39 results about "Vector fitting" patented technology

The invention belongs to the field of filter optimization of coupling matrixes and neural networks, and discloses a filter optimization design method of a neural network based on guidance of a coupling matrix, and physical elements and mechanisms are introduced into the neural network. The method comprises the following steps: firstly, determining filter optimization indexes, randomly generating sample data in a range near the size of the optimization indexes, and screening data samples by adopting a sample screening method to obtain high-quality samples; then, extracting a coupling matrix from the obtained S parameter according to a vector fitting algorithm, and forming new coupling information M'by combining the center frequency f0 and the bandwidth BW; a full-connection neural network is used as a medium of filter device size parameters and output frequency response, the size of a to-be-optimized device of the filter is input, and coupling information M'representing S parameters is output. And the forward simulator is connected with a genetic optimization algorithm GA to realize optimization design of a specific index parameter filter. According to the method, the optimization design time is effectively saved, the optimization efficiency is improved, and the optimization dimension is reduced.

The invention discloses a high-voltage direct-current cable electromagnetic transient frequency domain modeling and time domain solving method, system, medium and equipment, and the method comprises the steps: obtaining an initialization parameter of a high-voltage direct-current cable, calculating an internal impedance matrix [Zi] of a multi-layer cross-section cable body during frequency calculation, and calculating an admittance coefficient matrix of the multi-layer cross-section cable body during frequency calculation; calculating ground loop impedance [] and potential coefficient [] of the air laying cable or the direct burial laying cable, and obtaining a total impedance matrix [] and a total admittance matrix [] of the cable at the time of frequency: importing obtained multi-frequency [] and [] calculation results into a PSCAD TLine module, and realizing time domain solution of frequency domain calculation by using a vector fitting model.

The invention discloses a new energy system frequency domain modeling and equivalent circuit order reduction analysis method, and relates to the technical field of new energy power system modeling and stability analysis. The method is used for solving the problems that in an existing frequency domain modeling means, the automation degree of data acquisition is low, fitting precision and stability are poor, equivalent circuit universality is poor, and order reduction analysis is not systematic. The method comprises the following steps: acquiring system frequency domain response data based on disturbance injection; constructing a system rational function model by adopting an improved vector fitting algorithm; and then model order reduction is realized through state space modeling and an SVD-based balanced truncation method, and response consistency and stability analysis is carried out in a frequency domain and a time domain. The method can be widely applied to modeling analysis of new energy equipment such as wind power equipment, voltage source converters and high-voltage direct-current power transmission equipment, and has the advantages of being high in automation degree, high in modeling precision, good in visualization, clear in structure, suitable for simulation and control design and the like.

A calculation method for a transformer winding considering a frequency-dependent loss, comprising: according to simulation requirements, defining key parameters calculated by using a finite-difference time-domain (FDTD) algorithm; constructing an equivalent flat wire model in an FDTD grid; calculating frequency-dependent internal impedance per unit length of a flat wire; and on the basis of a vector fitting method and a time-domain convolution calculation method, substituting the frequency-dependent internal impedance into a time-domain equation of the FDTD algorithm for updating and iterative solving, so as to obtain an electromagnetic field calculation result. In the present invention, on the basis of the vector fitting method and time-domain convolution calculation, the impact of the frequency-dependent characteristics of an electromagnetic field distributed in a conductor on an electromagnetic transient process is accurately considered during the FDTD time-domain solving, so that the calculation accuracy and efficiency of conventional FDTD algorithms and even conventional cross-scale modeling techniques can be significantly improved, thereby carrying out the targeted electromagnetic transient analysis on the reliability, safety, and predictability of transformers, and achieving the early detection of potential faults and defects, or formulating targeted maintenance plans and repair schemes.

The invention discloses an unmanned aerial vehicle group scheduling method and system based on a multi-layer recurrent neural network, and relates to the technical field of unmanned aerial vehicle scheduling, and the method comprises the following steps: obtaining a state change sequence of offline unmanned aerial vehicles in a preset time window before offline, and obtaining an initial state vector; when re-online is detected, extracting a first state vector and performing vector fitting matching on the first state vector and the initial state vector; constructing a state fluctuation trajectory, evaluating changes of the state fluctuation trajectory under different task time scales, obtaining state fluctuation gradient distribution, converting the state fluctuation gradient distribution into a continuous state vector sequence, performing vector fitting truth compensation on the continuous state vector sequence and a preset reference state vector cluster, and identifying a weak oscillation region according to a truth compensation result; the state vector of the weak oscillation area is converted into a correction mask, the offline unmanned aerial vehicle input state vector of the multi-layer recurrent neural network is corrected and used for unmanned aerial vehicle group scheduling prediction, and the problem that state information is lagged or abnormal due to the fact that the unmanned aerial vehicles are online again after offline is solved.

The invention relates to the technical field of artificial intelligence analysis and optimization of a power system, and discloses a line loss variable separation method, system and device based on dynamic time sequence vector fitting, and a medium, and the method comprises the steps: fusing multi-source heterogeneous data, and constructing an enhanced feature vector sequence through an attention mechanism and a physical equation constraint; establishing a time-varying causal graph model based on a dynamic Bayesian network, introducing an attention mechanism to calculate time sequence feature similarity, calculating time-varying causal strength in combination with physical constraint loss and topological distance, and deducing dynamic causal; a theoretical line loss curve is dynamically fitted in a physical-data double-track modeling mode, and key nodes in a causal graph model are used as correction factors; the contribution degree of each factor to the line loss difference is quantified based on a Shapley value algorithm, and accurate separation and attribution of line loss components are realized.

The application discloses a macro modeling method for ensuring direct current precision, and the method comprises the following steps: reading n-port network parameters; initializing sampling points for constructing a macro model; initializing the order of the macro model; initializing the pole of the macro model; establishing a weighted linear system according to the current order, the sampling points and the pole; solving a linear equation set, judging convergence according to an error, and obtaining the macro model; and outputting the optimized macro model by applying a residue matrix disturbance to optimize the macro model. The macro modeling method for ensuring direct current precision provided by the application controls the direct current precision in two stages. In the first stage, a weighted least square method is adopted on the basis of a linear system established by a traditional vector fitting algorithm to preliminarily control the direct current precision. In the second stage, a small disturbance is applied to the residue matrix of the macro model, so that the disturbed macro model has accurate direct current characteristics.

The invention provides a parametric modeling method and device for a silicon-based millimeter wave on-chip component, and belongs to the technical field of integrated circuit modeling and millimeter wave circuit design. The method comprises the following steps: under a preset key parameter interpolation node, acquiring a transmission parameter of a de-embedding test structural member comprising a de-embedded component at each test frequency point; removing a parasitic effect embedded in the test structural member by using transmission matrix operation so as to obtain a transmission matrix of the de-embedded component and obtain a scattering parameter of the de-embedded component; then, through a vector fitting algorithm, obtaining a pole-residue model of the de-embedded component under the parameter interpolation node; and based on the pole-residue model under each parameter interpolation node, establishing a parameterized de-embedding model of the de-embedded component through a gravity center interpolation algorithm. According to the method, rapid and accurate modeling of silicon-based millimeter wave on-chip components of any size can be realized, and the reliability and efficiency of millimeter wave integrated circuit design are improved.

The present invention relates to a purifier turbulence fitting system, an intelligent state assessment system, and an intelligent control system based on an adversarial neural network. The intelligent control system includes a cloud-based purifier turbulence vector pre-training model, a purifier multi-point flow velocity sensor, a neural network turbulence vector correction module, a turbulence vector pre-processing model, a neural network turbulence vector single time slice generation module, a discriminative neural network turbulence vector single time slice assessment module, a neural network turbulence vector multi-time slice generation module, a discriminative neural network turbulence vector multi-time slice assessment module, a neural network turbulence vector fitting flow direction module, a neural network purifier operation status assessment module, and an intelligent control system. The present invention uses joint detection of multiple detection points and the purifier pre-training model to fit and iteratively correct the purifier turbulence output, thereby achieving accurate control of the purifier.

The invention discloses a neural network electromagnetic performance prediction method with causality and passivity constraints, and the method comprises the steps: obtaining geometric design variables of a TSV structure to be detected, inputting the geometric design variables into a trained electromagnetic performance prediction model, and obtaining the prediction values of a plurality of scattering coefficients of the TSV structure to be detected; wherein the electromagnetic performance prediction model comprises a polar point sub-network, a residue sub-network and a prediction sub-network, and the polar point sub-network and the residue sub-network are respectively used for determining a to-be-detected polar point vector and a to-be-detected residue vector corresponding to each scattering coefficient according to geometric design variables of a to-be-detected TSV structure; the prediction sub-network is used for determining a prediction value of a scattering coefficient of a corresponding type according to a to-be-measured pole vector and a to-be-measured residue vector; the electromagnetic performance prediction model is trained through a sample pole vector and a sample residue vector, and the sample pole vector and the sample residue vector are obtained by processing a sample scattering coefficient based on a vector fitting technology. The method is low in implementation cost and good in adaptability.

The invention discloses a macro modeling method for ensuring direct current precision. The method comprises the following steps: reading n-port network parameters; initializing sampling points used for constructing a macro model; initializing the order of the macro model; initializing a pole of the macro model; establishing a weighted linear system according to the current order, the sampling point and the pole; solving the system of linear equations, judging convergence according to errors, and obtaining a macro model; the macro model is optimized by applying residue matrix disturbance, and the optimized macro model is output. According to the macro modeling method for guaranteeing the direct current precision, the direct current precision is controlled in two stages, in the first stage, a weighted least square method is adopted on the basis of establishing a linear system through a traditional vector fitting algorithm, and the direct current precision is preliminarily controlled; and in the second stage, tiny disturbance is applied to the residue matrix of the macro model, so that the disturbed macro model has accurate direct current characteristics.

The present application relates to the technical field of network data processing, in particular to a self-evolving online learning personalized recommendation method, comprising: collecting behavior data of learners in real time during online learning; constructing a simplified knowledge graph of each subject knowledge system by using a hierarchical decoupling method; obtaining the learning behavior of learners at each knowledge point based on behavior data mapping by using a behavior continuity merging algorithm; fitting the learning ability of learners at each knowledge point based on behavior data by using a time sequence ability vector fitting algorithm; periodically determining the first recommended learning mode of each knowledge point based on the learning behavior and learning ability of group learners at each knowledge point; and correcting the first recommended learning mode of each knowledge point in the current period based on the learning behavior and learning ability of individual learners to serve as a personalized recommendation result, realizing double-driven recommendation of "group effectiveness + individual adaptation", and simultaneously realizing dynamic standard correction and real-time response, improving the logical coherence and accuracy of the recommendation.

A method for zero-point correction of an S-parameter model includes: calculating the S-parameters at zero frequency based on the constructed S-parameter model; calculating the error matrix between the S-parameter model and the original S-parameters at zero frequency; calculating the residues corresponding to the preset real poles based on preset real poles and the error matrix; and adding a term to the S-parameter model using the preset real poles and their corresponding residues to obtain the zero-point corrected S-parameter model. This method further corrects the S-parameters after vector fitting and passivity correction, ensuring that the values ​​of the S-parameters at zero frequency remain consistent with the original S-parameters while minimizing disruption of the original model's passivity and maintaining accuracy. This corrects the error of the original model's S-parameters at zero frequency, eliminating errors in subsequent simulations caused by the inaccuracy of the S-parameters at zero frequency.

The invention discloses an S parameter time domain modeling method, device, medium and system based on vector fitting, and belongs to the field of microwave radio frequency device modeling and emulation.The method comprises the steps that a frequency domain response function is constructed based on a device S parameter, a residue and a pole value are approximated step by step through iterative optimization and a least square solution method, and the frequency domain response function is obtained; and finally, carrying out time domain convolution on the input signal based on the transfer function, and carrying out conversion of the output signal through the time domain convolution. According to the method, the simulation efficiency of the broadband microwave array system link time domain signal flow is improved.

The invention relates to a mechanism-data fusion new energy grid-connected system small interference stability analysis method. The method comprises the following steps: firstly, obtaining operation data of a new energy unit, and carrying out normalization preprocessing; then, a new energy unit impedance characteristic neural network model is constructed and trained, and a new energy field station impedance identification model is synthesized based on the trained unit impedance model in combination with the field station topology and the line parameters; then, on the basis of the new energy station impedance identification model, a vector fitting method and a PySR algorithm are adopted to construct an optimal fitting transfer function of the new energy station; then, determining a discrete state space equation based on the optimal fitting transfer function of the new energy station; and finally, calculating a discrete eigenvalue and a continuous eigenvalue of the system based on the discrete state space equation, and analyzing the stability of the system based on the discrete eigenvalue and the continuous eigenvalue. The online, continuous and accurate dynamic description of the impedance of the new energy unit and the dynamic stability prediction and analysis of a complex system are realized.

The invention discloses a new energy station broadband oscillation online early warning method based on a virtual split ratio, and belongs to the technical field of power system stability analysis and control. The method comprises the following steps: injecting a harmonic wave small disturbance signal into a current or voltage sampling value of a new energy converter, synchronously recording a static var generator (SVG) branch current waveform and extracting a disturbance component, and calculating a virtual shunt ratio; obtaining wide frequency band data through frequency sweeping, and obtaining a domain expression of a virtual split ratio through vector fitting; and solving the zero point of the expression to obtain a station characteristic root, and carrying out oscillation risk judgment and early warning according to the position of the station characteristic root on the complex plane. According to the method, control parameters and line parameters of the new energy converter in the station do not need to be obtained, a high-power disturbance source is not needed, the problems that an existing method is high in parameter dependence degree, modeling is difficult, and the calculated amount is large are solved, and rapid online early warning of the broadband oscillation risk in the full black box state of the new energy station is achieved.

The application relates to a passive property analysis method, device, equipment and medium in an S parameter modeling process. The method comprises the following steps: acquiring pole points and residue matrixes of S parameter vector fitting, each pole point corresponding to a residue matrix; constructing a new S parameter rational fraction based on the pole points and the residue matrixes; constructing a judgment matrix based on the pole points and the residue matrixes; constructing a plurality of detection frequency points according to the judgment matrix; and determining a passive abnormal frequency point based on the new S parameter rational fraction and the plurality of detection frequency points. When the passive property analysis is performed in the S parameter modeling process, the pole points and the residue matrixes of the S parameter vector fitting are considered to determine the passive abnormal frequency point, the frequency at which the passive property of the S parameter will be abnormal can be quickly determined, the violation degree of the frequency point in which the passive property is seriously violated is given, the high-cost calculation process of an original Hamiltonian is avoided, the calculation efficiency is improved, and the pressure of subsequent passive property correction is reduced.

The application discloses a new energy station wide frequency oscillation online early warning method based on a virtual shunt ratio, and belongs to the technical field of power system stability analysis and control. The method comprises the following steps: injecting a harmonic small disturbance signal into a current or voltage sampling value of a new energy converter, synchronously recording a static var generator (SVG) branch current waveform and extracting a disturbance component, and calculating a virtual shunt ratio; obtaining wide frequency band data through frequency sweeping and obtaining a domain expression of the virtual shunt ratio by using vector fitting; solving the zero point of the expression to obtain station characteristic roots, and judging and warning an oscillation risk according to the position of the characteristic roots on a complex plane. The application does not need to obtain control parameters and line parameters of the new energy converter in the station, and does not need a high-power disturbance source, thereby solving the problems of high parameter dependency, difficult modeling and large calculation amount of the existing method, and realizing rapid online early warning of the wide frequency oscillation risk in the full "black box" state of the new energy station.

The invention discloses an AC / DC power transmission line broadband equivalent analysis modeling method and system, and belongs to the technical field of power system AC / DC power transmission, and the method comprises the steps: obtaining the self-impedance and mutual impedance frequency change parameters of each phase based on a phase domain frequency change model, and converting the self-impedance and mutual impedance into differential mode impedance and common mode impedance; vector fitting is carried out on the impedance data to construct an RL branch parameter solving equation, the cascade number is determined, and an RLC circuit equivalent model corresponding to differential mode impedance and common mode impedance is obtained; a topological form of a differential mode RLC equivalent circuit corresponding to differential mode impedance and a compensation current source is adopted to construct a power transmission line equivalent circuit considering mutual inductance. According to the long-distance AC / DC submarine cable RLC equivalent modeling method, an AC / DC cable port voltage and current relation considering mutual inductance characteristics is deduced based on phase-mode transformation, a cable mutual inductance equivalent circuit based on a differential / common mode RLC circuit and a compensation current source is constructed, and the long-distance AC / DC submarine cable RLC equivalent modeling method capable of accurately reflecting frequency change, time delay, distribution characteristics and mutual inductance effects is provided.

The application provides a network parameter representation method based on a multi-path convolutional autoencoder. Network parameters are divided into network parameter real parts and network parameter imaginary parts. Each part is processed through N+1 paths, the first of which is a low-frequency path, and the remaining N paths are high-frequency compensation paths, each path processing different information of the network parameters. The network parameter representation method can avoid the residual-pole mismatch problem existing in the vector fitting method, has higher compression efficiency and higher accuracy, and can be used to establish a neural network proxy model and accelerate the design of microwave devices.

A method for multi-objective vector fitting includes the following steps: 1) processing a given dataset to construct a single-objective fitting dataset; 2) determining initial poles and using the initial poles and frequency sampling points to establish a fundamental matrix; 3) separating the real and imaginary parts of the fundamental matrix to construct a real fundamental matrix; 4) performing a simplified QR decomposition on the real fundamental matrix to obtain the first M columns of the complete Q matrix, denoted as Q. s Matrix, and for Q s The matrix is ​​stored; 5) Construct and solve the pole coefficient equation to obtain the pole coefficients; 6) Construct the pole characteristic equation using the pole coefficients and the initial poles to calculate the new poles; 7) Calculate the residues of each matrix element corresponding to the new poles to complete the vector fitting. This invention provides a method for multi-objective vector fitting that significantly reduces the computational complexity and improves computational efficiency.

The application relates to a track train part abnormality detection method based on point-surface distance, and relates to the technical field of track part abnormality detection.The application comprises the following steps: a surface identification step, in which a measured special surface in a target image is identified through a surface identification strategy, and corresponding special identification features are generated; a model indexing step, in which a target part model is called from a part type database according to the special identification features and is imported into a space coordinate system; a vector fitting step, in which a presentation vector of the target part model in the space coordinate system is determined through a model presentation strategy, and a coordinate mapping relationship between the space coordinate system and the target image is constructed; a point confirmation step, in which the graphic plane coordinates of a reference special point in the target image are determined according to the mapping relationship; and a deviation calculation step, in which a difference value of the coordinates of the reference special point and the measured special point is calculated to obtain a special point deviation, and a reference distance deviation is solved through a preset distance solving algorithm.The application has the effect of facilitating detection of abnormal vector changes of track train parts.

The invention discloses a constraint vector fitting system and method fusing a shared pole structure and a local pole structure, designs a novel VF structure, introduces mixed pole configuration combining a shared pole and a local pole, and can maintain high-quality fitting of a Y parameter even in the presence of a loading phase. Therefore, the sensitivity of fitting precision to phase distortion is reduced; through post-processing identification of the model and iterative elimination of phase contributions corresponding to local poles and linear terms, compatibility with a traditional VF is ensured; in consideration of the characteristic that the VF mainly solves the residual error, the constraint on the number of transmission zeros is reconstructed into a group of linear constraints on the residual error, so that the problem can still be solved in the VF framework; in addition, a nonlinear residual constraint proposed in a physical realizability requirement is formalized into a nonlinear least square optimization problem to be introduced into a fitting process; the VF problem with physical constraints is solved by adopting an augmented Lagrange method ALM, and unified balance of fitting precision and physical consistency is realized.

The application provides a microwave filter shape-coupling relationship hybrid modeling method, device and storage device, constructs original data sets D1 and D2, extracts Y parameters y1 in D1 through a vector fitting method, constructs a data set Y1 containing resonance screw length x1 and Y parameters y1, extracts Y parameters y2 in D2, constructs a data set Y2 containing coupling screw length x2 and Y parameters y2, designs a microwave filter shape-coupling hybrid model, a shape-coupling relationship model in a serious detuning state and a shape-coupling relationship model in a slight detuning state, and realizes mapping from resonance screw length x1 and coupling screw length x2 to Y parameters y1 and y2. The application has the beneficial effects that the microwave filter is divided into two states of slight detuning and serious detuning, different structure geometric parameters are selected to establish shape-coupling relationship models, the complexity of establishing shape-coupling relationship models is reduced, and the accuracy of shape-coupling relationship models in various states is improved.

The present invention provides a model predictive control strategy for an optimal switching sequence of MMC based on output voltage space vector fitting. The strategy calculates the coordinates of each candidate vector in the g-h coordinate system from the vector prediction value according to the discrete prediction model of the output voltage space vector of the three-phase MMC AC side; obtains the optimal switching sequence by screening the redundant switching states of the candidate vectors; constructs a value function of the sum of squared output current errors based on the current change gradient and obtains the optimal action time expression by taking the partial derivative thereof; calculates the optimal duty cycle of the bridge arm and the number of submodules turned on according to the bridge arm unbalanced voltage drop prediction model; and achieves submodule capacitor voltage balance through a sorting algorithm. The benefit of the present invention is that compared with the traditional model predictive control strategy, the strategy has a small computational burden, effectively reduces the output current harmonic content, and has a more concentrated harmonic spectrum distribution. Taking MMC as an example, a general algorithm for screening the optimal switching sequence of a multi-level converter is designed, which can be applied to any level and has a constant computational load.

A new energy base oscillation risk multi-port screening method, system and related device, the method comprising: collecting basic data of a new energy base, the basic data of the new energy base comprising an impedance data set of a new energy unit, a grid structure and parameters of a new energy grid-connected system, and an operation mode of the new energy grid-connected system; obtaining a multi-port equivalent model of the new energy base by using the basic data of the new energy base through vector fitting, impedance aggregation and a multi-port model generation process; the oscillation risk of the multi-port equivalent model of the new energy base is evaluated by using a Nyquist stability criterion, and the oscillation risk at each port is quantitatively screened by using a damping ratio index. The improved stability judgment method considering the right half plane pole is provided based on the Nyquist stability criterion, the influence of the right half plane pole of the open-loop transfer function on stability judgment can be avoided, and accurate positioning of the oscillation dominant field station can be achieved by adopting the damping ratio index.

The invention discloses a positioning method for a performance abnormity problem of a three-dimensional heterogeneous integrated radio frequency circuit, and belongs to the field of integrated circuit design and manufacturing. The method comprises the following steps: firstly, carrying out electromagnetic field simulation on a circuit, carrying out joint simulation with an active device, obtaining a transfer function, and extracting poles through vector fitting; secondly, a variable parameter set representing physical attributes and geometric dimensions of the connection structure is defined, and small-amplitude disturbance is applied; then, calculating a sensitivity parameter set of poles based on disturbance, and further positioning a sensitive structure which has the most significant influence on the circuit performance according to sensitivity ranking; carrying out refined modeling on the sensitive structure; and finally, by comparing pole distribution and circuit performance change before and after refined modeling, realizing reason analysis of performance abnormality. According to the invention, the sensitive structure and the coupling path which cause electromagnetic performance problems such as high-frequency resonance and gain abnormity can be systematically and efficiently identified and positioned.

The invention provides a harmonic modeling method and system based on rotation coordinate transformation and vector fitting, and belongs to the field of power system analysis and modeling. The method comprises the steps of collecting three-phase voltage and three-phase current original data of a target node of the power distribution network, and performing preprocessing to obtain standardized voltage and current data; according to a preset rotation frequency set, performing rotation coordinate transformation on the standardized voltage data to obtain transformed voltage data; performing fast Fourier transform on the transformed voltage data and the standardized current data to obtain voltage frequency domain data and current frequency domain data; calculating a frequency domain admittance matrix according to the voltage and current frequency domain data to obtain frequency domain admittance data; fitting the frequency domain admittance data by adopting a vector fitting method to obtain a transfer function; and integrating all transfer functions in the rotation frequency set, and constructing a complete harmonic coupling admittance model. According to the method, the multi-frequency harmonic coupling characteristics can be accurately described, and the calculation efficiency is high.

The invention discloses an equivalent network modeling method for a passive device, and relates to the technical field of passive device modeling. The method comprises the following steps: acquiring port admittance data of a passive device, and performing rational function fitting on the port admittance data by adopting a vector fitting method to obtain a pole and a residue; carrying out passivity constraint optimization on the pole and the residue by adopting a PSO (Particle Swarm Optimization) algorithm to obtain an optimal solution; the passivity constraint optimization comprises port passivity optimization and element passivity optimization; and constructing an equivalent circuit network of the passive device according to the optimal solution. According to the method, passivity and physical realizability are met, and the engineering suitability of a device model is remarkably improved.

The invention discloses a method and a device for analyzing a feasible region and optimizing the capacity of a converter of a network-following hybrid system, and belongs to the technical field of stability analysis of a power system. Comprising the following steps: constructing an impedance model of a GFL-GFM parallel system to obtain a closed-loop admittance matrix of the system; rational approximation is carried out on the closed-loop admittance matrix through vector fitting, and system characteristic values are extracted; according to the relation between the system characteristic value and the output power of different converters, the action direction and the action degree of the power of any converter on the system dominant characteristic value are obtained; discretizing a feasible region in combination with capacity constraint and power constraint, and solving the feasible region of the system; and on the basis of the obtained feasible region, quantifying the power grid strength of the system, and analyzing the change of the feasible region of the system by combining the power grid strength of the system and the change of the output power of the converter, thereby optimizing the capacity of the converter. According to the method, the calculation burden of feasible region solution can be reduced, and the capacity configuration and power distribution of the converter can be accurately guided.