Method and device for controlling floating wind turbine

Abstract

The present application discloses a method and device for controlling a floating wind turbine, which is applied to the field of wind power generation technology. In the present application, based on the real-time operating condition data of the floating wind turbine acquired, the actual operating condition type of the operating condition and the tilt angle data and tilt angle acceleration of each component are determined. Each floating wind turbine includes multiple components. Based on the determined tilt angle data and tilt angle acceleration of each component, the collaborative control parameters of each component can be determined. And based on the actual operating condition type of the operating condition, the collaborative coefficient of each component under the operating condition is determined, and the floating wind turbine is collaboratively controlled through the collaborative coefficient and collaborative control parameters. Even in the face of complex conditions and different operating conditions, the proportion of different components in the collaborative control operation can be changed according to the collaborative coefficient, so that the balance of the floating wind turbine can be collaboratively controlled. Therefore, the balance stability of the floating wind turbine can be accurately controlled.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation, and in particular to a method and device for controlling a floating wind turbine. Background Art

[0002] Floating wind turbines consist of a wind turbine and a floating system. The floating system includes a foundation, mooring anchor, anchor foundation, and dynamic submarine cables. Floating wind turbines are suitable for deep waters and areas with high wind energy availability. However, floating wind turbines are bulky, subject to significant swing in the foundation, and the anchor chain has high nonlinearity due to random spatiotemporal constraints.

[0003] Typically, a single device and technology is used to control the balance and stability of floating wind turbines. However, under the influence of complex load environments that floating wind turbines are subjected to for a long time, a single device and technology is difficult to achieve stability control for large-capacity floating wind turbines. This results in an inability to accurately control the balance and stability of floating wind turbines. Summary of the Invention

[0004] In view of the above problems, the present application provides a method and device for controlling a floating wind turbine, which can accurately control the balance stability of the floating wind turbine.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] In a first aspect, the present application provides a method for controlling a floating wind turbine, wherein the floating wind turbine comprises a plurality of components, and the method comprises:

[0007] Determining, based on the real-time operating condition data of the floating wind turbine, the actual operating condition type of the floating wind turbine and the respective tilt angle data and tilt angle acceleration of the plurality of components;

[0008] determining a coordinated control parameter of the component according to the tilt angle data and the tilt angle acceleration of the component;

[0009] Determining a coordination coefficient of the components according to the actual operating condition type, wherein the coordination coefficient is a weight coefficient of the components during coordinated control;

[0010] Corresponding components in the floating wind turbine are coordinated and controlled according to the coordination coefficient and the coordination control parameter.

[0011] Optionally, before determining the synergy coefficient of the component according to the actual operating condition type, the method further includes:

[0012] Constructing a first mapping relationship between multiple operating condition types and synergy coefficients of components of the floating wind turbine;

[0013] Determining the coordination coefficient of the components according to the actual working condition type specifically includes:

[0014] Based on the first mapping relationship, a coordination coefficient of the component corresponding to the actual operating condition type is determined.

[0015] Optionally, the constructing of a first mapping relationship between the various operating condition types and synergy coefficients of the components of the floating wind turbine specifically includes:

[0016] For a target operating condition type among the multiple operating condition types, constructing multiple sets of synergy coefficient groups, each of which includes synergy coefficients of the multiple components; the target operating condition type is one of the multiple operating condition types;

[0017] Using each group of the synergy coefficients to perform synergistic control on the floating wind turbines under the target operating condition type;

[0018] Determining a target coordination coefficient group from the plurality of coordination coefficient groups according to a time required for the equilibrium state of the floating wind turbine to return to a preset equilibrium stability value, and the tilt angle data and tilt angle acceleration of each of the coordinatedly controlled components;

[0019] A first mapping relationship between the target operating condition type and the coordination coefficient of each component in the target coordination coefficient group is constructed.

[0020] Optionally, determining a target synergy coefficient group from the plurality of synergy coefficient groups according to a time required for the equilibrium state of the floating wind turbine to return to a preset equilibrium stability value, and tilt angle data and tilt angle acceleration of each of the synergistically controlled components, specifically includes:

[0021] For a target component among the plurality of components, respectively using a plurality of sets of the coordination coefficient groups and the coordination control parameters under the target operating condition type to coordinately control the target component;

[0022] The synergy coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value and minimizes the inclination angle data and inclination angle acceleration of the target component after synergistic control is selected as the target synergy coefficient group.

[0023] Optionally, the tilt angle data includes roll angle data and pitch angle data of the component, and the tilt angle acceleration includes roll acceleration and pitch acceleration; and selecting the coordination coefficient group that minimizes the time taken for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value and minimizes the tilt angle data and tilt angle acceleration of the target component after coordinated control as the target coordination coefficient group specifically includes:

[0024] The coordination coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value, minimizes the roll angle data of the target component after coordinated control, minimizes the pitch angle data of the target component after coordinated control, minimizes the roll acceleration of the target component after coordinated control, and minimizes the pitch acceleration of the target component after coordinated control is selected as the target coordination coefficient group.

[0025] Optionally, the performing coordinated control on corresponding components in the floating wind turbine according to the coordinated coefficient and the coordinated control parameter specifically includes:

[0026] The coordination coefficient and the coordinated control parameter are input into the objective function, and the error value of the tilt of the target component can be calculated according to the following formula. The error value is proportional to the time it takes for the balance of the target component to return to stability after coordinated control, the roll angle, the pitch angle, the roll acceleration, and the pitch acceleration:

[0027] f=p1Δt+p2Δθ 横摇 +p3Δθ 纵摇 +p4Δa 横摇 +p5Δa 纵摇

[0028] Wherein, f is the error value of the target component after coordinated control under the target operating condition type, p1 is the weight coefficient of the time for the balance of the floating wind turbine to return to stability after coordinated control, p2 is the weight coefficient of the roll angle of the floating wind turbine after coordinated control, p3 is the weight coefficient of the pitch angle of the floating wind turbine after coordinated control, p4 is the weight coefficient of the roll acceleration of the floating wind turbine after coordinated control, p5 is the weight coefficient of the pitch acceleration of the floating wind turbine after coordinated control, Δt is the time for the balance of the floating wind turbine to return to a preset stable value after coordinated control, Δθ 横摇 is the roll angle data of the floating wind turbine after coordinated control, Δθ 纵摇 is the pitch angle data of the floating wind turbine after coordinated control, Δa横摇 is the roll acceleration of the floating wind turbine after coordinated control, Δa 纵摇 is the pitch acceleration of the floating wind turbine after coordinated control.

[0029] Optionally, before constructing the first mapping relationship between the multiple operating condition types and the synergy coefficients of the components of the floating wind turbine, the method further includes:

[0030] determining overall tilt angle data of the floating wind turbine according to the operating condition data of the floating wind turbine;

[0031] The synergy coefficient of the components and the corresponding tilt angle data meet the following preset constraints:

[0032] The sum of the products of the synergy coefficients of the components and the corresponding tilt angle data is equal to the overall tilt angle data of the floating wind turbine; and the sum of the synergy coefficients of all the components is equal to 1.

[0033] Optionally, before determining the actual operating condition type of the floating wind turbine and the respective tilt angle data and tilt angle acceleration of the plurality of components based on the real-time operating condition data of the floating wind turbine, the method further comprises:

[0034] Constructing multiple sets of operating condition data of the floating wind turbine;

[0035] Calculating, based on the operating condition data, the overall tilt angle data of the floating wind turbine, the tilt angle data of the components, and the tilt angle acceleration;

[0036] The overall tilt angle data of the floating wind turbine and the tilt angle data and tilt angle acceleration of the components corresponding to the different operating condition data are saved.

[0037] In a second aspect, the present application provides a device for controlling a floating wind turbine, comprising:

[0038] a first acquisition module, configured to determine, based on real-time operating condition data of the floating wind turbine, an actual operating condition type of the floating wind turbine and respective tilt angle data and tilt angle acceleration of the plurality of components;

[0039] a second acquisition module, configured to determine a coordinated control parameter of the component according to the tilt angle data and the tilt angle acceleration of the component;

[0040] A third acquisition module is configured to determine a coordination coefficient of the components according to the actual operating condition type, where the coordination coefficient is a weight coefficient of the components during coordinated control;

[0041] The coordinated control module is used to coordinately control corresponding components in the floating wind turbine according to the coordinated coefficient and the coordinated control parameter.

[0042] Optionally, the third acquisition module is further configured to:

[0043] Constructing a first mapping relationship between multiple operating condition types and synergy coefficients of components of the floating wind turbine;

[0044] Determining the coordination coefficient of the components according to the actual working condition type specifically includes:

[0045] Based on the first mapping relationship, a coordination coefficient of the component corresponding to the actual operating condition type is determined.

[0046] Optionally, the third acquisition module is specifically configured to:

[0047] For a target operating condition type among the multiple operating condition types, constructing multiple sets of synergy coefficient groups, each of which includes synergy coefficients of the multiple components; the target operating condition type is one of the multiple operating condition types;

[0048] Using each group of the synergy coefficients to perform synergistic control on the floating wind turbines under the target operating condition type;

[0049] Determining a target coordination coefficient group from the plurality of coordination coefficient groups according to a time required for the equilibrium state of the floating wind turbine to return to a preset equilibrium stability value, and the tilt angle data and tilt angle acceleration of each of the coordinatedly controlled components;

[0050] A first mapping relationship between the target operating condition type and the coordination coefficient of each component in the target coordination coefficient group is constructed.

[0051] Optionally, the third acquisition module is specifically configured to:

[0052] For a target component among the plurality of components, respectively using a plurality of sets of the coordination coefficient groups and the coordination control parameters under the target operating condition type to coordinately control the target component;

[0053] The synergy coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value and minimizes the inclination angle data and inclination angle acceleration of the target component after synergistic control is selected as the target synergy coefficient group.

[0054] Optionally, the third acquisition module is specifically configured to:

[0055] The coordination coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value, minimizes the roll angle data of the target component after coordinated control, minimizes the pitch angle data of the target component after coordinated control, minimizes the roll acceleration of the target component after coordinated control, and minimizes the pitch acceleration of the target component after coordinated control is selected as the target coordination coefficient group.

[0056] Optionally, the third acquisition module is specifically configured to:

[0057] The coordination coefficient and the coordinated control parameter are input into the objective function, and the error value of the tilt of the target component can be calculated according to the following formula. The error value is proportional to the time it takes for the balance of the target component to return to stability after coordinated control, the roll angle, the pitch angle, the roll acceleration, and the pitch acceleration:

[0058] f=p1Δt+p2Δθ 横摇 +p3Δθ 纵摇 +p4Δa 横摇 +p5Δa 纵摇

[0059] Wherein, f is the error value of the target component after coordinated control under the target operating condition type, p1 is the weight coefficient of the time for the balance of the floating wind turbine to return to stability after coordinated control, p2 is the weight coefficient of the roll angle of the floating wind turbine after coordinated control, p3 is the weight coefficient of the pitch angle of the floating wind turbine after coordinated control, p4 is the weight coefficient of the roll acceleration of the floating wind turbine after coordinated control, p5 is the weight coefficient of the pitch acceleration of the floating wind turbine after coordinated control, Δt is the time for the balance of the floating wind turbine to return to a preset stable value after coordinated control, Δθ 横摇 is the roll angle data of the floating wind turbine after coordinated control, Δθ 纵摇 is the pitch angle data of the floating wind turbine after coordinated control, Δa 横摇 is the roll acceleration of the floating wind turbine after coordinated control, Δa 纵摇 is the pitch acceleration of the floating wind turbine after coordinated control.

[0060] Optionally, the first acquisition module is further configured to:

[0061] determining overall tilt angle data of the floating wind turbine according to the operating condition data of the floating wind turbine;

[0062] The synergy coefficient of the components and the corresponding tilt angle data meet the following preset constraints:

[0063] The sum of the products of the synergy coefficients of the components and the corresponding tilt angle data is equal to the overall tilt angle data of the floating wind turbine; and the sum of the synergy coefficients of all the components is equal to 1.

[0064] Optionally, the third acquisition module is further configured to:

[0065] Constructing multiple sets of operating condition data of the floating wind turbine;

[0066] Calculating, based on the operating condition data, the overall tilt angle data of the floating wind turbine, the tilt angle data of the components, and the tilt angle acceleration;

[0067] The overall tilt angle data of the floating wind turbine and the tilt angle data and tilt angle acceleration of the components corresponding to the different operating condition data are saved.

[0068] Compared with the existing technology, this application has the following beneficial effects:

[0069] In the present application, the actual working condition type of the working condition and the tilt angle data and tilt angle acceleration of each component therein are determined based on the real-time working condition data of the floating wind turbine obtained. Each floating wind turbine includes multiple components. Based on the determined tilt angle data and tilt angle acceleration of each component, the collaborative control parameters of each component can be determined. And based on the actual working condition type of the working condition, the collaborative coefficient of each component under the working condition can be determined, and the floating wind turbine can be collaboratively controlled through the collaborative coefficient and collaborative control parameters. Even in the face of complex conditions and different working condition types, the proportion of different components in the collaborative control operation can be changed according to the collaborative coefficient, so that the balance of the floating wind turbine can be collaboratively controlled. Therefore, the balance stability of the floating wind turbine can be accurately controlled. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0071] Figure 1 A flow chart of a method for controlling a floating wind turbine provided in an embodiment of the present application;

[0072] Figure 2Another flow chart of a method for controlling a floating wind turbine provided in an embodiment of the present application;

[0073] Figure 3 A schematic diagram of the structure of components for cooperative control of a floating wind turbine provided in an embodiment of the present application;

[0074] Figure 4 A comparison chart of collaborative control and non-collaborative control provided in an embodiment of the present application;

[0075] Figure 5 Another flow chart of a method for controlling a floating wind turbine provided in an embodiment of the present application;

[0076] Figure 6 A schematic structural diagram of a device for controlling a floating wind turbine provided in an embodiment of the present application. DETAILED DESCRIPTION

[0077] In order to enable those skilled in the art to more clearly understand the technical solution of the present application, the application scenario of the solution of the present application is first described below.

[0078] Floating wind power is an important way to develop deep-sea wind energy resources and achieve the dual carbon goals. A floating wind power system consists of two parts: a wind turbine and a floating system. The floating system includes a foundation, mooring anchor, anchor foundation, and dynamic submarine cables. Compared with fixed offshore wind power, floating wind turbines are suitable for areas with deep waters and high wind energy utilization, but they are difficult to design, expensive to build, and lack operation and maintenance equipment. The overseas floating offshore wind power market has experienced a transition from small-scale single-unit prototype demonstrations (2009-2015) to small-scale commercial development (2016-2022), and is currently accelerating towards large-scale commercial development.

[0079] 10MW-class floating wind turbines are large, highly integrated systems designed to capture deep-sea wind energy. These large floating wind turbines are characterized by their bulk, the distinct flexibility of their extremely long blades and towering towers, the significant swaying of the floating wind system foundation, the high degree of nonlinear random spatiotemporal constraints of the delicate anchor chains, the difficulty of analyzing rigid-flexible-fluid-structure coupling, the complexity of system coordinated control technology, and the difficulty of model testing and verification. These factors contribute to the high design margin, weight, and cost of the floating foundation, which has become a serious technical bottleneck restricting the development of deep-sea floating wind turbines in my country.

[0080] According to statistics, in existing floating offshore wind power projects in China, wind turbines only account for 11%-13% of the total cost, while the floating system accounts for 63%-67%, and construction and installation costs account for 21%-26%. Reducing the cost of floating wind turbines requires a comprehensive system approach. Technological breakthroughs should be made in the rigid-flexible-fluid-structure coupling mechanism, multi-degree-of-freedom dynamic stability mechanisms, and global stability control under motion and load constraints. This will reveal the stability mechanisms of floating wind turbines and research active and passive sway suppression and coordinated control methods based on a system that includes wind turbine controllers, tower dampers, foundation dynamic ballast, and mooring tension adjustment. The goal is to meet the Ministry of Science and Technology's requirements: "Under power generation conditions, the maximum tilt angle of the floating foundation should not exceed 5 degrees, the maximum acceleration should not exceed 0.3 times the acceleration of gravity, and under extreme conditions, the maximum tilt angle should not exceed 10 degrees." Ultimately, this will reduce the cost of floating wind power in my country, improve the economic viability of deep-sea wind power project development, and promote the rapid development of my country's large-scale deep-sea wind power industry.

[0081] Currently, single equipment and technology are typically used to control the stability of floating wind turbines. However, under the complex load conditions that floating wind turbines endure over long periods of time, single equipment and technology are difficult to achieve stability control for large-capacity floating wind power systems. This results in an inability to accurately control the balance of floating wind turbines.

[0082] In order to solve the above technical problems, the present application provides a method and device for controlling a floating wind turbine. The present application studies the mathematical modeling and stability mechanism of the dynamic load of a floating wind turbine, develops a monitoring method for the motion state of a floating wind turbine under multi-source excitation, proposes a swing suppression control method based on multiple tuned mass dampers, foundation dynamic ballast, and mooring anchor tension adjustment, and studies the global stability collaborative control strategy under the motion and load constraints of a floating wind turbine. In the present application, based on the real-time operating data of the floating wind turbine obtained, the actual operating condition type of the operating condition and the inclination angle data and inclination angle acceleration of each component therein are determined. Each floating wind turbine includes multiple components. Based on the determined inclination angle data and inclination angle acceleration of each component, the collaborative control parameters of each component can be determined. And based on the actual operating condition type of the operating condition, the collaborative coefficient of each component under the operating condition can be determined, and the floating wind turbine is collaboratively controlled through the collaborative coefficient and collaborative control parameters. Even in complex environments and under different operating conditions, the proportions of different components can be adjusted according to the synergy coefficient to coordinately control the balance of the floating wind turbine. Therefore, the balance stability of the floating wind turbine can be accurately controlled.

[0083] In order to help those skilled in the art better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0084] Figure 1 A flow chart of a method for controlling a floating wind turbine provided in an embodiment of the present application. Figure 1 As shown, the method includes:

[0085] S101: Determine, based on real-time operating condition data of the floating wind turbine, the actual operating condition type of the floating wind turbine and respective tilt angle data and tilt angle acceleration of a plurality of components.

[0086] In terms of stability mechanism functions, this application analyzes the dynamic load balance stability characteristics of floating wind turbines, establishes a mathematical model of system stability based on the Euler-Lagrange energy equation, and combines the matrix eigenvalue stability criterion and Lyapunov stability theory to reveal the multi-degree-of-freedom motion stability mechanism functions of floating wind turbines.

[0087] During the experimental training and testing phase, the target operating condition data of the floating wind turbine is obtained and stored, and the tilt angle data and tilt angle acceleration of each component under this operating condition can be calculated based on the target operating condition data.

[0088] According to the pre-classified target working condition type, after obtaining the real-time working condition data, the actual working condition type of the working condition and the respective tilt angle data and tilt angle acceleration can be known.

[0089] Actual operating data is collected through high-precision environmental monitoring, multi-factor state perception, and identification using a variety of sensors, enabling multi-sensor data correction and fusion of floating wind turbine status information. This environmental monitoring also facilitates data management throughout the entire lifecycle of floating wind turbines.

[0090] S102: Determine the coordinated control parameters of the components according to the tilt angle data and the tilt angle acceleration of the components.

[0091] According to the inclination angle data and the inclination angle acceleration of the components determined in S101 , the coordinated control parameters of the components are determined.

[0092] Specifically, simulation software that can simulate offshore floating wind turbines is used to calculate the tilt angle data of each component under the working condition and the coordinated control parameters of each component corresponding to the tilt angle acceleration.

[0093] By establishing the topological structure of the floating wind turbine, that is, forming a topological diagram of the components that need to be coordinated and controlled, a multi-input and multi-output high-order closed-loop control method is realized.

[0094] S103: Determine the coordination coefficient of the components according to the actual working condition type.

[0095] According to the actual working condition type determined in S101, the coordination coefficient of each component can be obtained. The coordination coefficient of each component is determined during the experimental training test.

[0096] S104: performing coordinated control on corresponding components in the floating wind turbine according to the coordinated coefficient and the coordinated control parameters.

[0097] By establishing a multi-objective collaborative optimization model for floating wind turbines, the balance and stability problems under different actual working conditions can be solved, and a multi-objective hierarchical control system based on a multi-dimensional and high-precision model can be established.

[0098] The coordinated control parameters obtained in S102 and the coordinated coefficients obtained in S103 are input, and the control result of the floating wind turbine can be obtained by using simulation software that can simulate the offshore floating wind turbine.

[0099] Currently, it is difficult to independently control the balance and stability of large-capacity floating wind turbines using a single component. Stability control methods such as advanced filtering PID algorithms, tuned mass dampers (TMDs), dynamic ballast, mooring windlass tension control, rotating mechanical flywheel control, and yaw and pitch system control are needed. These methods should establish criteria for optimizing the coordination coefficient and coordinated control parameters. This approach can achieve multi-objective optimization control strategies, such as reducing the tilt angle of floating wind turbines under the action of multi-component balance control and shortening the time it takes for the equilibrium state to return to a preset stable value. This will address the key issue of matching the load and stability balance of large-capacity floating wind turbines.

[0100] In the present application, the actual working condition type of the working condition and the tilt angle data and tilt angle acceleration of each component therein are determined based on the real-time working condition data of the floating wind turbine obtained. Each floating wind turbine includes multiple components. Based on the determined tilt angle data and tilt angle acceleration of each component, the collaborative control parameters of each component can be determined. And based on the actual working condition type of the working condition, the collaborative coefficient of each component under the working condition can be determined, and the floating wind turbine can be collaboratively controlled through the collaborative coefficient and collaborative control parameters. Even in the face of complex conditions and different working condition types, the proportion of different components in the collaborative control operation can be changed according to the collaborative coefficient, so that the balance of the floating wind turbine can be collaboratively controlled. Therefore, the balance stability of the floating wind turbine can be accurately controlled.

[0101] Figure 2 Another flow chart of the method for controlling a floating wind turbine provided in an embodiment of the present application. Figure 2 As shown, the method includes:

[0102] S201: Simulating operating data of a floating wind turbine to determine multiple operating condition types.

[0103] Using simulation software capable of simulating an offshore floating wind turbine, all possible operating conditions encountered by the floating wind turbine are simulated. During the simulation process, multiple sets of operating condition data are generated. These data are then divided into various operating condition types, each of which is then classified into the corresponding operating condition type. These operating condition types can be categorized as normal operating conditions and extreme operating conditions. Normal operating conditions refer to conditions under which the floating wind turbine can generate electricity normally, while extreme operating conditions refer to conditions under which the floating wind turbine cannot generate electricity.

[0104] The simulated working condition data is saved, and the corresponding working condition type is saved so that in subsequent actual use, it can be directly determined which working condition it belongs to based on the monitored real-time working condition data.

[0105] Among them, the simulation software for simulating offshore floating wind turbines can be Bladed software combined with SESAM software, FAST software, HAWC2 software, etc.

[0106] S202: Obtaining tilt angle data and tilt angle acceleration of components of the floating wind turbine according to the operating condition data, and saving the tilt angle data and tilt angle acceleration of the components.

[0107] Each floating wind turbine consists of multiple components. For example, the components of a floating wind turbine include a tuned mass damper, a dynamic ballast system, a mooring windlass, a rotating mechanical flywheel, a yaw system, a pitch system, etc. The structural diagram of each component is shown in the figure below. Figure 3 It is understood that the components of the floating wind turbine include but are not limited to the above-mentioned examples.

[0108] Specifically, the tuned mass damper is similar to flexible towers over 120m on land and fixed support structures on soft foundations over 20m at sea. It is used to reduce the sway amplitude of the tower top and fatigue load, so as to reduce the wall thickness and the weight of the support structure. The dynamic ballast system is a unique technology for floating wind turbines. Currently, only passive ballast is used in China. It is used to adjust the center of gravity of the floating wind power system when the wind direction changes, so as to reduce the roll and pitch angles. The mooring anchor windlass is used to adjust the length of the anchor chain according to the wind conditions and sea conditions, so as to adjust the mooring tension, change the stiffness of the floating body, and reduce the roll and pitch angles. The rotating mechanical flywheel provides restoring force based on the principle of fixed axis and can be placed inside the floating column to lower the center of gravity of the system and reduce the roll and pitch angles. The yaw and pitch system is similar to fixed wind turbines on land and at sea. It is used when the wind speed and direction change to keep the wind turbine load within the design value and maintain stable power generation.

[0109] Based on each set of operating condition data simulated in S201, the tilt angle data and tilt angle acceleration of each component of the floating wind turbine under that operating condition, as well as the overall tilt angle data of the floating wind turbine, are calculated. The tilt angle data and tilt angle acceleration of each component, as well as the overall tilt angle data of the floating wind turbine, are then saved. This allows for direct access to the tilt angle data and tilt angle acceleration of each component and the overall tilt angle data of the floating wind turbine corresponding to that set of simulated operating condition data during subsequent actual use.

[0110] Specifically, simulation software capable of simulating an offshore floating wind turbine is used to calculate the tilt angle data of each component corresponding to all simulated operating condition data, the tilt angle acceleration, and the overall tilt angle data of the floating wind turbine.

[0111] S203: Calculate the coordinated control parameters of each component based on the component's tilt angle data and tilt angle acceleration.

[0112] This embodiment uses a method for cooperatively controlling various components in a floating wind turbine to control the entire floating wind turbine and maintain a balanced and stable state.

[0113] Each component has its own parameters that need to be controlled when performing balance and stability control. These parameters need to be adjusted to the optimal state under collaborative control. Therefore, it is necessary to calculate the collaborative control parameters of each component.

[0114] Specifically, simulation software that can simulate offshore floating wind turbines is used to calculate the tilt angle data of each component under the working condition and the coordinated control parameters of each component corresponding to the tilt angle acceleration. Different control models can be used to calculate the coordinated control parameters of each component.

[0115] For example, the new high-precision PID control model can be used to calculate the collaborative control parameters of each component according to the following formula:

[0116] NFC(s)=-HPLO(s)HPPI(s) (1)

[0117] Where HPLO(s) is the transfer function of the high-performance lead observer, and HPPI(s) is the transfer function of the high-performance PI controller.

[0118] The new high-precision PID control model is an approximate sliding window filter extracted from existing engineering methods. The ASWF is used to construct a high-efficiency integrator (HEI) and a high-performance lead observer (HPLO). The high-performance PI controller HPPI constructed by HEI and HPLO are connected in series to obtain a new basic controller NFC. It significantly improves the feedback control performance, completely gets rid of the constraints of the model, has excellent robust performance, simplicity and good engineering usability, and is suitable for complex offshore floating wind turbine models.

[0119] For example, the LQR optimal control model can be used to calculate the collaborative control parameters of each component according to the following formula:

[0120]

[0121] Where x is the minimum number of variables sufficient to fully characterize the motion state of the component, A is the state matrix, B is the input matrix, u is the input quantity or active control force, X is the state vector, CX is the output vector, Q is the weight matrix of CX, and R is the weight matrix of u.

[0122] The LQR control method is mainly composed of the system equation Determine the gain matrix to obtain the control force u(t), with the goal of minimizing the cost function J. Q and R are used to balance the weights of the output vector and the input, and determine the relative importance of error and energy loss.

[0123] For example, we can use H ∞The control model calculates the collaborative control parameters of each component according to the following formula:

[0124]

[0125] Among them, w is the disturbance input, u is the control input, and z is the performance output (evaluation signal). Specifically, and is the Riccati algebraic equation.

[0126] The results of control theory show that by solving appropriate algebraic Riccati equations, the control parameters that minimize J can be obtained. However, in this design, the influence of interference is not considered. That is, the optimality of performance indicators can only be achieved when the controlled object can be completely roughly described. Due to the existence of uncertainties such as interference in actual systems, this optimal design is almost impossible to achieve. In order to overcome this, the interference term ω is introduced into the model of the connected object and the influence of interference on the system response characteristics is considered. In other words, the system design problem of stabilizing the closed-loop system while minimizing the influence of interference on the controllable output can be reduced to making the transfer function matrix G zw (s)H ∞ The norm is minimum. Formula min||G zw (jω)|| ∞ It can be regarded as a performance index of system design. The system controller designed with this index as the minimum is called H ∞ Optimal control.

[0127] Among them, the collaborative control parameters include yaw angle, yaw rate, pitch angle, pitch rate, pumping rate of the water pump, mass of the damper, speed of the rotating machinery, length of the anchor chain, etc.

[0128] S204: simulating the coordination coefficient of the floating wind turbine used for the experiment to obtain the coordination coefficient of the components that meet the preset constraint conditions.

[0129] The synergy coefficient is the weighting factor for components in collaborative control. Experimental design methods are used to simulate and permutate various synergy coefficients, from which samples are drawn. The sampled synergy coefficients are then judged to see if they meet the pre-set constraints. Only those that meet these constraints are used in the subsequent experimental design in S205.

[0130] Specifically, the synergy coefficient should meet the following preset constraints: the sum of the product of the synergy coefficient of each component and the tilt angle data of each component under this working condition is equal to the overall tilt angle data of the floating wind turbine, and the sum of the synergy coefficients of all components under this working condition is equal to 1.

[0131] In addition, the equipment performance of each component should meet the actual construction conditions, that is, this component should be a component that can actually be produced by current production technology.

[0132] Among them, the equipment performance of the components includes: the maximum volume and mass of the tuned mass damper, the maximum power and pumping volume of the water pump used in the dynamic ballast system, the volume and mass of the rotating mechanical flywheel, the volume of the mooring anchor windlass, the maximum speed of the yaw and pitch system, etc.

[0133] In addition, during actual use, if customized adjustments to the synergy coefficient are required, the adjusted synergy coefficient must also meet the preset constraints.

[0134] S205: Constructing a first mapping relationship between the coordination coefficients of components that meet preset constraints and multiple operating condition types, and determining a target coordination coefficient group.

[0135] According to the various operating condition types obtained by the simulation in S201, a first mapping relationship between the synergy coefficient and the various operating condition types is constructed, that is, each operating condition type has a mapping relationship with multiple synergy coefficients.

[0136] Specifically, for the target operating condition type among the multiple operating condition types, according to the multiple synergy coefficients obtained in S204 that meet the preset constraint conditions, the synergy coefficients are divided into synergy coefficient groups based on the entire floating wind turbine. That is, the synergy coefficients corresponding to all components in a floating wind turbine are taken as a group.

[0137] Each synergy coefficient group is used to coordinately control the floating wind turbine under the target operating condition type. From the multiple synergy coefficient groups, the synergy coefficient group that minimizes the time used for the equilibrium state of the floating wind turbine to return to the preset equilibrium stability value and minimizes the inclination angle data and inclination angle acceleration of the target component after coordinated control is selected as the target synergy coefficient group.

[0138] Specifically, the collaborative control parameters obtained in S203 and the collaborative coefficient obtained in S204 are input into the simulation software that can simulate the offshore floating wind turbine to calculate the error value of the target component tilt. Among them, the tilt angle data of a component includes roll angle data and pitch angle data, and the tilt angle acceleration includes roll angle acceleration and pitch angle acceleration. For the target component, the factors that affect the error in the balance of the target component include: the time used to restore the equilibrium state to the preset equilibrium stability value, roll angle data, pitch angle data, roll angle acceleration and pitch angle acceleration. Among them, when calculating the error value, the weight coefficients of these five factors can be modified according to the user's needs and wishes to adjust the error value result. Comprehensively considering the error value results of all target components, when the overall error value is smaller, it means that the collaborative coefficient group selected at this time is optimal for the target component under the target working condition type, and this collaborative coefficient group is used as the target collaborative coefficient group.

[0139] The error value of the target component tilt can be calculated according to the following formula:

[0140] f=p1Δt+p2Δθ 横摇 +p3Δθ 纵摇 +p4Δa 横摇 +p5Δa 纵摇 (4)

[0141] Wherein, f is the error value of the target component after coordinated control under the target operating condition type, p1 is the weight coefficient of the time it takes for the balance of the floating wind turbine to return to stability after coordinated control, p2 is the weight coefficient of the roll angle of the floating wind turbine after coordinated control, p3 is the weight coefficient of the pitch angle of the floating wind turbine after coordinated control, p4 is the weight coefficient of the roll acceleration of the floating wind turbine after coordinated control, p5 is the weight coefficient of the pitch acceleration of the floating wind turbine after coordinated control, Δt is the time it takes for the balance of the floating wind turbine to return to the preset stable value after coordinated control, and Δθ 横摇 is the roll angle data of the floating wind turbine after coordinated control, Δθ 纵摇 is the pitch angle data of the floating wind turbine after coordinated control, Δa 横摇 The rolling acceleration of the floating wind turbine after coordinated control, Δa 纵摇 It is the pitch acceleration of the floating wind turbine after coordinated control.

[0142] S206: Constructing a first mapping relationship between the coordination coefficient of each component in the target coordination coefficient group and the target operating condition type.

[0143] A first mapping relationship is established between the synergy coefficient of each component in the target synergy coefficient group obtained in step S205 and the target operating condition type. In other words, a mapping relationship exists between the target operating condition type and the synergy coefficient of each component. In subsequent actual use, the synergy coefficient corresponding to each component can be obtained by obtaining the actual operating condition type.

[0144] S207: Acquire real-time operating condition data of the floating wind turbine generator, and determine the actual operating condition type of the operating condition and the tilt angle data and tilt angle acceleration of each component.

[0145] The operating condition data of the floating wind turbine is detected in real time by a variety of sensors. As can be seen from S201, the real-time operating condition data can be used to determine the actual operating condition type of the operating condition and the tilt angle data and tilt angle acceleration of each component.

[0146] Operating condition data includes environmental data such as wind, waves, currents, and soil conditions, as well as the status and operating conditions of the floating wind turbine. Furthermore, real-time operating condition data acquired by various sensors can be used to estimate the operating conditions of the floating wind turbine for a certain period of time in the future, allowing the floating wind turbine to prepare for the actual operating conditions in advance.

[0147] S208: Determine the coordinated control parameters of the components according to the tilt angle data and the tilt angle acceleration of the components.

[0148] In combination with the method mentioned in S203 above, it can be seen that the coordinated control parameters corresponding to the components can be determined according to the inclination angle data and the inclination angle acceleration of the components determined in S207.

[0149] S209: Determine the coordination coefficient of each component under the actual working condition type.

[0150] In combination with the method of S205 , it can be seen that the coordination coefficient of each component under the actual working condition type obtained in S207 can be found accordingly.

[0151] When the actual working condition type is one of the target working condition types among the multiple working condition types during the experiment, the target coordination coefficient group corresponding to the first mapping relationship of the actual working condition type can be retrieved, thereby obtaining the coordination coefficients of each component corresponding to the first mapping relationship of the actual working condition type.

[0152] For example, as shown in Table 1, under normal operating conditions, the coordination coefficients of the various components are as follows: 0.2 for the tuned mass damper, 0.3 for the dynamic ballast system, 0.1 for the mooring windlass, 0 for the rotating machinery flywheel, and 0.4 for the yaw and pitch system. Under extreme operating conditions, the coordination coefficients of the various components are as follows: 0.1 for the tuned mass damper, 0.1 for the dynamic ballast system, 0.1 for the mooring windlass, 0.1 for the rotating machinery flywheel, and 0.5 for the yaw and pitch system. Furthermore, users can modify the coordination coefficients of various components according to their needs.

[0153] Table 1 Synergy coefficients of cooperatively controlled components under different working conditions

[0154]

[0155] S210: Performing coordinated control on corresponding components in the floating wind turbine according to the coordinated coefficient and the coordinated control parameter.

[0156] The coordination coefficient obtained in S209 and the coordination control parameters obtained in S208 are input into simulation software that can simulate an offshore floating wind turbine, so that corresponding components in the floating wind turbine can be coordinated and controlled.

[0157] For example, when the tuned mass damper only controls the balance stability of its own components, it can reduce the tilt angle of the entire floating wind turbine and shorten the time it takes for the balance state to return to the preset stable value. However, the floating wind turbine also includes components such as the dynamic ballast system, mooring windlass, rotating mechanical flywheel, yaw and pitch control system, etc. In this case, a solution for coordinated optimization of the components can better adjust the balance stability of the floating wind turbine. Figure 4 As shown, Figure 4 This chart compares the balance stability of a floating wind turbine without balance stability control, with a tuned mass damper controlling the balance stability of its own components, and with coordinated control of all components. As can be seen, the overall tilt angle of the floating wind turbine is significantly reduced, and the time it takes to return to the preset equilibrium state is significantly shortened. As shown in Table 2, tuned mass dampers can be used in floating wind turbines with tower heights greater than 100 meters. After coordinated control, they can reduce the tower top sway amplitude by more than 15%, reduce the fatigue load at the tower base by 20%, and reduce the weight of the floating wind turbine by more than 5%.

[0158] Specifically, the yaw and pitch system can be used in all active yaw and pitch wind turbines. After coordinated control, it can reduce the ultimate loads on the blade root and tower bottom by 10%-30%, and reduce the roll or pitch angle of the floating wind turbine by more than 2°; the dynamic ballast system can be activated when the wind direction changes by more than 30°, and after coordinated control, it can reduce the roll or pitch angle of the floating wind turbine by more than 1°; the rotating mechanical flywheel can be activated when encountering extreme working conditions, and after coordinated control, it can reduce the roll or pitch angle of the floating wind turbine by more than 0.2°, but due to the limitations of the structural form and the size of the flywheel, it is generally recommended to use it in a vertical column floating foundation; the mooring anchor windlass can be activated when encountering extreme working conditions such as typhoons and power outages, and after coordinated control, it can reduce the roll or pitch angle of the floating wind turbine by more than 0.2°, but the reliability of the anchor windlass needs to be verified.

[0159] Table 2 Application scenarios and functions of components and the effects after coordinated control

[0160]

[0161] Table 2 Application scenarios and functions of components and the effects of coordinated control

[0162]

[0163] Table 2 Application scenarios and functions of components and the effects of coordinated control

[0164]

[0165] Among them, when the working conditions affected by the typhoon are extreme, the yaw and pitch system, dynamic ballast system, rotating mechanical flywheel and mooring anchor windlass need to make attitude adjustments in advance in conjunction with the meteorological forecast system; if in the sea area not affected by the typhoon, the coordination coefficient of the mooring anchor windlass and dynamic ballast system can be further reduced, as shown in the example of S209; the rotating mechanical flywheel can decide whether to configure the coordination coefficient based on the effect it can achieve under constraints such as reliability, volume, and mass.

[0166] like Figure 5 As shown, Figure 5 The implementation process of this embodiment can be summarized as follows: after the sensor detects relevant information of the floating wind turbine, the tilt angle of the floating wind turbine can be obtained, and the various components are coordinated and controlled through coordinated control optimization based on the tilt angle and the pre-acquired coordination coefficient.

[0167] Figure 6 This is a schematic diagram of the structure of the device for controlling a floating wind turbine provided in an embodiment of the present application. Figure 6 As shown, the device includes:

[0168] The first acquisition module 610 is configured to determine the actual operating condition type of the floating wind turbine and the tilt angle data and tilt angle acceleration of each of the plurality of components according to the real-time operating condition data of the floating wind turbine.

[0169] During the experimental training and testing phase, the target operating condition data of the floating wind turbine is obtained and stored, and the tilt angle data and tilt angle acceleration of each component under this operating condition can be calculated based on the target operating condition data.

[0170] According to the pre-classified target working condition type, after obtaining the real-time working condition data, the actual working condition type of the working condition and the respective tilt angle data and tilt angle acceleration can be known.

[0171] The second acquisition module 620 is configured to determine the coordinated control parameters of the components according to the tilt angle data and the tilt angle acceleration of the components.

[0172] The coordinated control parameters of the components are determined according to the inclination angle data and the inclination angle acceleration of the components determined by the first acquisition module 610 .

[0173] Specifically, simulation software that can simulate offshore floating wind turbines is used to calculate the tilt angle data of each component under the working condition and the coordinated control parameters of each component corresponding to the tilt angle acceleration.

[0174] The third acquisition module 630 is used to determine the coordination coefficient of the components according to the actual working condition type. The coordination coefficient is the weight coefficient of the components during coordinated control.

[0175] The coordination coefficient of each component can be obtained according to the actual working condition type determined by the first acquisition module 610. The coordination coefficient of each component is determined during the experimental training test process.

[0176] The coordinated control module 640 is used to coordinately control corresponding components in the floating wind turbine according to the coordinated coefficient and the coordinated control parameters.

[0177] By inputting the coordinated control parameters obtained by the second acquisition module 620 and the coordinated coefficient obtained by the third acquisition module 630, a control result of the floating wind turbine can be obtained by using simulation software that can simulate the offshore floating wind turbine.

[0178] In the present application, the first acquisition module 610 can be used to determine the actual operating condition type of the operating condition and the tilt angle data and tilt angle acceleration of each component therein based on the real-time operating condition data of the floating wind turbine obtained. Each floating wind turbine includes multiple components. The second acquisition module 620 can be used to determine the collaborative control parameters of each component based on the determined tilt angle data and tilt angle acceleration of each component. The third acquisition module 630 can be used to determine the collaborative coefficient of each component under the operating condition based on the actual operating condition type of the operating condition. In the collaborative control module 640, the floating wind turbine is collaboratively controlled using the collaborative coefficient and the collaborative control parameters. Even in the face of complex conditions and different operating conditions, the proportions of different components can be changed according to the collaborative coefficient to collaboratively control the balance of the floating wind turbine. Therefore, the balance stability of the floating wind turbine can be accurately controlled.

[0179] It should be noted that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. The device embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components indicated as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without expending creative work.

[0180] The above is merely one specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for controlling a floating wind turbine, characterized in that: The floating wind turbine includes a plurality of components, and the method includes: Determining, based on the real-time operating condition data of the floating wind turbine, the actual operating condition type of the floating wind turbine and the respective tilt angle data and tilt angle acceleration of the plurality of components; determining a coordinated control parameter of the component according to the tilt angle data and the tilt angle acceleration of the component; Determining a coordination coefficient of the components according to the actual operating condition type, wherein the coordination coefficient is a weight coefficient of the components during coordinated control; performing coordinated control on corresponding components of the floating wind turbine according to the coordinated coefficient and the coordinated control parameter; Before determining the synergy coefficient of the components according to the actual operating condition type, the method further includes: Constructing a first mapping relationship between multiple operating condition types and synergy coefficients of components of the floating wind turbine; Determining the coordination coefficient of the components according to the actual working condition type specifically includes: Determining, based on the first mapping relationship, a coordination coefficient of a component corresponding to the actual operating condition type; The constructing of the first mapping relationship between the various operating conditions of the floating wind turbine and the coordination coefficients of the components specifically includes: For a target operating condition type among the multiple operating condition types, constructing multiple sets of synergy coefficient groups, each of which includes synergy coefficients of the multiple components; the target operating condition type is one of the multiple operating condition types; Using each group of the synergy coefficients to perform synergistic control on the floating wind turbines under the target operating condition type; Determining a target coordination coefficient group from the plurality of coordination coefficient groups according to a time required for the equilibrium state of the floating wind turbine to return to a preset equilibrium stability value, and the tilt angle data and tilt angle acceleration of each of the coordinatedly controlled components; Constructing a first mapping relationship between the target operating condition type and the coordination coefficient of each component in the target coordination coefficient group; Determining a target synergy coefficient group from the plurality of synergy coefficient groups based on a time required for the equilibrium state of the floating wind turbine to return to a preset equilibrium stability value, and tilt angle data and tilt angle acceleration of each of the synergistically controlled components, specifically includes: For a target component among the plurality of components, respectively using a plurality of sets of the coordination coefficient groups and the coordination control parameters under the target operating condition type to coordinately control the target component; The synergy coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value and minimizes the inclination angle data and inclination angle acceleration of the target component after synergistic control is selected as the target synergy coefficient group.

2. The method according to claim 1, characterized in that The tilt angle data includes roll angle data and pitch angle data of the component, and the tilt angle acceleration includes roll acceleration and pitch acceleration. The selection of the coordination coefficient group that minimizes the time used to restore the equilibrium state of the floating wind turbine to the preset equilibrium stability value and minimizes the tilt angle data and tilt angle acceleration of the target component after coordinated control, as the target coordination coefficient group, specifically includes: The coordination coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value, minimizes the roll angle data of the target component after coordinated control, minimizes the pitch angle data of the target component after coordinated control, minimizes the roll acceleration of the target component after coordinated control, and minimizes the pitch acceleration of the target component after coordinated control is selected as the target coordination coefficient group.

3. The method according to claim 2, characterized in that The collaborative control of corresponding components in the floating wind turbine according to the collaborative coefficient and the collaborative control parameter specifically includes: The coordination coefficient and the coordinated control parameter are input into the objective function, and the error value of the tilt of the target component can be calculated according to the following formula. The error value is proportional to the time it takes for the balance of the target component to return to stability after coordinated control, the roll angle, the pitch angle, the roll acceleration, and the pitch acceleration: f=p1Δt+p2Δθ 横摇 +p3Δθ 纵摇 +p4Δa 横摇 +p5Δa 纵摇 Wherein, f is the error value of the target component after coordinated control under the target operating condition type, p1 is the weight coefficient of the time for the balance of the floating wind turbine to return to stability after coordinated control, p2 is the weight coefficient of the roll angle of the floating wind turbine after coordinated control, p3 is the weight coefficient of the pitch angle of the floating wind turbine after coordinated control, p4 is the weight coefficient of the roll acceleration of the floating wind turbine after coordinated control, p5 is the weight coefficient of the pitch acceleration of the floating wind turbine after coordinated control, Δt is the time for the balance of the floating wind turbine to return to a preset stable value after coordinated control, Δθ 横摇 is the roll angle data of the floating wind turbine after coordinated control, Δθ 纵摇 is the pitch angle data of the floating wind turbine after coordinated control, Δa 横摇 is the roll acceleration of the floating wind turbine after coordinated control, Δa 纵摇 is the pitch acceleration of the floating wind turbine after coordinated control.

4. The method according to claim 1, characterized in that Before constructing the first mapping relationship between the various operating condition types and the synergy coefficients of the components of the floating wind turbine, the method further includes: determining overall tilt angle data of the floating wind turbine according to the operating condition data of the floating wind turbine; The synergy coefficient of the components and the corresponding tilt angle data meet the following preset constraints: The sum of the products of the synergy coefficients of the components and the corresponding tilt angle data is equal to the overall tilt angle data of the floating wind turbine; and the sum of the synergy coefficients of all the components is equal to 1.

5. The method according to claim 4, characterized in that: Before determining the actual operating condition type of the floating wind turbine and the respective tilt angle data and tilt angle acceleration of the plurality of components based on the real-time operating condition data of the floating wind turbine, the method further comprises: Constructing multiple sets of operating condition data of the floating wind turbine; Calculating, based on the operating condition data, the overall tilt angle data of the floating wind turbine, the tilt angle data of the components, and the tilt angle acceleration; The overall tilt angle data of the floating wind turbine and the tilt angle data and tilt angle acceleration of the components corresponding to the different operating condition data are saved.

6. A device for controlling a floating wind turbine, characterized in that: The device for controlling a floating wind turbine is used to implement any one of claims 1 to 5, comprising: a first acquisition module, configured to determine, based on real-time operating condition data of the floating wind turbine, an actual operating condition type of the floating wind turbine and respective tilt angle data and tilt angle acceleration of the plurality of components; a second acquisition module, configured to determine a coordinated control parameter of the component according to the tilt angle data and the tilt angle acceleration of the component; A third acquisition module is configured to determine a coordination coefficient of the components according to the actual operating condition type, where the coordination coefficient is a weight coefficient of the components during coordinated control; a coordinated control module, configured to perform coordinated control on corresponding components of the floating wind turbine according to the coordinated coefficient and the coordinated control parameter; The third acquisition module is further configured to: Constructing a first mapping relationship between multiple operating condition types and synergy coefficients of components of the floating wind turbine; Determining the coordination coefficient of the components according to the actual working condition type specifically includes: Determining, based on the first mapping relationship, a coordination coefficient of a component corresponding to the actual operating condition type; The third acquisition module is specifically configured to: For a target operating condition type among the multiple operating condition types, constructing multiple sets of synergy coefficient groups, each of which includes synergy coefficients of the multiple components; the target operating condition type is one of the multiple operating condition types; Using each group of the synergy coefficients to perform synergistic control on the floating wind turbines under the target operating condition type; Determining a target coordination coefficient group from the plurality of coordination coefficient groups according to a time required for the equilibrium state of the floating wind turbine to return to a preset equilibrium stability value, and the tilt angle data and tilt angle acceleration of each of the coordinatedly controlled components; Constructing a first mapping relationship between the target operating condition type and the coordination coefficient of each component in the target coordination coefficient group; The third acquisition module is specifically configured to: For a target component among the plurality of components, respectively using a plurality of sets of the coordination coefficient groups and the coordination control parameters under the target operating condition type to coordinately control the target component; The synergy coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value and minimizes the inclination angle data and inclination angle acceleration of the target component after synergistic control is selected as the target synergy coefficient group.

7. The device according to claim 6, characterized in that The third acquisition module is specifically configured to: The coordination coefficient group that minimizes the time used for the floating wind turbine to restore its equilibrium state to the preset equilibrium stability value, minimizes the roll angle data of the target component after coordinated control, minimizes the pitch angle data of the target component after coordinated control, minimizes the roll acceleration of the target component after coordinated control, and minimizes the pitch acceleration of the target component after coordinated control is selected as the target coordination coefficient group.

8. The device according to claim 7, characterized in that The third acquisition module is specifically configured to: The coordination coefficient and the coordinated control parameter are input into the objective function, and the error value of the tilt of the target component can be calculated according to the following formula. The error value is proportional to the time it takes for the balance of the target component to return to stability after coordinated control, the roll angle, the pitch angle, the roll acceleration, and the pitch acceleration: f=p1Δt+p2Δθ 横摇 +p3Δθ 纵摇 +p4Δa 横摇 +p5Δa 纵摇 Wherein, f is the error value of the target component after coordinated control under the target operating condition type, p1 is the weight coefficient of the time for the balance of the floating wind turbine to return to stability after coordinated control, p2 is the weight coefficient of the roll angle of the floating wind turbine after coordinated control, p3 is the weight coefficient of the pitch angle of the floating wind turbine after coordinated control, p4 is the weight coefficient of the roll acceleration of the floating wind turbine after coordinated control, p5 is the weight coefficient of the pitch acceleration of the floating wind turbine after coordinated control, Δt is the time for the balance of the floating wind turbine to return to a preset stable value after coordinated control, Δθ 横摇 is the roll angle data of the floating wind turbine after coordinated control, Δθ 纵摇 is the pitch angle data of the floating wind turbine after coordinated control, Δa 横摇 is the roll acceleration of the floating wind turbine after coordinated control, Δa 纵摇 is the pitch acceleration of the floating wind turbine after coordinated control.

9. The device according to claim 6, characterized in that The first acquisition module is further configured to: determining overall tilt angle data of the floating wind turbine according to the operating condition data of the floating wind turbine; The synergy coefficient of the components and the corresponding tilt angle data meet the following preset constraints: The sum of the products of the synergy coefficients of the components and the corresponding tilt angle data is equal to the overall tilt angle data of the floating wind turbine; and the sum of the synergy coefficients of all the components is equal to 1.

10. The device according to claim 6, characterized in that: The third acquisition module is further configured to: Constructing multiple sets of operating condition data of the floating wind turbine; Calculating, based on the operating condition data, the overall tilt angle data of the floating wind turbine, the tilt angle data of the components, and the tilt angle acceleration; The overall tilt angle data of the floating wind turbine and the tilt angle data and tilt angle acceleration of the components corresponding to the different operating condition data are saved.

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