Mooring system condition monitoring for floating offshore wind turbines

Abstract

A method for monitoring a mooring system (10) of a floating offshore installation (FOI) (100) moored by the mooring system (10) is provided. The method includes obtaining parameters related to the position of the FOI, the parameters including at least mooring system parameters indicative of an area (15) in which the FOI is expected to be located. The method further includes obtaining position measurements of the actual position (11) of the FOI, and deriving a status of the FOI's mooring system (10) from the obtained parameters and the FOI's position measurements.

Description

[Technical Field]

[0001] The present invention relates to a method for monitoring a mooring system of a floating offshore installation, a method for operating a floating offshore wind turbine (FOWT), and the respective monitoring systems. The present invention further relates to a computer program for monitoring a mooring system of a floating offshore installation.

[0002] Background technology Floating offshore installations (FOIs), particularly floating offshore wind turbines (FOWTs), are typically attached to the seabed by mooring systems that provide positioning. Positioning is important to ensure that the FOWT's movements are constrained to a small, predefined area and that the FOWT's float maintains its planned orientation. There are various types of floaters, which can be classified into various categories, such as semisubmersibles, spars, tension leg platforms, or barges. In addition to providing positioning, tendons on tension leg platforms can also prevent the turbine from capsizing. For semisubmersibles, spars, or barges, the mooring system generally only provides positioning but can affect turbine dynamics. A broken mooring line, for example, can result in increased turbine loads and reduced performance. In the event of a mooring system failure, it is generally necessary to protect the FOWT, for example, by providing a protective function. Therefore, reliable detection of mooring system failures is desirable.

[0003] To detect mooring line faults, WO 2022 / 017834 describes, for example, measuring strain on the mooring system or providing an electrical signal through the mooring system to determine whether the mooring lines are intact. While such solutions provide reliable monitoring of the mooring system, they require the installation of additional equipment, which can increase costs. Furthermore, these additional means for monitoring the mooring lines may not function in harsh seawater environments.

[0004] The document US Patent No. 9,671,231 further describes a method for monitoring the mooring system of a floating vessel, which employs the timing of the vessel's natural periods, such as the natural periods of motion, swell, and / or heave. If the natural periods deviate from a reference natural period, a fault in the mooring system is detected. This method appears to be applicable only to systems in which the mooring lines have a significant effect on the motion, swell, and heave of the floating vessel.

[0005] Summary of the Invention Therefore, there is a need to improve monitoring of mooring systems of floating offshore installations, and in particular to provide reliable monitoring that is relatively easy to implement. It is also desirable to avoid the need to use additional sensors.

[0006] This need is met by a method for monitoring the mooring system of a floating offshore installation (FOI) moored by the mooring system. The method includes obtaining parameters related to the position of the FOI, the parameters including at least mooring system parameters indicative of an area in which the FOI is expected to be located. It further includes obtaining position measurements of the actual position of the FOI and deriving a state of the mooring system of the FOI from the obtained parameters and the position measurements of the FOI.

[0007] According to one aspect, this need is met by the features of the independent claims.The dependent claims describe embodiments of the invention.

[0008] Such a method can enable accurate monitoring of the FOI's mooring system, thereby detecting faults without the need for additional, dedicated sensors. Furthermore, monitoring can detect changes in the mooring system, such as mooring line length or anchor position, and can enable mooring system parameters to be kept up-to-date so that they can be further taken into account when monitoring the mooring system's condition, for example, for fault detection. Monitoring the mooring system in this manner is therefore more cost-effective and less prone to sensor failure. Unlike dedicated sensors on the mooring system, which are exposed to harsh conditions in seawater, sensors acquiring position measurements of the FOI can be located, for example, inside the tower or wind turbine nacelle, where they are protected from such harsh conditions. Position and motion sensors are generally inexpensive, mature, and widely available sensor technologies. Furthermore, such position and / or motion sensors may already be present on the FOI, and therefore additional sensors may not be required.

[0009] In one embodiment, obtaining position measurements of the actual location of the FOI includes obtaining a measured absolute position of the FOI and / or obtaining the actual location measurements using satellite-based positioning (e.g., GPS, GLONASS, or GALILEO, or any Global Navigation Satellite System, GNSS) and / or motion reference unit (MRU)-based positioning. Thus, the position measurements can be obtained in a simple and cost-effective manner.

[0010] Mooring system parameters may include parameters of one or more elements of the mooring system (e.g., anchors and / or mooring lines) that restrict the movement of the FOI (e.g., restrict locations where the FOI can be placed, i.e., define an area where the FOI can be placed). Mooring system parameters may include, for example, the anchor positions and / or mooring line lengths of at least one of one, two, three, or more anchor assemblies of the mooring system. The anchor positions and mooring line lengths generally restrict the movement of the FOI, and when multiple such anchor assemblies are provided, the movement of the FOI may be restricted to a relatively small area. By utilizing such mooring system parameters that define such areas and actual position measurements, the state of the mooring system can be accurately and efficiently derived. The area where the movement of the FOI is restricted may be defined, for example, by the intersection of two, three, or more circles around different anchor positions of two, three, or more anchor assemblies, respectively. Each circle may correspond to an area on the sea surface where the respective anchor assembly restricts the movement of the FOI. Thus, the radius of the circle depends on the length of the mooring line. In other words, the radius of the circle may correspond to the farthest possible distance from the anchor position that the mooring point on the FOI to which the mooring line is moored can be when the anchor position is projected onto the sea surface.

[0011] In one example, one or more, preferably all, of the mooring system parameters may be provided in the form of a probability density function (PDF). By utilizing a PDF instead of fixed values, the expected accuracy of the parameter values ​​(e.g., via the width of the respective distribution) can be taken into account. The error distribution of the parameters (e.g., initial anchor position and mooring line length) can be taken into particular consideration. Taking into account the error uncertainty can increase the robustness of detecting the mooring system state.

[0012] The parameters may further include one or more environmental parameters, which preferably include at least one of meteorological and oceanographic parameters, wind parameters, wind speed, wind direction, oceanographic parameters, current speed, current direction, wave height, wave period, and tidal parameters. Such environmental parameters may affect the actual location of the FOI. They may be used in estimating the predicted location of the FOI based on the mooring system parameters, particularly to refine such predicted location. Thus, providing an accurate estimate of the predicted location may enable a more reliable determination of the state of the mooring system.

[0013] Deriving the state of the mooring system may include estimating a predicted position from the obtained parameters and comparing the predicted position with position measurements of the actual position of the FOI. In this manner, it is possible to reliably detect when the mooring system parameters are inaccurate and may require adjustment, and / or when a mooring system fault exists.

[0014] Deriving the state of the mooring system of the FOI, in an exemplary embodiment, may include employing a model of the expected location of the FOI, where the model may employ the obtained parameters, particularly the mooring system parameters and optionally one or more environmental parameters, and comparing the model to the position measurements. For example, statistical methods may be used to compare the model to the position measurements (e.g., using the position measurements as the desired results of the model) and / or by comparing the results or predicted location provided by the model to the actual position measurements.

[0015] The method may include obtaining updated values ​​for one or more of the obtained parameters and adjusting the model based on the obtained updated parameter values. For example, one or more updated environmental parameters and / or one or more updated mooring system parameters may be obtained and the model may be updated using the respective updated parameters. The model may be updated, for example, as soon as the updated parameters are available, or may be updated periodically or at predetermined time intervals. Thus, a model that matches current conditions may be obtained, and reliability in detecting mooring system faults may be improved.

[0016] For example, in simple cases, the model may define an area within which the position of the FOI is restricted, and actual position measurements may be compared to this area to derive the state of the mooring system.

[0017] Deriving the state can include, for example, comparing a region where the FOI is expected to be present with actual position measurements of the FOI. The region where the FOI is expected to be present can correspond to an area where the FOI's movement is restricted by mooring system parameters (in a simple model), or can correspond to a portion thereof (e.g., when employing additional parameters, such as environmental parameters, in a more complex model). The region can, for example, correspond to a probability distribution that the FOI is at a particular location. The probability distribution can change over time, particularly as the derived parameters change (e.g., due to changing environmental conditions and / or changes in the calibration of the mooring system parameters).

[0018] For example, deriving the state of the mooring system may include deriving a probability distribution of the expected location of the FOI from the obtained parameters and comparing the actual location of the FOI to the probability distribution of the expected location of the FOI. A model employing the obtained parameters, particularly the mooring system parameters and optionally environmental parameters, may be employed to determine the probability distribution of the expected location of the FOI. The comparison may be used, for example, to detect a fault in the mooring system. A fault may be detected when the actual location of the FOI does not match the probability distribution of the expected location, for example, when the actual location is outside a (predefined) region of minimum probability.

[0019] Preferably, the model is a statistical model of the position of the FOI. The model can, for example, model the position of the FOI using position perturbations and further use mooring system parameters as constraints. The position perturbations of the model can, for example, include perturbations derived from one or more environmental parameters. The position can, for example, be modeled from previous positions, unconstrained perturbations, and constraints imposed by mooring system parameters. Such a model can be initialized with initial mooring system parameters, which can, for example, be obtained when installing the FOI.

[0020] Comparing the model to the position measurements can include, for example, determining the probability that the model matches the observed position measurements. This probability is, in particular, the probability that the model is correct given the observed position measurements. Such a probability can be expressed, for example, as a conditional probability P(M|X(n)), where M is the model (which depends on the obtained parameters) and X(n) is the obtained position measurement. Such a probability can also be called a "probability of failure," as it can be effectively used to indicate a fault in the mooring system.

[0021] Obtaining position measurements may include repeatedly obtaining position measurements of the actual position of the FOI. The method may further include using the repeatedly obtained position measurements (e.g., as soon as they become available) to update the probability that the model matches the observed position measurements. The probability update may be performed using, for example, Bayesian estimation. Using such a method, it may be possible to quickly and efficiently determine whether the actual position of the FOI no longer matches the model, thereby reliably detecting a fault in the mooring system.

[0022] In one embodiment, deriving the state of the mooring system includes detecting whether a fault in the mooring system exists.

[0023] For example, detecting that a mooring system fault exists may include detecting that a position measurement of the actual location of the FOI differs from the location of the FOI expected from the obtained parameters. For example, a fault may be detected if the actual location differs from the area in which the location is expected to be, e.g., the actual location differs from the area to which the expected location would be limited based on the mooring system parameters associated with an intact mooring system. For example, if three or more anchor assemblies are used, the mooring system parameters may limit the expected location of the FOI to a (relatively small) area, and a fault may be detected if the actual measured location of the FOI is (significantly) outside the area.

[0024] Preferably, such fault detection is model-based. For example, if the model employs mooring system parameters of an intact mooring system, and the probability that the model matches the observed position measurements is below a threshold, a mooring system fault (e.g., a mooring line fault) may be detected to exist. Additionally or alternatively, if the model employs mooring system parameters of a faulted mooring system, and the probability that the model matches the observed position measurements is above a threshold, a fault may be detected to exist. A model of a faulted mooring system may, for example, assume that one mooring line is severed, resulting in a larger area where the FOI location is constrained by the mooring system; by detecting a high probability that the actual measured FOI location matches this faulted mooring system model, a mooring system fault may be efficiently detected.

[0025] In an exemplary embodiment, the mooring system parameters include intact mooring system parameters associated with an intact mooring system and a set of one or more faulted mooring system parameters associated with a mooring system having a fault, such as one or more broken mooring lines. Detecting whether a mooring system fault exists can include providing a model of the expected location of the FOI employing the intact mooring system parameters; providing one or more models of the expected location of the FOI, each model employing one (particularly a different set) of the one or more sets of faulted mooring system parameters; determining, for each model, a probability that the model matches the observed position measurements; and detecting whether a mooring system fault exists based on the probabilities. By matching the location measurements of the actual FOI location against multiple different models for different mooring system faults and intact mooring systems, the presence of a mooring system fault and the type of mooring system fault can be reliably detected.

[0026] For example, the presence of a mooring system fault may be detected by detecting that the probability of the model employing the faulty set of mooring system parameters rises above a threshold, by detecting that the probability of the model employing the intact mooring system parameters falls below a threshold, and / or by detecting that the probability of the model employing the faulty set of mooring system parameters rises above the probability of the model employing the intact mooring system parameters. Thus, the probability of the faulty mooring system model may be compared to a threshold, which may be a dynamic threshold determined by the model of the intact mooring system parameters. Thus, reliable and accurate fault detection may be achieved.

[0027] As outlined above, the obtained parameters may include the respective environmental parameters, and the model employing the intact mooring system parameters and / or one or more models employing the respective sets of failed mooring system parameters may employ the environmental parameters. The method may include obtaining updated values ​​of one or more of the obtained parameters, as described above, and adjusting the model employing the intact mooring system parameters and / or one or more models employing the respective sets of failed mooring system parameters with the respective updated parameters. For example, one or more updated environmental parameters and / or one or more updated mooring system parameters may be obtained, and the respective models may be updated with the obtained updated parameters, for example, as soon as the updated parameters are available or at regular or predetermined time intervals. The updated mooring system parameters may be derived as further described below.

[0028] In one embodiment, obtaining the parameters may include obtaining an initial set of mooring system parameters, which may preferably be obtained during installation of the mooring system, and which may be used to initialize the model.

[0029] In one embodiment, deriving the state of the mooring system of the FOI may include deriving updated mooring system parameters of the mooring system of the FOI. Each updated mooring system parameter is preferably derived repeatedly during operation of the FOI. Such updated mooring system parameters may be derived, for example, at a predetermined time point or after a predetermined period of time has elapsed. They may also be derived periodically.

[0030] The method may include, for example, adjusting the model based on the obtained position measurements, and adjusting the model may include updating the model based on the derived updated mooring system parameters.

[0031] Fault detection can be further improved by updating the mooring system parameters and / or models.

[0032] For example, deriving updated mooring system parameters can include obtaining position measurements by repeatedly obtaining position measurements of the FOI's actual position over a period of time, and updating the model, particularly the mooring system parameters, by adjusting the model so that the model matches the obtained position measurements. The period can be, for example, longer than one day, or longer than one, two, or three weeks, or longer than one month. The period can be, for example, between 0.5 and four months, e.g., between one and two months. For example, after initializing the model, position measurements can be obtained over a period of one month or more and used to update the model by updating the mooring system parameters (initial and / or subsequent calibrations). After such a period, the FOI should have traversed most of the area where its position is constrained by the mooring system, and comparing the predicted position (i.e., the area where its position is expected to be due to the constraints imposed by the mooring system) with the actually measured position allows the mooring system parameters to be accurately and efficiently updated. An intact mooring system can be assumed for the mooring system parameters and / or model.

[0033] Such updating of the mooring system parameters may be performed, for example, after installation, e.g., after initialization of the model. Updating of the mooring system parameters may also be performed repeatedly during operation of the FOI, for example, by assuming an intact mooring system and collecting position measurements over respective periods of time.

[0034] The mooring system parameters may define an area within which the possible locations of the FOI are restricted, and updating the mooring system parameters may include adjusting the mooring system parameters so that the area corresponds to a position measurement of the actual location of the FOI.

[0035] As a particular example, deriving updated mooring system parameters may include deriving, from the area covered by the obtained position measurements of the FOI, the curvature and / or position of a circle segment tangent to the area. Such a circle segment may correspond to a circle defined by the anchors and mooring lines. It may further include deriving, from the curvature and / or position of the circle segment, mooring line lengths and / or anchor positions, respectively, of anchor assemblies of the mooring system. This may be done for each circle segment tangent to the area covered by the measured actual position of the FOI, and thus for each anchor assembly of the mooring system. Thus, actual updated mooring line lengths and / or anchor positions may be obtained.

[0036] In a preferred embodiment, adjusting the model to match the obtained position measurements may include adjusting mooring system parameters to increase the probability (i.e., the probability that the model is correct given the observed position measurements of the actual FOI location). In particular, the probability (e.g., conditional probability) may be maximized.

[0037] The probability can be determined using a numerical method. For example, a Markov Chain Monte Carlo (MCMC) sampling method can be used to determine the probability. By such a method, the mooring system parameters can be adjusted to increase the probability.

[0038] The derivation of the state of the mooring system can be performed repeatedly as soon as new position measurements of the actual position of the FOI are obtained. For example, the state of the mooring system can be derived every time a new position measurement is obtained. This allows for fast and efficient fault detection.

[0039] The floating offshore installation FOI may in particular be a floating offshore wind turbine (FOWT).

[0040] Using models, particularly statistical models, for the predicted location of the FOI can achieve several advantages. For example, if the measured position of the actual FOI falls outside the area defined by the constraints imposed by the mooring system parameters, this may be due to measurement error, but a fault will not be immediately detected. Therefore, outliers that may be due to detection noise will not lead to the detection of a fault. Furthermore, such models of FOI movement can take into account environmental data such as wind speed and direction, or the speed and direction of currents, so that a mooring system fault can be detected even if the FOI does not move away from the area defined by the mooring system parameters. For example, a fault may be detected if the equilibrium position of the FOI changes so that it no longer coincides with the direction of the wind or current.

[0041] In one embodiment, a method of operating a floating offshore wind turbine (FOWT) with a mooring system is provided. The method includes monitoring a condition of the FOWT according to any of the methods described herein. If the condition of the mooring system indicates a mooring system fault, the method includes implementing predetermined mitigating actions. Such a method can prevent inefficient operation of the FOWT and even damage to the FOWT.

[0042] According to one embodiment and / or independent aspect, a method for operating a floating offshore wind turbine (FOWT) is disclosed, the method including generating power and / or electrical energy by the FOWT, transmitting at least a portion of the power and / or electrical energy to a power receiving facility located in international waters, particularly a land-based, non-shore-located facility, and supplying at least a portion of the power and / or electrical energy to an electrical grid, particularly a coastal electrical grid.

[0043] Executing the predetermined mitigation action may include, for example, one or a combination of: activating an alarm, changing the operation of the FOWT to a safe mode, reducing the power output of the FOWT, shutting down the FOWT, disabling a power increase mode of the FOWT (e.g., a power boost operation mode), enabling a power decrease mode of the FOWT (e.g., applying a conservative joint pitch angle offset), and providing an event notification indicating a mooring system fault. Such a notification may be provided to an operator, for example, via a communications connection, which may prevent damage to the wind turbine and / or initiate inspection / repair of the mooring system.

[0044] After the mooring system has been inspected or repaired, the method may continue operation, for example, by reinitializing the model or by using the previous set of mooring system parameters.

[0045] According to a further embodiment of the present invention, there is provided a system for monitoring a mooring system of a floating offshore installation moored by the mooring system. The monitoring system comprises an interface for obtaining parameters and position measurements of the FOI (particularly the parameters and position measurements mentioned above), a processing unit, and a memory. The memory includes control instructions that, when executed by the processing unit, cause the processing unit to perform any of the methods described herein. Such a system may further comprise a control system for controlling the operation of the FOI, e.g., the FOWT, as described herein. It will be apparent that the system may comprise parts that reside within the FOI, such as the control system that controls the function of the FOI, and parts that may reside remotely from the FOI (e.g., on shore), e.g., parts of the system that derive the state of the mooring system by obtaining position measurements from the FOI via a communication connection and interface. Thus, the system may be a distributed system. In other embodiments, the system is entirely contained within the FOI.

[0046] According to a further embodiment, a FOWT comprising such a system is provided.

[0047] A further embodiment of the present invention provides a computer program for monitoring a mooring system of a moored FOI by the mooring system. The computer program includes control instructions that, when executed by a processing unit of the system monitoring the mooring system, cause the processing unit to perform any of the methods described herein. Such a computer program may similarly be operated remotely from the FOI, or components thereof may be present on the FOI.

[0048] The computer program may be provided on a volatile or non-volatile data carrier or storage medium. The computer program may also be provided via a network connection. The computer program may operate in any of the systems disclosed herein.

[0049] It is to be understood that the features mentioned above and those yet to be described below can be used not only in the respective combinations shown, but also in other combinations or alone, without departing from the scope of the invention. In particular, features of different aspects and embodiments of the invention can be combined with one another, unless stated to the contrary.

[0050] The foregoing and other features and advantages of the present invention will become more apparent from the following detailed description read in conjunction with the accompanying drawings, in which like reference numerals refer to like elements and in which: [Brief explanation of the drawings]

[0051] [Figure 1] FIG. 1 is a schematic diagram illustrating a floating offshore wind turbine FOWT including a system for monitoring a mooring system according to an embodiment. [Figure 2] FIG. 1 is a schematic diagram illustrating constraints on the position of a FOWT imposed by a mooring system according to one embodiment. [Figure 3]1 is a flow chart illustrating a method for monitoring a mooring system according to one embodiment for detecting a fault in the mooring system. [Figure 4] FIG. 10 is a diagram illustrating the measured position of the FOWT in the event of a mooring system failure. [Figure 5] FIG. 10 is a diagram illustrating the probabilities of different models of the predicted position of a FOWT according to an embodiment. [Figure 6] 1 is a flow chart illustrating a method for monitoring a mooring system, according to one embodiment, where parameters of the mooring system are calibrated based on position measurements. [Figure 7] FIG. 1 shows a schematic representation of the actual measured position of a FOWT over a period of time and the constraints on the position of the FOWT imposed by mooring system parameters. [Figure 8] FIG. 8 is a diagram that schematically illustrates the adjustment of probability density functions representing mooring system parameters based on the position measurements shown in FIG. 7, according to one embodiment.

[0052] MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be understood that the following description of the embodiments is provided for illustrative purposes only and should not be construed in a limiting sense. It should be noted that the drawings are schematic, and the elements in the drawings are not necessarily drawn to scale. Rather, the representation of various elements is chosen so that their function and general purpose will be apparent to those skilled in the art. As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly dictates otherwise. The terms "comprising," "having," "including," and "containing" should be construed as open-ended terms (i.e., meaning "including, but not limited to") unless otherwise specified.

[0053] 1 illustrates, in accordance with one embodiment, a FOWT 100 comprising a rotor 101, a tower 102, and a spar-shaped platform 103 moored by a mooring system 10. The mooring system 10 includes anchor assemblies 20, 30, 40, each including a respective anchor 21, 31, 41 and a respective mooring line 22, 32, and 42. The mooring system 10 restricts the movement of the FOWT 100.

[0054] FIG. 1 further illustrates a system 50, including a monitoring system. The system 50 includes a processing unit 51 and a memory 52. ​​The processing unit 51 can include a microprocessor, an application-specific integrated circuit, a programmable logic device (PLD) such as a field programmable gate array (FPGA), a digital signal processor, etc. The memory 52 can include volatile and non-volatile memory, particularly a hard disk drive, an SSD, a flash memory, a RAM, a ROM, an EEPROM, etc. The memory 52 can store control instructions that, when executed by the processing unit 51, cause the processing unit 51 to perform any of the methods disclosed herein. The control instructions, particularly respective software code, can implement, for example, the methods of FIG. 3 and / or FIG. 6. The system 50, particularly the monitoring system, can include additional components not explicitly shown, such as input / output interfaces to other data sources and controlled components, a user interface including a display and input unit, and buses coupling these components and other components common to computer systems.

[0055] The system 50 further includes an interface 53 for data communication. For example, via the communication connection 55, measured position data can be acquired from the FOWT 100 and control commands can be provided to the FOWT 100. For this purpose, the system 50 can further include a control system. For example, via the communication connection 56, data can be provided to or received from an external data source, for example, via a network such as the Internet. Environmental parameters can be acquired, for example, via the communication connection 56. The system 50 may be provided within the FOWT 100, on a different offshore platform, a floating vessel, or at a coastal site. The system 50 may be further distributed, for example, by providing a monitoring system at the coastal site and a control system within the FOWT 100. Parts of the system can communicate via the communication connections 55, 56. The system 50 can include position sensors and / or environmental sensors (e.g., wind, current, and / or wave sensors) located within or on the FOWT 100.

[0056] Each of the anchor assemblies 20, 30, and 40 of the mooring system 10 restricts the movement of the FOWT 100. FIG. 2 shows circles around the locations of the anchors 21, 31, and 41, representing areas 25, 35, and 45 that restrict movement within each anchor assembly 20, 30, and 40. Thus, if all mooring lines and anchors of the mooring system 10 are intact, movement is restricted to area 15, which may be designated the "fault-free area." If anchor assembly 20 fails, the corresponding restriction no longer applies, and the FOWT 100 can move within area 16 (which includes area 15). Similarly, if anchor assemblies 30 and 40 fail, movement is restricted to areas 17 and 18, respectively. If two anchor assemblies fail, movement is restricted only within the circles 25, 35, and 45 of the remaining anchor assemblies. If all anchor assemblies fail, movement is no longer restricted. In an embodiment, mooring system parameters, particularly the anchor locations and mooring line lengths that determine the areas 25, 35, and 45 of the three anchor assemblies, are employed to estimate the expected location of the FOWT. For example, a model of the FOWT location is employed, which uses the mooring system parameters as constraints. Such a model may further employ environmental parameters, such as the aforementioned wind / current conditions, wave conditions, and tidal information. The mooring system parameters may further include splice line lengths, FOWT float dimensions, and other mooring system parameters related to the location of the FOWT.

[0057] Additionally, position measurements of the FOWT 100 are obtained. The absolute position of the FOWT can be measured, for example, using GPS, GLONASS, GALILEO, or other satellite-based positioning systems. Additionally or alternatively, a motion reference unit (MRU) can be used. Respective position and / or motion sensors can be provided within the FOWT 100, for example, in the nacelle or tower. Such sensors can form part of the system 50, which can use these sensors to measure position.

[0058] If the sensor error distribution or value is not directly available for a sensor or parameter, an estimate can be used instead.

[0059] In one embodiment, the FOWT is monitored for movement outside of a region 15 defined by the constraints of the mooring system parameters. If the FOWT moves outside of region 15, the presence of a mooring fault can be detected. Depending on the region through which the FOWT moves, it can be determined which anchor assembly has failed. However, noise in the FOWT's position signal can trigger fault detection. Therefore, it is preferable to use a statistical model of the FOWT's position for fault detection.

[0060] Such statistical models can be initialized with initial mooring system parameters, which can be determined when installing the FOWT. However, errors may occur in the initial values. Anchor positions, for example, may have a standard deviation of 1 m, while mooring line lengths may have a standard deviation of 10 m. To account for such errors, a probability density function (PDF) can be used for the mooring system parameters at fixed values.

[0061] After setting the initial values, the model can be calibrated, as further described below with respect to Figure 6. The model of the expected position of the FOWT can further employ environmental parameters, for example, as perturbations to the position, so that the model can accurately reflect the expected position of the FOWT relative to the intact mooring system.

[0062] FIG. 3 shows an example of how such a model can be used to monitor the condition of a mooring system, in particular to detect whether a fault exists. New data, in particular new position measurements and / or parameters, may be obtained every period (e.g., determined by a sampling rate), which may be called an epoch. In step S1, a period is waited until new data is available. In step S2, a position measurement of the actual position of the FOWT is obtained, for example, via a data connection or by measuring the position directly. In step S3, mooring line parameters and optionally environmental parameters are obtained. It will be apparent that these do not need to be obtained every time a new position measurement is obtained, but may, for example, only be obtained when the respective parameters are updated.

[0063] In step S4, the probability of the model of the FOWT's expected position is updated. As previously described, a statistical model can be used to model the FOWT's expected position. The observed position model can be composed of, for example, a position term and a noise term, where the position term can be based on previous positions and perturbations. Such perturbations can include constraints on mooring system parameters and can further include unconstrained perturbations due to environmental conditions. Because the parameters of the model are known, the probability that the model accurately reflected the FOWT's position can be determined given the actual observed position measurements of the FOWT. For example, the respective conditional probabilities can be calculated.

[0064] As new data, in particular new position measurements, become available, the probabilities can be updated with new FOWT position observations. For such updates, inference, in particular Bayesian inference, can be used.

[0065] Steps S1-S4 therefore allow the model probabilities to be continuously updated as soon as new position measurements become available.

[0066] Such a probability is indicative of a mooring system fault, and since this model is based, for example, on parameters of an intact mooring system, if the probability that this model is correct based on measurement data is below a certain threshold, a mooring system fault may be detected. Similarly, on the other hand, it is possible to construct a model of a faulty mooring system, for example one whose movements are restricted to only within one of areas 16, 17, 18, and if the probability that such a model is correct exceeds a certain threshold, a fault may likewise be detected. Thus, in step S5, it is determined whether the probability, sometimes referred to as the "probability of fault," is indicative of a mooring system fault, such as a mooring line fault. If not, the method continues to step S1 to obtain the next position measurement.

[0067] If a mooring system fault is detected in step S5, the method proceeds to step S6, where mitigating measures are taken. Such mitigating measures may include activating an alarm, operating the FOWT in a safe mode, for example, stopping FOWT operation, reducing the FOWT and power output, enabling or disabling the FOWT's operating mode (in particular, an up-power mode or a down-power mode), and providing a notification to the operator. It will be apparent that several of these mitigating measures may be implemented in parallel. Typically, activation of an alarm and operation of the FOWT in a safe mode are performed, which may include respective notifications.

[0068] In step S7, maintenance or repair of the FOWT is performed. It will be apparent that step S7 may not form part of an embodiment of the method and may be performed by maintenance personnel. In step S8, mooring system fault detection is reset, which may include resetting parameters of the model, e.g., initializing mooring system parameters. The method may then start again from step S1.

[0069] In certain embodiments, several models are employed, with one model using mooring system parameters for an intact mooring system, while one or more other models use mooring system parameters corresponding to a failed mooring system. In particular, a respective model and mooring system parameters can be used for each detected failure mode. In the example of Figure 2, for example, three models of a failed mooring system can be employed: one model restricting movement to area 16 (mooring line 22 failed), one model restricting movement to area 17 (mooring line 32 failed), and one model restricting movement to area 18 (mooring line 42 failed). For each of these four or more models (one for the intact mooring system and three for the three failure modes), a respective probability can be calculated and updated in step S4.

[0070] In such an embodiment, a mooring system failure may be detected in step S5 either by one of the models corresponding to the failed mooring system having a probability above a respective threshold and / or by the probability of the model of the intact mooring system being below a respective threshold. Preferably, the probability of the failed mooring system model is compared with the probability of the intact mooring system model, and a failure is detected if the probability of the intact mooring system model is exceeded. This allows for reliable and efficient fault detection.

[0071] FIG. 4 shows an example of such fault detection. The position 11 of the FOWT is measured. As can be seen in FIG. 4, the FOWT moves along a path having a first section 401 and a second section 402. FIG. 5 shows the determined probability P for a model corresponding to an intact mooring system (diagram curve 502) and the probability P for a model corresponding to a faulted mooring line 22 of the mooring system (diagram curve 501). As can be seen, after the FOWT leaves the area 15 defined by the intact mooring system, the probability of the model corresponding to the intact mooring system (diagram curve 502) decreases, while the probability of the model corresponding to the faulted mooring line 22 increases (diagram curve 501). Thus, a fault in the mooring line 22 can be reliably detected. Note that in FIG. 4, the first section 401 of the path corresponds to the portion of curves 501, 502 where the intact mooring system model (curve 502) still has a high probability. Section 402 of the path corresponds to a high probability of a failed mooring system model (curve 501). Because a statistical model is used that is more tolerant to outliers, the probability only changes after the FOWT has already passed circle 25, which indicates the constraint imposed by mooring lines 22.

[0072] The mooring system line parameters may suffer from inaccuracies in the initial values, for example, as the mooring lines get longer or the anchors move, they may suffer from drift, etc. Thus, the condition of the mooring system may change. Therefore, monitoring the condition of the mooring system may include adjusting the mooring system parameters based on the obtained parameters, in particular the model, and the obtained position measurements of the actual position of the FOWT.

[0073] In one embodiment, the obtained position measurements are used to calibrate or adjust mooring system parameters. For example, over a period of time, the obtained position measurements should correspond to area 15 (FIG. 2), assuming no mooring system faults. The FOWT position, in particular, will, over time, approximately rub the intersection of the three circles 25, 35, and 45 in FIG. 2. If the corresponding area defined by the current mooring system parameters does not correspond to the measurement positions actually obtained by the FOWT, the mooring system parameters can be adjusted to match this area to the actually measured area. For example, the curvature of the circular portions bounding the area indicates the length of each mooring line. Furthermore, the position of the circular portions indicates the anchor position of each anchor assembly. Therefore, based on the actual position measurements of the FOWT position, the mooring system parameters (e.g., anchor positions and mooring line lengths) can be adjusted to match the actually measured FOWT position.

[0074] However, there may be sensor noise and / or the FOWT may only have searched a small region of area 15, for example due to wind or current conditions. To improve the calibration of the mooring system parameters, the use of a statistical model is preferred. The model may be the same as or similar to the models described above and may, in particular, take environmental conditions into account.

[0075] An example of each method is shown in the flow diagram of Figure 6. In step S61, a model of the expected position of the FOWT is initialized with initial mooring system parameters. The model is used to calibrate the mooring system parameters, so it assumes an intact mooring system. As mentioned above, the anchor position and mooring line length measured during installation of the FOWT can be used for initialization. In step S62, the system waits again for a period of time, which may correspond to the update period for updating the mooring system parameters. In step S63, position measurements of the FOWT's actual position are obtained over a specific period of time. For example, position measurements may be collected over a period of one, two, or three weeks, preferably over a period of one to two months. During this period, the FOWT will brush against an area 15 where its movement is restricted by the mooring system. This is exemplarily shown in Figure 7, which shows the measured position 11 of the FOWT. The position is displayed as a dark cloud brushing against the area 15.

[0076] In step S64, optionally further parameters are obtained, such as environmental parameters, which can be used in the statistical model of the FOWT position, as described above.

[0077] In step S65, the mooring system parameters are updated by adjusting the model of the predicted FOWT position to match the position measurements of the actual FOWT position. This is shown in FIG. 7, where circles 25, 35, and 45 indicate the initial mooring system parameters. As can be seen, the area 701 covered by the actual measured position 11 of the FOWT is different, specifically, smaller than the area formed by the intersection of the three circles. Therefore, the model, specifically the mooring system parameters, are adjusted so that the model matches the observations. In FIG. 7, this is shown by adjusted circles 26, 36, and 46, which correspond to the adjusted mooring system parameters. Note that both the anchor position and the mooring line length may be adjusted.

[0078] Adjustments can be made using statistical methods applied to a model of the expected FOWT location. For example, a conditional probability can be determined that a model containing mooring system parameters is correct given the actual observed position measurements. This probability can be maximized by varying the parameters to obtain an adjusted set of mooring system parameters that more closely resemble the observed values. Due to nonlinearities, it can be difficult to derive an analytical expression for this probability, so numerical methods can be used to derive the probability. Such a method may be, for example, Markov Chain Monte Carlo (MCMC) sampling. In Figure 7, such an MCMC algorithm is applied to derive adjusted mooring system parameters, indicated by circles 26, 36, and 46, based on the measured location 11. As can be seen, the adjusted mooring system parameters better reflect the area 15 where the FOWT 100's movement is actually restricted.

[0079] As mentioned above, the model can employ a probability density function (PDF) to describe the mooring system parameters. This is exemplarily shown in FIG. 8. In the first diagram, curve 801 shows the PDF for the position px of the mooring line 22 at which the model is initialized. The second diagram in FIG. 8 shows, in curve 811, the probability density function for the position py of the anchor 21 at which the model is initialized. Finally, the third diagram in FIG. 8 shows, using curve 821, the probability density function for the length of the mooring line 22 at which the model is initialized. It is clear that the remaining anchors 31, 41 and mooring lines 32, 42 are provided with their own PDFs. FIG. 8 further shows each PDF after the calibration / adjustment of FIG. 6 has been performed. As can be seen, the calibration has shifted the position px of the anchor 21 to correspond to the newly adjusted PDF 802. Similarly, the position py of the anchor 21 has been shifted and is now represented by the adjusted PDF 812. The expected accuracy of both the anchor positions x and y has been maintained by the calibration. In the third diagram of Figure 8, we can see that the PDF for mooring line length has similarly shifted due to calibration. Furthermore, the width (i.e., variance) of the PDF has been significantly reduced, implying a higher expected accuracy for mooring line length. Meanwhile, for anchor position, the accuracy of the estimation remains essentially unchanged. The changes to the PDF for mooring system parameters shown in Figure 8 correspond to those shown in Figure 7. Because a relatively large number of position measurements are available, calibration can shift the position of the PDF by a relatively large distance from its initial position while maintaining accuracy, as shown in Figure 7.

[0080] 6 may be performed immediately after installation of the FOWT for initial calibration. It may also be repeated periodically. Thus, after calibrating the mooring system parameters in step S65, the method returns to step S62 to await the next calibration cycle.

[0081] It should be apparent that deriving the state of the mooring system of the FOI from the obtained position measurements preferably includes both fault detection, as shown in FIG. 3, and mooring system parameter updating, as shown in FIG. 6. Preferably, after installation of the FOWT, the calibration of FIG. 6 is first performed to derive an accurate state of the mooring system, and in particular, to accurately derive the mooring system parameters. During and / or after the initial calibration, the method of FIG. 3 is performed to detect a fault condition in the mooring system. Both methods may employ similar or the same model, and the mooring system parameters of the model employed by the method of FIG. 3 may be updated as soon as new mooring system parameters are determined by the method of FIG. 6. The calibration of FIG. 6 may be performed repeatedly at predetermined times, for example, after a certain period of time has elapsed. In other embodiments, the method of FIG. 6 may be performed continuously during operation of the FOWT.

[0082] Although the above description has been given in terms of FOWTs, it will be apparent that it is equally applicable to other floating offshore installations.

[0083] While particular embodiments are disclosed herein, various changes and modifications can be made without departing from the scope of the invention. The present embodiments are considered in all respects to be illustrative and not restrictive, and all changes that come within the meaning and range of equivalency of the appended claims are intended to be embraced therein.

[0084] It should be noted that embodiments of the present invention are described with reference to different subject matters. In particular, some embodiments are described with reference to apparatus-type claims, and other embodiments are described with reference to method-type claims. However, those skilled in the art will understand from the above and following description that, unless otherwise specified, in addition to any combination of features belonging to one type of subject matter, any combination between features relating to different subject matters, in particular any combination between features of an apparatus-type claim and a feature of a method-type claim, is also considered to be disclosed together with this application.

Claims

1. 1. A method for monitoring a mooring system (10) of a floating offshore installation (FOI) (100) moored by said mooring system (10), comprising: obtaining parameters related to the location of the FOI, the parameters including at least mooring system parameters indicative of an area (15) in which the FOI is expected to be located; obtaining a position measurement of the actual position (11) of said FOI; deriving a state of the mooring system (10) of the FOI from the acquired parameters and the position measurements of the FOI; Including, The mooring system parameters include parameters of one or more elements of the mooring system that limit movement of the FOI relative to an area in which the FOI may be located, and the mooring system parameters that limit the movement of the FOI relative to the area include a length of at least one mooring line of two, three, or more anchor assemblies of the mooring system. method.

2. 2. The method of claim 1, wherein obtaining position measurements of the actual location (11) of the FOI comprises obtaining a measured absolute position of the FOI and / or obtaining measurements of the actual location using satellite-based position measurements and / or motion reference unit-based position measurements.

3. The method of claim 1 or 2, wherein the mooring system parameters further include at least one anchor position of the two, three, or more anchor assemblies (10, 20, 30) of each of the mooring systems.

4. 4. The method of claim 1, wherein deriving a state of the mooring system (10) of the FOI comprises employing a model of the expected position of the FOI, the model employing the obtained parameters, and comparing the model with the position measurements.

5. The method of claim 4 , wherein comparing the model to the location measurements comprises determining a probability that the model matches the observed location measurements.

6. 6. The method of claim 5, wherein the step of obtaining position measurements comprises repeatedly obtaining position measurements of the actual position (11) of the FOI (100), and the method further comprises using the repeatedly obtained position measurements to update the probability that the model matches the observed position measurements, and the updating of the probability is preferably performed using Bayesian estimation.

7. The method of any one of claims 1 to 6, wherein deriving a state of the mooring system (10) comprises detecting whether a fault in the mooring system (10) exists.

8. the model employs mooring system parameters of an intact mooring system and the probability that the model matches the observed position measurements is below a threshold; and / or if the model employs mooring system parameters of the failed mooring system and the probability that the model matches the observed position measurements is above a threshold; 8. The method of claim 7 when dependent on claim 4, wherein the presence of a fault in the mooring system (10) is detected.

9. the mooring system parameters include one or more sets of intact mooring system parameters associated with an intact mooring system (10) and faulted mooring system parameters associated with a mooring system (10) having a fault; Detecting whether a fault exists in the mooring system (10) comprises: providing a model of the expected location of said FOI (100) employing intact mooring system parameters; providing one or more models for the predicted location of the FOI (100), each of the models employing one of the one or more sets of failed mooring system parameters; determining, for each model, the probability that said model matches the observed location measurements; Detecting whether a fault in the mooring system (10) exists based on said probability, preferably comprising: detecting when the probability of the model adopting a faulty set of mooring system parameters rises above a threshold; detecting that the probability of the model employing the intact mooring system parameters falls below a threshold; and / or detecting when the probability of a model employing the failed set of mooring system parameters rises above a threshold based on the probability of the model employing the intact mooring system parameters; detecting that a fault in the mooring system (10) exists by 9. The method of claim 7 or 8, comprising:

10. 10. The method of claim 1, wherein the step of deriving a state of the mooring system (10) of the FOI (100) comprises deriving updated mooring system parameters of the mooring system (10) of the FOI (100), each updated mooring system parameter preferably being derived repeatedly during operation of the FOI (100).

11. 11. The method of claim 10 when dependent on claim 4, wherein deriving updated mooring system parameters comprises obtaining position measurements by repeatedly obtaining position measurements of the actual position (11) of the FOI (100) over a period of time, and updating the mooring system parameters by adjusting the mooring system parameters so that the model is consistent with the obtained position measurements.

12. 12. A method according to claim 10 or 11 when dependent on claim 5, wherein matching the model with the acquired position measurements comprises adjusting the mooring system parameters to increase the probability.

13. A method of operating a floating offshore wind turbine (FOWT) (100) with a mooring system (10), comprising: monitoring the condition of the FOWT (100) according to the method of any one of claims 1 to 12; performing a predetermined mitigation action if the condition indicates a fault in the mooring system (10), the predetermined mitigation action preferably comprising: activating an alarm, changing the operation of the FOWT (100) to a safe mode; reducing the power output of the FOWT (100); Disabling the power boost mode of the FOWT (100); enabling a power ramp-down mode of the FOWT (100); Stopping operation of the FOWT (100); providing an event notification indicative of a fault in the mooring system; or a combination thereof; Including, Preferably, the method comprises: generating power and / or electrical energy by said FOWT (100); transmitting at least a portion of said power and / or said electrical energy to a receiving facility not located in international waters, in particular located on land, near the coast; supplying at least a portion of said power and / or said electrical energy to an electricity grid, in particular a coastal electricity grid; A method comprising:

14. 14. A system for monitoring a mooring system (10) of a floating offshore installation (FOI) (100) moored by said mooring system (10), said system (50) comprising an interface (53) for obtaining parameters and position measurements of said FOI (100), a processing unit (51) and a memory (52), said memory (52) containing control instructions which, when executed by said processing unit (51), cause said processing unit (51) to perform the method of any one of claims 1 to 13.

15. 14. A computer program for monitoring a mooring system (10) of a floating offshore installation FOI (100) moored by said mooring system (10), said computer program comprising control instructions that, when executed by a processing unit (51) of a system (50) monitoring said mooring system (10), cause said processing unit (51) to perform the method according to any one of claims 1 to 13.

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