Abstract: A method for optimizing power production of a wind turbine includes determining at least one operational constraint for the wind turbine. The method also includes operating the wind turbine with at least one operational constraint being activated. Further, the method includes varying a tip speed ratio for the wind turbine while the at least one operational constraint is activated so as to maximize a power coefficient of the wind turbine.

Abstract: The present disclosure is directed to systems and methods for generating one or more farm-level power curves for a wind farm that can be used to validate an upgrade provided to the wind farm. The method includes operating the wind farm in a first operational mode. Another step includes collecting turbine-level operational data from one or more of the wind turbines in the wind farm during the first operational mode. The method also includes aggregating the turbine-level operational data into a representative farm-level time-series. Another step includes analyzing the operational data collected during the first second operational mode. Thus, the method also includes generating one or more farm-level power curves for the first operational mode based on the analyzed operational data.

Abstract: The present disclosure is directed to a system and method for assessing farm-level performance of a wind farm. The method includes operating the wind farm in a first operational mode and identifying one or more pairs of wind turbines having wake interaction. The method also includes generating a pairwise dataset for the wind turbines pairs. Further, the method includes generating a first wake model based on the pairwise dataset and predicting a first farm-level performance parameter based on the first wake model. The method also includes operating the wind farm in a second operational mode and collecting operational data during the second operational mode. Moreover, the method includes predicting a first farm-level performance parameter for the second operational mode using the first wake model and the operational data from the second operational mode. The method further includes determining a second farm-level performance parameter during the second operational mode.

Abstract: A system and method for simultaneously coordinating a wake control system and a noise control system of a wind farm having a plurality of wind turbines is disclosed. The method includes determining, via a farm controller, one or more wake control set points for the wake control system. Further, the method includes determining, via the farm controller, one or more noise control set points for the noise control system. The method also includes selecting, via the farm controller, between the wake control set points and the noise control set points for each of the plurality of wind turbines. Thus, the method also includes sending, via the farm controller, the selected control set points to local controllers of the plurality of wind turbines and operating the wind farm based on the selected control set points.

Abstract: The present disclosure is directed to a method for optimizing power production of a wind turbine. The method includes determining at least one operational constraint for the wind turbine. The method also includes operating the wind turbine with at least one operational constraint being activated. Further, the method includes varying a tip speed ratio for the wind turbine while the at least one operational constraint is activated so as to maximize a power coefficient of the wind turbine.

Abstract: The present disclosure is directed to a system and method for assessing farm-level performance of a wind farm. The method includes operating the wind farm in a first operational mode and identifying one or more pairs of wind turbines having wake interaction. The method also includes generating a pairwise dataset for the wind turbines pairs. Further, the method includes generating a first wake model based on the pairwise dataset and predicting a first farm-level performance parameter based on the first wake model. The method also includes operating the wind farm in a second operational mode and collecting operational data during the second operational mode. Moreover, the method includes predicting a first farm-level performance parameter for the second operational mode using the first wake model and the operational data from the second operational mode. The method further includes determining a second farm-level performance parameter during the second operational mode.

Abstract: A system and method for simultaneously coordinating a wake control system and a noise control system of a wind farm having a plurality of wind turbines is disclosed. The method includes determining, via a farm controller, one or more wake control set points for the wake control system. Further, the method includes determining, via the farm controller, one or more noise control set points for the noise control system. The method also includes selecting, via the farm controller, between the wake control set points and the noise control set points for each of the plurality of wind turbines. Thus, the method also includes sending, via the farm controller, the selected control set points to local controllers of the plurality of wind turbines and operating the wind farm based on the selected control set points.

Abstract: The present disclosure is directed to systems and methods for generating one or more farm-level power curves for a wind farm that can be used to validate an upgrade provided to the wind farm. The method includes operating the wind farm in a first operational mode. Another step includes collecting turbine-level operational data from one or more of the wind turbines in the wind farm during the first operational mode. The method also includes aggregating the turbine-level operational data into a representative farm-level time-series. Another step includes analyzing the operational data collected during the first second operational mode. Thus, the method also includes generating one or more farm-level power curves for the first operational mode based on the analyzed operational data.

Abstract: The present disclosure is directed to a system and method for controlling a wind farm. The method includes operating the wind farm based on multiple control settings over a plurality of time intervals. A next step includes collecting one or more wind parameters of the wind farm over the plurality of time intervals and one or more operating data points for each of the wind turbines in the wind farm for the plurality time intervals. The method also includes calculating a contribution of the operating data points for each of the wind turbines as a function of the one or more wind parameters. Further steps of the method include estimating an energy production for the wind farm for each of the control settings based at least in part on the contribution of the operating data points and controlling the wind farm based on optimal control settings.

Abstract: A system for wind power dispatch that includes a wind farm controller for controlling operation of wind turbines in a wind farm and regulating real time power output of the wind farm. The system also includes a wind power dispatch management system for computing a difference between a predefined power output and the real time power output and dispatching a transient wind farm reserve to reduce the difference or, if the transient wind farm reserve is insufficient to reduce the difference, additionally or alternatively dispatching a storage reserve to reduce the difference.

Abstract: A method for optimizing one or more farm-level metrics in a wind farm is presented. The method includes identifying an optimization objective and one or more decision variables for optimization. Furthermore, the method includes optimizing the optimization objective based on wake-affected wind conditions, power capture values, or damage equivalent load values, to calculate optimum decision variable values for each wind turbine. The method also includes transmitting the optimum decision variable values to the respective wind turbines. In addition, the method includes applying the optimum decision variable values to the respective wind turbines to achieve the optimization objective. Systems and non-transitory computer readable medium configured to perform the method for optimizing one or more farm-level metrics in a wind farm are also presented.

Abstract: The present disclosure is directed to a system and method for controlling a wind farm. The method includes operating the wind farm based on multiple control settings over a plurality of time intervals. A next step includes collecting one or more wind parameters of the wind farm over the plurality of time intervals and one or more operating data points for each of the wind turbines in the wind farm for the plurality time intervals. The method also includes calculating a contribution of the operating data points for each of the wind turbines as a function of the one or more wind parameters. Further steps of the method include estimating an energy production for the wind farm for each of the control settings based at least in part on the contribution of the operating data points and controlling the wind farm based on optimal control settings.

Abstract: A system for wind power dispatch that includes a wind farm controller for controlling operation of wind turbines in a wind farm and regulating real time power output of the wind farm. The system also includes a wind power dispatch management system for computing a difference between a predefined power output and the real time power output and dispatching a transient wind farm reserve to reduce the difference or, if the transient wind farm reserve is insufficient to reduce the difference, additionally or alternatively dispatching a storage reserve to reduce the difference.

Abstract: A method for optimizing one or more farm-level metrics in a wind farm is presented. The method includes identifying an optimization objective and one or more decision variables for optimization. Furthermore, the method includes optimizing the optimization objective based on wake-affected wind conditions, power capture values, or damage equivalent load values, to calculate optimum decision variable values for each wind turbine. The method also includes transmitting the optimum decision variable values to the respective wind turbines. In addition, the method includes applying the optimum decision variable values to the respective wind turbines to achieve the optimization objective. Systems and non-transitory computer readable medium configured to perform the method for optimizing one or more farm-level metrics in a wind farm are also presented.