Machine-learning model-based analytic for monitoring wind farm power performance

    公开(公告)号:US10954919B1

    公开(公告)日:2021-03-23

    申请号:US16590580

    申请日:2019-10-02

    Abstract: A method for controlling a wind turbine includes detecting a plurality of analytic outputs relating to power performance of the wind turbine from a plurality of different analytics. The method also includes analyzing the plurality of analytic outputs relating to power performance of the wind turbine. Further, the method includes generating at least one computer-based model of the power performance of the wind turbine using at least a portion of the analyzed plurality of analytic outputs. Moreover, the method includes training the computer-based model(s) of the power performance of the wind turbine using annotated analytic outputs relating to the power performance of the wind turbine. In addition, the method includes estimating a power magnitude of the wind turbine using the machine-learned computer-based model(s). As such, the method includes implementing a control action when the power magnitude of the wind turbine is outside of a selected range.

    METHOD AND SYSTEM FOR CLOUD PARALLELIZATION OF RECURSIVE LIFING CALCULATIONS

    公开(公告)号:US20170185485A1

    公开(公告)日:2017-06-29

    申请号:US14982901

    申请日:2015-12-29

    CPC classification number: G06Q10/20 G06F11/008

    Abstract: A system and method include receiving data elements associated with optimizing a work scope associated with a repair to a first component of a plurality of components of a piece of equipment associated with a system; assigning each component to a group; creating at least one sub-group for each group, wherein each sub-group is a first level sub-group; and recursively generating at least one additional sub-group for each sub-group until a recursion stop point is achieved, wherein each additional sub-group is a second level sub-group and without calculating a life-cycle cost for a path from the group to a last sub-group generated at the recursion stop point. Numerous other aspects are provided.

    Machine-Learning Model-Based Analytic for Monitoring Wind Farm Power Performance

    公开(公告)号:US20210102525A1

    公开(公告)日:2021-04-08

    申请号:US16590580

    申请日:2019-10-02

    Abstract: A method for controlling a wind turbine includes detecting a plurality of analytic outputs relating to power performance of the wind turbine from a plurality of different analytics. The method also includes analyzing the plurality of analytic outputs relating to power performance of the wind turbine. Further, the method includes generating at least one computer-based model of the power performance of the wind turbine using at least a portion of the analyzed plurality of analytic outputs. Moreover, the method includes training the computer-based model(s) of the power performance of the wind turbine using annotated analytic outputs relating to the power performance of the wind turbine. In addition, the method includes estimating a power magnitude of the wind turbine using the machine-learned computer-based model(s). As such, the method includes implementing a control action when the power magnitude of the wind turbine is outside of a selected range.

    SYSTEM AND METHOD FOR DISTRIBUTED COMPUTING USING AUTOMATED PROVISONING OF HETEROGENEOUS COMPUTING RESOURCES
    6.
    发明申请
    SYSTEM AND METHOD FOR DISTRIBUTED COMPUTING USING AUTOMATED PROVISONING OF HETEROGENEOUS COMPUTING RESOURCES 审中-公开
    使用自动提供异构计算资源进行分布式计算的系统和方法

    公开(公告)号:US20140189703A1

    公开(公告)日:2014-07-03

    申请号:US13730450

    申请日:2012-12-28

    CPC classification number: G06F9/50 G06F9/5027 G06F2209/5011

    Abstract: A system for distributed computing includes a job scheduler module configured to identify a job request including request requirements and comprising one or more individual jobs. The system also includes a resource module configured to determine an execution set of computing resources from a pool of computing resources based on the request requirements. Each computing resource of the pool of computing resources has an application programming interface. The pool of computing resources comprises public cloud computing resources and internal computing resources. The system further includes a plurality of interface modules, where each interface module is configured to facilitate communication with the computing resources using the associated application programming interface. The system also includes an executor module configured to identify the appropriate interface module based on facilitating communication with the execution computing resource and transmit jobs for execution to the execution computing resource using the interface modules.

    Abstract translation: 一种用于分布式计算的系统包括作业调度器模块,其配置为识别包括请求要求并包括一个或多个单独作业的作业请求。 该系统还包括资源模块,该资源模块被配置为基于请求要求从计算资源池确定计算资源的执行集。 计算资源池的每个计算资源都有一个应用程序编程接口。 计算资源池包括公共云计算资源和内部计算资源。 该系统还包括多个接口模块,其中每个接口模块被配置为便于使用相关联的应用编程接口与计算资源进行通信。 该系统还包括执行器模块,该执行器模块被配置为基于促进与执行计算资源的通信来识别适当的接口模块,并且使用接口模块将执行的作业发送到执行计算资源。

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