Novel oscillation damping optimization control device and method based on quantum annealing algorithm

Abstract

The invention discloses a novel oscillation damping optimization control device and method based on a quantum annealing algorithm, and the device comprises an analog quantity collection module which is connected with a bus and an analog-to-digital conversion module, completes the collection of the voltage analog quantity of an AC bus, and completes the analog-to-digital conversion. The band elimination filter, the band pass filter, the proportional phase shift module and the amplitude limiting module form a multi-channel damping controller. And the quantum annealing intelligent optimization module completes optimization of proportion and compensation parameters and compensates current for the additional parallel converter. And finally, injecting the output suppression current of the additional parallel converter into the bus to complete novel oscillation suppression. According to the invention, the coordination control effect of the multi-channel damping controller can be fully exerted, the coordination optimization of the parameters of the multi-channel damping controller is realized by setting different dynamic damping ratio thresholds, and the optimal suppression of multi-modal oscillation is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of novel power system stability control, and in particular to a novel oscillation damping optimization control device and method based on a quantum annealing algorithm. Background Art

[0002] In recent years, with the continuous development of wind power and photovoltaic renewable energy in the power system, the power system has also shown a "double high" feature. A large number of power electronic devices are prone to "mechanical-electrical-magnetic" interactions with the power grid, which can easily cause new oscillations in the power system with frequencies varying from several Hz to several kHz.

[0003] At present, the methods for suppressing broadband oscillations can be roughly divided into two categories: oscillation source and additional damping control. When broadband oscillation occurs in the power system, the system exhibits a "negative damping" effect. The additional damping controller is used to provide "positive damping" to the system, thereby achieving the effect of suppressing frequency oscillation. In order to improve the suppression efficiency and reduce the amount of calculation, it is possible to consider combining intelligent algorithms with damping control.

[0004] In the invention patent with announcement number CN115360697A, a method for suppressing subsynchronous oscillations in the power supply system is proposed, and the parameters of the DC additional damper are optimized based on the swarm intelligence optimization algorithm. However, it is mainly aimed at suppressing subsynchronous oscillations caused by equipment such as bridge cranes, automatic guided vehicle charging equipment and rail cranes, and does not involve new energy power generation systems. In the invention patent with announcement number CN109347097B, a subsynchronous oscillation suppression strategy for a doubly fed wind power system based on an improved particle swarm optimization algorithm is proposed, which mainly superimposes the output signal of the additional damping controller on the grid-side converter control of the wind power system, but only considers the subsynchronous oscillations caused by the single factor of wind power. Taking into account the existence of photovoltaic and wind power in the power system, it is urgent to explore broadband oscillation suppression optimization methods to avoid large calculations and falling into local optimality. Summary of the invention

[0005] The present invention aims to solve one of the technical problems in the related art at least to a certain extent.

[0006] The present invention proposes a novel oscillation damping optimization control device based on quantum annealing algorithm, which is not limited to the range of oscillation frequency and can achieve wide-band and multi-modal oscillation suppression. It can give full play to the coordinated control function of the multi-channel damping controller, realize the coordinated optimization of the multi-channel damping controller parameters by setting different dynamic damping ratio thresholds, and achieve the optimal suppression of multi-modal oscillations.

[0007] Another object of the present invention is to propose a novel oscillation damping optimization control method based on quantum annealing algorithm.

[0008] To achieve the above-mentioned object, the present invention proposes, on one hand, a novel oscillation damping optimization control device based on a quantum annealing algorithm, an analog quantity acquisition module, an analog-to-digital conversion module, a band-stop filter module, a band-pass filter module, a proportional phase shift module, a limiting module, a quantum annealing intelligent optimization module and an additional parallel converter;

[0009] The analog quantity acquisition module is connected to the bus and the analog-to-digital conversion module to collect the voltage analog quantity of the AC bus and complete the analog-to-digital conversion;

[0010] A multi-channel damping controller is formed by a band-stop filter, a band-pass filter, a proportional phase shift module and a limiting module;

[0011] The quantum annealing intelligent optimization module is used to optimize the proportion and compensation parameters, compensate the current for the additional parallel converter, and inject the output suppression current of the additional parallel converter into the bus to complete the new oscillation suppression.

[0012] The novel oscillation damping optimization control device based on the quantum annealing algorithm in the embodiment of the present invention may also have the following additional technical features:

[0013] In one embodiment of the present invention, determining the objective function to be optimized of the damping controller includes:

[0014] Determine the transfer function of the link to be optimized, expressed as:

[0015]

[0016] In the formula, k pi is the proportionality coefficient, T pi is the compensation coefficient, m is the number of series compensation links;

[0017] Identify the oscillation mode of the open-loop system without a damping controller, and combine the oscillation mode of the open-loop system with the transfer function of the damping controller to be optimized;

[0018] The oscillation mode of the open-loop system is expressed as:

[0019] λ i =σ i ±jω i (i=1,2,…,n)(2)

[0020] The simplified transfer function of the open-loop system with oscillation mode is expressed as:

[0021] G o =s-λ i (i=1,2,…,n)(3)

[0022] The transfer function of the open-loop oscillation mode after the damping controller is expressed as:

[0023] G c =G i G o (4)

[0024]

[0025] The transfer function of the open-loop oscillation mode after the damping controller is normalized and the corresponding characteristic equation is extracted, which is expressed as:

[0026]

[0027] Solve the characteristic root corresponding to the closed-loop characteristic equation and calculate the damping size that the damping controller can provide, expressed as:

[0028]

[0029] Calculate the closed-loop damping corresponding to the oscillation mode, expressed as:

[0030]

[0031] In the formula, σ i is the damping of the oscillation mode corresponding to the undamped controller;

[0032] Calculate the closed-loop damping ratio and determine the objective function of the optimization function, which is expressed as:

[0033]

[0034] In one embodiment of the present invention, a multi-objective damping control parameter coordinated optimization model is established, including:

[0035] Taking the maximization of the target mode damping ratio as the optimization goal, a multi-objective damping control parameter coordinated optimization model is established, which is expressed as:

[0036] f=max(η i ξ ci ) (10)

[0037] Where η i is the inertia coefficient of target mode i, indicating the degree of attention paid to different oscillation modes; ξ i is the closed-loop damping ratio of target mode i;

[0038] For sub / supersynchronous oscillation signals, the objective function is established and expressed as:

[0039] f=max{ξ c1 ,ξ c2 ,…,ξ ci} (11)

[0040] The constraints for the coordinated optimization of multiple oscillation modes are established as follows:

[0041]

[0042] Establish the damping controller objective function. For the objective function f(x) of the optimization algorithm and the nonlinear constraint condition st, it can be expressed as:

[0043]

[0044] Where f is the defined performance function, i.e., the objective function, n is the number of the corresponding oscillation mode, i is the number of the corresponding oscillation mode, and σ i is the closed-loop mode damping of the i-th oscillation mode, k i is the gain coefficient of oscillation mode i, k imin is the upper limit of the gain coefficient of oscillation mode i, k imax is the upper limit of the gain coefficient of oscillation mode i; T i is the time constant of oscillation mode i, T imin is the lower limit of the time constant of oscillation mode i, T imax is the upper limit of the time constant of oscillation mode i;

[0045] Improve the objective function, expressed as:

[0046]

[0047] In the formula, ξ i =f(k i ,T pi ) is about k i and T pi Function of η i =(1 / k pi )(i=1,2,3,…,n) is the inertia coefficient corresponding to the damping ratio of the oscillation frequency.

[0048] In one embodiment of the present invention, a novel oscillation suppression based on a damping optimization control device comprises:

[0049] Collect AC voltage signals from the busbar and determine the grid phase information through a phase-locked loop;

[0050] Calculate the active power setting value required for outer loop control according to the grid phase information and generate corresponding control signals;

[0051] Inputting the control signal into a multi-channel damping controller to generate an optimized damping control signal, and superimposing the damping control signal onto an inner loop current control signal to generate an optimized current control signal;

[0052] The optimized current control signal is converted into a switching signal using pulse width modulation technology;

[0053] According to the received switching signal, the additional parallel converter is controlled to generate corresponding current output and injected into the bus to complete the new oscillation suppression.

[0054] To achieve the above object, the present invention proposes a novel oscillation damping optimization control method based on a quantum annealing algorithm, comprising:

[0055] Get the controller parameters to be optimized;

[0056] simulating quantum states in a quantum system according to controller parameters to be optimized;

[0057] The damping ratio is used as the objective function to characterize the state potential energy of the quantum in the quantum system, and the energy of the quantum system is used to determine the size of the damping ratio under the selected parameters to achieve parameter optimization of the damping controller.

[0058] Furthermore, the method further comprises:

[0059] Using path integral Monte Carlo, the problem is mapped into a quantum Hamiltonian function H qa (t) The energy expression of the Hamiltonian operator Hamiltonian, find the variable combination that minimizes the value of H(t), and find the optimal value, which is expressed as:

[0060] H qa (t) = H pot (t)+H kin (t) (15)

[0061] Where, the quantum Hamiltonian function H qa (t) represents the evaluation function in the quantum annealing algorithm, H pot (t) represents the state potential energy, corresponding to the evaluation function of the simulated annealing algorithm, H kin (t) represents kinetic energy,

[0062] Determine the relationship between the quantum Hamiltonian function and the objective function of the damping controller, which is expressed as:

[0063] H qa (k,τ)=H pot (k,τ)+H kin (k,τ) (16)

[0064] The improvement is expressed as:

[0065] H qa (k,τ)=η i ξ ci (k pi ,τ i)+H kin (k pi ,τ i ) (17)

[0066] In the formula, {ξ ci =f(k pi ,T pi )}={ξ ci =f(k pi ,τ i )}; The optimal time constant of the damping controller is represented by τ;

[0067] The objective function of the optimization problem is mapped to the Hamiltonian energy function of the quantum system, and damping optimization control is implemented based on the quantum annealing algorithm.

[0068] The novel oscillation damping optimization control device and method based on the quantum annealing algorithm in the embodiment of the present invention aims at the characteristic that different oscillation modes correspond to different attenuation speeds, and gives corresponding weighted inertia coefficients to different oscillation modes in the objective function to highlight the attention paid to different oscillation modes, so as to achieve the effect of rapid attenuation of different oscillation modes.

[0069] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The above and / or additional aspects and advantages of the present invention will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0071] Figure 1 is a structural diagram of a novel oscillation damping optimization control device based on a quantum annealing algorithm according to an embodiment of the present invention;

[0072] Figure 2 is a structural diagram of a novel oscillation damping optimization control based on a quantum annealing algorithm according to an embodiment of the present invention;

[0073] Figure 3 is a schematic diagram of a damping optimization control device for novel oscillation suppression according to an embodiment of the present invention;

[0074] Figure 4 This is a simulation result diagram of a new oscillation damping optimization control based on a quantum annealing algorithm according to an embodiment of the present invention. DETAILED DESCRIPTION

[0075] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0076] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0077] The following describes a novel oscillation damping optimization control device and method based on a quantum annealing algorithm according to an embodiment of the present invention with reference to the accompanying drawings.

[0078] Figure 1 is a structural diagram of a novel oscillation damping optimization control device based on a quantum annealing algorithm according to an embodiment of the present invention, such as Figure 1 As shown, the connection method of this system is as follows:

[0079] 1. (1) is connected to the bus, and (2) is connected to (1) to complete the acquisition of the voltage analog quantity of the AC bus and complete the analog-to-digital conversion.

[0080] 2. (3) is connected to (2), (4) is connected to (2), (5) is connected to (3), (6) is connected to (4), (7) is connected to (5), and (8) is connected to (6), thereby completing the extraction of the fundamental wave signal, the subsynchronous oscillation signal, and the supersynchronous oscillation signal.

[0081] 3. (9) is connected to (7), (10) is connected to (8), (11) is connected to (9), and (11) is connected to (10), so as to realize the optimization of the ratio and compensation parameters based on the quantum annealing algorithm.

[0082] 4. (12) is connected to (9), (13) is connected to (10), and the limiting module is superimposed to output the compensation current.

[0083] 5. (14) is connected to (12), and (14) is connected to (13), and the current signal is superimposed on the double closed-loop control to complete the operation of the additional parallel converter.

[0084] 6. (14) is connected to the bus, and the output suppression current of the additional parallel converter is injected into the bus to complete the new oscillation suppression.

[0085] Figure 2 This is a novel oscillation damping optimization control structure diagram based on the quantum annealing algorithm of the present invention, based on which, the following controls are included:

[0086] Furthermore, the objective function to be optimized of the multi-channel damping controller is determined as follows:

[0087] Step 1: Determine the transfer function of the link to be optimized, which can be expressed as:

[0088]

[0089] In the formula, k pi is the proportionality coefficient, T pi is the compensation coefficient, and m is the number of series compensation links.

[0090] Step 2: Identify the oscillation mode of the open-loop system without a damping controller, and combine the oscillation mode of the open-loop system with the transfer function of the link to be optimized of the damping controller.

[0091] The oscillation mode of the open-loop system can be expressed as:

[0092] λ i =σ i ±jω i (i=1,2,…,n)(2)

[0093] The simplified transfer function of the open-loop system with oscillation mode can be expressed as:

[0094] G o =s-λ i (i=1,2,…,n)(3)

[0095] The transfer function of the open-loop oscillation mode after the damping controller can be expressed as:

[0096] G c =G i G o (4)

[0097]

[0098] Step 3: Normalize the transfer function of the open-loop oscillation mode after the damping controller and extract the corresponding characteristic equation, which can be expressed as:

[0099]

[0100] Step 4: Solve the characteristic root corresponding to the closed-loop characteristic equation and calculate the damping size that the damping controller can provide, which can be expressed as:

[0101]

[0102] Step 5: Calculate the closed-loop damping corresponding to the oscillation mode, which can be expressed as:

[0103]

[0104] In the formula, σ i is the damping of the oscillation mode corresponding to the undamped controller.

[0105] Step 6: Calculate the closed-loop damping ratio and determine the objective function of the optimization function, which can be expressed as:

[0106]

[0107] Furthermore, a multi-objective damping control parameter coordinated optimization model is established. According to the regular distribution of the damping ratio to the oscillation attenuation speed, an inertia coefficient is further added to the different oscillation modes in the objective function to improve the response speed of the damping controller, thereby achieving coordinated optimization between different oscillation modes and multi-objective damping control parameters. The steps are as follows:

[0108] Step 1: Taking the maximization of the target mode damping ratio as the optimization goal, a multi-objective damping control parameter coordinated optimization model is established, which can be expressed as:

[0109] f=max(η i ξ ci ) (10)

[0110] Where η i is the inertia coefficient of target mode i, indicating the degree of attention paid to different oscillation modes; ξ i is the closed-loop damping ratio of target mode i.

[0111] Step 2: For the sub / super synchronous oscillation signal, establish the objective function, which can be expressed as:

[0112] f=max{ξ c1 ,ξ c2 ,…,ξ ci} (11)

[0113] Step 3: Establish the constraints for coordinated optimization of multiple oscillation modes, which can be expressed as:

[0114]

[0115] Step 4: Establish the objective function of the damping controller to increase the damping ratio and make the oscillation frequency decay rapidly. The objective function f(x) of the optimization algorithm and the nonlinear constraint condition st can be expressed as:

[0116]

[0117] Where f is the defined performance function, i.e., the objective function, n is the number of the corresponding oscillation mode, i is the number of the corresponding oscillation mode, and σ i is the closed-loop mode damping of the i-th oscillation mode, k i is the gain coefficient of oscillation mode i, k imin is the upper limit of the gain coefficient of oscillation mode i, k imax is the upper limit of the gain coefficient of oscillation mode i; T iis the time constant of oscillation mode i, T imin is the lower limit of the time constant of oscillation mode i, T imax is the upper limit of the time constant of oscillation mode i.

[0118] Step 5: Realize the coordinated optimization of different oscillation modes and multi-objective damping control parameters, so that different oscillation modes can achieve a larger attenuation speed, and further improve the objective function, which can be expressed as:

[0119]

[0120] In the formula, ξ i =f(k i ,T pi ) is about k i and T pi The function of the damping ratio threshold is different for different oscillation modes. The low oscillation mode has a slow decay speed, so a larger damping ratio threshold is set. η i =(1 / k pi )(i=1,2,3,…,n) is the inertia coefficient corresponding to the damping ratio of the oscillation frequency.

[0121] Figure 3 For damping-optimized control devices for novel oscillation suppression, such as Figure 3 As shown, a new type of oscillation suppression based on a damping optimization control device includes: collecting an AC voltage signal from a bus and determining grid phase information through a phase-locked loop; performing an outer loop control calculation on the grid phase information to obtain a required active power setting value and generating a corresponding control signal; inputting the control signal into a multi-channel damping controller to generate an optimized damping control signal, and superimposing the damping control signal on an inner loop current control signal to generate an optimized current control signal; converting the optimized current control signal into a switching signal using pulse width modulation technology; and controlling an additional parallel converter to generate a corresponding current output according to the received switching signal, and injecting the current output into the bus to complete the new type of oscillation suppression.

[0122] According to the novel oscillation damping optimization control device based on the quantum annealing algorithm according to the embodiment of the present invention, it is not limited to the scope of action of the oscillation frequency, and can achieve wide-band and multi-modal oscillation suppression. It can give full play to the coordinated control function of the multi-channel damping controller, and realize the coordinated optimization of the parameters of the multi-channel damping controller by setting different dynamic damping ratio thresholds, so as to achieve the optimal suppression of multi-modal oscillations. In view of the different attenuation speeds corresponding to different oscillation modes, the corresponding weighted inertia coefficients of different oscillation modes are given in the objective function to highlight the attention paid to different oscillation modes, so as to achieve the effect of rapid attenuation of different oscillation modes. The "tunneling" effect of quantum annealing can be used to quickly and accurately find the optimal value of the parameter to be optimized, so as to achieve the optimization of the objective function. By taking the maximum value of the damping ratio as the optimization target for the dynamic characteristics reflecting the stability of the system, the damping characteristics of the system are optimized, and the suppression of system oscillation is further achieved.

[0123] In order to implement the above embodiment, this embodiment also provides a novel oscillation damping optimization control method based on a quantum annealing algorithm, including:

[0124] Get the controller parameters to be optimized;

[0125] simulating quantum states in a quantum system according to controller parameters to be optimized;

[0126] The damping ratio is used as the objective function to characterize the state potential energy of the quantum in the quantum system, and the energy of the quantum system is used to determine the size of the damping ratio under the selected parameters to achieve parameter optimization of the damping controller.

[0127] Furthermore, Path Integral Monte Carlo (PIMC) is used to map the problem into a quantum Hamiltonian function H qa The energy expression of (t) (Hamiltonian operator) is used to find the variable combination that minimizes the value of H(t), and then the optimal value is obtained, which can be expressed as:

[0128] H qa (t) = H pot (t)+H kin (t) (15)

[0129] Where, the quantum Hamiltonian function H qa (t) represents the evaluation function in the quantum annealing algorithm, H pot (t) represents the state potential energy, corresponding to the evaluation function of the simulated annealing algorithm, H kin (t) represents kinetic energy, to which quantum fluctuations are added (this value is initially large and then slowly decreases to 0 according to a certain schedule).

[0130] Furthermore, the relationship between the quantum Hamiltonian function and the objective function of the damping controller can be expressed as:

[0131] H qa (k,τ)=H pot (k,τ)+H kin (k,τ) (16)

[0132] Further improvement can be expressed as:

[0133] H qa (k,τ)=η i ξ ci (k pi ,τ i )+H kin (k pi ,τ i ) (17)

[0134] In the formula, {ξ ci =f(k pi ,T pi )}={ξ ci =f(k pi ,τ i )}; To avoid conflict with the temperature T in the quantum annealing algorithm, the optimization time constant of the damping controller is represented by τ.

[0135] Furthermore, the objective function of the optimization problem is mapped to the Hamiltonian energy function of the quantum system, and damping optimization control is achieved based on the quantum annealing algorithm.

[0136] Specifically, Figure 4 This is a simulation result diagram of a new oscillation damping optimization control based on a quantum annealing algorithm according to an embodiment of the present invention.

[0137] According to the novel oscillation damping optimization control method based on the quantum annealing algorithm according to the embodiment of the present invention, it is not limited to the scope of action of the oscillation frequency, and can achieve wide-band and multi-modal oscillation suppression. It can give full play to the coordinated control function of the multi-channel damping controller, and realize the coordinated optimization of the parameters of the multi-channel damping controller by setting different dynamic damping ratio thresholds, so as to achieve the optimal suppression of multi-modal oscillations. In view of the different attenuation speeds corresponding to different oscillation modes, the corresponding weighted inertia coefficients of different oscillation modes are given in the objective function to highlight the attention paid to different oscillation modes, so as to achieve the effect of rapid attenuation of different oscillation modes. The "tunneling" effect of quantum annealing can be used to quickly and accurately find the optimal value of the parameter to be optimized to achieve the optimization of the objective function. By taking the maximum value of the damping ratio as the optimization target for the dynamic characteristics reflecting the stability of the system, the damping characteristics of the system are optimized, and the suppression of system oscillation is further achieved.

[0138] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0139] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

Claims

1. A novel oscillation damping optimization control device based on quantum annealing algorithm, characterized in that: include: Analog quantity acquisition module, analog-to-digital conversion module, band-stop filter module, band-pass filter module, proportional phase shift module, amplitude limiting module, quantum annealing intelligent optimization module and additional parallel converter; The analog quantity acquisition module is connected to the bus and the analog-to-digital conversion module to collect the voltage analog quantity of the AC bus and complete the analog-to-digital conversion; A multi-channel damping controller is formed by a band-stop filter, a band-pass filter, a proportional phase shift module and a limiting module; The quantum annealing intelligent optimization module is used to optimize the proportion and compensation parameters, compensate the current for the additional parallel converter, and inject the output suppression current of the additional parallel converter into the bus to complete the new oscillation suppression.

2. The device according to claim 1, characterized in that Determine the objective function to be optimized of the damping controller, including: Determine the transfer function of the link to be optimized, expressed as: In the formula, k pi is the proportionality coefficient, T pi is the compensation coefficient, m is the number of series compensation links; Identify the oscillation mode of the open-loop system without a damping controller, and combine the oscillation mode of the open-loop system with the transfer function of the damping controller to be optimized; The oscillation mode of the open-loop system is expressed as: l i =s i ±jω i (i=1,2,…,n)(2) The simplified transfer function of the open-loop system with oscillation mode is expressed as: G o =s-λ i (i=1,2,…,n)(3) The transfer function of the open-loop oscillation mode after the damping controller is expressed as: G c =G i G o (4) The transfer function of the open-loop oscillation mode after the damping controller is normalized and the corresponding characteristic equation is extracted, which is expressed as: Solve the characteristic root corresponding to the closed-loop characteristic equation and calculate the damping size that the damping controller can provide, expressed as: Calculate the closed-loop damping corresponding to the oscillation mode, expressed as: In the formula, σ i is the damping of the oscillation mode corresponding to the undamped controller; Calculate the closed-loop damping ratio and determine the objective function of the optimization function, which is expressed as:

3. The device according to claim 1, characterized in that A multi-objective damping control parameter coordinated optimization model is established, including: Taking the maximization of the target mode damping ratio as the optimization goal, a multi-objective damping control parameter coordinated optimization model is established, which is expressed as: f=max(η i x ci ) (10) Where η i is the inertia coefficient of target mode i, indicating the degree of attention paid to different oscillation modes; ξ i is the closed-loop damping ratio of target mode i; For sub / supersynchronous oscillation signals, the objective function is established and expressed as: f=max{ξ c1 ,x c2 ,…,x ci } (11) The constraints for the coordinated optimization of multiple oscillation modes are established as follows: Establish the damping controller objective function. For the objective function f(x) of the optimization algorithm and the nonlinear constraint condition st, it can be expressed as: Where f is the defined performance function, i.e., the objective function, n is the number of the corresponding oscillation mode, i is the number of the corresponding oscillation mode, and σ i is the closed-loop mode damping of the i-th oscillation mode, k i is the gain coefficient of oscillation mode i, k imin is the upper limit of the gain coefficient of oscillation mode i, k imax is the upper limit of the gain coefficient of oscillation mode i; T i is the time constant of oscillation mode i, T imin is the lower limit of the time constant of oscillation mode i, T imax is the upper limit of the time constant of oscillation mode i; Improve the objective function, expressed as: In the formula, ξ i =f(k i ,T pi ) is about k i and T pi Function of η i =(1 / k pi )(i=1,2,3,…,n) is the inertia coefficient corresponding to the damping ratio of the oscillation frequency.

4. The device according to claim 1, characterized in that New oscillation suppression based on damping-optimized control, including: Collect AC voltage signals from the busbar and determine the grid phase information through a phase-locked loop; Calculate the active power setting value required for outer loop control according to the grid phase information and generate corresponding control signals; Inputting the control signal into a multi-channel damping controller to generate an optimized damping control signal, and superimposing the damping control signal onto an inner loop current control signal to generate an optimized current control signal; The optimized current control signal is converted into a switching signal using pulse width modulation technology; According to the received switching signal, the additional parallel converter is controlled to generate corresponding current output and injected into the bus to complete the new oscillation suppression.

5. A novel oscillation damping optimization control method based on quantum annealing algorithm, characterized in that: include: Get the controller parameters to be optimized; simulating quantum states in a quantum system according to controller parameters to be optimized; The damping ratio is used as the objective function to characterize the state potential energy of the quantum in the quantum system, and the size of the damping ratio under the selected parameters is determined by the energy size of the quantum system to achieve parameter optimization of the damping controller.

6. The method according to claim 5, characterized in that The method further comprises: Using path integral Monte Carlo, the problem is mapped into a quantum Hamiltonian function H qa (t) The energy expression of the Hamiltonian operator Hamiltonian, find the variable combination that minimizes the value of H(t), and find the optimal value, which is expressed as: H qa (t)=H pot (t)+H kin (t) (15) Where, the quantum Hamiltonian function H qa (t) represents the evaluation function in the quantum annealing algorithm, H pot (t) represents the state potential energy, corresponding to the evaluation function of the simulated annealing algorithm, H kin (t) represents kinetic energy, Determine the relationship between the quantum Hamiltonian function and the objective function of the damping controller, which is expressed as: H qa (k,τ)=H pot (k,τ)+H kin (k,t) (16) The improvement is expressed as: H qa (k,τ)=η i x ci (k pi ,t i )+H kin (k pi ,t i ) (17) In the formula, {ξ ci =f(k pi ,T pi )}={ξ ci =f(k pi ,τ i )}; The optimal time constant of the damping controller is represented by τ; The objective function of the optimization problem is mapped to the Hamiltonian energy function of the quantum system, and damping optimization control is implemented based on the quantum annealing algorithm.

Images