The invention relates to a method for controlling a yaw offset of a plurality of wind turbines. The method uses a decision function which generates an activation parameter for determining if the yaw offset control of a specific wind turbine should be enabled or disabled. The decision function depends on two or more variables comprising a wind direction variable indicative of the wind direction of the specific wind turbine, and a wind variation variable defining at least a wind variation range where yaw offset control is disabled or enabled. Based on the decision function it is determined if a yaw offset should be added to the current yaw setting of the specific wind turbine.

The present disclosure is directed to a system and method for determining wake losses of a wind farm. The wind farm includes a plurality of wind turbines. The method includes operating the wind farm in a first operational mode. Another step includes collecting turbine-level data from at least one upstream wind turbines in the wind farm during the first operational mode. The method also includes estimating a freestream farm-level power output for the wind farm during first operational mode based, at least in part, on the collected turbine-level data. A further step includes measuring an actual farm-level power output for the wind farm for the first operational mode. Thus, the method also includes determining the wake losses of the wind farm for the first operational mode as a function of the measured actual farm-level power output and the estimated freestream farm-level power output.

Provided is a wind park, a wind park controller, and a method for controlling a first wind turbine of a plurality of wind turbines of a wind park, wherein a second wind turbine of the plurality of wind turbines can be affected by a wake region caused by the first wind turbine which is positioned upstream of the second wind turbine. A current yaw state is determined and is selected from at least one of: a) an actual rotor yaw misalignment angle of the first wind turbine, wherein the actual rotor yaw misalignment angle is an angle between a rotating axis of a rotor of the first wind turbine and a current wind direction at the rotating axis upstream of the first wind turbine, b) an identifier representing whether the actual rotor yaw misalignment angle is either in a range of positive yaw misalignment angles or of negative yaw misalignment angles.

Disclosed is a wind turbine layout optimization method combining with a dispatching strategy for the wind farm. In the wind farm micro-siting stage, the installed wind turbines number and the arrangement positions are optimized. In this method, the dispatching strategy of wind turbines is considered during the layout optimization of wind turbines, and the axial induction factor of each wind turbine is introduced into the layout optimization variables. The dispatching strategy of maximizing the wind farm power generation is combined with the layout optimization of wind turbines in the construction stage of the wind farm, so that the wake effect is effectively reduced and the capacity cost is reduced, which meet the requirement of actual wind farm. A hybrid optimization algorithm is proposed in this method, with a greedy algorithm to optimize the turbine number and a particle swarm optimization (PSO) algorithm to refine the turbine layout scheme.

The present invention relates to a method of operating a wind farm comprising an upstream and a downstream turbine, wherein the upstream turbine is operated with current operation parameters under current wind conditions, wherein the method comprises the steps of: receiving future wind conditions for a time period for the wind farm, and evaluating required operation parameters for minimising wake effect of the downstream turbine under the future wind conditions, and determining a cost coefficient for changing the operation parameters to required operation parameters under consideration of fatigue effect of the wind turbine, calculating power productions P.sub.o and P.sub.c, in the predetermined time period, by the wind farm if operated with the current operation parameters under the current wind conditions and if operated with the required operation parameters under the future wind conditions, respectively, and operating the upstream turbine with the required operation parameters if the cost coefficient is lower than a cost that would be obtained by a power production increment P.sub.c-P.sub.o.

A wind turbine having a wake control system that is configured so as to control the wind turbine on the basis of wake effects caused at a further wind turbine, wherein the wake control system is configured so as to achieve control based on a turbulence measured value from a turbulence measurement sensor of the further wind turbine. A wind turbine having a turbulence measurement sensor that is configured so as to determine a turbulence measured value, wherein the turbulence measured value is indicative of a turbulence and/or wind shear at the wind turbine, wherein the wind turbine is configured so as to provide the turbulence measured value in order to control the wind turbine and/or a further wind turbine. A wake control system for a wind turbine, but also an improved wind farm and an improved method for controlling a wind turbine and a wind farm.

Methods, systems, and devices for controlling a yaw offset of an upstream wind turbine based on reinforcement learning are provided. The method includes receiving data indicative of a current state of the first wind turbine and of a current state of a second wind turbine adjacent to the first wind turbine downstream along a wind direction, determining one or more controlling actions associated with the yaw offset of the first wind turbine based on the current state of the first wind turbine, the current state of the second wind turbine, and a reinforcement learning algorithm, and applying the determined one or more controlling actions to the first wind turbine.

Method of operating a wind farm comprising a plurality of wind turbines, each of the turbines having a plurality of blades, the method comprising determining a possible wake situation at a first wind turbine caused by a second wind turbine, the second wind turbine being located upstream of the first wind turbine, and individually adapting the blades of the second wind turbine such that a wake generated by the second wind turbine is deflected away from the first wind turbine.

A method for operating a first wind power installation comprising a rotor having a rotor blade that is adjustable with a pitch angle, which generates an electrical power and in the wake of which a second wind power installation is located in at least one wake wind direction, comprising the step of: operating the first wind power installation in a substantially wake-free normal mode with a first pitch characteristic, and operating the first wind power installation in a wake-loaded wake mode with a second pitch characteristic, wherein the first pitch characteristic represents a first profile of the pitch angle and the second pitch characteristic represents a second profile of the pitch angle as a function of the electrical power, wherein the pitch angle of the second pitch characteristic is greater than the pitch angle of the first pitch characteristic for at least one range of the electrical power. The method seeks to maximise the annual energy production of the second wind power installation while complying with constraints, such as compliance with maximum thrust coefficients or wake-influenced turbulence intensities.

Systems and methods coordinate drone flights in an operating windfarm. A drone flight path that is removed from any location where the drone is conducting observations of a wind turbine and that extends through at least part of a windfarm to a destination location is determined. A respective wake pattern along at least one portion of the drone fight path is determined based on respective operating parameters for each of at least one wind turbine in the windfarm. Flight time commands to adjust at least one respective operating parameter of the respective wind turbine to reduce the effect of the respective wake pattern at a point ahead of the drone on the drone flight path are sent by a windfarm controller controlling the at least one wind turbine.