Embodiments of the present disclosure include a data processing and control augmentation system capable of identifying overloading of one or more wind turbine assemblies and providing information to a wind farm controller to reduce a power output of each overloaded turbine. The augmentation system thus reduces the power output of each overloaded turbine and, in turn, reduces loads applied to the wind turbine assembly, such as for a period of time until conditions favorably change. A described analysis of the present disclosure is able to utilize several incoming data streams from sensors so arranged to measure wind effects on blades to calculate and compare cyclic loads to threshold limits to o keep the loads within design limits. The control strategy reduces premature failure of components within the wind turbine assembly, and can be applied across an entire wind farm, even with only a subset of wind turbine assemblies being retrofitted.

A method for controlling a wind turbine is provided. The wind turbine is a turbine of the type that is operated to perform a control function that controls the amount of power produced based upon measures of fatigue life consumption of one or more turbine components. The method comprises initialising the control function by: over-riding or bypassing (405) the control function for a predetermined period of time, such that power produced by the wind turbine is not altered based upon the determined measures of fatigue life consumption; during the predetermined period of time, operating (407) one or more fatigue lifetime usage estimation algorithms, to determine a measure of the fatigue life consumed by each of the one or more turbine components; and after the predetermined period of time has elapsed, activating (409) the control function and using, in the control function, at least one of the measures of fatigue life consumption determined during the predetermined period of time. A corresponding wind turbine controller and wind power plant controller are also provided.

Embodiments of the present disclosure include a data processing and control augmentation system capable of identifying overloading of one or more wind turbine assemblies and providing information to a wind farm controller to reduce a power output of each overloaded turbine. The augmentation system thus reduces the power output of each overloaded turbine and, in turn, reduces loads applied to the wind turbine assembly, such as for a period of time until conditions favorably change. A described analysis of the present disclosure is able to utilize several incoming data streams from sensors so arranged to measure wind effects on blades to calculate and compare cyclic loads to threshold limits to o keep the loads within design limits. The control strategy reduces premature failure of components within the wind turbine assembly, and can be applied across an entire wind farm, even with only a subset of wind turbine assemblies being retrofitted.

A method for estimating future risk of failure of a component of an industrial asset. The method includes receiving a plurality of different types of data associated with the industrial asset or a fleet of industrial assets. The plurality of different types of data includes, at least, reliability data (such as time-to-event data). The method also includes generating a failure prediction model for the component based on the reliability data and available time-series measurements. Further, the method includes applying the failure prediction model to the different types of data based on the types of data available in the received data. The applied failure prediction model includes one of a default model, a conditional survival model, or a joint conditional survival model. Thus, the method includes estimating, via the failure prediction model, the future risk of failure of the industrial asset and implementing a control action as needed.

A method of operating a wind turbine and a method of determining fatigue in a wind turbine component are provided. The method of operating a wind turbine comprises determining a reference accumulated fatigue, determining an operational time, obtaining a partial load indicator, determining a real accumulated fatigue, comparing the real accumulated fatigue and the reference accumulated fatigue and controlling the operation of the wind turbine. The method of determining fatigue in a wind turbine component comprises determining an operational time, obtaining wind speed, obtaining turbulence intensity, determining a time for each combination of wind speed and turbulence intensity and determining a real accumulated fatigue. In a further aspect, this is also provided a wind turbine controller configured to perform any of the methods herein disclosed.

Embodiments of the present disclosure include a data processing and control augmentation system capable of identifying overloading of one or more wind turbine assemblies and providing information to a wind farm controller to reduce a power output of each overloaded turbine. The augmentation system thus reduces the power output of each overloaded turbine and, in turn, reduces loads applied to the wind turbine assembly, such as for a period of time until conditions favorably change. A described analysis of the present disclosure is able to utilize several incoming data streams from sensors so arranged to measure wind effects on blades to calculate and compare cyclic loads to threshold limits to o keep the loads within design limits. The control strategy reduces premature failure of components within the wind turbine assembly, and can be applied across an entire wind farm, even with only a subset of wind turbine assemblies being retrofitted.

A method of controlling a wind turbine is provided. Data is obtained that identifies, based on forecast data, one or more future periods of time during which it would be desirable to over-rate the wind turbine, and measures of the fatigue life consumed by one or more turbine components are determined. The total fatigue life consumed by the one or more turbine components is limited prior to the one or more periods of time by controlling the power output of the wind turbine, in advance of the one or more periods of time, based upon the measure of the fatigue life consumed by the one or more turbine components. For example the overall rate of consumption of fatigue life by the one or more turbine components may be reduced prior to the one or more periods of time commencing. The wind turbine is then over-rated during the one or more identified periods. A corresponding wind turbine and wind power plant controller is also provided.

A method for controlling a wind turbine is provided. The wind turbine is a turbine of the type that is operated to perform a control function that controls the amount of power produced based upon measures of fatigue life consumption of one or more turbine components. The method comprises initialising the control function by: over-riding or bypassing (405) the control function for a predetermined period of time, such that power produced by the wind turbine is not altered based upon the determined measures of fatigue life consumption; during the predetermined period of time, operating (407) one or more fatigue lifetime usage estimation algorithms, to determine a measure of the fatigue life consumed by each of the one or more turbine components; and after the predetermined period of time has elapsed, activating (409) the control function and using, in the control function, at least one of the measures of fatigue life consumption determined during the predetermined period of time. A corresponding wind turbine controller and wind power plant controller are also provided.

A method of generating a control schedule for a wind turbine is provided, the control schedule indicating how the turbine maximum power level varies over time, the method comprising: receiving input indicative of a target minimum wind turbine lifetime; determining a value indicative of the current remaining fatigue lifetime of the wind turbine or one or more turbine components, based on measured wind turbine site and/or operating data; and varying a parameter of an initial predefined control schedule that specifies how the turbine maximum power level varies over time. The parameter is varied by: (i) adjusting the parameter of the initial predefined control schedule; (ii) estimating the future fatigue lifetime consumed by the wind turbine or the one or more turbine components, over the duration of the varied control schedule, based upon the varied control schedule; and (iii) repeating steps (i) and (ii) until the estimated future fatigue lifetime consumed by the wind turbine or each of the one or more turbine components is sufficient to allow the target minimum wind turbine life to be reached.

A wind turbine power plant comprises a plurality of wind turbines, each having a rated output and under the control of a power plant controller. The power plant also has a rated output which may be over-rated in response to one or more of electricity pricing data, power plant age and operator demand. The power plant controller can send over-rating demand signals to individual turbines. The controllers at the turbines include a fatigue life usage estimator which estimates a measure of the fatigue life consumed by key components of the turbine. If this measure exceeds a target value for any component, over-rating is prevented at that turbine.