Abstract: A method to operate a wind turbine is provided, the method including determining a correction model associated with the wind turbine, determining a corrected turbulence intensity parameter associated with the wind turbine based on the correction model, and operating the wind turbine based on the corrected turbulence intensity parameter.

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 method to operate a wind turbine is provided, the method including determining a correction model associated with the wind turbine, determining a corrected turbulence intensity parameter associated with the wind turbine based on the correction model, and operating the wind turbine based on the corrected turbulence intensity parameter.

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 method of operating a wind turbine and a method of determining fatigue in a wind turbine component are provided. The method of operating a wind turbine comprises determining a reference accumulated fatigue, determining an operational time, obtaining a partial load indicator, determining a real accumulated fatigue, comparing the real accumulated fatigue and the reference accumulated fatigue and controlling the operation of the wind turbine. The method of determining fatigue in a wind turbine component comprises determining an operational time, obtaining wind speed, obtaining turbulence intensity, determining a time for each combination of wind speed and turbulence intensity and determining a real accumulated fatigue. In a further aspect, this is also provided a wind turbine controller configured to perform any of the methods herein disclosed.

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 wind turbine includes a wind turbine rotor and rotor blades mounted on the rotor, at least one sensing device disposed on the wind turbine for measuring a first signal representative of a first wind speed at a first distance from the wind turbine rotor and a second signal representative of a second wind speed at a second distance from the wind turbine rotor. The wind turbine system includes a blade pitch actuator for adjusting a pitch of the rotor blades and a generator controller for adjusting a voltage of a wind turbine generator. The wind turbine system also includes a control unit in communication with the blade pitch actuator and the generator controller, the control unit being used for controlling the wind turbine via the blade pitch actuator and the generator controller based on an induction factor derived from the first and second signals.

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: Methods, apparatus, systems and articles of manufacture are disclosed to provide wind turbine control and compensate for wind induction effects. An example method includes receiving wind speed data from a Light Detecting and Ranging (LIDAR) sensor. The example method includes receiving operating data indicative of wind turbine operation. The example method includes determining an apriori induction correction for wind turbine operating conditions with respect to the LIDAR wind speed data based on the operating data. The example method includes estimating a wind signal from the LIDAR sensor that is adjusted by the correction. The example method includes generating a control signal for a wind turbine based on the adjusted LIDAR estimated wind signal.

Abstract: A wind turbine includes a wind turbine rotor and rotor blades mounted on the rotor, at least one sensing device disposed on the wind turbine for measuring a first signal representative of a first wind speed at a first distance from the wind turbine rotor and a second signal representative of a second wind speed at a second distance from the wind turbine rotor. The wind turbine system includes a blade pitch actuator for adjusting a pitch of the rotor blades and a generator controller for adjusting a voltage of a wind turbine generator. The wind turbine system also includes a control unit in communication with the blade pitch actuator and the generator controller, the control unit being used for controlling the wind turbine via the blade pitch actuator and the generator controller based on an induction factor derived from the first and second signals.

Abstract: A wind turbine includes a hub configured to rotate about an axis at a first rotation speed and at least one blade coupled to the hub. The wind turbine also includes a sensor assembly configured to detect at least one characteristic of wind flowing through the wind turbine. The sensor assembly is mounted to the hub. The sensor assembly includes a laser device configured to emit a laser beam and at least one optical element configured to direct the laser beam. The sensor assembly also includes a non-motorized mechanism configured to rotate the at least one optical element at a second rotation speed when the hub rotates at the first rotation speed. The second rotation speed is greater than the first rotation speed.

Abstract: A method of operating a wind turbine and a method of determining fatigue in a wind turbine component are provided. The method of operating a wind turbine comprises determining a reference accumulated fatigue, determining an operational time, obtaining a partial load indicator, determining a real accumulated fatigue, comparing the real accumulated fatigue and the reference accumulated fatigue and controlling the operation of the wind turbine. The method of determining fatigue in a wind turbine component comprises determining an operational time, obtaining wind speed, obtaining turbulence intensity, determining a time for each combination of wind speed and turbulence intensity and determining a real accumulated fatigue. In a further aspect, this is also provided a wind turbine controller configured to perform any of the methods herein disclosed.

Abstract: A method for controlling a wind turbine includes receiving signals representative of oncoming wind speeds approaching at least a portion of a wind turbine, receiving background noise and signals representative of signal-to-noise ratios corresponding to the signals representative of the oncoming wind speeds, determining an availability-and-atmospheric noise in the signals based on one or more of the signal-to-noise ratios, blade positions of blades of the wind turbine, and the yaw position of a nacelle of the wind turbine, determining a wind incoherence noise in the signals due to a change in the oncoming wind speeds while approaching at least the portion of the wind turbine, determining a net measurement noise in the signals based on the background noise, the availability-and-atmospheric noise, and the wind incoherence noise, and controlling the wind turbine based at least on the signals representative of the oncoming wind speeds and the net measurement noise.

Abstract: A control system for a dynamic system including at least one measurement sensor. The system includes at least one computing device configured to generate and transmit at least one regulation device command signal to at least one regulation device to regulate operation of the dynamic system based upon at least one inferred characteristic.

Abstract: A wind turbine includes a hub configured to rotate about an axis at a first rotation speed and at least one blade coupled to the hub. The wind turbine also includes a sensor assembly configured to detect at least one characteristic of wind flowing through the wind turbine. The sensor assembly is mounted to the hub. The sensor assembly includes a laser device configured to emit a laser beam and at least one optical element configured to direct the laser beam. The sensor assembly also includes a non-motorized mechanism configured to rotate the at least one optical element at a second rotation speed when the hub rotates at the first rotation speed. The second rotation speed is greater than the first rotation speed.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to provide wind turbine control and compensate for wind induction effects. An example method includes receiving wind speed data from a Light Detecting and Ranging (LIDAR) sensor. The example method includes receiving operating data indicative of wind turbine operation. The example method includes determining an apriori induction correction for wind turbine operating conditions with respect to the LIDAR wind speed data based on the operating data. The example method includes estimating a wind signal from the LIDAR sensor that is adjusted by the correction. The example method includes generating a control signal for a wind turbine based on the adjusted LIDAR estimated wind signal.