Abstract: A system and method operate a wind farm having a plurality of wind turbines, and include determining a wind direction of a wind affecting the wind farm. Based on the wind direction, at least one upwind turbine is identified that produces a wake effect on one or more downwind wind turbines, the upwind wind turbine and affected downwind wind turbines defining a cluster. Based on a current yaw position of the upwind turbine and the wind direction, a yaw steer is determined for the upwind turbine to reduce the wake effect on the downstream wind turbines in the cluster. The yaw steer is based on increasing a net energy gain from the cluster, the net energy gain determined by subtracting an energy cost of the yaw steer from an increased energy production of the cluster resulting from the yaw steer. The upwind wind turbine is controlled to change yaw position in accordance with the yaw steer when the net energy gain satisfies a minimum threshold level.

Abstract: Systems and methods are provided. A method includes obtaining, by one or more computing devices, one or more work instructions associated with a proof-of-work protocol. The method includes performing, by the one or more computing devices, one or more first tasks based at least in part on the work instructions. The method includes determining, by the one or more computing devices and based on one or more values generated by the one or more computing devices during the one or more first tasks, one or more random or pseudorandom values. The method includes performing, by the one or more computing devices and based on the one or more random or pseudorandom values, one or more second tasks different from the one or more first tasks.

Abstract: According to some embodiments, a system to facilitate hierarchical data exchange may include an aggregation platform data store containing electronic records. A data aggregation platform may collect, from a plurality of data source devices, information associated with a plurality of data sources and store the collected information into the aggregation platform data store. The data aggregation platform may also receive a data request from a data consumer device, and, responsive to the received data request, determine a precision tier associated with the data request. The data aggregation platform may then automatically calculate a resource value for the data request based on the precision tier. It may then be arranged for information from the aggregation platform data store to be modified and transmitted to the data consumer device.

Abstract: A system and method are provided for operating a wind farm includes determining a wind direction and identifying a turbine cluster, which is a subset of a plurality of wind turbines of the wind farm. The subset includes an upwind turbine and a downwind turbine that is affected by a wake emanating from the upwind turbine. The controller then determines a difference between a freestream maximal cluster power output and a wake-affected cluster power output for the turbine cluster. The controller determines a mitigation setpoint combination for the subset configured to establish a mitigated cluster power output. Based on the mitigation setpoint combination, an operating state of at least one wind turbine of the turbine cluster is changed.

Abstract: According to some embodiments, a system to facilitate hierarchical data exchange may include an aggregation platform data store containing electronic records. A data aggregation platform may collect, from a plurality of data source devices, information associated with a plurality of data sources and store the collected information into the aggregation platform data store. The data aggregation platform may also receive a data request from a data consumer device, and, responsive to the received data request, determine a precision tier associated with the data request. The data aggregation platform may then automatically calculate a resource value for the data request based on the precision tier. It may then be arranged for information from the aggregation platform data store to be modified and transmitted to the data consumer device.

Abstract: A method for optimizing performance of a wind farm having at least one wind turbine includes maneuvering a first unmanned aerial vehicle (UAV) having at least one sensor to a first location near the at least one wind turbine of the wind farm; collecting, via the at least one sensor of the first UAV, data corresponding to one or more wind conditions at the at least one wind turbine; receiving the data corresponding to the one or more wind conditions at the at least one wind turbine via a controller; generating a control action for the at least one wind turbine using the data corresponding to the one or more wind condition at the at least one wind turbine; and implementing, via the controller, the control action.

Abstract: A computer system is provided. The computer system includes a scheduling computing device configured to receive computational task data defining a computational task to be performed, retrieve site data corresponding to each of a plurality of data processing computing devices, select, based on the computational task data and the site data, i) a first computational algorithm for executing the computational task, ii) a first data processing computing device of the plurality of data processing computing devices, and iii) at least one time period for executing the first computational algorithm by the first data processing computing device, wherein the first computational algorithm, the first data processing computing device, and the at least one time period are selected to facilitate reducing carbon dioxide emissions associated with executing the computational algorithm, and instruct the first data processing computing device to execute the first computational algorithm during the at least one time period.

Abstract: According to some embodiments, a system to facilitate hierarchical data exchange may include an aggregation platform data store containing electronic records. A data aggregation platform may collect, from a plurality of data source devices, information associated with a plurality of data sources and store the collected information into the aggregation platform data store. The data aggregation platform may also receive a data request from a data consumer device, and, responsive to the received data request, determine a precision tier associated with the data request. The data aggregation platform may then automatically calculate a resource value for the data request based on the precision tier. It may then be arranged for information from the aggregation platform data store to be modified and transmitted to the data consumer device.

Abstract: 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.

Abstract: According to some embodiments, a system to facilitate hierarchical data exchange may include an aggregation platform data store containing electronic records. A data aggregation platform may collect, from a plurality of data source devices, information associated with a plurality of data sources and store the collected information into the aggregation platform data store. The data aggregation platform may also receive a data request from a data consumer device, and, responsive to the received data request, determine a precision tier associated with the data request. The data aggregation platform may then automatically calculate a resource value for the data request based on the precision tier. It may then be arranged for information from the aggregation platform data store to be modified and transmitted to the data consumer device.

Abstract: A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller prepares a yaw bias correction function based, at least in part, on a yaw offset function, and on wind speed measurement data and wind direction reference data of a wind event acting on at least a portion of the wind farm. The controller also applies the yaw bias correction function based at least in part on position data of a nacelle of the wind turbine, to yaw the nacelle of the wind turbine.

Abstract: A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller implements a first model to determine a modeled performance parameter for the first wind turbine. The modeled performance parameter is based, at least in part, on an operation of a designated grouping of wind turbines of the plurality of wind turbines, which is exclusive of the first wind turbine. The controller then determines a performance parameter differential for the first wind turbine at multiple sampling intervals. The performance parameter differential is indicative of a difference between the modeled performance parameter and a monitored performance parameter for the first wind turbine. A second model is implemented to determine a predicted performance parameter of the first wind turbine at each of a plurality of setpoint combinations based, at least in part, on the performance parameter differential the first wind turbine.

Abstract: A system and method are provided for operating a wind farm. Accordingly, a wind direction affecting the wind farm is determined. Based on the wind direction, a controller identifies a turbine cluster, which is a subset of a plurality of wind turbines of the wind farm. The subset includes at least an upwind turbine and a downwind turbine that is affected by a wake emanating from the upwind turbine. With the turbine cluster identified for the given wind direction, the controller then determines a difference between a freestream maximal cluster power output and a wake-affected cluster power output for the turbine cluster. The controller then determines a mitigation setpoint combination for the subset of wind turbines. The mitigation setpoint combination is configured to establish a mitigated cluster power output.

Abstract: A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller implements a first model to determine a modeled performance parameter for the first wind turbine. The modeled performance parameter is based, at least in part, on an operation of a designated grouping of wind turbines of the plurality of wind turbines, which is exclusive of the first wind turbine. The controller then determines a performance parameter differential for the first wind turbine at multiple sampling intervals. The performance parameter differential is indicative of a difference between the modeled performance parameter and a monitored performance parameter for the first wind turbine. A second model is implemented to determine a predicted performance parameter of the first wind turbine at each of a plurality of setpoint combinations based, at least in part, on the performance parameter differential the first wind turbine.

Abstract: A method for controlling a wind turbine includes detecting, via a controller, a plurality of analytic outputs of the wind turbine from a plurality of different analytics. The method also includes analyzing, via the controller, the plurality of analytic outputs of the wind turbine. Further, the method includes generating, via the controller, at least one computer-based model of the wind turbine using at least a portion of the analyzed plurality of analytic outputs. Moreover, the method includes training, via the controller, the at least one computer-based model of the wind turbine using annotated analytic outputs of the wind turbine. As such, the method includes checking the plurality of analytic outputs for anomalies using the at least one computer-based model. Accordingly, the method includes implementing a control action when at least one anomaly is detected.

Abstract: 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.

Abstract: According to some embodiments, a system to facilitate hierarchical data exchange may include an aggregation platform data store containing electronic records. A data aggregation platform may collect, from a plurality of data source devices, information associated with a plurality of data sources and store the collected information into the aggregation platform data store. The data aggregation platform may also receive a data request from a data consumer device, and, responsive to the received data request, determine a precision tier associated with the data request. The data aggregation platform may then automatically calculate a resource value for the data request based on the precision tier. It may then be arranged for information from the aggregation platform data store to be modified and transmitted to the data consumer device.

Abstract: According to some embodiments, a system to facilitate hierarchical data exchange may include an aggregation platform data store containing electronic records. A data aggregation platform may collect, from a plurality of data source devices, information associated with a plurality of data sources and store the collected information into the aggregation platform data store. The data aggregation platform may also receive a data request from a data consumer device, and, responsive to the received data request, determine a precision tier associated with the data request. The data aggregation platform may then automatically calculate a resource value for the data request based on the precision tier. It may then be arranged for information from the aggregation platform data store to be modified and transmitted to the data consumer device.

Abstract: A system and method are provided for controlling a wind turbine of a wind farm. Accordingly, a controller determines a performance differential for the wind turbine at multiple sampling intervals of a yaw event. The controller determines a trendline for the wind turbine correlating the performance differential to a deviation of a wind direction at each of the multiple sampling intervals from an first yaw angle. A difference between an angle associated with the vertex of the trendline and the first yaw angle are utilized by the controller to determine a yaw angle offset. The yaw angle offset is used to adjust a second yaw angle of the wind turbine.

Abstract: A control system is disclosed. The control system includes a wind turbine, at least one sensor configured to detect at least one property of the wind turbine to generate measurement data, and a controller communicatively coupled to the wind turbine and the at least one sensor. The controller includes at least one processor in communication with at least one memory device. The at least one processor is configured to control, during a training phase, the wind turbine according to at least one test parameter, receive, from the at least one sensor, during the training phase, first measurement data, generate, based on the at least one test parameter and the received first measurement data, a control model, receive, during an operating phase, second measurement data from the at least one sensor, and update the control model continuously based on the second measurement data.