Harmonic suppression control method and device for offshore wind power static var generator

Abstract

The invention discloses a harmonic suppression control method and device for an offshore wind power static var generator, and the control of the static var generator comprises the steps: symmetric reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shifting PWM, and obtaining a current instruction and a harmonic current of the static var generator; when it is detected that the harmonic current of the static var generator is larger than a threshold value, parameters of PI closed-loop control are set through the particle swarm optimization, and compensation current of the harmonic current is obtained based on PI closed-loop control; the compensation current of the harmonic current is used for correcting the current instruction of the static var generator, the corrected current instruction is obtained, and according to the variable quantity of the harmonic, parameters of PI closed-loop control are dynamically adjusted to achieve a more accurate harmonic suppression effect.

Description

Technical Field

[0001] The present invention belongs to the technical field of new energy control, and in particular, relates to an application method and device of a particle swarm optimization algorithm in a harmonic control strategy of an offshore wind power static VAR generator (SVG). Background Art

[0002] Offshore wind power has become an important direction for wind energy development due to its advantages such as abundant marine wind resources, small space constraints, and low noise pollution. However, the development of offshore wind power also faces a series of challenges, among which power quality is a key issue. The power quality problems of offshore wind power systems are mainly manifested in voltage fluctuations, grid frequency changes, harmonics, etc. Among them, the harmonic problem is one of the most serious problems in wind power grid connection. The generation of harmonics not only affects the operating efficiency of the wind power system itself, but also has adverse effects on the power system, such as causing premature damage to power equipment, affecting the normal use of other power equipment, and even threatening the stable operation of the power system.

[0003] In the prior art, the harmonic control method usually adopts the method of adding multiple branches and single-tuned filters. This solution has the disadvantages of large investment, short life, space occupation, high maintenance cost, and high power consumption, making it unsuitable for offshore wind farms with special environmental requirements.

[0004] With the development of new power equipment, static VAR generators (SVG) have gradually shown their unique advantages in new energy power plants, especially in offshore wind farms, where the status of SVG is particularly important. First of all, SVG can provide reactive power support to help maintain grid voltage stability. SVG can provide compensation current opposite to harmonic current by adding APF function, which can effectively suppress harmonics and significantly improve power quality. However, the harmonic compensation effect of existing SVG to achieve high-voltage APF depends largely on whether it has a perfect control strategy. An accurate and efficient control strategy can enable SVG to better adapt to offshore wind power voltage compensation while realizing additional active filtering of harmonic currents to achieve comprehensive compensation effect of power management. Therefore, the offshore wind power SVG control strategy with additional high-voltage APF function is of high value for harmonic management. Summary of the invention

[0005] In order to solve the deficiencies in the prior art, the present invention provides a harmonic control method and device for an offshore wind power static reactive generator, which dynamically adjusts the parameters of the PI closed-loop control according to the change in the harmonics to achieve a more accurate harmonic suppression effect.

[0006] The present invention adopts the following technical solution.

[0007] The present invention proposes a harmonic control method for an offshore wind power static VAR generator. The control of the static VAR generator includes symmetrical reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shift PWM, including:

[0008] Obtain current command and harmonic current of static VAR generator;

[0009] When it is detected that the harmonic current of the static VAR generator is greater than the threshold, the particle swarm algorithm is used to adjust the parameters of the PI closed-loop control, and the compensation current of the harmonic current is obtained based on the PI closed-loop control;

[0010] The current command of the static VAR generator is corrected by using the compensation current of the harmonic current to obtain a corrected current command.

[0011] Preferably, the current instruction of the static VAR generator includes: a reactive current instruction and an active current instruction;

[0012] The harmonic current orders of the static VAR generator include: 3, 5, 7, 11, and 13.

[0013] Preferably, the threshold value is determined according to the limit value of harmonic current in national and industry standards.

[0014] Preferably, the parameters of the PI closed-loop control include the proportional coefficient K P And the integral action coefficient K I .

[0015] Preferably, a particle swarm algorithm is used to adjust the parameters of the PI closed-loop control, including:

[0016] The proportional coefficient K of PI closed loop control P And the integral action coefficient K I is the member variable of each particle in the population, the dimension of the search space is 2, and the position vector of particle i is is the proportional coefficient K in particle i P location, is the integral action coefficient K in particle i I The velocity vector of particle i is is the proportional coefficient K in particle i P speed, is the integral action coefficient K in particle i I speed; i = 1, 2, ..., N, N is the number of particles in the population;

[0017] Initialize the position vector, velocity vector, search space dimension, learning factor, individual optimal position vector and global optimal position vector of each particle in the search space Ω of the PI closed-loop control parameters.

[0018] Preferably, the particle swarm algorithm is used to adjust the parameters of the PI closed-loop control, and further includes:

[0019] Taking the minimization of the sum of harmonic currents after harmonic control as the objective function, an improved fitness function is established, and the improved fitness function satisfies the following relationship:

[0020]

[0021] Where Ω is the search space of PI closed-loop control parameters, K P is the proportional coefficient of PI closed-loop control, K I is the integral action coefficient of PI closed-loop control, J(K P ,K I ) is the proportional coefficient K in the particle P And the integral action coefficient K I The fitness function, j = 3, 5, 7, 11, ..., j is the order of the harmonic current of the static VAR generator, α j is the suppression weight of the jth harmonic current set under harmonic control, I dj ,I qj are the d-axis component and q-axis component of the j-th harmonic current, respectively, and t is the duration of harmonic control; It is the square value of each harmonic current after harmonic control.

[0022] Preferably, the improved fitness function is used to generate a fitness value to update the inertia weight. The iterative update process of the inertia weight is expressed as:

[0023]

[0024] In the formula, w k is the inertia weight in the kth iteration, w min 、w max are the minimum and maximum values ​​of the inertia weight, J avg , J min are the average and minimum fitness values ​​of the particle group, J i is the fitness value of particle i.

[0025] Preferably, the iterative update process of the d-th dimension component of the velocity vector and position vector of particle i is expressed as:

[0026]

[0027] In the formula, is the d-th component of the velocity vector of particle i in the k-th iteration, is the d-th dimension component of the individual optimal position vector of particle i in the k-th iteration, is the d-th component of the position vector of particle i in the k-th iteration, is the d-th dimension component of the global optimal position vector of the population in the k-th iteration, is the d-th component of the position vector of the population in the k-th iteration, w k is the inertia weight in the kth iteration, c1 and c2 are learning factors, and r1 and r2 are random numbers in the range of (0,1).

[0028] Preferably, during the iterative update process of the particle's velocity vector and position vector, the following two constraints are satisfied at the same time:

[0029] 1) In the kth iteration, the d-th component of the velocity vector of particle i Constrained within the speed range [V min ,V max ]Inside, V min 、V max are the lower and upper limits of the speed respectively; when season when season

[0030] 2) In the kth iteration, the search space of the PI closed-loop control parameters satisfies the following relationship:

[0031]

[0032] Where, L h (K P ,K I ) is the amplitude margin corresponding to the search space of the PI closed-loop control parameters when the system is stable, dB is the signal gain unit, γ(K P ,K I ) is the phase margin corresponding to the search space of PI closed-loop control parameters when the system is stable.

[0033] The present invention also proposes a harmonic control device for an offshore wind power static VAR generator. The control of the static VAR generator includes symmetrical reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shift PWM. The harmonic control device includes:

[0034] An acquisition module is used to obtain current instructions and harmonic currents of a static VAR generator;

[0035] A compensation current generation module is used to adjust the parameters of the PI closed-loop control by using a particle swarm algorithm when it is detected that the harmonic current of the static VAR generator is greater than a threshold value, and obtain a compensation current of the harmonic current based on the PI closed-loop control;

[0036] The current instruction correction module is used to correct the current instruction of the static VAR generator by using the compensation current of the harmonic current to obtain the corrected current instruction.

[0037] The present invention is also a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0038] The present invention is also a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0039] The beneficial effects of the present invention are that, compared with the prior art, at least the method and device proposed by the present invention realize reactive power control and harmonic suppression in offshore wind power harmonic control projects; SVG itself has good reactive power compensation capability, and through the integrated harmonic suppression function, it can provide dynamic reactive power compensation and real-time harmonic suppression at the same time. This comprehensive compensation capability is crucial to improving the stability and reliability of the power system; it can effectively reduce the harmonic content in the power grid, improve the power factor, and improve the quality of power.

[0040] Moreover, the fast response characteristics of power electronics can be used to track and compensate for reactive power and harmonics in real time, providing a faster response time. By implementing the harmonic suppression function on SVG, the number of devices that need to be installed can be reduced, the system design can be simplified, and the cost can be reduced.

[0041] In addition, the particle swarm algorithm is used to optimize the control parameters of the harmonic control loop, and the parameters of the control loop are adaptively adjusted, which has good dynamic response capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a harmonic control method for an offshore wind power static reactive generator proposed by the present invention;

[0043] Figure 2 It is a logical schematic diagram of the harmonic control method in an embodiment of the present invention. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only embodiments of a part of the present invention, rather than all embodiments. Based on the spirit of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work belong to the protection scope of the present invention.

[0045] The invention proposes a harmonic control method for an offshore wind power static VAR generator, wherein the control of the static VAR generator includes symmetrical reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shift PWM; Figure 1 As shown, including:

[0046] Step 1: Obtain the current command and harmonic currents of the static VAR generator.

[0047] Specifically, the input of the entire SVG control system is the DC voltage of each phase module, the three-phase voltage and current of the device and system (i.e., the test point), and the three-phase current of the load. The output is the desired three-phase modulation voltage.

[0048] The current instructions of the static VAR generator include: reactive current instructions and active current instructions;

[0049] The reactive power actual value and reactive power reference value of the static VAR generator are obtained, and the reactive current instruction is determined based on the symmetrical reactive closed-loop control method. Figure 2 As shown, the symmetrical reactive closed-loop control has a control mode selection function, and the control modes that can be realized include but are not limited to: fixed reactive power control mode, fixed system voltage control mode, fixed line voltage control mode, and fixed power factor control mode. Moreover, in various control modes, the deviation between the actual reactive power value and the reactive power reference value is used as the input of the PI loop, so as to calculate and output the symmetrical reactive current command I QA ,I QB ,I QC ;

[0050] The active power actual value and active power reference value of the static VAR generator are obtained, and the active current command is determined based on the active closed-loop control method. Figure 2 As shown, the active closed-loop control outputs the active current command I PA ,I PB ,I PC ;

[0051] Reactive current command I QA ,I QB ,I QC With active current command I PA ,I PB ,I PC The sum of the current command I of the static VAR generator a_ref ,I b_ref ,I c_ref .

[0052] The harmonic current orders of the static VAR generator include but are not limited to: 3, 5, 7, 11, and 13.

[0053] Step 2: When it is detected that each harmonic current of the static VAR generator is greater than a threshold value, a particle swarm algorithm is used to adjust the parameters of the PI closed-loop control, and a compensation current of each harmonic current is obtained based on the PI closed-loop control.

[0054] In the embodiment, the start condition of the harmonic control mode is that the 3rd, 5th, 7th, 11th and 13th harmonic currents of the static VAR generator are greater than a set threshold; wherein the threshold is determined according to the limit value of harmonic current in national and industry standards.

[0055] Specifically, the positive-sequence dq component and the negative-sequence dq component of each harmonic current are extracted; according to the positive-sequence dq component of each harmonic current, the positive-sequence compensation current of each harmonic current is obtained based on the PI closed-loop control; according to the negative-sequence dq component of each harmonic current, the negative-sequence compensation current of each harmonic current is obtained based on the PI closed-loop control;

[0056] Among them, the parameters of PI closed-loop control include the proportional coefficient K P And the integral action coefficient K I .

[0057] In the prior art, the parameters of PI closed-loop control are usually determined by modeling simulation, and this method often needs to rely on experience to give the numerical values ​​of the parameters. However, when the harmonic currents of each order change, the parameters of the PI closed-loop control determined by the simulation cannot be adjusted dynamically, and thus cannot adapt to the dynamic changes in the magnitude of each harmonic, resulting in a decrease in the effect of the PI closed-loop control. Therefore, the compensation current of each harmonic current of the static VAR generator obtained by the PI control loop determined by the existing parameter setting method cannot achieve an accurate harmonic suppression effect of the static VAR generator, and the output current still carries harmonics, resulting in poor power quality. Even this under-compensation and over-compensation state will make the modulation voltage inaccurate, thereby affecting the reactive power output of the static VAR generator and affecting the reactive compensation of the power grid. Therefore, the dynamic setting of the parameters of the PI closed-loop control based on the magnitude of each harmonic current is a key link in improving the harmonic control of the offshore wind power static VAR generator and ensuring the reactive compensation and power quality of the power grid.

[0058] Specifically, the particle swarm algorithm is used to dynamically optimize the parameters of the PI closed-loop control, including:

[0059] In the particle swarm algorithm, each particle in the population flies at a certain speed in the D-dimensional search space, x i =(x i1 ,x i2 ,…,x id ,…,x iD ) T is the position vector of particle i, where x idis the d-th dimension component of the position vector of particle i, d = 1, 2, …, D; V i =(V i1 ,V i2 ,…,V id ,…,V iD ) T is the velocity vector of particle i, where V id is the d-th component of the velocity vector of particle i; P i =(P i1 ,P i2 ,…,P id ,…,P iD ) T is the individual optimal position vector of particle i, where P id is the d-th dimension component of the individual optimal position vector of particle i; P g =(P g1 ,P g2 ,…,P gd ,…,P gD ) T is the global optimal position vector searched by the population, where P gd is the d-th dimension component of the global optimal position vector of the population; i = 1, 2, ..., N, N is the number of particles in the population; when the particle swarm algorithm is started, the particle swarm is initialized, including: initializing the position vector, velocity vector, search space dimension, learning factor, individual optimal position vector and global optimal position vector of each particle.

[0060] In the present invention, the proportional coefficient K of the PI closed-loop control is P And the integral action coefficient K I is the member variable of each particle in the population, then the search dimension is 2, and the position vector of particle i is is the proportional coefficient K in particle i P location, is the integral action coefficient K in particle i I The velocity vector of particle i is is the proportional coefficient K in particle i P speed, is the integral action coefficient K in particle i I speed.

[0061] The present invention proposes to take the minimization of the sum of the harmonic currents after harmonic control as the objective function and establish an improved fitness function. The improved fitness function satisfies the following relationship:

[0062]

[0063] Where Ω is the search space of PI closed-loop control parameters, KP is the proportional coefficient of PI closed-loop control, K I is the integral action coefficient of PI closed-loop control, J(K P ,K I ) is the proportional coefficient K in the particle P And the integral action coefficient K I The fitness function, j = 3, 5, 7, 11, ..., j is the order of the harmonic current of the static VAR generator, α j is the suppression weight of the jth harmonic current set under harmonic control, i dj ,I qj are the d-axis component and q-axis component of the j-th harmonic current, respectively, and t is the duration of harmonic control;

[0064] It is the square value of each harmonic current after harmonic control;

[0065] The improved fitness function is used to generate fitness values ​​to update the inertia weights. The inertia weights are adaptively updated according to the particle fitness values, so that particles with good fitness values ​​tend to do "local fine mining" near the current optimal solution, and particles with poor fitness values ​​use a larger step size to "roughly explore the breadth of the solution space" in order to have the opportunity to discover new global solutions. This allows the entire particle population to maintain better diversity and good convergence characteristics. The iterative update process of the inertia weight is expressed as:

[0066]

[0067] In the formula, w k is the inertia weight in the kth iteration, w min 、w max are the minimum and maximum values ​​of the inertia weight, J avg , J min are the average and minimum fitness values ​​of the entire particle group at present; J i is the current fitness value of particle i.

[0068] As the number of iterations increases, the sum of the harmonic currents after harmonic control decreases, and the fitness value decreases. The decrease in fitness value causes the inertia weight to decrease.

[0069] Compare the fitness value of the particle at the current position with the fitness value of the individual optimal position. If the fitness value at the current position is better, the current position is used as the updated individual optimal position, and the updated individual optimal position corresponding to the best fitness value is used as the updated global optimal position.

[0070] The iterative update process of the d-th dimension component of the velocity vector and position vector of particle i is expressed as:

[0071]

[0072] In the formula, is the d-th component of the velocity vector of particle i in the k-th iteration, is the d-th dimension component of the individual optimal position vector of particle i in the k-th iteration, is the d-th component of the position vector of particle i in the k-th iteration, is the d-th dimension component of the global optimal position vector of the population in the k-th iteration, is the d-th component of the position vector of the population in the k-th iteration, w k is the inertia weight in the kth iteration, c1 and c2 are learning factors, and r1 and r2 are random numbers in the range of (0,1).

[0073] During the iterative update process of the particle's velocity vector and position vector, the following two constraints are met at the same time:

[0074] 1) In the kth iteration, the d-th component of the velocity vector of particle i Constrained within the speed range [V min ,V max ]Inside, V min 、V max are the lower and upper limits of the speed respectively; when season when season

[0075] 2) In the kth iteration, the search space of the PI closed-loop control parameters satisfies the following relationship:

[0076]

[0077] Where, L h (K P ,K I ) is the amplitude margin corresponding to the search space of the PI closed-loop control parameters when the system is stable, dB is the signal gain unit, γ(K P ,K I ) is the phase margin corresponding to the search space of the PI closed-loop control parameters when the system is stable;

[0078] Under the joint constraints of the above speed range and search space, not only the iterative convergence is accelerated, but also the parameters of the PI closed-loop control meet the system stability requirements.

[0079] Step 3: Use the compensation current of each harmonic current to correct the current command of the static VAR generator to obtain a corrected current command.

[0080] like Figure 2 As shown, the current command I of the static VAR generator a_ref ,I b_ref ,I c_ref The sum of the compensation currents HarmA, HarmB, and HarmC of each harmonic current constitutes the corrected current instruction for harmonic control, and the device current sampling value I is introduced. a ,I b ,I c As negative feedback to avoid over-compensation of harmonic current, the sum of the corrected current command and the device current sampling value is used as the input signal of the current inner loop control; the modulation voltage W output by the current inner loop control a_Calc 、V b_Calc 、V c_Calc , after carrier phase-shift PWM, the trigger signal of the static VAR generator is obtained.

[0081] The present invention also proposes a harmonic control device for an offshore wind power static VAR generator. The control of the static VAR generator includes symmetrical reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shift PWM. The harmonic control device includes:

[0082] An acquisition module is used to obtain current instructions and harmonic currents of a static VAR generator;

[0083] A compensation current generation module is used to adjust the parameters of the PI closed-loop control by using a particle swarm algorithm when it is detected that the harmonic current of the static VAR generator is greater than a threshold value, and obtain a compensation current of the harmonic current based on the PI closed-loop control;

[0084] The current instruction correction module is used to correct the current instruction of the static VAR generator by using the compensation current of the harmonic current to obtain the corrected current instruction.

[0085] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0086] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0087] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0088] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0089] 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 it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A harmonic control method for an offshore wind power static VAR generator, wherein the control of the static VAR generator includes symmetrical reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shift PWM, characterized in that: include: Obtain current command and harmonic current of static VAR generator; When it is detected that the harmonic current of the static VAR generator is greater than the threshold, the particle swarm algorithm is used to adjust the parameters of the PI closed-loop control, and the compensation current of the harmonic current is obtained based on the PI closed-loop control; The current command of the static VAR generator is corrected by using the compensation current of the harmonic current to obtain a corrected current command.

2. The harmonic control method for offshore wind power static VAR generator according to claim 1 is characterized in that: The current instructions of the static VAR generator include: reactive current instructions and active current instructions; The harmonic current orders of the static VAR generator include: 3, 5, 7, 11, and 13.

3. The harmonic control method for offshore wind power static VAR generator according to claim 1 is characterized in that: The threshold is determined based on the limit values ​​for harmonic current in national and industry standards.

4. The harmonic control method for offshore wind power static VAR generator according to claim 1 is characterized in that: The parameters of PI closed-loop control include the proportional coefficient K P And the integral action coefficient K I .

5. The harmonic control method for offshore wind power static VAR generator according to claim 4 is characterized in that: The particle swarm algorithm is used to adjust the parameters of PI closed-loop control, including: The proportional coefficient K of PI closed loop control P And the integral action coefficient K I is the member variable of each particle in the population, the dimension of the search space is 2, and the position vector of particle i is is the proportional coefficient K in particle i P location, is the integral action coefficient K in particle i I The velocity vector of particle i is is the proportional coefficient K in particle i P speed, is the integral action coefficient K in particle i I speed; i = 1, 2, ..., N, N is the number of particles in the population; Initialize the position vector, velocity vector, search space dimension, learning factor, individual optimal position vector and global optimal position vector of each particle in the search space Ω of the PI closed-loop control parameters.

6. The harmonic control method for offshore wind power static VAR generator according to claim 4 is characterized in that: The particle swarm algorithm is used to adjust the parameters of the PI closed-loop control, including: Taking the minimization of the sum of harmonic currents after harmonic control as the objective function, an improved fitness function is established, and the improved fitness function satisfies the following relationship: Where Ω is the search space of PI closed-loop control parameters, K P is the proportional coefficient of PI closed-loop control, K I is the integral action coefficient of PI closed-loop control, J(K P ,K I ) is the proportional coefficient K in the particle P and the fitness function of the integral action coefficient KI, j = 3, 5, 7, 11, ..., j is the order of the harmonic current of the static VAR generator, α j is the suppression weight of the jth harmonic current set under harmonic control, I dj ,I qj are the d-axis component and q-axis component of the j-th harmonic current, respectively, and t is the duration of harmonic control; It is the square value of each harmonic current after harmonic control.

7. The harmonic control method for offshore wind power static VAR generator according to claim 6 is characterized in that: The improved fitness function is used to generate the fitness value to update the inertia weight. The iterative update process of the inertia weight is expressed as: In the formula, w k is the inertia weight in the kth iteration, w min 、w maz are the minimum and maximum values ​​of the inertia weight, J avg , J min are the average and minimum fitness values ​​of the particle group, J i is the fitness value of particle i.

8. The harmonic control method for offshore wind power static VAR generator according to claim 7 is characterized in that: The iterative update process of the d-th dimension component of the velocity vector and position vector of particle i is expressed as: In the formula, is the d-th component of the velocity vector of particle i in the k-th iteration, is the d-th dimension component of the individual optimal position vector of particle i in the k-th iteration, is the d-th component of the position vector of particle i in the k-th iteration, is the d-th dimension component of the global optimal position vector of the population in the k-th iteration, is the d-th component of the position vector of the population in the k-th iteration, w k is the inertia weight in the kth iteration, c1 and c2 are learning factors, and r1 and r2 are random numbers in the range of (0,1).

9. The harmonic control method for offshore wind power static VAR generator according to claim 8 is characterized in that: During the iterative update process of the particle's velocity vector and position vector, the following two constraints are met at the same time: 1) In the kth iteration, the d-th component of the velocity vector of particle i Constrained within the speed range [V min ,V max ]Inside, V min 、V max are the lower and upper limits of the speed respectively; when season when season 2) In the kth iteration, the search space of the PI closed-loop control parameters satisfies the following relationship: Where, L h (K P ,K I ) is the amplitude margin corresponding to the search space of the PI closed-loop control parameters when the system is stable, dB is the signal gain unit, γ(K P ,K I ) is the phase margin corresponding to the search space of PI closed-loop control parameters when the system is stable.

10. A harmonic control device for an offshore wind power static VAR generator, wherein the control of the static VAR generator includes symmetrical reactive closed-loop control, active closed-loop control, current inner-loop control and carrier phase-shift PWM, characterized in that: The harmonic control device includes: An acquisition module is used to obtain current instructions and harmonic currents of a static VAR generator; A compensation current generation module is used to adjust the parameters of the PI closed-loop control by using a particle swarm algorithm when it is detected that the harmonic current of the static VAR generator is greater than a threshold value, and obtain a compensation current of the harmonic current based on the PI closed-loop control; The current instruction correction module is used to correct the current instruction of the static VAR generator by using the compensation current of the harmonic current to obtain the corrected current instruction.

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