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    System and method for controlling power production from a wind farm
    2.
    发明授权
    System and method for controlling power production from a wind farm 有权

    公开(公告)号：US11334834B2

    公开(公告)日：2022-05-17

    申请号：US15601145

    申请日：2017-05-22

    Applicant: General Electric Company

    Inventor： Subhankar Ghosh ,  Abhirup Mondal ,  Necip Doganaksoy ,  Hongyan Liu ,  Zhanpan Zhang ,  Robert August Kaucic ,  Jay Zhiqiang Cao

    IPC: G06Q10/06 ,  G06F16/48 ,  H02J3/38 ,  F03D7/04

    Abstract: The system and method described herein relate to production of power from the wind farm that incorporate tunable power production forecasts for optimal wind farm performance, where the wind farm power production is controlled at least in part by the power production forecasts. The system and method use a tunable power forecasting model to generate tunable coefficients based on asymmetric loss function applied on actual power production data, along with tuning factor(s) that tune forecast towards under forecasting or over forecasting. The power production forecasts are generated using the tunable coefficients 34 and power characteristic features that are derived from actual power production data. The power production forecasts are monitored for any degradation, and a control action to regenerate the coefficients or retune the model is undertaken if degradation is observed.

    System and method for forecasting power output of a wind farm
    3.
    发明授权
    System and method for forecasting power output of a wind farm 有权

    公开(公告)号：US11242842B2

    公开(公告)日：2022-02-08

    申请号：US16303243

    申请日：2017-05-19

    Applicant: GENERAL ELECTRIC COMPANY

    Inventor： Robert August Kaucic ,  Zhanpan Zhang ,  Subhankar Ghosh ,  Hongyan Liu ,  Necip Doganaksoy

    IPC: F03D9/00 ,  H02P9/04 ,  F03D7/04 ,  F03D7/02 ,  F03D17/00

    Abstract: The present disclosure is directed to a system and method for forecasting a farm-level power output of a wind farm having a plurality of wind turbines. The method includes collecting actual operational data and/or site information for the wind farm. The method also includes predicting operational data for the wind farm for a future time period. Further, the method includes generating a model-based power output forecast based on the actual operational data, the predicted operational data, and/or the site information. In addition, the method includes measuring real-time operational data from the wind farm and adjusting the power output forecast based on the measured real-time operational data. Thus, the method also includes forecasting the farm-level power output of the wind farm based on the adjusted power output forecast.

    Creating predictive damage models by transductive transfer learning
    5.
    发明授权
    Creating predictive damage models by transductive transfer learning 有权

    公开(公告)号：US10229369B2

    公开(公告)日：2019-03-12

    申请号：US15132884

    申请日：2016-04-19

    Applicant: General Electric Company

    Inventor： Paul Alex Ardis ,  Subhankar Ghosh ,  Alexander Turner Graf

    IPC: G06N99/00 ,  G05B23/02 ,  G06K9/62

    Abstract: A method for creating predictive damage models includes receiving a first predictive damage model, identifying latent space between a first and a second domain asset, building a regression model from first domain asset projected source data, creating target dependent variables of a second model, applying classification or regression techniques to determine a function expressing the dependent variables, determining data points from the function to develop a second regression model, applying the second regression model to data points to predict target dependent variables, evaluating the second predictive damage model using the predicted target dependent variables, performing a sensitivity study to determine a directionality parameter of the second predictive damage model, and if the results are within an acceptable predetermined range, providing maintenance or servicing recommendations generated by the second predictive model to a user platform display, else repeating the process by rebuilding the regression model to further refine the regression model.

    Wheel deformity warning system
    6.
    发明授权
    Wheel deformity warning system 有权

    公开(公告)号：US10124819B2

    公开(公告)日：2018-11-13

    申请号：US15231343

    申请日：2016-08-08

    Applicant: General Electric Company

    Inventor： Subhankar Ghosh ,  Aditya Ramkrishna Karnik ,  Tapan Shah ,  Babu Ozhur Narayanan

    IPC: B61K9/12 ,  G01M17/10 ,  G01L5/00

    Abstract: A rail vehicle wheel flat warning system comprising a first sensor, a second sensor and a controller. The first sensor may be located adjacent to a first side of a rail to provide data associated with a rail vehicle wheel passing over the first side of the rail. The second sensor may be located adjacent to the first side of the rail to provide data associated with the rail vehicle wheel passing over the first side of the rail. Furthermore, the controller may be in communication with the first sensor and the second sensor to receive data from the first sensor and the second sensor. The controller may determine a potential wheel deformity based on the data received from the first sensor and the second sensor.

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