General Electric Company

General Electric Renovables Espana, S.l.

Gm Global Technolgoy Operations, Inc.

Proterra Inc.

Samuel Bryan Shartzer

Scott Charles Evans

Samuel Davoust

Bernard P Landa

Nurali Virani

Dhiraj Arora

Arunvenkataraman Subramanian

Pierino Gianni Bonanni

Igor Anilovich

Darren John Danielsen

William Forrester Seely

Danian Zheng

John W Siekkinen

David August Snider

Srinivas Bollapragada

Wajdi B Hamama

Seamus McGrath

Xu Fu

Kasi Viswanadha Raju Gadiraju

Joseph Lawrence Chacon

Pranav Agarwal

Keyur M Shah

John Carver Maters

Collin McKee Sheppard

Brian Allen Rittenhouse

Jaehak Jung

Stefan Kern

Shuang Gu

Roberto De Paula

Joseph Edward Birkenstock

Sara Simonne Louisa Delport

Neeraj Chirmulay

Philip James Verzella

Alvaro Enrique Gil

Nikolina Kourteva Kristeva

Raul Munoz

Eugene A Post

Tapan Ravin Shah

Joerg Wanink

Ricardo Zetina

Gordon Dollar

Bernard Landa

Nikolina Kristeva

A system and method are provided for operating a wind farm includes determining a wind direction and identifying a turbine cluster, which is a subset of a plurality of wind turbines of the wind farm. The subset includes an upwind turbine and a downwind turbine that is affected by a wake emanating from the upwind turbine. 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 determines a mitigation setpoint combination for the subset configured to establish a mitigated cluster power output. Based on the mitigation setpoint combination, an operating state of at least one wind turbine of the turbine cluster is changed.

Systems and methods for operating a wind farm

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.

Systems and methods for controlling a wind turbine

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 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.

System and method for controlling a wind turbine based on a collective pitch-offset

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.

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.

Method and system for determining and tracking the top pivot point of a wind turbine tower

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.

Systems and methods for continuous machine learning based control of wind turbines

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.

System and method for assessing and validating wind turbine and wind farm performance

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.

System and method for controlling thrust and/or tower loads of a wind turbine

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.

Method for controlling operation of a wind turbine

An electric vehicle charging system includes a charging interface positioned on an external surface of the electric vehicle and one or more electrodes positioned on the charging interface. The charging system may also include a heating system positioned on the charging interface. The heating system may be configured to heat at least a portion of the charging interface. The charging system may also include a control system configured to selectively activate the heating system based at least on one or more ambient conditions.

Electric vehicle charging interface

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).

System and method for monitoring movement of a roller element of a bearing

Embodiments of the present invention employ a closed loop controls philosophy, which actively controls the starting means of a powerplant machine, throughout the start-up process. Here, the present invention may provide a method for adjusting a nominal operating schedule of the starting means, which may have the form of a Load Commutated Inverter (LCI). Embodiments of the method may adjust the nominal operating schedule based, in part, on an operating parameter, which is associated with the gas turbine. The operating parameter may include, but is not limited to: a rotor speed, a desired start-up time, or the like. Here, the control system may receive data on the operating parameter associated with the gas turbine.

Method for starting a turbomachine

A control system for an engine includes a block heater determination module, an adjustment module, and an engine control module. The block heater determination module generates a block heater usage signal based on ambient temperature, measured engine coolant temperature, and a length of time of the engine being off prior to engine startup. The adjustment module generates a temperature signal based on the ambient temperature. The engine control module determines a desired fuel mass for fuel injection at engine startup based on the temperature signal when the block heater usage signal has a first state. The engine control module determines the desired fuel mass at engine startup based on the measured engine coolant temperature when the block heater usage signal has a second state.

Block heater usage detection and coolant temperature adjustment

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Greenville, SC, United States of America

Samuel Bryan Shartzer