The present disclosure is directed to a method for estimating tower loads, such as tower deflection, of a wind turbine. The method includes receiving an estimate of slow variations in thrust of a tower of the wind turbine. The method also includes determining, via one or more sensors, tower accelerations of the tower of the wind turbine. Thus, the method also includes estimating the tower loads of the wind turbine as a function of the estimate of slow variations in thrust of the tower and the tower accelerations.

The system and method described herein relate to production of power from the wind farm that incorporate tunable power production forecasts for optimal wind farm performance, where the wind farm power production is controlled at least in part by the power production forecasts. The system and method use a tunable power forecasting model to generate tunable coefficients based on asymmetric loss function applied on actual power production data, along with tuning factor(s) that tune forecast towards under forecasting or over forecasting. The power production forecasts are generated using the tunable coefficients 34 and power characteristic features that are derived from actual power production data. The power production forecasts are monitored for any degradation, and a control action to regenerate the coefficients or retune the model is undertaken if degradation is observed.

The present disclosure is directed to a system and method for determining wake losses of a wind farm. The wind farm includes a plurality of wind turbines. The method includes operating the wind farm in a first operational mode. Another step includes collecting turbine-level data from at least one upstream wind turbines in the wind farm during the first operational mode. The method also includes estimating a freestream farm-level power output for the wind farm during first operational mode based, at least in part, on the collected turbine-level data. A further step includes measuring an actual farm-level power output for the wind farm for the first operational mode. Thus, the method also includes determining the wake losses of the wind farm for the first operational mode as a function of the measured actual farm-level power output and the estimated freestream farm-level power output.

The invention is a method for controlling and/or monitoring a wind turbine 1 equipped with a LIDAR sensor 2. Control and/or monitoring provides an estimation of the wind speed at the rotor obtained an estimator and a LIDAR sensor 2. The estimator of the wind speed at the rotor is constructed from a representation of the wind, a model of the LIDAR sensor and a model of wind propagation.

The present invention relates to an operation control method for a gasification power generation system for gasifying carbon-based fuel such as coal in a gasifier using oxygen or oxygen-enriched air as an oxidizing agent, burning the obtained syngas as fuel in a gas turbine, driving the gas turbine by the syngas, driving a steam turbine by steam generated using exhaust heat of the gas turbine, thus executing combined power generation.

A wind turbine includes a rotor, a plurality of rotor blades coupled to the rotor, and a blade pitch control system coupled to each rotor blade. A computer-implemented method for controlling the wind turbine includes determining at least one pitch position for a first blade. The method also includes determining whether there is a malfunction of the blade pitch control system associated with the first blade. The method further includes predicting a rotor imbalance using a model of at least a portion of the wind turbine. The method also includes comparing the predicted rotor imbalance with a predetermined threshold value. The method further includes one of regulating the pitch position for the second blade such that the predicted rotor imbalance is restored to a value below the predetermined threshold and regulating a pitch position for a second blade such that the predicted rotor imbalance does not exceed the predetermined threshold.

Provided is a method of controlling at least one wind turbine in case of a rotational overspeed situation, the method including: determining a current state related to the wind turbine; providing data related to the current state as input to a turbine model; predicting a load of at least one wind turbine component and power output of the wind turbine using the turbine model provided with the input for plural control strategies; comparing the predicted load and power output for the plural control strategies; and selecting that control strategy among the plural control strategies that satisfies a target criterion including the load and the power output.

The present disclosure is directed to a system and method for forecasting a farm-level power output of a wind farm having a plurality of wind turbines. The method includes collecting actual operational data and/or site information for the wind farm. The method also includes predicting operational data for the wind farm for a future time period. Further, the method includes generating a model-based power output forecast based on the actual operational data, the predicted operational data, and/or the site information. In addition, the method includes measuring real-time operational data from the wind farm and adjusting the power output forecast based on the measured real-time operational data. Thus, the method also includes forecasting the farm-level power output of the wind farm based on the adjusted power output forecast.

The invention relates to techniques for verifying a nacelle yaw position sensor installed on a wind turbine and for taking restorative action to control the nacelle yaw position. The invention relates to a method performing the comprising determining a first absolute wind direction signal associated with the first wind turbine; determining a second absolute wind signal direction signal associated with the plurality of other wind turbines; comparing the two wind direction signals; and issuing a nacelle yaw position sensor fault signal if the first signal is beyond a predetermined error range of the second signal. A benefit of the invention is that it enables the detection of an inaccurate nacelle yaw sensor without direct measurement or inspection.

A system and method are provided for controlling a wind turbine based on a collective pitch-offset. Accordingly, a wind condition acting on a rotor of the wind turbine is determined, and a first collective pitch angle for the plurality of rotor blades is set, and the wind turbine is operated. A thrust of the rotor based, at least in part, on the wind condition is determined, and an actual collective pitch angle is calculated. A collective pitch offset is determined based on the difference between the first collective pitch angle and the actual collective pitch angle. The collective pitch offset is integrated with at least one pitch setpoint command. The at least one pitch setpoint command is transmitted to a pitch control mechanism of the wind turbine.