A power optimization method and system for suppressing the load of wind turbine transmission system

Abstract

The present invention discloses a power optimization method and system for suppressing the load on a wind turbine transmission system. The method comprises: S1, obtaining the operating parameters of each wind turbine and establishing a wind turbine state-space equation; S2, using a power demand command as a boundary condition, upper and lower limits of the wind turbine active power output, and the angular velocity and torsional torque of the transmission system as constraints, and minimizing the variation of the transmission system angular acceleration and torsional torque as the objective function, to solve the active power reference value for each wind turbine based on the wind turbine state-space equation; S3, measuring the fatigue level of the transmission system based on historical operating data of each wind turbine, calculating a corresponding weight based on the fatigue level, and then correcting the active power reference value based on the weight to obtain the final active power command. The present invention can effectively suppress torsional vibration, improve fatigue damage to the transmission system, and enhance the safety and stability of wind turbine grid-connected operation.

Description

Technical Field

[0001] The present invention mainly relates to the technical field of wind power generation, and in particular to a power optimization method and system for suppressing the load of a wind turbine transmission system. Background Art

[0002] With the growing global demand for clean energy, wind power generation, as a key renewable energy source, is rapidly expanding. However, the safety and stability of wind turbine grid-connected operations face increasingly severe challenges. As a key component in electromechanical energy conversion, the performance of wind turbine transmission systems directly impacts the efficiency and reliability of wind turbine operations. In harsh natural environments and under time-varying operating conditions, transmission systems are subjected to the simultaneous impact of mechanical and electromagnetic torque disturbances. This can not only cause fatigue damage to the transmission system but can also lead to failures, compromising the safety and stability of wind turbine grid-connected operations.

[0003] The industry has already implemented several measures to address fatigue damage in wind turbine transmission systems. For example, some wind turbines employ complex transmission chain structures, utilizing multi-stage gearing to improve transmission efficiency and load-bearing capacity. Furthermore, some technologies attempt to improve system reliability and fatigue resistance by optimizing the transmission system's structural design, such as employing short main shafts and compact designs. Furthermore, some research is also developing rigid-flexible coupled dynamic models of the main transmission system to analyze load transfer characteristics in the hope of finding a basis for optimal design.

[0004] Although existing technical solutions have improved the performance of wind turbine transmission systems to a certain extent, some shortcomings still exist. First, although the complex transmission chain structure can improve transmission efficiency, it also increases the complexity of the system and the risk of failure, especially in harsh operating environments. Second, existing optimization design methods are mostly based on static analysis, which makes it difficult to fully consider torque disturbances and fatigue damage during dynamic operation. In addition, most existing technical solutions focus on the structural optimization of the transmission system, while there is insufficient research on torsional vibration suppression strategies under the interaction characteristics of the machine and the grid, which cannot fundamentally solve the stability problem of the transmission system during grid-connected operation. Summary of the Invention

[0005] In response to the technical problems existing in the prior art, the present invention provides a power optimization method and system for suppressing the load of the wind turbine transmission system, which effectively suppresses torsional vibration, improves fatigue damage of the transmission system, and thus improves the safety and stability of the wind turbine grid-connected operation.

[0006] In order to solve the above technical problems, the technical solution proposed by the present invention is:

[0007] A power optimization method for suppressing the load of a wind turbine transmission system comprises the following steps:

[0008] S1. Obtain the operating parameters of each wind turbine and establish the state space equation of the wind turbine;

[0009] S2. Using the power demand command from the dispatch center as the boundary condition, the upper and lower limits of the wind turbine active power output, the angular velocity and torsional torque of the transmission system as the constraint conditions, and minimizing the changes in the angular acceleration and torsional torque of the transmission system as the objective function, the active power reference value of each wind turbine is solved based on the wind turbine state space equation;

[0010] S3. Measure the fatigue degree of the transmission system based on the historical operating data of each wind turbine, calculate the corresponding weight based on the fatigue degree of the transmission system, and then correct the active power reference value based on the weight, and send it to each wind turbine as the final active power instruction.

[0011] Preferably, in step S1, the state space equation of the wind turbine generator set includes the dynamic equation of the wind turbine generator set transmission system and the power-torque state space equation of the wind turbine generator set; the process of establishing the dynamic equation of the wind turbine generator set transmission system is:

[0012] The generator is modeled as a mass block related to the mechanical inertia of the generator rotor, namely the flexible blade mass block, the rigid blade-hub mass block and the generator mass block; the flexible blade mass block concentrates the inertia of the flexible part of the blade; the rigid blade-hub mass block concentrates the inertia of the rigid part of the blade and the hub; the generator mass block concentrates the inertia of the generator; the stiffness and damping of the effective blade connect the flexible blade mass block and the rigid blade-hub mass block, and the total stiffness and damping of the low-speed shaft and the high-speed shaft connect the rigid blade-hub mass block and the generator mass block; the dynamic equation of the wind turbine transmission system established based on the three mass blocks is:

[0013]

[0014] in, , , are the inertias of the flexible blade mass, the rigid blade-hub mass, and the generator mass, respectively; , , is the angular velocity of the flexible blade mass, the rigid blade-hub mass, and the generator mass; , , is the torsion angle of the flexible blade mass, the rigid blade-hub mass and the generator mass; is the aerodynamic torque; is the generator torque; is the effective blade stiffness; is the effective blade damping; is the total stiffness of the low-speed shaft; is the total damping of the low and high speed shaft; is the gearbox transmission ratio; is the torsional torque on the flexible part of the blade; is the torsional torque on the low-speed shaft.

[0015] Preferably, in step S1, the power-torque state space equation of the wind turbine is:

[0016] ;

[0017] , , ;

[0018] ; ;

[0019] ; ; ;

[0020] ; ;

[0021] in, For the prediction, is the state quantity, is the input quantity, is the output, All are matrices; is the change in the pitch angle reference value, is the change in pitch angle, is the change in generator speed, is the change in generator filter speed, is the change in active power reference value, are the angular acceleration changes of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block, is the variation of the torsional torque on the flexible part of the blade, is the change in torsional torque on the low-speed shaft; , are all constants, is the equivalent mass of the blade and generator, is the active power output at the current moment, is the generator efficiency, is the aerodynamic torque at the current moment, is the generator torque at the current moment, Both are variables related to the torsion angle and angular velocity increment.

[0022] Preferably, in step S2, the angular acceleration of the transmission system is the angular acceleration of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block; the torsional torque change is the torsional torque change on the flexible part of the blade and the torsional torque change on the low-speed shaft respectively.

[0023] Preferably, in step S2, the objective function is expressed as:

[0024] ;

[0025] in, is the total number of sampling steps within the prediction time range, is the sampling time, is the total number of wind turbines, Number the wind turbine. is the weight, Respectively Typhoon turbines in the The per-unit value of the angular acceleration change of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block at the sampling moment, For the Typhoon turbines in the The per-unit value of the torsional torque variation on the flexible part of the blade at the sampling moment, For the Typhoon turbines in the The per-unit value of the torsional torque change on the low-speed shaft at the sampling moment.

[0026] Preferably, in step S2, the constraint condition is expressed as:

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] The underline indicates the lower limit, and the overline indicates the upper limit. For the The active power output of the typhoon turbine generator set, is the power demand instruction of the dispatching center, For the Active power reference value of typhoon generator set, For the The maximum power that can be generated by the typhoon turbine generator set, For the The corresponding angular velocity of the typhoon turbine, For the The corresponding torque of the typhoon turbine.

[0032] Preferably, in step S3, the historical operation data of the wind turbine generator system includes the variation of the torsional torque on the flexible portion of the blade and the variation of the torsional torque on the low-speed shaft.

[0033] Preferably, in step S3, the fatigue level The expression is:

[0034]

[0035] in, For the Fatigue level of typhoon turbines; For the The change in torsional torque on the flexible part of the blade at the sampling moment, For the The change in torsional torque on the low-speed shaft at the sampling moment.

[0036] Preferably, the weight The expression is:

[0037] .

[0038] The present invention also discloses a power optimization system for suppressing the load of a wind turbine transmission system, comprising a memory and a processor connected to each other, wherein the memory stores a computer program, and when the computer program is run by the processor, the steps of the above method are executed.

[0039] Compared with the prior art, the advantages of the present invention are:

[0040] The present invention establishes a correlation model between the torque and power output of the wind turbine transmission system and integrates a detailed wind turbine model into the active power optimization scheduling problem to describe the real dynamic response and achieve better dynamic performance; proposes a two-layer active power optimization scheduling method based on model predictive control to reduce the transmission system load of the wind turbine and improve the power flow of the wind farm; establishes a two-layer dynamic control framework for the wind farm, in which the lower-layer wind turbine controller measures the accumulated fatigue damage of the transmission system in real time, and the upper-layer wind farm controller corrects the issued power reference instructions according to the health status of each wind turbine to achieve a more balanced fatigue load distribution. In summary, the present invention can effectively suppress torsional vibration under the machine-grid interaction characteristics, improve the fatigue damage of the transmission system, and thus improve the safety and stability of the wind turbine grid-connected operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1The flowchart is a specific application of the power optimization method for suppressing the load of the wind turbine transmission system of the present invention.

[0042] Figure 2 Schematic diagram of the structure of the three-mass model of the transmission system in an embodiment of the present invention.

[0043] Figure 3 This is a simulation diagram of the torsional torque of the low-speed transmission shaft under different scheduling modes in an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0045] like Figure 1 As shown, the power optimization method for suppressing the load of the wind turbine transmission system provided by the embodiment of the present invention establishes a two-layer dynamic control framework, wherein the two-layer dynamic control framework adopts a centralized control algorithm. The corresponding control framework is divided into two layers, the upper layer controller is the wind farm controller, and the lower layer controller is the local controller of each wind turbine. During the operation of the wind farm, the upper layer controller collects feedback information from the lower layer controller and issues control instructions to the lower layer controller based on the calculation results of the model predictive control algorithm. The specific steps are as follows:

[0046] S1. The upper controller establishes the wind turbine state space equation for model predictive control calculation based on the operating parameters of each wind turbine fed back by the lower controller; the operating parameters include pitch angle, generator speed, active power reference value, aerodynamic torque and generator torque;

[0047] S2. The upper-level controller receives the power demand command from the dispatch center as a boundary condition. The upper-level controller uses the upper and lower limits of the wind turbine active power output, the angular velocity and torsional torque of the transmission system as constraints. The upper-level controller uses the minimization of the change in the angular acceleration and torsional torque of the transmission system as the objective function, and solves the active power reference value of each wind turbine based on the wind turbine state space equation and the model predictive control algorithm.

[0048] S3. The lower-level controller measures the fatigue level of the transmission system locally based on the historical operating data of each wind turbine and feeds it back to the upper-level controller. The upper-level controller calculates the corresponding weight based on the fatigue level of each transmission system and modifies the active power reference value based on the weight. The result is sent to the lower-level controller as the final active power instruction to control each wind turbine.

[0049] In step S1, the state space equation of the wind turbine generator set includes the dynamic equation of the wind turbine generator set transmission system and the power-torque state space equation of the wind turbine generator set;

[0050] like Figure 2As shown in Figure 1, a three-mass model is used to describe the wind turbine drive system. This model describes the drive system as a torsional system with discrete masses, and the in-plane dynamics of the blades are also described as a torsional system. The model inputs are the aerodynamic torque and the generator torque, and the outputs are the angular acceleration of each mass and the torque between them. Because blade bending occurs far from the connection between the blade and the hub, the blades are modeled as flexible and rigid parts respectively. The gearbox is simplified to an ideal gearbox, and only the transmission ratio is considered.

[0051] In order to describe the impact of the mechanical disturbance of the generator on the transmission system, the generator is modeled as a mass block related to the mechanical inertia of the generator rotor, namely the flexible blade mass block, the rigid blade-hub mass block, and the generator mass block. The flexible blade mass block concentrates the inertia of the flexible part of the blade; the rigid blade-hub mass block concentrates the inertia of the rigid part of the blade and the hub; and the generator mass block concentrates the inertia of the generator. The stiffness and damping of the effective blade are connected to the blade mass block and the rigid blade-hub mass block, and the total stiffness and damping of the low-speed shaft and high-speed shaft are connected to the rigid blade-hub mass block and the generator mass block. The dynamic equation of the wind turbine transmission system established based on the three-mass model is:

[0052]

[0053] in, , , are the inertias of the flexible blade mass, the rigid blade-hub mass, and the generator mass, respectively; , , is the angular velocity of the flexible blade mass, the rigid blade-hub mass, and the generator mass; , , is the torsion angle of the flexible blade mass, the rigid blade-hub mass and the generator mass; is the aerodynamic torque; is the generator torque; is the effective blade stiffness; is the effective blade damping; is the total stiffness of the low-speed shaft; is the total damping of the low and high speed shaft; is the gearbox transmission ratio; is the torsional torque on the flexible part of the blade; is the torsional torque on the low-speed shaft.

[0054] In addition, a power-torque model of the wind turbine is established based on the coupling relationship between the torque and power output of the wind turbine. The model is affected by the pitch angle, generator speed, active power reference value, aerodynamic torque and generator torque. The model is expressed by the state space equation:

[0055]

[0056] , , ;

[0057] ; ; ;

[0058] ; ; ; .

[0059] in, For the prediction, is the state quantity, is the input quantity, is the output, All are matrices; is the change in the pitch angle reference value, is the change in pitch angle, is the change in generator speed, is the change in generator filter speed, is the change in active power reference value, are the angular acceleration changes of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block, is the variation of the torsional torque on the flexible part of the blade, is the change in torsional torque on the low-speed shaft; , are all constants, is the equivalent mass of the blade and generator, is the active power output at the current moment, is the generator efficiency, is the aerodynamic torque at the current moment, is the generator torque at the current moment, Both are variables related to the torsion angle and angular velocity increment.

[0060] In step S2, to reduce the load on the drivetrain and improve the health of the wind turbine, the objective function of the model predictive control is set to minimize the angular acceleration and torsional torque fluctuations in the three-mass model. The angular acceleration refers to the angular acceleration of the flexible blade mass, the rigid blade-hub mass, and the generator mass. The torsional torque (abbreviated as torque) refers to the torsional torque on the flexible portion of the blade and the torsional torque on the low-speed shaft.

[0061] The specific expression of the objective function in model predictive control is as follows:

[0062] ;

[0063] in, is the total number of sampling steps within the prediction time range, is the sampling time, is the total number of wind turbines, Number the wind turbine. is the weight, Respectively Typhoon turbines in the The per-unit value of the angular acceleration change of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block at the sampling moment, For the Typhoon turbines in the The per-unit value of the torsional torque variation on the flexible part of the blade at the sampling moment, For the Typhoon turbines in the The per-unit value of the torsional torque change on the low-speed shaft at the sampling moment.

[0064] To maintain stable wind farm operation, the total active power output of all wind turbines must be equal to the power demand command from the dispatch center, and the active power output of each wind turbine must not exceed its maximum power capacity. To ensure the reliability of the transmission system, its internal angular velocity and torque must remain within a safe range. The specific expressions of the constraints in model predictive control are as follows:

[0065]

[0066]

[0067]

[0068]

[0069] The underline indicates the lower limit, and the overline indicates the upper limit. For the The active power output of the typhoon turbine generator set, is the power demand instruction of the dispatching center, For the Active power reference value of typhoon generator set, For the The maximum power that can be generated by the typhoon turbine generator set, For the The corresponding angular velocity of the typhoon turbine, For the The corresponding torque of the typhoon turbine.

[0070] In step S3, the lower-level wind turbine controller measures the cumulative fatigue of the transmission system in real time, and the upper-level wind farm controller modifies the issued power reference command according to the health status of each wind turbine to achieve a more balanced fatigue load distribution. Specifically, an optimization weight algorithm that considers the historical operating data of the transmission system is proposed, which calculates the corresponding weight based on the past torsional torque fluctuations. The algorithm improves the fatigue load distribution of the wind turbine transmission system by optimizing the power flow in the wind farm. The local controller of each wind turbine in the lower layer locally measures the fatigue of the transmission system based on the cumulative increment of the torsional torque in the three-mass model:

[0071]

[0072] in, For the Fatigue level of typhoon turbines; For the The change in torsional torque on the flexible part of the blade at the sampling moment, For the The change in torsional torque on the low-speed shaft at the sampling moment.

[0073] At the upper level, the wind farm controller calculates the corresponding optimization weight in real time according to the fatigue level of the transmission system of each wind turbine. :

[0074]

[0075] The larger the optimization weight of a wind turbine, the more severe the fatigue of its transmission system. During the optimization process of the wind farm controller, the load of the fatigued wind turbine will be appropriately reduced to improve the health of the wind turbine.

[0076] The double-layer dynamic control framework of the present invention comprehensively considers the power generation of the wind farm and the health status of the wind turbines. The simulation results compared with the traditional proportional distribution control method are as follows: Figure 3 As shown, from Figure 3 It can be seen from the figures that the method proposed in the present invention can effectively suppress the torque fluctuation of the wind turbine, reduce the fatigue of the transmission system, and improve the power flow of the system.

[0077] The present invention establishes a correlation model between the torque and power output of the wind turbine transmission system and integrates a detailed wind turbine model into the active power optimization scheduling problem to describe the real dynamic response and achieve better dynamic performance; proposes a two-layer active power optimization scheduling method based on model predictive control to reduce the transmission system load of the wind turbine and improve the power flow of the wind farm; establishes a two-layer dynamic control framework for the wind farm, in which the lower-layer wind turbine controller measures the accumulated fatigue damage of the transmission system in real time, and the upper-layer wind farm controller corrects the issued power reference instructions according to the health status of each wind turbine to achieve a more balanced fatigue load distribution. In summary, the present invention can effectively suppress torsional vibration under the machine-grid interaction characteristics, improve the fatigue damage of the transmission system, and thus improve the safety and stability of the wind turbine grid-connected operation.

[0078] The present invention also discloses a power optimization system for suppressing load on a wind turbine transmission system, comprising a memory and a processor connected to each other. The memory stores a computer program that, when executed by the processor, performs the steps of the above-described method. The optimization system of the present invention corresponds to the above-described optimization method and shares the same advantages as the above-described optimization method.

[0079] The present invention can implement all or part of the process steps in the above-described method embodiments through hardware associated with computer program instructions. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of the above-described method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. Computer-readable storage media include any entity or device capable of carrying computer program code, recording media, USB flash drives, removable 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. Memory is used to store computer programs and / or modules. The processor implements various functions by running or executing the computer programs and / or modules stored in the memory and accessing data stored in the memory. The memory may include a high-speed random access memory and may also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one disk storage device, a flash memory device, or other volatile solid-state storage device.

[0080] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A power optimization method for suppressing the load of a wind turbine transmission system, characterized in that: Including steps: S1. Obtain the operating parameters of each wind turbine and establish the state space equation of the wind turbine; S2. Using the power demand command from the dispatch center as the boundary condition, the upper and lower limits of the wind turbine active power output, the angular velocity and torsional torque of the transmission system as the constraint conditions, and minimizing the changes in the angular acceleration and torsional torque of the transmission system as the objective function, the active power reference value of each wind turbine is solved based on the wind turbine state space equation; S3. Measure the fatigue level of the transmission system based on the historical operating data of each wind turbine, calculate the corresponding weight based on the fatigue level of the transmission system, and then modify the active power reference value based on the weight. The active power command is sent to each wind turbine as the final active power instruction. In step S3, the historical operation data of the wind turbine generator system includes the change amount of the torsional torque on the flexible part of the blade and the change amount of the torsional torque on the low-speed shaft; In step S3, the fatigue level The expression is: in, is the total number of sampling steps within the prediction time range; For the Fatigue level of typhoon turbines; For the The change in torsional torque on the flexible part of the blade at the sampling moment, For the The change in torsional torque on the low-speed shaft at the sampling moment.

2. The power optimization method for suppressing the load of the wind turbine transmission system according to claim 1, characterized in that: In step S1, the state space equation of the wind turbine generator set includes the dynamic equation of the wind turbine generator set transmission system and the power-torque state space equation of the wind turbine generator set; the process of establishing the dynamic equation of the wind turbine generator set transmission system is as follows: The generator is modeled as a mass block related to the mechanical inertia of the generator rotor, which are the flexible blade mass block, the rigid blade-hub mass block and the generator mass block; The flexible blade mass concentrates the inertia of the flexible part of the blade; The rigid blade-hub mass concentrates the inertia of the blade rigid part and the hub; the generator mass concentrates the inertia of the generator; The stiffness and damping of the effective blade are connected to the flexible blade mass block and the rigid blade-hub mass block, and the total stiffness and damping of the low-speed shaft and high-speed shaft are connected to the rigid blade-hub mass block and the generator mass block. The dynamic equation of the wind turbine transmission system based on the three mass blocks is: in, , , are the inertias of the flexible blade mass, the rigid blade-hub mass, and the generator mass, respectively; , , is the angular velocity of the flexible blade mass, the rigid blade-hub mass, and the generator mass; , , is the torsion angle of the flexible blade mass, the rigid blade-hub mass and the generator mass; is the aerodynamic torque; is the generator torque; is the effective blade stiffness; is the effective blade damping; is the total stiffness of the low-speed shaft; is the total damping of the low and high speed shaft; is the gearbox transmission ratio; is the torsional torque on the flexible part of the blade; is the torsional torque on the low-speed shaft.

3. The power optimization method for suppressing the load of the wind turbine transmission system according to claim 2, characterized in that: In step S1, the power-torque state space equation of the wind turbine is: ； , , ； ； ； ； ； ； ； ； in, For the prediction, is the state quantity, is the input quantity, is the output, All are matrices; is the change in the pitch angle reference value, is the change in pitch angle, is the change in generator speed, is the change in generator filter speed, is the change in active power reference value, are the angular acceleration changes of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block, is the variation of the torsional torque on the flexible part of the blade, is the change in torsional torque on the low-speed shaft; , are all constants, is the equivalent mass of the blade and generator, is the active power output at the current moment, is the generator efficiency, is the aerodynamic torque at the current moment, is the generator torque at the current moment, Both are variables related to the torsion angle and angular velocity increment.

4. The power optimization method for suppressing the load of the wind turbine transmission system according to claim 3, characterized in that: In step S2, the angular acceleration of the transmission system is the angular acceleration of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block; the torsional torque changes are the torsional torque changes on the flexible part of the blade and the torsional torque changes on the low-speed shaft respectively.

5. The power optimization method for suppressing the load of a wind turbine transmission system according to any one of claims 1 to 4, characterized in that: In step S2, the objective function is expressed as: ； in, is the total number of sampling steps within the prediction time range, is the sampling time, is the total number of wind turbines, Number the wind turbine. is the weight, Respectively Typhoon turbines in the The per-unit value of the angular acceleration change of the flexible blade mass block, the rigid blade-hub mass block and the generator mass block at the sampling moment, For the Typhoon turbines in the The per-unit value of the torsional torque variation on the flexible part of the blade at the sampling moment, For the Typhoon turbines in the The per-unit value of the torsional torque change on the low-speed shaft at the sampling moment.

6. The power optimization method for suppressing the load of a wind turbine transmission system according to any one of claims 1 to 4, characterized in that: In step S2, the constraint condition is expressed as: ； ； ； ； The underline indicates the lower limit, and the overline indicates the upper limit. is the total number of wind turbines; For the The active power output of the typhoon turbine generator set, is the power demand instruction of the dispatching center, For the Active power reference value of typhoon generator set, For the The maximum power that can be generated by the typhoon turbine generator set, For the The corresponding angular velocity of the typhoon turbine, For the The corresponding torque of the typhoon turbine.

7. The power optimization method for suppressing the load of a wind turbine transmission system according to claim 1, characterized in that: Weight The expression is: ； in is the total number of wind turbines.

8. A power optimization system for suppressing the load of a wind turbine transmission system, comprising a memory and a processor connected to each other, wherein a computer program is stored in the memory, characterized in that: When the computer program is executed by a processor, the computer program performs the steps of the method according to any one of claims 1 to 7.

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