System and method for operating a wind turbine using an improved power curve

Abstract

This invention relates to systems and methods for operating wind turbines using improved power curves. A wind turbine control system is disclosed. The wind turbine control system includes: a wind turbine; at least one sensor configured to detect at least one environmental condition associated with the wind turbine; and a wind turbine controller communicatively coupled to the wind turbine and the at least one sensor. The wind turbine controller includes at least one processor communicating with at least one memory device. The at least one processor is configured to: retrieve at least one wind condition variable associated with the wind turbine; retrieve a power curve, generating the power curve based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values; receive sensor data from the at least one sensor; and control the wind turbine using the generated power curve based on the received sensor data.

Description

Technical Field

[0001] The field of this invention generally relates to wind turbine control systems, and more particularly to systems and methods for operating wind turbines using improved power curves. Background Technology

[0002] Most known wind turbines include a rotor with multiple blades. The rotor is sometimes attached to a casing or nacelle positioned atop a base (e.g., a tubular tower). At least some known utility-class wind turbines (i.e., wind turbines designed to supply electrical power to the public power grid) have rotor blades with predetermined shapes and dimensions. The rotor blades convert kinetic wind energy into blade aerodynamic forces, which in turn generate mechanical rotational torque to drive one or more generators, which then produce electrical power.

[0003] Wind turbines are exposed to large variations in wind inflow, which impose varying loads on the turbine structure (particularly the turbine rotor and shaft). Some known wind turbines include sensor assemblies for remotely detecting wind characteristics such as direction and speed. The detected wind characteristics can be used to control the mechanical load on the wind turbine. For example, a wind turbine can be controlled to operate at a specific output power based on the detected wind speed. The output power is generally selected using a power curve. At least some known power curves are generally flat above a certain threshold wind speed. That is, when the current wind speed at the turbine is above the threshold level, the selected output power is constant relative to the wind speed. In at least some cases, controlling the wind turbine in this way results in suboptimal annual power generation (AEP), turbine lifespan, and / or other operating characteristics. Improved control systems for wind turbines are therefore desirable. Summary of the Invention

[0004] In one aspect, a wind turbine control system is disclosed. The wind turbine control system includes: a wind turbine; at least one sensor configured to detect at least one environmental condition associated with the wind turbine; and a wind turbine controller communicatively coupled to the wind turbine and the at least one sensor. The wind turbine controller includes at least one processor communicating with at least one memory device. The at least one processor is configured to: retrieve at least one wind condition variable associated with the wind turbine; retrieve a power curve, generating the power curve based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values; receive sensor data from the at least one sensor; and control the wind turbine using the generated power curve based on the received sensor data.

[0005] In another aspect, a wind turbine controller is disclosed. The wind turbine controller is communicatively coupled to a wind turbine and at least one sensor configured to detect at least one environmental condition associated with the wind turbine. The wind turbine controller includes at least one processor communicating with at least one memory device. The at least one processor is configured to: retrieve at least one wind condition variable associated with the wind turbine; retrieve a power curve, and generate the power curve based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values; receive sensor data from the at least one sensor; and control the wind turbine using the generated power curve based on the received sensor data.

[0006] In another aspect, a method for controlling a wind turbine using a wind turbine controller is disclosed. The wind turbine controller is communicatively coupled to the wind turbine and at least one sensor configured to detect at least environmental conditions associated with the wind turbine. The wind turbine controller includes at least one processor communicating with at least one memory device. The method includes: retrieving at least one wind condition variable associated with the wind turbine by the wind turbine controller; retrieving a power curve by the wind turbine controller, generating the power curve based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values; receiving sensor data from the at least one sensor by the wind turbine controller; and controlling the wind turbine using the generated power curve based on the received sensor data.

[0007] Technical Solution 1. A wind turbine control system, comprising:

[0008] Wind turbine;

[0009] At least one sensor configured to detect at least one environmental condition associated with the wind turbine; and

[0010] A wind turbine controller communicatively coupled to the wind turbine and the at least one sensor, the wind turbine controller including at least one processor communicating with at least one memory device, the at least one processor being configured to:

[0011] Retrieve at least one wind condition variable associated with the wind turbine;

[0012] Retrieve the power curve, and generate the power curve based on the at least one wind condition variable by taking each calculated power value among multiple wind speed values;

[0013] Receive sensor data from the at least one sensor; and

[0014] The wind turbine is controlled using the generated power curve based on the received sensor data.

[0015] Technical Solution 2. The wind turbine control system according to Technical Solution 1, wherein the at least one processor is further configured to generate the power curve.

[0016] Technical Solution 3. The wind turbine control system according to Technical Solution 2, characterized in that, in order to generate the power curve, the at least one processor is configured to:

[0017] The computational problem of generating an increased annual power output (AEP) of the wind turbine; and

[0018] Calculate one or more solutions to the computational problem.

[0019] Technical Solution 4. The wind turbine control system according to Technical Solution 3, characterized in that the computational problem is a mixed integer linear programming (MILP) problem.

[0020] Technical Solution 5. The wind turbine control system according to Technical Solution 3, characterized in that, in order to generate the computational problem, the at least one processor is configured to generate the computational problem based on one or more operating variables of the characteristics of the wind turbine limited during operation.

[0021] Technical Solution 6. The wind turbine control system according to Technical Solution 5, characterized in that the operating variable includes at least one of the fatigue load, extreme load and gearbox load of the wind turbine.

[0022] Technical Solution 7. The wind turbine control system according to Technical Solution 5, characterized in that, in order to generate the computational problem, the at least one processor is further configured to calculate the one or more operational variables based on one or more combinations of wind conditions that define the specific environmental conditions at the wind turbine.

[0023] Technical Solution 8. The wind turbine control system according to Technical Solution 7, characterized in that, in order to calculate the one or more operating variables, the at least one processor is configured to:

[0024] Discretize the at least one wind condition variable into specific wind condition values; and

[0025] The one or more wind condition combinations are identified based on the specific wind condition value.

[0026] Technical Solution 9. The wind turbine control system according to Technical Solution 8, characterized in that, in order to generate the computational problem, the at least one processor is further configured to generate the computational problem based on the probability distribution of the wind condition variables.

[0027] Technical Solution 10. A wind turbine controller communicatively coupled to a wind turbine and at least one sensor configured to detect at least one environmental condition associated with the wind turbine, the wind turbine controller including at least one processor communicating with at least one memory device, the at least one processor being configured to:

[0028] Retrieve at least one wind condition variable associated with the wind turbine;

[0029] Retrieve the power curve, and generate the power curve based on the at least one wind condition variable by taking each calculated power value among multiple wind speed values;

[0030] Receive sensor data from the at least one sensor; and

[0031] The wind turbine is controlled using the generated power curve based on the received sensor data.

[0032] Technical Solution 11. The wind turbine controller according to Technical Solution 10, wherein the at least one processor is further configured to generate the power curve.

[0033] Technical Solution 12. The wind turbine controller according to Technical Solution 11, characterized in that, in order to generate the power curve, the at least one processor is configured to:

[0034] The computational problem of generating an increased annual power output (AEP) of the wind turbine; and

[0035] Calculate one or more solutions to the computational problem.

[0036] Technical Solution 13. The wind turbine controller according to Technical Solution 13 is characterized in that the computational problem is a mixed integer linear programming (MILP) problem.

[0037] Technical Solution 14. The wind turbine controller according to Technical Solution 12, characterized in that, in order to generate the computational problem, the at least one processor is configured to generate the computational problem based on one or more operating variables of the characteristics of the wind turbine during operation.

[0038] Technical Solution 15. The wind turbine controller according to Technical Solution 14, characterized in that the operating variable includes at least one of the fatigue load, extreme load and gearbox load of the wind turbine.

[0039] Technical Solution 16. The wind turbine controller according to Technical Solution 14, characterized in that, in order to generate the computational problem, the at least one processor is further configured to calculate the one or more operational variables based on one or more combinations of wind conditions that define the specific environmental conditions at the wind turbine.

[0040] Technical Solution 17. The wind turbine controller according to Technical Solution 16, characterized in that, in order to calculate the one or more operating variables, the at least one processor is configured to:

[0041] Discretize the at least one wind condition variable into specific wind condition values; and

[0042] The one or more wind condition combinations are identified based on the specific wind condition value.

[0043] Technical Solution 18. The wind turbine controller according to Technical Solution 16, characterized in that, in order to generate the computational problem, the at least one processor is further configured to generate the computational problem based on the probability distribution of the wind condition variables.

[0044] Technical Solution 19. A method for controlling a wind turbine using a wind turbine controller, the wind turbine controller being communicatively coupled to the wind turbine and at least one sensor configured to detect at least one environmental condition associated with the wind turbine, the wind turbine controller including at least one processor communicating with at least one memory device, the method comprising:

[0045] The wind turbine controller retrieves at least one wind condition variable associated with the wind turbine;

[0046] The power curve is retrieved by the wind turbine controller, and the power curve is generated based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values.

[0047] The wind turbine controller receives sensor data from the at least one sensor; and

[0048] The wind turbine controller controls the wind turbine using the generated power curve based on the received sensor data.

[0049] Technical Solution 20. The method according to Technical Solution 19, characterized in that it further includes generating the power curve by the wind turbine controller. Attached Figure Description

[0050] These and other features, aspects, and advantages of this disclosure will become better understood when the following detailed description is read with reference to the accompanying drawings, in which the same characters throughout the drawings denote the same parts, wherein:

[0051] Figure 1 This is a perspective view of an exemplary wind turbine.

[0052] Figure 2 It is used for control Figure 1 A block diagram of an exemplary wind turbine control system used in a wind turbine is shown.

[0053] Figure 3 The diagram can be used for control. Figure 1 The graph shows an exemplary power curve of a wind turbine.

[0054] Figure 4 This is a flowchart of an exemplary method for controlling a wind turbine.

[0055] Figure 5 This is a flowchart of an exemplary method for generating a power curve. Detailed Implementation

[0056] In the following description and claims, references shall be limited to a number of terms having the following meanings.

[0057] Unless the context clearly specifies otherwise, the singular forms “a,” “a,” and “the” include a plural number of referenced objects.

[0058] As used herein and throughout the specification and claims, approximate language may be applied to modify any quantitative expression that may be varied without altering its essential function. Therefore, a value modified by one or more terms such as “approximately,” “substantially,” and “approximately” will not be limited to the specified precise value. In at least some instances, approximate language may correspond to the precision of the instrument used to measure the value. Scope limitations may be combined and / or interchanged herein and throughout the specification and claims, and unless otherwise indicated by context or language, such scope is identified and includes all subscopes contained therein.

[0059] The embodiments described herein include a wind turbine control system comprising: a wind turbine; at least one sensor configured to detect at least one environmental condition associated with the wind turbine; and a wind turbine controller communicatively coupled to the wind turbine and the at least one sensor. The wind turbine controller includes at least one processor communicating with at least one memory device. The at least one processor is configured to: retrieve at least one wind condition variable associated with the wind turbine; retrieve a power curve, generating the power curve based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values; receive sensor data from the at least one sensor; and control the wind turbine using the generated power curve based on the received sensor data.

[0060] Figure 1 This is a schematic perspective view of an exemplary wind turbine 100. In an exemplary embodiment, the wind turbine 100 is a horizontal axis wind turbine. The wind turbine 100 includes a tower 102 extending from a support surface (not shown), a nacelle 106 coupled to the tower 102, and a rotor 108 coupled to the nacelle 106. The rotor 108 has a rotatable hub 110 and a plurality of blades 112, 114, 116 coupled to the rotatable hub 110. In an exemplary embodiment, the rotor 108 has a first blade 112, a second blade 114, and a third blade 116. In an alternative embodiment, the rotor 108 has any number of blades 112, 114, 116 that enable the wind turbine 100 to function as described herein. In an exemplary embodiment, the tower 102 is made of tubular steel and has a cavity (not shown) extending between the support surface and the nacelle 106. Figure 1 (as shown in the diagram). In alternative embodiments, the wind turbine 100 includes any tower 102 that enables the wind turbine 100 to operate as described herein. For example, in some embodiments, the tower 102 is any of a lattice steel tower, a cable-stayed tower, a concrete tower, and a hybrid tower.

[0061] In an exemplary embodiment, blades 112, 114, and 116 are positioned about a rotatable hub 110 to rotate the rotor 108 as airflow passes over the wind turbine 100. As the rotor 108 rotates, kinetic energy from the wind is converted into usable mechanical energy, and subsequently into electrical energy. During operation, the rotor 108 rotates about an axis of rotation 120 that is substantially parallel to the support surface. Additionally, in some embodiments, the rotor 108 and nacelle 106 rotate about a tower 102 on a yaw axis 122 to control the orientation of the blades 112, 114, and 116 relative to the wind direction. In alternative embodiments, the wind turbine 100 includes any rotor 108 that enables the wind turbine 100 to operate as described herein.

[0062] In an exemplary embodiment, each blade 112, 114, 116 is coupled to a rotatable hub 110 at a hub end 124 and extends radially outward from the rotatable hub 110 to a distal end 126. Each blade 112, 114, 116 defines a longitudinal axis 128 extending between the hub end 124 and the distal end 126. In an alternative embodiment, the wind turbine 100 includes any of the blades 112, 114, 116 that enable the wind turbine 100 to operate as described herein.

[0063] Figure 2 This is a block diagram of an exemplary wind turbine control system 200. The wind turbine control system 200 includes a wind turbine 202, a wind turbine controller 204, and one or more sensors 206. In some embodiments, the wind turbine 202 is substantially similar to the wind turbine 100 (in...). Figure 1 (As shown in the figure). The wind turbine controller 204 is communicatively coupled to the wind turbine 202 and includes a processor 208 and a memory device 210. In some embodiments, at least some functions of the wind turbine controller 204 are performed by the processor 208 and / or the memory device 210.

[0064] The wind turbine 202 converts kinetic wind energy into blade aerodynamic force that causes mechanical rotational torque that can be used to generate electrical power. The amount of output power generated by the wind turbine 202 depends, for example, on the operating speed and / or the amount of torque of the wind turbine 202. In addition, other characteristics of the wind turbine 202 (such as fatigue on the components of the wind turbine 202) may depend on the operating speed and / or torque of the wind turbine 202.

[0065] The wind turbine controller 204 controls the operation of the wind turbine 202, for example, by controlling the speed, torque, thrust limit, cut-out wind speed, and / or other controller tuning parameters of the wind turbine 202. For example, in some embodiments, the wind turbine controller 204 can control blades 112, 114, 116 (in... Figure 1 The pitch angle (shown in the diagram), yaw of the wind turbine 202, gearbox settings of the wind turbine 202, and / or other operating parameters of the wind turbine 202 that affect its speed and / or torque. By controlling the speed and / or torque of the wind turbine 202, the wind turbine controller 204 can select the output power at which the wind turbine 202 operates.

[0066] In some embodiments, the wind turbine controller 204 is configured to generate a power profile that can be used to control the wind turbine 202. Additionally or alternatively, in some embodiments, the wind turbine controller 204 is configured to retrieve a power profile that has been previously generated by the wind turbine controller 204 and / or another computing device. In some embodiments, the power profile may be generated based on, for example, environmental factors expected to be experienced by the wind turbine (sometimes referred to herein as “wind condition variables”) and variables expected to affect the operation and / or lifespan of the wind turbine (sometimes referred to herein as “operational variables”) (such as, for example, fatigue loads, extreme loads, or gearbox loads). In some embodiments, the wind turbine controller 204 calculates a corresponding power value for each of a plurality of wind speed values. For example, in some embodiments, the power values ​​are selected such that using the power profile increases the annual power output (AEP) of the wind turbine without substantially shortening the lifespan of the wind turbine. During operation of the wind turbine 202, when one of the plurality of wind speeds is detected by the sensor 206, the wind turbine controller uses the generated power profile to control the wind turbine 202 to operate at the corresponding power value.

[0067] In some embodiments, to generate a power curve, the wind turbine controller 204 considers several wind condition variables, such as wind speed, turbulence intensity, air density, and / or other such factors, that define the environmental conditions that the wind turbine 202 may experience. In some embodiments, the probability that a particular value of a wind condition variable will be experienced by the wind turbine 202 is characterized by a wind condition probability distribution. The wind turbine controller 204 selects one or more such wind condition variables and discretizes the wind condition variables into a finite set of values, which enables the wind turbine controller 204 to identify a finite set of possible combinations of different wind condition variables (sometimes referred to herein as "wind condition variable combinations"). The wind turbine controller 204 calculates operating variables, such as fatigue load, extreme load, and / or gearbox load, for each of the identified wind condition variable combinations. In some embodiments, for each wind condition variable combination, the operating variables are calculated at multiple different wind turbine operating points (e.g., different torques and / or speeds). Based on the calculated operational variables and wind condition probability distributions, in an exemplary embodiment, the wind turbine controller 204 formulates a computational problem (e.g., an optimization problem) that maximizes the AEP while satisfying operational constraints, resulting in a computational problem such that it is, for example, a mixed-integer linear programming (MILP) problem. For example, the MILP problem generated to increase and / or maximize the AEP subject to certain operational constraints could be:

[0068] (Equation 1)

[0069] It is subject to:

[0070] (Equation 2)

[0071] Among them, the discretized wind condition combinations are limited to ,and, ,in, n i yes F i The number of elements in It is limited to a discrete vector for all combinations of wind conditions. w(X) Limited to targeting X The probability distribution of wind turbine operating points is used to limit the number of wind turbine operating points to the set of candidate wind turbine operating points. ,and, The operating point of the wind turbine is defined as the wind turbine operating point under wind condition combination X. The SENSOR is the set of all key sensor locations considered in AEP optimization. This is an upper bound designed for the Damage Equivalent Load (DEL) or any other measure of cumulative damage at a specific sensor. The total DEL can be calculated as:

[0072] (Equation 3)

[0073] in, n i It refers to the number of cycles under specific wind conditions and wind turbine operating points.

[0074] In some embodiments, to generate power curves, a MILP problem is solved (e.g., by wind turbine controller 204 and / or another computing device) to generate one or more power curves. As those skilled in the art will recognize, the MILP problem can be solved using a variety of algorithms and software implementations. In some embodiments, for example, a mixed-integer linear problem is generated such that its solution power curve maximizes and / or otherwise increases the AEP of the wind turbine 202 under predefined limit constraints of the operated variables.

[0075] Once one or more power curves have been generated, the wind turbine controller 204 controls the operation of the wind turbine 202 using one or more power curves, for example, by selecting a power curve based on wind speed and air density and using the selected power curve to determine the output power based on the current wind speed and current air density. In some embodiments, using the generated power curves to control the wind turbine 202 can increase the AEP of the wind turbine 202 relative to a flat power curve, while reducing and / or minimizing any corresponding lifespan reduction caused by operating the wind turbine 202 at higher output power.

[0076] Figure 3 The diagram shows how to control the wind turbine 100 (in Figure 1 A graph 300 showing a first power curve 302, a second power curve 304, and a third power curve 306 (shown in the figure). Graph 300 includes a horizontal axis 308 corresponding to wind speed (such as, for example, wind speed detected at wind turbine 100). Graph 300 further includes a vertical axis 310 corresponding to the output power of wind turbine 100. The output power of wind turbine 100 can be selected based on the current wind speed using, for example, the first power curve 302, the second power curve 304, or the third power curve 306.

[0077] When the output power is selected based on the first power curve 302 or the second power curve 304, the output power generally increases with increasing wind speed until a threshold wind speed 312 is reached, after which the output power remains constant. Controlling the wind turbine 100 based on the first power curve 302 generally results in higher output power and a correspondingly higher AEP compared to controlling the wind turbine 100 based on the second power curve 304. Conversely, in some embodiments, controlling the wind turbine 100 based on the second power curve 304 generally results in lower fatigue and a correspondingly longer operating life of the wind turbine 100 compared to controlling the wind turbine 100 based on the first power curve 302. In some embodiments, the third power curve 306 is a power curve generated by the wind turbine controller 204 using the systems and methods described herein, and the third power curve 306 is used to control the wind turbine 100 to increase the AEP of the wind turbine 100 while minimizing the increase in fatigue of the wind turbine 100.

[0078] Figure 4 An exemplary method 400 for controlling a wind turbine 202 is illustrated. In some embodiments, method 400 is performed by a wind turbine controller 204. Method 400 includes retrieving at least one wind condition variable corresponding to the wind turbine 202. Method 400 further includes retrieving a power curve 404, generating the power curve based on the at least one wind condition variable by calculating power values ​​for each of a plurality of wind speed values. Method 400 further includes receiving sensor data 406 from at least one sensor (such as sensor 206). Method 400 further includes controlling the wind turbine 202 408 using the power curve based on the received sensor data.

[0079] Figure 5An exemplary method 500 for generating a power curve to control a wind turbine 100 is illustrated. In some embodiments, method 500 is performed by a wind turbine controller 204. Method 500 includes retrieving 502 at least one wind condition variable. Method 500 further includes discretizing 504 the at least one wind condition variable into specific wind condition values. Method 500 further includes identifying 506 wind condition combinations based on specific wind condition values. Method 500 further includes calculating 508 one or more operating variables based on one or more wind condition combinations defining specific environmental conditions at the wind turbine. Method 500 further includes generating 510 a MILP problem based on one or more operating variables defining characteristics of the wind turbine during operation. Method 500 further includes calculating one or more solutions to the MILP problem.

[0080] Exemplary technical effects of the methods, systems, and apparatuses described herein include at least one of the following: (a) improving the AEP of a wind turbine by controlling the wind turbine using a power curve based on environmental conditions at the wind turbine; (b) improving the AEP of a wind turbine relative to its lifetime by controlling the wind turbine using a power curve calculated based on environmental conditions at the wind turbine; and (c) improving the efficiency of generating a power curve by calculating the power curve based on environmental conditions at the wind turbine, a probability distribution corresponding to the environmental conditions, and operating variables of the wind turbine.

[0081] Exemplary embodiments of systems for controlling wind turbines are provided herein. Systems and methods for operating and manufacturing such systems and apparatus are not limited to the specific embodiments described herein; rather, components of the system and / or steps of the method may be used independently of and separately from other components and / or steps described herein. For example, methods may also be used in combination with other electronic systems and are not limited to practice using only the electronic systems and methods described herein. Rather, exemplary embodiments may be implemented and utilized in conjunction with many other electronic systems.

[0082] Some embodiments relate to the use of one or more electronic devices or computing devices. Such devices typically include processors, processing devices, or controllers, such as general-purpose central processing units (CPUs), graphics processing units (GPUs), microcontrollers, reduced instruction set computer (RISC) processors, application-specific integrated circuits (ASICs), programmable logic circuits (PLCs), field-programmable gate arrays (FPGAs), digital signal processing (DSP) devices, and / or any other circuitry or processing devices capable of performing the functions described herein. The methods described herein may be encoded as executable instructions embodied in a computer-readable medium, including but not limited to storage devices and / or memory devices. When executed by a processing device, such instructions cause the processing device to perform at least a portion of the methods described herein. The examples above are merely illustrative and are therefore not intended to limit the definition and / or meaning of the terms processor and processing device in any way.

[0083] Although specific features of various embodiments of this disclosure may be shown in some of the accompanying drawings but not in others, this is merely for convenience. Any feature of the drawings may be combined with any feature of any other drawing in accordance with the principles of this disclosure and may be referenced and / or claimed.

[0084] This written description uses examples to disclose the invention (including the best mode) and also enables any person skilled in the art to practice the invention (including making and using any apparatus or system, and performing any incorporated methods). The patentability of the invention is defined by the claims and may include other examples that would occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they have structural elements that are not different from the literal language of the claims, or if they include equivalent structural elements that are not substantially different from the literal language of the claims.

Claims

1. A wind turbine control system, comprising: Wind turbine; At least one sensor configured to detect at least one environmental condition associated with the wind turbine; as well as A wind turbine controller communicatively coupled to the wind turbine and the at least one sensor, the wind turbine controller including at least one processor communicating with at least one memory device, the at least one processor being configured to: Retrieve at least one wind condition variable associated with the wind turbine; The power curve is retrieved and generated based on the at least one wind condition variable, the probability distribution corresponding to the at least one wind condition variable, and one or more operating variables of the wind turbine, wherein the power curve is generated for each calculated power value among a plurality of wind speed values. Receive sensor data from the at least one sensor; as well as The wind turbine is controlled using the generated power curve based on the received sensor data.

2. The wind turbine control system according to claim 1, characterized in that, The at least one processor is further configured to generate the power curve.

3. The wind turbine control system according to claim 2, characterized in that, To generate the power curve, the at least one processor is configured to: The computational problem of generating an increased annual power output (AEP) of the wind turbine; and Calculate one or more solutions to the computational problem.

4. The wind turbine control system according to claim 3, characterized in that, The computational problem is a mixed-integer linear programming (MILP) problem.

5. The wind turbine control system according to claim 3, characterized in that, In order to generate the computational problem, the at least one processor is configured to generate the computational problem based on one or more operating variables that define the characteristics of the wind turbine during operation.

6. The wind turbine control system according to claim 5, characterized in that, The operating variables include at least one of the wind turbine's fatigue load, extreme load, and gearbox load.

7. The wind turbine control system according to claim 5, characterized in that, In order to generate the computational problem, the at least one processor is further configured to calculate the one or more operational variables based on one or more combinations of wind conditions that define the specific environmental conditions at the wind turbine.

8. The wind turbine control system according to claim 7, characterized in that, In order to compute the one or more operational variables, the at least one processor is configured to: Discretize the at least one wind condition variable into specific wind condition values; and The one or more wind condition combinations are identified based on the specific wind condition value.

9. The wind turbine control system according to claim 8, characterized in that, In order to generate the computational problem, the at least one processor is further configured to generate the computational problem based on the probability distribution of the wind condition variables.

10. A wind turbine controller communicatively coupled to a wind turbine and at least one sensor configured to detect at least one environmental condition associated with the wind turbine, the wind turbine controller including at least one processor in communication with at least one memory device, the at least one processor being configured to: Retrieve at least one wind condition variable associated with the wind turbine; The power curve is retrieved and generated based on the at least one wind condition variable, the probability distribution corresponding to the at least one wind condition variable, and one or more operating variables of the wind turbine, wherein the power curve is generated for each calculated power value among a plurality of wind speed values. Receive sensor data from the at least one sensor; as well as The wind turbine is controlled using the generated power curve based on the received sensor data.

11. The wind turbine controller according to claim 10, characterized in that, The at least one processor is further configured to generate the power curve.

12. The wind turbine controller according to claim 11, characterized in that, To generate the power curve, the at least one processor is configured to: The computational problem of generating an increased annual power output (AEP) of the wind turbine; and Calculate one or more solutions to the computational problem.

13. The wind turbine controller according to claim 12, characterized in that, The computational problem is a mixed-integer linear programming (MILP) problem.

14. The wind turbine controller according to claim 12, characterized in that, In order to generate the computational problem, the at least one processor is configured to generate the computational problem based on one or more operating variables that define the characteristics of the wind turbine during operation.

15. The wind turbine controller according to claim 14, characterized in that, The operating variables include at least one of the wind turbine's fatigue load, extreme load, and gearbox load.

16. The wind turbine controller according to claim 14, characterized in that, In order to generate the computational problem, the at least one processor is further configured to calculate the one or more operational variables based on one or more combinations of wind conditions that define the specific environmental conditions at the wind turbine.

17. The wind turbine controller according to claim 16, characterized in that, In order to compute the one or more operational variables, the at least one processor is configured to: Discretize the at least one wind condition variable into specific wind condition values; and The one or more wind condition combinations are identified based on the specific wind condition value.

18. The wind turbine controller according to claim 16, characterized in that, In order to generate the computational problem, the at least one processor is further configured to generate the computational problem based on the probability distribution of the wind condition variables.

19. A method for controlling a wind turbine using a wind turbine controller, the wind turbine controller being communicatively coupled to the wind turbine and at least one sensor configured to detect at least one environmental condition associated with the wind turbine, the wind turbine controller including at least one processor communicating with at least one memory device, the method comprising: The wind turbine controller retrieves at least one wind condition variable associated with the wind turbine; The power curve is retrieved by the wind turbine controller and generated based on the at least one wind condition variable, the probability distribution corresponding to the at least one wind condition variable, and one or more operating variables of the wind turbine, wherein the power curve is generated for each calculated power value among a plurality of wind speed values. The wind turbine controller receives sensor data from the at least one sensor; as well as The wind turbine controller controls the wind turbine using the generated power curve based on the received sensor data.

20. The method according to claim 19, characterized in that, This further includes generating the power curve by the wind turbine controller.

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