Power optimization control method and device for direct-drive wave power generation system

Abstract

The invention discloses a power optimization control method and device for a direct-drive type wave power generation system, and belongs to the field of electric power systems.The method comprises the steps that an ideal model is obtained according to the direct-drive type wave power generation system; inputting the current wave excitation force and an ideal compensation control quantity solved based on a previous round of ideal state quantity into an ideal model, and obtaining the ideal state quantity through Kalman filtering; inputting the current wave exciting force, the sliding mode compensation amount and the actual compensation control amount solved based on the actual state amount of the previous round into the direct-driven wave power generation system, and obtaining the actual state amount through Kalman filtering; and finally, obtaining reference electromagnetic force according to the actual state quantity and converting the reference electromagnetic force into reference current to realize system power optimization control. Therefore, by implementing the method and the device, the problem that the wave energy power capturing efficiency is difficult to improve while the adaptability to different wave conditions is ensured in the prior art can be solved.

Description

Technical Field

[0001] This invention relates to the field of power systems, and more particularly to a power optimization control method and apparatus for direct-drive wave power generation systems. Background Technology

[0002] In modern power systems, direct-drive wave power generation systems are one of the core devices for utilizing marine renewable energy. The key feature of direct-drive wave power generation systems is the elimination of intermediate gearboxes and other transmission mechanisms found in traditional wave power generation systems. Instead, they directly drive a floating body through wave-driven reciprocating motion, which in turn drives a permanent magnet synchronous linear motor, directly converting the mechanical energy contained in the waves into electrical energy. This structure reduces energy loss in intermediate transmission links, simplifies the system structure, and allows for a more direct response to wave motion. Theoretically, it possesses higher energy conversion efficiency and represents an important technological direction for the large-scale development of wave energy. It can contribute to the diversification of energy supply in power systems and alleviate dependence on traditional fossil fuels.

[0003] In existing technologies, the control of wave power generation systems mainly relies on two methods: passive damping control and reactive power control. Since passive damping control can only achieve linear matching between the reaction force and the velocity of the oscillating body, it cannot adapt to the dynamic changes of irregular incident waves in the ocean. Furthermore, it requires real-time feedback to adjust the damping value in order to approach the resonance state. Therefore, it has the problem of not being able to stably achieve resonance between the wave driving force and the buoy velocity, and it is difficult to meet the conditions for maximum power acquisition. While reactive power control pursues resonance by superimposing the equivalent spring force and damping force, it requires the use of approximate methods to achieve control optimization under limited conditions. Moreover, the control algorithm has high complexity, and the prediction of wave state is prone to significant errors, which limits the control performance. Therefore, it has the problems of low power capture efficiency and insufficient robustness, making it difficult to adapt to complex sea conditions. Summary of the Invention

[0004] This invention provides a power optimization control method and apparatus for direct-drive wave power generation systems, which can solve the problem in the prior art of improving wave energy capture efficiency while ensuring adaptability to different wave conditions.

[0005] In a first aspect, embodiments of the present invention provide a power optimization control method for a direct-drive wave power generation system, comprising:

[0006] An ideal model of the direct-drive wave power generation system is established based on the direct-drive wave power generation system.

[0007] The current wave excitation force and the current ideal compensation control quantity of the direct-drive wave power generation system are input into the ideal model of the direct-drive wave power generation system to obtain the current ideal output state information, and the current ideal state quantity information is obtained according to the first preset Kalman filter and the current ideal output state information; wherein, the current ideal compensation control quantity is obtained by solving the ideal state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation.

[0008] The current wave excitation force, current sliding mode compensation amount, and current actual compensation control amount of the direct-drive wave power generation system are input into the ideal model of the direct-drive wave power generation system to obtain the current actual output state information. The current actual state quantity information is obtained based on the second preset Kalman filter and the current actual output state information. Among them, the current actual compensation control amount is obtained by solving the state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation. The current sliding mode compensation amount is obtained based on the ideal state quantity information and the actual state quantity information of the previous round of control output.

[0009] The current reference electromagnetic force is obtained based on the current actual state information, and the reference current is calculated based on the current reference electromagnetic force. Then, the power optimization control of the direct-drive wave power generation system is performed based on the reference current.

[0010] This application embodiment establishes an ideal model of a direct-drive wave power generation system, providing a precise system characteristic mapping basis for the implementation of subsequent control strategies, thus avoiding deviations in control direction due to excessive discrepancies between the model and the actual system. The current wave excitation force and the ideal compensation control quantity, calculated using the optimal gain method and the Riccati equation based on the ideal state quantity from the previous round, are input into the model. The output state information is then processed by a first preset Kalman filter, which not only ensures that the control under the ideal state conforms to the optimal theoretical framework and reduces deviations at the ideal control level, but also improves the accuracy of the ideal state quantity information through filtering, providing a reliable optimal reference for subsequent actual control. Meanwhile, in the actual control path, a sliding mode compensation quantity obtained by combining the ideal and actual state quantities from the previous round is introduced. This is paired with the actual compensation control quantity, which is also solved using the optimal method, and input into the model. Then, the actual output state is processed by a second preset Kalman filter. This effectively corrects the deviation between the ideal and actual systems, enhances the system's resistance to disturbances such as model mismatch and wave condition changes, and improves the accuracy of the actual state quantity information. Finally, a reference electromagnetic force is obtained based on the actual state quantities and converted into a reference current to achieve control. This allows the optimized strategy to be accurately implemented, ensuring that the system can stably approach the maximum power capture target even under complex sea conditions. Therefore, this application can solve the problem in the prior art of improving wave energy power capture efficiency while ensuring adaptability to different wave conditions.

[0011] As a preferred example of the first aspect, the establishment of an ideal model of the direct-drive wave power generation system based on the direct-drive wave power generation system specifically includes:

[0012] The radiation force data of the direct-drive wave power generation system is obtained, and a system state-space model is established based on the radiation force data using the float force analysis method.

[0013] The radiation force in the state space model of the system is simplified by using finite element analysis software simulation method to obtain the ideal model of the direct-drive wave power generation system.

[0014] In this preferred example, system radiation force data is first acquired, and a system state-space model is constructed by combining the buoy force analysis. Then, the radiation force is simplified through finite element analysis software simulation. This application accurately focuses on the hydrodynamic characteristics of the wave power generation system, avoiding modeling biases caused by neglecting radiation force or coarse processing in existing models. The buoy force analysis ensures that the model reflects the core mechanical relationships of the floating body's motion, while the simplified radiation force through finite element simulation retains the key influence of radiation force on system dynamics and avoids model redundancy due to complex radiation force calculations. This allows the ideal model to accurately map the actual operating characteristics of the system, providing a reliable foundation for subsequent control strategies, without affecting the control response speed due to excessive model complexity. This solves the problems of control bias and low power capture efficiency caused by improper radiation force processing in existing models, improving the effectiveness of subsequent optimized control.

[0015] As a preferred example of the first aspect, the current ideal compensation control quantity is obtained by solving the optimal gain calculation method and the Riccati equation based on the ideal state quantity information of the previous round of control output, specifically:

[0016] Based on the ideal state quantity information of the previous round of control output and the preset weight matrix, the minimum performance index function is constructed using the optimal gain calculation method;

[0017] The Riccati equation is established based on the quadratic optimal control theory, and the ideal feedback gain matrix is ​​obtained by solving the Riccati equation according to the minimum performance index function.

[0018] Based on the ideal feedback gain matrix and the ideal state quantity information of the previous round of control output, the current ideal compensation control quantity is obtained by using the state feedback calculation formula.

[0019] In this preferred example, based on the information of the previous round of ideal state variables, a minimum performance index function is constructed by combining it with a preset weight matrix. Then, the ideal feedback gain matrix is ​​solved using the Riccati equation to obtain the control quantity. This application allows for flexible adjustment of the control objective's emphasis through the weight matrix, such as optimizing power capture or system stability according to sea state requirements, avoiding the poor adaptability problem caused by fixed gain in existing control methods. The application of the Riccati equation ensures that the feedback gain matrix solved within the framework of quadratic optimal control theory achieves optimal control under ideal conditions, overcoming the suboptimal limitations caused by approximate calculations in reactive power control. Simultaneously, based on the calculation of the previous round of ideal state variables, there is no need to reconstruct the performance function and solve equations in real time, reducing the computational pressure of real-time control. This ensures both the power capture potential under ideal conditions and provides a precise optimal reference benchmark for subsequent actual control, enhancing the optimization foundation of the overall control strategy.

[0020] As a preferred example of the first aspect, the current actual compensation control quantity is obtained by solving the optimal gain calculation method and the Riccati equation based on the state quantity information of the previous round of control output, specifically:

[0021] Based on the actual state information of the previous round of control output and the preset weight matrix, the minimum performance index function is constructed using the optimal gain calculation method.

[0022] The Riccati equation is established based on the quadratic optimal control theory, and the Riccati equation is solved according to the minimum performance index function to obtain the actual feedback gain matrix.

[0023] Based on the actual feedback gain matrix and the ideal state quantity information of the previous round of control output, the current actual compensation control quantity is calculated using the state feedback calculation formula.

[0024] In this preferred example, a minimum performance index function is first constructed based on the actual state information from the previous round, combined with a preset weight matrix. Then, the actual feedback gain matrix is ​​solved using the Riccati equation to generate the control quantity. This differs from existing technologies where actual control is disconnected from the actual system state. By using the actual operating state as the basis for calculation, it ensures that the actual compensation control quantity accurately adapts to the real-time dynamics of the system, avoiding control failure due to deviations between ideal and reality. The application of the Riccati equation guarantees that actual control operates within the optimal theoretical framework, solving the problems of complex algorithms and predictive errors in reactive power control, and improving the accuracy of actual control. Simultaneously, it uses the same solution logic as the ideal compensation control quantity, simplifying the overall design and debugging difficulty of the control strategy. It can respond promptly to changes in the actual system state under complex sea conditions, reducing power loss during actual operation and enhancing the system's stability and power capture efficiency under dynamic conditions.

[0025] As a preferred example of the first aspect, the current sliding mode compensation amount is obtained based on the ideal state information and the actual state information of the previous round of control output, specifically:

[0026] Based on the ideal state quantity information and actual state quantity information of the previous round of control output, the displacement error is calculated using the displacement error formula, and the sliding surface is constructed based on the ideal state quantity information and actual state quantity information of the previous round of control output.

[0027] A switching function is constructed based on the sliding surface, and the current sliding compensation amount is obtained by using the sliding compensation value calculation formula based on the switching function, the displacement error, and the preset adjustable parameters.

[0028] In this preferred example, the displacement error is calculated using the previous round of ideal and actual state quantities, a sliding mode surface is constructed, and then the compensation amount is obtained by combining the switching function and adjustable parameters. The switching function is also smoothed. This accurately captures the deviation between the ideal and actual states. The design of the sliding mode surface ensures that the compensation amount can specifically correct the direction of the deviation, solving the state offset and power loss problems caused by model mismatch in existing technologies. The smoothing of the switching function effectively avoids high-frequency chattering in traditional sliding mode control, reducing the impact of chattering on motors and system components, and improving system stability. Adjustable parameters allow for adjustment of the compensation intensity according to different sea states, enhancing adaptability to complex operating conditions and avoiding over- or under-compensation problems caused by fixed compensation amounts. Overall, this effectively improves system robustness, ensuring that the system stably tracks the ideal power optimization target during actual control, reducing energy loss caused by model errors, and further guaranteeing the achievement of maximum power capture.

[0029] Secondly, the present invention provides a power optimization control device for a direct-drive wave power generation system, comprising: a model building module, a first processing module, a second processing module, and a power optimization control module;

[0030] The model building module is used to build an ideal model of the direct-drive wave power generation system based on the direct-drive wave power generation system.

[0031] The first processing module is used to input the current wave excitation force and the current ideal compensation control quantity of the direct-drive wave power generation system into the ideal model of the direct-drive wave power generation system to obtain the current ideal output state information, and to obtain the current ideal state quantity information based on the first preset Kalman filter and the current ideal output state information; wherein, the current ideal compensation control quantity is obtained by solving the ideal state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation;

[0032] The second processing module is used to input the current wave excitation force, current sliding mode compensation amount, and current actual compensation control amount of the direct-drive wave power generation system into the ideal model of the direct-drive wave power generation system to obtain the current actual output state information, and to obtain the current actual state quantity information based on the second preset Kalman filter and the current actual output state information; wherein, the current actual compensation control amount is obtained by solving the state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation, and the current sliding mode compensation amount is obtained based on the ideal state quantity information and the actual state quantity information of the previous round of control output;

[0033] The power optimization control module is used to obtain the current reference electromagnetic force based on the current actual state information, calculate the reference current based on the current reference electromagnetic force, and then perform power optimization control on the direct-drive wave power generation system based on the reference current.

[0034] As a preferred example of the second aspect, the model building module includes a first model building unit and a second model building unit;

[0035] The first model building unit is used to acquire the radiation force data of the direct-drive wave power generation system, and to establish a system state space model based on the radiation force data using the float force analysis method.

[0036] The second model building unit is used to perform equivalent simplification of the radiation force in the system state space model using finite element analysis software simulation methods to obtain the ideal model of the direct-drive wave power generation system.

[0037] As a preferred example of the second aspect, the first processing module includes a first processing unit, a second processing unit, and a third processing unit;

[0038] The first processing unit is used to construct a minimum performance index function based on the ideal state quantity information of the previous round of control output and the preset weight matrix, using the optimal gain calculation method.

[0039] The second processing unit is used to establish the Riccati equation based on the quadratic optimal control theory, and solve the Riccati equation based on the minimum performance index function to obtain the ideal feedback gain matrix;

[0040] The third processing unit is used to calculate the current ideal compensation control quantity based on the ideal feedback gain matrix and the ideal state quantity information of the previous round of control output using the state feedback calculation formula.

[0041] As a preferred example of the second aspect, the second processing module includes a fourth processing unit, a fifth processing unit, and a sixth processing unit;

[0042] The fourth processing unit is used to construct a minimum performance index function based on the actual state quantity information of the previous round of control output and the preset weight matrix, using the optimal gain calculation method.

[0043] The fifth processing unit is used to establish the Riccati equation based on the quadratic optimal control theory, and solve the Riccati equation based on the minimum performance index function to obtain the actual feedback gain matrix.

[0044] The sixth processing unit is used to calculate the current actual compensation control quantity based on the actual feedback gain matrix and the ideal state quantity information of the previous round of control output using the state feedback calculation formula.

[0045] As a preferred example of the second aspect, the second processing module includes a seventh processing unit and an eighth processing unit;

[0046] The seventh processing unit is used to calculate the displacement error using the displacement error formula based on the ideal state quantity information and actual state quantity information output from the previous round of control, and to construct the sliding surface based on the ideal state quantity information and actual state quantity information output from the previous round of control.

[0047] The eighth processing unit is used to construct a switching function based on the sliding surface, and to calculate the current sliding compensation amount using the sliding compensation value calculation formula based on the switching function, the displacement error, and the preset adjustable parameters.

[0048] In summary, this application embodiment establishes an ideal model of a direct-drive wave power generation system, providing a precise system characteristic mapping basis for the implementation of subsequent control strategies, thus avoiding deviations in control direction due to excessive discrepancies between the model and the actual system. The current wave excitation force and the ideal compensation control quantity, calculated using the optimal gain method and the Riccati equation based on the previous round of ideal state quantities, are input into the model. The output state information is then processed using a first preset Kalman filter. This not only ensures that the control under the ideal state conforms to the optimal theoretical framework, reducing deviations at the ideal control level, but also improves the accuracy of the ideal state quantity information through filtering, providing a reliable optimal reference for subsequent actual control. Meanwhile, in the actual control path, a sliding mode compensation quantity obtained by combining the ideal and actual state quantities from the previous round is introduced. This is paired with the actual compensation control quantity, which is also solved using the optimal method, and input into the model. Then, the actual output state is processed by a second preset Kalman filter. This effectively corrects the deviation between the ideal and actual systems, enhances the system's resistance to disturbances such as model mismatch and wave condition changes, and improves the accuracy of the actual state quantity information. Finally, a reference electromagnetic force is obtained based on the actual state quantities and converted into a reference current to achieve control. This allows the optimized strategy to be accurately implemented, ensuring that the system can stably approach the maximum power capture target even under complex sea conditions. Therefore, this application can solve the problem in the prior art of improving wave energy power capture efficiency while ensuring adaptability to different wave conditions.

[0049] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the power optimization control method for direct-drive wave power generation systems of the present invention.

[0050] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the power optimization control method for direct-drive wave power generation system of the present invention. Attached Figure Description

[0051] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0052] Figure 1 A flowchart illustrating an embodiment of a power optimization control method for a direct-drive wave power generation system provided by the present invention;

[0053] Figure 2A flowchart of a linear quadratic Gaussian control system, which is an embodiment of a power optimization control method for a direct-drive wave power generation system provided by the present invention;

[0054] Figure 3 A system control block diagram of a wave energy conversion device, which is an embodiment of a power optimization control method for a direct-drive wave power generation system provided by the present invention;

[0055] Figure 4 A schematic diagram of a direct-drive wave energy converter device, which is an embodiment of a power optimization control method for a direct-drive wave power generation system provided by the present invention.

[0056] Figure 5 This is a module structure diagram of an embodiment of a power optimization control device for a direct-drive wave power generation system provided by the present invention. Detailed Implementation

[0057] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0058] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0059] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0060] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0061] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0062] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0063] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0064] Example 1

[0065] See Figure 1 To address the problem in existing technologies of simultaneously improving wave energy capture efficiency while ensuring adaptability to different wave conditions, an embodiment of the present invention provides a power optimization control method for direct-drive wave power generation systems, comprising:

[0066] S1. Establish an ideal model of the direct-drive wave power generation system based on the direct-drive wave power generation system.

[0067] In some embodiments of this application, the step of establishing an ideal model of the direct-drive wave power generation system based on the direct-drive wave power generation system specifically includes:

[0068] The radiation force data of the direct-drive wave power generation system is obtained, and a system state-space model is established based on the radiation force data using the float force analysis method.

[0069] The radiation force in the state space model of the system is simplified by using finite element analysis software simulation method to obtain the ideal model of the direct-drive wave power generation system.

[0070] Specifically, the hydrodynamic equations for the forces acting on the float and the third-order equivalent state-space model for the radiating forces in the aforementioned float force analysis method are as follows:

[0071] The hydrodynamic equations for the forces acting on the float in the float force analysis method are as follows:

[0072]

[0073] Where m is the mass of the float; m x denoted as ρ, where ρ is the added mass of the float in the infinite frequency domain; α is the acceleration of the float; K is the buoyancy coefficient; z is the displacement of the float; R0 is the coefficient of frictional resistance; v is the velocity of the float; k r (t-τ) is the time delay function of the radiating force; f c The excitation force of the incident wave; f z This is the anti-electromagnetic force of a linear motor.

[0074] The third-order equivalent state-space model of radiation force is shown below:

[0075]

[0076] In the formula, x r A is the third-order state vector corresponding to the radiation force; r B r C r It is the coefficient matrix of the third-order state vector.

[0077] S2. Input the current wave excitation force and the current ideal compensation control quantity of the direct-drive wave power generation system into the ideal model of the direct-drive wave power generation system to obtain the current ideal output state information, and obtain the current ideal state quantity information according to the first preset Kalman filter and the current ideal output state information; wherein, the current ideal compensation control quantity is obtained by solving the ideal state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation.

[0078] In some embodiments of this application, the current ideal compensation control quantity is obtained by solving the optimal gain calculation method and the Riccati equation based on the ideal state quantity information of the previous round of control output, specifically:

[0079] Based on the ideal state quantity information of the previous round of control output and the preset weight matrix, the minimum performance index function is constructed using the optimal gain calculation method;

[0080] The Riccati equation is established based on the quadratic optimal control theory, and the ideal feedback gain matrix is ​​obtained by solving the Riccati equation according to the minimum performance index function.

[0081] Based on the ideal feedback gain matrix and the ideal state quantity information of the previous round of control output, the current ideal compensation control quantity is obtained by using the state feedback calculation formula.

[0082] It should be noted that, as Figure 2 As shown, a Kalman filter is used to solve the optimal control problem of a wave power generation system with noise interference. The system has process noise (such as random wave disturbances and parameter fluctuations) w1 and measurement noise (such as sensor errors). The Kalman filter uses the system output y and input u to make an optimal estimate of the system state. Based on the quadratic performance index, the feedback gain -F is calculated, and the estimated state is fed back to generate the control input u, so that the system can remain stable and achieve optimal power under noise.

[0083] Specifically, the preferred expression for the minimum performance index function is as follows:

[0084]

[0085] In the formula: x=[z,v,x r ] represents the system state vector; u = f z For system input, Q is a fifth-order positive semi-definite diagonal state weight matrix, R is a normal input weight matrix, and N = [0; 0.5; 0; 0; 0] is a matrix that incorporates the captured energy into the performance function.

[0086] Specifically, the preferred expression for the Riccati equation is as follows:

[0087]

[0088] In the formula: S is the solution to the Riccati equation; A and B are the system state-space matrices; F is the feedback gain matrix.

[0089] S3. Input the current wave excitation force, current sliding mode compensation amount, and current actual compensation control amount of the direct-drive wave power generation system into the ideal model of the direct-drive wave power generation system to obtain the current actual output state information, and obtain the current actual state quantity information based on the second preset Kalman filter and the current actual output state information; wherein, the current actual compensation control amount is obtained by solving the state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation, and the current sliding mode compensation amount is obtained based on the ideal state quantity information and the actual state quantity information of the previous round of control output.

[0090] In some embodiments of this application, the current actual compensation control quantity is obtained by solving the optimal gain calculation method and the Riccati equation based on the state quantity information of the previous round of control output, specifically:

[0091] Based on the actual state information of the previous round of control output and the preset weight matrix, the minimum performance index function is constructed using the optimal gain calculation method.

[0092] The Riccati equation is established based on the quadratic optimal control theory, and the Riccati equation is solved according to the minimum performance index function to obtain the actual feedback gain matrix.

[0093] Based on the actual feedback gain matrix and the ideal state quantity information of the previous round of control output, the current actual compensation control quantity is calculated using the state feedback calculation formula.

[0094] In some embodiments of this application, the current sliding mode compensation amount is obtained based on the ideal state information and actual state information of the previous round of control output, specifically:

[0095] Based on the ideal state quantity information and actual state quantity information of the previous round of control output, the displacement error is calculated using the displacement error formula, and the sliding surface is constructed based on the ideal state quantity information and actual state quantity information of the previous round of control output.

[0096] A switching function is constructed based on the sliding surface, and the current sliding compensation amount is obtained by using the sliding compensation value calculation formula based on the switching function, the displacement error, and the preset adjustable parameters.

[0097] It should be noted that, as Figure 3 As shown, to address the mismatch between the ideal and actual models of wave power generation systems (such as parameter perturbations and external disturbances), sliding mode compensation is introduced on the basis of LQG to enhance robustness. Wave excitation force f e Simultaneously applied to both the ideal model and the actual model; the outputs of both (state z / z′, noise v / v′) are respectively processed by Kalman filtering to obtain state estimates. and The estimated deviation generates the sliding mode error e, and the sliding mode compensator generates the compensation control quantity u based on this. * Meanwhile, the ideal / actual model generates the control quantity u through the optimal gain; finally, the control input combines LQG control and sliding mode compensation, enabling the actual system to still track the power optimization performance of the ideal model under model mismatch.

[0098] Specifically, the optimal calculation process for the sliding mode compensation amount is as follows:

[0099] To address the system model mismatch problem, a sliding mode compensator is designed, defining the sliding surface and displacement error, and calculating the sliding mode compensation value. The system stability is proven using the Lyapunov function, and the switching function is smoothed to avoid high-frequency chattering, compensating for the state shift and power loss caused by model mismatch.

[0100] The design process of the sliding mode compensator is as follows: The displacement error e(t) is defined as e(t) = z′ - z (z' is the actual displacement, z is the ideal displacement). The relevant calculation formulas for the sliding mode compensation value are as follows:

[0101]

[0102] In the formula: λ is a positive constant, η and h are adjustable parameters, and the sliding mode compensation value is u. * (k).

[0103] S4. Obtain the current reference electromagnetic force based on the current actual state information, calculate the reference current based on the current reference electromagnetic force, and then perform power optimization control on the direct-drive wave power generation system based on the reference current.

[0104] Specifically, the formula for converting the motor reference current is as follows:

[0105]

[0106] Where τ is the motor pole pitch; p is the number of motor pole pairs; ψ is the permanent magnet flux linkage; F is the feedback gain; and x is the state variable output by the Kalman filter.

[0107] Specifically, to fully explain the above steps, the following scheme will be used as an example:

[0108] like Figure 4 As shown in the diagram, this illustrates the hardware process of converting wave energy into electrical energy and connecting it to the grid. The wave drive mechanism on the right (such as a permanent magnet synchronous linear motor) performs linear motion, converting mechanical energy into electrical energy through the motor. Power electronic devices (including a rectifier bridge, DC bus capacitor, and inverter bridge) achieve the "AC → DC → AC" electrical energy conversion, with the DC capacitor stabilizing the bus voltage. Current loop control adjusts the inverter bridge switch to control the amplitude and phase of the grid-connected current, enabling efficient grid connection of electrical energy while optimizing the power output on the wave generation side.

[0109] In summary, this application embodiment establishes an ideal model of a direct-drive wave power generation system, providing a precise system characteristic mapping basis for the implementation of subsequent control strategies, thus avoiding deviations in control direction due to excessive discrepancies between the model and the actual system. The current wave excitation force and the ideal compensation control quantity, calculated using the optimal gain method and the Riccati equation based on the previous round of ideal state quantities, are input into the model. The output state information is then processed using a first preset Kalman filter. This not only ensures that the control under the ideal state conforms to the optimal theoretical framework, reducing deviations at the ideal control level, but also improves the accuracy of the ideal state quantity information through filtering, providing a reliable optimal reference for subsequent actual control. Meanwhile, in the actual control path, a sliding mode compensation quantity obtained by combining the ideal and actual state quantities from the previous round is introduced. This is paired with the actual compensation control quantity, which is also solved using the optimal method, and input into the model. Then, the actual output state is processed by a second preset Kalman filter. This effectively corrects the deviation between the ideal and actual systems, enhances the system's resistance to disturbances such as model mismatch and wave condition changes, and improves the accuracy of the actual state quantity information. Finally, a reference electromagnetic force is obtained based on the actual state quantities and converted into a reference current to achieve control. This allows the optimized strategy to be accurately implemented, ensuring that the system can stably approach the maximum power capture target even under complex sea conditions. Therefore, this application can solve the problem in the prior art of improving wave energy power capture efficiency while ensuring adaptability to different wave conditions.

[0110] Example 2

[0111] like Figure 5 As shown, based on the above method embodiments, corresponding device embodiments are provided;

[0112] An embodiment of the present invention provides a power optimization control device for a direct-drive wave power generation system, comprising: a model building module 51, a first processing module 52, a second processing module 53, and a power optimization control module 54;

[0113] Model building module 51 is used to build an ideal model of the direct-drive wave power generation system based on the direct-drive wave power generation system.

[0114] The first processing module 52 is used to input the current wave excitation force and the current ideal compensation control quantity of the direct-drive wave power generation system into the ideal model of the direct-drive wave power generation system to obtain the current ideal output state information, and to obtain the current ideal state quantity information according to the first preset Kalman filter and the current ideal output state information; wherein, the current ideal compensation control quantity is obtained by solving the ideal state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation;

[0115] The second processing module 53 is used to input the current wave excitation force, current sliding mode compensation amount, and current actual compensation control amount of the direct-drive wave power generation system into the ideal model of the direct-drive wave power generation system to obtain the current actual output state information, and to obtain the current actual state quantity information based on the second preset Kalman filter and the current actual output state information; wherein, the current actual compensation control amount is obtained by solving the state quantity information of the previous round of control output using the optimal gain calculation method and the Riccati equation, and the current sliding mode compensation amount is obtained based on the ideal state quantity information and the actual state quantity information of the previous round of control output;

[0116] The power optimization control module 54 is used to obtain the current reference electromagnetic force based on the current actual state information, calculate the reference current based on the current reference electromagnetic force, and then perform power optimization control on the direct-drive wave power generation system based on the reference current.

[0117] In some embodiments of this application, the model building module includes a first model building unit and a second model building unit;

[0118] The first model building unit is used to acquire the radiation force data of the direct-drive wave power generation system, and to establish a system state space model based on the radiation force data using the float force analysis method.

[0119] The second model building unit is used to perform equivalent simplification of the radiation force in the system state space model using finite element analysis software simulation methods to obtain the ideal model of the direct-drive wave power generation system.

[0120] In some embodiments of this application, the first processing module includes a first processing unit, a second processing unit, and a third processing unit;

[0121] The first processing unit is used to construct a minimum performance index function based on the ideal state quantity information of the previous round of control output and the preset weight matrix, using the optimal gain calculation method.

[0122] The second processing unit is used to establish the Riccati equation based on the quadratic optimal control theory, and solve the Riccati equation based on the minimum performance index function to obtain the ideal feedback gain matrix;

[0123] The third processing unit is used to calculate the current ideal compensation control quantity based on the ideal feedback gain matrix and the ideal state quantity information of the previous round of control output using the state feedback calculation formula.

[0124] In some embodiments of this application, the second processing module includes a fourth processing unit, a fifth processing unit, and a sixth processing unit;

[0125] The fourth processing unit is used to construct a minimum performance index function based on the actual state quantity information of the previous round of control output and the preset weight matrix, using the optimal gain calculation method.

[0126] The fifth processing unit is used to establish the Riccati equation based on the quadratic optimal control theory, and solve the Riccati equation based on the minimum performance index function to obtain the actual feedback gain matrix.

[0127] The sixth processing unit is used to calculate the current actual compensation control quantity based on the actual feedback gain matrix and the ideal state quantity information of the previous round of control output using the state feedback calculation formula.

[0128] In some embodiments of this application, the second processing module includes a seventh processing unit and an eighth processing unit;

[0129] The seventh processing unit is used to calculate the displacement error using the displacement error formula based on the ideal state quantity information and actual state quantity information output from the previous round of control, and to construct the sliding surface based on the ideal state quantity information and actual state quantity information output from the previous round of control.

[0130] The eighth processing unit is used to construct a switching function based on the sliding surface, and to calculate the current sliding compensation amount using the sliding compensation value calculation formula based on the switching function, the displacement error, and the preset adjustable parameters.

[0131] For more detailed steps and working principles of this embodiment, please refer to the relevant description in Embodiment 1, but not limited to these descriptions.

[0132] In summary, this application embodiment establishes an ideal model of a direct-drive wave power generation system, providing a precise system characteristic mapping basis for the implementation of subsequent control strategies, thus avoiding deviations in control direction due to excessive discrepancies between the model and the actual system. The current wave excitation force and the ideal compensation control quantity, calculated using the optimal gain method and the Riccati equation based on the previous round of ideal state quantities, are input into the model. The output state information is then processed using a first preset Kalman filter. This not only ensures that the control under the ideal state conforms to the optimal theoretical framework, reducing deviations at the ideal control level, but also improves the accuracy of the ideal state quantity information through filtering, providing a reliable optimal reference for subsequent actual control. Meanwhile, in the actual control path, a sliding mode compensation quantity obtained by combining the ideal and actual state quantities from the previous round is introduced. This is paired with the actual compensation control quantity, which is also solved using the optimal method, and input into the model. Then, the actual output state is processed by a second preset Kalman filter. This effectively corrects the deviation between the ideal and actual systems, enhances the system's resistance to disturbances such as model mismatch and wave condition changes, and improves the accuracy of the actual state quantity information. Finally, a reference electromagnetic force is obtained based on the actual state quantities and converted into a reference current to achieve control. This allows the optimized strategy to be accurately implemented, ensuring that the system can stably approach the maximum power capture target even under complex sea conditions. Therefore, this application can solve the problem in the prior art of improving wave energy power capture efficiency while ensuring adaptability to different wave conditions.

[0133] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can implement the power optimization control method for direct-drive wave power generation systems provided by any of the above-described method embodiments of the present invention.

[0134] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0135] Example 3

[0136] Based on the above embodiments of the power optimization control method for direct-drive wave power generation systems, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the power optimization control method for direct-drive wave power generation systems according to any embodiment of the present invention.

[0137] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0138] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0139] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0140] Example 4

[0141] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the power optimization control method for direct-drive wave power generation systems described in any of the above-described method embodiments of the present invention.

[0142] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0143] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A power optimization control method for a direct drive wave power system, characterized by, The application relates to a power optimization control method for a direct-drive wave power generation system. An ideal model of the direct-drive wave power generation system is established according to the direct-drive wave power generation system; current wave excitation force and current ideal compensation control amount of the direct-drive wave power generation system are input into the ideal model of the direct-drive wave power generation system to obtain current ideal output state information, and current ideal state amount information is obtained according to a first preset Kalman filter and the current ideal output state information; the current ideal compensation control amount is obtained by solving an optimal gain calculation method and a Riccati equation according to ideal state amount information output by a previous round of control; current wave excitation force, current sliding mode compensation amount and current actual compensation control amount of the direct-drive wave power generation system are input into the ideal model of the direct-drive wave power generation system to obtain current actual output state information, and current actual state amount information is obtained according to a second preset Kalman filter and the current actual output state information; the current actual compensation control amount is obtained by solving an optimal gain calculation method and a Riccati equation according to state amount information output by a previous round of control, and the current sliding mode compensation amount is obtained according to ideal state amount information and actual state amount information output by a previous round of control; current reference electromagnetic force is obtained according to the current actual state amount information, reference current is calculated according to the current reference electromagnetic force, and power optimization control is performed on the direct-drive wave power generation system according to the reference current.

2. A power optimization control method for direct drive wave power system as claimed in claim 1, wherein, The ideal model of the direct-drive wave power generation system is established according to the direct-drive wave power generation system, and specifically comprises the following steps: radiation force data of the direct-drive wave power generation system are obtained, and a system state space model is established by using a floater force analysis method according to the radiation force data; the radiation force in the system state space model is subjected to equivalent simplification processing by using a finite element analysis software simulation method, and the ideal model of the direct-drive wave power generation system is obtained.

3. The power optimization control method for direct drive wave power system of claim 1, wherein, The current ideal compensation control amount is obtained by solving an optimal gain calculation method and a Riccati equation according to ideal state amount information output by a previous round of control, and specifically comprises the following steps: a minimum performance index function is constructed by using an optimal gain calculation method according to ideal state amount information output by a previous round of control and a preset weight matrix; a Riccati equation is established according to a quadratic optimal control theory, and the Riccati equation is solved according to the minimum performance index function to obtain an ideal feedback gain matrix; the current ideal compensation control amount is calculated by using a state feedback calculation formula according to the ideal feedback gain matrix and the ideal state amount information output by the previous round of control.

4. The power optimization control method for direct drive wave power system of claim 1, wherein, The current actual compensation control amount is obtained by solving an optimal gain calculation method and a Riccati equation according to state amount information output by a previous round of control, and specifically comprises the following steps: a minimum performance index function is constructed by using an optimal gain calculation method according to actual state amount information output by a previous round of control and a preset weight matrix; According to a quadratic optimal control theory, a Riccati equation is established, and the Riccati equation is solved according to the minimum performance index function to obtain an actual feedback gain matrix; According to the actual feedback gain matrix and ideal state quantity information of a previous control output, a state feedback calculation formula is used to calculate to obtain a current actual compensation control quantity.

5. A power optimization control method for direct drive wave power system as claimed in claim 1, wherein, The current sliding mode compensation quantity is obtained according to ideal state quantity information and actual state quantity information of a previous control output, and specifically: According to the ideal state quantity information and the actual state quantity information of the previous control output, a displacement error formula is used to calculate to obtain a displacement error, and a sliding mode surface is constructed according to the ideal state quantity information and the actual state quantity information of the previous control output. According to the sliding mode surface, a switching function is constructed, and a sliding mode compensation value calculation formula is used to calculate to obtain the current sliding mode compensation quantity according to the switching function, the displacement error and a preset adjustable parameter.

6. A power optimization control device for a direct drive wave power system, characterized by It comprises: a model establishing module, a first processing module, a second processing module and a power optimization control module; The model establishing module is configured to establish an ideal model of the direct-drive wave power system according to the direct-drive wave power system. The first processing module is configured to input a current wave excitation force of the direct-drive wave power system and a current ideal compensation control quantity into the ideal model of the direct-drive wave power system to obtain current ideal output state information, and obtain current ideal state quantity information according to a first preset Kalman filter and the current ideal output state information; wherein the current ideal compensation control quantity is obtained by solving the Riccati equation and the optimal gain calculation method according to ideal state quantity information of a previous control output. The second processing module is configured to input the current wave excitation force of the direct-drive wave power system, a current sliding mode compensation quantity and a current actual compensation control quantity into the ideal model of the direct-drive wave power system to obtain current actual output state information, and obtain current actual state quantity information according to a second preset Kalman filter and the current actual output state information; wherein the current actual compensation control quantity is obtained by solving the Riccati equation and the optimal gain calculation method according to state quantity information of a previous control output, and the current sliding mode compensation quantity is obtained according to ideal state quantity information and actual state quantity information of a previous control output. The power optimization control module is configured to obtain a current reference electromagnetic force according to the current actual state quantity information, calculate a reference current according to the current reference electromagnetic force, and then perform power optimization control on the direct-drive wave power system according to the reference current.

7. A power optimization control device for direct drive wave power system as claimed in claim 6, wherein, The model establishing module comprises a first model establishing unit and a second model establishing unit. The first model establishing unit is configured to obtain radiation force data of the direct-drive wave power system, and establish a system state space model by using a floater force analysis method according to the radiation force data. The second model establishing unit is configured to perform equivalent simplification on the radiation force in the system state space model by using a finite element analysis software simulation method, and obtain the direct-drive wave power system ideal model.

8. A power optimization control device for direct drive wave power system as claimed in claim 6, wherein, The first processing module comprises a first processing unit, a second processing unit and a third processing unit. The first processing unit is configured to construct a minimum performance index function by using an optimal gain calculation method according to ideal state quantity information output by a previous round of control and a preset weight matrix. The second processing unit is configured to establish a Riccati equation according to a quadratic optimal control theory, and solve the Riccati equation according to the minimum performance index function to obtain an ideal feedback gain matrix. The third processing unit is configured to calculate a current ideal compensation control quantity by using a state feedback calculation formula according to the ideal feedback gain matrix and the ideal state quantity information output by the previous round of control.

9. A power optimization control device for direct drive wave power system as claimed in claim 6, wherein, The second processing module comprises a fourth processing unit, a fifth processing unit and a sixth processing unit. The fourth processing unit is configured to construct a minimum performance index function by using an optimal gain calculation method according to actual state quantity information output by a previous round of control and a preset weight matrix. The fifth processing unit is configured to establish a Riccati equation according to a quadratic optimal control theory, and solve the Riccati equation according to the minimum performance index function to obtain an actual feedback gain matrix. The sixth processing unit is configured to calculate a current actual compensation control quantity by using a state feedback calculation formula according to the actual feedback gain matrix and the ideal state quantity information output by the previous round of control.

10. A power optimization control device for direct drive wave power system as claimed in claim 6, wherein, The second processing module comprises a seventh processing unit and an eighth processing unit. The seventh processing unit is configured to calculate a displacement error by using a displacement error formula according to ideal state quantity information and actual state quantity information output by a previous round of control, and construct a sliding mode surface according to the ideal state quantity information and the actual state quantity information output by the previous round of control. The eighth processing unit is configured to construct a switching function according to the sliding mode surface, and calculate a current sliding mode compensation quantity by using a sliding mode compensation value calculation formula according to the switching function, the displacement error and a preset adjustable parameter.

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