Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scoring candidate routes. One of the methods includes obtaining a predictive model trained on training examples from trip log data, wherein each training example has feature values from a particular trip and a value of a dependent variable that represents an outcome of a portion of the particular trip, wherein the features of each particular trip include values obtained from one or more external data feed sources that specify a value of a sensor measurement at a particular point in time during the trip. Sensor values from one or more external data feed sources of a sensor network are received. Feature values are generated using the sensor values received from the one or more external data feed sources. A predicted score is computed for each route using the feature values for the candidate route.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scoring candidate routes. One of the methods includes obtaining a predictive model trained on training examples from trip log data, wherein each training example has feature values from a particular trip and a value of a dependent variable that represents an outcome of a portion of the particular trip, wherein the features of each particular trip include values obtained from one or more external data feed sources that specify a value of a sensor measurement at a particular point in time during the trip. Sensor values from one or more external data feed sources of a sensor network are received. Feature values are generated using the sensor values received from the one or more external data feed sources. A predicted score is computed for each route using the feature values for the candidate route.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for scoring candidate routes. One of the methods includes obtaining a predictive model trained on training examples from trip log data, wherein each training example has feature values from a particular trip and a value of a dependent variable that represents an outcome of a portion of the particular trip, wherein the features of each particular trip include values obtained from one or more external data feed sources that specify a value of a sensor measurement at a particular point in time during the trip. Sensor values from one or more external data feed sources of a sensor network are received. Feature values are generated using the sensor values received from the one or more external data feed sources. A predicted score is computed for each route using the feature values for the candidate route.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.