Aspects of the present invention relate to a method for determining annual energy production of a wind farm. The method comprises: receiving a definition of the wind farm; modelling the wind field of the wind farm for a plurality of freestream wind speeds in a plurality of wind directions; defining locations for virtual measurement masts upstream of upstream turbines in each wind direction at a clearance from each upstream turbine for identifying wind farm blockage effects; determining a wind farm blockage factor for each freestream wind speed in each wind direction based on data from the virtual measurement masts; receiving measurements from a physical measurement mast located at the site of the wind farm; and determining an annual energy production for the wind farm based on adjusted wind speeds obtained by applying the blockage factors to measurements from the physical measurement mast.

To solve the problem of a mis-calibration of a wind turbine a computer-implemented method for re-calibrating at least one yaw-angle of a wind turbine starting from an initial yaw-angle calibration of said wind turbine, based on determining a turbulence intensity estimation value (20) related to said appropriate yaw-angle (10), wherein the turbulence intensity (TI) being a ratio of wind speed deviation to average wind speed over a pre-determined period of time. Further, to solve the problem of a mis-calibration of a wind turbine a system for re-calibrating at least one yaw-angle of a wind turbine based on above re-calibration method. Further, to solve the problem of a management of a wind park below optimum a computer-implemented method for wind park optimization based on simulation calculation including turbulence intensity estimation values (20) estimating said at least one effecting wind turbine (101,102,103) to suffer from wake from said at least one effected wind turbine (100,101,102). Further, to solve the problem of a management of a wind park below optimum a wind park, including a management system for optimizing that wind park based on above optimization method. Moreover, present invention relates to a computer-readable medium comprising such methods.

A wind turbine includes tower, a nacelle mounted at the top of the tower, a rotor mounted rotatable relatively to the nacelle about a rotation axis and includes at least one blade, wherein the blade, when rotating about the rotation axis, is configured to span a swept area, and a control device which is configured to control an actuator so as to move the swept area.

Systems and methods of autonomous farm-level control and optimization of wind turbines are provided. Exemplary embodiments comprise a site controller running on a site server. The site controller collects and analyzes yaw control data of a plurality of wind turbines and wind direction data relating to the plurality of wind turbines. The site server determines collective wind direction across an area occupied by the plurality of wind turbines and sends yaw control signals including desired nacelle yaw position instructions to the plurality of wind turbines. The site controller performs wake modeling analysis and determines desired nacelle positions of one or more of the plurality of wind turbines. The desired nacelle yaw position instructions systematically correct static yaw misalignment for all of the plurality of wind turbines. Embodiments of the disclosure provide means to perform whole site or partial site level controls of the yaw controllers of a utility scale wind turbine farm. The overall effect of the coordinated yaw control of wind turbines across the whole or partial site is intended to keep the wake loss of the wind turbines from the upstream wind turbines to the minimum and to maximize the production of turbines that are not waking other turbines.

The present disclosure is directed to a system and method for assessing farm-level performance of a wind farm. The method includes operating the wind farm in a first operational mode and identifying one or more pairs of wind turbines having wake interaction. The method also includes generating a pairwise dataset for the wind turbines pairs. Further, the method includes generating a first wake model based on the pairwise dataset and predicting a first farm-level performance parameter based on the first wake model. The method also includes operating the wind farm in a second operational mode and collecting operational data during the second operational mode. Moreover, the method includes predicting a first farm-level performance parameter for the second operational mode using the first wake model and the operational data from the second operational mode. The method further includes determining a second farm-level performance parameter during the second operational mode. Thus, the method includes determining a difference in the farm-level performance of the wind farm as a function of the first and second farm-level performance parameters.

A system and method for simultaneously coordinating a wake control system and a noise control system of a wind farm having a plurality of wind turbines is disclosed. The method includes determining, via a farm controller, one or more wake control set points for the wake control system. Further, the method includes determining, via the farm controller, one or more noise control set points for the noise control system. The method also includes selecting, via the farm controller, between the wake control set points and the noise control set points for each of the plurality of wind turbines. Thus, the method also includes sending, via the farm controller, the selected control set points to local controllers of the plurality of wind turbines and operating the wind farm based on the selected control set points.

Embodiments of the present invention provide methods and apparatus for increasing turbulent mixing in the wake of at least one wind turbine. Doing so, increases efficiency of a wind turbine located in the wake by transferring energy to the wake that was lost when the wind passed through the upwind turbine. Turbulent mixing may be increased by changing the induction factor for a rotor by, for example, altering the pitch of the blades, the RPMs of the rotor, or the yaw of the nacelle. These techniques may be static or dynamically changing. Further, the different induction factors for a plurality of wind turbines may be synchronized according to a predetermined pattern to further increase turbulent mixing.

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.

A method of controlling a plurality of wind turbines of a wind park includes: determining an axial induction zone of at least a wind turbine of the wind park; and modifying the axial induction zone for controlling wind farm blockage by adjusting at least one of the following operational variables: a yaw angle of a blade rotor of the wind turbine, a pitch offset angle of at least one blade of the blade rotor, a rotor speed of the blade rotor.

A control arrangement for a variable-speed wind turbine includes a loading analysis module configured to analyse a number of environment values to establish whether the momentary wind turbine loading is lower than a loading threshold when the rotational speed of the aerodynamic rotor has reached its rated value; and a speed boost module configured to determine a speed increment for the rotational speed of the aerodynamic rotor if the wind turbine loading is lower than the loading threshold.