Paddle adjustment of floating wind turbine blades in response to wave activity

Abstract

A method, computing system, and computer program product are provided for reducing floating wind turbine loads caused by ocean waves by adjusting a blade pitch angle of at least one rotor blade of the floating wind turbine to minimize a moment imbalance at a platform top of the floating wind turbine caused by ocean wave activity.

Description

Technical Field

[0001] The following describes embodiments for blade pitch adjustment of floating wind turbines, and more particularly, embodiments for methods for reducing loads on floating wind turbine towers caused by ocean waves. Background Technology

[0002] Floating wind turbines experience environmental disturbances from various sources, such as turbulence, aeroelastic effects, and ocean waves. Loads caused by ocean waves account for a significant portion of the overall cost of a floating wind turbine. Traditional approaches address fatigue loads at the wind turbine / floating platform interface by over-designing connecting components or curtailing the extraction of available energy from the environment, but these methods increase the complexity and cost of the floating wind turbine tower construction and operation. Summary of the Invention

[0003] One aspect relates to a method for reducing loads on a floating wind turbine caused by ocean waves. The blade pitch angle of at least one rotor blade of the floating wind turbine is adjusted to minimize the moment imbalance at the top of the platform caused by ocean wave activity.

[0004] In an exemplary embodiment, the method includes calculating an error signal based on a torque imbalance measured between a tower base moment and a thrust moment. The tower base moment is a moment generated at the top of the floating wind turbine platform due to environmental loads, and the thrust moment is a moment defined by the thrust of the rotor blades of the floating wind turbine, which is measured on the shaft of the floating turbine near the top of the platform.

[0005] In an exemplary embodiment, the method includes filtering an error signal using a bandpass filter within a frequency range attributable to ocean wave activity to obtain a filtered error signal. The filtering separates wave excitation frequencies from the error signal, the wave excitation frequencies being within a frequency range defined by the ocean wave spectrum. The blade pitch angle is adjusted based on a pitch offset signal converted from the filtered error signal. The pitch offset signal is converted from the filtered error signal by calculating the difference between the actual pitch angle value of at least one rotor blade and the desired blade pitch angle of at least one rotor blade, wherein the difference defines the pitch offset signal.

[0006] On the other hand, a method for reducing loads caused by ocean waves on a floating wind turbine is provided. The processor of the computing system calculates an error signal defined by the torque imbalance between the tower base moment and the thrust moment of the floating wind turbine. The error signal is filtered within a frequency range attributable to ocean wave activity to eliminate frequencies that do not contribute to the error signal but are not attributable to ocean wave activity, thereby generating a filtered error signal. The filtered error signal is converted into a pitch offset signal. The blade pitch angle of at least one rotor blade of the floating wind turbine is adjusted based on the pitch offset signal.

[0007] In an exemplary embodiment, the error signal includes frequencies attributable to one or more of the following: turbulence caused by winds above sea level, ocean wave activity, ocean current variability, vibrations caused by eddies, structural resonance, power grid phenomena, and normal turbine operation. Furthermore, the error signal is filtered using a bandpass filter tuned to filter out frequencies above or below the frequency range attributable to ocean wave activity; the frequency range attributable to ocean wave activity is defined by the ocean wave spectrum in the range of approximately 0.03 Hz to 0.25 Hz.

[0008] In an exemplary embodiment, converting the filtered error signal into a pitch offset signal includes calculating the difference between the actual pitch angle value of at least one rotor blade and the desired blade pitch angle of at least one rotor blade, wherein the difference defines the pitch offset signal. For example, the pitch offset signal is calculated from the filtered error signal according to a function having the following characteristics: a term proportional to the current value of the filtered error signal; a term proportional to the time integral of the filtered error signal; and a term proportional to the time derivative of the filtered error signal.

[0009] On the other hand, a computer system is involved, comprising: a processor; a memory device coupled to the processor; a pitch controller coupled to the processor; and a computer-readable storage device coupled to the processor, wherein the storage device contains program code executable by the processor via the memory device to implement a method for reducing loads caused by ocean waves on a floating wind turbine tower.

[0010] On the other hand, it relates to a computer program product comprising a computer-readable hardware storage device storing computer-readable program code, the computer-readable program code including an algorithm that, when executed by a computer processor of a computing system, implements a method for reducing loads on floating wind turbine towers caused by ocean waves.

[0011] The foregoing and other features of the construction and operation will be more readily understood and fully appreciated from the following detailed description taken in conjunction with the accompanying drawings. Attached Figure Description

[0012] Some of the embodiments will be described in detail with reference to the following figures, wherein the same reference numerals denote the same components, wherein:

[0013] Figure 1 A schematic diagram of a floating wind turbine according to an embodiment of the present invention is depicted;

[0014] Figure 2 A block diagram of a blade pitch control system according to an embodiment of the present invention is depicted;

[0015] Figure 3 A block diagram of an alternative blade pitch control system according to an embodiment of the present invention is depicted;

[0016] Figure 4 An embodiment of the invention is depicted. Figure 1 A schematic diagram of a floating wind turbine, showing the thrust torque and the tower base torque;

[0017] Figure 5 The filtered error signal is graphically depicted so that only frequencies within the ocean wave spectrum pass through, while frequencies outside the ocean wave spectrum are blocked.

[0018] Figure 6 A flowchart is depicted for a method for reducing loads caused by ocean waves on a floating wind turbine according to an embodiment of the present invention;

[0019] Figure 7 A flowchart depicts the conversion steps of a method for reducing loads caused by ocean waves on a floating wind turbine according to an embodiment of the present invention;

[0020] Figure 8 A schematic block diagram depicting blade pitch angle adjustment in a method for reducing loads caused by ocean waves on a floating wind turbine, according to an embodiment of the present invention; and

[0021] Figure 9 A description of an embodiment of the invention for use Figure 1-5 A block diagram of the computer system for the blade pitch control system, which is capable of reducing... Figure 6-8 Methods for handling loads caused by ocean waves on floating wind turbines. Detailed Implementation

[0022] A detailed description of embodiments of the disclosed apparatus and methods described below is presented herein by way of example rather than limitation, with reference to the accompanying drawings. While certain embodiments are shown and described in detail, it should be understood that various changes and modifications may be made without departing from the scope of the appended claims. The scope of this disclosure is by no means limited to the number of constituent components, their materials, their shapes, their relative arrangements, etc., and is disclosed merely as an example of embodiments of this disclosure.

[0023] As a preamble to the detailed description, it should be noted that, as used in this specification and the appended claims, the singular forms “a,” “an,” and “the” include plural indicators unless the context clearly specifies otherwise.

[0024] In short, floating wind turbine towers are subjected to loads from numerous environmental sources, such as wind and ocean waves. Ocean wave activity, particularly that experienced by the underwater portion of the floating wind turbine platform top, generates loads that must be offset for the proper operation and structural integrity of the floating wind turbine. Embodiments of the present invention reduce the floating platform loads caused by ocean waves by adjusting and / or modifying the blade pitch angle of one or more rotor blades of the floating wind turbine, rather than offsetting these loads by designing a more robust platform top that increases cost, weight, and structural complexity. Adjusting the blade pitch angle of the rotor blades can mitigate the bending moment at the base of the floating wind turbine tower and fatigue loads at the floating platform interface. For example, adjusting the blade pitch angle of at least one rotor blade can minimize the moment imbalance at the platform top of the floating wind turbine tower caused by ocean wave activity.

[0025] The moment imbalance at the base of a floating wind turbine tower is the difference between the measured tower base moment and the moment generated by the rotor thrust (i.e., thrust moment) measured at the shaft or, alternatively, at the blade root. The tower base moment is the moment generated at the top of the floating wind turbine tower platform due to environmental loads, while the thrust moment is the moment defined by the thrust of the rotor blades of the floating wind turbine tower, measured at a location near the shaft of the floating turbine tower, close to the platform top. The difference between the tower base moment and the thrust moment is calculated by the control mechanism (i.e., the computing system) and output as an error signal. Because the error signal contains both disturbances related to ocean activity and other disturbances not caused by ocean activity, it is filtered by the control mechanism to separate the frequencies related to ocean activity, called the "wave excitation frequencies." The error signal is filtered using filters such as bandpass filters within a frequency range defined by the ocean wave spectrum, which is the range of frequencies in which ocean waves are observed to exist. Thus, the filtered error signal focuses only on the effects of ocean wave activity. The unbalanced, filtered error signal is then converted into a pitch offset signal, which is used by the control mechanism to adjust the blade pitch angle of the rotor blades. Thus, the torque imbalance is counteracted by the blade pitch control, causing the torque at the base of the tower and the thrust torque to cancel each other out, thereby reducing and / or eliminating the load on the platform top of the floating wind turbine tower caused by ocean waves.

[0026] Now refer to the attached diagram, Figure 1 A schematic diagram of a floating wind turbine 1 according to an embodiment of the present invention is depicted. The floating wind turbine 1 includes one or more rotor blades 5 connected to a hub 6 of the floating wind turbine 1. The hub 6 is connected to a nacelle 3 located at the top of a wind turbine tower 4. The wind turbine tower 4 can be constructed in multiple sections, such as tower section 9 and tower section 10, or it can be a single tower section. The tower 4 extends from the nacelle 3 to a transition section 7; the location where the bottom 8 of the tower intersects with the top 1 of the platform is referred to as the transition section or transition portion 7. A platform hull 12 is located near or at the water surface and extends below the water surface. The platform hull 12 is designed to float in the water while supporting the floating wind turbine 1 at an offshore location. Although in Figure 1 The diagram schematically shows a single foundation structure, but the platform hull 12 can be constructed from other known configurations. For example, multiple foundation structures configured to support a floating wind turbine tower 1 in the ocean, a semi-submersible platform, or a tension leg platform (TLP).

[0027] The floating wind turbine 1 is subjected to loads caused by wave activity and other environmental factors. In particular, ocean waves exert forces on the platform top 11, which, if not properly mitigated, leads to undesirable performance of the floating wind turbine 1. A computing system, such as a pitch control mechanism, is operatively coupled to the floating wind turbine tower 1 for adjusting and / or controlling the blade pitch angle of the rotor blades. In a first exemplary embodiment, the computing system is one or more remote servers serving components of the floating wind turbine 1, such as an onboard pitch controller. In a second exemplary embodiment, the computing system is an onboard computer located within the floating wind turbine 1. The computing system includes components that are executed remotely and on-site within the floating wind turbine. For example, a low-level controller responsible for making fast and fundamental decisions that affect the second-by-second performance of motors / hydraulic devices / etc. can be implemented on a floating wind turbine because communication delays / dropouts / failures in the network will require the turbine to be shut down, while the software runs on a remote server located at the wind farm, which performs some high-level processing and decision-making (e.g., deciding whether to enable / disable different functions based on weather conditions, etc.).

[0028] This calculation system reduces the floating wind turbine tower load caused by ocean waves by adjusting the blade pitch angle of at least one rotor blade 5 of the floating wind turbine 1, thereby minimizing the moment imbalance at the transition piece 7 between the platform top 11 and the tower bottom 8 of the floating wind turbine 1 caused by ocean wave activity. Furthermore, the calculation system is part of the blade pitch control system described in detail below.

[0029] Figure 2 A block diagram of a blade pitch control system 100 according to an embodiment of the present invention is depicted. The blade pitch control system 100 is a system for adjusting the blade pitch angle of the rotor blades of a floating wind turbine tower to counteract the torque imbalance of the floating wind turbine caused by ocean wave activity. The blade pitch control system 100 may alternatively be referred to as a pitch control mechanism, a load reduction system, a floating wind turbine tower system, a pitch adjuster for a floating wind turbine, a load reduction system, and the like. Furthermore, the blade pitch control system 100 includes a computing system 120. The computing system 120 may be a computer system, a computer, a server, one or more servers, a back-end computing system, and the like. Figure 2 The blade pitch control system 100 depicted in the figure relates to an embodiment in which the computing system 120 is located away from the floating wind turbine tower 1.

[0030] Furthermore, the blade pitch control system 100 includes a floating wind turbine 1 and a bandpass filter 113 communicatively coupled to a computing system 120 via a network 107. For example, information / data is transmitted to and / or received from the floating wind turbine tower 1 and the bandpass filter 113 via the network 107. In an exemplary embodiment, the network 107 is a cloud computing network. Further embodiments of the network 107 refer to a group of two or more computer systems linked together. The network 107 includes any type of computer network known to those skilled in the art. Examples of the network 107 include LANs, WANs, campus area networks (CANs), home area networks (HANs), metropolitan area networks (MANs), enterprise networks, cloud computing networks (physical or virtual), such as the Internet, cellular communication networks such as GSM or CDMA networks, or mobile communication data networks. In one embodiment, the architecture of the network 107 is peer-to-peer, while in another embodiment, the network 107 is organized as a client / server architecture.

[0031] In an exemplary embodiment, in addition to the computing system 120, the network 107 further includes connections to one or more network-accessible knowledge bases 114, which are network repositories containing information about floating wind turbines, blade pitch angle data, load data, environmental condition data, etc., network repositories connected to the network 107 that are considered nodes of the network 107, or other systems. In embodiments where the computing system 120 or the network repository allocates resources for use by other nodes of the network 107, the computing system 120 and the network-accessible knowledge base 114 are referred to as servers.

[0032] The network-accessible knowledge base 114 is a data collection area on network 107, which backs up and stores all data transmitted back and forth between nodes of network 107. For example, a network repository is a data center that stores and catalogs information about floating wind turbines, blade pitch angle data, load data, environmental condition data, and similar data to generate both historical and predictive reports on blade pitch angle adjustments. In an exemplary embodiment, the data collection center housing the network-accessible knowledge base 114 includes an analysis module capable of analyzing each piece of data stored in the network-accessible knowledge base 114. Furthermore, the computing system 120 may be integrated with or be part of the data collection center housing the network-accessible knowledge base 114. In an alternative embodiment, the network-accessible knowledge base 114 is a local repository connected to the computing system 120.

[0033] The floating wind turbine 1 includes at least one rotor blade sensor 110, at least one transition or platform top sensor 111, and a pitch controller 112. The transition sensor 111 may be located at the tower bottom 8 or the platform top 11. The rotor blade sensor 110 measures the thrust of the rotor blades, and the platform top / transition sensor 111 measures the forces acting on the platform top 11 and / or transition 7 of the floating wind turbine 1. Examples of sensors 110 and 111 include strain gauges, fiber Bragg grating sensors (FBGS), accelerometers, piezoelectric sensors, and the like. The pitch controller 112 is responsible for sending commands to the rotor blades to adjust the blade pitch angle. In an exemplary embodiment, the pitch controller 112 is a proportional-integral-derivative (PID) controller. The pitch controller 112 includes other modules for controlling pitch damage attenuation, speed regulation, etc.

[0034] Figure 3 A block diagram of an alternative blade pitch control system 100' according to an embodiment of the present invention is depicted. Figure 3 The blade pitch control system 100' depicted in the figure relates to an embodiment in which the computing system 120 is an onboard computer of the floating wind turbine tower 1.

[0035] The computing system 120 of the blade pitch control systems 100, 100' is equipped with a memory device 142 for storing various data / information / code, and a processor 141 for performing tasks associated with the blade pitch control systems 100, 100'. A blade pitch angle adjustment application 130 is loaded into the memory device 142 of the computing system 120. The blade pitch angle adjustment application 130 may be an interface, application, program, module, or a combination of modules. In an exemplary embodiment, the blade pitch angle adjustment application 130 is a software application running on the computing system 120.

[0036] Return to reference Figure 2 The blade pitch angle adjustment application 130 of the computing system 120 includes an error signal module 131, a filter module 132, a conversion module 133, and an adjustment module 134. A "module" refers to a hardware-based module, a software-based module, or a combination of hardware and software. Hardware-based modules include independent components such as chipsets, dedicated circuits, and one or more memory devices, while software-based modules are part of or linked to program code containing specific programming instructions loaded into the memory devices of the computing system 120. Modules (whether hardware, software, or a combination thereof) are designed to implement or perform one or more specific functions or routines.

[0037] Error signal module 131 includes one or more components of hardware and / or software program code for calculating an error signal defined by the torque imbalance between the tower base torque and the thrust torque of the floating wind turbine. Figure 4 An embodiment of the invention is depicted. Figure 1 A schematic diagram of a floating wind turbine 1, showing the thrust torque M. T and the moment M at the bottom of the tower B The moment M at the base of the tower B The moment is generated at the transition section 7 / platform top 11 of the floating wind turbine 1 due to environmental loads. The tower base moment M... B The value is measured by the platform top / transition sensor 111, or can be estimated based on other data received from other sensors, such as strain gauges. Thrust torque M T It is a torque defined at the tower section 4 of the floating wind turbine 1, near the platform top 11 and transition piece 7, which is based on the thrust T of the rotor blades of the floating wind turbine measured by the rotor blade sensor 110. F Calculate the thrust torque M. T Defined as thrust T F Multiply by the distance or height H of the tower measured from transition piece 7. Ref (i.e. H) Ref ×T F ).

[0038] Therefore, torque imbalance is the thrust torque M T and the moment M at the bottom of the tower B The difference between them. The error signal ε is received or obtained by the calculation system 120 in response to the error signal module 131. F and the moment M at the bottom of the tower B The value is calculated according to the following equation: ε = M B -(H Ref ×T F The error signal ε includes frequencies attributable to various disturbances, including ocean wave activity. For example, the error signal includes frequencies attributable to one or more of the following: turbulence caused by winds above sea level, ocean wave activity, ocean current variability, vibrations caused by eddies, structural resonance, power grid phenomena, normal turbine operation, and the like. Frequencies in the error signal not attributable to ocean wave activity are unnecessary for the purpose of canceling out torque imbalances, particularly those caused by ocean wave activity. Therefore, unwanted signals are filtered out from the error signal.

[0039] Filter module 132 includes one or more components of hardware and / or software program code for filtering error signals within a frequency range attributable to ocean wave activity to eliminate frequencies that do not contribute to the error signals and are not attributable to ocean wave activity. Frequency not attributable to ocean wave activity is filtered out to ensure that the calculated error signal ε and the resulting blade pitch offset (Δ) calculated by calculation system 120 are accurate. β Specifically responsive to ocean wave activity, while remaining relatively insensitive to various other disturbances considered negligible or compensated for by other modules of the blade pitch control system. Filtering performed by filter module 132 generates a filtered error signal. Filter module 132 filters the error signal using a bandpass filter tuned to filter out frequencies above or below the frequency range attributable to ocean wave activity. The frequency range used corresponds to the ocean wave spectrum. In an exemplary embodiment, the ocean wave spectrum is in the range of approximately 0.03 Hz to 0.25 Hz. Therefore, filter module 132 separates the wave excitation frequency from the error signal, which is within the frequency range defined by the ocean wave spectrum, such as... Figure 5 As shown schematically in the diagram. Figure 5 The error signal is graphically depicted, having been filtered so that only frequencies within the ocean wave spectrum pass through, while frequencies outside the ocean wave spectrum are blocked. In the illustrated embodiment, the ocean wave spectrum is limited to the left frequency f. L Limits and right frequency limit f R Between; the center frequency is shown as f C B is the passband, i.e., the frequency range through which the filter passes. It is set to the ocean wave spectrum, with 0 dB being pure passband and -3 dB being the point where the input signal is considered to be completely filtered out. This is therefore output as a filtering error signal by the filter module 132. The filtering error signal is then converted into a pitch offset signal.

[0040] Return to reference Figure 2 The conversion module 133 includes one or more components of hardware and / or software program code for converting the filtered error signal into a pitch offset signal. For example, the conversion module 133 converts the filtered error signal into a representation of the actual blade pitch angle to be applied. β The difference in pitch offset signal (Δ) βIn other words, the conversion module 133 converts the filtered error signal into a pitch offset signal by calculating the difference between the actual pitch angle of at least one rotor blade and the desired blade pitch angle of at least one rotor blade, where this difference defines the pitch offset signal. For example, if one of the blades currently has a blade pitch angle of 3°, and the filtered error signal suggests that the blade pitch angle of the blade should be adjusted to 3.25°, then the offset pitch signal is a blade pitch of 0.25°. Each rotor blade can have a different actual blade pitch angle, therefore the conversion of the filtered error signal to the pitch offset signal can have different values ​​relative to each blade.

[0041] The conversion from error signal to pitch offset is based on three factors: the value of the error itself, and the amount by which it is scaled. k p (Scale); The degree to which the error accumulates over time using the time integral of the error signal, which scales a certain quantity. k i (Integral); and the degree to which the value of the error changes when approximated by the time derivative of the error signal, which scales a certain quantity. k d (Derivative). Scale k p , k i , k d Used to adjust each item for pitch offset Δ β The degree of contribution of the final adjustment:

[0042]

[0043] In an exemplary embodiment, the pitch offset signal is calculated from the filtered error signal based on a function having terms proportional to the current value of the filtered error signal, the time integral of the filtered error signal, and the time derivative of the filtered error signal.

[0044] The adjustment module 134 includes one or more components of hardware and / or software program code for adjusting the blade pitch angle of at least one rotor blade of the floating wind turbine based on a pitch offset signal. For example, the adjustment module 134 sends a command to the pitch controller 112 of the floating wind turbine 1 to adjust the blade pitch angle of one or more rotor blades. Continuing the example above, if the pitch offset signal is 0.25°, the adjustment module 134 sends a command to the pitch controller 112 to adjust the blade pitch angle of one of the blades by 0.25°. The adjustment module 134 adjusts the blade pitch angle of each rotor blade independently of the other blades. In an exemplary embodiment, the adjustment module 134 adjusts the blade pitch angle of all rotor blades based on a specific blade-specific pitch offset signal. In another exemplary embodiment, the adjustment module 134 adjusts the blade pitch angle of only one or two of the three rotor blades based on a pitch offset signal specific to the selected blade for adjustment.

[0045] The various tasks and specific functions of the modules of computing system 120 can be performed by additional modules or combined into one or more other modules to reduce the number of modules. Furthermore, embodiments of the computer or computer system 120 include dedicated, non-general-purpose hardware and circuitry (i.e., dedicated discrete non-general-purpose analog, digital, and logic-based circuitry) (independently or in combination) specifically designed to perform only the methods of the present invention. The dedicated discrete non-general-purpose analog, digital, and logic-based circuitry includes proprietary, specially designed components (e.g., application-specific integrated circuits, such as, for example, application-specific integrated circuits (ASICs) designed to implement only the methods of the present invention).

[0046] Furthermore, the blade pitch control systems 100 and 100' utilize specific hardware, such as pitch controllers, wind turbine components, and sensors, to calculate pitch offset signals to counteract the torque caused by ocean wave activity of the floating wind turbine. The rotor blades of the floating wind turbine are physically moved to change the blade pitch angle, minimizing torque imbalance on the floating wind turbine tower. This is a practical application of the technology, using the blade pitch control systems 100 and 100' to counteract torque imbalance instead of modifying the structural configuration of the platform hull and floating wind turbine tower. This technology improves the efficiency of the floating wind turbine and allows for the design of floating wind turbines with lower material costs.

[0047] Now for reference Figure 6 The document depicts a flowchart of a method 200 for reducing loads caused by ocean waves on a floating wind turbine according to an embodiment of the present invention. An embodiment of method 200 or algorithm may be implemented to utilize... Figure 1-5The blade pitch control systems 100 and 100' described herein use one or more computer systems to reduce loads on floating wind turbines caused by ocean waves, as follows: Figure 9 The general definition and more specifically by Figure 2-3 As defined in the specific implementation.

[0048] According to an embodiment of the present invention, an embodiment of method 200 for reducing loads caused by ocean waves on a floating wind turbine can receive shaft thrust T. F and the moment M at the bottom of the tower B Value begins. Shaft thrust T F and tower moment M B The value can be measured by one or more sensors on the floating wind turbine, with the sensor data transmitted to the computing system 120. Shaft thrust T F The length or height H of the tower, measured between the rotor blades and the transition section 7 where the tower section intersects (meet) the platform top 111. ref Used in combination to calculate thrust torque M T Step 201: Calculate the moment M at the bottom of the tower. B and thrust torque M T The error between the two. The output of step 201 is error signal 21, which represents the torque imbalance occurring at the transition member 7 of the floating wind turbine tower 1. Step 202 filters error signal 21 within the frequency range where ocean energy is concentrated to eliminate unwanted frequencies associated with disturbances not attributable to ocean wave activity. In an exemplary embodiment, a custom bandpass filter is used, which is configured to separate the wave excitation frequencies from error signal 21, which are within the frequency range defined by the ocean wave spectrum. The output of step 202 is filtered error signal 22. Filtered error signal 22 is a signal with frequencies representing torque, although other units may be used depending on the custom bandpass filter used. Step 203 converts the filtered error signal 22.

[0049] Figure 7A flowchart depicts a conversion step 203 of a method 200 for reducing loads caused by ocean waves on a floating wind turbine according to an embodiment of the present invention. Step 301 determines the actual blade pitch angle of at least one rotor blade. Using a filtered error signal 22, step 302 determines the desired blade pitch angle of at least one rotor blade. Step 303 calculates the difference between the actual blade pitch angle of at least one rotor blade and the desired blade pitch angle of at least one rotor blade to obtain a pitch offset signal 23 for adjusting the blade pitch angle of at least one rotor blade. Conversion step 203 can be performed on one, some, or all of the rotor blades. The output of conversion step 203 is the pitch offset signal 23 and potential pitch offset signals for additional rotor blades 23', 23'". (Return to Reference) Figure 6 Step 204 adjusts the blade pitch angle of one or more rotor blades according to the pitch offset signals 23, 23', 23"

[0050] Figure 8 A schematic block diagram depicts blade pitch angle adjustment in a method 200 for reducing loads caused by ocean waves on a floating wind turbine according to an embodiment of the present invention. Pitch offset signals 23, 23', 23" are transmitted to a pitch controller of the floating wind turbine that controls the pitch of the rotor blades. The pitch controller adjusts the blade pitch angle of "blade 1" according to the pitch offset signal 23. The pitch controller adjusts the blade pitch angle of "blade 2" according to the pitch offset signal 23'. The pitch controller adjusts the blade pitch angle of "blade 3" according to the pitch offset signal 23". For example, if the pitch offset signal 23 is 0.24°, then "blade 1" is adjusted by 0.24° from its current blade pitch angle position. Similarly, if the pitch offset signal 23' is 0.37° and the pitch offset signal 23" is 0.15°, then "blade 2" is adjusted by 0.37° from its current blade pitch angle position, and "blade 3" is adjusted by 0.15° from its current blade pitch angle position.

[0051] Therefore, method 200 counteracts the moment imbalance of the floating wind turbine tower by adjusting the blade pitch control, so that the moment at the bottom of the tower and the thrust moment cancel each other out, thereby reducing and / or eliminating the load transfer from the platform hull 12 to the platform top 11, especially caused by ocean waves.

[0052] Figure 9 A description of an embodiment of the invention for use Figure 1-5 A block diagram of the computer system for the blade pitch control system 100, 100', which is capable of reducing the... Figure 6-8A method for handling loads caused by ocean waves on a floating wind turbine. Computer system 500 typically includes a processor 591, an input device 592 coupled to the processor 591, an output device 593 coupled to the processor 591, and memory devices 594 and 595, each coupled to the processor 591. Input devices 592, output devices 593, and memory devices 594 and 595 may each be coupled to the processor 591 via a bus. The processor 591 can perform calculations and control the functions of computer system 500, including executing instructions for tools and programs included in computer code 597, which are capable of using... Figure 1-5 The blade pitch control system 100, 100' is controlled by Figure 6-8 The embodiments described herein implement a method for reducing loads caused by ocean waves on a floating wind turbine, wherein instructions for computer code 597 can be executed by processor 591 via memory device 595. Computer code 597 may include software or program instructions that implement one or more algorithms for implementing the method for reducing loads caused by ocean waves on a floating wind turbine, as described in detail above. Processor 591 executes computer code 597. Processor 591 may include a single processing unit, or may be distributed across one or more locations (e.g., on a client and a server).

[0053] Memory device 594 may include input data 596. Input data 596 includes any input required by computer code 597. Output device 593 displays the output from computer code 597. Either or both of memory devices 594 and 595 may be used as a computer-usable storage medium (or program storage device) containing a computer-readable program and / or storing other data, wherein the computer-readable program includes computer code 597. Typically, the computer program product (or alternatively, the article of manufacture) of computer system 500 may include said computer-usable storage medium (or said program storage device).

[0054] Memory devices 594 and 595 include any known computer-readable storage medium, including those described in detail below. In one embodiment, cache memory elements of memory devices 594 and 595 may provide temporary storage for at least some program code (e.g., computer code 597) to reduce the number of times code must be retrieved from mass storage when executing instructions of computer code 597. Furthermore, similar to processor 591, memory devices 594 and 595 may reside in a single physical location (including one or more types of data storage devices) or be distributed across multiple physical systems in various forms. Additionally, memory devices 594 and 595 may include data distributed across, for example, a local area network (LAN) or a wide area network (WAN). Furthermore, memory devices 594 and 595 may include an operating system (not shown) and may include… Figure 9 Other systems not shown.

[0055] In some embodiments, the computer system 500 may be further coupled to an input / output (I / O) interface and a computer data storage unit. The I / O interface may include any system for exchanging information to or from input device 592 or output device 593. Input device 592 may in particular be a keyboard, mouse, etc., or in some embodiments a touchscreen of a computing device. Output device 593 may in particular be a printer, plotter, display device (such as a computer screen), magnetic tape, removable hard disk, floppy disk, etc. Memory devices 594 and 595 may in particular be hard disks, floppy disks, magnetic tapes, optical storage devices such as CDs or DVDs, dynamic random access memory (DRAM), read-only memory (ROM), etc. A bus may provide a communication link between each of the components in the computer 500 and may include any type of transmission link, including electrical, optical, wireless, etc.

[0056] The I / O interface allows computer system 500 to store information (e.g., data or program instructions, such as program code 597) on and retrieve information from a computer data storage unit (not shown). The computer data storage unit includes known computer-readable storage media, as described below. In one embodiment, the computer data storage unit may be a non-volatile data storage device, such as a disk drive (i.e., a hard disk drive) or an optical disk drive (e.g., a CD-ROM drive that holds CD-ROM discs). In other embodiments, the data storage unit may include a knowledge base or data repository 125, such as... Figure 2 As shown in the image.

[0057] As those skilled in the art will recognize, in a first embodiment, the invention may be a method; in a second embodiment, the invention may be a system; and in a third embodiment, the invention may be a computer program product. Any component of the embodiments of the invention may be deployed, managed, serviced, etc., by a service provider that provides deployment or integration of computing infrastructure and portable computing devices for assisted learning. Therefore, embodiments of the invention disclose a process for supporting a computer infrastructure, wherein the process includes providing at least one support service for integrating, hosting, maintaining, and deploying at least one of computer-readable code (e.g., program code 597) in a computer system (e.g., computer system 500) including one or more processors 591, wherein the processor(s) execute instructions contained in the computer code 597 such that the computer system reduces loads caused by ocean waves on a floating wind turbine. Another embodiment discloses a process for supporting a computer infrastructure, wherein the process includes integrating computer-readable program code into a computer system 500 including a processor.

[0058] The integration step includes storing program code in a computer-readable storage device of computer system 500 using a processor. When executed by the processor, the program code implements a method for reducing loads caused by ocean waves on a floating wind turbine. Therefore, this invention discloses a process for supporting, deploying, and / or integrating computer infrastructure, integrating, hosting, maintaining, and deploying computer-readable code into computer system 500, wherein the code integrated with computer system 500 is capable of executing a method for reducing loads caused by ocean waves on a floating wind turbine.

[0059] The computer program product of the present invention includes one or more computer-readable hardware storage devices storing computer-readable program code, the program code comprising instructions executable by one or more processors of a computer system to implement the method of the present invention.

[0060] The computer system of the present invention includes one or more processors, one or more memories, and one or more computer-readable hardware storage devices, wherein the one or more hardware storage devices contain program code executable by the one or more processors via the one or more memories to implement the method of the present invention.

[0061] This invention can be a system, method, and / or computer program product at any level of integration of possible technical details. The computer program product may include a computer-readable storage medium (or medium) having computer-readable program instructions thereon for causing a processor to execute aspects of the invention.

[0062] Computer-readable storage media can be tangible devices capable of retaining and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital universal disc (DVD), memory sticks, floppy disks, mechanical encoding devices (such as punched cards or raised structures in recesses on which instructions are recorded), and any suitable combination of the foregoing. As used herein, computer-readable storage media is not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted over lines.

[0063] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to a corresponding computing / processing device via a network (e.g., the Internet, a local area network, a wide area network, and / or a wireless network), or to an external computer or external storage device. The network may include copper transmission cables, optical fiber transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to a computer-readable storage medium within the corresponding computing / processing device.

[0064] Computer-readable program instructions for performing the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, configuration data for integrated circuits, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, or the like, and procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet through an Internet service provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs) may execute the computer-readable program instructions by utilizing state information from the computer-readable program instructions to personalize the electronic circuitry for performing aspects of the invention.

[0065] Aspects of the invention have been described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0066] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / actions specified in the flowchart and / or one or more block diagram blocks. These computer-readable program instructions can also be stored in a computer-readable storage medium that can instruct a computer, programmable data processing apparatus, and / or other equipment to operate in a particular manner, such that the computer-readable storage medium storing the instructions includes an article of writing comprising instructions for implementing aspects of the functions / actions specified in the flowchart and / or one or more block diagram blocks.

[0067] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer-implemented process, such that the instructions, which execute on the computer, other programmable apparatus or other device, implement the functions / actions specified in the flowchart and / or one or more block diagram boxes.

[0068] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each box in a flowchart or block diagram may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing one or more specified logical functions. In some alternative implementations, the functions marked in the boxes may occur in a non-diagrammatical order. For example, two boxes shown consecutively may actually be executed substantially simultaneously, or the boxes may sometimes be executed in reverse order, depending on the functions involved. It will also be noted that each box in the block diagrams and / or flowcharts, and combinations of boxes in the block diagrams and / or flowcharts, may be implemented by a system based on dedicated hardware that performs the specified functions or actions or executes a combination of dedicated hardware and computer instructions.

[0069] While this disclosure has been described in conjunction with the specific embodiments outlined above, many alternatives, modifications, and variations will be apparent to those skilled in the art. Therefore, the preferred embodiments of this disclosure as set forth above are intended to be illustrative and not restrictive. Various changes may be made without departing from the spirit and scope of the invention, as claimed by the appended claims. The claims provide for the scope of the invention and should not be limited to the specific examples provided herein.

Claims

1. A method for reducing the load on a floating wind turbine caused by ocean waves, the method comprising: Adjust the blade pitch angle of at least one rotor blade of the floating wind turbine to minimize the tower base moment imbalance at the top of the platform of the floating wind turbine caused by ocean wave activity, wherein the tower base moment is a moment generated at the top of the platform of the floating wind turbine due to environmental loads. The method further includes calculating an error signal defined by the torque imbalance between the tower base torque and the thrust torque of the floating wind turbine, wherein the thrust torque is defined by the thrust of the rotor blades of the floating wind turbine. The method further includes filtering the error signal using a bandpass filter within a frequency range attributable to ocean wave activity to obtain a filtered error signal, wherein the blade pitch angle is adjusted based on a pitch offset signal converted from the filtered error signal.

2. The method according to claim 1, wherein, The filter separates the wave excitation frequency from the error signal, the wave excitation frequency being within a frequency range defined by the ocean wave spectrum.

3. The method according to claim 1, wherein, A pitch offset signal is converted from a filtered error signal by calculating the difference between the actual pitch angle of at least one rotor blade and the expected blade pitch angle of at least one rotor blade, wherein the difference defines the pitch offset signal.

4. A method for reducing loads caused by ocean waves on a floating wind turbine, the method comprising: The processor of the computing system calculates an error signal defined by the torque imbalance between the tower base moment and the thrust moment of the floating wind turbine, wherein the tower base moment is the moment generated at the top of the platform of the floating wind turbine due to environmental loads, and the thrust moment is the moment defined by the thrust of the rotor blades of the floating wind turbine. The processor filters the error signal within a frequency range attributable to ocean wave activity to eliminate frequencies that do not contribute to the error signal but are not attributable to ocean wave activity, thereby generating a filtered error signal. The processor converts the filtered error signal into a pitch offset signal; and The processor adjusts the blade pitch angle of at least one rotor blade of the floating wind turbine based on the blade pitch offset signal.

5. The method according to claim 4, wherein, Error signals include frequencies attributable to one or more of the following: turbulence caused by winds above sea level, ocean wave activity, ocean current variability, vibrations caused by eddies, structural resonance, power grid phenomena, and normal turbine operation.

6. The method according to claim 4, wherein, The error signal is filtered using a bandpass filter, which is tuned to filter out frequencies that are above or below the frequency range attributable to ocean wave activity.

7. The method according to claim 6, wherein, The frequency range attributable to ocean wave activity is defined by the ocean wave spectrum in the range of 0.03 Hz to 0.25 Hz.

8. The method according to claim 4, wherein, Converting the filtered error signal into a pitch offset signal involves calculating the difference between the actual pitch angle value of at least one rotor blade and the expected blade pitch angle of at least one rotor blade, wherein the difference defines the pitch offset signal.

9. The method according to claim 4, wherein, The pitch offset signal is calculated from the filtered error signal based on a function with the following characteristics: A term proportional to the current value of the filtered error signal; A term proportional to the time integral of the filtered error signal; and A term that is proportional to the time derivative of the filtered error signal.

10. A computer system, comprising: processor; Memory devices coupled to the processor; Pitch controller coupled to the processor; as well as A computer-readable storage device coupled to a processor, wherein the storage device contains program code executable by the processor via the memory device to implement a method for reducing loads caused by ocean waves on a floating wind turbine tower, the method comprising: The processor of the computing system calculates an error signal defined by the torque imbalance between the tower base moment and the thrust moment of the floating wind turbine, wherein the tower base moment is the moment generated at the top of the platform of the floating wind turbine due to environmental loads, and the thrust moment is the moment defined by the thrust of the rotor blades of the floating wind turbine. The processor filters the error signal within a frequency range attributable to ocean wave activity to eliminate frequencies that do not contribute to the error signal but are not attributable to ocean wave activity, thereby generating a filtered error signal. The processor converts the filtered error signal into a pitch offset signal; and The processor adjusts the blade pitch angle of at least one rotor blade of the floating wind turbine based on the blade pitch offset signal.

11. The computer system according to claim 10, wherein, The error signal is filtered using a bandpass filter, which is tuned to filter out frequencies above or below the frequency range attributable to ocean wave activity, wherein the frequency range attributable to ocean wave activity is defined by the ocean wave spectrum in the range of 0.03 Hz to 0.25 Hz.

12. The computer system according to claim 10, wherein, Converting the filtered error signal into a pitch offset signal involves calculating the difference between the actual pitch angle value of at least one rotor blade and the expected blade pitch angle of at least one rotor blade, wherein the difference defines the pitch offset signal.

13. A computer program product comprising a computer-readable hardware storage device storing computer-readable program code, the computer-readable program code including an algorithm that, when executed by a computer processor of a computing system, implements the method according to claim 4.

Images