General Electric Company

General Electric Renovables Espana, S.l.

Peter Alan Gregg

Scott Charles Evans

Zhanpan Zhang

Raimundo Onetto

Arnold M Lund

Colin Craig McCulloch

Megan Michela Wilson

Jeng-Weei Lin

Jeffrey Eric Bergman

Karl Mochel

Jayanthi Srinivasan

Kenneth D Hartling

Anwar Ahmed

Sham Chotai

John David Hilton, Jr

David William Eldridge

John Anderson Fergus Ross

Awadesh Kumar Tiwari

Achalesh Kumar Pandey

Waseem Ibrahim Faidi

Danian Zheng

Kevin Wayne Kinzie

John Joseph Mihok

Ulrich Uphues

Craig Leonard Christenson

Henk-Jan Kooijman

Thomas Siebers

Guangliang Zhao

Lang Tong

David Charles Korim

Siddhanth Chandrashekar

Vineel Chandrakanth Gujjar

Donald M Rogers

Ryan Michael LeClair

Bouchra Bouqata

Frank Theodoor Ormel

Christopher R Banares

Jin Xia

Satish Giridhar Iyengar

Raul Munoz Medina

Andrew Ferree

Manisha Srivastava

Joshua Benjamin Schoenstedt

William Arthur Flodder

Mark Nicolaas Jonkhof

Steven E Dahler

Andrew T Ferree

Ricardo Zetina Benignos

Manuel Rodolfo Valdez

Matthew David Pepple

Matthew N Daly

Jeff Eric Bergman

Isaac Alejandro Martinez Tovar

Colin Craig Mcculloch

John D Hilton

A system and method are provided for operating a power generating asset. Accordingly, at least one external data set indicative of a plurality of variables affecting the performance of the power generating asset is received by the controller. The controller also receives at least one operational data set indicative of the performance of the power generating asset. A plurality of production-assessment models for the power generating asset are generated and trained based on the data sets. A performance prediction is then generated for each of a plurality of model-variable combinations and a control action is implemented based on one of the performance predictions.

Systems and methods for operating power generating assets

A method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.

System and method for detecting turbine underperformance and operation anomaly

A method for protecting a wind turbine from extreme and fatigue loads associated with high wind speed events includes receiving, via a wind turbine condition estimator programmed in a turbine controller of the wind turbine, operating data indicative of current wind turbine operation. Further, the method includes determining, via the wind turbine condition estimator, a plurality of estimated wind turbine conditions at the wind turbine by solving a control algorithm having one or more equations using the operating data. The estimated wind turbine conditions include, at least, an estimated wind speed at the wind turbine and a loading proxy of the wind turbine. As such, the method includes implementing, via the turbine controller, a corrective action only when each of the estimated wind turbine conditions indicates that one or more loading conditions of the wind turbine exceeds a predetermined limit.

System and method for protecting wind turbines from extreme and fatigue loads

Systems and methods for condition-based validation of performance updates are provided. According to one embodiment of the disclosure, a method can include operating an asset under updated settings, ascertaining ambient conditions of the asset and matching the ambient conditions to a condition range, determining whether data completion criteria for the condition range are satisfied and, based at least in part on the determination, selectively switching between using the updated settings for operating the asset and using baseline settings for operating the asset while collecting data points for a predetermined period of time.

Condition-based validation of performance updates

The present disclosure is directed to systems and methods for validating wind farm performance improvements so as to optimize wind farm performance. In one embodiment, the method includes operating, via a controller, the wind farm in a first operating mode. Another step includes collecting a first set of operating data, via a processor, during the first operating mode. A further step includes operating, via the controller, the wind farm in a second operating mode. The method also includes collecting a second set of operating data, via the processor, during the second operating mode. Next, the method includes normalizing the first and second sets of operating data based on wind speed distributions. As such, another step includes comparing, via the processor, the normalized first and second sets of operating data so as to validate one or more wind farm performance measurements.

Systems and methods for validating wind farm performance improvements

In one aspect, a method for assessing the performance impact of wind turbine upgrades may generally include determining a baseline power curve for a wind turbine prior to the wind turbine being upgraded and determining a baseline wind speed transfer function for the wind turbine prior to the wind turbine being upgraded. The method may also include determining an upgraded wind speed transfer function for the wind turbine after the wind turbine is upgraded. In addition, the method may include determining a corrected local wind speed for the wind turbine based on the baseline and upgraded wind speed transfer functions and determining an upgraded power curve for the wind turbine based on the corrected local wind speed.

System and method for assessing the performance impact of wind turbine upgrades

A computer-implemented method for recalibrating nacelle-positions of a plurality of wind turbines in a wind park is implemented by a nacelle calibration computing device including a processor and a memory device coupled to the processor. The method includes identifying at least two associated wind turbines included within the wind park wherein each associated wind turbine includes location information, determining a plurality of predicted wake features for the associated wind turbines based at least partially on the location information of each associated wind turbine, retrieving a plurality of historical performance data related to the associated wind turbines, determining a plurality of current wake features based on the plurality of historical performance data, identifying a variance between the predicted wake features and the current wake features, and determining a recalibration factor for at least one of the associated wind turbines based on the identified variance.

Systems and methods for wind turbine nacelle-position recalibration and wind direction estimation

The present disclosure is directed to a digital system for managing a wind farm having a plurality of wind turbines electrically coupled to a power grid. The system includes a farm-based first communication network having one or more individual wind turbine control systems communicatively coupled to the one or more wind turbines and an overall wind farm control system. The system also includes a cloud-based second communication network communicatively coupled to the first communication network via an industrial gateway. The second communication network includes a digital infrastructure having a plurality of digital models of the one or more wind turbines, wherein the plurality of digital models of the one or more wind turbines are continuously updated during operation of the wind farm via data supplied by the farm-based first communication network.

Digital system and method for managing a wind farm having plurality of wind turbines coupled to power grid

The present disclosure is directed to a digital twin interface for managing a wind farm having a plurality of wind turbines. The digital twin interface includes a graphical user interface (GUI) displaying a digital equivalent of the wind farm. For example, the digital equivalent of the wind farm includes environmental information and a digital representation of each of the wind turbines arranged in the wind farm. The interface also includes a control icon arranged with each of the digital representations of the wind turbines. In certain embodiments, the control icons of each wind turbine may correspond to a control dial. More specifically, the control icon of each digital representation of the wind turbines includes information regarding current and optimum operating conditions of the digital wind turbine. The interface also includes one or more control features configured to optimize performance of the wind farm.

Digital twin interface for operating wind farms

The present subject matter is directed to a system and method for optimizing wind turbine operation. For example, the present disclosure is configured to generate operating data for at least one operational parameter of the wind turbine for a predetermined time period. The system can then determine a robustness measurement of at least a portion of the operating data. In general, the robustness measurement indicates the tendency of the operating data to be affected by outliers present in the operating data. In addition, the robustness measurement is typically a function of a distribution of the operating data. The present disclosure is then configured to determine at least one optimal set point for the operational parameter as a function of the robustness measurement and a power production of the wind turbine. The wind turbine can then be operated based on the optimal set point.

System and method for robust wind turbine operation

The present disclosure is directed to systems and methods for validating and/or identifying wind farm performance measurements so as to optimize wind farm performance. The method includes measuring operating data from one or more wind turbines of the farm. Another step includes generating a plurality of baseline models of performance of the wind farm from at least a portion of the operating data. Thus, each of the baseline models of performance is developed from a different portion of operating data so as to provide comparable models. The method also includes selecting an optimal baseline model and comparing the optimal baseline model with actual performance of the wind farm. In a particular embodiment, the actual performance of the wind farm is determined after one or more wind turbines of the wind farm is modified by one or more upgrades.

Systems and methods for validating wind farm performance measurements

A control system for use with a plurality of wind turbines includes a processor and a memory device coupled to the processor. The memory device is configured to store a plurality of program modules that, when executed by the processor, configure the processor to receive data representative of a power generation of a first wind turbine of the plurality of wind turbines, and determine an expected power generation of a second wind turbine of the plurality of wind turbines based on the power generation of the first wind turbine.

Control system and method of predicting wind turbine power generation

A method for operating a wind turbine having at least one blade includes determining an ambient air operating envelope and controlling a power output of the wind turbine at least partially based on the determined ambient air operating envelope. Determining an ambient air operating envelope includes measuring at least one of an ambient air temperature, an ambient air pressure, an ambient air humidity, and wind turbine power output. The method also includes comparing at least one of a measured ambient air temperature, a measured ambient air humidity and a measured ambient air pressure to predetermined ambient air temperature, pressure and humidity values. The method further includes referencing the predetermined ambient air temperature, pressure and humidity values to at least one operational parameter of the wind turbine. The method also includes determining if an existing wind turbine power output is within a range associated with the determined ambient air operating envelope.

Methods for operating a wind turbine

A transport device includes a first segment fixedly coupled to a wall. The transport device also includes at least one second segment coupled to the first segment. The at least one second segment includes at least one of a fluid-driven device, a rack and pinion drive device, and a carriage. The transport device further includes an automated position control system. The control system includes at least one axial positioning device coupled to the at least one second segment. The control system also includes at least one axial position feedback device coupled to at least one of the first segment and the at least one second segment.

Apparatus to measure fluids in a conduit

Growing community of inventors

Niskayuna, NY, United States of America

Peter Alan Gregg