Photovoltaic inverter control parameter optimization and broadband oscillation suppression method based on seat head whale migration algorithm

Abstract

The invention discloses a photovoltaic inverter control parameter optimization and broadband oscillation suppression method based on a seathead whale migration algorithm, and the method comprises the steps: S1, building each subsystem model, and building a sequence impedance model of a photovoltaic inverter; s2, selecting to-be-optimized control parameters in the sequence impedance model, calculating normalized sensitivity at each frequency point by using a multi-frequency-point central difference method, and performing full-frequency-band analysis; the global sensitivity of each control parameter is obtained through a global sensitivity calculation formula, and then the optimization range of each to-be-optimized control parameter is given through the global sensitivity; and S3, on the basis of the optimization range of the to-be-optimized control parameters calculated based on the global sensitivity, optimizing the control parameters by adopting a sedan whale migration algorithm. By adopting the method, the capability of avoiding local optimum and effective convergence is improved, the optimized and given parameter values can be effectively matched with the impedance of the photovoltaic inverter and the impedance of the power grid, and the stability of the photovoltaic grid-connected system is improved.

Description

Technical Field

[0001] This invention relates to the field of power system optimization control technology, and in particular to a method for optimizing control parameters and suppressing wideband oscillations in photovoltaic inverters based on the humpback whale migration algorithm. Background Technology

[0002] With the increasing prevalence of the "high voltage and high efficiency" characteristics of new power systems, the problem of broadband oscillations (1Hz to 10kHz) caused by the interaction between power electronic equipment and the weak grid impedance during photovoltaic power generation system grid connection is becoming increasingly prominent. Broadband oscillations originate from the negative damping characteristics of the inverter within a wide frequency band, which can easily lead to grid current distortion, equipment disconnection, and even system collapse.

[0003] Impedance reshaping technology is a core method for suppressing the interactive resonance between power electronic devices and the power grid. Its purpose is to actively adjust the frequency domain characteristics of the converter's output impedance to achieve a stable match with the grid impedance, thereby improving the stability of the power grid system. Impedance reshaping can be achieved through controller parameter optimization and control structure optimization. Parameter optimization often relies on empirical adjustments, which can easily lead to a degraded dynamic response performance and a tendency to get trapped in local optima during multi-band resonance suppression. Existing methods lack a full-band sensitivity quantitative assessment of current loop control parameters, resulting in low efficiency and poor coordination in photovoltaic inverter parameter optimization, making it difficult to balance multi-band stability and dynamic performance. Therefore, it is essential to propose a method for optimizing photovoltaic inverter parameters across the entire frequency band. Summary of the Invention

[0004] The purpose of this invention is to provide a method for optimizing control parameters and suppressing broadband oscillations in photovoltaic inverters based on the humpback whale migration algorithm, so as to solve the problem of broadband oscillations caused by the dynamic interaction between the impedance characteristics of photovoltaic inverters and grid impedance in different frequency bands.

[0005] To achieve the above objectives, this invention provides a method for optimizing photovoltaic inverter control parameters and suppressing broadband oscillations based on the humpback whale migration algorithm, comprising the following steps:

[0006] S1. Based on the specific revenue situation of the actual photovoltaic grid-connected system, build models of various subsystems including photovoltaic power generation module, converter module and current loop control module, and establish the sequence impedance model of photovoltaic inverter.

[0007] S2. Select the control parameters to be optimized in the sequence impedance model, calculate the normalized sensitivity at each frequency point using the multi-frequency center difference method, and perform full-band analysis; obtain the global sensitivity of each control parameter through the global sensitivity calculation formula, and then give the optimization range of each of the control parameters to be optimized from the global sensitivity.

[0008] S3. Based on the optimization range of the control parameters to be optimized obtained from the global sensitivity calculation, the humpback whale migration algorithm is used to optimize the control parameters.

[0009] Preferably, step S1 includes:

[0010] S11. Construct an equivalent circuit model to simulate a photovoltaic grid-connected system. Select an ideal DC voltage source, series resistor, and capacitor to form a photovoltaic power generation model to simulate the DC power generated by the photovoltaic grid-connected system and the resistance of the photovoltaic modules.

[0011] S12. Establish a model of a three-phase bridge current source photovoltaic inverter and introduce a control structure for the power outer loop and the current inner loop.

[0012] S13. By establishing the sequence impedance model of the photovoltaic grid-connected system, the relationship between the parameters to be optimized and the impedance model is obtained.

[0013] Preferably, the sequence impedance model in step S13 includes a positive sequence impedance model and a negative sequence impedance model, which are represented as follows:

[0014] The positive-sequence impedance model is as follows:

[0015]

[0016] The negative sequence impedance model is as follows:

[0017]

[0018] In the formula, V p (s) represents the positive sequence voltage, I p (s) represents the positive sequence current, V n (s) represents the negative sequence voltage, I n (s) represents the negative sequence current, J represents the imaginary part of the complex variable, and L f 、V dc f1 and f1 represent the filter inductance on the grid-connected inverter side, the DC side voltage, and the base frequency, respectively, and K f K d G represents the voltage feedforward coefficient and the feedforward decoupling gain coefficient. v (s) is the voltage sampling function, G i (s) is the current sampling function, H i For the inner loop control parameters of the current, I dr , I qr These are the current reference values ​​along the d-axis and q-axis in the dq coordinate system. The subscripts p and n represent the positive and negative sequence, respectively, and s represents the Laplace operator. T PLL The parameters related to the phase-locked loop are represented, and V1 represents the fundamental voltage.

[0019] Preferably, step S2 includes:

[0020] S21. Based on the derived sequence impedance model, establish the photovoltaic inverter control parameter vector p = [k pi ,k ii ,K d ,K f ] T Nonlinear models;

[0021] S22. Using the sequence impedance model, the normalized sensitivity is approximately calculated using the central difference method. The calculation process covers the frequency band from 1Hz to 10kHz. 1000 points are taken at logarithmic intervals for full-band analysis to obtain the influence of control parameters on resonance characteristics.

[0022] S23. Establish the global sensitivity calculation equation based on the calculated full-band sensitivity.

[0023] Preferably, the nonlinear model in step S21 is:

[0024]

[0025] In the formula, Z p (p,ω) represents the inverter impedance, G i (ω) represents the current sampling function, G v (ω) represents the voltage sampling function, T PLL (ω) represents parameters related to the phase-locked loop, ω g =2πf g k is the fundamental angular frequency of the power grid. pi and k ii The proportional-integral control parameters are represented by ω, which represents the angular frequency at different frequencies. A(p,ω) and B(p,ω) are used to simplify the expression.

[0026] The full-band sensitivity obtained through full-band analysis in step S22 is expressed as follows:

[0027]

[0028] In the formula, Z p Representing the impedance mathematical model, S pi Δp represents the sensitivity at each frequency point. i =0.05p i p is the parameter perturbation step size. i This represents the control parameter, where ω represents the angular frequency at different frequencies. Indicates a positive change. Indicates a change in the negative direction;

[0029] The global sensitivity calculation equation in step S23 is as follows:

[0030]

[0031] In the formula, ω k What does this represent? N is the number of frequency points, N = 1000; SI i SI represents the global sensitivity, which reflects the overall influence of parameters on the impedance amplitude. i >1 indicates that this parameter is highly sensitive to impedance, and the optimization range is p ± 10%; SI i <1 indicates that the parameter is less sensitive to impedance, and the optimization range is p±30%.

[0032] Preferably, step S3 includes:

[0033] S31. Based on the Nyquist stability criterion and the Bode graph criterion, the objective function and constraints are constructed by analyzing the distance between the Nyquist graph and the point (-1,j0) and the stability margin shown by the Bode graph.

[0034] S32. Set the population size to N. pop The maximum number of iterations is T. Initial positions are generated using random initialization, resulting in the initial whale coordinates W. i ;

[0035] S33. Set the individual humpback whale position as a combination of photovoltaic inverter control parameters. In each humpback whale pod, the individual with the higher objective function value is designated as the humpback whale leader, guiding other members towards the target position. The average position of the current leader is defined as:

[0036]

[0037] In the formula, N L W represents the number of leaders. j Indicates the position of the leader;

[0038] S34. Assume all population members are sorted in descending order of their positions:

[0039]

[0040] In the formula, W1 represents the individual position of the highest objective function value, denoted as W best W i This indicates the current position of the non-leader, and also the current control parameter value. The position of an individual is represented by the minimum objective function value, and all non-leader whales will imitate their neighboring companions.

[0041] Preferably, step S3 further includes:

[0042] S35. The current position of the entire migrating whale pod in the ocean is assumed to be the average of the current positions of all whale leaders, W.Mean If W Mean With W best The distance between them begins to shorten, and the non-leader whale begins to move along the vector rand(1,D)×(W). Best -W Mean Move forward in the given direction and update the position as follows:

[0043]

[0044] in, Indicates the current update position, W Mean W represents the average position of leaders. best Indicates the optimal position of the population;

[0045] S36. Compare the values ​​of the objective function after the whale's position is updated;

[0046] S37. Determine the iteration termination condition. If the current iteration number t reaches the maximum iteration number T, stop the iteration and output the optimal solution; otherwise, increase the iteration number t = t + 1, return to step S32, and continue the next iteration until the iteration ends and the optimal parameters are obtained.

[0047] Preferably, the objective function and constraints in step S31 are expressed as follows:

[0048]

[0049] Where G(jω)=Z grid (jω) / Z inv (jω) is the open-loop transfer function, |G(jω)+1| is the minimum Euclidean distance from the Nyquist curve to (-1, j0) over the entire frequency range; GM and PM are the gain margin and phase margin, respectively; ω1, ω2, ω3, and ω4 are the assigned weights; GM min and PM min This represents the stability margin under critical stability conditions.

[0050] Preferably, the initialization of whale coordinates W in step S32 is... i Represented as:

[0051] W i =L+rand(1,D)×(UL),i=1,2,…,N pop ;

[0052] In the formula, U and L are the lower and upper bound vectors of the search space, respectively; the function rand(1,D) generates a random number vector of dimension D, with the random numbers taken from the interval [0,1]; the operator × represents the Hadamard product of two vectors.

[0053] Preferably, the comparison of the objective function values ​​after the whale's position update in step S36 is as follows: if the objective function value corresponding to the whale's position before the update is better, then the whale's position remains unchanged; if the objective function value corresponding to the updated position is better, then the whale's position is updated, as shown in the following formula:

[0054]

[0055] Among them, W i This represents the current position of the non-leader, and F represents the objective function, with each position corresponding to an objective function value.

[0056] Therefore, the photovoltaic inverter control parameter optimization and broadband oscillation suppression method based on the humpback whale migration algorithm described above has the following beneficial effects:

[0057] 1. This invention proposes a calculation method based on multi-frequency sensitivity coefficients. By quantifying the correlation strength between parameters such as current loop proportional gain and feedforward decoupling coefficient and inverter impedance through global sensitivity quantification, it provides the parameter optimization range and improves the efficiency of subsequent parameter optimization.

[0058] 2. This invention uses the humpback whale migration algorithm to optimize control parameters. Compared with traditional methods, it effectively balances the exploration and development stages, improves its ability to avoid local optima and achieve effective convergence, and the optimized parameter values ​​can effectively match the impedance of the photovoltaic inverter and the grid impedance, thereby improving the stability of the photovoltaic grid-connected system.

[0059] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0060] Figure 1 This is a flowchart of a photovoltaic inverter control parameter optimization and broadband oscillation suppression method based on the humpback whale migration algorithm according to an embodiment of the present invention;

[0061] Figure 2 This is a flowchart illustrating the optimization of control parameters using the humpback whale migration algorithm in an embodiment of the present invention.

[0062] Figure 3 This is a sensitivity analysis diagram of the control parameters at various frequency points according to an embodiment of the present invention;

[0063] Figure 4 The Nyquist plots before and after positive sequence impedance optimization are shown in the embodiments of the present invention.

[0064] Figure 5 The images show Bode plots before and after positive sequence impedance optimization in an embodiment of the present invention. Detailed Implementation

[0065] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0066] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0067] like Figure 1 As shown, this invention provides a method for optimizing control parameters and suppressing wideband oscillations in photovoltaic inverters based on the humpback whale migration algorithm, comprising the following steps:

[0068] S1. Based on the specific revenue situation of the actual photovoltaic grid-connected system, models of various subsystems including photovoltaic power generation module, converter module and current loop control module were built, and the sequence impedance model of photovoltaic inverter was established.

[0069] S2. Select the control parameters to be optimized in the photovoltaic grid-connected model, i.e., the sequence impedance model, and calculate the normalized sensitivity at each frequency (1-10kHz) using the multi-frequency center difference method to perform full-band analysis; obtain the global sensitivity of each control parameter through the global sensitivity calculation formula, and then give the optimization range of each control parameter to be optimized from the global sensitivity.

[0070] S3. Based on the optimization range of the control parameters obtained from global sensitivity calculation, the humpback whale migration algorithm is used to optimize the control parameters.

[0071] Furthermore, step S1 specifically includes:

[0072] S11. Build an equivalent circuit model that can simulate a photovoltaic grid-connected system. Select components such as an ideal DC voltage source, series resistor, and capacitor to form a photovoltaic power generation model to simulate the DC power generated by the photovoltaic grid-connected system and the resistance of the photovoltaic modules.

[0073] S12. Establish a simulation model of a three-phase bridge current source photovoltaic inverter and introduce a control structure for the power outer loop and the current inner loop.

[0074] S13. By establishing the sequence impedance model of the photovoltaic grid-connected system, the relationship between the parameters to be optimized and the impedance model is obtained.

[0075] The positive sequence impedance model is as follows:

[0076]

[0077] The negative sequence impedance model is as follows:

[0078]

[0079] In the formula, V p (s) represents the positive sequence voltage, I p (s) represents the positive sequence current, V n (s) represents the negative sequence voltage, I n (s) represents the negative sequence current, J represents the imaginary part of the complex variable, and L f 、V dc f1 and f1 represent the filter inductance on the grid-connected inverter side, the DC side voltage, and the base frequency, respectively, and K f K d G represents the voltage feedforward coefficient and the feedforward decoupling gain coefficient. v (s) is the voltage sampling function, G i (s) is the current sampling function, H i For the inner loop control parameters of the current, I dr , I qr These are the current reference values ​​along the d-axis and q-axis in the dq coordinate system. The subscripts p and n represent the positive and negative sequence, respectively, and s represents the Laplace operator. T PLL The parameters related to the phase-locked loop are represented, and V1 represents the fundamental voltage.

[0080] Furthermore, step S2 specifically includes:

[0081] S21. Based on the derived sequence impedance model, establish the photovoltaic inverter control parameter vector p = [k pi ,k ii ,K d ,K f ] T Nonlinear model:

[0082]

[0083] In the formula, Z p (p,ω) represents the inverter impedance, G i (ω) represents the current sampling function, G v (ω) represents the voltage sampling function, T PLL (ω) represents parameters related to the phase-locked loop, ω g =2πf g k is the fundamental angular frequency of the power grid.pi and k ii The proportional-integral control parameters are represented by ω, which represents the angular frequency at different frequencies. A(p,ω) and B(p,ω) are used to simplify the expression.

[0084] S22. Using the sequence impedance model and the central difference method, the normalized sensitivity is approximately calculated. The calculation process covers the frequency band from 1Hz to 10kHz. A full-band analysis is performed at logarithmic intervals of 1000 points to obtain the influence of control parameters on the resonance characteristics. The calculation formula is as follows:

[0085]

[0086] In the formula, Z p Representing the impedance mathematical model, S pi Δp represents the sensitivity at each frequency point. i =0.05p i p is the parameter perturbation step size. i This represents the control parameter, where ω represents the angular frequency at different frequencies. Indicates a positive change. It indicates a negative change.

[0087] S23. Based on the calculated full-band sensitivity, establish the global sensitivity calculation equation:

[0088]

[0089] In the formula, ω k What does this represent? N is the number of frequency points, N = 1000; SI i SI represents the global sensitivity, which reflects the overall influence of parameters on the impedance amplitude. i >1 indicates that this parameter is highly sensitive to impedance, and the optimization range is p ± 10%; SI i <1 indicates that the parameter is less sensitive to impedance, and the optimization range is p±30%.

[0090] Further, refer to Figure 2 Step S3 is as follows:

[0091] S31. Based on the Nyquist stability criterion and the Bode plot criterion, by analyzing the distance between the Nyquist plot and the point (-1,j0) and the stability margin shown by the Bode plot, the objective function and constraints are constructed as follows:

[0092]

[0093] Where G(jω)=Z grid (jω) / Z inv(jω) is the open-loop transfer function, |G(jω)+1| is the minimum Euclidean distance from the Nyquist curve to (-1, j0) over the entire frequency range; GM and PM are the gain margin and phase margin, respectively; ω1, ω2, ω3, and ω4 are the assigned weights; GM min and PM min The stability margin under critical stability is generally taken as 6dB and 45° based on engineering experience.

[0094] S32. Set the population size to N. pop The maximum number of iterations is T. The initial position is generated using random initialization. The initial whale coordinates W are denoted as:

[0095] W i =L+rand(1,D)×(UL),i=1,2,…,N pop ;

[0096] In the formula, U and L are the lower and upper bound vectors of the search space, respectively; the function rand(1,D) generates a random number vector of dimension D, and the random numbers are taken from the interval [0,1]; the operator × represents the Hadamard product of two vectors, that is, each element of the result vector is obtained by multiplying the corresponding elements of the original vectors one by one.

[0097] S33. Set the individual humpback whale position as a combination of photovoltaic inverter control parameters. Within each humpback whale pod, the individual with the higher objective function value is designated as the leader, guiding the other members towards the target position. The average position of the current leader is defined as:

[0098]

[0099] In the formula, N L W represents the number of leaders. j Indicates the position of a leader.

[0100] S34. Assume all population members are sorted in descending order of their positions:

[0101]

[0102] In the formula, W1 represents the individual position of the highest objective function value, denoted as W best W i This indicates the current position of the non-leader, i.e., the current control parameter value. Let W represent the individual position of the whale with the minimum objective function value. All non-leader whales will imitate their neighboring companions. Therefore, in this model, each non-leader W... i The movement is mainly influenced by its nearest preceding member W in the above sequence. i-1 Influence.

[0103] S35. As mentioned earlier, the current position of the entire migrating whale pod in the ocean is assumed to be the average of the current positions of all whale leaders, W. Mean If W Mean With W best The distance between them is beginning to shorten, indicating that the entire whale leader group is approaching W. best In this situation, the non-leader whale must also begin along the vector rand(1,D)×(W). Best -W Mean Move forward in the given direction and update the position as follows:

[0104]

[0105] in, Indicates the current update position, W Mean W represents the average position of leaders. best This indicates the optimal position of the population.

[0106] S36. Compare the objective function values ​​after the whale's position is updated. If the objective function value corresponding to the whale's original position is better, then the whale's original position remains unchanged; if the objective function value corresponding to the updated position is better, then the whale's position is updated, as shown in the following formula:

[0107]

[0108] Here, F represents the objective function, and each position corresponds to an objective function value.

[0109] S37. Determine the iteration termination condition. If the current iteration number t reaches the maximum iteration number T, stop the iteration and output the optimal solution; otherwise, increase the iteration number t = t + 1, return to step S32, and continue the next iteration until the iteration ends and the optimal parameters are obtained.

[0110] Example

[0111] To verify the effectiveness of the proposed current loop control parameter optimization method, this paper constructs a sequence impedance model of a photovoltaic grid-connected system based on the MATLAB platform, and optimizes the control parameters of the sequence impedance model using the humpback whale migration algorithm. The specific circuit parameter settings are shown in Table 1, and the optimized parameters are shown in Table 2.

[0112] Table 1. Main circuit and control parameters before optimization.

[0113]

[0114]

[0115] Table 2 shows the optimized key parameters.

[0116]

[0117] The optimized parameters are substituted into the constructed simulation model to obtain the response curve. Finally, the simulation results before and after optimization are compared and verified. Figures 3 to 5 The comparison chart of the response curves before and after optimization shows that the positive-sequence Nyquist curve before optimization encircles (-1, j0), indicating an unstable system. The optimized curve, however, does not encircle the (-1, j0) point, and the minimum Euclidean distance increases by approximately 0.94, indicating the system has stabilized. According to the Bode plot stability criterion, at the intersection of the amplitude-frequency logarithmic characteristic curves of the inverter output impedance and the grid impedance, the phase difference between the inverter output impedance and the grid impedance under the original parameters is greater than 180°, indicating an unstable system. After optimization, the phase difference increases by 58.51° and is less than 180°, demonstrating the effectiveness of the proposed method.

[0118] Therefore, this invention adopts the above-mentioned photovoltaic inverter control parameter optimization and broadband oscillation suppression method based on the humpback whale migration algorithm. By quantifying the correlation strength of parameters such as current loop proportional gain and feedforward decoupling coefficient with inverter impedance through global sensitivity, the optimization range of parameters is given, which improves the efficiency of subsequent parameter optimization.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical solutions of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical solutions to deviate from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for optimizing control parameters and suppressing broadband oscillations in photovoltaic inverters based on the humpback whale migration algorithm, characterized in that, The following steps are involved: S1. Based on the specific revenue situation of the actual photovoltaic grid-connected system, build models of various subsystems including photovoltaic power generation module, converter module and current loop control module, and establish the sequence impedance model of photovoltaic inverter. S2. Select the control parameters to be optimized in the sequence impedance model, calculate the normalized sensitivity at each frequency point using the multi-frequency center difference method, and perform full-band analysis. The global sensitivity of each control parameter is obtained by using the global sensitivity calculation formula, and then the optimization range of each control parameter to be optimized is given by the global sensitivity. S3. Based on the optimization range of the control parameters to be optimized obtained from the global sensitivity calculation, the humpback whale migration algorithm is used to optimize the control parameters.

2. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 1, characterized in that, Step S1 includes: S11. Construct an equivalent circuit model to simulate a photovoltaic grid-connected system. Select an ideal DC voltage source, series resistor, and capacitor to form a photovoltaic power generation model to simulate the DC power generated by the photovoltaic grid-connected system and the resistance of the photovoltaic modules. S12. Establish a model of a three-phase bridge current source photovoltaic inverter and introduce a control structure for the power outer loop and the current inner loop. S13. By establishing the sequence impedance model of the photovoltaic grid-connected system, the relationship between the parameters to be optimized and the impedance model is obtained.

3. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 2, characterized in that, The sequence impedance model in step S13 includes a positive sequence impedance model and a negative sequence impedance model, which are represented as follows: The positive-sequence impedance model is as follows: The negative sequence impedance model is as follows: In the formula, V p (s) represents the positive sequence voltage, I p (s) represents the positive sequence current, V n (s) represents the negative sequence voltage, I n (s) represents the negative sequence current, J represents the imaginary part of the complex variable, and L f 、V dc f1 and f1 represent the filter inductance on the grid-connected inverter side, the DC side voltage, and the base frequency, respectively, and K f K d G represents the voltage feedforward coefficient and the feedforward decoupling gain coefficient. v (s) is the voltage sampling function, G i (s) is the current sampling function, H i For the inner loop control parameters of the current, I dr , I qr These are the current reference values ​​along the d-axis and q-axis in the dq coordinate system. The subscripts p and n represent the positive and negative sequence, respectively, and s represents the Laplace operator. T PLL The parameters related to the phase-locked loop are represented, and V1 represents the fundamental voltage.

4. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 1, characterized in that, Step S2 includes: S21. Based on the derived sequence impedance model, establish the photovoltaic inverter control parameter vector p = [k pi ,k ii ,K d ,K f ] T Nonlinear models; S22. Using the sequence impedance model, the normalized sensitivity is approximately calculated using the central difference method. The calculation process covers the frequency band from 1Hz to 10kHz. 1000 points are taken at logarithmic intervals for full-band analysis to obtain the influence of control parameters on resonance characteristics. S23. Establish the global sensitivity calculation equation based on the calculated full-band sensitivity.

5. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 4, characterized in that, The nonlinear model in step S21 is: In the formula, Z p (p,ω) represents the inverter impedance, G i (ω) represents the current sampling function, G v (ω) represents the voltage sampling function, T PLL (ω) represents parameters related to the phase-locked loop, ω g =2πf g k is the fundamental angular frequency of the power grid. pi and k ii The proportional-integral control parameters are represented by ω, which represents the angular frequency at different frequencies. A(p,ω) and B(p,ω) are used to simplify the expression. The full-band sensitivity obtained through full-band analysis in step S22 is expressed as follows: In the formula, Z p Representing the impedance mathematical model, S pi Δp represents the sensitivity at each frequency point. i =0.05p i p is the parameter perturbation step size. i This represents the control parameter, where ω represents the angular frequency at different frequencies. Indicates a positive change. Indicates a change in the negative direction; The global sensitivity calculation equation in step S23 is as follows: In the formula, ω k What does this represent? N is the number of frequency points, N = 1000; SI i SI represents the global sensitivity, which reflects the overall influence of parameters on the impedance amplitude. i >1 indicates that this parameter is highly sensitive to impedance, and the optimization range is p ± 10%; SI i <1 indicates that the parameter is less sensitive to impedance, and the optimization range is p±30%.

6. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 1, characterized in that, Step S3 includes: S31. Based on the Nyquist stability criterion and the Bode graph criterion, the objective function and constraints are constructed by analyzing the distance between the Nyquist graph and the point (-1,j0) and the stability margin shown by the Bode graph. S32. Set the population size to N. pop The maximum number of iterations is T. Initial positions are generated using random initialization, resulting in the initial whale coordinates W. i ; S33. Set the individual humpback whale position as a combination of photovoltaic inverter control parameters. In each humpback whale pod, the individual with the higher objective function value is designated as the humpback whale leader, guiding other members towards the target position. The average position of the current leader is defined as: In the formula, N L W represents the number of leaders. j Indicates the position of the leader; S34. Assume all population members are sorted in descending order of their positions: In the formula, W1 represents the individual position of the highest objective function value, denoted as W best W i This indicates the current position of the non-leader, and also the current control parameter value. The position of an individual is represented by the minimum objective function value, and all non-leader whales will imitate their neighboring companions.

7. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 6, characterized in that, Step S3 also includes: S35. The current position of the entire migrating whale pod in the ocean is assumed to be the average of the current positions of all whale leaders, W. Mean If W Mean With W best The distance between them begins to shorten, and the non-leader whale begins to move along the vector rand(1,D)×(W). Best -W Mean Move forward in the given direction and update the position as follows: in, Indicates the current update position, W Mean W represents the average position of leaders. best Indicates the optimal position of the population; S36. Compare the values ​​of the objective function after the whale's position is updated; S37. Determine the iteration termination condition. If the current iteration number t reaches the maximum iteration number T, stop the iteration and output the optimal solution; otherwise, increase the iteration number t = t + 1, return to step S32, and continue the next iteration until the iteration ends and the optimal parameters are obtained.

8. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 7, characterized in that, The objective function and constraints in step S31 are expressed as follows: Where G(jω)=Z grid (jω) / Z inv (jω) is the open-loop transfer function, |G(jω)+1| is the minimum Euclidean distance from the Nyquist curve to (-1, j0) over the entire frequency range; GM and PM are the gain margin and phase margin, respectively; ω1, ω2, ω3, and ω4 are the assigned weights; GM min and PM min This represents the stability margin under critical stability conditions.

9. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 8, characterized in that, The initialization of whale coordinates W in step S32 i Represented as: W i =L+rand(1,D)×(U-L),i=1,2,…,N pop ; In the formula, U and L are the lower and upper bound vectors of the search space, respectively; the function rand(1,D) generates a random number vector of dimension D, with the random numbers taken from the interval [0,1]; the operator × represents the Hadamard product of two vectors.

10. The method for optimizing photovoltaic inverter control parameters and suppressing wideband oscillations based on the humpback whale migration algorithm according to claim 9, characterized in that, The comparison of the objective function values ​​after the whale's position update in step S36 is as follows: If the objective function value corresponding to the whale's position before the update is better, then the whale's position remains unchanged; if the objective function value corresponding to the updated position is better, then the whale's position is updated, as shown in the following formula: Among them, W i This represents the current position of the non-leader, and F represents the objective function, with each position corresponding to an objective function value.

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