A method for operating a wind farm having a plurality of wind turbines, each of which is assigned a minimum power limit (CMPLj), wherein a power setpoint value (SPP) for a power which is to be fed in is specified for the wind farm, in dependence on which power setpoint value (SPP), individual wind turbines are activated or shut down, wherein the activation or shut-down of one or more wind turbines in the wind farm takes place in dependence on the respectively assigned minimum power limits (CMPLj), wherein each wind turbine of the wind farm is assigned a current value for its minimum power limit, and wherein the value takes into account variable operating conditions and/or ambient conditions of the respective wind turbine.

Enabling control of wind turbines is provided. The method comprises receiving power production signals from wind turbines comprising a wind farm and estimating wake travel times from upstream wind turbines to downstream turbines. Correlations of the power production signals are calculated among all pairs of wind turbines in the wind farm. Wind turbines with a power production correlation above a specified threshold at an expected time are considered to have wake interaction. A probability density function of northing directions is calculated for the wind turbine pairs with wake interaction. A determination is made whether the probability density function has a dominant direction. Responsive to the probability density function having a dominant direction, the wind turbine pairs with wake interaction are identified as turbine clusters. A control strategy is applied to each turbine cluster as an operational unit to optimize power production of the wind farm.

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.

An aquifer storage and recovery system can include a pump, an electric motor coupled to the pump, a drive unit configured to control operation of the electric motor, and a controller. The controller can be configured to flow water into a well bore from a source reservoir through the pump such that the pump rotates in a reverse direction and drives the electric motor coupled to the pump in the reverse direction to operate as a generator, determine a power output of the electric motor, determine a difference between the power output of the electric motor and a power output set point, and operate the drive unit to control a rotational speed of the electric motor based at least in part on the difference between the power output of the electric motor and the power output set point.

The present invention relates to non-thermal renewable energy turbines (20,24,34, 38,40), in particular to the monitoring of turbine performance to identify a loss of performance indicative of faults or component degradation. The method involves comparison of measured power from a target turbine (20) with a predicted value for same turbine. The predicted value is calculated using the output from a plurality of other turbines (24,34,38,40) from an array and a predictive model including weightings for the other turbines (24, 34,38,40) based on the strength of correlation of their historical with historical data from the target turbine (20).

The present disclosure relates to a method of operating a wind turbine, a corresponding wind turbine, a method of controlling a wind farm and a corresponding wind farm. The method comprises the steps of: determining a target maximum active power to be fed by the wind turbine into a power grid, in particular into an electricity power grid; monitoring a current active power fed from the wind turbine into the power grid; determining a reference time period corresponding to the determined target maximum active power; deriving an average of the active power fed from the wind turbine into the power grid during the reference time period; comparing the average of the active power with the target maximum active power; and operating the wind turbine at a set operating point permitting active power above the target maximum active power in case the average of the active power is below the target maximum active power.

Method for controlling a rotor speed of a rotor of a wind turbine at rated or curtailed operation conditions the rotor being an aerodynamic rotor having one or a plurality of rotor blades, and the wind turbine further having a tower and a generator wherein a pitch control provides a pitch angle set value depending on an actual rotor speed for setting a pitch angle of the rotor blades, a main control provides a main power or torque set value for controlling the power or torque of the generator, and an additional control provides an additional power or torque set value depending on the actual rotor speed , wherein the additional power or torque set value is provided as an offset value and is added to the main power or torque set value respectively, wherein the additional power or torque set value is calculated depending on a control deviation of the rotor speed, and optionally, in combination with the additional control, or instead of it, a maximum power control provides a maximum power value as a varying value for limiting an output power of the generator and the maximum power value is calculated depending on a predetermined power limit value, and depending on a predetermined reference duration, in order to provide for the reference duration an average power reaching or at least not exceeding the predetermined power limit value.

Regulating a power ramp rate of a wind park at a point of common coupling (PCC) between the wind park and a utility grid. The method comprises receiving a power reference for the wind park; determining the power ramp rate of the wind park as a function of the power output of each individual wind turbine in the park, wherein the power ramp rate of the wind park is based on the power ramp rates of the individual wind turbines and determining a corresponding plurality of power set-points for each wind turbine based on the power ramp rates and power reference. The corresponding plurality of power set-points is dispatched to the plurality of wind turbines for regulating the power ramp rate of the wind park in dependency of the power ramp rates of the plurality of wind turbines.

A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller implements a first model to determine a modeled performance parameter for the first wind turbine. The modeled performance parameter is based, at least in part, on an operation of a designated grouping of wind turbines of the plurality of wind turbines, which is exclusive of the first wind turbine. The controller then determines a performance parameter differential for the first wind turbine at multiple sampling intervals. The performance parameter differential is indicative of a difference between the modeled performance parameter and a monitored performance parameter for the first wind turbine. A second model is implemented to determine a predicted performance parameter of the first wind turbine at each of a plurality of setpoint combinations based, at least in part, on the performance parameter differential the first wind turbine. A setpoint combination is then selected based on the predicted performance parameter and an operating state of the first wind turbine is changed based on the setpoint combination.

A wind turbine generator fault detection method is described. The method includes obtaining a first signal from a generator of a wind turbine and a second signal from a vibration sensor coupled to the wind turbine, the first signal representing an output current of the generator, and the second signal being a time-sampled signal representing vibrations of a bearing in the wind turbine. Determining a shaft rotation frequency signal from the first signal, the shaft rotation frequency signal representing a time-varying rotational speed of a shaft of the wind turbine. Resampling an envelope of the second signal based on the shaft rotation frequency signal to provide a third signal, the third signal being an angular sampled signal. Detecting, by the at least one processor, a fault in the bearing of the wind turbine by identifying a characteristic signature of a bearing fault in the third signal.