Abstract: A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller prepares a yaw bias correction function based, at least in part, on a yaw offset function, and on wind speed measurement data and wind direction reference data of a wind event acting on at least a portion of the wind farm. The controller also applies the yaw bias correction function based at least in part on position data of a nacelle of the wind turbine, to yaw the nacelle of the wind turbine.

Abstract: 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.

Abstract: A system and method are provided for operating a wind farm. Accordingly, a wind direction affecting the wind farm is determined. Based on the wind direction, a controller identifies a turbine cluster, which is a subset of a plurality of wind turbines of the wind farm. The subset includes at least an upwind turbine and a downwind turbine that is affected by a wake emanating from the upwind turbine. With the turbine cluster identified for the given wind direction, the controller then determines a difference between a freestream maximal cluster power output and a wake-affected cluster power output for the turbine cluster. The controller then determines a mitigation setpoint combination for the subset of wind turbines. The mitigation setpoint combination is configured to establish a mitigated cluster power output.

Abstract: 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.

Abstract: A system and method are provided for controlling a wind turbine based on a collective pitch-offset. Accordingly, a wind condition acting on a rotor of the wind turbine is determined, and a first collective pitch angle for the plurality of rotor blades is set, and the wind turbine is operated. A thrust of the rotor based, at least in part, on the wind condition is determined, and an actual collective pitch angle is calculated. A collective pitch offset is determined based on the difference between the first collective pitch angle and the actual collective pitch angle. The collective pitch offset is integrated with at least one pitch setpoint command. The at least one pitch setpoint command is transmitted to a pitch control mechanism of the wind turbine.

Abstract: A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller determines a performance differential for the wind turbine at multiple sampling intervals of a yaw event. The controller determines a trendline for the wind turbine correlating the performance differential to a deviation of a wind direction at each of the multiple sampling intervals from an first yaw angle. A difference between an angle associated with the vertex of the trendline and the first yaw angle are utilized by the controller to determine a yaw angle offset. The yaw angle offset is used to adjust a second yaw angle of the wind turbine.

Abstract: A system and method are provided for determining a geographic location of a tower top pivot point (TPP) of a wind turbine tower having a nacelle that includes a machine head and rotor at a top thereof. At least one rover receiver of a global navigation satellite system (GNSS) is configured at a fixed position on the nacelle. A plurality of 360-degree yaw sweeps of the nacelle are conducted and the geo-location signals received by the rover receiver during the yaw sweeps are recorded. With a controller, the geo-location signals are converted into a circular plot and a radius of the plot is determined, the radius being a distance between the rover receiver and the TPP. Based on a GNSS geo-location of the rover receiver and the radius, a geo-location of the TPP is computed.

Abstract: A method for optimizing wake management in a wind farm includes receiving, via one or more position localization sensors, position data from at least one nacelle of wind turbines in the wind farm. The method also includes determining angle of the nacelle(s) of the wind turbines with respect to true north based on the position data. Moreover, the method includes determining a wind direction at the nacelle(s) of the wind turbines. As such, the method includes generating a wake estimation model of the wind farm in real-time using the wind direction and the angle of the nacelle(s). In addition, the method includes running the wake estimation model to determine one or more optimal operating parameters for the wind turbines that maximize energy production of the wind turbine. Thus, the method includes operating the wind farm using the optimal operating parameter(s) so as to optimize wake management of the wind farm.

Abstract: A control system is disclosed. The control system includes a wind turbine, at least one sensor configured to detect at least one property of the wind turbine to generate measurement data, and a controller communicatively coupled to the wind turbine and the at least one sensor. The controller includes at least one processor in communication with at least one memory device. The at least one processor is configured to control, during a training phase, the wind turbine according to at least one test parameter, receive, from the at least one sensor, during the training phase, first measurement data, generate, based on the at least one test parameter and the received first measurement data, a control model, receive, during an operating phase, second measurement data from the at least one sensor, and update the control model continuously based on the second measurement data.

Abstract: A system and method are provided for controlling a wind turbine based on a collective pitch-offset. Accordingly, a wind condition acting on a rotor of the wind turbine is determined, and a first collective pitch angle for the plurality of rotor blades is set, and the wind turbine is operated. A thrust of the rotor based, at least in part, on the wind condition is determined, and an actual collective pitch angle is calculated. A collective pitch offset is determined based on the difference between the first collective pitch angle and the actual collective pitch angle. The collective pitch offset is integrated with at least one pitch setpoint command. The at least one pitch setpoint command is transmitted to a pitch control mechanism of the wind turbine.

Abstract: A method for assessing or validating wind turbine or wind farm performance produced by one or more upgrades is provided. Measurements of operating data from wind turbines in a wind farm are obtained. Baseline models of performance are generated, and each of the baseline models is developed from a different portion of the operating data. A generating step filters the wind turbines so that they are in a balanced randomized state. An optimal baseline model of performance is selected from the baseline models and the optimal baseline model includes direction. The optimal baseline model of performance and an actual performance of the wind farm or wind turbine is compared. The comparing step determines a difference between an optimal baseline model of power output and an actual power output of the wind farm/turbine. The difference is reflective of a change in the power output produced by the upgrades.

Abstract: A method for assessing or validating wind turbine or wind farm performance produced by one or more upgrades is provided. Measurements of operating data from wind turbines in a wind farm are obtained. Baseline models of performance are generated, and each of the baseline models is developed from a different portion of the operating data. A generating step filters the wind turbines so that they are in a balanced randomized state. An optimal baseline model of performance is selected from the baseline models and the optimal baseline model includes direction. The optimal baseline model of performance and an actual performance of the wind farm or wind turbine is compared. The comparing step determines a difference between an optimal baseline model of power output and an actual power output of the wind farm/turbine. The difference is reflective of a change in the power output produced by the upgrades.

Abstract: A method for controlling loads of a wind turbine includes receiving sensor signals from one or more sensors being indicative of a movement of a nacelle of the wind turbine from a reference point. More particularly, the movement corresponds, at least, to a tilt and/or a displacement of the wind turbine tower and/or nacelle. The method also includes generating a deflection profile of the tower along its overall length from a bottom end to a top end thereof based on the sensor signals. Further, the method includes determining at least one of a thrust or a tower load of the wind turbine from the deflection profile. In addition, the method includes implementing a control action for the wind turbine based on the thrust and/or the tower load.

Abstract: A method for controlling operation of a wind turbine includes collecting training data, training a machine learning model, obtaining recent data, and applying the machine learning model the recent data to output a reference power or reference power differential corresponding to the recent data. The machine learning model is then applied to the recent data to output at least one of estimated power or estimated power differential corresponding to values of the pitch setpoints and the tip speed ratio setpoints which differ from the recent data. A turbine setting is determined by comparing the estimated power or estimated power differential to the reference power or reference power differential, and then applying the turbine setting to the wind turbine if the estimated power or estimated power differential is greater than or equal to a threshold amount above the reference power or reference power differential.

Abstract: A method for controlling operation of a wind turbine includes collecting training data, training a machine learning model, obtaining recent data, and applying the machine learning model the recent data to output a reference power or reference power differential corresponding to the recent data. The machine learning model is then applied to the recent data to output at least one of estimated power or estimated power differential corresponding to values of the pitch setpoints and the tip speed ratio setpoints which differ from the recent data. A turbine setting is determined by comparing the estimated power or estimated power differential to the reference power or reference power differential, and then applying the turbine setting to the wind turbine if the estimated power or estimated power differential is greater than or equal to a threshold amount above the reference power or reference power differential.

Abstract: A method for controlling loads of a wind turbine includes receiving sensor signals from one or more sensors being indicative of a movement of a nacelle of the wind turbine from a reference point. More particularly, the movement corresponds, at least, to a tilt and/or a displacement of the wind turbine tower and/or nacelle. The method also includes generating a deflection profile of the tower along its overall length from a bottom end to a top end thereof based on the sensor signals. Further, the method includes determining at least one of a thrust or a tower load of the wind turbine from the deflection profile. In addition, the method includes implementing a control action for the wind turbine based on the thrust and/or the tower load.

Abstract: A bearing assembly for a wind turbine includes a bearing having an outer race, an inner race rotatable relative to the outer race, and a plurality of roller elements positioned within at least one raceway defined between the outer and inner races. Further, the bearing assembly includes at least one position sensor arranged with the at least one raceway. As such, the position sensor(s) is configured for monitoring movement of the plurality of roller elements. Moreover, the bearing assembly includes a controller communicatively coupled to the position sensor(s). Thus, the controller is configured to determine receive an output from the position sensor(s) and determine a position of one or more of the plurality of roller elements based on an output from the position sensor(s).

Abstract: A bearing assembly for a wind turbine includes a bearing having an outer race, an inner race rotatable relative to the outer race, and a plurality of roller elements positioned within at least one raceway defined between the outer and inner races. Further, the bearing assembly includes at least one position sensor arranged with the at least one raceway. As such, the position sensor(s) is configured for monitoring movement of the plurality of roller elements. Moreover, the bearing assembly includes a controller communicatively coupled to the position sensor(s). Thus, the controller is configured to determine receive an output from the position sensor(s) and determine a position of one or more of the plurality of roller elements based on an output from the position sensor(s).

Abstract: An apparatus and method of simultaneous spectroelectrochemical analysis is disclosed. A transparent surface is provided. An analyte solution on the transparent surface is contacted with a working electrode and at least one other electrode. Light from a light source is focused on either a surface of the working electrode or the analyte solution. The light reflected from either the surface of the working electrode or the analyte solution is detected. The potential of the working electrode is adjusted, and spectroscopic changes of the analyte solution that occur with changes in thermodynamic potentials are monitored.

Abstract: An apparatus and method of simultaneous spectroelectrochemical analysis is disclosed. A transparent surface is provided. An analyte solution on the transparent surface is contacted with a working electrode and at least one other electrode. Light from a light source is focused on either a surface of the working electrode or the analyte solution. The light reflected from either the surface of the working electrode or the analyte solution is detected. The potential of the working electrode is adjusted, and spectroscopic changes of the analyte solution that occur with changes in thermodynamic potentials are monitored.