Frequency modulation control method and system for wind power flexible direct current grid-connected system

Abstract

The present invention provides a frequency regulation control method and system for a wind power flexible direct current grid-connected system, which relates to the field of wind power flexible direct current grid-connected systems. The method comprises obtaining a reactive current value to divide the reactive current value into each wind turbine according to a preset ratio; establishing a mathematical model according to proportional control, integral control and differential control to obtain an objective function, optimizing the objective function by an improved PRGO optimization algorithm to update the preset ratio and obtain a target ratio; dividing the reactive current value into each wind turbine according to the target ratio to frequency-regulate the wind power flexible direct current grid-connected system; optimizing the proportional gain, differential gain and integral gain of a PID controller by adopting an improved PRGO optimization algorithm, and the obtained parameters effectively improve the control accuracy of frequency regulation of the wind power flexible direct current grid-connected system, so that the wind farm flexible direct current grid-connected system maintains a stable operating state; and solving the technical problem that the frequency regulation control of the wind power flexible direct current grid-connected system cannot be achieved in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field of wind power flexible direct current grid-connected systems, and in particular to a frequency modulation control method and system for wind power flexible direct current grid-connected systems. Background Art

[0002] A flexible wind power direct current (VSC) grid-connected system connects wind turbines to the power grid via voltage source converter (VSC-HVDC) technology. Frequency regulation in this system ensures a stable frequency and reliable operation.

[0003] Currently, numerous studies are underway on flexible wind power grid-connected systems. One approach involves applying harmonic injection and information transmission to address harmonic resonance, communication delays, and submodule failures. Another approach involves applying improved V / F control strategies (i.e., voltage-frequency ratio control strategies) to direct-drive wind power grid-connected flexible wind power systems to improve operational stability. While these two approaches provide the necessary foundation for stable operation, they do not enable frequency regulation. Summary of the Invention

[0004] Based on this, the purpose of the present invention is to provide a frequency regulation control method and system for a wind power flexible direct current grid-connected system, which is used to solve the technical problem that the frequency regulation control of a wind power flexible direct current grid-connected system cannot be achieved in the prior art.

[0005] In one aspect, the present invention provides a frequency modulation control method for a wind power flexible direct current grid-connected system, which is applied to a PID controller. The PID controller includes proportional control, integral control, and differential control. The method includes:

[0006] Obtaining a reactive current value and dividing the reactive current value among the wind turbines according to a preset ratio;

[0007] A mathematical model is established based on proportional control, integral control, and differential control to obtain an objective function, and the objective function is optimized using an improved PRGO optimization algorithm to update the preset ratio to obtain a target ratio, where the target ratio includes a target proportional gain, a target differential gain, and a target integral gain;

[0008] Divide the reactive current value to each wind turbine according to the target ratio to adjust the frequency of the wind power flexible direct current grid-connected system;

[0009] The improved PRGO optimization algorithm includes a fibrous root growth mathematical model, and the expression of the fibrous root growth mathematical model is:

[0010] ;

[0011] Where, Seed1 represents the ith fiber root grown at the t+1th time; X best It means that the best fiber root has been found so far in history; X worst This indicates that the search for the worst fiber root in history has been conducted so far; represents the t-th growth of the i-th fiber root; represents a fiber root randomly selected from the N fiber roots grown at the tth time; α 1 is a random number in the interval (-0.5, 1.5); or Represents a constant that changes with the number of iterations; t Indicates the current iteration number; T max Indicates the maximum number of iterations.

[0012] The above-mentioned frequency regulation control method of the wind power flexible direct current grid-connected system optimizes the proportional gain, differential gain and integral gain of the PID controller by adopting the improved PRGO optimization algorithm to obtain the target proportion, obtains the optimized PID controller parameters according to the target proportion, and improves the control accuracy of the PID controller according to the optimized PID controller parameters, so that the obtained PID controller parameters effectively improve the control accuracy of the frequency regulation of the wind power flexible direct current grid-connected system, thereby maintaining a stable operating state of the wind farm flexible direct current grid-connected system; and solves the technical problem that the frequency regulation control of the wind power flexible direct current grid-connected system cannot be realized in the existing technology.

[0013] In addition, the frequency modulation control method for the wind power flexible direct current grid-connected system according to the present invention may also have the following additional technical features:

[0014] Furthermore, the improved PRGO optimization algorithm also includes a taproot growth mathematical model, the expression of which is:

[0015] ;

[0016] Where, Seed2 represents the nutrients absorbed by the lateral root during the t+1th growth; Seed3 represents the nutrients absorbed by the main root during the t+1th growth; is the entire soil space; u and l are the upper and lower bounds of the problem space respectively; α 3 is a random integer; for e The negation of e When 1 is taken, α 3∈(0,1); when e When 0 is taken, α 3=1; g is a random value.

[0017] Furthermore, the improved PRGO optimization algorithm also includes a mathematical model for the growth of fibrous root plants. The expression of the mathematical model for the growth of fibrous root plants is:

[0018] ;

[0019] Where, X c Indicates the current adventitious root The nutrients absorbed by the rhizomes other than the thick adventitious roots to diffuse and grow in the soil. Seed4 represents the nutrients absorbed by the adventitious roots in the t+1th growth. α 4 represents a random number; s is a random integer of 0 or 1 generated by the rand(0,1) function. s =1, α 4∈(0,1), when s =0, α 4=0; r3 and r4 are random integers selected from the interval (1,N) and r3≠r4; λ1 and λ2 both represent weights; X r3 and X r4 They represent the r3th individual and the r4th individual respectively.

[0020] Furthermore, the step of optimizing the objective function by using the improved PRGO optimization algorithm to update the preset ratio to obtain the target ratio includes:

[0021] Get the current iteration number;

[0022] Determine whether the current number of iterations has reached the maximum number of iterations;

[0023] If not, continue iterating;

[0024] If so, stop the iteration and output the target ratio.

[0025] Another aspect of the present invention provides a frequency modulation control system for a wind power flexible direct current grid-connected system, which is applied to a PID controller. The PID controller includes proportional control, integral control, and differential control. The system includes:

[0026] an acquisition module, configured to acquire a reactive current value and divide the reactive current value into each wind turbine according to a preset ratio;

[0027] an optimization module, configured to establish a mathematical model based on proportional control, integral control, and differential control to obtain an objective function, and optimize the objective function using an improved PRGO optimization algorithm to update the preset ratio to obtain a target ratio, wherein the target ratio includes a target proportional gain, a target differential gain, and a target integral gain;

[0028] Frequency regulation module, used to divide the reactive current value to each wind turbine according to the target ratio to regulate the frequency of the wind power flexible direct current grid-connected system;

[0029] The improved PRGO optimization algorithm includes a fibrous root growth mathematical model, and the expression of the fibrous root growth mathematical model is:

[0030] ;

[0031] Where, Seed1 represents the ith fiber root grown at the t+1th time; X best It means that the best fiber root has been found so far in history; X worst This indicates that the search for the worst fiber root in history has been conducted so far; represents the t-th growth of the i-th fiber root; represents a fiber root randomly selected from the N fiber roots grown at the tth time; α 1 is a random number in the interval (-0.5, 1.5); or Represents a constant that changes with the number of iterations; t Indicates the current iteration number; T max Indicates the maximum number of iterations.

[0032] Another aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the frequency regulation control method for a wind power flexible direct current grid-connected system as described above.

[0033] On the other hand, the present invention also provides a data processing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the frequency regulation control method of the wind power flexible direct current grid-connected system as described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 Flowchart of a frequency regulation control method for a wind power flexible direct current grid-connected system according to an embodiment of the present invention;

[0035] Figure 2 Schematic diagram comparing the relationship between the number of iterations and fitness value of the improved PRGO optimization algorithm and the conventional PRGO optimization algorithm in an embodiment of the present invention;

[0036] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION

[0037] To facilitate understanding of the present invention, the present invention will be described more fully below with reference to the accompanying drawings. The drawings illustrate several embodiments of the present invention. However, the present invention may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive understanding of the present invention.

[0038] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0039] The two methods in the prior art provide the necessary foundation for the stable operation of the wind power flexible direct current grid-connected system, but cannot realize the frequency modulation control of the wind power flexible direct current grid-connected system. The PID control algorithm has the characteristics of strong robustness, but has the defects of high error and poor control accuracy caused by nonlinear motion. Therefore, there is an urgent need for a frequency modulation control method for a wind power flexible direct current grid-connected system to solve the technical problem that the prior art cannot realize the frequency modulation control of the wind power flexible direct current grid-connected system. Specifically, the present application provides a frequency modulation control method and system for a wind power flexible direct current grid-connected system, which optimizes the proportional gain, differential gain and integral gain of the PID controller by adopting an improved PRGO optimization algorithm to obtain a target proportion, obtains the optimized PID controller parameters according to the target proportion, and improves the control accuracy of the PID controller according to the optimized PID controller parameters, so that the obtained PID controller parameters effectively improve the control accuracy of the frequency modulation of the wind power flexible direct current grid-connected system, thereby maintaining a stable operating state of the wind farm flexible direct current grid-connected system; and solves the technical problem that the prior art cannot realize the frequency modulation control of the wind power flexible direct current grid-connected system.

[0040] To facilitate understanding of the present invention, several embodiments of the present invention are provided below. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and comprehensive disclosure of the present invention.

[0041] Example 1

[0042] See also Figure 1, which shows a frequency modulation control method for a wind power flexible direct current grid-connected system in a first embodiment of the present invention, and is applied to a PID controller. The PID controller includes proportional control, integral control, and differential control. The method includes steps S101 to S103:

[0043] S101 : Obtain reactive current values to divide the reactive current values into respective wind turbines according to a preset ratio.

[0044] S102. Establish a mathematical model based on proportional control, integral control, and differential control to obtain an objective function. Optimize the objective function using the improved PRGO optimization algorithm to update the preset ratio to obtain a target ratio. The target ratio includes a target proportional gain, a target differential gain, and a target integral gain.

[0045] The objective functions established include proportional control, integral control and differential control. Specifically:

[0046] Proportional control. The signal output gain is adjusted through proportional control of the PID controller. The frequency modulation control of the wind power flexible DC grid-connected system forms a deviation hysteresis, and the proportional control link is used to control the system frequency modulation. The larger the deviation value, the stronger the control performance of the proportional control link, reducing the system deviation and achieving the ideal input of the reactive current value of the wind power flexible DC grid-connected system. Specifically, the objective function of proportional control is as follows:

[0047] u(τ)=K1﹒e(τ)

[0048] e(τ)=r(τ)-y(τ)

[0049] Where K1 represents the proportional gain, e(τ) and r(τ) represent the error signal and reactive current reference signal, respectively; u(τ) represents the objective function of proportional control, y(τ) represents the reactive current feedback signal; and τ represents time.

[0050] Integral control. The force of the PID controller's integral control is positively correlated with the set integral value. The error between the reactive current command signal and the output signal of the wind power flexible direct current grid-connected system is eliminated by introducing the integral term. The objective function expression of the integral control is as follows:

[0051] ;

[0052] in, represents the objective function of integral control, K2 and They represent the integral gain and integral time constant of the PID controller respectively; τ represents time.

[0053] Differential control. The differential control link of the PID controller is used to achieve dynamic adjustment of the system frequency modulation control. The introduction of the differential control link improves the rapid response capability of the PID controller and makes the control performance of the PID controller more stable. The objective function expression of the differential control is as follows:

[0054] ;

[0055] Where, represents the objective function of differential control, K3 and represents the differential gain and differential time constant; τ represents time.

[0056] As a specific example, in order to avoid the problem of uneven initial population distribution caused by the random generation of the initial population in the original algorithm, this application introduces the Henon chaotic map to initialize the population to set the initial population number and the maximum number of iterations. Specifically:

[0057] ;

[0058] in:

[0059] x i,j =( ub - lb )+ lb ;

[0060] x i,j =cos(π(4r x i,j (1- x i,j )+(1-r)sin(π x i,j )-0.5)),r∈[0,1];

[0061] Where, X represents the initial population, x i,j Representative i Individuals in j The values in the dimensions, where i ∈1,2,…,n; j ∈1,2,…,d; n is the population size, d is the dimension of the problem; each individual represents a set of optimal parameter solutions for the proportional gain, differential gain, and integral gain of the PID controller. ub and lb are the upper bound and the lower bound of the problem respectively; r represents a random number between 0 and 1.

[0062] Furthermore, in order to obtain a better ratio to update the preset ratio, specifically, the steps of optimizing the objective function by the improved PRGO optimization algorithm to update the preset ratio and obtain the target ratio include:

[0063] Get the current number of iterations; determine whether the current number of iterations has reached the maximum number of iterations; if not, continue iterating; if it has reached the maximum number of iterations, stop iterating and output the target ratio.

[0064] It should be further explained that the target ratio is the best ratio within the set maximum number of iterations, so that the reactive current value can be better divided into the ratios of each wind turbine. Figure 2 As shown in the figure, from the relationship diagram between the number of iterations and fitness value of the improved PRGO optimization algorithm and the conventional PRGO optimization algorithm, it can be seen that the improved PRGO optimization algorithm and the conventional PRGO optimization algorithm can find better individuals.

[0065] In this embodiment, the improved PRGO optimization algorithm includes a fibrous root growth mathematical model, a taproot growth mathematical model, and a fibrous root plant growth mathematical model.

[0066] Among them, in order to avoid the problem of high convergence precision of the PRGO optimization algorithm in the early stage of iteration, as a specific example, an adaptive elite selection formula is introduced in the fiber root growth mathematical model part of the PRGO optimization algorithm to improve its convergence precision. Specifically, the expression of the improved fiber root growth mathematical model is:

[0067] ;

[0068] Where, Seed1 represents the t+1th growth i fibrous roots; X best It means that the best fiber root has been found so far in history; X worst This indicates that the search for the worst fiber root in history has been conducted so far; represents the t-th growth of the i-th fiber root; represents a fiber root randomly selected from the N fiber roots grown at the tth time; α 1 is a random number in the interval (-0.5, 1.5); or Represents a constant that changes with the number of iterations; t Indicates the current iteration number; T max Indicates the maximum number of iterations.

[0069] Secondly, in order to prevent the PRGO optimization algorithm from falling into the local optimum in the late iteration, in this embodiment, an escape formula is introduced into the taproot growth mathematical model of the PRGO optimization algorithm to help jump out of the local optimum. Specifically, the expression of the improved taproot growth mathematical model is:

[0070] ;

[0071] Where, Seed2 represents the nutrients absorbed by the lateral root during the t+1th growth; Seed3 represents the nutrients absorbed by the main root during the t+1th growth; is the entire soil space, i.e. the target problem search space; u and l are the upper and lower bounds of the problem space respectively; α 3 is a random integer; for e The negation of e When 1 is taken, α 3∈(0,1); when e When 0 is taken, α 3=1; g is a random value.

[0072] Furthermore, to avoid the slow running speed of the PRGO optimization algorithm, in this embodiment, an adaptive factor is introduced into the fibrous root plant growth mathematical model of the PRGO optimization algorithm to improve the running speed. Specifically, the expression of the improved fibrous root plant growth mathematical model is:

[0073] ;

[0074] Where, X c Indicates the current adventitious root The nutrients absorbed by the rhizomes other than the thick adventitious roots to diffuse and grow in the soil. Seed4 represents the nutrients absorbed by the adventitious roots in the t+1th growth. α 4 represents a random number; s is a random integer of 0 or 1 generated by the rand(0,1) function. s =1, α 4∈(0,1), when s =0, α 4=0; r3 and r4 are random integers selected from the interval (1,N) and r3≠r4; λ1 and λ2 both represent weights; X r3 and X r4 They represent the r3th individual and the r4th individual respectively.

[0075] S103, dividing the reactive current value into each wind turbine according to the target ratio to adjust the frequency of the wind power flexible direct current grid-connected system.

[0076] In summary, the frequency regulation control method of the wind power flexible direct current grid-connected system in the above-mentioned embodiment of the present invention optimizes the proportional gain, differential gain and integral gain of the PID controller by adopting the improved PRGO optimization algorithm to obtain the target proportion, obtains the optimized PID controller parameters according to the target proportion, and improves the control accuracy of the PID controller according to the optimized PID controller parameters, so that the obtained PID controller parameters effectively improve the control accuracy of the frequency regulation of the wind power flexible direct current grid-connected system, thereby maintaining a stable operating state of the wind farm flexible direct current grid-connected system; and solves the technical problem that the frequency regulation control of the wind power flexible direct current grid-connected system cannot be realized in the prior art.

[0077] Example 2

[0078] A second embodiment of the present invention provides a frequency modulation control system for a wind power flexible direct current grid-connected system, which is applied to a PID controller. The PID controller includes proportional control, integral control, and differential control. The system includes:

[0079] an acquisition module, configured to acquire a reactive current value and divide the reactive current value into each wind turbine according to a preset ratio;

[0080] an optimization module, configured to establish a mathematical model based on proportional control, integral control, and differential control to obtain an objective function, and optimize the objective function using an improved PRGO optimization algorithm to update the preset ratio to obtain a target ratio, wherein the target ratio includes a target proportional gain, a target differential gain, and a target integral gain;

[0081] Frequency regulation module, used to divide the reactive current value to each wind turbine according to the target ratio to regulate the frequency of the wind power flexible direct current grid-connected system;

[0082] The improved PRGO optimization algorithm includes a fibrous root growth mathematical model, and the expression of the fibrous root growth mathematical model is:

[0083] ;

[0084] Where, Seed1 represents the ith fiber root grown at the t+1th time; X best It means that the best fiber root has been found so far in history; X worst This indicates that the search for the worst fiber root in history has been conducted so far; represents the t-th growth of the i-th fiber root; represents a fiber root randomly selected from the N fiber roots grown at the tth time; α 1 is a random number in the interval (-0.5, 1.5); or Represents a constant that changes with the number of iterations;t Indicates the current iteration number; T max Indicates the maximum number of iterations.

[0085] In summary, the frequency regulation control system of the wind power flexible direct current grid-connected system in the above-mentioned embodiment of the present invention optimizes the proportional gain, differential gain and integral gain of the PID controller by adopting the improved PRGO optimization algorithm to obtain the target proportion, obtains the optimized PID controller parameters according to the target proportion, and improves the control accuracy of the PID controller according to the optimized PID controller parameters, so that the obtained PID controller parameters effectively improve the control accuracy of the frequency regulation of the wind power flexible direct current grid-connected system, thereby maintaining a stable operating state of the wind farm flexible direct current grid-connected system; and solves the technical problem that the frequency regulation control of the wind power flexible direct current grid-connected system cannot be realized in the prior art.

[0086] In addition, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method in the above embodiment when the program is executed by a processor.

[0087] In addition, an embodiment of the present invention further provides a data processing device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method in the above embodiment when executing the program.

[0088] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0089] More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting, or processing it in another suitable manner as necessary, and then storing it in a computer memory.

[0090] It should be understood that various components of the present invention may be implemented using hardware, software, firmware, or a combination thereof. In the above-described embodiments, multiple steps or methods may be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof may be used: a discrete logic circuit having logic gate circuits for implementing logic functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0091] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0092] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

Claims

1. A frequency modulation control method for a wind power flexible direct current grid-connected system, characterized in that: Applied to a PID controller, the PID controller includes proportional control, integral control, and differential control, and the method includes: Obtaining a reactive current value and dividing the reactive current value among the wind turbines according to a preset ratio; A mathematical model is established based on proportional control, integral control, and differential control to obtain an objective function, and the objective function is optimized using an improved PRGO optimization algorithm to update the preset ratio to obtain a target ratio, where the target ratio includes a target proportional gain, a target differential gain, and a target integral gain; Divide the reactive current value to each wind turbine according to the target ratio to adjust the frequency of the wind power flexible direct current grid-connected system; The improved PRGO optimization algorithm includes a fibrous root growth mathematical model, and the expression of the fibrous root growth mathematical model is: ； Where, Seed1 represents the ith fiber root grown at the t+1th time; X best It means that the best fiber root has been found so far in history; X worst This indicates that the search for the worst fiber root in history has been conducted so far; represents the t-th growth of the i-th fiber root; represents a fiber root randomly selected from the N fiber roots grown at the tth time; α 1 is a random number in the interval (-0.5, 1.5); η Represents a constant that changes with the number of iterations; t Indicates the current iteration number; T max Indicates the maximum number of iterations.

2. The frequency modulation control method of a wind power flexible direct current grid-connected system according to claim 1, characterized in that: The improved PRGO optimization algorithm also includes a taproot growth mathematical model, the expression of which is: ； Where, Seed2 represents the nutrients absorbed by the lateral root during the t+1th growth; Seed3 represents the nutrients absorbed by the main root during the t+1th growth; is the entire soil space, i.e. the target problem search space; u and l are the upper and lower bounds of the problem space respectively; α 3 is a random integer; for ε The negation of when ε When 1 is taken, α 3∈(0,1); when ε When 0 is taken, α 3=1; ζ is a random value.

3. The frequency modulation control method of the wind power flexible direct current grid-connected system according to claim 2, characterized in that: The improved PRGO optimization algorithm also includes a mathematical model for the growth of fibrous root plants. The expression of the mathematical model for the growth of fibrous root plants is: ； Where, X c Indicates the current adventitious root The nutrients absorbed by the rhizomes other than the thick adventitious roots to diffuse and grow in the soil. Seed4 represents the nutrients absorbed by the adventitious roots in the t+1th growth. α 4 represents a random number; σ is a random integer of 0 or 1 generated by the rand(0,1) function. σ =1, α 4∈(0,1), when σ =0, α 4=0; r3 and r4 are random integers selected from the interval (1,N) and r3≠r4; λ1 and λ2 both represent weights; X r3 and X r4 They represent the r3th individual and the r4th individual respectively.

4. The frequency modulation control method of a wind power flexible direct current grid-connected system according to claim 1, characterized in that: The step of optimizing the objective function by using the improved PRGO optimization algorithm to update the preset ratio to obtain the target ratio includes: Get the current iteration number; Determine whether the current number of iterations has reached the maximum number of iterations; If not, continue iterating; If so, stop the iteration and output the target ratio.

5. A frequency modulation control system for a wind power flexible direct current grid-connected system, characterized in that: Applied to a PID controller, the PID controller includes proportional control, integral control and differential control, and the system includes: an acquisition module, configured to acquire a reactive current value and divide the reactive current value into each wind turbine according to a preset ratio; an optimization module, configured to establish a mathematical model based on proportional control, integral control, and differential control to obtain an objective function, and optimize the objective function using an improved PRGO optimization algorithm to update the preset ratio to obtain a target ratio, wherein the target ratio includes a target proportional gain, a target differential gain, and a target integral gain; Frequency regulation module, used to divide the reactive current value to each wind turbine according to the target ratio to regulate the frequency of the wind power flexible direct current grid-connected system; The improved PRGO optimization algorithm includes a fibrous root growth mathematical model, and the expression of the fibrous root growth mathematical model is: ； Where, Seed1 represents the ith fiber root grown at the t+1th time; X best It means that the best fiber root has been found so far in history; X worst This indicates that the search for the worst fiber root in history has been conducted so far; represents the t-th growth of the i-th fiber root; represents a fiber root randomly selected from the N fiber roots grown at the tth time; α 1 is a random number in the interval (-0.5, 1.5); η Represents a constant that changes with the number of iterations; t Indicates the current iteration number; T max Indicates the maximum number of iterations.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the frequency regulation control method of the wind power flexible direct current grid-connected system as described in any one of claims 1 to 4 is implemented.

7. A data processing 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, the frequency regulation control method for the wind power flexible direct current grid-connected system as described in any one of claims 1 to 4 is implemented.

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