EP4728183A1

EP4728183A1 - Controlling a floating wind turbine system based on a sea state parameter

Info

Publication number: EP4728183A1
Application number: EP24737004.2A
Authority: EP
Inventors: Bruno MARTINS CUNHA; Alexander Duncan GILES; Jesper Sandberg Thomsen; Thea VANELLI
Original assignee: Vestas Wind Systems AS
Current assignee: Vestas Wind Systems AS
Priority date: 2023-06-15
Filing date: 2024-06-14
Publication date: 2026-04-22
Also published as: KR20260023054A; WO2024255979A1; CN121569109A

Abstract

Disclosed is a method for controlling a floating wind turbine system. The floating wind turbine system comprises a floating platform, a tower mounted to the floating platform and a nacelle. The method comprises receiving, from one or more sensors of the floating wind turbine system, a signal indicative of a vertical acceleration of the floating wind turbine system. The method comprises determining, based on the received signal, a sea state parameter indicative of an oscillation of the vertical acceleration. The method comprises controlling the floating wind turbine system based on the sea state parameter.

Description

CONTROLLING A FLOATING WIND TURBINE SYSTEM BASED ON A SEA STATE PARAMETER The present disclosure pertains to the field of wind turbines and related systems. The present disclosure relates to a method for controlling a wind turbine and related electronic device. In particular, the present disclosure relates to a method for controlling a wind turbine based on a sea state parameter and related electronic device. BACKGROUND During operation of a floating wind turbine system, environmental conditions, such as sea state conditions, may affect the load acting on the floating wind turbine system. Under certain conditions, such as under severe or extreme sea state conditions, high loads may act on the wind turbine system which may eventually cause failure of the floating wind turbine system. To prevent a failure of the system, wind turbines have a control and monitoring system, that is designed to optimize the operations of the wind turbine and protect it against harm. Part of the protection mechanism involves a safety stop function where the wind turbine rotor is brought to a fast stop. Safety stops are used when there is a risk of structural damage or a severe incident. The safety stop can by itself cause structural damage or at least excessive wear of the wind turbine. SUMMARY There is a need for a method and an electronic device that allow estimation of sea conditions and enable a control of an operation of the wind turbine based on the estimated sea conditions so that a safety stop of the wind turbine due to severe sea conditions can be avoided. Accordingly, there is a need for an electronic device and a method for controlling a floating wind turbine system, which mitigate, alleviate or address the shortcomings existing and reduce the wear and the risk of structural damage of the wind turbine. Disclosed is a method for controlling a floating wind turbine system. The floating wind turbine system comprises a floating platform, a tower mounted to the floating platform and a nacelle. The method comprises receiving, from one or more sensors of the floating wind turbine system, a signal indicative of a vertical acceleration of the floating wind turbine system. The method comprises determining, based on the received signal, a sea state parameter indicative of an oscillation of the vertical acceleration. The method comprises controlling the floating wind turbine system based on the sea state parameter. Disclosed is an electronic device comprising a memory circuitry, a processor circuitry, and an interface, wherein the electronic device is configured to perform any of the methods disclosed herein. Disclosed is a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device cause the electronic device to perform any of the methods disclosed herein. Disclosed is a floating wind turbine system comprising the electronic device of the present disclosure. It is an advantage of the present disclosure that the method, the electronic device, and the computer readable storage medium enable an identification of rough sea conditions that could potentially be harmful to the floating wind turbine system. By identifying the sea state conditions appropriate measures can be taken to control the floating wind turbine system. By controlling the wind turbine based on the determined sea state parameter, the loads acting on the floating wind turbine system can be reduced, while allowing the floating wind turbine system to produce power at more severe sea state conditions in which the wind turbine would previously have initiated a safety stop. By allowing the wind turbine to continue operation the benefits of aerodynamic damping can be maintained, a lost production factor (LPF) and a risk of damage caused by a safety stop of the wind turbine can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS The above and other features and advantages of the present disclosure will become readily apparent to those skilled in the art by the following detailed description of exemplary embodiments thereof with reference to the attached drawings, in which: Fig.1 is a diagram illustrating schematically a wind farm comprising a plurality of floating wind turbine systems, Fig.2 is a flow-chart illustrating a method for controlling a floating wind turbine system according to one or more examples of this disclosure, Fig.3 is a flow-chart illustrating an example method for controlling a floating wind turbine system according to this disclosure, Fig.4 is a flow-chart illustrating an example method for controlling a floating wind turbine system according to this disclosure, Fig.5 is a block diagram illustrating an exemplary electronic device according to this disclosure, Fig.6 is an illustration of a simulation result for a power derate based on an example sea state parameter according to the current disclosure, and Fig.7 is an illustration of a simulation result for a thrust derate based on an example sea state parameter according to the current disclosure. DETAILED DESCRIPTION Various exemplary embodiments and details are described hereinafter, with reference to the figures when relevant. It should also be noted that the figures are only intended to facilitate the description of the embodiments. They are not intended as an exhaustive description of the disclosure or as a limitation on the scope of the disclosure. In addition, an illustrated embodiment needs not have all the aspects or advantages shown. An aspect or an advantage described in conjunction with a particular embodiment is not necessarily limited to that embodiment and can be practiced in any other embodiments even if not so illustrated, or if not so explicitly described. The figures are schematic and simplified for clarity, and they merely show details which aid understanding the disclosure, while other details have been left out. Throughout, the same reference numerals are used for identical or corresponding parts. Fig.1 is a diagram schematically illustrating an example wind farm 1 comprising a plurality of floating wind turbine systems 10. Each of the floating wind turbine systems comprises a floating platform 11, a tower 12 mounted to the floating platform 11 and a nacelle. The nacelle may comprise power electronics and a rotor 14 comprising a plurality of rotor blades 15. Typically, the rotor comprises three rotor blades, but the number may vary. An electronic device 30, such as a controller, may form part of the floating wind turbine systems 10 or may be external to the floating wind turbine systems 10. The electronic device 30 may be seen as an electronic device, such as a controller, configured to control operations of the floating wind turbine systems 10. The floating platform 11 is configured to float in water, and may follow the movements of the water, such as of waves. The loads acting on the floating wind turbine system are influenced on site specific environmental conditions (such as wind conditions, and/or sea state conditions). Rough sea state conditions may cause extreme loads acting on the floating wind turbine system 10, such as on the bottom of the tower 12, which can lead to structural damage and failure of the floating wind turbine system 10. To prevent a failure of the floating wind turbine system, the floating wind turbine system may be configured to perform a safety stop function where the wind turbine rotor is brought to a fast stop. The safety stop can however by itself cause structural damage or at least excessive wear of the wind turbine. The present disclosure provides methods, electronic devices and floating wind turbine systems that enable prediction of a sea state. The sea state may be predicted based on a sea state parameter determined based on a sensor signal indicative of a vertical acceleration of the floating wind turbine system. The sensor signal may be detected using one or more sensors of the floating wind turbine system. The sensor signal may be compared with a sea state threshold value to determine the sea state parameter. The sea state parameter may be indicative of one or more of a normal sea state (NSS), a severe sea state (SSS) and an extreme sea state (ESS), defined in relation to the severeness of the sea state and which are cases that are part of certification of a floating wind turbine and are drivers for extreme loads on the tower. The roughness of the sea states increases from normal sea state to severe sea state to extreme sea state. Based on the sea state parameter a floating wind turbine system, can be controlled, such as by controlling a power, a speed and/or a thrust of the floating wind turbine system. For example, if the sea state parameter is indicative of SSS and/or ESS, the speed, the power and/or the thrust of the floating wind turbine may be derated based on the sea state parameter. The present disclosure thus provides a method allowing a differentiation of the NSS from SSS and ESS, and an adaption of control parameters in these harsher environments without affecting the operation under normal scenarios, such as NSS, where the floating wind turbine system is expected to be producing energy at its rated power. Furthermore, even for normal sea states, the method can be used to mitigate loads by targeting larger waves that may be concerning for the structural rigidity of the floating wind turbine system. The sea states may be predefined sea states according to classification and certification standards for floating offshore wind turbines (FOWT). The sea states are indicative of marine conditions in which the floating wind turbine system operates. The sea states may be determined based on wave conditions of the sea. The sea states may be given in terms of wave height distribution. The sea states may be defined by two parameters, such as a wave height and a wave period. Severe sea states are characterized by higher wave heights and larger wave periods compared to the normal sea state. The normal sea state corresponds to a normal wave height (NWH) distribution. The severe sea state corresponds to a severe wave height (SWH) distribution, and to a maximum wave height for which the floating wind turbine system is configured to produce electricity. The severe sea state is characterized by higher wave heights and larger wave periods then the normal sea state. The extreme sea state corresponds to an extreme wave height (EWH), such as to a wave height associated to extreme conditions. The extreme sea state is characterized by higher wave heights and larger wave periods then the normal sea state and the severe sea state. By being able to estimate the sea states, the floating wind turbine system may be controlled, for example based on the sea state parameter, continue to produce power during the harsher sea states, such as during SSS and ESS. Since the floating wind turbine system does not stop producing power, but rather adapts to the estimated sea state, the benefits of aerodynamic damping may be kept, a lost production factor (LPF) may be reduced and the risk of damage to the floating wind turbine system due to a hard shutdown can be reduced. In one or more examples herein, the floating wind turbine system may comprise a power limit control function and/or a speed limit control function executed by a controller of the floating wind turbine for derating a power and/or speed of the turbine in case turbulence increases. According to one or more examples of the current disclosure, an activation of the power limit control function and/or speed limit control function may be triggered based on the estimated sea state, such as based on the sea state parameter. The power limit control function and/or speed limit control function may be configured to set a set point for speed, power and/or blade pitch of the floating wind turbine. In one or more examples herein, the floating wind turbine system may comprise a thrust limit control function executed by a controller of the floating wind turbine, such as by a variable thrust limiter (VTL), for derating a thrust of the floating wind turbine based in case turbulence increases. In one or more example methods of the current disclosure, the sea state parameter is used to thrust derate the floating wind turbine system. A maximum thrust, such as a maximum thrust setpoint or a variable thrust control variable, of the floating wind turbine system, may be updated based on the sea state parameter, for example by multiplying the sea state parameter with a maximum thrust reference parameter, such as a maximum thrust reference parameter obtained from the thrust limit control function. In one or more example methods, a new maximum value for the thrust may be determined based on the current sea state, such as based on the sea state parameter, and using the minimum value of the maximum thrust reference parameter and the new maximum value for the thrust based on the current sea state for controlling the floating wind turbine. In one or more example methods disclosed herein, the sea state parameter may be used to define a threshold from which a control function, such as a thrust limit control function safe mode, is activated. Fig.2 shows a flow diagram of an example method 100 for controlling a floating wind turbine system according to the disclosure. The method may be performed by an electronic device, such as a controller disclosed herein, such as the electronic device 300 of Fig.3. The floating wind turbine system comprises a floating platform, a tower mounted to the floating platform and a nacelle. The method 100 comprises receiving S101, from one or more sensors of the floating wind turbine system, a signal indicative of a vertical acceleration of the floating wind turbine system. The signal indicative of the vertical acceleration may be used to estimate wave induced motions in the floating platform. The wave induced motions may be indicative of different sea states. In other words, the signals received from the sensors of the floating wind turbine may be used to estimate the sea conditions, such as the sea states, acting on the floating wind turbine system. The vertical acceleration can herein be seen as an acceleration in a vertical direction of the tower, such as in a longitudinal direction of the tower, of the floating wind turbine system in a coordinate system of the wind turbine. The signal indicative of the vertical acceleration is substantially decoupled from wind turbine dynamics, thereby providing a much cleaner signal to determine a movement of the floating platform and thus a sea state. The one or more sensors may be one or more acceleration sensors located in the tower, the nacelle and/or at the floating platform of the floating wind turbine system. The sensor signal may be an acceleration signal from the one or more acceleration sensors and may be indicative of the vertical acceleration of the floating wind turbine system. In one or more example methods, the method 100 comprises filtering S103 the signal to provide a filtered signal. In one or more example methods, filtering S103 comprises applying S103A a high pass filter to filter out one or more of a gravity component and a natural frequency of the floating platform from the signal indicative of the vertical acceleration of the floating wind turbine system. In one or more example methods, filtering S103 comprises applying S103B a notch filter to filter out a tower frequency, such as from the signal indicative of the vertical acceleration of the floating wind turbine system. The tower frequency may be filtered out since the tower frequency is not driven by the sea state conditions. The high pass filter and/or the notch filter may be applied to the received signal indicative of the vertical acceleration of the floating wind turbine system. The vertical acceleration of the floating wind turbine system is much more impacted by the motion of the floating platform than by turbine operations. Therefore, by removing the gravity component (such as through the high pass filter) and/or the coupled mode, such as the tower frequency (such as through a notch filter), the output is a filtered signal that is representative of the floating platforms motion due to the waves. The method 100 comprises determining S105, based on the received signal, a sea state parameter indicative of an oscillation of the vertical acceleration. In one or more example methods, determining S105 comprises determining S105A the sea state parameter based on the filtered signal. In one or more example methods, determining S105 the sea state parameter comprises determining S105A whether the signal, such as the filtered signal, meets a criterion. Upon the signal meeting the criterion, determining S105 comprises determining S105AA that the sea state parameter is indicative of a first sea state. Upon the signal failing to meet the criterion, determining S105 comprises determining S105AB that the sea state parameter is indicative of a second sea state. In one or more example methods, the criterion is met upon the signal being equal to or above a threshold. In one or more example methods, determining S105 the sea state parameter comprises determining S105B one or more of a standard deviation and a maximum amplitude of the received signal, such as of the filtered signal. The standard deviation may be used as input to a look-up table. The look-up table may comprise control parameters, such as a weight parameter, associated with the standard deviation. The look-up table may be configured to use the standard deviation of the received signal as input and to output a signal that varies from 0 to 1. The look-up table may be configured so that a minimum value of the standard deviation outputs a 1, a maximum value of the standard deviation outputs a 0, and any values therebetween are outputs an interpolation between 0 and 1 as control parameter. The control parameters, such as the weight parameter, may be used as an input for controlling the floating wind turbine system. In one or more example methods, the standard deviation may be directly used as an input to a look-up table. The look-up table will vary between a minimum and maximum standard deviation of the signal, such as of the filtered signal. In this case there are two parameters to tune, namely the minimum and the maximum standard deviation. The minimum standard deviation may define a value where a control feature, such as a power derate and/or thrust derate, becomes active. The maximum standard deviation may define a maximum value where the floating wind turbine has been derated to an extent such that the wind turbine does not produce power. Between the minimum standard deviation and the maximum standard deviation, the derate may be an interpolation between the two values. In one or more example methods, determining S105 the sea state parameter comprises generating S105C, based on the filtered signal and one or more of the standard deviation and the maximum amplitude, a normalized sea state parameter. The normalized sea state parameter may be used as a weight parameter for controlling the floating wind turbine system. In one or more example methods, a relationship between the filtered signal and the normalized sea state parameter is provided in a look up table or a transfer function. In one or more example methods, the normalized sea state parameter has a value of 1 upon the filtered signal being equal to or below a first sea state threshold, a value of 0 upon the filtered signal being equal to or above a second sea state threshold. In one or more example methods, the normalized sea state parameter varies gradually between 1 and 0 upon the filtered signal being above the first threshold and below the second threshold. In one or more example methods, the look-up table may be kept between 0 and 1 and provide a normalization parameter, such as the maximum amplitude of the signal. By dividing the filtered standard deviation by the normalization parameter, such as by the maximum amplitude, a normalized signal that ranges from 0 to 1 may be provided. The normalized signal may be provided as an input to the look-up table. In this approach, there may only be one parameter to tune. The method 100 comprises controlling S107 the floating wind turbine system based on the sea state parameter, such as based on the normalized sea state parameter. The floating wind turbine may be controlled to reduce loads acting on the floating wind turbine system. In one or more example methods, such as when a standard deviation of the received signal has been determined, controlling S107 the floating wind turbine system comprises controlling the floating wind turbine system based on the standard deviation. In one or more example methods, such as when a normalized sea state parameter has been determined, controlling S107 the floating wind turbine system comprises controlling S107A the floating wind turbine system based on the normalized sea state parameter. In one or more example methods, the normalized sea state parameter has a value of 1 upon the filtered signal being equal to or below a first sea state threshold. The filtered signal being equal to or below a first sea state threshold may be indicative of a first sea state, such as a normal sea state (NSS). In one or more example methods, the normalized sea state parameter has a value of 0 upon the filtered signal being equal to or above a second sea state threshold. The filtered signal being equal to or above a second sea state threshold may be indicative of a second sea state, such as an extreme sea state (ESS). In one or more example methods, the normalized sea state parameter has a value that varies gradually between 1 and 0 upon the filtered signal being above the first threshold and below the second threshold. The filtered signal being above the first threshold and below the second threshold may be indicative of a third sea state, such as a severe sea state (SSS). In one or more example methods, controlling S107 the floating wind turbine system comprises multiplying S107AA an activation threshold of a control function of the floating wind turbine system with the normalized sea state parameter. The control function may be a control function of the wind turbine, such as a safe mode control function, such as a load limit control function, a thrust limit control function, a power limit control function and/or a speed limit control function. In one or more example methods, the normalized sea state parameter is multiplied by the threshold that activates the control function. If the sea state condition is an NSS, the normalized sea state parameter signal will be 1, making the calculation neutral. However, when the sea conditions worsen, the normalized sea state parameter will be below 1, thereby reducing the actual activation threshold of the control function. In one or more example methods, the control function, such as the power control function and/or the speed control function, is triggered by turbulence and may derate power or speed if the turbulence increases. According to one or more examples of the current disclosure, the control function may be triggered based on sea state. In one or more example methods, controlling S107 the floating wind turbine system comprises multiplying S107AB a control parameter of the floating wind turbine system with the sea state parameter, such as the normalized sea state parameter, for determining a resulting control parameter or setpoint for controlling the floating wind turbine system. In one or more example methods, the resulting control parameter may be a limit parameter, such as a limit pitch angle or a power limit. In one or more example methods, controlling S107 the floating wind turbine system comprises multiplying S107AC a gain of the control parameter of the floating wind turbine system with the normalized sea state parameter. In one or more example methods, controlling the floating wind turbine system comprises determining S107AD, based on the normalized sea state parameter, a first maximum reference value, comparing S107AE the first maximum reference value with a second maximum reference value of a variable control signal of the floating wind turbine system, and controlling S107AF a control function based on the minimum value of the first maximum reference value and the second maximum reference value. In one or more example methods, controlling S107 the floating wind turbine system comprises controlling a power derate of the wind turbine. The control parameter for controlling the power derate may be one or more of a power reference parameter and a speed reference parameter. The power reference parameter may be a normal operating power reference, which in full load is a rated power of the wind turbine. In one or more example methods, controlling the power derate comprises outputting the sea state parameter, such as the normalized sea state parameter, to a power controller of the floating wind turbine system. In one or more example methods, controlling the power derate comprises multiplying the power reference parameter (P_ref) with the normalized sea state parameter to determine a power setpoint (P_set). This may also be expressed as: ^^_^^௧ ൌ ^^_^^^ ∗ sea state (1) In one or more example methods, controlling the power derate comprises multiplying the speed reference parameter (N_ref) with the normalized sea state parameter to determine a speed setpoint (N_set). This may also be expressed as: ^^_^^௧ ൌ ^^_^^^ ∗ sea state (2) In one or more example methods, controlling S107 the floating wind turbine system comprises controlling a thrust derate of the wind turbine. The control parameter for controlling the thrust derate of the wind turbine may be a thrust related parameter. The thrust related parameter may be one or more of a load sensor signal, such as a blade load sensor signal, a maximum allowable rotor thrust for normal operation, such as for operation under NSS, and a pitch signal. The maximum allowable thrust may be variable, and may be obtained from a controller, such as a variable thrust limiter of the floating wind turbine system. In one or more example methods, controlling the thrust derate comprises outputting the sea state parameter, such as the normalized sea state parameter, to a thrust controller of the floating wind turbine system. In one or more example methods, controlling the thrust derate comprises determining S107AD, based on the normalized sea state parameter, a first maximum thrust reference, comparing S107AE the first maximum thrust reference with a second maximum thrust reference of a variable thrust signal of the floating wind turbine system, and controlling S107AF the thrust derate based on a minimum value of the first maximum thrust reference and the second maximum thrust reference. Fig.3 illustrates an example method for controlling a floating wind turbine system according to the present disclosure. A sensor signal 3001 indicative of a vertical acceleration of the floating wind turbine is obtained, such as from a sensor of the floating wind turbine. The sensor signal may be signal processed 3002, for example by filtering the obtained sensor signal using a notch filter and/or a high pass filter to filter out one or more of a gravity component, a natural frequency of the floating platform, and a tower frequency from the signal, and provide a filtered signal 3003 indicative of the vertical acceleration of the floating wind turbine. The filtered signal 3003 is then provided as input into a look-up table 3004A or transfer function 3004B, which outputs a normalized sea state parameter 3005 varying between 0 and 1, wherein 1 is indicative of a normal sea state and 0 is indicative of an extreme sea state. The thresholds for when the normal sea state and/or the extreme sea state are entered based on the vertical acceleration may be tuneable, so that they can be adapted to different types of floating wind turbine systems. The normalized sea state parameter 3005 is then multiplied with a control parameter 3006 obtained from control function 3007 of the floating wind turbine system, to determine a control variable 3008 for controlling the floating wind turbine system. The control function 3007 may be a safe mode control function, such as a load limit control function, a thrust limit control function, a power limit control function and/or a speed limit control function of the floating wind turbine system. Accordingly, the control parameter 3006 may be one or more of a power reference parameter, a speed reference, a thrust related parameter, such as one or more of a load sensor signal, such as a blade load sensor signal, a maximum allowable rotor thrust for normal operation, such as for operation under NSS, and a pitch signal. This example method corresponds to the example method according to S107AB and/or 107AC of Fig.2. Fig.4 illustrates an example method for controlling a floating wind turbine system according to the present disclosure. The sensor signal 3001 indicative of a vertical acceleration of the floating wind turbine is obtained, such as from a sensor of the floating wind turbine. The sensor signal may be signal processed 3002, for example by filtering the obtained sensor signal using a notch filter and/or a high pass filter to filter out one or more of a gravity component, a natural frequency of the floating platform, and a tower frequency from the signal, and provide a filtered signal 3003 indicative of the vertical acceleration of the floating wind turbine. The filtered signal 3003 is then provided as input, such as into a look-up table 3004A or transfer function 3004B, for determining a sea state based maximum value 3005A for a control parameter. The sea state based maximum value 3005A of the control parameter may be determined based on a current sea state, such as a current sea state parameter, indicated by the vertical acceleration of the floating wind turbine. The sea state based maximum value 3005A of the control parameter may for example be determined by applying the normalized sea state parameter to a thrust refence signal. The sea state based maximum value 3005A of the control parameter may have its highest value during NSS and its lowest value during ESS, and may be interpolated between these values based on the vertical acceleration of the floating wind turbine. The thresholds for when the NSS and the ESS are entered based on the vertical acceleration may be tuneable, so that they can be adapted to different types of floating wind turbine systems. The sea state based maximum value 3005A of the control parameter is then compared with a maximum value of a control parameter 3006A obtained from a control function 3007 of the floating wind turbine system. The minimum value of the sea state based maximum value 3005A and the maximum value of the control parameter 3006A is then used as a setpoint or control variable 3008 for controlling the floating wind turbine system. The control variable 3008 may for example be a resulting control value of a safe mode control function, such as a load limit control function, a maximum rotor thrust limit control function, a power limit control function and/or a speed limit control function of the floating wind turbine system.adapted to a current sea state. Accordingly, the control parameter 3006A may be one or more of a power reference parameter, a speed reference parameter, and a thrust related parameter, such as one or more of a load sensor signal (such as a blade load sensor signal), a maximum allowable rotor thrust for normal operation (such as for operation under NSS), and a pitch signal. This example method corresponds to the example method according to S107AD to S107AF of Fig.2. Fig.5 shows a block diagram of an exemplary electronic device 300 according to the disclosure. The electronic device 300 comprises memory circuitry 301, processor circuitry 302, and an interface 303. The electronic device 300 is configured to perform any of the methods disclosed in Fig.2-4. In other words, the electronic device 300 is configured for enabling control of operation of a wind turbine, such as for controlling a floating wind turbine system. For example, the electronic device 300 may be a controller of a wind turbine, such as an internal controller of the wind turbine. For example, the electronic device 300 may be a device remote from the wind turbine. For example, the electronic device may be an external controller of the wind turbine. The electronic device 300 is configured to receive (e.g., via processor circuitry 302 and/or interface 303), from one or more sensors of the floating wind turbine system, a signal indicative of a vertical acceleration of the floating wind turbine system. The electronic device 300 is configured to determine (e.g., via processor circuitry 302), based on the received signal, a sea state parameter indicative of an oscillation of the vertical acceleration. The electronic device 300 is configured to control the floating wind turbine system based on the sea state parameter. The processor circuitry 302 is optionally configured to perform any of the operations disclosed in Fig.2 (such as any one or more of: S101, S103, S103A, S103B, S105, S105A, S105AA, S105AB, S105B, S105C, S107, S107A, S107AA, S107AB, S107AC, S107AD, S107AE, S107AF). The operations of the electronic device 300 may be embodied in the form of executable logic routines (e.g., lines of code, software programs, etc.) that are stored on a non-transitory computer readable medium (e.g., the memory circuitry 301) and are executed by the processor circuitry 302). Furthermore, the operations of the electronic device 300 may be considered a method that the electronic device 300 is configured to carry out. Also, while the described functions and operations may be implemented in software, such functionality may as well be carried out via dedicated hardware or firmware, or some combination of hardware, firmware and/or software. The memory circuitry 301 may be one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, a random access memory (RAM), or other suitable device. In a typical arrangement, the memory circuitry 301 may include a non-volatile memory for long term data storage and a volatile memory that functions as system memory for the processor circuitry 302. The memory circuitry 301 may exchange data with the processor circuitry 302 over a data bus. Control lines and an address bus between the memory circuitry 301 and the processor circuitry 302 also may be present (not shown in Fig.3). The memory circuitry 301 is considered a non-transitory computer readable medium. The memory circuitry 301 may be configured to store sensor data, environmental conditions (such as sea state conditions), operational parameters (such as power reference parameters, speed reference parameters and/or thrust related parameters), and control data in a part of the memory. Fig.6 shows graphs illustrating a simulation result for a power derate based on an example sea state parameter according to the current disclosure. Baseline herein refers to a floating wind turbine system not applying a power derate and 85% Derate relates to a floating wind turbine system according to one or more examples of the present disclosure in which the power is derated by 85%, for example due to harsh sea state conditions. As can be seen in the top graph of Fig.4 the simulated wind speed is identical for both the baseline simulation and the 85% derate simulation. The middle graph of Fig.4 shows a power output of the wind turbine in response to the wind speed. The baseline simulation has an initial power output, such as rated power, around 1.6 x10^4 kW (or 16 MW), while the 85% derate simulation operates at 85% of the rated power output at around 1.27 x10^4 kW. At around 180 seconds, the baseline simulation starts to heavily fluctuate between 1.6 x10^4 kW and 1.25 x10^4 kW. These fluctuations may be due to the wind dropping and there not being enough energy to keep the wind turbine at the rated power output. As can be seen in the bottom graph the maximum tower bottom moment acting on the floating wind turbine system for the baseline simulation occurs in response to the first drop in power output at around 180 seconds, as indicated by the max point of the baseline. In contrast, the maximum tower bottom moment of the 85% power derated simulation, which has a substantially continuous output around 2.7 x10^4 kW, is significantly lower, as indicated by the max point of the 85% Derate curve. For the 85% power derated wind turbine the wind may be enough to keep the wind turbine at the derated power output, thus reducing the fluctuations and tower bottom moment of the wind turbine. Applying a power derate based on estimated sea states according to the present disclosure, thus reduces the loads acting on the floating wind turbine system, such as on the tower, while maintaining a steady power output. Fig.7 shows graphs illustrating a simulation result for a thrust derate based on an example sea state parameter according to the current disclosure. Baseline herein refers to a legacy floating wind turbine system not applying a power derate and ThrustLimited relates to a floating wind turbine system according to one or more examples of the present disclosure in which the thrust of the floating wind turbine has been limited, for example due to harsh sea state conditions. As can be seen in the top graph of Fig.5 the simulated wind speed is identical for both the baseline simulation and the ThrustLimited simulation. The maximum allowable thrust of the wind turbine may be limited according to the bottom graph of Fig.5, for example by increasing the blade pitch angle of the ThrustLimited simulation compared to the Baseline in accordance with the second graph from the top of Fig.5. As can be seen in the third graph from the top of Fig.5, limiting the maximum allowable thrust of the floating wind turbine system leads to a significant reduction of the maximum tower bottom moment, in this case a reduction of around 20% in an extreme tower bottom load. Applying a thrust limitation, such as a thrust derate based on estimated sea states according to the present disclosure, can thus reduce the loads acting on the floating wind turbine system, such as on the tower of the floating wind turbine system, and thus reduces the risk of failure of the floating wind turbine system. It should further be noted that any reference signs do not limit the scope of the claims, that the exemplary embodiments may be implemented at least in part by means of both hardware and software, and that several "means", "units" or "devices" may be represented by the same item of hardware. The various exemplary methods, devices, nodes, and systems described herein are described in the general context of method steps or processes, which may be implemented in one aspect by a computer program product, embodied in a computer- readable medium, including computer-executable instructions, such as program code, executed by computers in networked environments. A computer-readable medium may include removable and non-removable storage devices including, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), compact discs (CDs), digital versatile discs (DVD), etc. Generally, program circuitries may include routines, programs, objects, components, data structures, etc. that perform specified tasks or implement specific abstract data types. Computer-executable instructions, associated data structures, and program circuitries represent examples of program code for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps or processes. Although features have been shown and described, it will be understood that they are not intended to limit the claimed disclosure, and it will be made obvious to those skilled in the art that various changes and modifications may be made without departing from the scope of the claimed disclosure. The specification and drawings are, accordingly, to be regarded in an illustrative rather than restrictive sense. The claimed disclosure is intended to cover all alternatives, modifications, and equivalents.

Claims

CLAIMS 1. A method for controlling a floating wind turbine system, the floating wind turbine system comprising a floating platform, a tower mounted to the floating platform and a nacelle, the method comprising: - receiving (S101), from one or more sensors of the floating wind turbine system, a signal indicative of a vertical acceleration of the floating wind turbine system, - determining (S105), based on the received signal, a sea state parameter indicative of an oscillation of the vertical acceleration, and - controlling (S107) the floating wind turbine system based on the sea state parameter. 2. The method according to claim 1, wherein the method comprises: - filtering (S103) the signal to provide a filtered signal, and wherein determining (S105) comprises determining (S105A) the sea state parameter based on the filtered signal. 3. The method according to claim 2, wherein filtering (S103) comprises applying (S103A) a high pass filter to filter out one or more of a gravity component and a natural frequency of the floating platform. 4. The method according to claim 2 or 3, wherein filtering (S103) comprises applying (S103B) a notch filter to filter out a tower frequency. 5. The method according to any one of the previous claims, wherein determining (S105) the sea state parameter comprises determining (S105A) whether the signal meets a criterion, wherein: upon the signal meeting the criterion, determining (S105AA) that the sea state parameter is indicative of a first sea state; and upon the signal failing to meet the criterion, determining (S105AB) that the sea state parameter is indicative of a second sea state. 6. The method according to any one of the previous claims, wherein determining (S105) the sea state parameter comprises determining (S105B) one or more of a standard deviation and a maximum amplitude of the received signal. 7. The method according to claim 6, wherein controlling the floating wind turbine system comprises controlling the floating wind turbine system based on the standard deviation. 8. The method according to claim 6 or 7, wherein determining (S105) the sea state parameter comprises generating (S105C), based on the filtered signal and one or more of the standard deviation and the maximum amplitude, a normalized sea state parameter, and wherein controlling (S107) the floating wind turbine system comprises controlling (S107A) the floating wind turbine system based on the normalized sea state parameter. 9. The method according to claim 8, wherein the normalized sea state has a value of 1 upon the filtered signal being equal to or below a first sea state threshold, a value of 0 upon the filtered signal being equal to or above a second sea state threshold, and varies gradually between 1 and 0 upon the filtered signal being above the first threshold and below the second threshold. 10. The method according to claims 8 and 2, wherein a relationship between the filtered signal and the normalized sea state parameter is provided in a look up table or transfer function. 11. The method according to any one of the claims 8 to 10, wherein controlling (S107A) comprises multiplying (S107AA) an activation threshold of a control function of the floating wind turbine system with the normalized sea state parameter. 12. The method according to any one of the claims 8 to 11, wherein the controlling (S107A) comprises multiplying (S107AB) a control parameter of the floating wind turbine system with the normalized sea state parameter. 13. The method according to any one of the claims 8 to 12, wherein controlling (S107A) comprises multiplying (S107AC) a gain of the control parameter of the floating wind turbine system with the normalized sea state parameter. 14. The method according to any one of the previous claims, wherein controlling (S107, S107A) the floating wind turbine system comprises controlling a power derate of the wind turbine and wherein the control parameter is a power reference parameter and/or a speed reference parameter. 15. The method according to any one of the previous claims, wherein controlling (S107, S107A) the floating wind turbine system comprises controlling a thrust derate of the floating wind turbine system and wherein the control parameter is a thrust related parameter. 16. The method according to claim 15, wherein the thrust related parameter is a load sensor signal. 17. The method according to claim 15 or 16, wherein controlling the thrust derate comprises: - determining (S107AD), based on the normalized sea state parameter, a first maximum thrust reference, - comparing (S107AE) the first maximum thrust reference with a second maximum thrust reference of a variable thrust signal of the floating wind turbine system, and - controlling (S107AF) the thrust derate based on a minimum value of the first thrust reference and the second thrust reference. 18. The method according to any one of the previous claims, wherein the one or more sensors is one or more acceleration sensors located in the tower, the nacelle or at the floating platform of the floating wind turbine system, wherein the sensor signal is an acceleration signal from the one or more acceleration sensors and being indicative of the vertical acceleration of the floating wind turbine system. 19. An electronic device comprising a memory circuitry, a processor circuitry, and an interface, wherein the electronic device is configured to perform any of the methods according to any one of claims 1-18. 20. A floating wind turbine system comprising the electronic device according to claim 19. 21. A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device cause the electronic device to perform any of the methods of claims 1-18.