations; and selecting one of the combinations of physical and control parameters as the configuration of the wind turbine for the target location on the basis of the performance parameter and fatigue life estimation values.