Systems and methods for building predictive and prescriptive analytics of wind turbines generate a historical operational dataset by loading historical operational SCADA data of one or more wind turbines. Each sensor measurement is associated with an engineering tag and at least one component of a wind turbine. The system creates one or more performance indicators corresponding to one or more sensor measurements, and applies at least one data clustering algorithm onto the dataset to identify and label normal operation data clusters. The system builds a normal operation model using normal operational data clusters with Efficiency of Wind-To-Power (EWTP) and defines a statistical confidence range around the normal operation model as criterion for monitoring wind turbine performance. As real-time SCADA data is received by the system, the system can detect an anomalous event, and issue an alert notification and prescriptive early-action recommendations to a user, such as a turbine operator, technician or manager.

Provided is a method of determining a control setting of at least one wind turbine of a wind park, the method including: determining a free-stream wind turbulence and deriving the control setting based on the free-stream wind turbulence, wherein the control setting includes a yawing offset, and wherein the yawing offset is derived to be the smaller, the higher the free-stream wind turbulence is.

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. A setpoint combination is then selected based on the predicted performance parameter and an operating state of the first wind turbine is changed based on the setpoint combination.

A method for monitoring a condition of a sliding bearing operated with lubricating oil for a rotating component includes calculating, by a control unit as an output variable of a sliding bearing model, a calculated value of a minimum gap thickness of the sliding bearing. The calculated value is calculated by orbit analysis from at least one physical sliding bearing model to which at least a rotational speed of the rotating component, a bearing load, and a temperature of the sliding bearing are supplied as input variables. The method further includes measuring, with at least one sensor, a minimum gap thickness to provide a measured value of the minimum gap thickness, and comparing the measured value of the minimum gap thickness with the calculated value of the minimum gap thickness for the purpose of adjustment.

A method for determining improved control parameters of a number of wind turbines of a wind park is provided. The method considers the impact of individual turbine manufacturing tolerances on the turbine performance, thereby avoiding under-utilization of those wind turbines. The method includes the steps of: receiving, by an interface, one or more actual manufacturing tolerances of characteristic values for each of the number of wind turbines; determining, by a processing unit, for each of the number of wind turbines a power versus wind speed map which is calculated from a given turbine model with the one or more actual manufacturing tolerances of the respective wind turbines as input parameters; and deriving, by the processing unit, the control parameters for each of the number of wind turbines from their associated power versus wind speed map.

A method for computer-implemented identifying an unauthorized access to a wind farm is provided by obtaining environmental and operational data of the wind farm from a repository, which include technical data and organizational data of the wind farm indicating tasks to be dealt with in the wind farm in the future. Based on the environmental and operational data, for a predetermined time interval, a prediction of the operation and/or states of the wind farm is determined by a trained data driven mode. The trained data driven model provides a prediction of the operation and/or states of the wind farm as a digital output. The prediction is compared to operational conditions of the wind farm resulting from current or past user machine interactions of a user. An unauthorized access is identified in case of a predetermined deviation of the obtained operational conditions from the prediction of the operation and/or states of the wind farm.

A method for analyzing of a road transport route for transport of a heavy load from an origin to a destination includes i) obtaining images of the transport route, the images being images taken by a drone or satellite camera system, where each of the images includes a different road section of the complete transport route and an peripheral area adjacent to the respective road section; ii) determining objects and their location in the peripheral area of the road section by processing each of the images by a first trained data driven model, where the images are as a digital input to the first trained data driven model and where the first trained data driven model provides the objects, if any, and their location as a digital output; and iii) determining critical objects from the number of determined objects along the road transport route

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. Mitigated cluster power output has a difference from the freestream maximal cluster power output that is less than the difference between the freestream maximal cluster power output in the wake-affected cluster power output for the turbine cluster. Based on the mitigation setpoint combination, an operating state of at least one wind turbine of the turbine cluster is changed.

A runner for a hydraulic turbine configured to reduce fish mortality. The runner includes a hub and a plurality of blades extending from the hub. Each blade includes a root connected to the hub and a tip opposite the root. Each blade further includes a leading edge opposite a trailing edge, and a ratio of a thickness of the leading edge to a diameter of the runner can range from about 0.06 to about 0.35. Further, each blade has a leading edge that is curved relative to a radial axis of the runner.

The present disclosure provides a method and an apparatus for self-adaption of a cut-out strategy. The method may include: predicting, using a wind speed prediction model, a wind resource parameter of a wind turbine at each machine location; predicting, using a load prediction model, a fatigue load and a limit load of the wind turbine based on the predicted wind resource parameter and an air density; comparing the predicted fatigue load and limit load with a reference load; and determining the cut-out strategy based on a result of the comparison, wherein determining the cut-out strategy includes determining a cut-out wind speed and an output power.