Mooring system condition monitoring for floating offshore wind turbines

Abstract

Mooring system condition monitoring for floating offshore wind turbines. A method of monitoring a mooring system (10) of a floating offshore facility (FOI) (100) is provided, the FOI being moored by the mooring system (10). The method comprises obtaining parameters relating to the position of the FOI, where the parameters comprise at least mooring system parameters indicative of an area (15) within which the position of the FOI is expected to be located. The method further comprises obtaining a position measurement of an actual position (11) of the FOI and deriving a state of a mooring system (10) of the FOI from the obtained parameter and from the position measurement of the FOI.

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 a corresponding monitoring system. The present invention also relates to a computer program for monitoring a mooring system of a floating offshore installation. Background Art

[0002] Floating offshore installations (FOIs) and in particular floating offshore wind turbines (FOWTs) are typically attached to the seabed by a mooring system to provide position retention. Position retention is important to ensure that the movement of the FOWT is constrained to a small defined area and to maintain the desired orientation of the floating body of the FOWT. There are different types of floating bodies, and they can be classified into different categories, such as semi-submersible, spar, tension-leg platform or barge type. In addition to providing position retention, the tendons of a tension-leg platform can also ensure that the turbine does not capsize. For semi-submersible, spar or barge type FOWTs, the mooring system typically only provides position retention, but affects the dynamics of the turbine. For example, a broken mooring line can cause an increase in turbine loads and may reduce performance. When such a failure of the mooring system occurs, it is typically necessary to protect the FOWT, for example by a protection function. Therefore, it is desirable to be able to reliably detect failures of the mooring system.

[0003] To detect failures of mooring lines, document WO 2022 / 017834 A1 describes, for example, the measurement of strain in a mooring system or the provision of an electrical signal through the mooring system to determine whether the mooring line is intact. While such solutions provide reliable monitoring of the mooring system, they may require the installation of additional equipment and, therefore, may result in increased costs. In addition, such additional means for monitoring mooring lines may also fail in a harsh seawater environment.

[0004] Document US 9,671,231 B2 also describes a method for monitoring a mooring system for a floating vessel that employs the time of the natural period of the vessel, such as the surge, sway, and / or heave natural period. If the natural period deviates from a reference natural period, a mooring system failure is detected. This method seems to be applicable only to systems in which the mooring lines have a significant effect on the surge, sway, and heave motions of the floating vessel. Summary of the Invention

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

[0006] This need is met by providing a method for monitoring a mooring system of a floating offshore installation (FOI), the floating offshore installation being moored by the mooring system. The method includes obtaining parameters related to the position of the FOI, wherein the parameters at least include mooring system parameters indicating a region within which the position of the FOI is expected to be located. The method further includes obtaining a position measurement of the actual position of the FOI, and deriving the state of the mooring system of the FOI from the obtained parameters and the position measurement 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 may allow for precise monitoring of the mooring system of the FOI such that faults can be monitored without additional dedicated sensors. Furthermore, the monitoring may allow for keeping the mooring system parameters up to date such that changes to the mooring system, such as changes to the mooring line lengths or anchor positions, can be detected and also taken into account when monitoring the state of the mooring system, for example for fault detection. Thus, monitoring the mooring system in this way can be more cost-effective and also less prone to sensor failures. Different from dedicated sensors in a mooring system that are subject to harsh conditions in seawater, sensors for obtaining position parameters for the FOI may for example be placed in the tower or nacelle of a wind turbine where they are protected from such harsh conditions. Position and motion sensors are generally inexpensive, mature and widespread sensor technologies. Furthermore, such position and / or motion sensors may already be present on the FOI such that additional sensors may not be required.

[0009] In one embodiment, obtaining a position measurement of the actual position of the FOI includes using satellite-based position measurements (such as GPS, GLONASS or GALILEO, or any global navigation satellite system GNSS) and / or motion reference unit (MRU)-based position measurements to obtain a measured absolute position of the FOI and / or obtain a measurement of the actual position. Thus, position measurements can be obtained in a simple and cost-effective manner.

[0010] Mooring system parameters can include parameters of one or more elements of the mooring system (e.g., anchors and / or mooring lines), which parameters limit the movement of the FOI (e.g., it can limit the positions where the FOI can be located, i.e., define the area within which the FOI can be located). For example, the mooring system parameters can include the anchor positions and / or mooring line lengths of at least one, two, three, or more anchor assemblies of the mooring system. The anchor positions and mooring line lengths generally limit the movement of the FOI, and if a plurality of such anchor assemblies are provided, the movement of the FOI can be restricted to a relatively small area. By utilizing such mooring system parameters that define such an area and actual position measurements, the state of the mooring system can be obtained accurately and efficiently. For example, the area to which the movement of the FOI is restricted can be defined by the intersection of two, three, or more circles around the different anchor positions of the two, three, or more anchor assemblies. Each circle can correspond to the area on the sea surface within which the corresponding anchor assembly restricts the movement of the FOI. Thus, the circle radius depends on the mooring line length. In other words, the circle radius can correspond to the maximum distance that the mooring point on the FOI to which the mooring line is attached can be from the anchor position when the anchor position is projected onto the sea surface.

[0011] In one example, one or more, preferably all, of the mooring system parameters can be provided in the form of a probability density function (PDF). By utilizing the PDF instead of fixed values, the expected accuracy of the parameter values (e.g., through the width of the corresponding distribution) can be taken into account. The error distributions of the parameters (e.g., initial anchor positions and mooring line lengths) can be particularly taken into account. By taking into account the error uncertainties, the robustness of detecting the state of the mooring system can be increased.

[0012] The parameters can also include one or more environmental parameters, where the one or more environmental parameters can preferably include at least one of meteorological oceanographic parameters, wind conditions parameters, wind speed, wind direction, oceanographic parameters, flow velocity, flow direction, wave height, wave periodicity, and tidal parameters. Such environmental parameters can affect the actual position of the FOI. They can be used in the estimation of the expected position of the FOI based on the mooring system parameters, particularly for fine-tuning the expected position. Thus, providing an accurate estimate of the expected position can allow for a more reliable determination of the state of the mooring system.

[0013] Obtaining the state of the mooring system can include estimating the expected position from the obtained parameters and comparing the expected position with the position measurement of the actual position of the FOI. By this method, it can be reliably detected whether the mooring system parameters are inaccurate and may need adjustment, and / or whether there is a fault in the mooring system.

[0014] The state of the mooring system for the FOI can include, in an exemplary embodiment, employing a model for the expected position of the FOI, where the model can employ the obtained parameters, in particular mooring system parameters and optionally the one or more environmental parameters, and comparing the model with position measurements. For example, statistical methods can be used to compare the model with position measurements (e.g., using the position measurements as the expected result of the model), and / or by comparing the result or expected position provided by the model with the actual position measurement.

[0015] The method can include obtaining updated values of 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 can be obtained, and the corresponding updated parameters can be used to update the model. For example, the model can be updated when the updated parameters become available, or can be updated at periodic or predetermined time intervals. Thus, a model that matches the current conditions can be obtained, and the reliability of detecting mooring system failures can be improved.

[0016] For example, in a simple case, the model can define the area within which the position of the FOI is limited, and the actual position measurement can be compared with this area to obtain the state of the mooring system.

[0017] For example, obtaining the state can include comparing the area within which the FOI is expected to be located with the actual position measurement for the FOI. The area within which the FOI is expected to be located can correspond to the area within which the movement of the FOI is restricted by the mooring system parameters (in a simple model), or can correspond to a part thereof (e.g., when other parameters such as environmental parameters are employed in a more complex model). For example, the area can correspond to the probability distribution of the FOI being in a particular position. The probability distribution can change over time, especially when the obtained parameters change (e.g., due to changing environmental conditions and / or changes in the calibration of the mooring system parameters).

[0018] For example, obtaining the state of the mooring system can include obtaining the probability distribution of the expected position of the FOI from the obtained parameters, and comparing the actual position of the FOI with the probability distribution of the expected position of the FOI. A model that employs the obtained parameters, in particular mooring system parameters and optionally environmental parameters, can be used to determine the probability distribution of the expected position of the FOI. For example, this comparison can be used to detect failures of the mooring system. If the actual position of the FOI does not match the probability distribution of the expected position, for example if the actual position is outside the area with a (predetermined) minimum probability, a failure can be detected.

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

[0020] For example, comparing the model with a position measurement can include determining the probability that the model matches the observed position measurement. In particular, this probability can be the probability that the model is correct given the observed position measurement. For example, this probability can be expressed as the conditional probability P(M|X(n)), where M is the model (which depends on the parameters obtained) and X(n) is the obtained position measurement result. This probability can be efficiently used to indicate a failure of the mooring system; thus, it can also be referred to as the "failure probability".

[0021] Obtaining a position measurement can include repeatedly obtaining a position measurement of the actual position of the FOI. The method can also include using the repeatedly obtained position measurements (e.g., once they become available) to update the probability that the model matches the observed position measurement. For example, updating this probability can be performed using Bayesian inference. By using such a method, it can be quickly and efficiently determined whether the actual position of the FOI no longer matches the model, such that a failure of the mooring system can be reliably detected.

[0022] In one embodiment, obtaining the state of the mooring system includes detecting whether there is a failure of the mooring system.

[0023] For example, detecting that there is a failure of the mooring system can include detecting that a position measurement of the actual position of the FOI is different from the position of the FOI expected according to the parameters obtained. For example, if the actual position is different from the region in which the position is expected to be located, e.g., if the actual position is different from the region to which the expected position is limited based on the mooring system parameters associated with an intact mooring system, then a failure can be detected. For example, if three or more anchor assemblies are used, the mooring system parameters may limit the expected position of the FOI to a (relatively small) region, and if the actual measured position of the FOI is (significantly) outside this region, then a failure can be detected.

[0024] Preferably, the detection of such a fault is based on the model. For example, if the model uses mooring system parameters for an intact mooring system and the probability that the model matches the observed position measurement drops below a threshold, a fault in the mooring system (e.g., a mooring line fault) can be detected. Additionally or alternatively, if the model uses mooring system parameters for a faulty mooring system and the probability that the model matches the observed position measurement rises above a threshold, a fault can be detected. For example, the model for a faulty mooring system can assume that a mooring line is broken, such that the area in which the position of the FOI is confined by the mooring system is larger; by detecting that the probability that the actually measured position of the FOI matches the faulty mooring system model is high, a fault in the mooring system can be efficiently detected.

[0025] In one exemplary embodiment, the mooring system parameters include intact mooring system parameters associated with an intact mooring system and one or more sets of faulty mooring system parameters associated with a mooring system having a fault, such as one or more broken mooring lines. Detecting whether there is a fault in the mooring system can include: providing a model for the expected position of the FOI that uses the intact mooring system parameters; providing one or more models for the expected position of the FOI, each of the models using one (in particular, a different) set of the one or more sets of faulty mooring system parameters; determining, for each model, the probability that the model matches the observed position measurement; and based on the probabilities, detecting whether there is a fault in the mooring system. By matching the position measurement of the actual FOI position to a plurality of different models for different mooring system faults and for an intact mooring system, the presence and type of a mooring system fault can be reliably detected.

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

[0027] As described above, the obtained parameters may include corresponding environmental parameters, and the model(s) with intact mooring system parameters and / or the one or more models with a corresponding set of faulty mooring system parameters may utilize the environmental parameters. The method may include obtaining updated values of one or more of the obtained parameters and using the corresponding updated parameters to adjust the model(s) with intact mooring system parameters and / or the one or more models with a corresponding set of faulty mooring system parameters, as explained above. For example, one or more updated environmental parameters and / or one or more updated mooring system parameters may be obtained, and the corresponding model(s) may be updated with the obtained updated parameters, e.g., once the updated parameters become available, or at periodic or predetermined time intervals. The updated mooring system parameters may be obtained as further described below.

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

[0029] In one embodiment, obtaining the state of the mooring system of the FOI may include obtaining updated mooring system parameters of the mooring system of the FOI. The corresponding updated mooring system parameters may preferably be obtained repeatedly during the operation of the FOI. Such updated mooring system parameters may be obtained, for example, at predetermined time points or after predetermined time periods. They may be obtained periodically.

[0030] For example, the method may include adjusting the model based on the obtained position measurements, wherein adjusting the model may include updating the model based on the obtained updated mooring system parameters.

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

[0032] For example, obtaining updated mooring system parameters may include: obtaining the position measurements by repeatedly obtaining position measurements of the actual position of the FOI over a period of time, and updating the mooring system parameters by adjusting the model, in particular the mooring system parameters, such that the model matches the obtained position measurements. The period of time may be, for example, more than one day, or more than one week, two weeks or three weeks, or even more than one month. The period of time may be, for example, between 0.5 months and 4 months, such as 1 to 2 months. For example, after initializing the model, the position measurements may be obtained over a month or more, and the position measurements may be used to update the model by updating the mooring system parameters (initial and / or subsequent calibrations). After this period of time, the FOI should have outlined most of the area within which its position is confined by the mooring system; by comparing the expected position (i.e., the area within which it is expected to be located due to the constraints of the mooring system) with the actually measured position, the mooring system parameters can be updated in an accurate and efficient manner. A mooring system in good condition may be assumed for the mooring system parameters and / or the model.

[0033] For example, such an update of the mooring system parameters may be performed after installation, for example, after the initialization of the model. The update of the mooring system parameters may be repeatedly performed during the operation of the FOI, for example, by assuming a mooring system in good condition and collecting position measurements over a corresponding period of time.

[0034] The mooring system parameters may define the area within which the possible position of the FOI is limited, and updating the mooring system parameters may include adjusting the mooring system parameters such that the area corresponds to the position measurements of the actual position of the FOI.

[0035] As a specific example, obtaining updated mooring system parameters may include obtaining the curvature and / or position of a circular segment surrounding the area covered by the obtained position measurements of the FOI. The circular segment may correspond to a circle defined by the anchor and the mooring line. It may also include obtaining the mooring line length and / or the anchor position of the anchor assembly of the mooring system accordingly from the curvature and / or position of the circular segment. This may be done for each circular segment surrounding the area covered by the actual measured position of the FOI, and thus for each anchor assembly of the mooring system. Thus, the actual updated mooring line length and / or anchor position can be obtained.

[0036] In a preferred embodiment, adjusting the model to match the obtained position measurements may include adjusting the 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 position). In particular, the probability (e.g., conditional probability) may be maximized.

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

[0038] Obtaining the state of the mooring system can be repeatedly performed when a new position measurement of the actual position of the FOI is obtained. For example, each time a new position measurement is obtained, the state of the mooring system can be obtained. Thus, fast and efficient fault detection can be achieved.

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

[0040] By using a model for the expected position of the FOI and in particular a statistical model, several advantages can be achieved. For example, if the position measurement of the actual FOI position is outside the region defined by the constraints due to the mooring system parameters, which may be due to measurement errors, a fault is not immediately detected. Thus, outliers that may be due to detection noise do not lead to the detection of a fault. In addition, since such a model for the movement of the FOI can take into account environmental data such as wind speed or wind direction or current speed and current direction, a fault in the mooring system can be detected even if the FOI has not left the region defined by the mooring system parameters. If the equilibrium position of the FOI changes, for example, in a manner inconsistent with the wind direction or current direction, a fault can be detected.

[0041] In one embodiment, a method of operating a floating offshore wind turbine (FOWT) including a mooring system is provided. The method includes monitoring the state of the FOWT according to any one of the methods described herein. If the state of the mooring system indicates a fault in the mooring system, the method includes performing a predetermined mitigation action. By this method, inefficient operation of the FOWT and even damage to the FOWT can be prevented.

[0042] According to one embodiment and / or according to an independent aspect, a method for operating a floating offshore wind turbine (FOWT) is disclosed, wherein the method includes: generating electrical power and / or electrical energy by the FOWT; transmitting at least a portion of the electrical power and / or electrical energy to an electrical receiving device that is not located in international waters and in particular is located on land, ashore; and supplying at least a portion of the electrical power and / or electrical energy to a public power grid, in particular an onshore public power grid.

[0043] For example, performing a predetermined mitigation action may include: activating an alarm, changing the operation of the FOWT into a safe mode, reducing the power output of the FOWT, stopping the operation of the FOWT, disabling an enhanced rating mode of the FOWT (such as a power boost operation mode), initiating a reduced rating mode of the FOWT (e.g., applying a conservative collective pitch angle offset), and providing an event notification indicating a mooring system failure, either singly or in combination. For example, such notification may be provided to an operator via a communication link. Thereby, damage to the wind turbine can be prevented, and an inspection / repair of the mooring system can be triggered.

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

[0045] According to another embodiment of the present invention, there is provided a system for monitoring a mooring system of a floating offshore installation, the floating offshore installation being moored by the mooring system. The system for monitoring includes an interface for obtaining parameters and position measurements of the FOI (in particular the parameters and position measurements mentioned above), a processing unit, and a memory. The memory includes control instructions which, when executed by the processing unit, cause the processing unit to perform any one of the methods described herein. Such a system may also include a control system which controls the operation of the FOI (e.g., the FOWT), as described herein. It should be clear that the system may include: a part resident in the FOI, such as a control system that controls the functions of the FOI; and a part that may be resident away from the FOI (e.g., on shore), for example, the part of the system that obtains the state of the mooring system, for example, this is by obtaining position measurements from the FOI via a communication link and the interface. Thus, the system may be a distributed system. In other embodiments, the system is entirely contained within the FOI.

[0046] According to another embodiment, there is provided a FOWT including such a system.

[0047] Another embodiment of the present invention provides a computer program for monitoring a mooring system of an FOI, the FOI being moored by the mooring system. The computer program includes control instructions which, when executed by the processing unit of the system for monitoring the mooring system, cause the processing unit to perform any one of the methods described herein. Such a computer program may equally operate away from the FOI, or its components may be resident 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 on any system disclosed herein.

[0049] It is to be understood that the features mentioned above and those explained below can be used not only in the corresponding combinations indicated, but also in other combinations or alone, without departing from the scope of the present invention. In particular, the features of different aspects and embodiments of the present invention can be combined with each other, unless otherwise stated. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The foregoing and other features and advantages of the present invention will become further apparent from the following detailed description read in conjunction with the accompanying drawings. In the drawings, like reference numerals represent like elements.

[0051] Figure 1 FIG. is a schematic view showing a floating offshore wind turbine FOWT according to an embodiment, which includes a system for monitoring a mooring system.

[0052] Figure 2 FIG. is a schematic view showing the constraints imposed on the position of the FOWT by the mooring system according to an embodiment.

[0053] Figure 3 FIG. is a flowchart illustrating a method for monitoring a mooring system according to an embodiment, in which a fault of the mooring system is detected.

[0054] Figure 4 FIG. is a schematic view showing the actual measured position of the FOWT when a fault occurs in the mooring system.

[0055] Figure 5 FIG. is a schematic view showing the probabilities of different models for the expected position of the FOWT according to an embodiment.

[0056] Figure 6 FIG. is a flowchart illustrating a method for monitoring a mooring system according to an embodiment, in which mooring system parameters are calibrated based on position measurements.

[0057] Figure 7 FIG. is a schematic view showing the actual measured position of the FOWT over a period of time and the constraints imposed on the position of the FOWT by the mooring system parameters.

[0058] Figure 8 FIG. is a schematic view showing an adjustment of a probability density function representing mooring system parameters based on Figure 7 the position measurements shown in. DETAILED DESCRIPTION

[0059] In the following, embodiments of the present invention will be described in detail with reference to the accompanying drawings. It is to be understood that the following description of the embodiments is given only for illustrative purposes and should not be construed in a limiting sense. It should be noted that the drawings are to be regarded as being only schematically represented and the elements in the drawings are not necessarily drawn to scale with each other. Instead, the representations of the various elements are chosen such that their function and general purpose become apparent to a person skilled in the art. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Unless otherwise specified, the terms "comprising", "having", "including" and "containing" will be construed as open terms (i.e., meaning "including but not limited to").

[0060] Figure 1 Schematically illustrated is a FOWT 100 moored by a mooring system 10 according to an embodiment. The FOWT 100 includes a rotor 101, a tower 102 and a column-type platform 103. The mooring system 10 includes anchor assemblies 20, 30, 40, which include respective anchors 21, 31, 41 and mooring lines 22, 32 and 42. The mooring system 10 restricts the movement of the FOWT 100.

[0061] Figure 1 Also illustrated is a system 50 including a monitoring system. The system 50 includes a processing unit 51 and a memory 52. The processing unit 51 may 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 may include volatile and non-volatile memories, in particular hard disk drives, SSDs, flash memories, RAMs, ROMs, EEPROMs, etc. The memory 52 may store control instructions which, when executed by the processing unit 51, may cause the processing unit 51 to execute any method disclosed herein. These control instructions, in particular the corresponding software code, may implement, for example Figure 3 and / or Figure 6 the methods. The system 50, in particular the monitoring system, may include other components not explicitly shown, such as input / output interfaces to other data sources as well as components to be controlled, a user interface including a display and an input unit, a bus coupling these components, and other components common in computer systems.

[0062] System 50 also includes an interface 53 for data communication. Via a communication link 55, for example, position data measured from the FOWT 100 can be obtained, and control commands can be provided to the FOWT 100. For this purpose, system 50 may also include a control system. Via a communication link 56, data can be supplied to or received from an external data source, for example, through a network such as the Internet. For example, environmental parameters can be obtained via the communication link 56. System 50 can be provided within the FOWT 100, on a different offshore platform, on a floating vessel, or at an onshore location. For example, by providing the monitoring system at an onshore location and the control system within the FOWT 100, system 50 can be further decentralized. The various parts of the system can communicate via the communication links 55, 56. System 50 may include position sensors and / or environmental sensors (e.g., wind sensors, current sensors, and / or wave sensors) located within or on the FOWT 100.

[0063] Each of the anchor assemblies 20, 30, 40 of the mooring system 10 restricts the movement of the FOWT 100. Figure 2 Corresponding circles around the positions of the anchors 21, 31, 41 are illustrated, which represent the regions 25, 35, 45 within which each anchor assembly 20, 30, 40 limits the movement. Thus, if all the mooring lines and anchors of the mooring system 10 are intact, the movement is restricted within the region 15, which can be designated as the "fault-free region". If the anchor assembly 20 fails, the corresponding restriction is no longer imposed, and the FOWT 100 can move within the region 16 (which includes the region 15). Similarly, if the anchor assemblies 30 and 40 fail, the movement is correspondingly restricted within the regions 17 and 18. If two anchor assemblies fail, the movement is only restricted within the corresponding circles 25, 35, 45 of the remaining anchor assemblies. If all the anchor assemblies fail, the movement is no longer restricted. In an embodiment, the parameters of the mooring system, particularly the anchor positions and mooring line lengths that determine the regions 25, 35, 45 of the three anchor assemblies, are used to estimate the expected position of the FOWT. For example, a model of the FOWT position is employed, which uses the mooring system parameters as constraints. The model can also incorporate environmental parameters such as the wind / seacurrent conditions, wave conditions, tidal information, etc., mentioned above. The mooring system parameters can also include the mooring line lengths, the dimensions of the floating body of the FOWT, and other parameters of the mooring system related to the position of the FOWT.

[0064] In addition, position measurements of the FOWT 100 are obtained. For example, the absolute position of the FOWT can be measured using GPS, GLONASS, GALILEO, or other satellite-based position detection systems. Additionally or alternatively, a motion reference unit (MRU) can be used. Corresponding position and / or motion sensors can be provided within the FOWT 100, such as within the nacelle or tower. Such sensors can form part of the system 50, and the system 50 can use these sensors to measure position.

[0065] If for a sensor or parameter, the sensor error distribution or value cannot be obtained directly, then estimation can be used alternatively.

[0066] In one embodiment, it is monitored whether the FOWT moves outside of a region 15 defined by the constraints of the mooring system parameters. If the FOWT moves outside of the region 15, a mooring failure can be detected. Depending on the region where the FOWT moves, which anchor assembly has failed can be determined. However, noise in the position signal of the FOWT may trigger the detection of a failure. Therefore, it is preferred to use a statistical model of the FOWT position for failure detection.

[0067] This statistical model can be initialized using initial mooring system parameters, which can be determined when the FOWT is installed. However, the initial values may be subject to errors. For example, the anchor position may have a standard deviation of 1 m, while the mooring line length may have a standard deviation of 10 m. To address such errors, probability density functions (PDFs) can be used for the mooring system parameters in a fixed value state.

[0068] 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 also incorporate environmental parameters, such as as a perturbation to the position. Thus, for an intact mooring system, the model can accurately reflect the expected position of the FOWT.

[0069] Figure 3 An example is illustrated of how such a model can be used to monitor the state of the mooring system and in particular to detect whether a failure exists. New data, in particular new position measurements and / or parameters, can be obtained each time period (e.g., determined by a certain sampling rate), which time period can be referred to as a training epoch. In step S1, the time period is waited for until new data becomes available. In step S2, a position measurement of the actual position of the FOWT is obtained, such as via a data connection or by directly measuring the position. In step S3, the mooring line parameters and optionally environmental parameters are obtained. It should be clear that these parameters need not be obtained each time a new position measurement is obtained, e.g., they can be obtained only in the case where the corresponding parameters are updated.

[0070] In step S4, the probability of the model for the expected position of the FOWT is updated. As mentioned above, a statistical model can be used to model the expected position of the FOWT. The model for the observed position can, for example, consist of a position term and a noise term, and the position term can be based on the previous position and perturbations. Such perturbations can include constraints on the mooring system parameters and can also include unconstrained perturbations due to environmental conditions. Since the parameters of the model are known, given the actual observed position measurement of the FOWT, the probability that the model correctly reflects the position of the FOWT can be determined. For example, the corresponding conditional probability can be calculated.

[0071] When new data becomes available, particularly new position measurements, this probability can be updated by new FOWT position observations. For such updates, inference, particularly Bayesian inference, can be used.

[0072] Thus, through steps S1 to S4, the probability of the model can be continuously updated once new position measurements become available.

[0073] Since the model is, for example, based on the parameters of an intact mooring system, this probability indicates a fault in the mooring system, and if the probability that the model is correct based on the measurement data drops below a certain threshold, a fault in the mooring system can be detected. On the other hand, it is also possible to construct a model for a faulty mooring system, for example, a model where the movement is restricted to within one of regions 16, 17, 18, and if the probability that this model is correct exceeds a certain threshold, a fault can also be detected. Thus, in step S5, it is determined whether the probability that can thus be called the "fault probability" indicates a mooring system fault, such as a mooring line fault. If this is not the case, the method continues in step S1 and the next position measurement is acquired.

[0074] If a mooring system fault is detected in step S5, the method continues in step S6 with mitigation actions. Such mitigation actions can include activating an alarm, operating the FOWT in a safe mode, for example, stopping the FOWT operation, reducing the power output of the FOWT, starting or disabling the operating mode of the FOWT (particularly increasing or decreasing the rated mode) and providing a notification to the operator. It should be clear that several of these mitigation measures can be formed in parallel. Generally speaking, performing the activation of the alarm and operating the FOWT in a safe mode can include the corresponding notifications.

[0075] In step S7, the FOWT is repaired or serviced. It should be clear that step S7 may not form part of an embodiment of the method but can be performed by maintenance personnel. In step S8, the mooring system fault detection is reset, which can include resetting the parameters of the model, for example, initializing the mooring system parameters. Then, the method can start again at step S1.

[0076] In certain embodiments, a number of models are employed, where one model uses mooring system parameters for an intact mooring system, and one or more other models use mooring system parameters corresponding to a failed mooring system. In particular, for each failure mode to be detected, a corresponding model and mooring system parameters can be used. In Figure 2 the example of, for example, three models for a failed mooring system can be employed, where one model limits movement to region 16 (failure of mooring line 22), one to region 17 (failure of mooring line 32), and one to region 18 (failure of mooring line 42). In step S4, the corresponding probabilities can be calculated and updated for each of these four or more models (one for the intact mooring system and three for the three failure modes).

[0077] In this embodiment, a failure of the mooring system can be detected in step S5 by any one of the models corresponding to the failed mooring system having a probability exceeding a corresponding threshold, and / or the probability of the model for the intact mooring system dropping below a corresponding threshold. Preferably, the probability of the failed mooring system model is compared with the probability of the intact mooring system model, and if the probability of the intact mooring system model is exceeded, a failure is detected. Thereby, reliable and efficient failure detection can be achieved.

[0078] Figure 4 An example of such failure detection is illustrated. The position 11 of the FOWT is measured. As can be in Figure 2 seen, the FOWT moves along a path having a first segment 401 and a second segment 402. Figure 5 Illustrated are the probabilities P (graph curve 502) determined for the model corresponding to the intact mooring system and the probability P (graph curve 501) of the model corresponding to the failed mooring line 22 of the mooring system. As can be seen, after the FOWT has left region 15 defined by the intact mooring system, the probability (graph curve 502) of the model corresponding to the intact mooring system drops, while the probability of the model corresponding to the failed mooring line 22 rises (graph curve 501). Thus, a failure of mooring line 22 can be reliably detected. Note that in Figure 4 this, the first segment 401 of the path corresponds to the part of curves 501, 502 where the model of the intact mooring system (curve 502) still has a relatively high probability. The segment 402 of the path corresponds to the relatively high probability of the model of the failed mooring system (curve 501). When using a statistical model more tolerant to outliers, the probability only changes after the FOWT has passed through circle 25 indicating the constraint imposed by mooring line 22.

[0079] The mooring system line parameters may suffer from insufficient accuracy of the initial values ​​and may also suffer from drift etc., for example if the mooring line is lengthened or the anchor moves. The state of the mooring system may change as a result. Therefore, monitoring the state of the mooring system may include adjusting the mooring system parameters based on the obtained parameters, in particular based on the model, and the obtained position measurements of the actual position of the FOWT.

[0080] In one embodiment, the position measurements obtained are used to calibrate or adjust mooring system parameters. For example, over a period of time, assuming there is no mooring system failure, the position measurements obtained should be consistent with area 15 ( Figure 2 ) corresponds to the FOWT position. In particular, the FOWT position over time will be approximately outlined. Figure 2 The intersection of the three circles 25, 35, 45 in FIG. 4 is a graph showing the intersection of the three circles 25, 35, 45 in FIG. 4. If the corresponding area specified by the current mooring system parameters does not correspond to the measured position actually occupied by the FOWT, the mooring system parameters may be adjusted to align the area with the actually measured area. For example, the curvature of the circle segment surrounding the area indicates the length of the corresponding mooring line. Furthermore, the position of the circle segment indicates the anchor position of the corresponding anchor assembly. Therefore, based on the actual position measurement of the FOWT position, the mooring system parameters (e.g., anchor position and mooring line length) may be adjusted to make them consistent with the actually measured FOWT position.

[0081] However, there may be sensor noise and / or the FOWT may have explored only a small area of ​​the area 15, for example due to wind or current conditions. In order to improve the calibration of the mooring system parameters, a statistical model is preferably used. The model may be the same as or may be similar to the model described above and may specifically take into account environmental conditions.

[0082] Figure 6 An example of a corresponding method is illustrated in the flow chart of . In step S61, a model for the expected position of the FOWT is initialized using the initial mooring system parameters. When the model is used to calibrate the mooring system parameters, it assumes an intact mooring system. As mentioned, the anchor position and mooring line length measured during the installation of the FOWT can be used for this initialization. In step S62, a time period is waited again, which time period may correspond to an update period for updating the mooring system parameters. In step S63, position measurements of the actual position of the FOWT may be obtained within a specific time period. For example, the position measurements may be collected within a time period longer than 1 week, 2 weeks or 3 weeks, preferably within a period of time between 1 month and 2 months. During this time period, the FOWT should outline the area 15 where its movement is confined by the mooring system. This is in Figure 7 , where the measurement locations 11 of the FOWT are shown. These locations appear as dark clouds outlining the area 15.

[0083] In step S64, further parameters are optionally obtained, such as environmental parameters. These parameters may be used in a statistical model for the FOWT location, as described above.

[0084] In step S65, the mooring system parameters are updated by adjusting the model for the expected FOWT position so that it matches the position measurements of the actual FOWT position. Figure 7 , where circles 25, 35 and 45 indicate initial mooring system parameters. As can be seen, the area 701 outlined by the actual measurement position 11 of the FOWT is different from and in particular smaller than the area defined by the intersection of these three circles. Therefore, the model and in particular the mooring system parameters are adjusted so that the model matches the observations. Figure 7 In FIG. 5 , this is indicated by the adjusted circles 26, 36 and 46, which correspond to the adjusted mooring system parameters. It should be noted that both the anchor position and the mooring line length can be adjusted.

[0085] This adjustment may occur by using a statistical method applied to the model of the expected FOWT position. For example, given the actual observed position measurements, the conditional probability that the model including the mooring system parameters is correct may be determined. This probability may be maximized by varying these parameters in order to obtain a set of adjusted mooring system parameters that better matches the observations. Because an analytical expression for this probability may be difficult to obtain due to nonlinearities, a numerical method may be used to obtain this probability. For example, the method may be Markov Chain Monte Carlo (MCMC) sampling. In Figure 7 , such an MCMC algorithm has been applied in order to obtain adjusted mooring system parameters indicated by circles 26, 36 and 46 based on the measured positions 11. As can be seen, the adjusted mooring system parameters better reflect the area 15 to which the movement of the FOWT 100 is actually confined.

[0086] As mentioned above, the model can use probability density functions (PDF) to describe the mooring system parameters. Figure 8 In the first diagram, curve 801 shows the PDF of the position px of the mooring line 22, with which the model is initialized. Figure 8 The second diagram shows the probability density function of the position py of the anchor 21 with the curve 811, with which the model is initialized. Finally, Figure 8 The third diagram of shows the probability density function of the length of the mooring line 22 with which the model is initialized with the curve 821. It should be clear that for the remaining anchors 31, 41 and mooring lines 32, 42, corresponding PDFs are provided. Figure 8 It also shows that in the implementation Figure 6The corresponding PDF after calibration / adjustment. As can be seen, the calibration has shifted the position px of the anchor 21 to correspond to the new adjusted PDF 802. Similarly, the position PY of the anchor 21 has shifted and is now represented by the adjusted PDF 812. The expected accuracy of both the x and y anchor positions is maintained through calibration. In Figure 8 In the third illustration of, it can be seen that the PDF of the mooring line length has also been shifted through calibration. Additionally, the width of the PDF (i.e., the variance) has been significantly reduced, which means a higher expected accuracy of the mooring line length. On the other hand, for the anchor position, the estimated accuracy remains substantially unchanged. Figure 8 The change in the PDF of the mooring system parameters shown in corresponds to Figure 7 the change shown in. As Figure 7 shown in, since a relatively large number of position measurements are available, calibration can move the PDF position a relatively large distance away from the initial position while maintaining accuracy.

[0087] Figure 6 The calibration shown in can be performed immediately after the FOWT installation to calibrate the initial values. Additionally, it can also be repeated periodically. Thus, after calibrating the mooring system parameters in step S65, the method can return to step S62, where it waits for the next calibration cycle.

[0088] It should be clear that the state of the mooring system for which the FOI is obtained from the acquired position measurements preferably includes Figure 3 the fault detection shown in and Figure 6 the update of the mooring system parameters shown in. Preferably, after the FOWT installation, the Figure 6 calibration is first performed to obtain the exact state of the mooring system, especially to obtain the mooring system parameters precisely. During and / or after the initial calibration, the Figure 3 method is performed to detect the fault state of the mooring system. The two methods can use similar or identical models, and once new mooring system parameters are determined by the Figure 6 method, the mooring system parameters used by the Figure 3 method can be updated. Figure 6 The calibration of can be repeatedly performed at predetermined time points, for example, after a specific time period. In other embodiments, the Figure 6 method can be continuously performed during the operation of the FOWT.

[0089] Although the above description has been given with respect to the FOWT, it should be clear that it is equally applicable to other floating offshore facilities.

[0090] Although specific embodiments are disclosed herein, various changes and modifications can be made without departing from the scope of the present invention. The current embodiments should be considered illustrative rather than restrictive in all respects, and all changes falling within the meaning and equivalent scope of the appended claims are intended to be included therein.

[0091] It should be noted that embodiments of the present invention have been described with reference to different subject matters. In particular, some embodiments have been described with reference to apparatus-type claims, while other embodiments have been described with reference to method-type claims. However, those skilled in the art will learn from the foregoing and the following description that, unless otherwise stated, any combination between features related to different subject matters, especially any combination between the features of apparatus-type claims and the features of method-type claims, is also considered to be utilized in the disclosure of this application, in addition to any combination of features belonging to one type of subject matter.

Claims

1. A method for monitoring a mooring system (10) of a floating offshore installation (FOI) (100), wherein the floating offshore installation is moored by means of the mooring system (10), wherein, The method includes: obtaining parameters related to the position of the FOI, where the parameters at least include mooring system parameters indicating a region (15) within which the position of the FOI is expected to be located; obtaining a position measurement of the actual position (11) of the FOI; and obtaining the state of the mooring system (10) of the FOI from the obtained parameters and the position measurement of the FOI, where the mooring system parameters include parameters of one or more elements of the mooring system (10), the parameters limiting the movement of the FOI (100) to a region (15) within which the FOI (100) can be located, and where the mooring system parameters limiting the movement of the FOI (100) to the region (15) at least include the mooring cable lengths of 2, 3 or more anchor assemblies (10, 20, 30) of the mooring system.

2. The method according to claim 1, wherein, Obtaining a position measurement of the actual position (11) of the FOI includes: using satellite-based position measurements and / or motion reference unit-based position measurements to obtain a measured absolute position of the FOI and / or obtaining a measurement of the actual position.

3. The method according to claim 1 or 2, wherein The mooring system parameters further include at least the anchor positions of the corresponding 2, 3 or more anchor assemblies (10, 20, 30) of the mooring system.

4. The method according to any one of the preceding claims, wherein, Obtaining the state of the mooring system (10) of the FOI includes: adopting a model for the expected position of the FOI, where the model adopts the obtained parameters; and comparing the model with the position measurement.

5. The method according to claim 4, wherein Comparing the model with the position measurement includes determining the probability that the model matches the observed position measurement.

6. The method according to claim 5, wherein, Obtaining a position measurement includes repeatedly obtaining a position measurement of the actual position (11) of the FOI (100), and where the method further includes using the repeatedly obtained position measurements to update the probability that the model matches the observed position measurement, where updating the probability is preferably performed using Bayesian inference.

7. The method according to any one of the preceding claims, wherein, Obtaining the state of the mooring system (10) includes detecting whether a fault exists in the mooring system (10).

8. The method according to claim 7 when dependent on claim 4, wherein, A fault in the mooring system (10) is detected in the following cases: if the model adopts mooring system parameters for an intact mooring system and the probability that the model matches the observed position measurement drops below a threshold; and / or if the model adopts mooring system parameters for a faulty mooring system and the probability that the model matches the observed position measurement rises above a threshold.

9. The method according to claim 7 or 8, wherein The mooring system parameters include intact mooring system parameters associated with an intact mooring system (10), and one or more sets of faulty mooring system parameters associated with a mooring system (10) having a fault, where detecting whether a fault exists in the mooring system (10) includes: providing a model for the expected position of the FOI (100) that adopts the intact mooring system parameters; Provide one or more models for the expected position of the FOI (100), each of the models employing a set of the one or more sets of mooring system failure parameters; Determine, for each model, the probability that the model matches the observed position measurements; and Based on the probability, detect whether a failure of the mooring system (10) exists, wherein, preferably, a failure of the mooring system (10) is detected by: Detecting that the probability of a model employing a set of mooring system failure parameters rises above a threshold; Detecting that the probability of a model employing the intact mooring system parameters drops below a threshold; and / or Detecting that the probability of a model employing a set of mooring system failure parameters rises above a threshold, the threshold being based on the probability of a model employing the intact mooring system parameters.

10. The method according to any one of the preceding claims, wherein, Obtaining the state of the mooring system (10) of the FOI (100) includes obtaining updated mooring system parameters of the mooring system (10) of the FOI (100), wherein the corresponding updated mooring system parameters are preferably obtained repeatedly during operation of the FOI (100).

11. The method according to claim 10 when dependent on claim 4, wherein, Obtaining updated mooring system parameters includes obtaining the 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 such that the model matches the obtained position measurements.

12. The method according to claim 10 or 11 when dependent on claim 5, wherein, Causing the model to match the obtained position measurements includes adjusting the mooring system parameters to increase the probability.

13. A method of operating a floating offshore wind turbine FOWT (100) including a mooring system (10), wherein, The method includes: Monitoring the state of the FOWT (100) according to the method of any one of the preceding claims, If the state indicates a failure of the mooring system (10), performing a predetermined mitigation action, wherein the predetermined mitigation action preferably includes one or a combination of the following: Activating an alarm; Changing the operation of the FOWT (100) to a safe mode; Reducing the power output of the FOWT (100); Disabling the increased rating mode of the FOWT (100); Enabling the reduced rating mode of the FOWT (100); Stopping the operation of the FOWT (100); and Providing an event notification indicating the mooring system failure; And preferably, wherein the method further includes: Generating electrical power and / or electrical energy by the FOWT (100); Transmitting at least a portion of the electrical power and / or the electrical energy to an electrical receiving device not located in international waters, particularly located on land, ashore; and Supplying at least a portion of the electrical power and / or the electrical energy to a public power grid, particularly an onshore public power grid.

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

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

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