Model predictive control method for floating wind and wave combined power generation system

Abstract

The present application relates to the technical field of ocean renewable energy power generation, and particularly discloses a kind of floating wind wave combined power generation system model predictive control method, comprising: establishing the nonlinear mathematical model of floating wind wave combined power generation system;Determine the steady state operating point of the system;Nonlinear model linearization processing;Discrete time prediction model is constructed;Design objective function;Define state and input constraint conditions;Real-time rolling optimization solution;Dynamic feedback correction mechanism.The present application starts from the mechanism of wind wave excitation, on the one hand, through the wind turbine variable pitch control to reduce the response in the turbulent wind frequency band, on the other hand, through the wave energy power generation device PTO control to reduce the response in the wave frequency band, thereby effectively reducing the tower base load and suppressing the platform pitch motion.Through the design of objective function, the definition of constraint conditions and the solution of objective function, global multi-objective optimization is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ocean renewable energy power generation, and utilizes a model predictive control strategy to realize optimization of a combined power generation system, in particular to a model predictive control method for a floating wind-wave combined power generation system. BACKGROUND

[0002] The floating wind-wave combined power generation system in the deep sea complex marine environment faces structural load and dynamic response fluctuations brought by turbulent wind, sea waves and ocean currents, which brings great challenges to the control system. Although the concept of floating wind-wave combined power generation system has been proposed for many years, the current research on its control technology still mainly focuses on the individual control of each part, such as floating wind turbine variable pitch control and PTO (Power Take-Off) control of wave energy generation device.

[0003] The common floating wind turbine control method mainly includes blade variable pitch control, variable speed control, yaw control and structural control. Among them, the blade variable pitch control includes two categories of unified variable pitch control and independent variable pitch control, of which the unified variable pitch control is often divided into PI controller and optimal controller, the PI controller includes feedback control and tuning gain, and the optimal controller mainly has LQR, H2 and H∞ and MPC (Model Predictive Control). The wind turbine structural control is mainly divided into three categories: passive control device, semi-active control device and active control device. The PTO control strategy mainly has passive control and reactive control, of which the passive control realizes the power control of the wave energy generation device by changing the force related to the PTO system, and usually includes linear damping control, lock control and clutch control. And the reactive control often sacrifices part of the power output to realize the stability of the wave energy generation device power output.

[0004] At present, the joint control technology research of the floating wind-wave combined power generation system is relatively less.

[0005] 1) The Chinese patent application with the application number 202410080364.9 discloses a full-direction excitation pendulum wind-wave combined power generation platform energy acquisition and roll reduction method, which absorbs the kinetic energy of the platform pitch and roll motion through the energy acquisition pendulum and damping mechanism, plays a dual role of energy acquisition and roll reduction, and can improve the overall power generation capacity and power generation stability.

[0006] 2) The Chinese patent application with the application number 202410615877.5 discloses a wind-wave combined power generation platform device and control method based on TMD vibration reduction, which takes the wave energy generation device as the mass component of the whole platform TMD vibration reduction, can realize the vibration control of the platform under normal power generation conditions without introducing external mass, so as to realize the vibration control of the overall structure.

[0007] However, the above-mentioned technology is mainly based on passive control technology, and it is difficult to respond to changes in the wind and wave environment in a timely manner; the output power stability of the wave power generation device is not considered; the influence of the turbulent wind frequency band on the structural response of the combined power generation system is not considered. SUMMARY

[0008] The purpose of the present application is to overcome the shortcomings of the prior art, and to provide a floating wind-wave combined power generation system model predictive control method. Under the rated wind speed working condition, this method can simultaneously reduce the structural response of the wind-wave combined power generation system in the turbulent wind frequency band and the wave frequency band, thereby effectively reducing the fluctuation of the tower foundation load and suppressing the fluctuation of the platform pitch motion, while improving the power output stability of the combined power generation system.

[0009] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0010] A floating wind-wave combined power generation system model predictive control method, comprising:

[0011] 1) Establish a nonlinear mathematical model of the floating wind-wave combined power generation system;

[0012] According to the model parameters of the floating wind-wave combined power generation system, the blade momentum theory and the potential flow theory, a nonlinear mathematical model is established, which can be expressed as:

[0013] (1),

[0014] Where x is the state variable, u c is the control input variable, u d is the environmental disturbance, and y is the output variable;

[0015] 2) Determine the steady-state working point of the system;

[0016] A high-fidelity physical model of the floating wind-wave combined power generation system is established by a numerical simulation method. In the operating condition range, different environmental conditions are selected, and numerical simulation is carried out based on the established high-fidelity physical model. The steady-state working point of the floating wind-wave combined power generation system is determined based on the statistical value;

[0017] The operating condition range is determined by the wind speed and the wave height. The present application is aimed at the operating condition above the rated wind speed, i.e. the rated wind speed to the cut-out wind speed and the rated wave height to the cut-out wave height. For example, 11.4 m / s to 25 m / s and 1 m to 6 m.

[0018] The method for determining the steady state working point, for example, taking the wind speed of 15 m / s, the wave height of 3 m, based on the established high-fidelity physical model, numerical simulation under the steady state wind and regular wave working condition, the simulation time is 2000 s, the simulation results of 1500-2000 s are selected to statistically average the state variables, control input variables and output variables, so as to obtain the steady state working point.

[0019] 3) Nonlinear model linearization processing;

[0020] According to the above nonlinear mathematical model, the state space expression of the floating wind and wave combined power generation system is designed; at the steady state working point, the first order Taylor series expansion or parameter identification method is used to linearize the nonlinear model, and the linear time-varying state space model is obtained;

[0021] The state space expression is:

[0022] (2),

[0023] Wherein, δ represents a small increment, A represents a state matrix, B c represents a control input matrix, B d represents an environmental disturbance input matrix, C represents an output matrix, state variable , control input , environmental input , state space output , T represents the transpose of the matrix, ω r represents the wind wheel speed, d t represents the front and rear displacement of the tower top of the floating wind and wave combined power generation system, β p represents the blade pitch angle, T g represents the generator electromagnetic torque, B p represents the wave energy power generation device PTO system damping force, ω a represents the angular velocity of the wave energy power generation device hinge point; β pr represents the control signal reference value of the blade pitch angle, T gr represents the control signal reference value of the generator electromagnetic torque, B pr represents the control signal reference value of the wave energy power generation device PTO system damping, ω ara control signal reference value representing the angular velocity at the hinge point of the wave energy converter; v w a control signal reference value representing the wind speed, H s a control signal reference value representing the wave height; P HS a control signal reference value representing the output power of the floating wind-wave combined power generation system.

[0024] The linear time-varying state space model is:

[0025] (3),

[0026] (4),

[0027] wherein δ represents a small increment, ω r a control signal reference value representing the wind speed of the wind turbine, B dd is the damping coefficient of the wind turbine transmission shaft, β p a control signal reference value representing the blade pitch angle, v w a control signal reference value representing the wind speed, H s a control signal reference value representing the wave height, N g is the transmission ratio of the wind turbine gearbox, T g a control signal reference value representing the electromagnetic torque of the generator, J r and J g are the moments of inertia of the blades and the generator, respectively, d t a control signal reference value representing the front and rear displacements of the tower top of the floating wind-wave combined power generation system, β pr a control signal reference value representing the blade pitch angle, is the blade pitch angle inertia time constant, T gr a control signal reference value representing the electromagnetic torque of the generator, is the wind turbine generator electromagnetic torque inertia time constant, B pr a control signal reference value representing the PTO system damping of the wave energy converter, B p a control signal reference value representing the PTO system damping force of the wave energy converter, is the PTO system inertia time constant of the wave energy converter; ω a a control signal reference value representing the angular velocity at the hinge point of the wave energy converter, P HSThe power output of the floating wind-wave combined power generation system, η WT The efficiency of the wind turbine generator, η WEC The power generation efficiency of the PTO system of the wave energy generator, N WECs The number of wave energy generators in the floating wind-wave combined power generation system, ω rr The rated speed of the wind wheel, ω ar The control signal reference value representing the angular velocity at the hinge point of the wave energy generator, i The value range of 1~ is 1~ 1. N WECs , M is the front and rear pitch bending moment of the tower foundation, and the parameter a t , K T 、K M And K B Obtained by model identification.

[0028] 4) Construct a discrete-time prediction model

[0029] Based on the linear time-varying state space model, formula (3) is discretized to construct a discrete-time prediction model for predicting the dynamic response of the system state variables and control inputs in the future time window;

[0030] The discrete-time prediction model is:

[0031] (5),

[0032] Where x(k) and x(k+1) represent the state variables of the system at discrete time steps k and k+1, respectively, u(k) represents the input variable of the system at discrete time step k, y(k) represents the observed output variable of the system at discrete time step k, G is the state transition matrix, which describes the natural evolution of the system state without external input; H is the input matrix, which quantifies the direct influence of control input and environmental disturbance on state change; C is the output matrix, which maps the system state x to the system output y.

[0033] 5) Design the objective function

[0034] When the floating wind-wave combined power generation system operates above the rated wind speed, the power output of the wind turbine side, load suppression and platform stability requirements are considered, and the optimization objective function of the floating wind-wave combined power generation system is designed:

[0035] (6);

[0036] wherein, δy(k+i) represents the output deviation vector at future time k+i δu(k+i-1) represents the control input change vector at time k+i-1 N represents the prediction horizon; the weight matrix Q is used to quantify the influence of the output deviation vector on the system performance, the weight matrix R is used to limit the drastic fluctuation of the control input.

[0037] 6) Define state and input constraints

[0038] To ensure that the control algorithm meets the system performance requirements during the optimization solving process, necessary constraints are set for the control input, as follows:

[0039] (7),

[0040] wherein, u(k) represents the control input variable of the system at discrete time step k, δu(k) represents the control input change of the system at discrete time step k, u max is the control input amplitude constraint, δu max is the control input change rate constraint.

[0041] 7) Real-time rolling optimization solving

[0042] In each control period, the CasADi solver is used to quickly solve the constrained optimization problem, obtain the optimal control sequence at a certain time, and extract the first step control output to the wind turbine variable pitch actuator and the wave energy generation device PTO system. Repeat the above steps at the next time to realize the dynamic adjustment of the system.

[0043] 8) Dynamic feedback correction mechanism

[0044] The system state is collected in real time by the state monitoring system of the floating wind-wave combined power generation system composed of multiple sensors, and compared with the output value of the prediction model. The parameters of the prediction model or the target function weight coefficient are dynamically corrected to compensate for the errors caused by sudden changes in wind speed or surge and other environmental disturbances and model mismatch, thereby improving the robustness and adaptability of the control system.

[0045] The beneficial effects of the present application are:

[0046] ​​The floating wind-wave combined power generation system model predictive control method provided by the application can reduce the structural response of the wind-wave combined power generation system in the turbulent wind frequency band and the wave frequency band, thereby effectively reducing the tower foundation load fluctuation and inhibiting the fluctuation of the platform pitch motion, while improving the power output stability of the combined power generation system.

[0047] The application designs a target function considering the total power of the combined power generation system, defines constraint conditions considering the tower foundation front and rear pitch bending moments and the platform pitch motion, solves the target function based on a CasADi solver, optimizes the wind turbine pitch control parameters and the wave energy power generation device PTO control parameters online, and thus realizes global multi-objective optimization. The method can start from the mechanism of wind-wave excitation, reduce the response in the turbulent wind frequency band (0-0.10 Hz) through wind turbine pitch control, reduce the response in the wave frequency band (0.10-0.60 Hz) through wave energy power generation device PTO control, thereby effectively reducing the tower foundation load fluctuation and inhibiting the fluctuation of the platform pitch motion, while improving the power output stability of the combined power generation system. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 A floating wind-wave combined power generation system schematic diagram is provided for the application.

[0049] Figure 2 A floating wind-wave combined power generation system model predictive control method flow chart is provided for the application.

[0050] Figure 3 A floating wind-wave combined power generation system model predictive control method structure block diagram is provided for the application.

[0051] Figure 4 A wind speed, wave height, pitch angle, wind turbine side power, engine room horizontal acceleration and tower foundation front and rear pitch bending moment time history curve comparison diagram of the floating wind-wave combined power generation system model predictive control method and the baseline controller is provided for the application.

[0052] Figure 5 A platform six-degree-of-freedom response time history curve comparison diagram of the floating wind-wave combined power generation system model predictive control method and the baseline controller is provided for the application.

[0053] Figure 6 A wind speed and wave height power spectral density diagram of the floating wind-wave combined power generation system model predictive control method is provided for the application.

[0054] Figure 7A tower base pitch moment power spectral density comparison chart of the floating wind-wave combined power generation system model predictive control method provided by the present application and the baseline controller;

[0055] Figure 8 A platform pitch motion power spectral density comparison chart of the floating wind-wave combined power generation system model predictive control method provided by the present application and the baseline controller;

[0056] Figure 9 A power generation power statistical value comparison chart of the floating wind-wave combined power generation system model predictive control method provided by the present application and the baseline controller;

[0057] Wherein, 1. wind, 2. wave, 3. seabed, 4. blade, 5. hub, 6. cabin, 7. tower, 8. wave energy generator and platform connection hinge point, 9. wave energy generator rocker arm, 10. wave energy generator float, 11. floating platform, 12. anchor chain. DETAILED DESCRIPTION

[0058] The present application will be further described below in conjunction with the drawings and examples.

[0059] The structures, proportions, sizes, etc. shown in the drawings of the present specification are only used to cooperate with the content disclosed in the specification, to be understood and read by those skilled in the art, and do not have technical significance to limit the conditions under which the present application can be implemented. Any modification of structure, change of proportion relationship or adjustment of size, without affecting the effect and purpose that the present application can produce, should still fall within the scope of the technical content disclosed by the present application. At the same time, the terms such as "upper", "lower", "left", "right", "middle" and "one" in the present specification are only for the convenience of clear understanding of the description, and are not used to limit the scope of the present application. The change or adjustment of the relative relationship, without substantially changing the technical content, is also considered as the scope of the present application.

[0060] As shown in Figure 1 , the environmental conditions include wind 1, wave 2 and seabed 3. The floating wind-wave combined power generation system includes three blades 4, a hub 5, a cabin 6, a tower 7, three wave energy generator and platform connection hinge points 8, three wave energy generator rocker arms 9, three wave energy generator floats 10, a floating platform 11 and three anchor chains 12. Among them, the third wave energy generator and platform connection hinge point, rocker arm and float are not shown in the picture.

[0061] As shown in Figures 2-3 , the floating wind-wave combined power generation system model predictive control method comprises:

[0062] 1) Establishing a nonlinear mathematical model of the floating wind-wave combined power generation system;

[0063] According to the model parameters of the floating wind-wave combined power generation system, the blade element momentum theory and the potential flow theory, a nonlinear mathematical model thereof is established, which can be expressed as:

[0064] (1),

[0065] Wherein, x is a state variable, u c is a control input variable, u d is an environmental disturbance, and y is an output variable;

[0066] 2) Determining the steady state working point of the system;

[0067] A high-fidelity physical model of the floating wind-wave combined power generation system is established by a numerical simulation method, different environmental conditions are selected within the operating condition range thereof, numerical simulation is carried out based on the established high-fidelity physical model, and the steady state working point of the floating wind-wave combined power generation system is determined based on statistical values;

[0068] The operating condition range is determined by the wind speed and the wave height. The present application is aimed at the operating condition above the rated wind speed, i.e. the rated wind speed to the cut-out wind speed and the rated wave height to the cut-out wave height. For example, 11.4 m / s to 25 m / s and 1 m to 6 m.

[0069] The method for determining the steady state working point is, for example, taking the wind speed as 15 m / s and the wave height as 3 m, carrying out numerical simulation under the steady state wind and regular wave condition based on the established high-fidelity physical model, the simulation time being 2000 s, selecting the simulation results of 1500-2000 s to statistically determine the mean values of the state variables, the control input variables and the output variables, so as to obtain the steady state working point.

[0070] The key parameters (such as the wind wheel rotating speed, the generator rotating speed, the pitch angle and the angular velocity of the wave energy power generation device hinge point) in the balanced state are determined, a reference working condition is provided for the subsequent control strategy design, and the applicability of the model under the typical sea conditions is ensured.

[0071] 3) Linearization processing of the nonlinear model;

[0072] According to the above nonlinear mathematical model, a corresponding state space expression of the floating wind-wave combined power generation system is designed; at the steady state working point, the nonlinear model is linearized by using the first-order Taylor series expansion or the parameter identification method, so as to obtain a linear time-varying state space model;

[0073] The state space expression is:

[0074] (2),

[0075] where δ represents a small increment, A represents a state matrix, B c represents a control input matrix, B d represents an environmental disturbance input matrix, C represents an output matrix, state variable , control input , environmental input , state space output , T represents the transpose of a matrix, ω r represents a wind turbine speed, d t represents a floating wind-wave combined power generation system tower top front and rear displacement, β p represents a blade pitch angle, T g represents a generator electromagnetic torque, B p represents a wave energy power generation device PTO system damping force, ω a represents a wave energy power generation device hinge point angular velocity; β pr represents a blade pitch angle control signal reference value, T gr represents a generator electromagnetic torque control signal reference value, B pr represents a wave energy power generation device PTO system damping control signal reference value, ω ar represents a wave energy power generation device hinge point angular velocity control signal reference value; v w represents a wind speed, H s represents a wave height; P HS represents a floating wind-wave combined power generation system output power generation power.

[0076] The linear time-varying state space model is:

[0077] (3),

[0078] (4),

[0079] where δ represents a small increment, ω r represents a wind turbine speed, B dd is a wind turbine transmission shaft damping coefficient, βp represents the blade pitch angle, v w represents wind speed, H s represents the wave height, N g is the fan gearbox transmission ratio, T g represents the electromagnetic torque of the generator, J r and J g are the rotational inertia of the blade and generator, d t Represents the front-to-back displacement of the tower top of the floating wind-wave combined power generation system, β pr represents the control signal reference value of the blade pitch angle, is the blade pitch angle inertia time constant, T gr The control signal reference value representing the electromagnetic torque of the generator, is the inertia time constant of electromagnetic torque of wind turbine generator, B pr The reference value of the control signal representing the damping of the PTO system of the wave energy generator, B p Represents the damping force of the PTO system of the wave energy generator, is the inertia time constant of the PTO system of the wave energy generator; ω a represents the angular velocity at the hinge point of the wave energy generator, P HS Represents the power output of the floating wind-wave combined power generation system, η WT is the wind turbine generator efficiency, η WEC The power generation efficiency of the PTO system of the wave energy power generation device is N WECs is the number of wave energy power generation devices in the floating wind and wave combined power generation system, ω rr is the rated speed of the wind wheel, ω ar The reference value of the control signal representing the angular velocity at the hinge point of the wave energy generator, i The value range is 1~ N WECs , M is the front and rear pitching moment of the tower base, parameter a t 、 K T 、K M and K BObtained through model identification.

[0080] 4) Build a discrete-time prediction model

[0081] Based on the linear time-varying state space model, formula (3) is discretized to construct a prediction model in the discrete time domain to predict the dynamic response of the system's state variables and control inputs in the future time window;

[0082] The prediction model in the discrete time domain is:

[0083] (5),

[0084] Among them, x(k) and x(k+1) represent the state variables of the system at discrete time steps k and k+1 respectively, u(k) represents the input variable of the system at discrete time step k, y(k) represents the observed output variable of the system at discrete time step k, G is the state transition matrix, which describes the natural evolution law of the system state in the absence of external input; H is the input matrix, which quantifies the direct impact of control input and environmental disturbance on state change; C is the output matrix, whose function is to map the system state x to the system output y.

[0085] 5) Design objective function

[0086] When the floating wind-wave combined power generation system operates above the rated wind speed, the wind turbine side needs to adjust the generator speed to keep the wind turbine side output power stable near the rated power. At the same time, in order to reduce the fatigue load of the wind turbine pitch actuator, the pitch angle and generator torque should not move too frequently. The wave energy generator side needs to adjust the angular velocity at the hinge point to keep the PTO system output power stable. At the same time, the PTO system damping force of the wave energy generator device should not move too frequently. Taking all the above factors into consideration, the optimization objective function of the floating wind-wave combined power generation system is designed as follows:

[0087] (6);

[0088] in, δy(k+i) Indicates the future k+i The output deviation vector at time , δu(k+i-1) Indicates the k+i-1 The control input change vector at time , N Represents the prediction time domain; weight matrix Q Used to quantify the impact of the output deviation vector on system performance, the weight matrix R Used to limit sharp fluctuations in control input.

[0089] 6) Define state and input constraints

[0090] To ensure that the control algorithm meets the system performance requirements during the optimization solving process, the control input is necessary to be constrained, such as the following:

[0091] (7),

[0092] wherein, u(k) represents the control input variable of the system at the discrete time step k, δu(k) represents the control input change of the system at the discrete time step k, u max is the control input amplitude constraint, δu max is the control input change rate constraint.

[0093] 7) Real-time rolling optimization solving

[0094] In each control period, the CasADi solver is used to quickly solve the constrained optimization problem, obtain the optimal control sequence at a certain time, and extract the first step control output to the fan variable pitch actuator and the wave energy generation device PTO system, and repeat the above steps at the next time to realize the dynamic adjustment of the system.

[0095] 8) Dynamic feedback correction mechanism

[0096] The system state is collected in real time by the state monitoring system of the floating wind-wave combined power generation system composed of multiple sensors, and compared with the output value of the prediction model. The parameters of the prediction model or the target function weight coefficient are dynamically corrected to compensate for the errors caused by sudden changes in wind speed or environmental disturbances such as swells and model mismatch, and to improve the robustness and adaptability of the control system.

[0097] As shown in Figure 4 , under the working conditions of turbulent wind (average wind speed 15 m / s) and irregular wave (significant wave height 3 m, spectral peak period 6 s), the fan side power, cabin horizontal acceleration and tower base front and rear pitch moment fluctuation of the floating wind-wave combined power generation system using the control method of the application are smaller than those using the baseline controller.

[0098] As shown in Figure 5 , under the same working conditions, compared with the baseline controller, the platform surge motion, heave motion of the floating wind-wave combined power generation system using the control method of the application has slightly increased fluctuation, while the platform roll motion has significantly reduced fluctuation, and the platform sway motion, platform roll motion and platform yaw motion have not changed significantly. The platform roll motion is the most important parameter affecting the fan side power generation performance and platform stability of the floating wind-wave combined power generation system, therefore, the control method of the application can effectively improve the platform stability.

[0099] As shown in Figure 6 , the power spectral densities of the environmental wind speed and wave height present different distribution rules, in which the energy of the turbulent wind is mainly concentrated in the high frequency band between 0 and 0.10 Hz, and the energy of the wave is mainly concentrated in the high frequency band between 0.10 and 0.60 Hz. This indicates that the environmental excitation of the floating wind-wave combined power generation system has obvious wideband characteristics.

[0100] As shown in Figure 7 , compared with using the baseline controller, using the control method of the present application can effectively reduce the responses of the tower base fore and aft pitch bending moments of the floating wind-wave combined power generation system in the turbulent wind frequency band (0-0.10 Hz), and can also greatly reduce the responses of the tower base pitch bending moments in the wave frequency band (0.10-0.60 Hz). This indicates that the method of the present application has great potential in reducing the structural fatigue load of the floating wind-wave combined power generation system.

[0101] As shown in Figure 8 , compared with using the baseline controller, using the control method of the present application can greatly reduce the responses of the platform pitch motion of the floating wind-wave combined power generation system in the turbulent wind frequency band (0-0.10 Hz), and can also weakly reduce the responses of the platform pitch motion in the wave frequency band (0.10-0.60 Hz). This indicates that the method of the present application has certain potential in improving the platform stability of the floating wind-wave combined power generation system.

[0102] As shown in Figure 9 , compared with using the baseline controller, using the control method of the present application can effectively reduce the fluctuations of the power generation of the wind turbine side of the floating wind-wave combined power generation system, and will not affect the average power generation of the wind turbine side. In addition, the wave energy power generation device side of the floating wind-wave combined power generation system can also output about 300 kW of power generation, about 6% of the power generation of the wind turbine side. This indicates that the method of the present application is conducive to improving the power generation output stability of the floating wind-wave combined power generation system.

[0103] Although the specific embodiments of the present application have been described above with reference to the accompanying drawings, it is not a limitation on the protection scope of the present application, and those skilled in the art should understand that various modifications or changes made by those skilled in the art on the basis of the technical solutions of the present application without creative labor are still within the protection scope of the present application.

Claims

1. A model predictive control method for a floating wind-wave combined power generation system, characterized in that: include: (1) Establish a nonlinear mathematical model of the floating wind-wave combined power generation system; it can be expressed as: （1）， Among them, x is the state variable, u c is the control input variable, u d is the environmental disturbance, y is the output variable; (2) Determine the steady-state operating point of the system; (3) Linearization of the nonlinear model: Based on the nonlinear mathematical model of step (1), the state space expression of the corresponding floating wind-wave combined power generation system is designed; at the steady-state operating point, the nonlinear model is linearized using a first-order Taylor series expansion or parameter identification method to obtain a linear time-varying state space model; (4) Constructing a discrete-time prediction model; Based on the linear time-varying state space model, the state space expression is discretized and a prediction model in the discrete time domain is constructed to predict the dynamic response of the system's state variables and control inputs in the future time window; (5) Design objective function; When the floating wind-wave power generation system operates above the rated wind speed, the optimization objective function of the floating wind-wave power generation system is designed, taking into account the power output of the wind turbine side, load suppression and platform stability requirements; (6) Define state and input constraints; To ensure that the control actions of the floating wind-wave combined power generation system always meet the performance requirements of the system itself during the optimization process of the control algorithm, constraints are set on the control input. The specific constraints are as follows: （7）， in, u(k) represents the control input variable of the system at discrete time step k, δu(k) represents the change in the control input of the system at discrete time step k, u max To control the input amplitude constraint, δu max To constrain the rate of change of the control input; (7) Real-time rolling optimization solution; In each control cycle, the CasADi solver is used to quickly solve the constrained optimization problem, obtain the optimal control sequence at a certain moment, and extract the first-step control variable output to the wind turbine pitch actuator and the wave energy generator PTO system. The above steps are repeated at the next moment to achieve dynamic adjustment of the system. (8) Dynamic feedback correction mechanism; The floating wind-wave combined power generation system's status monitoring system collects system status in real time and compares it with the output value of the prediction model; dynamically corrects the parameters of the prediction model or adjusts the objective function weight coefficient to compensate for errors caused by sudden changes in wind speed or surge environment disturbances and model mismatch, thereby improving the robustness and adaptability of the control system.

2. The model predictive control method for a floating wind-wave combined power generation system according to claim 1, wherein: In the step (2), a high-fidelity physical model of the floating wind-wave combined power generation system is established by a numerical simulation method, different environmental conditions are selected within the operating range of the floating wind-wave combined power generation system, and numerical simulation is performed based on the established high-fidelity physical model, and the steady-state operating point of the floating wind-wave combined power generation system is determined based on statistical values; The method for determining the steady-state operating point is to perform numerical simulations under steady-state wind and regular wave conditions based on the established high-fidelity physical model. The simulation results are statistically analyzed to obtain the mean values ​​of state variables, control input variables and output variables to obtain the steady-state operating point.

3. The model predictive control method for a floating wind-wave combined power generation system according to claim 1, wherein: In step (3), the state space expression is: （2）， Where δ represents a small increment, A represents the state matrix, B c represents the control input matrix, B d represents the environmental disturbance input matrix, C Represents the output matrix, state variables , control input , environmental input , state space output , where T represents the transpose of the matrix, ω r Represents the wind wheel speed, d t Represents the front-to-back displacement of the tower top of the floating wind-wave combined power generation system, β p represents the blade pitch angle, T g represents the electromagnetic torque of the generator, B p Represents the damping force of the PTO system of the wave energy generator, ω a Represents the angular velocity at the hinge point of the wave energy generator; β pr represents the control signal reference value of the blade pitch angle, T gr The control signal reference value representing the electromagnetic torque of the generator, B pr The reference value of the control signal representing the damping of the PTO system of the wave energy generator, ω ar A control signal reference value representing the angular velocity at the hinge point of the wave energy generator; v w represents wind speed, H s Represents wave height; P HS Represents the power generated by the floating wind and wave combined power generation system.

4. The model predictive control method for a floating wind-wave combined power generation system according to claim 1, wherein: In step (3), the linear time-varying state space model is: （3）， （4）， Where δ represents a small increment, ω r Represents the wind wheel speed, B dd is the damping coefficient of the fan drive shaft, β p represents the blade pitch angle, v w represents wind speed, H s represents the wave height, N g is the transmission ratio of the fan gearbox, T g represents the electromagnetic torque of the generator, J r and J g are the rotational inertia of the blade and generator, d t Represents the front-to-back displacement of the tower top of the floating wind-wave combined power generation system, β pr represents the control signal reference value of the blade pitch angle, is the blade pitch angle inertia time constant, T gr The control signal reference value representing the electromagnetic torque of the generator, is the inertia time constant of electromagnetic torque of wind turbine generator, B pr The reference value of the control signal representing the damping of the PTO system of the wave energy generator, B p Represents the damping force of the PTO system of the wave energy generator, is the inertia time constant of the PTO system of the wave energy generator; ω a represents the angular velocity at the hinge point of the wave energy generator, P HS Represents the power output of the floating wind-wave combined power generation system, η WT is the wind turbine generator efficiency, η WEC The power generation efficiency of the PTO system of the wave energy power generation device is N WECs is the number of wave energy power generation devices in the floating wind and wave combined power generation system, ω rr is the rated speed of the wind wheel, ω ar The reference value of the control signal representing the angular velocity at the hinge point of the wave energy generator, i The value range is 1~ N WECs , M is the front and rear pitching moment of the tower base, parameter a t 、 K T 、K M and K B Obtained through model identification.

5. The model predictive control method for a floating wind-wave combined power generation system according to claim 1, wherein: In step (4), the prediction model in the discrete time domain is: （5）， Among them, x(k) and x(k+1) represent the state variables of the system at discrete time steps k and k+1 respectively, u(k) represents the input variable of the system at discrete time step k, y(k) represents the observed output variable of the system at discrete time step k, G is the state transition matrix, which describes the natural evolution law of the system state in the absence of external input; H is the input matrix, which quantifies the direct impact of control input and environmental disturbance on state change; C is the output matrix, whose function is to map the system state x to the system output y.

6. The model predictive control method for a floating wind-wave combined power generation system according to claim 1, wherein: In step (5), the optimization objective function of the floating wind-wave combined power generation system is: （6） in, δy(k+i) Indicates the future k+i The output deviation vector at time , δu(k+i-1) Indicates the k+i-1 The control input change vector at time , N Represents the prediction time domain; weight matrix Q Used to quantify the impact of the output deviation vector on system performance, the weight matrix R Used to limit sharp fluctuations in control input.

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