Inverter power supply system frequency response modeling method and device, electronic equipment and medium

Abstract

The invention discloses an inverter power supply system frequency response modeling method and device, electronic equipment and a medium, which are used for solving the problem of inaccurate modeling caused by sensitive initial parameters and low identification precision during parameter identification in the traditional method. Linearization state space modeling based on multi-time scale analysis is carried out on the inverter power supply system to be analyzed, a second-order frequency response parameter model is obtained, and a second-order frequency response coefficient model is further deduced; constructing a coefficient optimization solving model of the second-order frequency response coefficient model by considering a dynamic performance index of the inverter power supply system under unit step disturbance; performing coefficient optimization solution on the second-order frequency response coefficient model according to the coefficient optimization solution model to obtain a frequency response coefficient value, and substituting the frequency response coefficient value back to the second-order frequency response coefficient model; and performing parameter optimization solution based on frequency response coefficient equivalent conversion on the second-order frequency response parameter model to obtain a frequency response parameter value, and substituting the frequency response parameter value back to the second-order frequency response parameter model.

Description

Technical Field

[0001] The present invention relates to the technical field of power system frequency response characteristics, and particularly relates to a frequency response modeling method, device, electronic device and medium for an inverter power supply system. Background Art

[0002] In recent years, with the rapid development and large-scale application of inverter power supplies, the penetration rate of inverter power supply systems in the power grid has been continuously increasing. Based on this, new energy power generation forms represented by inverter power supplies and wind turbines have gradually participated in system frequency modulation. Therefore, the modeling of the frequency response process of inverter power supply systems, the research on the frequency response mechanism of inverter power supply systems, and the parameter identification of frequency response models have gradually become important contents of power system stability analysis, and thus are of great significance for the optimization and stability improvement of power systems.

[0003] In current technologies, in order to simplify the analysis, technicians often use a first-order inertia link or a constant gain to describe the role of the inverter power supply system, which simplifies the analysis process. In addition, relevant means of using data-driven models to study the inverter power supply system also have strong flexibility and applicability. With the continuous emergence of new methods applied in the parameter identification of inverter power supply models, although the accuracy of frequency response modeling can be improved to a certain extent, the currently adopted methods still cannot completely solve the core problems existing in traditional identification methods, such as sensitivity to initial parameters and low identification accuracy, and thus cannot well improve the modeling accuracy. Summary of the Invention

[0004] The present invention provides a frequency response modeling method, device, electronic device and medium for an inverter power supply system, which is used to solve or partially solve the technical problem that in the traditional frequency response modeling method of the inverter power supply system, the initial parameters are sensitive and the identification accuracy is low during parameter identification, resulting in inaccurate modeling.

[0005] The present invention provides a frequency response modeling method for an inverter power supply system, and the method includes:

[0006] Performing linearized state-space modeling based on multi-time scale analysis on the inverter power supply system to be analyzed to obtain a second-order frequency response parameter model;

[0007] Deriving a second-order frequency response coefficient model of the inverter power supply system according to the second-order frequency response parameter model;

[0008] Considering the dynamic performance index of the inverter power supply system under a unit step disturbance, constructing a coefficient optimization solution model for the second-order frequency response coefficient model;

[0009] Optimize and solve the coefficients of the second-order frequency response coefficient model according to the coefficient optimization and solution model, obtain the frequency response coefficient values, and substitute the frequency response coefficient values back into the second-order frequency response coefficient model;

[0010] Perform parameter optimization and solution based on the equivalent conversion of frequency response coefficients on the second-order frequency response parameter model, obtain the frequency response parameter values, and substitute the frequency response parameter values back into the second-order frequency response parameter model.

[0011] The present invention also provides a frequency response modeling device for an inverter power supply system, including:

[0012] A linearized state-space modeling unit for performing linearized state-space modeling based on multi-time scale analysis on the inverter power supply system to be analyzed, and obtaining a second-order frequency response parameter model;

[0013] A second-order frequency response coefficient model derivation unit for deriving the second-order frequency response coefficient model of the inverter power supply system according to the second-order frequency response parameter model;

[0014] A coefficient optimization and solution model construction unit for constructing a coefficient optimization and solution model of the second-order frequency response coefficient model by considering the dynamic performance index of the inverter power supply system under a unit step disturbance;

[0015] A frequency response coefficient value solution unit for optimizing and solving the coefficients of the second-order frequency response coefficient model according to the coefficient optimization and solution model, obtaining the frequency response coefficient values, and substituting the frequency response coefficient values back into the second-order frequency response coefficient model;

[0016] A frequency response parameter value solution unit for performing parameter optimization and solution based on the equivalent conversion of frequency response coefficients on the second-order frequency response parameter model, obtaining the frequency response parameter values, and substituting the frequency response parameter values back into the second-order frequency response parameter model.

[0017] The present invention also provides an electronic device, which includes a processor and a memory:

[0018] The memory is used to store program codes and transmit the program codes to the processor;

[0019] The processor is used to execute the frequency response modeling method of the inverter power supply system as described in any one of the above according to the instructions in the program codes.

[0020] The present invention also provides a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the frequency response modeling method of the inverter power supply system as described in any one of the above.

[0021] As can be seen from the above technical solutions, the present invention has the following advantages:

[0022] A frequency response modeling method for an inverter power supply system is provided. First, a linearized state-space model of the inverter power supply system based on multi-time scale analysis is performed to obtain a second-order frequency response parameter model, so as to achieve a better balance between high accuracy and low order. It can not only reflect the frequency dynamics of the system with high accuracy, but also greatly reduce the model order. Then, according to the second-order frequency response parameter model, a second-order frequency response coefficient model of the inverter power supply system can be derived. Then, fully considering the dynamic performance index of the inverter power supply system under a unit step disturbance as a characteristic index, a coefficient optimization solution model for the second-order frequency response coefficient model is constructed. According to the coefficient optimization solution model, the coefficients of the second-order frequency response coefficient model are optimized and solved to obtain the frequency response coefficient values, and then substituted back into the second-order frequency response coefficient model to obtain a second-order frequency response coefficient model that can be actually used. Finally, parameter optimization and solution based on frequency response coefficient equivalent conversion are performed on the second-order frequency response parameter model to obtain the frequency response parameter values, and then substituted back into the second-order frequency response parameter model to obtain a second-order frequency response coefficient model that can be actually used, completing the frequency response modeling of the inverter power supply system. Thus, under the parameter optimization and solution combined with the characteristic index, each identified parameter of the model can effectively approach the optimal solution, which can greatly improve the accuracy of the identification result and further improve the modeling accuracy of the frequency response model. Description of the Drawings

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0024] Figure 1 It is a flowchart of the steps of a frequency response modeling method for an inverter power supply system;

[0025] Figure 2 It is a frequency response block diagram of an inverter power supply system;

[0026] Figure 3 It is a schematic diagram of the overall control structure of an inverter power supply system;

[0027] Figure 4 It is a schematic diagram of the overall process of a frequency response modeling method for an inverter power supply system;

[0028] Figure 5It is a comparison chart of the system frequency response under active power disturbance between the reduced-order model and the electromagnetic transient model provided by the present invention;

[0029] Figure 6 It is a comparison chart of the response curve between the frequency response model response and the actual system response under the identification method provided by the present invention;

[0030] Figure 7 It is a structural block diagram of a frequency response modeling device for an inverter power supply system. Specific implementation manners

[0031] The embodiments of the present invention provide a frequency response modeling method, device, electronic device and medium for an inverter power supply system, which are used to solve or partially solve the technical problems in the traditional frequency response modeling method for an inverter power supply system, such as being sensitive to initial parameters during parameter identification and having low identification accuracy, resulting in inaccurate modeling.

[0032] To make the objectives, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0033] As an example, in the current technology, in order to simplify the analysis, technicians often use a first-order inertia link or a constant gain to describe the function of the inverter power supply system, which simplifies the analysis process. In addition, relevant means of using data-driven models to study the inverter power supply system also have strong flexibility and applicability. With the continuous emergence of new methods applied to the parameter identification of the inverter power supply model, although the accuracy of frequency response modeling can be improved to a certain extent, the currently adopted methods still cannot completely solve the core problems such as sensitivity to initial parameters and low identification accuracy in the traditional identification methods, thus unable to well improve the modeling accuracy.

[0034] Therefore, one of the core inventive points of the embodiments of the present invention lies in: providing a frequency response modeling method for an inverter power supply system. First, perform linearized state space modeling on the inverter power supply system based on multi-time scale analysis to obtain a second-order frequency response parameter model, so as to achieve a better balance between high precision and low order. It can not only reflect the frequency dynamics of the system with high precision, but also greatly reduce the model order to a large extent. Then, according to the second-order frequency response parameter model, the second-order frequency response coefficient model of the inverter power supply system can be deduced. Then, fully consider the dynamic performance index of the inverter power supply system under a unit step disturbance as a characteristic index, and construct a coefficient optimization solution model for the second-order frequency response coefficient model. According to the coefficient optimization solution model, perform coefficient optimization solution on the second-order frequency response coefficient model to obtain the frequency response coefficient value, and substitute it back into the second-order frequency response coefficient model to obtain a second-order frequency response coefficient model that can be actually used. Finally, perform parameter optimization solution on the second-order frequency response parameter model based on the equivalent conversion of the frequency response coefficient to obtain the frequency response parameter value, and substitute it back into the second-order frequency response parameter model to obtain a second-order frequency response coefficient model that can be actually used, completing the frequency response modeling of the inverter power supply system. By using the frequency response modeling method for the inverter power supply system provided by the embodiments of the present invention, under the parameter optimization solution combined with the characteristic index, each identified parameter of the model can effectively approach the optimal solution, thereby greatly improving the accuracy of the identification result and further improving the modeling accuracy of the frequency response model.

[0035] Referring to Figure 1 , a flowchart of the steps of a frequency response modeling method for an inverter power supply system provided by an embodiment of the present invention is shown, which may specifically include the following steps:

[0036] Step 101, perform linearized state space modeling on the inverter power supply system to be analyzed based on multi-time scale analysis to obtain a second-order frequency response parameter model;

[0037] In a specific implementation, it is necessary to first derive a second-order frequency response model applicable to the inverter power supply system based on multi-time scale. Among them, the second-order frequency response model mainly includes a second-order frequency response parameter model and a second-order frequency response coefficient model.

[0038] To enable those skilled in the art to better understand the technical solution of the present invention, Figure 2 a frequency response block diagram of an inverter power supply system is shown. Figure 3 Then, a schematic diagram of the overall control structure of an inverter power supply system is shown.

[0039] In some embodiments, the process of performing linearized state space modeling on the inverter power supply system to be analyzed based on multi-time scale analysis to obtain a second-order frequency response parameter model can be implemented by executing the following sub-steps S1011 to S1013:

[0040] Step S1011: Perform multi-time scale analysis on the inverter power supply system to be analyzed, and based on the multi-time scale analysis results, perform linearized state space modeling on the inverter power supply system under the frequency dynamic time scale to obtain a power control loop model, a phase-locked loop model, a filter model, a transmission line and a load model;

[0041] Specifically, first perform multi-time scale analysis on the inverter power supply system to be analyzed to obtain multi-time scale analysis results. When performing linearized state space modeling on the inverter power supply system under the frequency dynamic time scale based on the multi-time scale analysis results, the links to be considered include four parts: the power control loop, the phase-locked loop, the filter, the transmission line and the load.

[0042] Among them, the mathematical model of the power control loop is:

[0043]

[0044] In the formula, is the droop control coefficient of primary frequency regulation; , are the proportional and integral gains of the PI regulator in the active power-frequency control loop respectively; is the rated active power output of the inverter power supply, is the system frequency reference value.

[0045] The mathematical model of the phase-locked loop is:

[0046]

[0047] Among them, , are the PI controller parameters of the phase-locked loop respectively; is the rotation angular velocity of the dq synchronous coordinate system; is the initial angular velocity; is the phase of the d axis; represents the integral value of the q-axis voltage of the filter capacitor , as an intermediate variable in the state equation.

[0048] The mathematical model of the filter is:

[0049]

[0050] Among them, , respectively represent the d-axis and q-axis components of the current flowing through the filter inductor ; , respectively represent the d-axis and q-axis components of the voltage of the filter capacitor ; , respectively represent the d-axis and q-axis components of the inverter output voltage; , respectively represent the d-axis and q-axis components of the line current.

[0051] The mathematical models of the transmission line and the load are:

[0052]

[0053] Among them, is the load resistance; is the sum of the filter inductance and the load reactance.

[0054] Step S1012: Integrate the power control loop model, the phase-locked loop model, the filter model, the transmission line and the load model to obtain the small-signal model of the inverter power system;

[0055] Then, organize the mathematical models of the four parts of the power control loop model, the phase-locked loop model, the filter model, the transmission line and the load model in step S1011 into the following small-signal model:

[0056]

[0057] Step S1013: Derive the second-order frequency response parameter model of the inverter power system through the small-signal model; The second-order frequency response parameter model is the expression of the inverter output power driven by the system frequency perturbation.

[0058] According to the above small-signal model (i.e., the link transfer function), the second-order frequency response parameter model of the inverter power system can be derived as follows:

[0059]

[0060] Among them, ; ; ; ; ; ; is the active output power of the inverter; , are the steady-state values of the d-axis and q-axis components of the filter output voltage respectively; , are the d-axis and q-axis components of the line current flowing through respectively, , are the steady-state values of the d-axis and q-axis components of the line current flowing through respectively.

[0061] Among them, the second-order frequency response parameter model constructed in the embodiments of the present invention has reached the reduced-order limit. The second order is the lowest effective order of the model. That is, by achieving a better balance point in this pair of contradictions between high precision and low order, it can not only meet the requirement of reflecting the frequency dynamics of the system with high precision, but also reduce the model order to a large extent.

[0062] Next, the process of deriving the second-order frequency response parameter model of the inverter power supply system according to the above link transfer function will be further described.

[0063] First, when using the active-frequency controller structure, the linearized expression of the active power of the inverter power supply system under frequency perturbation is:

[0064]

[0065] It can be denoted as:

[0066]

[0067] The calculated value of the output power of the inverter The corresponding linearized expression is:

[0068]

[0069] Among them, 、 are the d-axis and q-axis components of the voltage at the filter outlet, respectively.

[0070] Using the linearized expression of the phase-locked loop model to eliminate :

[0071]

[0072] It can be denoted as:

[0073]

[0074] From the transmission line + load small-signal model, it can be obtained that:

[0075]

[0076]

[0077] From the above equations, it can be obtained that:

[0078]

[0079] Denoted as:

[0080]

[0081] Among them, ; .

[0082] Then eliminate ,get:

[0083]

[0084] Denoted as:

[0085]

[0086] in, ; .

[0087] So far, we can get:

[0088]

[0089] in:

[0090]

[0091] Combined, we get:

[0092]

[0093] Finally, eliminate the intermediate variables in the above formula The expression of the inverter output power driven by the system frequency disturbance can be obtained, that is, the second-order frequency response parameter model of the inverter power system:

[0094]

[0095] in, .

[0096] Step 102, deriving a second-order frequency response coefficient model of the inverter power system according to the second-order frequency response parameter model;

[0097] In a specific implementation, the second-order frequency response coefficient model of the inverter power system is derived according to the second-order frequency response parameter model. The system frequency disturbance in the second-order frequency response parameter model is used as the denominator of one side of the equation, and the inverter output power is used as the numerator of the same side of the equation. At the same time, the frequency response coefficient is introduced, and the second-order rational fraction transfer function expression on the other side of the equation is derived based on the second-order frequency response parameter model to obtain the second-order frequency response coefficient model of the inverter power system.

[0098] Through the second-order frequency response parameter model, it can be organized into the following second-order frequency response coefficient model:

[0099]

[0100] in:

[0101]

[0102] 、 、 、 、 、 are all introduced frequency response coefficients.

[0103] Step 103: Considering the dynamic performance indexes of the inverter power supply system under a unit step disturbance, construct a coefficient optimization and solution model for the second-order frequency response coefficient model;

[0104] In this step, the main task is to construct a coefficient optimization and solution model for the second-order frequency response coefficient model.

[0105] In some embodiments, the process of constructing a coefficient optimization and solution model for the second-order frequency response coefficient model by considering the dynamic performance indexes of the inverter power supply system under a unit step disturbance can be implemented by performing the following sub-steps S1031 to S1036:

[0106] Step S1031: According to the second-order frequency response coefficient model, deduce the output response model of the inverter power supply system under a unit step disturbance;

[0107] First, the dynamic performance index expression of the second-order frequency response coefficient model (i.e., the dynamic performance index expression corresponding to the frequency response curve) can be obtained through deduction.

[0108] The output response of the inverter power supply system under a unit step disturbance is:

[0109]

[0110] Parameter is a complex variable in the Laplace transform, representing the frequency and damping characteristics of the system.

[0111] Step S1032: Perform an inverse Laplace transform on the output response model to obtain the unit step time-domain model of the second-order frequency response coefficient model;

[0112] Through the inverse Laplace transform, the time-domain expression of the unit step response of the second-order frequency response coefficient model can be obtained as shown in the following formula:

[0113]

[0114] In the formula, ; ; ; ; ; ; 。

[0115] Step S1033: Combine the unit step time-domain model to derive the dynamic performance index model of the time-domain response curve corresponding to the second-order frequency response coefficient model;

[0116] Among them, the dynamic performance index model includes the peak time expression, the peak expression, the overshoot expression, and the rise time expression.

[0117] Combining the unit step time-domain model, the peak time of the time-domain response curve of the second-order frequency response coefficient model can be obtained through derivation , peak , overshoot , rise time analytical expressions.

[0118] Among them, the peak time expression is:

[0119]

[0120] In the formula, 。

[0121] The value of the time-domain response curve at the peak time is the peak , and its expression is:

[0122]

[0123] The corresponding overshoot expression is:

[0124]

[0125] The corresponding rise time expression is:

[0126]

[0127] Step S1034: Taking the minimum error between the actual value and the theoretical value of each sample point on the time-domain response curve as the optimization goal, construct the first objective function for coefficient optimization and solution;

[0128] Comparing with the measured curve is an effective method to detect whether the parameter values of the inverter power supply system frequency response model are ideal. Therefore, the following first objective function can be established:

[0129]

[0130] In the formula, represents the The actual value of a disturbance response curve sample at time ; is the theoretical value of the formula at time under the same disturbance. To avoid measurement errors caused by a single sample, the mean value of samples is used as the objective function.

[0131] Step S1035: Construct the first constraint condition for optimizing the solution of coefficients according to the peak time expression, peak expression, overshoot expression, and rise time expression;

[0132] At this time, the first objective function satisfies the following equality constraint conditions:

[0133]

[0134] In the formula, , , , respectively represent the measured values of the peak time, peak, overshoot, and rise time measured from the disturbance response curve (time-domain response curve); , , , represent the theoretical values calculated by substituting the current model parameters into the analytical expressions of the peak time , peak , overshoot , and rise time introduced above.

[0135] Step S1036: Based on the first objective function and the first constraint condition, construct a coefficient optimization solution model for the second-order frequency response coefficient model.

[0136] Based on the first objective function and the first constraint condition constructed in the previous steps, a coefficient optimization solution model for the inverse second-order frequency response coefficient model can be constructed.

[0137] Step 104: Optimize the solution of the coefficients of the second-order frequency response coefficient model according to the coefficient optimization solution model, obtain the frequency response coefficient value, and substitute the frequency response coefficient value back into the second-order frequency response coefficient model;

[0138] In this step, it mainly realizes the optimization of the solution of the coefficients of the second-order frequency response coefficient model based on the Levenberg-Marquardt (an iterative algorithm for nonlinear least squares optimization) method.

[0139] In some embodiments, the process of optimizing and solving the coefficients of the second-order frequency response coefficient model according to the coefficient optimization solution model to obtain the frequency response coefficient values can be implemented by performing the following sub-steps S1 to S7:

[0140] Step S1: Obtain the initial values of the frequency response coefficients of the second-order frequency response coefficient model;

[0141] For the second-order frequency response coefficient model (i.e., the corresponding coefficient optimization solution model), a set of initial values of the frequency response coefficients can be given 、 、 、 、 、 。

[0142] Step S2: Substitute the initial values of the frequency response coefficients into the coefficient optimization solution model to solve the calculated values of the peak time, peak value, overshoot, and rise time;

[0143] In actual calculation, substitute the initial values of the frequency response coefficients 、 、 、 、 、 into the following formula to calculate the values of the dynamic performance indicators of the second-order frequency response coefficient model:

[0144]

[0145] Step S3: Obtain the measured values of the peak time, peak value, overshoot, and rise time of the time-domain response curve through measurement;

[0146] Measure the values of the dynamic performance indicators of the time-domain response curve, including the measured values of the peak time, peak value, overshoot, and rise time.

[0147] Step S4: Combine the peak time, peak value, overshoot, and rise time of the time-domain response curve to construct the Jacobian matrix related to the frequency response coefficients;

[0148] Calculate the Jacobian matrix through the following formula :

[0149]

[0150] In the formula, represents the th dynamic performance indicator item; is the th frequency response coefficient to be solved.

[0151] Step S5: Calculate the residual vector based on the first objective function, the error between the calculated peak time and the measured peak time, the error between the calculated peak value and the measured peak value, the error between the calculated overshoot and the measured overshoot, and the error between the calculated rise time and the measured rise time;

[0152] Calculate the current residual vector using the following formula :

[0153]

[0154] Step S6: Based on the Jacobian matrix and the residual vector, combined with the damping factor, perform coefficient optimization to obtain the frequency response coefficient values at the end of the k-th iteration;

[0155] Based on the Jacobian matrix and the current residual vector , update the frequency response coefficient values. The updated coefficient vector expression is:

[0156]

[0157] where , the value of the -th iteration containing each coefficient, is the identity matrix; is the damping factor, and its value can be adjusted dynamically. Specifically, the damping factor can be adjusted according to the change of the objective function value : when the objective function value decreases, decrease the damping factor to increase the iteration step size; when the objective function value increases, increase the damping factor

[0158] to decrease the iteration step size. Thus, through the dynamic adjustment of the damping factor, the algorithm can converge robustly when the initial estimate is far from the true solution and converge quickly when approaching the true solution.

[0159] Step S7: Determine whether the current iteration number k (k≠0) reaches the maximum iteration number or whether the current calculation error meets the preset convergence condition; if not, jump to Step S2, use the frequency response coefficient value at the end of the k-th iteration as the coefficient update value for the (k + 1)-th iteration, substitute it into the coefficient optimization solution model, and re-execute Steps S2 to S6 to perform the coefficient optimization solution iteration process for the (k + 1)-th time; if so, output the frequency response coefficient value of the k-th iteration.

[0160] Determine whether the maximum convergence number is reached , or whether the following convergence condition is met:

[0161]

[0162] where represents the preset residual threshold.

[0163] If it is satisfied, stop the iteration and output the frequency response coefficient value of the final second-order frequency response coefficient model 、 、 、 、 、 ; if not, based on the updated frequency response coefficient values 、 、 、 、 、 recalculate the dynamic performance index values of the second-order frequency response coefficient model and perform subsequent related steps.

[0164] Thus, through the above relevant steps, the frequency response coefficients of the second-order frequency response coefficient model can be solved 、 、 、 、 、 , and then the second-order frequency response coefficient model is obtained.

[0165] Step 105, perform parameter optimization solution for the second-order frequency response parameter model based on the equivalent conversion of frequency response coefficients, obtain the frequency response parameter values, and substitute the frequency response parameter values back into the second-order frequency response parameter model.

[0166] This step mainly realizes the parameter optimization solution of the second-order frequency response parameter model.

[0167] In some embodiments, the process of obtaining the frequency response parameter values by performing parameter optimization and solution based on the equivalent conversion of frequency response coefficients for the second-order frequency response parameter model can be implemented by executing the following sub-steps S1051 to S1054:

[0168] Step S1051: Derive an equivalent conversion relationship model between the frequency response coefficients corresponding to the second-order frequency response coefficient model and the frequency response parameters corresponding to the second-order frequency response parameter model;

[0169] Combining the foregoing, the equivalent conversion relationship between the second-order frequency response coefficient model and the second-order frequency response parameter model of the inverter power supply system is:

[0170]

[0171] Step S1052: Substitute the equivalent conversion relationship model into the dynamic performance index model to transform the first objective function into the second objective function of the second-order frequency response parameter model and transform the first constraint condition into the second constraint condition of the second-order frequency response parameter model;

[0172] Substitute the equivalent conversion relationship model into the dynamic performance index model, that is, the peak time expression, the peak expression, the overshoot expression, and the rise time expression:

[0173]

[0174] At this time, the first objective function and the first constraint condition of the coefficient optimization and solution model of the second-order frequency response coefficient model have been transformed into the second objective function and the second constraint condition of the parameter optimization and solution model of the second-order frequency response parameter model.

[0175] Step S1053: Based on the second objective function and the second constraint condition, construct a parameter optimization and solution model for the second-order frequency response parameter model;

[0176] Step S1054: Refer to the coefficient optimization and solution process of the second-order frequency response coefficient model, and perform parameter optimization and solution on the second-order frequency response parameter model according to the parameter optimization and solution model to obtain the frequency response parameter values.

[0177] At this time, the coefficient optimization and solution process of the second-order frequency response coefficient model can be transformed into the parameter optimization and solution process of the second-order frequency response parameter model.

[0178] In an embodiment of the present invention, a method for frequency response modeling of an inverter power supply system is provided. First, a linearized state-space modeling of the inverter power supply system based on multi-time scale analysis is performed to obtain a second-order frequency response parameter model, so as to achieve a better balance between high accuracy and low order. It can not only meet the requirement of reflecting the frequency dynamics of the system with high accuracy, but also greatly reduce the model order to a large extent. Then, according to the second-order frequency response parameter model, a second-order frequency response coefficient model of the inverter power supply system can be derived. Then, fully considering the dynamic performance index of the inverter power supply system under a unit step disturbance as a characteristic index, a coefficient optimization solution model for the second-order frequency response coefficient model is constructed. According to the coefficient optimization solution model, the coefficients of the second-order frequency response coefficient model are optimized and solved to obtain the frequency response coefficient values, and then substitute them back into the second-order frequency response coefficient model to obtain a second-order frequency response coefficient model that can be actually used. Finally, parameter optimization and solution based on frequency response coefficient equivalent conversion are performed on the second-order frequency response parameter model to obtain the frequency response parameter values, and then substitute them back into the second-order frequency response parameter model to obtain a second-order frequency response coefficient model that can be actually used, thus completing the frequency response modeling of the inverter power supply system. By using the frequency response modeling method of the inverter power supply system provided by the embodiment of the present invention, under the parameter optimization and solution combined with the characteristic index, each identified parameter of the model can effectively approach the optimal solution, so as to greatly improve the accuracy of the identification result, and further improve the modeling accuracy of the frequency response model.

[0179] For better illustration, refer to Figure 4 , which shows the overall flowchart of a method for frequency response modeling of an inverter power supply system provided by an embodiment of the present invention. It should be noted that this embodiment only briefly describes the general process of frequency response modeling of the inverter power supply system. The specific implementation process of each step can be understood by referring to the relevant content in the foregoing embodiment, and will not be elaborated here. It can be understood that the present invention is not limited thereto.

[0180] Step 401: Perform multi-time scale analysis on the inverter power supply system, and based on the multi-time scale analysis results, perform linearized state-space modeling on the inverter power supply system under the frequency dynamic time scale to obtain a power control loop model, a phase-locked loop model, a filter model, a transmission line and a load model.

[0181] Step 402: Integrate the power control loop model, the phase-locked loop model, the filter model, the transmission line and the load model to obtain a small-signal model of the inverter power supply system, and derive a second-order frequency response parameter model of the inverter power supply system through the small-signal model.

[0182] Step 403: According to the second-order frequency response parameter model, deduce the second-order frequency response coefficient model of the inverter power supply system. Then, considering the peak time, peak value, overshoot, and rise time of the inverter power supply system under a unit step disturbance, construct a coefficient optimization and solution model for the coefficients of the second-order frequency response coefficient model;

[0183] Step 404: Optimize and solve the coefficients of the second-order frequency response coefficient model according to the coefficient optimization and solution model to obtain the frequency response coefficient values, and substitute them back into the second-order frequency response coefficient model;

[0184] Step 405: Deduce an equivalent conversion relationship model between the frequency response coefficients corresponding to the second-order frequency response coefficient model and the frequency response parameters corresponding to the second-order frequency response parameter model, and based on the equivalent conversion relationship model, construct a parameter optimization and solution model for the second-order frequency response parameter model;

[0185] Step 406: Refer to the coefficient optimization and solution process of the second-order frequency response coefficient model, optimize and solve the parameters of the second-order frequency response parameter model according to the parameter optimization and solution model to obtain the frequency response parameter values, and substitute them back into the second-order frequency response parameter model.

[0186] To enable those skilled in the art to better understand the technical solution of the present invention, the embodiments of the present invention will be described below through a specific example.

[0187] Set up a simulation example of a distributed inverter power supply station to verify the accuracy of the second-order frequency response model of the inverter power supply system.

[0188] First, set the relevant parameters. The relevant parameter settings in the embodiments of the present invention are as follows:

[0189] The rated frequency of the inverter power supply grid-connected system is 50 Hz, the filter capacitor is 10 μF, the filter inductor is 5 mH, the proportional coefficient of the phase-locked loop PI controller is 0.01, the integral coefficient is 0.2, the effective value of the grid voltage is 220 V, and the DC voltage of the inverter power supply is 1000 V.

[0190] Then, perform the simulation. At the initial moment, the active power reference command of the inverter power supply , . At 0 s, the active power reference command of the inverter power supply steps to 12 kW in a stepwise manner.

[0191] According to the above operating conditions, the comparison diagram of the second-order frequency response parameter model (reduced-order model) and the electromagnetic transient model of the inverter power supply system under active power disturbance is as follows Figure 5 shown. Based on the Levenberg-Marquardt identification method provided by the embodiments of the present invention, the coefficient optimization solution model of the second-order frequency response coefficient model is solved to obtain the second-order frequency response coefficient model. Measure its frequency response curve and compare it with the system frequency response curve. The comparison results of the two are as follows Figure 6 shown.

[0192] According to Figure 5 it can be seen that the second-order frequency response parameter model of the inverter power supply system proposed in the embodiments of the present invention has a high degree of coincidence with the electromagnetic transient model on the time scale and can accurately reflect the power-frequency dynamics of the inverter power supply system. Therefore, the modeling rationality of the present invention and the correctness of the derivation process are well verified, and the second-order frequency response parameter model can reflect the frequency dynamics of the system under active power disturbance.

[0193] According to Figure 6 it can be seen that the second-order frequency response coefficient model obtained based on Levenberg-Marquardt identification can accurately reflect the power-frequency dynamics of the system. The frequency response coefficients corresponding to the model , , , , , have an error less than 1% from the accurate values. The model response (abbreviated as the identification system response in the figure) under this identification coefficient has a high degree of coincidence with the electromagnetic transient model response and has strong robustness to noise and fast time-scale dynamics.

[0194] Referring to Figure 7 , the structural block diagram of a frequency response modeling device for an inverter power supply system provided by the embodiments of the present invention is shown, which may specifically include:

[0195] A linearized state-space modeling unit 701, configured to perform linearized state-space modeling based on multi-time scale analysis on the inverter power supply system to be analyzed, and obtain a second-order frequency response parameter model;

[0196] A second-order frequency response coefficient model derivation unit 702, configured to derive the second-order frequency response coefficient model of the inverter power supply system according to the second-order frequency response parameter model;

[0197] A coefficient optimization solution model construction unit 703, configured to construct a coefficient optimization solution model of the second-order frequency response coefficient model in consideration of the dynamic performance index of the inverter power supply system under a unit step disturbance;

[0198] A frequency response coefficient value solving unit 704 is configured to perform coefficient optimization and solution on the second-order frequency response coefficient model according to the coefficient optimization solution model, obtain a frequency response coefficient value, and substitute the frequency response coefficient value back into the second-order frequency response coefficient model;

[0199] A frequency response parameter value solving unit 705 is configured to perform parameter optimization and solution on the second-order frequency response parameter model based on frequency response coefficient equivalent conversion, obtain a frequency response parameter value, and substitute the frequency response parameter value back into the second-order frequency response parameter model.

[0200] In an optional embodiment, the linearized state space modeling unit 701 includes:

[0201] A linearized state space modeling subunit is configured to perform multi-time scale analysis on the inverter power supply system to be analyzed, and based on the multi-time scale analysis result, perform linearized state space modeling on the inverter power supply system under the frequency dynamic time scale to obtain a power control loop model, a phase-locked loop model, a filter model, a transmission line and load model;

[0202] A small signal model integration unit is configured to integrate the power control loop model, the phase-locked loop model, the filter model, the transmission line and load model to obtain a small signal model of the inverter power supply system;

[0203] A second-order frequency response parameter model derivation unit is configured to derive a second-order frequency response parameter model of the inverter power supply system through the small signal model; the second-order frequency response parameter model is an expression of the inverter output power driven by a system frequency perturbation.

[0204] In an optional embodiment, the second-order frequency response coefficient model derivation unit 702 is specifically configured to:

[0205] Use the system frequency perturbation in the second-order frequency response parameter model as the denominator on one side of the equation and the inverter output power as the numerator on the same side of the equation, and at the same time introduce a frequency response coefficient, and derive a second-order rational fraction transfer function expression on the other side of the equation based on the second-order frequency response parameter model to obtain the second-order frequency response coefficient model of the inverter power supply system.

[0206] In an optional embodiment, the coefficient optimization solution model construction unit 703 includes:

[0207] An output response model derivation unit is configured to derive an output response model of the inverter power supply system under a unit step perturbation according to the second-order frequency response coefficient model;

[0208] The unit - step time - domain model construction unit is used to perform the inverse Laplace transform on the output response model to obtain the unit - step time - domain model of the second - order frequency - response coefficient model;

[0209] The dynamic performance index model derivation unit is used to combine the unit - step time - domain model to derive the dynamic performance index model of the time - domain response curve corresponding to the second - order frequency - response coefficient model; the dynamic performance index model includes a peak - time expression, a peak expression, an overshoot expression, and a rise - time expression;

[0210] The first objective - function construction unit is used to construct the first objective function for coefficient optimization and solution with the minimum error between the actual values and the theoretical values of each sample point on the time - domain response curve as the optimization objective;

[0211] The first constraint - condition construction unit is used to construct the first constraint condition for coefficient optimization and solution according to the peak - time expression, the peak expression, the overshoot expression, and the rise - time expression;

[0212] The coefficient optimization and solution model construction sub - unit is used to construct the coefficient optimization and solution model of the second - order frequency - response coefficient model based on the first objective function and the first constraint condition.

[0213] In an alternative embodiment, the frequency - response coefficient value solving unit 704 includes:

[0214] The frequency - response coefficient initial - value acquisition unit is used to execute step S1: obtain the initial value of the frequency - response coefficient of the second - order frequency - response coefficient model;

[0215] The dynamic performance index calculation unit is used to execute step S2: substitute the initial value of the frequency - response coefficient into the coefficient optimization and solution model to solve the calculated values of peak time, peak value, overshoot, and rise time;

[0216] The dynamic performance index measurement unit is used to execute step S3: obtain the measured values of peak time, peak value, overshoot, and rise time of the time - domain response curve through measurement;

[0217] The Jacobian matrix construction unit is used to execute step S4: combine the peak time, peak value, overshoot, and rise time of the time - domain response curve to construct the Jacobian matrix related to the frequency - response coefficient;

[0218] A residual vector calculation unit, configured to perform step S5: calculating a residual vector based on the first objective function, the error between the calculated peak time and the measured peak time, the error between the calculated peak value and the measured peak value, the error between the calculated overshoot and the measured overshoot, and the error between the calculated rise time and the measured rise time;

[0219] A coefficient optimization and solution unit, configured to perform step S6: performing coefficient optimization and solution according to the Jacobian matrix and the residual vector, in combination with a damping factor, to obtain the frequency response coefficient value at the end of the k-th iteration;

[0220] An iterative solution determination unit, configured to perform step S7: determining whether the current iteration number k (k≠0) reaches the maximum iteration number, or whether the current calculation error meets a preset convergence condition; if not, then jump to step S2, use the frequency response coefficient value at the end of the k-th iteration as the coefficient update value for the (k + 1)-th iteration, substitute it into the coefficient optimization and solution model, and re-perform steps S2 to S6 to perform the coefficient optimization and solution iterative process for the (k + 1)-th time; if so, then output the frequency response coefficient value of the k-th iteration.

[0221] In an alternative embodiment, the coefficient optimization and solution unit is specifically configured to:

[0222] Perform coefficient optimization and solution according to the Jacobian matrix and the residual vector, in combination with a damping factor, and dynamically adjust the damping factor according to the change of the objective function value during the parameter optimization and solution process, to obtain the frequency response coefficient value at the end of the k-th iteration;

[0223] Wherein, when the objective function value decreases, the damping factor is decreased to increase the iteration step; when the objective function increases, the damping factor is increased to decrease the iteration step.

[0224] In an alternative embodiment, the frequency response parameter value solving unit 705 includes:

[0225] An equivalent conversion relationship model derivation unit, configured to derive an equivalent conversion relationship model between the frequency response coefficients corresponding to the second-order frequency response coefficient model and the frequency response parameters corresponding to the second-order frequency response parameter model;

[0226] An objective function and constraint condition conversion unit, configured to substitute the equivalent conversion relationship model into the dynamic performance index model, so as to convert the first objective function into a second objective function of the second-order frequency response parameter model, and convert the first constraint condition into a second constraint condition of the second-order frequency response parameter model;

[0227] The parameter optimization solution model construction unit is configured to construct a parameter optimization solution model for the second-order frequency response parameter model based on the second objective function and the second constraint condition;

[0228] The parameter optimization solution unit is configured to refer to the coefficient optimization solution process of the second-order frequency response coefficient model and perform parameter optimization solution on the second-order frequency response parameter model according to the parameter optimization solution model to obtain frequency response parameter values.

[0229] For the apparatus embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For related parts, reference may be made to the corresponding descriptions in the foregoing method embodiments.

[0230] It should be noted that, to enable those skilled in the art to better distinguish data of the same type but with different actual meanings, in the embodiments of the present invention, some technical features are distinguished and described using first and second. First and second are only used for data distinction and have no other special meanings. It can be understood that the present invention makes no limitation in this regard.

[0231] The embodiments of the present invention further provide an electronic device, which includes a processor and a memory:

[0232] The memory is configured to store program codes and transmit the program codes to the processor;

[0233] The processor is configured to execute the frequency response modeling method for the inverter power supply system according to any one of the embodiments of the present invention based on the instructions in the program codes.

[0234] The embodiments of the present invention further provide a computer-readable storage medium, which is configured to store program codes, and the program codes are configured to execute the frequency response modeling method for the inverter power supply system according to any one of the embodiments of the present invention.

[0235] Those skilled in the art can clearly understand that for the convenience and conciseness of description, the specific working processes of the above-described systems, apparatuses, and units can refer to the corresponding processes in the foregoing method embodiments and will not be described herein again.

[0236] In several embodiments provided by the present invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed mutual coupling, direct coupling, or communication connection can be through some interfaces, and the indirect coupling or communication connection of the apparatuses or units can be in electrical, mechanical, or other forms.

[0237] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0238] In addition, each functional unit in various embodiments of the present invention may be integrated in a processing unit, may exist separately as individual physical units, or two or more units may be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0239] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs that can store program codes.

[0240] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A frequency response modeling method for an inverter power supply system, characterized in that, Including: Performing linearized state-space modeling based on multi-time scale analysis on the inverter power supply system to be analyzed, and obtaining a second-order frequency response parameter model; Deriving a second-order frequency response coefficient model of the inverter power supply system according to the second-order frequency response parameter model; Considering the dynamic performance index of the inverter power supply system under a unit step disturbance, and constructing a coefficient optimization solution model for the second-order frequency response coefficient model; Performing coefficient optimization solution on the second-order frequency response coefficient model according to the coefficient optimization solution model, obtaining frequency response coefficient values, and substituting the frequency response coefficient values back into the second-order frequency response coefficient model; Performing parameter optimization solution on the second-order frequency response parameter model based on frequency response coefficient equivalent conversion, obtaining frequency response parameter values, and substituting the frequency response parameter values back into the second-order frequency response parameter model.

2. The frequency response modeling method of the inverter power supply system according to claim 1, wherein The performing linearized state-space modeling based on multi-time scale analysis on the inverter power supply system to be analyzed and obtaining a second-order frequency response parameter model includes: Performing multi-time scale analysis on the inverter power supply system to be analyzed, and based on the multi-time scale analysis result, performing linearized state-space modeling on the inverter power supply system under the frequency dynamic time scale to obtain a power control loop model, a phase-locked loop model, a filter model, a transmission line and a load model; Integrating the power control loop model, the phase-locked loop model, the filter model, the transmission line and the load model to obtain a small-signal model of the inverter power supply system; Deriving a second-order frequency response parameter model of the inverter power supply system through the small-signal model; the second-order frequency response parameter model is an expression of the inverter output power driven by the system frequency disturbance.

3. The frequency response modeling method of the inverter power supply system according to claim 2, characterized in that The deriving a second-order frequency response coefficient model of the inverter power supply system according to the second-order frequency response parameter model includes: Taking the system frequency disturbance in the second-order frequency response parameter model as the denominator on one side of the equation and the inverter output power as the numerator on the same side of the equation, and at the same time introducing a frequency response coefficient, and deriving an expression of a second-order rational fraction transfer function on the other side of the equation based on the second-order frequency response parameter model to obtain a second-order frequency response coefficient model of the inverter power supply system.

4. The frequency response modeling method of the inverter power supply system according to claim 3, characterized in that The considering the dynamic performance index of the inverter power supply system under a unit step disturbance and constructing a coefficient optimization solution model for the second-order frequency response coefficient model includes: Deriving an output response model of the inverter power supply system under a unit step disturbance according to the second-order frequency response coefficient model; Performing Laplace inverse transform on the output response model to obtain a unit step time-domain model of the second-order frequency response coefficient model; Combining the unit step time-domain model, and deriving a dynamic performance index model of the time-domain response curve corresponding to the second-order frequency response coefficient model; the dynamic performance index model includes a peak time expression, a peak expression, an overshoot expression and a rise time expression; Taking the minimum error between the actual value and the theoretical value of each sample point on the time-domain response curve as the optimization objective, and constructing a first objective function for coefficient optimization solution; Construct a first constraint condition for coefficient optimization and solution according to the peak time expression, the peak expression, the overshoot expression, and the rise time expression; Based on the first objective function and the first constraint condition, construct a coefficient optimization and solution model for the second-order frequency response coefficient model.

5. The frequency response modeling method of the inverter power supply system according to claim 4, characterized in that The coefficient optimization and solution of the second-order frequency response coefficient model according to the coefficient optimization and solution model to obtain the frequency response coefficient value includes: Step S1: Obtain the initial value of the frequency response coefficient of the second-order frequency response coefficient model; Step S2: Substitute the initial value of the frequency response coefficient into the coefficient optimization and solution model to solve the calculated values of the peak time, the peak value, the overshoot value, and the rise time; Step S3: Obtain the measured values of the peak time, the peak value, the overshoot value, and the rise time of the time-domain response curve through measurement; Step S4: Combine the peak time, the peak value, the overshoot value, and the rise time of the time-domain response curve to construct a Jacobian matrix related to the frequency response coefficient; Step S5: Based on the first objective function, the error between the calculated value of the peak time and the measured value of the peak time, the error between the calculated value of the peak value and the measured value of the peak value, the error between the calculated value of the overshoot and the measured value of the overshoot, and the error between the calculated value of the rise time and the measured value of the rise time, calculate the residual vector; Step S6: According to the Jacobian matrix and the residual vector, combine the damping factor to perform coefficient optimization and solution to obtain the frequency response coefficient value at the end of the k-th iteration; Step S7: Determine whether the current iteration number k (k≠0) reaches the maximum iteration number, or whether the current calculation error meets the preset convergence condition; if not, jump to Step S2, use the frequency response coefficient value at the end of the k-th iteration as the coefficient update value for the (k + 1)-th iteration, substitute it into the coefficient optimization and solution model, and re-execute Steps S2 to S6 to perform the coefficient optimization and solution iteration process for the (k + 1)-th time; if so, output the frequency response coefficient value of the k-th iteration.

6. The frequency response modeling method of the inverter power supply system according to claim 5, characterized in that The coefficient optimization and solution according to the Jacobian matrix and the residual vector, combined with the damping factor to obtain the frequency response coefficient value at the end of the k-th iteration includes: According to the Jacobian matrix and the residual vector, combine the damping factor to perform coefficient optimization and solution. During the parameter optimization and solution process, dynamically adjust the damping factor according to the change of the objective function value to obtain the frequency response coefficient value at the end of the k-th iteration; Among them, when the objective function value decreases, reduce the damping factor to increase the iteration step size; when the objective function increases, increase the damping factor to reduce the iteration step size.

7. The frequency response modeling method for the inverter power supply system according to any one of claims 4 to 6, characterized in that The parameter optimization and solution of the second-order frequency response parameter model based on the equivalent conversion of the frequency response coefficient to obtain the frequency response parameter value includes: Derive an equivalent conversion relationship model between the frequency response coefficient corresponding to the second-order frequency response coefficient model and the frequency response parameter corresponding to the second-order frequency response parameter model; Substitute the equivalent conversion relationship model into the dynamic performance index model to convert the first objective function into the second objective function of the second-order frequency response parameter model and convert the first constraint condition into the second constraint condition of the second-order frequency response parameter model; Based on the second objective function and the second constraint condition, construct a parameter optimization solution model for the second-order frequency response parameter model; Referring to the coefficient optimization solution process of the second-order frequency response coefficient model, perform parameter optimization solution on the second-order frequency response parameter model according to the parameter optimization solution model to obtain the frequency response parameter values.

8. An inverter power supply system frequency response modeling device, characterized in that, It includes: A linearized state-space modeling unit for performing linearized state-space modeling based on multi-time scale analysis on the inverter power supply system to be analyzed to obtain a second-order frequency response parameter model; A second-order frequency response coefficient model derivation unit for deriving the second-order frequency response coefficient model of the inverter power supply system according to the second-order frequency response parameter model; A coefficient optimization solution model construction unit for constructing a coefficient optimization solution model for the second-order frequency response coefficient model considering the dynamic performance index of the inverter power supply system under a unit step disturbance; A frequency response coefficient value solution unit for performing coefficient optimization solution on the second-order frequency response coefficient model according to the coefficient optimization solution model to obtain the frequency response coefficient values and substituting the frequency response coefficient values back into the second-order frequency response coefficient model; A frequency response parameter value solution unit for performing parameter optimization solution based on frequency response coefficient equivalent conversion on the second-order frequency response parameter model to obtain the frequency response parameter values and substituting the frequency response parameter values back into the second-order frequency response parameter model.

9. An electronic device, characterized in that, The device includes a processor and a memory: The memory is used to store program codes and transmit the program codes to the processor; The processor is used to execute the inverter power supply system frequency response modeling method according to any one of claims 1-7 based on the instructions in the program codes.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program codes, and the program codes are used to execute the inverter power supply system frequency response modeling method according to any one of claims 1-7.

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