Floating fan power control method and device based on wave interval estimation and medium

Abstract

The invention discloses a floating type draught fan power control method and device based on wave interval estimation and a medium, and relates to the technical field of draught fan control. The method comprises the steps that an observed value of a state variable at the current moment and a predicted value of a control input quantity at the previous moment are obtained; determining an estimated value of wave interference at the current moment; determining a predicted value of the wave interference at the next moment based on the estimated values of the wave interference at the current moment and the previous moment by using a wave interference predictor; using a state predictor to determine a predicted value of a state variable at the next moment based on the observed value of the state variable at the current moment and a predicted value of wave interference at the next moment, and using a time delay controller to determine a predicted value of a control input quantity at the current moment; and controlling the floating fan at the current moment by using the predicted value of the control input quantity at the current moment. According to the invention, accurate compensation and control of wave interference are realized.

Description

Technical Field

[0001] The present application relates to the technical field of wind turbine control, and in particular to a floating wind turbine power control method, device and medium based on wave interval estimation. Background Art

[0002] In line with the trend of global energy transformation, China's offshore wind power generation is in a rapid development stage. Floating Offshore Wind Turbine (FOWT) has become a necessary means to develop deep-sea wind power. Unlike onshore wind turbines, the structural freedom of FOWT is more significantly affected by waves. The relatively slow hydrodynamics in the deep sea has a greater impact on the power response of FOWT. In addition to the interaction between waves and platforms, waves in certain sea areas may also cause additional vortex-induced vibrations on the platform, resulting in an increase in the amplitude of FOWT power response and affecting the stability of FOWT power generation. Therefore, it is very necessary to regulate waves as external interference to the FOWT system.

[0003] In order to overcome the impact of wave disturbances on FOWT power fluctuations, the following methods have been proposed: (1) Applying the traditional onshore wind turbine control strategy to FOWT. The control results of this method show that when the traditional onshore wind turbine control method is used without considering the offshore wind and wave conditions, the forward and backward rotation of the FOWT will impose negative damping oscillations to excite the tower oscillations, and cannot effectively suppress the impact of waves on the stability of the FOWT. (2) Design a model-based linear quadratic regulator (LQR) controller. LQR has been proven to be an effective method to resist wind disturbances. However, a single LQR controller does not have a good effect in suppressing wave disturbances. (3) Combine the traditional wind turbine controller with a new linear feedforward controller based on wave measurement. The purpose of the feedforward controller is to attenuate the rotor speed changes caused by fluctuations. Due to the randomness of wave frequency, the linear feedforward controller cannot accurately compensate for wave disturbances.

[0004] In summary, the above methods are unable to achieve accurate compensation and control of wave disturbance. Summary of the invention

[0005] The purpose of the present application is to provide a floating wind turbine power control method, device and medium based on wave interval estimation to solve the problem of being unable to accurately compensate and control wave interference.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a floating wind turbine power control method based on wave interval estimation, comprising:

[0008] Obtaining the observed value of the state variable of the floating wind turbine at the current moment and the predicted value of the control input at the previous moment; the state variables include: the rotation speed of the wind turbine blades and the front-back displacement of the tower top; when the current moment is the initial moment, the predicted value of the control input at the previous moment is the initialized control input;

[0009] Using the disturbance interval observer, based on the observed value of the state variable at the current moment and the predicted value of the control input at the previous moment, the estimated value of the wave disturbance at the current moment is determined;

[0010] Determine the predicted value of the wave disturbance at the next moment based on the estimated value of the wave disturbance at the current moment and the estimated value of the wave disturbance at the previous moment by using the wave disturbance predictor; when the current moment is the initial moment, the estimated value of the wave disturbance at the previous moment is the same as the estimated value of the wave disturbance at the current moment;

[0011] Using the state predictor, based on the observed value of the state variable at the current moment and the predicted value of the wave disturbance at the next moment, the predicted value of the state variable at the next moment is determined;

[0012] Using a time-delay controller, based on the predicted value of the wave disturbance at the next moment and the predicted value of the state variable at the next moment, the predicted value of the control input at the current moment is determined;

[0013] The floating wind turbine is controlled at the current moment using the predicted value of the control input quantity at the current moment.

[0014] Optionally, the construction of the interference interval observer includes:

[0015] Based on linear wave theory and wave frequency uncertainty, waves are modeled to obtain a linear wave model;

[0016] Based on the incremental relationship between wind turbine blade speed, tower top front and rear displacement and power generation, a floating wind turbine linear model is constructed.

[0017] By utilizing the uncertainty boundary of the wave model, the positive system theory and the interval observation technology, a disturbance interval observer is constructed based on the linear wave model and the floating wind turbine linear model.

[0018] Optionally, the linear wave model comprises:

[0019]

[0020] in, is the derivative of χ(t); χ(t) is the state quantity of the wave disturbance system at the tth moment; ω is the wave frequency; N = [1 -1] T; T is the transpose; θ(t) is the input of the wave disturbance system at the tth moment, and satisfies θ is the upper bound of the wave frequency uncertainty; is the lower bound of the wave frequency uncertainty; T = [a 0].

[0021] Optionally, the floating wind turbine linear model includes:

[0022]

[0023]

[0024] in, is the derivative of x(t); x(t) is the observed value of the state variable of the floating wind turbine at the tth moment, x(t) = [δω r (t),δξ t (t)] T ,δ is the increment,ω r (t) is the observed value of the fan blade speed at the tth moment, ξ t (t) is the observed value of the front-rear displacement of the tower top at the tth moment; u(t-τ) is the predicted value of the control input of the floating wind turbine at the t-τth moment, u(t-τ) = [δβ ref (t-τ),δT g,ref (t-τ)] T ; d(t) is the wave disturbance at the tth moment, d(t) = δH(t), H(t) is the wave height at the tth moment; y(t) is the output of the wind turbine at the tth moment, y(t) = δP g (t), P g (t) is the wind turbine power generation at the tth moment; A, B c , B d , C and D are coefficient matrices; K Tω , K Tβ With K Mβ These are the dynamic parameters of the fan control model. T r is the aerodynamic torque, ω r is the wind turbine blade speed, β is the wind turbine pitch angle command, M r is the tower bending moment; J r is the moment of inertia of the fan blade; N g J is the speed ratio of the gearbox; g is the generator moment of inertia; K T , K M , K B and ε t are all identification parameters; η is the generator efficiency; ω refis the rated blade speed; T ref is the rated electromagnetic torque; T is the transpose.

[0025] Optionally, the interference interval observer includes:

[0026]

[0027] α(t)=Q[(M-LB d T)L-LA]x(t)-QLB c u(t-τ);

[0028]

[0029] Among them, P and Q are the reversible matrices to be designed, P = Q -1 ; ξ(t) is the auxiliary variable at the tth moment; L is the gain matrix of the interference interval observer to be solved; is the derivative of ξ(t); α(t) is the lumped variable at the tth moment; for The derivative of is the upper bound estimate of ξ(t); O is a zero matrix, for (QN) + The element in the i-th row and j-th column of the matrix, (QN) ij is the element in the i-th row and j-th column of the (QN) matrix; for The derivative of is the lower bound estimate of ξ(t); for (QN) - The element in the i-th row and j-th column of the matrix; S u , Z u , S l and Z l They are all auxiliary matrices; is the upper bound estimate of d(t); P + The element in the i-th row and j-th column of the matrix, P ij is the element in the i-th row and j-th column of the P matrix; is the lower bound estimate of d(t); P - The element in the i-th row and j-th column of the matrix; is the estimated value of the wave disturbance at time t.

[0030] Optionally, the wave disturbance predictor comprises:

[0031]

[0032] in, is the predicted value of the wave disturbance at time t+τ; is the estimated value of the wave disturbance at the t-τth moment; x(t-τ) is the observed value of the state variable of the floating wind turbine at the t-τth moment, when the tth moment is the initial moment, x(t-τ)=x(t); is the upper boundary estimate of the auxiliary variable at the t-τth moment, when the tth moment is the initial moment, is the lower bound estimate of the auxiliary variable at the t-τth moment. When the tth moment is the initial moment,

[0033] Optionally, the state predictor comprises:

[0034]

[0035] in, is the predicted value of the state variable of the floating wind turbine at the t+τth moment; e is a natural constant; A(ts) is the A matrix at the tsth moment; u(s) is the predicted value of the control input quantity of the floating wind turbine at the sth moment; is the predicted value of the wave disturbance at the time s+τ.

[0036] Optionally, the time-delay controller comprises:

[0037]

[0038] Among them, σ(t+τ) is the sliding surface at the t+τth moment; G is the intermediate matrix, G=(B c T B c ) -1 B c T ; is the predicted value of the state variable of the floating wind turbine at the τth moment; is the predicted value of the state variable of the floating wind turbine at the s+τth moment; u0(s) is the nominal controller at the sth moment, K is the gain matrix of the time-delay controller to be solved; is the predicted value of the state variable of the floating wind turbine at the time t+τ; ||·|| is the modulus of the matrix; d w (t+τ) is the interval width at time t+τ; is the estimated value of the wave disturbance at time t+τ; is the estimated value at the time t+τ.

[0039] In a second aspect, the present application provides a computer device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the above-mentioned floating wind turbine power control methods based on wave interval estimation.

[0040] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-mentioned floating wind turbine power control methods based on wave interval estimation.

[0041] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0042] The present application discloses a floating wind turbine power control method, device and medium based on wave interval estimation. First, the observed value of the state variable of the floating wind turbine at the current moment and the predicted value of the control input at the previous moment are obtained; then, the estimated value of the wave interference at the current moment is determined by using an interference interval observer based on the observed value of the state variable at the current moment and the predicted value of the control input at the previous moment; secondly, the predicted value of the wave interference at the next moment is determined by using a wave interference predictor based on the estimated value of the wave interference at the current moment and the estimated value of the wave interference at the previous moment; subsequently, the predicted value of the state variable at the next moment is determined by using a state predictor based on the observed value of the state variable at the current moment and the predicted value of the wave interference at the next moment; thirdly, the predicted value of the control input at the current moment is determined by using a time-delay controller based on the predicted value of the wave interference at the next moment and the predicted value of the state variable at the next moment; finally, the floating wind turbine is controlled at the current moment by using the predicted value of the control input at the current moment. In order to solve the problem of wave disturbance on the power generation of floating wind turbines, this application proposes a composite control strategy DIO-DP-ISMC based on a disturbance interval observer (DIO), a wave disturbance predictor (DP) and an integral sliding mode control (ISMC), which realizes accurate compensation and control of wave disturbance. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments will be briefly introduced below. 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 creative work.

[0044] Figure 1 A schematic flow chart of a floating wind turbine power control method based on wave interval estimation provided in an embodiment of the present application;

[0045] Figure 2 It is a schematic diagram comparing the power control between PI and DIO-DP-ISMC;

[0046] Figure 3 Schematic diagram of predicted values ​​of wave disturbance;

[0047] Figure 4 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] The purpose of the present application is to provide a floating wind turbine power control method, device and medium based on wave interval estimation, aiming to achieve accurate compensation and control of wave interference.

[0050] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0051] In an exemplary embodiment, Figure 1 As shown, a floating wind turbine power control method based on wave interval estimation is provided, comprising:

[0052] Step 1: Obtain the observed values ​​of the state variables of the floating wind turbine at the current moment and the predicted values ​​of the control input at the previous moment.

[0053] Among them, the state variables include: the speed of the fan blades and the front-rear displacement of the tower top; when the current moment is the initial moment, the predicted value of the control input quantity at the previous moment is the initialized control input quantity.

[0054] Step 2: Using the disturbance interval observer, the estimated value of the wave disturbance at the current moment is determined based on the observed value of the state variable at the current moment and the predicted value of the control input at the previous moment.

[0055] As an optional implementation, the construction of the interference interval observer in step 2 includes:

[0056] Step 21: Based on linear wave theory and wave frequency uncertainty, the waves are modeled to obtain a linear wave model.

[0057] As an optional implementation, the linear wave model includes:

[0058]

[0059] in, is the derivative of χ(t); χ(t) is the state quantity of the wave disturbance system at the tth moment (the current moment); ω is the wave frequency; N = [1 -1] T ; T is the transpose; θ(t) is the input of the wave disturbance system at the tth moment, and satisfies θ is the upper bound of the wave frequency uncertainty; is the lower bound of the wave frequency uncertainty; T = [a 0].

[0060] Specifically, considering that the wave interference acting on the floating wind turbine is a linear wave, the nominal form of the linear wave is:

[0061] H(t)=acos(ωt).

[0062] Among them, H(t) is the wave height at the tth moment; a is the wave amplitude.

[0063] Considering the uncertainty of the actual wave frequency, the expression of wave interference is obtained as follows:

[0064] d(t)=acos[(ω+Δω)t].

[0065] Where d(t) is the wave disturbance at time t; Δω is the wave frequency uncertainty, and θ and is a constant.

[0066] Step 22: Based on the incremental relationship between wind turbine blade speed, tower top front and rear displacement, and power generation, a floating wind turbine linear model is constructed.

[0067] As an optional implementation, the floating wind turbine linear model includes:

[0068]

[0069]

[0070] in, is the derivative of x(t); x(t) is the observed value of the state variable of the floating wind turbine at the tth moment, x(t) = [δω r (t),δξt (t)] T ,δ is the increment,ω r (t) is the observed value of the fan blade speed at the tth moment, ξ t (t) is the observed value of the front-rear displacement of the tower top at the tth moment; u(t-τ) is the predicted value of the control input of the floating wind turbine at the t-τth moment (the previous moment), u(t-τ) = [δβ ref (t-τ),δT g,ref (t-τ)] T ; d(t) is the wave disturbance at the tth moment, d(t) = δH(t), H(t) is the wave height at the tth moment; y(t) is the output of the wind turbine at the tth moment, y(t) = δP g (t), P g (t) is the wind turbine power generation at the tth moment; A, B c , B d , C and D are coefficient matrices; K Tω , K Tβ With K Mβ These are the dynamic parameters of the fan control model. T r is the aerodynamic torque, ω r is the wind turbine blade speed, β is the wind turbine pitch angle command, M r is the tower bending moment; J r is the moment of inertia of the fan blade; N g J is the speed ratio of the gearbox; g is the generator moment of inertia; K T , K M , K B and ε t are all identification parameters; η is the generator efficiency; ω ref is the rated blade speed; T ref is the rated electromagnetic torque; T is the transpose.

[0071] Specifically, the expressions for the incremental relationship between the wind turbine blade speed, the front and rear displacement of the tower top and the power generation are:

[0072]

[0073] δP g =η(T ref δω r +ω ref δT g ).

[0074] in, ω r The derivative of s is the transmission shaft damping coefficient; Tg is the electromagnetic torque command of the fan; For t The derivative of ξ t is the front-to-back displacement of the tower top; P g The power generated by the wind turbine.

[0075] Considering the large inertia of the wind turbine, there is a time delay τ between the wind turbine pitch angle command and the wind turbine electromagnetic torque command, that is, δβ(t) = δβ ref (t-τ), δT g (t) = δT g,ref (t-τ).

[0076] Where, β(t) is the wind turbine pitch angle command at the tth moment; β ref (t-τ) is the reference value of the wind turbine pitch angle at the t-τ moment; T g (t) is the electromagnetic torque command of the fan at the tth moment; T g,ref (t-τ) is the electromagnetic torque reference value at the t-τ moment.

[0077] Step 23: Using the uncertainty boundary of the wave model, positive system theory and interval observation technology, a disturbance interval observer is constructed based on the wave model and the floating wind turbine linear model.

[0078] As an optional implementation manner, the interference interval observer includes:

[0079]

[0080] α(t)=Q[(M-LB d T)L-LA]x(t)-QLB c u(t-τ).

[0081]

[0082] Among them, P and Q are the reversible matrices to be designed, P = Q -1 ; ξ(t) is the auxiliary variable at the tth moment; L is the gain matrix of the interference interval observer to be solved; is the derivative of ξ(t); α(t) is the lumped variable at the tth moment; for The derivative of is the upper bound estimate of ξ(t); O is a zero matrix, for (QN) + The element in the i-th row and j-th column of the matrix, (QN) ij is the element in the i-th row and j-th column of the (QN) matrix; for The derivative of is the lower bound estimate of ξ(t); for (QN) - The element in the i-th row and j-th column of the matrix; S u , Z u , S l and Z l They are all auxiliary matrices; is the upper bound estimate of d(t); P + The element in the i-th row and j-th column of the matrix, P ij is the element in the i-th row and j-th column of the P matrix; is the lower bound estimate of d(t); P - The element in the i-th row and j-th column of the matrix; is the estimated value of the wave disturbance at time t.

[0083] Step 3: Using the wave disturbance predictor, based on the estimated value of the wave disturbance at the current moment and the estimated value of the wave disturbance at the previous moment, determine the predicted value of the wave disturbance at the next moment.

[0084] When the current moment is the initial moment, the estimated value of the wave disturbance at the previous moment is the same as the estimated value of the wave disturbance at the current moment.

[0085] As an optional implementation, the wave disturbance predictor comprises:

[0086]

[0087] in, is the predicted value of the wave disturbance at the time t+τ (the next moment); is the estimated value of the wave disturbance at the t-τth moment; x(t-τ) is the observed value of the state variable of the floating wind turbine at the t-τth moment, when the tth moment is the initial moment, x(t-τ)=x(t); is the upper boundary estimate of the auxiliary variable at the t-τth moment, when the tth moment is the initial moment, is the lower bound estimate of the auxiliary variable at the t-τth moment. When the tth moment is the initial moment,

[0088] Step 4: Using the state predictor, based on the observed value of the state variable at the current moment and the predicted value of the wave disturbance at the next moment, determine the predicted value of the state variable at the next moment.

[0089] As an optional implementation, the state predictor includes:

[0090]

[0091] in, is the predicted value of the state variable of the floating wind turbine at the t+τth moment; e is a natural constant; A(ts) is the A matrix at the tsth moment; u(s) is the predicted value of the control input quantity of the floating wind turbine at the sth moment; is the predicted value of the wave disturbance at the time s+τ.

[0092] Step 5: Using the time-delay controller, based on the predicted value of the wave disturbance at the next moment and the predicted value of the state variable at the next moment, determine the predicted value of the control input at the current moment.

[0093] As an optional implementation, the time-delay controller includes:

[0094]

[0095] Among them, σ(t+τ) is the sliding surface at the t+τth moment; G is the intermediate matrix, G=(B c T B c ) -1 B c T ; is the predicted value of the state variable of the floating wind turbine at the τth moment; is the predicted value of the state variable of the floating wind turbine at the s+τth moment; u0(s) is the nominal controller at the sth moment, K is the gain matrix of the time-delay controller to be solved; is the predicted value of the state variable of the floating wind turbine at the time t+τ; ||·|| is the modulus of the matrix; d w (t+τ) is the interval width at time t+τ; is the estimated value of the wave disturbance at time t+τ; is the estimated value at the time t+τ.

[0096] Step 6: Using the predicted value of the control input quantity at the current moment, the floating wind turbine is controlled at the current moment.

[0097] In order to verify the method of the present application, a semi-submersible floating wind turbine of the NREL 5MW model (parameters are shown in Table 1) is also selected, and the platform model is a simulation example of the NREL semi-submersible floating platform (parameters are shown in Table 2).

[0098] Table 1 Main parameters of semi-submersible floating wind turbine

[0099] parameter unit Numeric Rated power generation MW 5 Rated generator torque N·m 43093.55 Rated wind wheel speed r / min 12.1 Rated wind speed m / s 11.4 Damping coefficient N·m / (rad / s) 6215000 Upper limit of pitch angle change rate ° / s 8 Pitch angle change rate lower limit ° / s -8 Torque change rate upper limit N·m / s 15000 Torque change rate lower limit N·m / s -15000 Stiffness coefficient N·m / rad 867636000 Generator efficiency - 94.4％

[0100] Table 2 Main parameters of floating platform

[0101] parameter unit Numeric Column height m 26 Floating body height m 6 Platform main body draft m 20 Operating water depth m 200 Platform quality kg 1.3473×107

[0102] According to the known parameters, the gain matrix of the disturbance interval observer and the gain matrix of the time-delay controller are obtained as follows:

[0103] Figure 2 The schematic diagram for comparing PI and DIO-DP-ISMC power control is shown in Figure 1. Figure 2 As shown, in the case of linear wave interference, compared with the traditional PI control, the DIO-DP-ISMC control method of the present application has significantly improved power control capabilities, smaller fluctuations in generated power, significantly enhanced robustness of rated power tracking, higher power generation stability, and is conducive to grid connection.

[0104] Figure 3 This is a schematic diagram of the predicted values ​​of wave disturbance. Figure 3 As shown, the interference interval observer of the present application can effectively estimate the wave interference. The predicted value of the wave interference given by the wave interference predictor is used to compensate for the wave influence on the floating wind turbine, which effectively improves the anti-interference performance of the system.

[0105] In an exemplary embodiment, a computer device is provided, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement a floating wind turbine power control method based on wave interval estimation.

[0106] In an exemplary embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a floating wind turbine power control method based on wave interval estimation is implemented.

[0107] In an exemplary embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements a floating wind turbine power control method based on wave interval estimation.

[0108] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 4As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a floating wind turbine power control method based on wave interval estimation is implemented.

[0109] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0110] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0111] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0112] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0113] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0114] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A floating wind turbine power control method based on wave interval estimation, characterized in that: The floating wind turbine power control method based on wave interval estimation includes: Obtaining the observed value of the state variable of the floating wind turbine at the current moment and the predicted value of the control input at the previous moment; the state variables include: the rotation speed of the wind turbine blades and the front-back displacement of the tower top; when the current moment is the initial moment, the predicted value of the control input at the previous moment is the initialized control input; Using the disturbance interval observer, based on the observed value of the state variable at the current moment and the predicted value of the control input at the previous moment, the estimated value of the wave disturbance at the current moment is determined; Determine the predicted value of the wave disturbance at the next moment based on the estimated value of the wave disturbance at the current moment and the estimated value of the wave disturbance at the previous moment by using the wave disturbance predictor; when the current moment is the initial moment, the estimated value of the wave disturbance at the previous moment is the same as the estimated value of the wave disturbance at the current moment; Using the state predictor, based on the observed value of the state variable at the current moment and the predicted value of the wave disturbance at the next moment, the predicted value of the state variable at the next moment is determined; Using a time-delay controller, based on the predicted value of the wave disturbance at the next moment and the predicted value of the state variable at the next moment, the predicted value of the control input at the current moment is determined; The floating wind turbine is controlled at the current moment using the predicted value of the control input quantity at the current moment.

2. The floating wind turbine power control method based on wave interval estimation according to claim 1 is characterized in that: The construction of the interference interval observer includes: Based on linear wave theory and wave frequency uncertainty, waves are modeled to obtain a linear wave model; Based on the incremental relationship between wind turbine blade speed, tower top front and rear displacement and power generation, a floating wind turbine linear model is constructed. By utilizing the uncertainty boundary of the wave model, the positive system theory and the interval observation technology, a disturbance interval observer is constructed based on the linear wave model and the floating wind turbine linear model.

3. The floating wind turbine power control method based on wave interval estimation according to claim 2 is characterized in that: The linear wave model comprises: in, is the derivative of χ(t); χ(t) is the state quantity of the wave disturbance system at the tth moment; ω is the wave frequency; N = [1 -1] T ; T is the transpose; θ(t) is the input of the wave disturbance system at the tth moment, and satisfies θ is the upper bound of the wave frequency uncertainty; is the lower bound of the wave frequency uncertainty; T = [a 0].

4. The floating wind turbine power control method based on wave interval estimation according to claim 3 is characterized in that: The floating wind turbine linear model comprises: in, is the derivative of x(t); x(t) is the observed value of the state variable of the floating wind turbine at the tth moment, x(t) = [δω r (t),δξ t (t)] T ,δ is the increment,ω r (t) is the observed value of the fan blade speed at the tth moment, ξ t (t) is the observed value of the front-to-rear displacement of the tower top at the tth moment; u(t-τ) is the predicted value of the control input of the floating wind turbine at the t-τth moment, u(t-τ) = [δβ ref (t-τ),δT g,ref (t-τ)] T ; d(t) is the wave disturbance at the tth moment, d(t) = δH(t), H(t) is the wave height at the tth moment; y(t) is the output of the wind turbine at the tth moment, y(t) = δP g (t), P g (t) is the wind turbine power generation at the tth moment; A, B c , B d , C and D are coefficient matrices; K Tω , K Tβ With K Mβ These are the dynamic parameters of the fan control model. T r is the aerodynamic torque, ω r is the wind turbine blade speed, β is the wind turbine pitch angle command, M r is the tower bending moment; J r is the moment of inertia of the fan blade; N g J is the speed ratio of the gearbox; g is the generator moment of inertia; K T , K M , K B and ε t are all identification parameters; η is the generator efficiency; ω ref is the rated blade speed; T ref is the rated electromagnetic torque; T is the transpose.

5. The floating wind turbine power control method based on wave interval estimation according to claim 4 is characterized in that: The interference interval observer comprises: α(t)=Q[(M-LB d T)L-LA]x(t)-QLB c u(t-τ); Among them, P and Q are the reversible matrices to be designed, P = Q -1 ; ξ(t) is the auxiliary variable at the tth moment; L is the gain matrix of the interference interval observer to be solved; is the derivative of ξ(t); α(t) is the lumped variable at the tth moment; for The derivative of is the upper bound estimate of ξ(t); O is a zero matrix, for (QN) + The element in the i-th row and j-th column of the matrix, (QN) ij is the element in the i-th row and j-th column of the (QN) matrix; for The derivative of is the lower bound estimate of ξ(t); is the element in the i-th row and j-th column of the (QN)-matrix; S u , Z u , S l and Z l They are all auxiliary matrices; is the upper bound estimate of d(t); P + The element in the i-th row and j-th column of the matrix, P ij is the element in the i-th row and j-th column of the P matrix; is the lower bound estimate of d(t); is the element in the i-th row and j-th column of the P-matrix; is the estimated value of the wave disturbance at time t.

6. The floating wind turbine power control method based on wave interval estimation according to claim 5 is characterized in that: The wave disturbance predictor comprises: in, is the predicted value of the wave disturbance at time t+τ; is the estimated value of the wave disturbance at the t-τth moment; x(t-τ) is the observed value of the state variable of the floating wind turbine at the t-τth moment, when the tth moment is the initial moment, x(t-τ)=x(t); is the upper boundary estimate of the auxiliary variable at the t-τth moment, when the tth moment is the initial moment, is the lower bound estimate of the auxiliary variable at the t-τth moment. When the tth moment is the initial moment, 7. The floating wind turbine power control method based on wave interval estimation according to claim 6 is characterized in that: The state predictor comprises: in, is the predicted value of the state variable of the floating wind turbine at the t+τth moment; e is a natural constant; A(ts) is the A matrix at the tsth moment; u(s) is the predicted value of the control input quantity of the floating wind turbine at the sth moment; is the predicted value of the wave disturbance at the time s+τ.

8. The floating wind turbine power control method based on wave interval estimation according to claim 7 is characterized in that: The time-delay controller comprises: Among them, σ(t+τ) is the sliding surface at the t+τth moment; G is the intermediate matrix, G=(B c T B c ) -1 B c T ; is the predicted value of the state variable of the floating wind turbine at the τth moment; is the predicted value of the state variable of the floating wind turbine at the s+τth moment; u0(s) is the nominal controller at the sth moment, K is the gain matrix of the time-delay controller to be solved; is the predicted value of the state variable of the floating wind turbine at the time t+τ; ||·|| is the modulus of the matrix; d w (t+τ) is the interval width at time t+τ; is the estimated value of the wave disturbance at time t+τ; is the estimated value at the time t+τ.

9. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the floating wind turbine power control method based on wave interval estimation as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the floating wind turbine power control method based on wave interval estimation as described in any one of claims 1 to 7 is implemented.

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