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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
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.
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公开(公告)号：US12038354B2
公开(公告)日：2024-07-16
申请号：US17032218
申请日：2020-09-25
Applicant: General Electric Company
Inventor： Zhanpan Zhang , Guangliang Zhao , Jin Xia , John Joseph Mihok , Frank William Ripple, Jr. , Kyle Raymond Barden , Alvaro Enrique Gil
IPC: G01M99/00 , G05B19/042 , G06N20/00
CPC classification number: G01M99/005 , G05B19/042 , G06N20/00 , G05B2219/2619
Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.
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3.发明申请公开(公告)号：US20160265513A1
公开(公告)日：2016-09-15
申请号：US14644743
申请日：2015-03-11
Applicant: General Electric Company
Inventor： Scott Charles Evans , Zhanpan Zhang , Peter Alan Gregg , Kevin Wayne Kinzie , William Arthur Flodder , Mark Nicolaas Jonkhof , Megan Michela Wilson
CPC classification number: F03D13/30 , F03D7/048 , F03D9/257 , F03D17/00 , F05B2230/80 , F05B2270/32 , F05B2270/335 , Y02E10/723 , Y02P70/523
Abstract: 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.
Abstract translation: 本公开涉及用于验证风电场性能改进的系统和方法，以便优化风电场性能。 在一个实施例中，该方法包括经由控制器以第一操作模式操作风电场。 另一步骤包括在第一操作模式期间经由处理器收集第一组操作数据。 另一步骤包括经由控制器以第二操作模式操作风电场。 该方法还包括在第二操作模式期间经由处理器收集第二组操作数据。 接下来，该方法包括基于风速分布来归一化第一和第二组操作数据。 因此，另一步骤包括经由处理器比较归一化的第一和第二组操作数据，以便验证一个或多个风电场性能测量。
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4.发明申请公开(公告)号：US20160084233A1
公开(公告)日：2016-03-24
申请号：US14493464
申请日：2014-09-23
Applicant: General Electric Company
Inventor： Scott Charles Evans , Zhanpan Zhang , Peter Alan Gregg , Satish G. Iyengar
CPC classification number: F03D17/00 , F03D7/048 , F03D9/257 , F05B2260/84 , F05D2270/20 , F05D2270/335 , H02J3/00 , H02J3/386 , H02J2003/007 , Y02E10/723 , Y02E10/763 , Y02E60/76 , Y04S40/22
Abstract: 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.
Abstract translation: 本公开涉及用于验证和/或识别风电场性能测量的系统和方法，以便优化风电场性能。 该方法包括测量来自农场的一个或多个风力涡轮机的操作数据。 另一步骤包括从至少一部分操作数据生成风力场的多个基准模型。 因此，性能的每个基准模型是从不同部分的操作数据开发的，以便提供可比较的模型。 该方法还包括选择最佳基线模型，并将最佳基线模型与风电场的实际性能进行比较。 在特定实施例中，在风力发电场的一个或多个风力涡轮机被一个或多个升级修改之后确定风电场的实际性能。
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Patent Agency Ranking
公开(公告)号：US11378063B2
公开(公告)日：2022-07-05
申请号：US16797593
申请日：2020-02-21
Applicant: GENERAL ELECTRIC COMPANY
Inventor： Zhanpan Zhang , Peter Alan Gregg , Jin Xia , John Mihok , Guangliang Zhao , Bouchra Bouqata
Abstract: 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.
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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
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.
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公开(公告)号：US09644612B2
公开(公告)日：2017-05-09
申请号：US14493464
申请日：2014-09-23
Applicant: General Electric Company
Inventor： Scott Charles Evans , Zhanpan Zhang , Peter Alan Gregg , Satish G. Iyengar
CPC classification number: F03D17/00 , F03D7/048 , F03D9/257 , F05B2260/84 , F05D2270/20 , F05D2270/335 , H02J3/00 , H02J3/386 , H02J2003/007 , Y02E10/723 , Y02E10/763 , Y02E60/76 , Y04S40/22
Abstract: 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.
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公开(公告)号：US20220099532A1
公开(公告)日：2022-03-31
申请号：US17032218
申请日：2020-09-25
Applicant: General Electric Company
Inventor： Zhanpan Zhang , Guangliang Zhao , Jin Xia , John Joseph Mihok , Frank William Ripple, JR. , Kyle Raymond Barden , Alvaro Enrique Gil
IPC: G01M99/00 , G06N20/00 , G05B19/042
Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.
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公开(公告)号：US20160147816A1
公开(公告)日：2016-05-26
申请号：US14550405
申请日：2014-11-21
Applicant: General Electric Company
Inventor： Jerrold Allen Cline , Kete Long , Rui XU , Zhanpan Zhang
CPC classification number: G06F16/2365 , G06Q10/067
Abstract: According to some embodiments, a system includes a communication device operative to communicate with a user to receive a data set including a plurality of samples at a clustering module; a clustering module to receive the data set, store the data set, and calculate one or more clusters of samples using a clustering strategy; an optimization module to receive and store the one or more clusters of samples from the clustering module and generate one or more samples from the one or more clusters of samples using an optimization strategy; a memory for storing program instructions; at least one sample selection platform processor, coupled to the memory, and in communication with the clustering module and the optimization module and operative to execute program instructions to: calculate one or more clusters of samples based on the clustering strategy by executing the clustering module; analyze the data associated with the one or more clusters received from the clustering module using the optimization strategy associated with the optimization module to automatically select one or more samples from the one or more clusters; and provide one or more samples generated by the optimization module for replication in a validation model. Numerous other aspects are provided.
Abstract translation: 根据一些实施例，系统包括通信设备，其可操作以与用户通信以在聚类模块处接收包括多个样本的数据集; 聚类模块，用于接收数据集，存储数据集，并使用聚类策略计算一个或多个样本簇; 优化模块，用于从所述聚类模块接收和存储所述一个或多个样本簇，并使用优化策略从所述一个或多个样本簇生成一个或多个样本; 用于存储程序指令的存储器; 耦合到所述存储器并与所述聚类模块和所述优化模块通信的至少一个样本选择平台处理器，并且可操作以执行程序指令以：通过执行所述聚类模块，基于所述聚类策略来计算一个或多个样本簇; 使用与所述优化模块相关联的优化策略来分析与所述聚类模块接收的所述一个或多个聚类相关联的数据，以自动从所述一个或多个聚类中选择一个或多个样本; 并且在验证模型中提供由优化模块生成的用于复制的一个或多个样本。 提供了许多其他方面。
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