Self-adaptive state prediction control method for improving stability of network-forming type new energy shafting

Abstract

The invention provides a self-adaptive state prediction control method for improving the stability of a grid-forming type new energy shafting, and belongs to the technical field of wind power generation, and the method comprises the steps: determining an extended state observer based on a nonlinear function and a closed-loop system; obtaining a virtual torque compensation item by using the extended state observer, and feeding back the virtual torque compensation item to a virtual rotor motion equation of the virtual synchronous machine to perform additional power compensation; in the additional power compensation process, when the rotating speed of the draught fan is lower than a preset safety value, proportional integral differential control is set to zero through a rotating speed protection module, the wind power virtual synchronous machine system is controlled to exit additional power compensation, and the active supporting system is controlled to operate stably; in the stable operation process of the active support system, the rotating speed of the fan is recovered to the optimal value through the rotating speed recovery module, and the influence caused by unreasonable parameters is reduced and the dynamic stability of the wind power VSG grid-connected system is effectively enhanced by estimating the imbalance between the external disturbance power and the internal state quantity and performing tracking compensation in the controller.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power generation, and in particular, to an adaptive state prediction control method for improving the stability of the shafting of network-forming new energy sources. Background Art

[0002] Wind power generation is gradually becoming the main power source of the new power system. To ensure the stability of the new energy power system, "network-forming" wind power based on virtual synchronous control has become an important support for the "dual-high" power system. The virtual synchronous generator (VSG) control strategy without a phase-locked loop (PLL) dominates by introducing the synchronous machine rotor mechanical motion equation and the excitation voltage droop control into the wind turbine converter to provide dynamic stability support for the power grid. Research shows that under a low short-circuit ratio, the network-forming wind turbines demonstrate excellent adaptability to weak power grids, being able to effectively control the grid-connected power and interact well with the grid frequency and voltage. After virtual synchronous control is implemented for large-scale wind power, when the VSG actively supports the frequency, it will affect the transient stability characteristics of the power grid such as inertia, damping, and power angle. Therefore, it is necessary to comprehensively analyze its impact on system stability to evaluate the feasibility and safety of the wind turbine virtual synchronous control in the new power system.

[0003] Currently, the research on wind power VSG mostly focuses on system control strategy reconstruction and core parameter optimization, while the research on the influence of wind turbine virtual synchronous control on the power grid operation mechanism and coupling characteristics is relatively less. Theoretically, virtual synchronous control can improve system stability by adjusting the inertia coefficient, but large-scale power regulation still requires reliable active power output support from the wind turbine.

[0004] Therefore, how to ensure that the wind power virtual synchronous control has reliable speed recovery ability and sufficient flexible coupling shaft damping ability when providing frequency and voltage support for the grid-connected system has become a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] The present invention provides an adaptive state prediction control method for improving the stability of the shafting of network-forming new energy sources to solve the defect that the speed recovery ability and the flexible coupling shaft damping ability of the wind power virtual synchronous control are poor when providing frequency and voltage support for the grid-connected system in the prior art.

[0006] In a first aspect, the present invention provides an adaptive state prediction control method for improving the stability of the shafting of network-forming new energy sources, including: Determining an extended state observer based on a non-linear function and a closed-loop system; Estimating a virtual torque compensation term by using the extended state observer and feeding it back into the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; During the additional power compensation process, when the fan speed is lower than the preset safety value, the proportional-integral-derivative control is set to zero through the speed protection module, the wind power virtual synchronous machine system is controlled to exit the additional power compensation, and the active support system is controlled to operate stably; During the stable operation of the active support system, the fan speed is restored to the optimal value through the speed recovery module.

[0007] An adaptive state prediction control method for improving the stability of the grid-connected new energy shafting according to the present invention further includes: Determine the accelerating power curve; Apply the accelerating power curve to the speed recovery module to eliminate the secondary drop of the system frequency during the speed recovery process.

[0008] According to an adaptive state prediction control method for improving the stability of the grid-connected new energy shafting provided by the present invention, the determining of the accelerating power curve includes: Determine the trapezoidal function; Determine the fan speed, the optimal speed to which the fan needs to be restored, the speed at which the fan starts to recover, and the constant set power value; Based on the trapezoidal function, the fan speed, the optimal speed to which the fan needs to be restored, the speed at which the fan starts to recover, and the constant set power value, determine the accelerating power curve.

[0009] According to an adaptive state prediction control method for improving the stability of the grid-connected new energy shafting provided by the present invention, the accelerating power curve is: ; Wherein, represents the accelerating power curve, represents the fan speed, represents the optimal speed to which it needs to be restored, represents the speed at which the fan starts to recover, represents the constant set power value, represents the trapezoidal function.

[0010] According to an adaptive state prediction control method for improving the stability of the grid-connected new energy shafting provided by the present invention, the trapezoidal function is a trapezoidal curve that changes from a preset value to 1; The time corresponding to the preset value is the start time of the speed recovery, the time corresponding to 1 is the time when the function changes to 1, and the preset value is less than zero.

[0011] An adaptive state prediction control method for improving the stability of the grid-connected new energy shafting according to the present invention further includes: The trapezoidal function is used to control the active output of the fan so that it does not drop significantly at the initial stage of speed recovery, and the control coefficient gradually decreases to 0.

[0012] According to an adaptive state prediction control method for improving the stability of the grid-connected new energy shafting provided by the present invention, based on the nonlinear function and the closed-loop system, determining the extended state observer includes: Determining a first-order system including disturbances; Expanding the disturbance in the first-order system into a new state variable to obtain an extended system; Constructing the extended system into a nonlinear system; Based on the nonlinear system, the nonlinear function and the first-order system, constructing an extended state observer.

[0013] According to an adaptive state prediction control method for improving the stability of the grid-connected new energy shafting provided by the present invention, the extended state observer is: ; ; Wherein, and are state variables, , are the adjustment gains of the output error, is the nonlinear function, is the tracking error, is the nonlinear factor, is the filtering factor, is the system parameter, , , , , represents the input electromagnetic power, represents the system reference electromagnetic power command value, represents the extended state observer state variable, represents the state variable feedback correction parameter.

[0014] In a second aspect, the present invention also provides an adaptive state prediction control device for improving the stability of the grid-connected new energy shafting, including: A determination module, configured to determine an extended state observer based on a nonlinear function and a closed-loop system; A feedback module, configured to estimate a virtual torque compensation term by using the extended state observer and feedback it to the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; A control module, configured to, during the additional power compensation process, when the fan speed is lower than a preset safety value, set the proportional integral derivative control to zero through a speed protection module, control the wind power virtual synchronous machine system to exit the additional power compensation, and control the active support system to operate stably; A recovery module, configured to, during the stable operation of the active support system, restore the fan speed to an optimal value through a speed recovery module.

[0015] In a third aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it implements the adaptive state prediction control method for improving the stability of the grid-connected new energy shafting as described in any one of the above.

[0016] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the adaptive state prediction control method for improving the stability of the grid-connected new energy shafting as described in any one of the above.

[0017] In a fifth aspect, the present invention further provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the adaptive state prediction control method for improving the stability of the grid-connected new energy shafting as described in any one of the above.

[0018] An adaptive state prediction control method for improving the stability of the grid-connected new energy shafting provided by the present invention includes: determining an extended state observer based on a non-linear function and a closed-loop system; obtaining a virtual torque compensation term by using the extended state observer and feeding it back into the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; during the additional power compensation process, when the fan speed is lower than a preset safety value, set the proportional integral derivative control to zero through a speed protection module, control the wind power virtual synchronous machine system to exit the additional power compensation, and control the active support system to operate stably; during the stable operation of the active support system, restore the fan speed to an optimal value through a speed recovery module. By estimating the imbalance between the external disturbance power and the internal state variables and performing tracking compensation in the controller, the deviation between the disturbance compensation amount and the actual disturbance under fault conditions is significantly reduced, and the influence caused by unreasonable parameter settings is reduced, thereby effectively enhancing the dynamic stability of the wind power VSG grid-connected system. Description of the Drawings

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 It is a schematic flowchart of the adaptive state prediction control method for improving the stability of the grid-forming new energy shafting system provided in this embodiment; Figure 2 It is a schematic diagram of the virtual synchronous direct-drive wind power control principle based on adaptive state prediction control provided in this embodiment; Figure 3 It is a schematic diagram of the trapezoidal function provided in this embodiment; Figure 4 It is a schematic diagram of the fan speed recovery strategy based on the accelerating power provided in this embodiment; Figure 5 It is a schematic diagram of the comparison of the system angular frequency change provided in this embodiment; Figure 6 It is a schematic diagram of the comparison of the fan angular velocity change provided in this embodiment; Figure 7 It is a schematic diagram of the comparison of the wind power active power change provided in this embodiment; Figure 8 It is a schematic diagram of the structure of the adaptive state prediction control device for improving the stability of the grid-forming new energy shafting system provided in this embodiment; Figure 9 It is a schematic diagram of the structure of the electronic device provided in this embodiment. Detailed implementation manners

[0021] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without making creative efforts shall fall within the protection scope of the present invention.

[0022] Figure 1 It is a schematic flowchart of the adaptive state prediction control method for improving the stability of the grid-forming new energy shafting system provided in this embodiment.

[0023] As Figure 1 shown, the adaptive state prediction control method for improving the stability of the grid-forming new energy shafting system provided in the embodiments of the present invention mainly includes the following steps: 101. Determine an extended state observer based on a non-linear function and a closed-loop system.

[0024] In a specific implementation process, the adaptive state prediction control can perform real-time observation and estimation of the disturbance of the closed-loop system, and compensate for unknown interference factors in the feedback control. The first-order system containing the disturbance can be expressed as (1): (1) Wherein, is the estimated value of the state variable, is the state variable of the adaptive state prediction control; and are the input and output of the system respectively; is the disturbance of the system output; are the system parameters; is the unknown real-time action.

[0025] To facilitate the observation of the disturbance amount of the system, the disturbance expansion is extended into a new state variable , and the system is rewritten as (2): (2) In the formula, is the real-time action of the total disturbance of the system, represents the original state variable, represents the state variable with respect to time in the time domain, represents the newly generated state variable after the system disturbance expansion, and further constructs the nonlinear system (3): (3) Wherein, and are the estimated values of the state variable and the control variable of the nonlinear system, represents the state variable of the extended state observer, represents the state variable feedback correction parameter, , are the adjustment gains of the output error, and the nonlinear function can achieve the accurate tracking of , and the expression is (4): (4) Wherein, is the tracking error, is the nonlinear factor, is the filtering factor. Among them usually has a value range of (0, 1), generally has a value of (5T, 10T).

[0026] Substitute the function into equation (3), and according to equation (1), let , , input , input coefficient , and the designed extended state observer is: (5) (6) Among them, and are state variables, 、 are the adjustment gains of the output error, is a non - linear function, is the tracking error, is the non - linear factor, is the filtering factor, is the system parameter, , , , , represents the input electromagnetic power, represents the system reference electromagnetic power command value, represents the extended state observer state variable, represents the state variable feedback correction parameter.

[0027] 102. Estimate the virtual torque compensation term using the extended state observer and feedback it to the virtual rotor motion equation of the virtual synchronous machine for additional power compensation.

[0028] The control strategy of the virtual synchronous direct - drive wind turbine is as Figure 2 shown. Obtain the virtual torque compensation term through the extended state observer, feedback it to the VSG virtual rotor motion equation for additional power compensation, reduce the influence of wind power and load disturbances on the system stability, and enhance the ability of the wind turbine active support system to operate stably.

[0029] As Figure 2 shown, the speed recovery module, speed protection module, virtual synchronous PMSG control system and MPPT control cooperate with each other. After estimating the virtual torque compensation term through the extended state observer in the dotted box, then through speed recovery, speed protection and maximum power point tracking (MPPT), jointly achieve the control of virtual synchronous direct - drive wind power (PMSG).

[0030] 103. During the additional power compensation process, when the wind turbine speed is lower than the preset safety value, the proportional - integral - derivative control is set to zero through the speed protection module, and the wind power virtual synchronous machine system is controlled to exit the additional power compensation to control the stable operation of the active support system.

[0031] When the wind turbine speed is lower than the preset safety value , to avoid the threat of shaft - system torsional vibration caused by additional power control to the safety of the wind turbine, the speed protection module sets the proportional - integral - derivative control ( ) to zero, so that the wind power VSG system exits the additional power compensation.

[0032] 104. During the stable operation of the active support system, the fan speed is restored to the optimal value through the speed restoration module.

[0033] After the virtual synchronous PMSG controls the stable operation of the active support system, to avoid the secondary drop of the system frequency, it is necessary to restore the fan speed to the optimal value as soon as possible. Therefore, an acceleration power curve is designed based on the fan speed restoration strategy. . Specifically: determine the acceleration power curve; apply the acceleration power curve to the speed restoration module to eliminate the secondary drop of the system frequency during the speed restoration process. And determining the acceleration power curve includes: determining the trapezoidal function; determining the fan speed, the optimal speed that the fan needs to restore to, the speed when the fan starts to restore, and the constant set power value; based on the trapezoidal function, the fan speed, the optimal speed that the fan needs to restore to, the speed when the fan starts to restore, and the constant set power value, determine the acceleration power curve. As shown in (7): (7) Among them, represents the acceleration power curve, represents the fan speed, represents the optimal speed that needs to be restored to, represents the speed when the fan starts to restore, represents the constant set power value, represents the trapezoidal function.

[0034] Trapezoidal function is a trapezoidal curve that varies from to 1, as shown in Figure 3 . is the starting time of speed restoration, is the corresponding time moment when the function reaches 1. To further reduce the drop of the fan active power output at the beginning of speed restoration, takes a value less than 0. The speed restoration strategy based on the trapezoidal function is as shown in Figure 4 . represents the proportional coefficient for controlling the rotor restoration, represents the integral coefficient for controlling the rotor restoration, represents the command value of the speed restoration module.

[0035] Based on the trapezoidal function of the power acceleration restoration strategy, it ensures that the active power output of the fan will not drop too significantly at the initial stage of speed rise; at the same time, when the fan speed from restores to during the process, the coefficient It also gradually decreases to 0. Therefore, the power acceleration speed recovery strategy based on the PI controller can better support the virtual synchronous PMSG's ability to support the system inertia and damping, and avoid the adverse impact on the system frequency during the speed recovery process after the VSG dynamic regulation is completed.

[0036] To further verify the effectiveness of this solution, the following simulation tests are carried out: Verify the effectiveness of the virtual synchronous VSG optimization control strategy under different working conditions. At the rated wind speed, when the load L1 suddenly increases by 150 MW at the 10th second, the system angular frequency change is as Figure 5 shown, the fan angular velocity change is as Figure 6 shown, and the wind power active power change is as Figure 7 shown. It can be seen that after the virtual synchronous fan adopts the speed recovery strategy based on the step function, the oscillation amplitude of the system frequency decreases, and the fan speed recovers smoothly, thus reducing the impact on the system and wind turbines during load switching. Therefore, the control strategy can effectively improve the stability of the grid-connected wind power system under different working conditions.

[0037] The wind power virtual synchronous control strategy based on adaptive state prediction control of the present invention can effectively improve the grid connection friendliness of grid-forming fans. This control strategy estimates the imbalance between the external disturbance power and the internal state variables and performs tracking compensation in the controller, significantly reducing the deviation between the disturbance compensation amount and the actual disturbance under fault conditions, and reducing the influence caused by unreasonable parameter settings, thereby effectively enhancing the dynamic stability of the wind power VSG grid-connected system.

[0038] Based on the same general inventive concept, the present invention also protects an adaptive state prediction control device for improving the stability of the shafting of grid-forming new energy.

[0039] Figure 8 It is a schematic structural diagram of the adaptive state prediction control device for improving the stability of the shafting of grid-forming new energy provided in this embodiment.

[0040] As Figure 8 shown, an adaptive state prediction control device for improving the stability of the shafting of grid-forming new energy provided in this embodiment includes: A determination module 801, configured to determine an extended state observer based on a non-linear function and a closed-loop system; A feedback module 802, configured to estimate a virtual torque compensation term by using the extended state observer and feedback it into the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; The control module 803 is configured to, during the additional power compensation process, when the fan speed is lower than a preset safety value, set the proportional integral derivative control to zero through the speed protection module, control the wind power virtual synchronous machine system to exit the additional power compensation, and control the stable operation of the active support system; The recovery module 804 is configured to, during the stable operation of the active support system, restore the fan speed to the optimal value through the speed recovery module.

[0041] Figure 9 It is a schematic structural diagram of the electronic device provided in this embodiment.

[0042] As Figure 9 shown, the electronic device may include: a processor 910, a communications interface 920, a memory 930, and a communication bus 940. Among them, the processor 910, the communications interface 920, and the memory 930 complete mutual communication through the communication bus 940. The processor 910 may call the logic instructions in the memory 930 to execute an adaptive state prediction control method for improving the stability of the grid-forming new energy shaft system. The method includes: determining an extended state observer based on a non-linear function and a closed-loop system; estimating a virtual torque compensation term by using the extended state observer and feeding it back into the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; during the additional power compensation process, when the fan speed is lower than a preset safety value, setting the proportional integral derivative control to zero through the speed protection module, controlling the wind power virtual synchronous machine system to exit the additional power compensation, and controlling the stable operation of the active support system; during the stable operation of the active support system, restoring the fan speed to the optimal value through the speed recovery module.

[0043] In addition, when the logic instructions in the above-mentioned memory 930 are implemented in the form of a software functional unit and sold or used as an independent product, they may be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, may be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk, or an optical disc that can store program codes.

[0044] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the adaptive state prediction control method for improving the stability of the grid-connected new energy shaft system provided by the above-mentioned various methods. The method includes: determining an extended state observer based on a non-linear function and a closed-loop system; estimating a virtual torque compensation term by using the extended state observer and feeding it back into the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; during the additional power compensation process, when the fan speed is lower than a preset safety value, setting the proportional-integral-derivative control to zero through a speed protection module, controlling the wind power virtual synchronous machine system to exit the additional power compensation, and controlling the active support system to operate stably; during the stable operation of the active support system, restoring the fan speed to the optimal value through a speed recovery module.

[0045] In another aspect, the present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it realizes the adaptive state prediction control method for improving the stability of the grid-connected new energy shaft system provided by the above-mentioned various methods. The method includes: determining an extended state observer based on a non-linear function and a closed-loop system; estimating a virtual torque compensation term by using the extended state observer and feeding it back into the virtual rotor motion equation of the virtual synchronous machine for additional power compensation; during the additional power compensation process, when the fan speed is lower than a preset safety value, setting the proportional-integral-derivative control to zero through a speed protection module, controlling the wind power virtual synchronous machine system to exit the additional power compensation, and controlling the active support system to operate stably; during the stable operation of the active support system, restoring the fan speed to the optimal value through a speed recovery module.

[0046] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0047] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. An adaptive state prediction control method for improving the stability of a grid-type new energy shaft system, characterized in that: include: Based on nonlinear functions and closed-loop systems, an extended state observer is determined; The virtual torque compensation term is estimated by using the extended state observer and fed back to the virtual rotor motion equation of the virtual synchronous machine to perform additional power compensation; During the additional power compensation process, when the wind turbine speed is lower than a preset safety value, the proportional integral differential control is set to zero through the speed protection module, the wind power virtual synchronous machine system is controlled to exit the additional power compensation, and the active support system is controlled to operate stably; During the stable operation of the active support system, the fan speed is restored to an optimal value through the speed recovery module.

2. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 1 is characterized in that: Also includes: Determine the acceleration power curve; The acceleration power curve is applied to the rotation speed recovery module to eliminate the secondary drop of the system frequency during the rotation speed recovery process.

3. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 2 is characterized in that: The step of determining the acceleration power curve comprises: Determine the trapezoidal function; Determine the fan speed, the optimal speed to which the fan needs to be restored, the speed at which the fan starts to recover, and the constant set power value; An acceleration power curve is determined based on the trapezoidal function, the fan speed, the optimal speed to which the fan needs to be restored, the speed when the fan starts to recover, and the constant set power value.

4. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 3 is characterized in that: The acceleration power curve is: ； in, represents the acceleration power curve, Indicates the fan speed. Indicates the optimal speed to be restored. Indicates the speed when the fan starts to recover. Indicates a constant set power value, Represents a trapezoidal function.

5. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 4 is characterized in that: The trapezoidal function is a trapezoidal curve that changes from a preset value to 1; The time corresponding to the preset value is the start time of the speed recovery, the time corresponding to 1 is the time corresponding to when the function changes to 1, and the preset value is less than zero.

6. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 5 is characterized in that: Also includes: The trapezoidal function is used to control the active output of the fan to prevent a sharp drop in the initial stage of speed recovery and to control the coefficient Gradually decreases to 0.

7. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 1 is characterized in that: The method of determining an extended state observer based on a nonlinear function and a closed-loop system comprises: Identify first-order systems that contain perturbations; Expanding the disturbance in the first-order system into a new state variable to obtain an expanded system; constructing the expanded system as a nonlinear system; Based on the nonlinear system, nonlinear function and first-order system, an extended state observer is constructed.

8. The adaptive state prediction control method for improving the stability of a grid-type new energy shaft system according to claim 7 is characterized in that: The extended state observer is: ； ； in, and is the estimated value of the state variable, , is the regulation gain of the output error, is a nonlinear function, is the tracking error, is the nonlinear factor, is the filtering factor, is the system parameter, , , , , represents the input electromagnetic power, Indicates the system reference electromagnetic power command value, represents the state variable of the extended state observer, Represents the state variable feedback correction parameter.

9. An adaptive state prediction control device for improving the stability of a grid-type new energy shaft system, characterized in that: include: A determination module, for determining an extended state observer based on a nonlinear function and a closed-loop system; A feedback module, used to estimate a virtual torque compensation term using the extended state observer, and feed it back to the virtual rotor motion equation of the virtual synchronous machine to perform additional power compensation; A control module, used for, during the additional power compensation process, when the wind turbine speed is lower than a preset safety value, setting the proportional integral differential control to zero through the speed protection module, controlling the wind power virtual synchronous machine system to exit the additional power compensation, and controlling the active support system to operate stably; The recovery module is used to restore the fan speed to an optimal value through the speed recovery module during the stable operation of the active support system.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, it implements the adaptive state prediction control method for improving the stability of the networked new energy shaft system as described in any one of claims 1 to 8.

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