A multi-working-condition network-configuration type converter virtual impedance cooperative control method and system

Abstract

The present application relates to the technical field of power system control, and specifically discloses a kind of multi-working condition network type converter virtual impedance collaborative control method.The present application obtains global collaborative situation benchmark quantity and multiple current virtual impedance values according to multi-working condition operating state identification, obtains voltage total harmonic distortion and voltage unbalance degree to obtain overall virtual impedance stability coefficient and corrects current virtual impedance value according to overall power quality characteristics, obtains single capacity deviation according to power output characteristics, obtains equivalent line impedance value and obtains collaborative consistency regulation constraint quantity accordingly, and finally regulates and restricts current stable virtual impedance value to obtain target virtual impedance according to collaborative consistency regulation constraint quantity, controls multiple network type converters to converge to global collaborative situation benchmark quantity.The present application can effectively solve the problem of reactive power distribution and system oscillation caused by virtual impedance parameter mismatch when multiple network type converters are operated in parallel under multi-working condition.

Description

Technical Field

[0001] This invention relates to the field of power system control technology, and in particular to a virtual impedance collaborative control method and system for multi-condition grid-type converters. Background Technology

[0002] Grid-type converters are core equipment for achieving high-proportion renewable energy grid integration in new power systems. They provide voltage and frequency support to the grid by simulating the external characteristics of synchronous generators. Virtual impedance technology is a key means for grid-type converters to achieve reactive power distribution. By connecting a programmable virtual impedance in series in the control loop, each converter exhibits the desired output impedance characteristics, thereby achieving reactive load distribution according to capacity ratio.

[0003] However, when multiple grid-connected converters operate in parallel at a common coupling point, existing virtual impedance control schemes reveal significant coordination mismatch issues. On one hand, the actual line impedances from each converter to the common coupling point differ, causing the reactive load actually borne by each converter to deviate from the capacity-ratio allocation principle even with identical virtual impedance parameters. On the other hand, dynamic changes in grid operating conditions (such as sudden load changes, fluctuations in renewable energy output, and changes in grid short-circuit capacity) make fixed virtual impedance parameters unsuitable for multi-condition operation. This can easily lead to multi-machine interactive oscillations under weak grid conditions and insufficient reactive power regulation margin under strong grid conditions. Furthermore, deteriorating power quality (harmonic distortion, three-phase imbalance) further exacerbates the mismatch of virtual impedance parameters, creating a vicious cycle.

[0004] Existing solutions mostly employ a single-machine independent virtual impedance setting method, lacking information exchange and collaborative constraint mechanisms between multiple machines, thus failing to achieve globally optimal reactive power distribution under dynamic operating conditions. Although this can be mitigated by manually adjusting parameters offline, the response speed is slow and it cannot adapt to rapid changes in operating conditions. Therefore, a multi-condition network-type converter virtual impedance collaborative control method is needed to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide a virtual impedance collaborative control method and system for multi-condition grid-type converters to solve the technical problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: A method and system for virtual impedance coordinated control of a multi-condition grid-type converter, comprising: The real-time operating data of multiple grid-connected converters at a common coupling point is obtained. The real-time operating data includes overall power quality characteristics, power output characteristics of each converter, and multi-condition operating status indicators. The global collaborative situation reference quantity and multiple current virtual impedance values ​​are obtained based on the multi-condition operation status identifier. The global collaborative situation reference quantity includes multiple virtual common node voltages and total reactive load demand for a preset time period. The total harmonic distortion rate and voltage imbalance are obtained based on the overall power quality characteristics. A power quality coupling distortion index is constructed based on the total harmonic distortion rate and voltage imbalance. An overall virtual impedance stability coefficient is obtained based on the power quality coupling distortion index. Multiple current virtual impedance values ​​are corrected based on the overall virtual impedance stability coefficient to obtain multiple current stable virtual impedance values. The individual capacity deviation of each multi-grid converter is obtained based on the power output characteristics. The current stable virtual impedance values ​​are adjusted according to the single-unit capacity deviation to obtain multiple target virtual impedances. The multiple grid-type converters are then controlled according to the multiple target virtual impedances to obtain the control result.

[0007] The beneficial effects of this application are as follows: This invention achieves dynamic identification and correction of multi-condition operation through online impedance scanning and short-circuit capacity ratio estimation, enabling virtual impedance parameters to adapt to changes in grid strength; by introducing total harmonic distortion rate and voltage imbalance to construct an overall virtual impedance stability coefficient, it achieves proactive defensive correction of virtual impedance parameters under deteriorating power quality conditions; by injecting multi-frequency stepped detection signals and correcting for temperature and load rate, it obtains accurate equivalent line impedance, eliminating the impact of line parameter uncertainty on reactive power allocation accuracy; by constructing a line impedance coupling matrix and deviation priority sequence to obtain coordinated and consistent control constraints, it achieves global coordination of adjustment direction and rate among multiple units, effectively avoiding interactive oscillations caused by simultaneous large-scale adjustments by multiple units; and by using an iterative convergence closed-loop mechanism, it ensures that the final reactive power allocation deviation meets accuracy requirements. Compared with the existing method of independently setting virtual impedance for a single unit, this scheme significantly improves the reactive power allocation accuracy and system stability of multi-unit parallel operation, and reduces the risk of transient oscillations during multi-condition switching. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of a method flow according to an embodiment of this application.

[0009] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0010] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0011] like Figure 1As shown, this application provides a virtual impedance collaborative control method for a multi-condition network converter, including: This invention relates to the field of power system control technology, and more particularly to a virtual impedance collaborative control method for multi-condition grid-connected converters. Grid-connected converters, as core equipment for achieving high-proportion renewable energy grid integration in new power systems, provide voltage and frequency support to the power grid by simulating the external characteristics of synchronous generators. Virtual impedance technology is a key means for grid-connected converters to achieve reactive power distribution. By connecting a programmable virtual impedance in series in the control loop, each converter exhibits the desired output impedance characteristics, thereby achieving reactive load distribution according to capacity ratio.

[0012] However, when multiple grid-connected converters operate in parallel at a common coupling point, existing virtual impedance control schemes suffer from significant coordination mismatch issues. The actual line impedances from each converter to the common coupling point differ, causing the reactive load actually borne by each converter to deviate from the capacity-ratio allocation principle even with identical virtual impedance parameters. Dynamic changes in grid operating conditions mean that fixed virtual impedance parameters cannot adapt to the demands of multiple operating conditions. Under weak grid conditions, this can easily lead to multi-machine interactive oscillations, while under strong grid conditions, it results in insufficient reactive power regulation margin. Deteriorating power quality further exacerbates the mismatch of virtual impedance parameters. Existing schemes mostly employ independent virtual impedance setting for each machine, lacking information exchange and coordination constraint mechanisms between multiple machines, thus failing to achieve globally optimal reactive power allocation under dynamic operating conditions.

[0013] Based on the above, this invention provides a method for coordinated virtual impedance control of multi-condition network converters, which will be described in detail below with reference to specific embodiments and accompanying drawings.

[0014] Example 1

[0015] This invention provides a method for coordinated virtual impedance control of a multi-condition network converter. Figure 1 This is a flowchart illustrating a virtual impedance coordinated control method for a multi-condition network converter according to an exemplary embodiment. Figure 1 As shown, this method is applied to a power system in which multiple grid-connected converters are connected in parallel to a common coupling point. This system typically also includes a central coordination controller, local controllers for each converter, a power quality monitoring device at the common coupling point, a power measurement device, and a communication network. The central coordination controller is the core decision-making unit, responsible for global situational awareness and generating coordinated control commands; each converter's local controller receives the target virtual impedance command and updates the parameters of its local control loop; the power quality monitoring device is used to collect voltage harmonics and three-phase imbalance information at the common coupling point in real time; and the power measurement device is used to collect the active and reactive power output of each converter in real time. The method includes the following steps: S1. Obtain real-time operating data of multiple grid-connected converters at a common coupling point, wherein the real-time operating data includes overall power quality characteristics, power output characteristics of each converter, and multi-condition operating status identifiers. In this embodiment, multiple grid-connected converters refer to two or more grid-connected converters connected in parallel to the same common coupling point. These can be power electronic devices with grid-connected control capabilities, such as distributed photovoltaic inverters, energy storage converters, and wind power converters. The common coupling point is the converging node for the electrical connections of multiple converters and also the interface point with the external power grid.

[0016] Overall power quality characteristics refer to the description of the quality status of the voltage signal at the point of common coupling, including but not limited to indicators such as total harmonic distortion (THD), harmonic content, three-phase voltage imbalance, and voltage deviation. These characteristics reflect the current power quality level of the power grid and are an important basis for determining whether virtual impedance parameters need to be corrected.

[0017] The power output characteristics of each individual converter refer to the actual active and reactive power output values ​​and their changing trends of each grid-connected converter. This characteristic reflects the current load-bearing status of each converter and is the basic data for calculating reactive power distribution deviation.

[0018] The multi-condition operating status identifier is a discrete label used to characterize the current power grid operating condition type, which may include strong power grid condition, weak power grid condition, extremely weak power grid condition, load change condition, and new energy large-scale generation condition. This identifier can be obtained through preset operating condition classification rules or a classification model trained on historical operating data, and serves as the index key for subsequent matching of corresponding control strategies.

[0019] S2. Obtain the global collaborative situation reference quantity and multiple current virtual impedance values ​​based on the multi-condition operation status identifier, wherein the global collaborative situation reference quantity includes multiple virtual common node voltages and total reactive load demand for a preset time period; In this embodiment, the global collaborative situational baseline is the target reference quantity for the collaborative control of multiple converters, representing the ideal operating state that the system expects to achieve under the current operating conditions. The virtual common node voltage refers to the reference voltage value set in the control loop of each converter under the virtual impedance control framework; this voltage value determines the reactive power output characteristics of the converter. The total reactive power load demand refers to the total reactive power load demand at the current common coupling point, which is the total reactive power that each converter needs to collaboratively undertake.

[0020] Multiple current virtual impedance values ​​refer to the virtual impedance parameter values ​​currently in use in the virtual impedance control loops of each converter under the current operating conditions. These parameter values ​​are dynamically determined based on the current operating condition identification results and the estimated grid short-circuit capacity ratio, rather than fixed offline setting values.

[0021] S3. Obtain the total harmonic distortion rate and voltage imbalance based on the overall power quality characteristics, and obtain the overall virtual impedance stability coefficient based on the total harmonic distortion rate, the voltage imbalance and the voltage of multiple virtual common nodes, and correct multiple current virtual impedance values ​​based on the overall virtual impedance stability coefficient to obtain multiple current stable virtual impedance values. In this embodiment, the total harmonic distortion (THD) of voltage is a comprehensive indicator that measures the degree to which the voltage waveform deviates from an ideal sine wave; a higher value indicates worse power quality. Voltage unbalance is an indicator that measures the symmetry of the amplitude and phase of the three-phase voltage; a higher value indicates a more severe degree of three-phase asymmetry.

[0022] The overall virtual impedance stability coefficient is a quantitative indicator that comprehensively reflects the impact of the current power quality state on the stability of virtual impedance parameters. When power quality deteriorates, this coefficient deviates from the ideal value, indicating that the virtual impedance parameters need to be corrected to maintain system stability. The correction process includes stability correction for the fundamental virtual impedance component and attenuation correction for the harmonic virtual impedance components, and finally, the current stable virtual impedance value is obtained through superposition and reconstruction.

[0023] S4. Obtain the actual reactive power output of each converter based on the power output characteristics, and obtain the capacity deviation of each unit based on the multiple actual reactive power outputs and the total reactive load demand. In this embodiment, the actual reactive power output is the reactive power value actually injected into the grid by each converter at the current moment. Individual capacity deviation refers to the deviation between the reactive load actually borne by each converter and the reactive load it should bear according to its rated capacity ratio. This deviation is the core input for subsequent coordinated control; its positive or negative sign indicates whether the converter is over-outputting or under-outputting reactive power, and its absolute value reflects the severity of the deviation.

[0024] S5. Obtain multiple equivalent line impedance values ​​from multiple grid-type converters to the common coupling point, and obtain a coordinated consistency control constraint based on multiple individual capacity deviations and multiple equivalent line impedance values, wherein the coordinated consistency control constraint includes a control direction constraint and a control rate constraint. In this embodiment, the equivalent line impedance value refers to the equivalent line impedance from the output terminal of each converter to the common coupling point, including resistive and inductive components. This impedance value is obtained through a combination of theoretical calculation and online measurement, and is corrected for temperature and magnetic saturation to reflect the actual operating conditions.

[0025] Coordinated and consistent control constraints are comprehensive constraints used to constrain the virtual impedance regulation behavior of each converter. The regulation direction constraint indicates whether each converter should increase or decrease its virtual impedance; the regulation rate constraint limits the maximum change in virtual impedance of each converter within a single control cycle to prevent simultaneous large-scale regulation by multiple converters from causing interactive oscillations.

[0026] S6. Adjust and constrain multiple current stable virtual impedance values ​​according to the cooperative consistency control constraint to obtain multiple target virtual impedances, and control the multiple grid-type converters to converge to the global cooperative status reference quantity according to the multiple target virtual impedances.

[0027] In this embodiment, the target virtual impedance is the final virtual impedance parameter value of each converter determined after collaborative constraint control. This parameter value simultaneously satisfies the requirements for power quality stability, reactive power distribution accuracy, and multi-machine collaborative stability. The convergence process is an iterative closed-loop process. By continuously monitoring the reactive power distribution deviation and determining whether it meets the convergence criterion, it ensures that the system eventually reaches the ideal operating state defined by the global collaborative situation benchmark.

[0028] The technical solution described above, through the synergistic effect of the aforementioned steps, effectively solves the problems of uneven reactive power distribution and system oscillation caused by virtual impedance parameter mismatch during the parallel operation of multiple grid-connected converters. First, by identifying multiple operating conditions and performing online impedance scanning, adaptive matching of virtual impedance parameters to grid operating conditions is achieved. Second, by power quality sensing and overall virtual impedance stability coefficient correction, proactive defense against harmonics and unbalanced operating conditions is achieved. Third, by accurately acquiring equivalent line impedance and correcting coupling propagation, the impact of line parameter differences on reactive power distribution is eliminated. Next, by constructing coordinated and consistent control constraints, global coordination of the adjustment behavior among multiple converters is achieved. Finally, through an iterative convergence closed-loop mechanism, the final control accuracy is ensured to meet requirements, and the reactive power distribution accuracy and system stability of multiple converters operating in parallel are significantly improved.

[0029] In one embodiment, step S2, which involves obtaining the global collaborative situational reference quantity and multiple current virtual impedance values ​​based on the multi-condition operating status identifier, includes: S21. Match a target impedance scanning strategy from a preset scanning strategy library according to the multi-condition operating status identifier. The target impedance scanning strategy includes scanning frequency range, disturbance signal amplitude and scanning duration. S22. According to the target impedance scanning strategy, control at least one of the multiple grid-type converters to inject a disturbance signal into the common coupling point, and collect the voltage response signal and current response signal at the common coupling point; S23. Perform synchronous spectrum analysis on the voltage response signal and the current response signal to obtain the voltage spectrum component and the current spectrum component within the scanning frequency range, and obtain the equivalent impedance of the power grid based on the voltage spectrum component and the current spectrum component; S24. Obtain the rated voltage at the common coupling point, and obtain the grid short-circuit capacity based on the rated voltage and the grid equivalent impedance, and obtain the grid short-circuit capacity ratio estimate based on the grid short-circuit capacity and the preset rated total capacity of the multiple grid-type converters; S25. The multi-condition operation status identifier is corrected according to the membership relationship between the estimated power grid short-circuit capacity ratio and the preset short-circuit capacity ratio threshold interval, so as to obtain the corrected multi-condition operation status identifier. S26. Obtain multiple virtual common node voltages based on the corrected multi-condition operating status identifier, the rated voltage, and the preset voltage stability margin; S27. Obtain multiple reactive power values ​​from the multiple grid-connected converters, sum them to obtain the total reactive load demand, and obtain the total reactive load demand based on the reactive power reserve coefficient corresponding to the corrected multi-condition operating status identifier and the real-time reactive power sum; and obtain the corresponding reactive power reserve coefficient and real-time reactive power sum based on the corrected multi-condition operating status identifier, and obtain the total reactive load demand based on the reactive power reserve coefficient and real-time reactive power sum. S28. Based on the corrected multi-condition operating status identifier and the estimated grid short-circuit capacity ratio, obtain multiple initial virtual impedances, and perform capacity normalization correction on the initial virtual impedances based on the preset rated capacity of multiple grid-type converters to obtain multiple current virtual impedance values.

[0030] As described in steps S21-S28 above, due to the significant differences in the impedance characteristics of the power grid under different operating conditions, if a uniform scanning strategy is used for impedance identification, the amplitude of the disturbance signal will be too small under weak power grid conditions, leading to insufficient signal-to-noise ratio, while the amplitude of the disturbance signal will be too large under strong power grid conditions, causing unacceptable interference to power quality. To automatically match the optimal impedance scanning parameters according to the current operating condition, this invention matches the target impedance scanning strategy from a preset scanning strategy library based on the multi-operating-condition operating status identifier. In this embodiment, the preset scanning strategy library is a pre-established operating condition-scanning strategy mapping table, which stores the optimal scanning parameter combinations corresponding to different operating condition types. The scanning frequency range determines the frequency coverage of impedance identification, typically covering the fundamental frequency (50Hz or 60Hz) and nearby key harmonic frequencies. The amplitude of the disturbance signal determines the strength of the injected signal, requiring a balance between signal-to-noise ratio and power quality impact. The scanning duration determines the frequency resolution and identification accuracy. For example, for strong power grid conditions, the scanning frequency range can be set to 40Hz to 500Hz, the disturbance signal amplitude can be set to 1% of the rated voltage, and the scanning duration can be set to 5s; for weak power grid conditions, the scanning frequency range can be set to 20Hz to 1000Hz, the disturbance signal amplitude can be set to 2% to 3% of the rated voltage, and the scanning duration can be set to 10s.

[0031] Since the equivalent impedance of the power grid is a key physical quantity for judging the strength of the power grid and determining the virtual impedance parameters, and this impedance cannot be obtained in real time through offline measurement, it must be obtained through online identification methods. To achieve accurate online identification of the power grid impedance without affecting normal power supply, this invention controls at least one of the multiple grid-type converters to inject a disturbance signal into the common coupling point according to the target impedance scanning strategy, and collects the voltage and current response signals at the common coupling point. In this embodiment, the disturbance signal can be a small-amplitude sinusoidal sweep frequency signal or a pseudo-random binary sequence signal, with its amplitude typically controlled within 1% to 3% of the rated voltage to ensure that the impact on power quality is within an acceptable range. After the disturbance signal is injected, the voltage and current at the common coupling point will produce corresponding response changes, and these response signals are synchronously recorded by a high-precision acquisition device.

[0032] Since voltage and current response signals contain fundamental components, disturbance response components, and background noise, directly calculating impedance in the time domain would severely interfere with identification accuracy due to background noise. To accurately extract impedance information at each frequency point from the noisy signal, this invention performs synchronous spectrum analysis on the voltage and current response signals to obtain the voltage and current spectrum components within the scanning frequency range, and then obtains the equivalent impedance of the power grid based on these components. In this embodiment, synchronous spectrum analysis is implemented using Fast Fourier Transform or Discrete Fourier Transform. After converting the time-domain signal to the frequency domain, the complex ratio of the voltage spectrum component to the current spectrum component is calculated at each scanning frequency point, thus obtaining the equivalent impedance of the power grid at that frequency point.

[0033] Since the short-circuit capacity ratio is a core indicator for judging the strength of the power grid, and this indicator needs to be calculated based on the equivalent impedance of the power grid and the rated parameters of the system, this invention obtains the rated voltage at the point of common coupling and calculates the short-circuit capacity of the power grid based on the rated voltage and the equivalent impedance of the power grid. The calculation formula is as follows:

[0034] Among them, S sc U represents the grid short-circuit capacity under the fundamental frequency. N For the rated voltage, Z grid (f0) is the equivalent impedance of the power grid at the fundamental frequency f0; The short-circuit capacity ratio is estimated based on the grid short-circuit capacity and the preset rated total capacity of the multiple grid-connected converters, wherein the calculation formula is:

[0035] Among them, R scr S is the estimated short-circuit capacity ratio of the power grid. total This is the preset rated total capacity.

[0036] The larger the ratio, the stronger the power grid; the smaller the ratio, the weaker the power grid.

[0037] In this embodiment, the formula for calculating the grid short-circuit capacity is the square of the rated voltage divided by the modulus of the grid's equivalent impedance. The grid short-circuit capacity ratio estimate is the ratio of the grid short-circuit capacity to the preset total rated capacity of multiple grid-connected converters. A larger ratio indicates a stronger grid, while a smaller ratio indicates a weaker grid.

[0038] Since the initial multi-condition operating status identifier may be obtained based on historical data or coarse judgment rules, it has a certain degree of inaccuracy. If the identifier is directly used for subsequent control strategy matching, it may lead to a mismatch between control parameters and actual operating conditions. In order to accurately correct the operating status identifier using online identification results, this invention corrects the multi-condition operating status identifier according to the membership relationship between the estimated grid short-circuit capacity ratio and the preset short-circuit capacity ratio threshold interval, thus obtaining the corrected multi-condition operating status identifier. In this embodiment, the preset short-circuit capacity ratio threshold interval divides the grid short-circuit capacity ratio into several levels. For example, the preset short-circuit capacity ratio threshold interval can be set as follows: the first threshold interval is R scr ≥20 corresponds to high-voltage power grid operating conditions; the second threshold range is 10≤R. scr <20 corresponds to medium power grid operating conditions; the third threshold range is 3≤R scr <10 corresponds to weak grid conditions; the fourth threshold range is R. scr <3 corresponds to extremely weak power grid conditions.

[0039] The estimated short-circuit capacity ratio of the power grid calculated online is compared with the above threshold range to determine its level, thereby correcting the initial operating condition label.

[0040] Since the virtual common node voltage is the reference voltage for the control loop of the grid-type converter, its setpoint directly affects the converter's reactive power output characteristics and voltage regulation capability, and needs to be reasonably determined based on the current operating conditions and voltage stability margin requirements. To determine a reasonable virtual common node voltage while meeting the voltage stability margin requirements, this invention obtains multiple virtual common node voltages based on the corrected multi-condition operating status identifier, the rated voltage, and the preset voltage stability margin. The calculation formula is as follows: U vpc,i =U N ·(1+δ v ·λ i ); Among them, U vpc,i Let δ be the virtual common node voltage of the i-th converter. V To preset the voltage stability margin, λ i This is the voltage correction factor determined based on the corrected operating condition identifier.

[0041] λ under weak grid conditions i Take the smaller value (tighten the voltage range) for λ under strong power grid conditions. i Take the larger value (widen the voltage range). In this embodiment, the preset voltage stability margin refers to the maximum voltage deviation range allowed by the system, such as ±5% or ±10%. Under weak grid conditions, in order to ensure voltage stability, the setting value of the virtual common node voltage needs to be appropriately tightened; under strong grid conditions, it can be appropriately relaxed to increase the reactive power regulation margin.

[0042] Since the total reactive power load demand is the benchmark for the total reactive power load shared by all converters, its accuracy directly affects the reactive power allocation accuracy, and the reactive power reserve demand under the current operating conditions needs to be considered. To accurately determine the total reactive power load demand under the current operating conditions, this invention obtains multiple reactive power values ​​from the multiple grid-connected converters and sums them to obtain the total reactive power load demand. The calculation formula is as follows:

[0043] Among them, Q sum Q represents the total reactive power load demand. i Let N be the real-time reactive power output of the i-th grid-connected converter, N be the total number of parallel grid-connected converters, and i be the serial number of the grid-connected converter, i=1, 2, 3...N; The total reactive power load demand is obtained based on the reactive power reserve coefficient corresponding to the corrected multi-condition operating status identifier and the sum of real-time reactive power, wherein the calculation formula is: Q total =Q sum ·k res ; Among them, Q total k represents the total reactive power load demand. res This is the reactive power reserve factor; In this embodiment, the reactive power reserve factor is a coefficient greater than 1, used to reserve a certain reactive power reserve margin based on the total real-time reactive power. Different operating conditions correspond to different reactive power reserve factors. Under weak grid conditions, the reserve factor is larger to cope with possible voltage drop events. For example, under weak grid conditions, the reactive power reserve factor takes a larger value (such as 1.2, 1.3) to cope with possible voltage drop events; under strong grid conditions, the reactive power reserve factor takes a smaller value (such as 1.05, 1.1).

[0044] Since converters of different capacities should bear different proportions of reactive load, virtual impedance parameters need to be normalized according to capacity; otherwise, the virtual impedance parameters of large-capacity converters and small-capacity converters will not be comparable. To eliminate the influence of capacity differences on virtual impedance parameters and achieve the goal of distributing reactive power proportionally according to capacity, this invention obtains multiple initial virtual impedances based on the corrected multi-condition operating status identifier and the estimated grid short-circuit capacity ratio. The calculation formula is as follows: Z v,i,init =f Z (R scr (Working condition markings); Among them, Z v,i,init Let f be the initial virtual impedance of the i-th converter. Z(·) represents the preset impedance configuration function, which can be solved by looking up a table or by interpolation; The initial virtual impedance is normalized and corrected based on the preset rated capacity of multiple grid-connected converters to obtain multiple current virtual impedance values. The calculation formula is as follows:

[0045] Among them, Z v,i,current Let S be the current virtual impedance of the i-th converter. rated,i S is the rated capacity of the i-th converter. base This is the normalized baseline capacity.

[0046] In this embodiment, the initial virtual impedance is determined based on the estimated short-circuit capacity ratio of the power grid. Under weak grid conditions, a larger virtual impedance is needed to enhance system damping, while under strong grid conditions, a smaller virtual impedance can be used to increase the reactive power regulation range. Capacity normalization correction involves multiplying the initial virtual impedance by the ratio of the rated capacity of each converter to the baseline capacity, so that the normalized virtual impedance parameter directly reflects the reactive power distribution ratio of each converter.

[0047] In summary, dynamic identification of grid strength was achieved through online impedance scanning and short-circuit capacity ratio estimation; accurate matching of control strategy with actual operating conditions was ensured through operating condition identification correction; a target benchmark for global coordinated control was established by determining the virtual common node voltage and total reactive load demand; and the impact of converter capacity differences was eliminated through capacity normalization correction, laying a parameter foundation for subsequent coordinated regulation.

[0048] In one embodiment, step S3, which involves obtaining the total harmonic distortion (THD) and voltage imbalance based on the overall power quality characteristics, obtaining an overall virtual impedance stability coefficient based on the THD, the voltage imbalance, and the voltages of multiple virtual common nodes, and correcting multiple current virtual impedance values ​​based on the overall virtual impedance stability coefficient to obtain multiple currently stable virtual impedance values, includes: S31. Obtain the common coupling point voltage signal from the overall power quality characteristics, and perform Fourier transform on the common coupling point voltage signal to obtain the fundamental voltage component and each harmonic voltage component. Obtain the harmonic distortion rate of each harmonic voltage component and the fundamental voltage component, and then obtain the total harmonic distortion rate of the voltage based on the harmonic distortion rate of each harmonic. S32. Perform symmetrical component decomposition on the voltage signal at the common coupling point to obtain positive-sequence voltage components and negative-sequence voltage components, and obtain the voltage imbalance between the negative-sequence voltage components and the positive-sequence voltage components. S33. Obtain the harmonic stress factor based on the ratio of the total harmonic distortion rate of the voltage to the preset harmonic distortion safety threshold, and obtain the unbalanced stress factor based on the ratio of the voltage unbalance to the preset unbalance safety threshold. S34. Obtain the power quality coupling distortion index based on the harmonic stress factor and the unbalanced stress factor, and obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltages of multiple virtual common nodes. S35. Obtain the voltage deviation rate between the virtual common node voltage and the preset rated voltage, and obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltage deviation rate. S36. Decompose the multiple current virtual impedance values ​​into multiple fundamental virtual impedance components and multiple harmonic virtual impedance components respectively, and correct the multiple fundamental virtual impedance components according to the overall virtual impedance stability coefficient to obtain multiple fundamental virtual impedance components. S37. Attenuate and correct the multiple harmonic virtual impedance components according to the total harmonic distortion rate of the voltage to obtain multiple harmonic virtual impedance components. S38. The multiple fundamental virtual impedance components and the multiple harmonic virtual impedance components are superimposed and reconstructed to obtain multiple current stable virtual impedance values.

[0049] As described in steps S31-S38 above, since the voltage signal at the common coupling point contains fundamental and harmonic components, it is impossible to accurately assess the impact of harmonics on the virtual impedance control performance without separating and quantizing each harmonic. To accurately quantify the content of each harmonic and its overall distortion of the voltage waveform, this invention obtains the common coupling point voltage signal from the overall power quality characteristics, performs a Fourier transform on the common coupling point voltage signal to obtain the fundamental voltage component and each harmonic voltage component, obtains the harmonic distortion rate of each harmonic voltage component based on the fundamental voltage component, and then obtains the total harmonic distortion rate of the voltage based on the harmonic distortion rate.

[0050] The specific implementation steps are as follows: Perform a Fast Fourier Transform (FFT) on the signal to obtain the effective value of the fundamental (50Hz / 60Hz) voltage component and the effective value of each harmonic (2nd, 3rd, ..., Hth, where H is usually taken as 50) voltage component.

[0051] For the h-th harmonic, its harmonic distortion rate TED h for: ; Among them, THD h V is the distortion rate of the h-th harmonic. hV1 is the effective value of the h-th harmonic voltage, and V2 is the effective value of the fundamental voltage.

[0052] The formula for calculating the total harmonic distortion (THD) of voltage is: ; Where THD is the total harmonic distortion of voltage, and H is the highest harmonic order involved in the calculation.

[0053] In this embodiment, the Fourier transform decomposes the time-domain voltage signal into frequency components. The fundamental voltage component is a 50Hz (or 60Hz) component, and each harmonic voltage component is an integer multiple of the fundamental frequency. The harmonic distortion rate is the ratio of the amplitude of the corresponding harmonic voltage to the amplitude of the fundamental voltage. The total harmonic distortion rate is the ratio of the root mean square value of the amplitude of each harmonic voltage to the amplitude of the fundamental voltage, and is a comprehensive indicator for measuring the quality of the voltage waveform.

[0054] Three-phase voltage imbalance leads to negative-sequence current components in the control loop of a grid-type converter, affecting the effectiveness of the virtual impedance. If the impact of the imbalance is ignored, the virtual impedance parameters may become unstable under severe imbalance conditions. To quantify the degree of three-phase voltage asymmetry and its impact on the control system, this invention performs symmetrical component decomposition on the common coupling point voltage signal to obtain positive-sequence and negative-sequence voltage components. The calculation formula is as follows: For three-phase voltage , , (Phasor form), positive sequence components Negative order components and zero-order components The calculation formula is:

[0055] in, It is a positive sequence voltage phasor (positive sequence voltage component). It is a negative sequence voltage phasor (negative sequence voltage component). It is the zero-sequence voltage phasor (zero-sequence voltage component). Rotation operator; The voltage imbalance between the negative-sequence voltage component and the positive-sequence voltage component is calculated using the following formula:

[0056] Where VUF is the voltage imbalance, V1 is the effective value of the positive sequence voltage, and V2 is the effective value of the negative sequence voltage.

[0057] In this embodiment, symmetrical component decomposition decomposes the three-phase unbalanced voltage into three sets of symmetrical components: positive sequence, negative sequence, and zero sequence. Voltage imbalance is defined as the ratio of the amplitude of the negative sequence voltage component to the amplitude of the positive sequence voltage component, and is a parameter reflecting power quality.

[0058] Since harmonic distortion and three-phase imbalance have different mechanisms of influence on virtual impedance stability, and each has its own safe operating threshold, using only absolute values ​​for judgment cannot reflect the urgency of the current power quality state relative to the safety boundary. To normalize power quality indicators to a safety margin framework, this invention obtains the harmonic stress factor based on the ratio of the total harmonic distortion rate to a preset harmonic distortion safety threshold, and obtains the unbalanced stress factor based on the ratio of the voltage unbalance degree to a preset unbalanced safety threshold. The specific calculation steps are as follows: In this embodiment, the preset harmonic distortion safety threshold is the upper limit of the allowable harmonic distortion rate set according to the national power quality standard (for example, for a 380V system, THD). threshold =5). The formula for calculating the harmonic stress factor is:

[0059] Among them, F THD Harmonic stress factor, THD threshold To preset the harmonic distortion safety threshold; Similarly, a preset imbalance safety threshold VUF is used. threshold It is the allowable upper limit of voltage imbalance set according to national standards (e.g., for power systems, VUF). threshold =2). Unbalanced stress factor F VUF The calculation formula is:

[0060] Among them, F VUF The stress factor is the unbalanced stress factor. When the stress factor is greater than 1, it indicates that the corresponding power quality index has exceeded the standard. In this embodiment, the preset harmonic distortion safety threshold is the voltage total harmonic distortion rate limit specified in the national standard (e.g., 5%), and the preset unbalance safety threshold is the voltage unbalance degree limit specified in the national standard (e.g., 2%). Both the harmonic stress factor and the unbalance stress factor are dimensionless quantities. When the factor value is less than 1, it indicates that it is within the safe range, and when it is greater than 1, it indicates that it has exceeded the safety threshold.

[0061] Since harmonic distortion and three-phase imbalance often coexist and are coupled in actual power grids, considering either factor alone cannot fully reflect the comprehensive impact of power quality on virtual impedance stability. To integrate the dual effects of harmonics and imbalance and obtain a comprehensive power quality assessment index, this invention derives the power quality coupling distortion index based on the harmonic stress factor and the imbalance stress factor, wherein the calculation formula is:

[0062] Among them, I PQ F is the power quality coupling distortion index, ρ is the harmonic and unbalance coupling coefficient (0 < ρ < 1, ρ can be taken as 0.5 for example), and F THD F is the harmonic stress factor. VUF This refers to the unbalanced stress factor. Subsequently, the voltage deviation rate between the voltages of each virtual common node and the voltages of the nodes is calculated:

[0063] Where, σ i For the i-th voltage deviation rate, U vpc,i Let U be the voltage of the i-th virtual common node. N Preset rated voltage; Average voltage deviation of all converters for:

[0064] in, σ is the average voltage deviation rate. i Let be the i-th voltage deviation rate, and N be the number of voltage deviation rates, where i is the index of the voltage deviation rate, i = 1, 2, 3...N; The overall virtual impedance stability coefficient is obtained based on the power quality coupling distortion index and the voltages of multiple virtual common nodes, wherein the calculation formula is:

[0065] Among them, S VI I is the overall virtual impedance stability coefficient. PQ The power quality coupling distortion index. The average voltage deviation rate; When the power quality is worse (I PQ The larger the voltage drop, the more severe the voltage sag. When the value is larger, the stability coefficient S VI The smaller the value, the lower the stability margin of the current virtual impedance, and the more necessary it is to be reinforced and corrected. In this embodiment, the power quality coupling distortion index reflects the combined severity of the two power quality problems. The overall virtual impedance stability coefficient is a correction factor calculated based on this index and the virtual common node voltage, used to indicate the direction and magnitude of the current virtual impedance parameter correction.

[0066] Since the voltage deviation rate directly reflects the degree to which the voltage at the point of common coupling deviates from its rated value, it is an important supplementary information for judging the stability of the system voltage. If only harmonic and unbalance indicators are relied upon while ignoring the voltage deviation, inappropriate virtual impedance parameters may still be used even when the voltage deviation is severe. To incorporate voltage deviation information into the stability coefficient, this invention obtains the voltage deviation rate between the virtual common node voltage and the preset rated voltage, and obtains the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltage deviation rate. In this embodiment, the voltage deviation rate is the difference between the virtual common node voltage and the preset rated voltage divided by the preset rated voltage. When the voltage deviation rate is large, the overall virtual impedance stability coefficient will be adjusted accordingly to indicate whether the virtual impedance needs to be increased or decreased to restore the voltage level.

[0067] Since virtual impedance can be decomposed into fundamental and harmonic components in the frequency domain, and these two components have different response characteristics to power quality issues—the fundamental component mainly affects reactive power distribution, while the harmonic components mainly affect harmonic current suppression—if the same correction strategy is applied to both, fine-grained frequency-selective correction cannot be achieved. To achieve differentiated correction of different frequency components of virtual impedance, this invention decomposes multiple current virtual impedance values ​​into multiple fundamental virtual impedance components and multiple harmonic virtual impedance components, respectively. Based on the overall virtual impedance stability coefficient, the multiple fundamental virtual impedance components are corrected to obtain multiple fundamental virtual impedance components.

[0068] Specifically, multiple fundamental wave virtual impedance components are obtained by multiplying the overall virtual impedance stability coefficient by multiple fundamental wave virtual impedance components in sequence. In this embodiment, the fundamental virtual impedance component is the equivalent value of the virtual impedance at the fundamental frequency, which mainly determines the fundamental reactive power output characteristics of the converter. The overall virtual impedance stability coefficient corrects the fundamental component by scaling the amplitude of the fundamental virtual impedance. When power quality deteriorates, the fundamental virtual impedance is appropriately increased to enhance system damping.

[0069] Because excessively large impedance values ​​of harmonic virtual impedance components at higher harmonic frequencies can amplify harmonic voltages and degrade power quality, it is necessary to attenuate the harmonic virtual impedance components when harmonic distortion is severe. To avoid the negative effects of harmonic components of virtual impedance under harmonic operating conditions, this invention attenuates and corrects multiple harmonic virtual impedance components based on the total harmonic distortion rate of the voltage, resulting in multiple harmonic virtual impedance components. The calculation formula is as follows:

[0070] In the formula, is The i-th fundamental virtual impedance component Let be the virtual impedance component of the i-th harmonic, and THD be the total harmonic distortion of the voltage.

[0071] In this embodiment, the attenuation correction method is to multiply the harmonic virtual impedance component by an attenuation coefficient less than 1. This attenuation coefficient is negatively correlated with the total harmonic distortion rate of the voltage, that is, the more severe the harmonic distortion, the greater the attenuation.

[0072] Since the corrected fundamental and harmonic components need to be resynthesized into complete virtual impedance parameters before being written into the control loop, if only one component is corrected while the other is ignored, the frequency characteristics of the virtual impedance will be incomplete. In order to reconstruct the corrected frequency components into complete virtual impedance parameters, this invention superimposes and reconstructs multiple fundamental virtual impedance components and multiple harmonic virtual impedance components to obtain multiple current stable virtual impedance values.

[0073] In this embodiment, superposition reconstruction involves vector superposition of the fundamental component and each harmonic component in the frequency domain within a preset time to obtain complete frequency response characteristics, which are then converted into time-domain control parameters.

[0074] In summary, by sensing and correcting power quality in multiple dimensions, fine-grained frequency-selective adjustment of virtual impedance parameters is achieved. The stability correction of the fundamental component ensures the basic performance of reactive power distribution, while the attenuation correction of harmonic components avoids harmonic amplification effects. The synergistic effect of the two enables the virtual impedance parameters to maintain stable system operation even under deteriorating power quality conditions.

[0075] In one embodiment, step S4, which involves obtaining multiple equivalent line impedance values ​​from multiple grid-connected converters to a common coupling point, includes: S41. Obtain the line topology parameters between each grid-type converter and the common coupling point, wherein the line topology parameters include line length, conductor cross-sectional area, conductor resistivity and line equivalent inductance coefficient. S42. Calculate the fundamental frequency resistance value of each line based on the multiple line lengths, multiple conductor cross-sectional areas and multiple conductor resistivities, and calculate the fundamental frequency inductive reactance value of each line based on the line length and the equivalent inductance coefficient of the line. Perform vector synthesis of the multiple fundamental frequency resistance values ​​and the multiple fundamental frequency inductive reactance values ​​to obtain the basic line impedance of each line. S43. During the preset detection period, control each grid-type converter to inject multi-frequency stepped detection signals into the corresponding line, and collect the voltage response sequence and current response sequence of the output terminal of each grid-type converter under the excitation of the multi-frequency stepped detection signals, wherein the multi-frequency stepped detection signals cover multiple discrete frequency points within the fundamental frequency and the preset harmonic frequency band. S44. Obtain the amplitude ratio and phase difference at each discrete frequency point based on the voltage response sequence and the current response sequence, and obtain the measured impedance value at multiple discrete frequency points based on multiple amplitude ratios and multiple phase differences; S45. Compare the measured impedance values ​​of each line at the fundamental frequency with the corresponding impedance of the basic line. S46. When the deviation exceeds the preset impedance deviation threshold, the measured impedance value is used to replace the basic line impedance for updating, and the verified line impedance is obtained, wherein the line impedance includes a resistive component and an inductive reactance component. S47. Obtain the real-time conductor temperature and real-time load rate of each line, perform temperature coefficient correction on the resistance component according to the real-time conductor temperature to obtain the temperature-corrected resistance component, and perform magnetic saturation attenuation correction on the inductive reactance component according to the real-time load rate to obtain the attenuation-corrected inductive reactance component. S48. Perform vector reconstruction on the temperature-corrected resistance component and the magnetically saturated attenuation-corrected inductive reactance component to obtain the equivalent line impedance value from each converter to the common coupling point.

[0076] As described in steps S41-S48 above, line impedance is a key physical parameter determining the reactive power distribution ratio of each converter. However, in actual engineering practice, this parameter often deviates from the design value due to factors such as construction deviations, joint aging, and changes in ambient temperature. Relying solely on the nominal parameters in the design drawings will not yield an accurate line impedance value. To establish a theoretical calculation benchmark for line impedance, this invention obtains the line topology parameters between each grid-type converter and the common coupling point. In this embodiment, the line topology parameters are physical parameters obtained from engineering design drawings and field survey data, including line length (in meters), conductor cross-sectional area (in square millimeters), conductor resistivity (in ohm-meters), and equivalent inductance (in Henry / meter). These parameters constitute the basic input for the theoretical calculation of line impedance.

[0077] Since line impedance consists of two parts, resistance and inductive reactance, they need to be vector-synthesized at the fundamental frequency to obtain the complete impedance value. If only resistance is considered and inductive reactance is ignored, serious calculation errors will occur in inductive lines. To calculate the theoretical benchmark value of line impedance based on physical parameters, this invention calculates the fundamental frequency resistance value of each line based on multiple line lengths, multiple conductor cross-sectional areas, and multiple conductor resistivities, and calculates the fundamental frequency inductive reactance value of each line based on the line length and the equivalent inductance coefficient of the line. The multiple fundamental frequency resistance values ​​and multiple fundamental frequency inductive reactance values ​​are then vector-synthesized to obtain the basic line impedance of each line. The calculation formula is as follows:

[0078] Among them, R line,i,0 Basic line impedance, ρ i l is the resistivity of the conductor. i Let A be the length of the i-th line.i The cross-sectional area of ​​the conductor; The fundamental frequency inductive reactance X of the i-th line line,i,0 The calculation formula is: ; Among them, X line,i,0 Here, f0 is the fundamental frequency reactance, and L is the fundamental frequency (50Hz or 60Hz). line,i Let l be the impedance of the i-th foundation line. i Let A be the length of the i-th line. i Let be the cross-sectional area of ​​the conductor.

[0079] Basic line impedance Z line,i,0 The vector composition (complex form) of resistance and reactance is as follows: ; Among them, Z line,i,0 Basic line impedance, X line,i,0 R is the fundamental frequency reactance value. line,i,0 The basic line impedance is represented by j, which is the imaginary unit used to distinguish between the resistive component (real part) and the inductive reactance component (imaginary part) of the impedance. Vector synthesis uses the resistance value as the real part and the inductive reactance value as the imaginary part to construct a complex impedance for subsequent calculations.

[0080] Because the calculated basic line impedance deviates from the actual value, it needs to be verified and corrected through online measurement. This measurement requires acquiring impedance information at multiple frequency points to comprehensively characterize the line's frequency characteristics. To obtain the measured value of the line impedance through online detection, this invention controls each grid-type converter to inject multi-frequency stepped detection signals into the corresponding line within a preset detection period, and collects the voltage and current response sequences of each grid-type converter's output terminal under the excitation of the multi-frequency stepped detection signals. In this embodiment, the multi-frequency stepped detection signal is a set of sinusoidal signals injected sequentially in ascending frequency order, covering the fundamental frequency (50Hz) and multiple discrete frequency points within a preset harmonic band (e.g., 100Hz, 150Hz, 250Hz, 350Hz, etc.). The detection at each frequency point lasts for several cycles to ensure the establishment of a steady-state response.

[0081] Since impedance is a complex quantity, both amplitude and phase information are required for complete determination; obtaining only the amplitude ratio is insufficient to distinguish between resistive and inductive components. To fully extract the complex impedance at each frequency point from the voltage and current responses, this invention obtains the amplitude ratio and phase difference at each discrete frequency point based on the voltage and current response sequences, and then obtains the measured impedance values ​​at multiple discrete frequency points based on multiple amplitude ratios and multiple phase differences. The calculation formula is as follows:

[0082] in, For frequency f k Voltage amplitude, For frequency f k Current amplitude, Z represents the phase difference between voltage and current. line,i,meas (f k () represents the frequency f k The measured impedance value at the point; This method separates the impedance response corresponding to the probe signal from the sampling time series data containing background noise, distinguishes between the inherent disturbances of the power grid and the electrical changes brought about by artificially injected probe signals, avoids load fluctuations interfering with the impedance identification results, and achieves the local technical effect of quantifying the actual measured values ​​of the line impedance at each frequency point, forming a measured dataset that can be compared with the basic line impedance. In this embodiment, the amplitude ratio is the ratio of the voltage response amplitude to the current response amplitude, i.e., the magnitude of the impedance. The phase difference is the difference between the voltage response phase and the current response phase, i.e., the phase angle of the impedance. The sum of these two values ​​yields the measured value of the complex impedance at that frequency.

[0083] Since the deviation between theoretical and measured values ​​may arise from various reasons such as changes in line parameters, increased contact resistance at joints, or measurement errors, a reasonable deviation threshold needs to be set to determine whether the measured value should replace the theoretical value. To make a reasonable choice between theoretical and measured values, this invention compares the measured impedance value of each line at the fundamental frequency with the corresponding impedance of the underlying line. In this embodiment, the deviation comparison is calculated as the percentage relative deviation between the measured impedance value and the underlying line impedance.

[0084] When the deviation exceeds a preset impedance deviation threshold, the measured impedance value replaces the basic line impedance for updating, resulting in the verified line impedance. In this embodiment, the preset impedance deviation threshold is set to, for example, 10% or 15%. When the deviation exceeds this threshold, it is considered that the theoretical value can no longer reflect the actual line condition, and the measured value is used for replacement and updating.

[0085] Because conductor resistance increases with temperature, and line reactance decreases due to magnetic saturation caused by increased load current, if fixed parameters are used without considering the influence of real-time operating conditions, the equivalent line impedance will deviate from the true value. To correct the line impedance to the true value under current actual operating conditions, this invention obtains the real-time conductor temperature and real-time load rate of each line. Based on the real-time conductor temperature, the resistance component is corrected using a temperature coefficient to obtain a temperature-corrected resistance component. Then, based on the real-time load rate, the reactance component is corrected using magnetic saturation attenuation to obtain an attenuated reactance component. In this embodiment, the temperature coefficient correction is based on the temperature coefficient of resistance of the conductor material (e.g., 0.00393 / ℃ for copper), correcting the resistance value at the reference temperature to the resistance value at the actual conductor temperature. The magnetic saturation attenuation correction is performed by looking up the reactance attenuation coefficient in a table or by calculation based on the real-time load rate, correcting the no-load reactance value to the reactance value under actual load conditions.

[0086] Since the corrected resistive and inductive reactance components need to be reassembled into a complete complex impedance before they can be used for subsequent calculations, this invention performs vector reconstruction on the temperature-corrected resistive components and the magnetically saturated attenuation-corrected inductive reactance components to obtain the equivalent line impedance values ​​from each converter to the common coupling point in order to obtain the final usable equivalent line impedance values. In this embodiment, the vector reconstruction uses the temperature-corrected resistive components as the real part and the magnetically saturated attenuation-corrected inductive reactance components as the imaginary part to construct a complex impedance, which is the accurate equivalent line impedance from each converter to the common coupling point under the current operating conditions.

[0087] In summary, the multi-level impedance acquisition process ensures the accuracy and real-time performance of the equivalent line impedance value, providing a reliable physical parameter basis for subsequent reactive power distribution deviation analysis and coordinated control.

[0088] In one embodiment, step S5, which involves obtaining the coordinated consistency control constraint based on the plurality of individual unit capacity deviations and the plurality of equivalent line impedance values, includes: S51. Arrange the multiple individual unit capacity deviations in descending order of their absolute values ​​to obtain a deviation priority sequence; S52. Calculate the impedance ratio between any two grid-type converters based on the multiple equivalent line impedance values, and construct a line impedance coupling matrix based on the multiple impedance ratio values. S53. Based on the line impedance coupling matrix, the individual capacity deviation of each converter is corrected by coupling propagation to obtain multiple equivalent deviations. S54. Obtain multiple positive and negative signs according to the multiple equivalent deviations, and obtain the adjustment direction constraint of each grid-type converter according to the multiple positive and negative signs, wherein positive values ​​correspond to increasing virtual impedance and negative values ​​correspond to decreasing virtual impedance. S55. Determine the adjustment priority level of each grid-type converter according to the deviation priority sequence, obtain the absolute value of the equivalent deviation according to the multiple equivalent deviations, and obtain multiple adjustment step sizes according to the adjustment priority level and the multiple absolute values ​​of the equivalent deviations. S56. Obtain the preset control cycle duration, and use the multiple adjustment step sizes and the preset control cycle duration to obtain the adjustment rate constraint of each grid-type converter. S57. Associate and encapsulate the multiple adjustment direction constraints and the multiple adjustment rate constraints to obtain the coordinated and consistent control constraints.

[0089] As described in steps S51-S57 above, since the reactive power deviations of multiple converters vary, applying the same adjustment priority to all converters may result in over-adjustment of converters with smaller deviations and under-adjustment of converters with larger deviations, failing to achieve globally optimal deviation elimination. To determine the urgency and priority of adjustment for each converter, this invention arranges the individual capacity deviations in descending order of their absolute values, obtaining a deviation priority sequence. In this embodiment, the deviation priority sequence reflects the severity of reactive power deviations of each converter, with the converter at the top of the sequence exhibiting the largest deviation and requiring priority adjustment.

[0090] Since the converters are electrically coupled through a common coupling point, the virtual impedance adjustment of one converter can affect the reactive power output of other converters through voltage changes at the common coupling point. Ignoring this coupling effect and independently adjusting each converter may lead to adjustment conflicts or even oscillations. To quantify the reactive power flow interaction coupling relationship between the converters, this invention calculates the impedance ratio between any two grid-type converters based on multiple equivalent line impedance values, and constructs a line impedance coupling matrix based on these impedance ratios. In this embodiment, the line impedance coupling matrix is ​​an N×N square matrix (N is the number of converters), where the element in the i-th row and j-th column represents the reactive power flow interaction coupling strength between the i-th converter and the j-th converter. The smaller the impedance ratio, the stronger the coupling between the two converters.

[0091] Since the deviations of each converter are not independent but mutually influenced through line impedance coupling, the deviation adjustment of one converter will partially propagate to adjacent converters. If adjustments are made solely based on the original deviation, it cannot accurately reflect the actual adjustment amount that each converter needs to bear. To account for the influence of adjacent converter coupling propagation in the deviation, this invention performs coupling propagation correction on the individual capacity deviation of each converter based on the line impedance coupling matrix, obtaining multiple equivalent deviations. In this embodiment, the coupling propagation correction involves weighting and allocating the original deviation of each converter to adjacent converters according to the coupling strength of the corresponding elements in the line impedance coupling matrix, so that the equivalent deviation can reflect the actual deviation that each converter needs to eliminate after considering the influence of adjacent converters.

[0092] Since the adjustment direction of the virtual impedance directly determines the direction of reactive power output change, an incorrect adjustment direction will exacerbate the deviation rather than eliminate it. Therefore, the adjustment direction must be strictly determined based on the positive or negative sign of the equivalent deviation. To clarify the adjustment direction of the virtual impedance of each converter, this invention obtains multiple positive and negative signs based on the multiple equivalent deviations, and obtains the adjustment direction constraint for each grid-type converter based on the multiple positive and negative signs. In this embodiment, when the equivalent deviation is positive, it indicates that the converter has excessive reactive power output, and the virtual impedance needs to be increased to suppress reactive power output; when the equivalent deviation is negative, it indicates that the converter has insufficient reactive power output, and the virtual impedance needs to be decreased to increase reactive power output.

[0093] Because the urgency and magnitude of the deviation vary among the converters, using a uniform adjustment step size would result in converters with large and urgent deviations being adjusted too slowly, while converters with small deviations might be over-adjusted. To determine the adjustment range of each converter based on the degree of deviation and priority differences, this invention determines the adjustment priority level of each grid-type converter according to the deviation priority sequence, obtains the absolute value of the equivalent deviation based on multiple equivalent deviation values, and obtains multiple adjustment step sizes based on the adjustment priority level and the multiple absolute values ​​of the equivalent deviation values. In this embodiment, the higher the adjustment priority level and the larger the absolute value of the equivalent deviation, the larger the corresponding adjustment step size, ensuring that the converter with the most severe deviation can be adjusted most quickly.

[0094] Since the adjustment step size is the change in virtual impedance within a single control cycle, while the adjustment rate is the change per unit time, the two are linked through the control cycle duration. Furthermore, the adjustment rate needs to be subject to an upper limit constraint to prevent excessively rapid parameter changes from causing transient oscillations in the system. To convert the adjustment step size into a time-constrained adjustment rate, this invention obtains a preset control cycle duration and uses multiple adjustment step sizes and the preset control cycle duration to obtain the adjustment rate constraint for each grid-type converter. In this embodiment, the adjustment rate constraint is the adjustment step size divided by the preset control cycle duration, representing the maximum allowable rate of change of virtual impedance within each control cycle.

[0095] Since regulation direction and regulation rate are two inseparable dimensions of coordinated constraints, using either one alone cannot fully describe the regulation constraints; therefore, they need to be associated and encapsulated into a unified constraint quantity. To form complete coordinated regulation constraint information, this invention associates and encapsulates multiple regulation direction constraints and multiple regulation rate constraints to obtain coordinated and consistent regulation constraint quantities. In this embodiment, the association and encapsulation binds the regulation direction constraint quantity and regulation rate constraint quantity of each converter into a structured constraint object, facilitating unified invocation and execution in subsequent regulation steps.

[0096] In summary, global coordination of the regulation behavior among multiple converters was achieved through deviation priority sorting, coupling matrix construction, coupling propagation correction, and differential step size determination. Regulation direction constraints ensured the correctness of the regulation direction of each converter, while regulation rate constraints ensured the smoothness of the regulation process. The synergistic effect of these two constraints effectively avoided the risk of interactive oscillations caused by simultaneous large-scale regulation of multiple converters.

[0097] In one embodiment, step S6, which involves adjusting and constraining multiple currently stable virtual impedance values ​​according to the cooperative consistency control constraint to obtain multiple target virtual impedances, and controlling the multiple grid-type converters to converge towards the global cooperative status reference quantity based on the multiple target virtual impedances, includes: S61. Determine the virtual impedance adjustment direction of each grid-type converter according to the multiple adjustment direction constraints, and determine the maximum allowable impedance change of each grid-type converter in a single control cycle according to the multiple adjustment rate constraints. S62. The multiple current stable virtual impedance values ​​are incrementally updated along the corresponding virtual impedance adjustment direction according to the maximum allowable impedance change to obtain multiple candidate virtual impedances; S63. Perform upper and lower limit truncation verification on multiple candidate virtual impedances according to the preset virtual impedance safety boundary. S64. When any candidate virtual impedance exceeds the preset virtual impedance safety boundary, clamp it to the corresponding boundary value to obtain multiple virtual impedances after boundary verification. S65. Calculate the expected reactive power output allocation ratio of each grid-type converter based on multiple equivalent line impedance values ​​and multiple virtual impedances after boundary verification, and calculate the deviation between the expected reactive power output allocation ratio and the preset capacity ratio allocation benchmark to obtain the multi-machine consistency deviation index. S66. Determine whether the multi-machine consistency deviation index exceeds the preset consistency tolerance threshold. S67. When the multi-machine consistency deviation index exceeds the preset consistency tolerance threshold, the virtual impedances after boundary verification are proportionally redistributed and corrected according to the multi-machine consistency deviation index to obtain multiple target virtual impedances. S68. When the multi-machine consistency deviation index does not exceed the preset consistency tolerance threshold, the multiple virtual impedances after boundary verification are directly used as the multiple target virtual impedances. S69. Write the multiple target virtual impedances into the virtual impedance control loop of each grid-type converter, and control each grid-type converter to adjust the reactive power output according to the corresponding target virtual impedance. S610. Within the preset convergence observation window, continuously collect the actual reactive power output of each grid-type converter, and calculate the real-time reactive power distribution deviation based on the multiple actual reactive power outputs and the total reactive load demand. S611. Determine whether the real-time reactive power distribution deviation is less than the preset convergence criterion threshold within the preset convergence observation window. S612. When the real-time reactive power distribution deviation is less than the preset convergence criterion threshold within the preset convergence observation window, it is determined that the multiple grid-type converters have converged to the global collaborative situation reference quantity, and multiple target virtual impedances are locked. S613. When the real-time reactive power distribution deviation is not less than the preset convergence criterion threshold within the preset convergence observation window, return to the step of incrementally updating multiple current stable virtual impedance values ​​along the corresponding virtual impedance adjustment direction according to the maximum allowable impedance change to obtain multiple candidate virtual impedances for iterative control in the next control cycle.

[0098] As described in steps S61-S613 above, since the coordinated control constraints contain the adjustment direction and rate limit information of each converter, these constraints need to be parsed into executable control parameters first. To convert the constraints into specific control parameters, this invention determines the virtual impedance adjustment direction of each grid-type converter based on multiple adjustment direction constraints, and determines the maximum allowable impedance change of each grid-type converter within a single control cycle based on multiple adjustment rate constraints. In this embodiment, the virtual impedance adjustment direction is either increasing or decreasing in two discrete states. The maximum allowable impedance change is the upper limit of the absolute change obtained by multiplying the adjustment rate constraint by the preset control cycle duration.

[0099] Since the adjustment of virtual impedance is a gradual process, it requires incremental updates with finite steps based on the current value and constraints. Adjusting the virtual impedance to the target value all at once would cause a severe transient shock. To gradually approach the target value within the constraints, this invention incrementally updates multiple currently stable virtual impedance values ​​along the corresponding virtual impedance adjustment direction according to the maximum allowable impedance change, obtaining multiple candidate virtual impedances. In this embodiment, the incremental update involves adding or subtracting the maximum allowable impedance change along the adjustment direction based on the current stable virtual impedance value, obtaining the candidate value at the end of the current control cycle.

[0100] Because virtual impedance parameters have a physically safe operating range, excessively large or small virtual impedance values ​​can lead to system instability or severe degradation of control performance. Therefore, it is necessary to perform safety boundary verification on candidate values. To prevent virtual impedance parameters from exceeding the safe operating range, this invention performs upper and lower limit truncation verification on multiple candidate virtual impedances based on a preset virtual impedance safety boundary. In this embodiment, the preset virtual impedance safety boundary is a pre-determined allowable range of virtual impedance based on the converter's rated parameters and system stability analysis, including an upper limit and a lower limit.

[0101] Since directly using a candidate value that exceeds the safety boundary would jeopardize system security, it must be forcibly restricted to a safe range. To obtain usable virtual impedance values ​​under safety constraints, this invention clamps any candidate virtual impedance to the corresponding boundary value when it exceeds a preset virtual impedance safety boundary, resulting in multiple boundary-checked virtual impedances. In this embodiment, the clamping operation sets candidate values ​​exceeding the upper limit as the upper limit value and candidate values ​​below the lower limit as the lower limit value, ensuring that all virtual impedance values ​​are within the safe operating range.

[0102] Although the virtual impedance value after boundary verification meets the safety constraints, the reactive power distribution ratio among the converters may deviate from the ideal value due to clamping operations, requiring further evaluation of multi-machine consistency. To evaluate the reactive power distribution consistency under the current virtual impedance configuration, this invention calculates the expected reactive power output distribution ratio of each grid-type converter based on multiple equivalent line impedance values ​​and multiple virtual impedances after boundary verification. The deviation between the expected reactive power output distribution ratio and a preset capacity ratio distribution benchmark is then calculated to obtain a multi-machine consistency deviation index. In this embodiment, the expected reactive power output distribution ratio is the proportion of the theoretical reactive power output of each converter to the total reactive power, calculated based on the series voltage division relationship between the equivalent line impedance and the virtual impedance. The preset capacity ratio distribution benchmark is the proportion of the rated capacity of each converter to the total capacity. The multi-machine consistency deviation index is a comprehensive measure of the deviation between the two.

[0103] Since the multi-machine consistency deviation index reflects whether the current virtual impedance configuration meets the requirement of reactive power allocation according to capacity ratio, it is necessary to determine whether further correction is needed based on this index. To determine whether further correction is needed, this invention determines whether the multi-machine consistency deviation index exceeds a preset consistency tolerance threshold. In this embodiment, the preset consistency tolerance threshold is the maximum acceptable reactive power allocation deviation in engineering, for example, 5%.

[0104] When the consistency deviation exceeds the limit, proportional redistribution correction is needed to ensure that the virtual impedances of each converter re-satisfy the capacity ratio allocation relationship. To correct this when the deviation exceeds the limit, this invention performs proportional redistribution correction on multiple boundary-checked virtual impedances according to the multi-machine consistency deviation index when it exceeds a preset consistency tolerance threshold, resulting in multiple target virtual impedances. In this embodiment, the proportional redistribution correction recalculates the virtual impedance values ​​that satisfy the capacity ratio allocation relationship based on the capacity ratio of each converter and its equivalent line impedance.

[0105] Since no further correction is needed when the consistency deviation is within the allowable range, the value after boundary verification can be used directly. In order to avoid unnecessary correction when the deviation meets the requirements, this invention directly uses the multiple virtual impedances after boundary verification as the multiple target virtual impedances when the multi-machine consistency deviation index does not exceed the preset consistency allowable threshold.

[0106] Since the target virtual impedance ultimately needs to be written into the local control loop of each converter to take effect, the parameters need to be sent to the converter controllers via a communication network. To translate control decisions into actual control actions, this invention writes multiple target virtual impedances into the virtual impedance control loop of each grid-type converter, controlling each grid-type converter to adjust its reactive power output according to the corresponding target virtual impedance. In this embodiment, the writing operation transmits the target virtual impedance parameters to the local controller of each converter via a high-speed communication network (e.g., fiber optic Ethernet or industrial Ethernet), and the local controller updates the virtual impedance parameters at the beginning of the next control cycle.

[0107] Because there is a dynamic response process between the update of virtual impedance parameters and the actual change in reactive power output, and because multi-machine coupling effects may cause deviations between actual and expected reactive power distribution, convergence verification is required through closed-loop observation. To verify whether the control effect meets expectations, this invention continuously collects the actual reactive power output of each grid-type converter within a preset convergence observation window, and calculates the real-time reactive power distribution deviation based on multiple actual reactive power outputs and the total reactive power load demand. In this embodiment, the preset convergence observation window is an observation period after parameter updates, such as 3 to 5 control cycles. Within this window, the actual reactive power output of each converter is continuously collected, and the real-time reactive power distribution deviation is calculated.

[0108] Since the convergence criterion is the ultimate standard for determining whether a system has reached a steady state, it needs to be continuously satisfied throughout the entire observation window to determine convergence. To determine whether the system has converged, this invention determines whether the real-time reactive power distribution deviation is less than a preset convergence criterion threshold within a preset convergence observation window. In this embodiment, the preset convergence criterion threshold is the final accuracy requirement for determining system convergence, for example, 3%.

[0109] Since the convergence criterion indicates that the system has reached a steady state, the current parameters can be locked and no further adjustment can be made to avoid unnecessary parameter fluctuations. To stabilize the system after convergence, this invention determines that the multiple grid-connected converters have converged to the global cooperative situation reference quantity when the real-time reactive power distribution deviation is less than a preset convergence criterion threshold within a preset convergence observation window, and locks multiple target virtual impedances. In this embodiment, the locking operation stops the iterative update of the virtual impedance parameters, keeping the current target virtual impedance unchanged until the next change in operating conditions triggers readjustment.

[0110] Since the convergence criterion is not met, it indicates that the current parameters have not yet brought the system to a steady state, and iterative adjustment needs to continue. To continue iteration even before convergence, this invention returns to the incremental update step to perform iterative control for the next control cycle when the real-time reactive power allocation deviation is not less than a preset convergence criterion threshold within a preset convergence observation window. In this embodiment, iterative control involves re-executing incremental updates, boundary checks, and consistency assessments in the next control cycle to gradually approach the convergence state.

[0111] In summary, an iterative control mechanism was used to achieve progressive collaborative optimization of the virtual impedance parameters. Safety boundary verification ensured that the parameters remained within a safe range, consistency assessment guaranteed reactive power allocation accuracy, and closed-loop convergence verification ensured that the final control effect met requirements. The entire control process exhibited clear convergence and stability guarantees, effectively avoiding the risks of oscillation and divergence in multi-machine collaborative regulation.

[0112] This application also provides a virtual impedance collaborative control system for a multi-condition network converter, characterized in that it includes: The data acquisition module is used to acquire real-time operating data of multiple grid-connected converters at a common coupling point. The real-time operating data includes overall power quality characteristics, power output characteristics of each converter, and multi-condition operating status indicators. The reference quantity acquisition module is used to acquire global collaborative situation reference quantities and multiple current virtual impedance values ​​based on the multi-condition operation status identifier. The global collaborative situation reference quantities include multiple virtual common node voltages and total reactive load demand over a preset time period. The stability correction module is used to obtain the total harmonic distortion rate and voltage imbalance based on the overall power quality characteristics, construct the power quality coupling distortion index based on the total harmonic distortion rate and voltage imbalance, obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index, and correct multiple current virtual impedance values ​​based on the overall virtual impedance stability coefficient to obtain multiple current stable virtual impedance values. The deviation calculation module is used to obtain the individual capacity deviation of each multi-grid converter based on the power output characteristics. The control module is used to control multiple current stable virtual impedance values ​​according to the single-unit capacity deviation to obtain multiple target virtual impedances, and to control multiple grid-type converters according to the multiple target virtual impedances to obtain the control result.

[0113] In one embodiment, the stabilization correction module includes: The harmonic distortion rate acquisition unit is used to acquire the common coupling point voltage signal from the overall power quality characteristics, perform Fourier transform on the common coupling point voltage signal to obtain the fundamental voltage component and each harmonic voltage component, acquire the harmonic distortion rate of each harmonic voltage component and the fundamental voltage component, and then acquire the total harmonic distortion rate of the voltage based on the harmonic distortion rate of each harmonic voltage component. The imbalance degree acquisition unit is used to perform symmetrical component decomposition on the voltage signal at the common coupling point to obtain positive sequence voltage component and negative sequence voltage component, and to obtain voltage imbalance degree based on the negative sequence voltage component and the positive sequence voltage component. The stress factor acquisition unit is used to acquire the harmonic stress factor based on the ratio of the total harmonic distortion rate of the voltage to the preset harmonic distortion safety threshold, and to acquire the unbalanced stress factor based on the ratio of the voltage unbalance to the preset unbalance safety threshold. The coupling distortion index acquisition unit is used to acquire the power quality coupling distortion index based on the harmonic stress factor and the unbalanced stress factor, and to acquire the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltages of multiple virtual common nodes. The voltage deviation correction unit is used to obtain the voltage deviation rate between the virtual common node voltage and the preset rated voltage, and to obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltage deviation rate. The fundamental component correction unit is used to decompose the multiple current virtual impedance values ​​into multiple fundamental virtual impedance components and multiple harmonic virtual impedance components, and correct the multiple fundamental virtual impedance components according to the overall virtual impedance stability coefficient to obtain multiple corrected fundamental virtual impedance components. The harmonic component attenuation unit is used to attenuate and correct multiple harmonic virtual impedance components according to the total harmonic distortion rate of the voltage, so as to obtain multiple attenuated and corrected harmonic virtual impedance components. The superposition and reconstruction unit is used to superimpose and reconstruct multiple corrected fundamental virtual impedance components with multiple attenuation corrected harmonic virtual impedance components to obtain multiple current stable virtual impedance values.

[0114] This application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described method.

[0115] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0116] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0117] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0118] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for coordinated virtual impedance control of a multi-condition network converter, characterized in that, include: The real-time operating data of multiple grid-connected converters at a common coupling point is obtained. The real-time operating data includes overall power quality characteristics, power output characteristics of each converter, and multi-condition operating status indicators. The global collaborative situation reference quantity and multiple current virtual impedance values ​​are obtained based on the multi-condition operation status identifier. The global collaborative situation reference quantity includes multiple virtual common node voltages and total reactive load demand for a preset time period. The total harmonic distortion rate and voltage imbalance are obtained based on the overall power quality characteristics. A power quality coupling distortion index is constructed based on the total harmonic distortion rate and voltage imbalance. An overall virtual impedance stability coefficient is obtained based on the power quality coupling distortion index. Multiple current virtual impedance values ​​are corrected based on the overall virtual impedance stability coefficient to obtain multiple current stable virtual impedance values. The individual capacity deviation of each multi-grid converter is obtained based on the power output characteristics. The current stable virtual impedance values ​​are adjusted according to the single-unit capacity deviation to obtain multiple target virtual impedances. The multiple grid-type converters are then controlled according to the multiple target virtual impedances to obtain the control result.

2. The virtual impedance collaborative control method for a multi-condition network converter according to claim 1, characterized in that, The step of obtaining the global collaborative situation reference quantity and multiple current virtual impedance values ​​based on the multi-condition operating status identifier, wherein the global collaborative situation reference quantity includes multiple virtual common node voltages and total reactive load demand for a preset time period, includes: According to the multi-condition operation status identifier, a target impedance scanning strategy is matched from the preset scanning strategy library. The target impedance scanning strategy includes the scanning frequency range, the disturbance signal amplitude, and the scanning duration. According to the target impedance scanning strategy, at least one of the multiple grid-type converters is controlled to inject a disturbance signal into the common coupling point, and the voltage response signal and current response signal at the common coupling point are collected. Synchronous spectrum analysis is performed on the voltage response signal and the current response signal to obtain the voltage spectrum components and current spectrum components within the scanning frequency range, and the equivalent impedance of the power grid is obtained based on the voltage spectrum components and the current spectrum components. Obtain the rated voltage at the common coupling point, and obtain the grid short-circuit capacity based on the rated voltage and the grid equivalent impedance. Obtain the grid short-circuit capacity ratio estimate based on the grid short-circuit capacity and the preset rated total capacity of the multiple grid-type converters. The multi-condition operating status identifier is corrected based on the membership relationship between the estimated power grid short-circuit capacity ratio and the preset short-circuit capacity ratio threshold range, resulting in the corrected multi-condition operating status identifier. The voltages of multiple virtual common nodes are obtained based on the corrected multi-condition operating status identifier, the rated voltage, and the preset voltage stability margin. The reactive power is obtained from the multiple grid-type converters and summed to obtain the total reactive load demand. The corresponding reactive power reserve coefficient and real-time total reactive power are obtained according to the corrected multi-condition operating status identifier. The total reactive load demand is obtained according to the reactive power reserve coefficient and the real-time total reactive power. Multiple initial virtual impedances are obtained based on the corrected multi-condition operating status identifier and the estimated grid short-circuit capacity ratio. The initial virtual impedances are then normalized and corrected according to the preset rated capacity of multiple grid-type converters to obtain multiple current virtual impedance values.

3. The virtual impedance collaborative control method for a multi-condition network converter according to claim 1, characterized in that, The steps of obtaining the total harmonic distortion (THD) and voltage imbalance based on the overall power quality characteristics, constructing a power quality coupling distortion index based on the THD and voltage imbalance, obtaining an overall virtual impedance stability coefficient based on the power quality coupling distortion index, and correcting multiple current virtual impedance values ​​based on the overall virtual impedance stability coefficient to obtain multiple currently stable virtual impedance values ​​include: The common coupling point voltage signal is obtained from the overall power quality characteristics, and the common coupling point voltage signal is subjected to Fourier transform to obtain the fundamental voltage component and each harmonic voltage component. The harmonic distortion rate is obtained according to the harmonic voltage component and the fundamental voltage component, and the total harmonic distortion rate is obtained according to the harmonic distortion rate. The voltage signal at the common coupling point is decomposed into positive-sequence voltage components and negative-sequence voltage components, and the voltage imbalance is obtained based on the negative-sequence voltage components and the positive-sequence voltage components. The harmonic stress factor is obtained based on the ratio of the total harmonic distortion rate of the voltage to the preset harmonic distortion safety threshold, and the unbalanced stress factor is obtained based on the ratio of the voltage unbalance to the preset unbalance safety threshold. The power quality coupling distortion index is obtained based on the harmonic stress factor and the unbalanced stress factor, and the overall virtual impedance stability coefficient is obtained based on the power quality coupling distortion index and the voltages of multiple virtual common nodes. Obtain the voltage deviation rate between the virtual common node voltage and the preset rated voltage, and obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltage deviation rate; The multiple current virtual impedance values ​​are decomposed into multiple fundamental virtual impedance components and multiple harmonic virtual impedance components, respectively. The multiple fundamental virtual impedance components are corrected according to the overall virtual impedance stability coefficient to obtain multiple fundamental virtual impedance components. Based on the total harmonic distortion rate of the voltage, the attenuation correction is performed on the multiple harmonic virtual impedance components to obtain multiple harmonic virtual impedance components. Multiple fundamental virtual impedance components and multiple harmonic virtual impedance components are superimposed and reconstructed to obtain multiple current stable virtual impedance values.

4. The virtual impedance collaborative control method for a multi-condition network converter according to claim 1, characterized in that, After the step of obtaining the individual capacity deviation of each multi-grid converter based on the power output characteristics, the method further includes: Obtain the line topology parameters between each grid-type converter and the common coupling point, wherein the line topology parameters include line length, conductor cross-sectional area, conductor resistivity and line equivalent inductance coefficient; The fundamental frequency resistance value of each line is calculated based on the multiple line lengths, multiple conductor cross-sectional areas, and multiple conductor resistivities. The fundamental frequency inductive reactance value of each line is calculated based on the line length and the equivalent inductance coefficient of the line. The multiple fundamental frequency resistance values ​​and multiple fundamental frequency inductive reactance values ​​are vector-synthesized to obtain the basic line impedance of each line. During a preset detection period, each grid-type converter is controlled to inject multi-frequency stepped detection signals into the corresponding line, and the voltage response sequence and current response sequence of each grid-type converter output terminal under the excitation of the multi-frequency stepped detection signals are collected. The multi-frequency stepped detection signals cover multiple discrete frequency points within the fundamental frequency and the preset harmonic frequency band. The amplitude ratio and phase difference at each discrete frequency point are obtained based on the voltage response sequence and the current response sequence, and the measured impedance values ​​at multiple discrete frequency points are obtained based on multiple amplitude ratios and multiple phase differences. Compare the deviation between the measured impedance value of each line at the fundamental frequency and the corresponding impedance of the underlying line. When the deviation exceeds the preset impedance deviation threshold, the measured impedance value is used to replace the basic line impedance for updating, and the verified line impedance is obtained. The line impedance includes a resistive component and an inductive reactance component. The real-time conductor temperature and real-time load rate of each line are obtained. The resistance component is corrected by temperature coefficient according to the real-time conductor temperature to obtain the temperature-corrected resistance component. The inductive reactance component is corrected by magnetic saturation attenuation according to the real-time load rate to obtain the attenuation-corrected inductive reactance component. The temperature-corrected resistive component and the magnetically saturated attenuation-corrected inductive reactance component are vector reconstructed to obtain the equivalent line impedance value from each converter to the common coupling point.

5. The virtual impedance collaborative control method for a multi-condition network converter according to claim 4, characterized in that, After the step of vector reconstruction of the temperature-corrected resistive component and the magnetically saturated attenuation-corrected inductive reactance component to obtain the equivalent line impedance values ​​from each converter to the common coupling point, the method further includes: The multiple individual unit capacity deviations are arranged in descending order of their absolute values ​​to obtain a deviation priority sequence; Calculate the impedance ratio between any two grid-type converters based on the multiple equivalent line impedance values, and construct a line impedance coupling matrix based on the multiple impedance ratio values. Based on the line impedance coupling matrix, the individual capacity deviation of each converter is corrected by coupling propagation to obtain multiple equivalent deviations. Multiple positive and negative signs are obtained based on the multiple equivalent deviations, and the adjustment direction constraint of each grid-type converter is obtained based on the multiple positive and negative signs, wherein positive values ​​correspond to increasing virtual impedance and negative values ​​correspond to decreasing virtual impedance. The adjustment priority level of each grid-type converter is determined according to the deviation priority sequence, the absolute value of the equivalent deviation is obtained according to the multiple equivalent deviations, and multiple adjustment step sizes are obtained according to the adjustment priority level and the multiple absolute values ​​of the equivalent deviations. Obtain the preset control cycle duration, and use the multiple adjustment step sizes and the preset control cycle duration to obtain the adjustment rate constraint of each grid-type converter; By associating and encapsulating multiple adjustment direction constraints and multiple adjustment rate constraints, a coordinated and consistent control constraint is obtained.

6. The virtual impedance collaborative control method for a multi-condition network converter according to claim 5, characterized in that, The step of adjusting multiple current stable virtual impedance values ​​based on the single-unit capacity deviation to obtain multiple target virtual impedances, and controlling multiple grid-type converters to adjust based on the multiple target virtual impedances to obtain the adjustment result includes: The virtual impedance adjustment direction of each grid converter is determined according to multiple adjustment direction constraints, and the maximum allowable impedance change of each grid converter in a single control cycle is determined according to multiple adjustment rate constraints. Multiple current stable virtual impedance values ​​are incrementally updated along the corresponding virtual impedance adjustment direction according to the maximum allowable impedance change to obtain multiple candidate virtual impedances; The candidate virtual impedances are subjected to upper and lower limit truncation verification based on the preset virtual impedance safety boundary. When any candidate virtual impedance exceeds the preset virtual impedance safety boundary, it is clamped to the corresponding boundary value to obtain multiple virtual impedances after boundary verification. The expected reactive power output allocation ratio of each grid-type converter is calculated based on multiple equivalent line impedance values ​​and multiple virtual impedances after boundary verification. The deviation between the expected reactive power output allocation ratio and the preset capacity ratio allocation benchmark is calculated to obtain the multi-machine consistency deviation index. Determine whether the multi-machine consistency deviation index exceeds the preset consistency tolerance threshold; When the multi-machine consistency deviation index exceeds the preset consistency tolerance threshold, the virtual impedances after boundary verification are proportionally redistributed and corrected according to the multi-machine consistency deviation index to obtain multiple target virtual impedances. When the multi-machine consistency deviation index does not exceed the preset consistency tolerance threshold, the multiple virtual impedances after boundary verification are directly used as the multiple target virtual impedances. The multiple target virtual impedances are written into the virtual impedance control loop of each grid converter, and each grid converter is controlled to adjust the reactive power output according to the corresponding target virtual impedance. Within a preset convergence observation window, the actual reactive power output of each grid-type converter is continuously collected, and the real-time reactive power distribution deviation is calculated based on the multiple actual reactive power outputs and the total reactive load demand. Determine whether the real-time reactive power distribution deviation is less than a preset convergence criterion threshold within a preset convergence observation window; When the real-time reactive power distribution deviation is less than the preset convergence criterion threshold within the preset convergence observation window, it is determined that the multiple grid-type converters have converged to the global collaborative situation reference quantity, and multiple target virtual impedances are locked. When the real-time reactive power distribution deviation is not less than the preset convergence criterion threshold within the preset convergence observation window, the process returns to the step of incrementally updating multiple current stable virtual impedance values ​​along the corresponding virtual impedance adjustment direction according to the maximum allowable impedance change to obtain multiple candidate virtual impedances for iterative regulation in the next control cycle.

7. A virtual impedance coordinated control system for a multi-condition network converter, characterized in that, include: The data acquisition module is used to acquire real-time operating data of multiple grid-connected converters at a common coupling point. The real-time operating data includes overall power quality characteristics, power output characteristics of each converter, and multi-condition operating status indicators. The reference quantity acquisition module is used to acquire global collaborative situation reference quantities and multiple current virtual impedance values ​​based on the multi-condition operation status identifier. The global collaborative situation reference quantities include multiple virtual common node voltages and total reactive load demand over a preset time period. The stability correction module is used to obtain the total harmonic distortion rate and voltage imbalance based on the overall power quality characteristics, construct the power quality coupling distortion index based on the total harmonic distortion rate and voltage imbalance, obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index, and correct multiple current virtual impedance values ​​based on the overall virtual impedance stability coefficient to obtain multiple current stable virtual impedance values. The deviation calculation module is used to obtain the individual capacity deviation of each multi-grid converter based on the power output characteristics. The control module is used to control multiple current stable virtual impedance values ​​according to the single-unit capacity deviation to obtain multiple target virtual impedances, and to control multiple grid-type converters according to the multiple target virtual impedances to obtain the control result.

8. The virtual impedance collaborative control system for a multi-condition network converter according to claim 7, characterized in that, The stabilization correction module includes: The harmonic distortion rate acquisition unit is used to acquire the common coupling point voltage signal from the overall power quality characteristics, perform Fourier transform on the common coupling point voltage signal to obtain the fundamental voltage component and each harmonic voltage component, acquire the harmonic distortion rate of each harmonic voltage component and the fundamental voltage component, and then acquire the total harmonic distortion rate of the voltage based on the harmonic distortion rate of each harmonic voltage component. The imbalance degree acquisition unit is used to perform symmetrical component decomposition on the voltage signal at the common coupling point to obtain positive sequence voltage component and negative sequence voltage component, and to obtain voltage imbalance degree based on the negative sequence voltage component and the positive sequence voltage component. The stress factor acquisition unit is used to acquire the harmonic stress factor based on the ratio of the total harmonic distortion rate of the voltage to the preset harmonic distortion safety threshold, and to acquire the unbalanced stress factor based on the ratio of the voltage unbalance to the preset unbalance safety threshold. The coupling distortion index acquisition unit is used to acquire the power quality coupling distortion index based on the harmonic stress factor and the unbalanced stress factor, and to acquire the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltages of multiple virtual common nodes. The voltage deviation correction unit is used to obtain the voltage deviation rate between the virtual common node voltage and the preset rated voltage, and to obtain the overall virtual impedance stability coefficient based on the power quality coupling distortion index and the voltage deviation rate. The fundamental component correction unit is used to decompose the multiple current virtual impedance values ​​into multiple fundamental virtual impedance components and multiple harmonic virtual impedance components, and correct the multiple fundamental virtual impedance components according to the overall virtual impedance stability coefficient to obtain multiple corrected fundamental virtual impedance components. The harmonic component attenuation unit is used to attenuate and correct multiple harmonic virtual impedance components according to the total harmonic distortion rate of the voltage, so as to obtain multiple attenuated and corrected harmonic virtual impedance components. The superposition and reconstruction unit is used to superimpose and reconstruct multiple corrected fundamental virtual impedance components with multiple attenuation corrected harmonic virtual impedance components to obtain multiple current stable virtual impedance values.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

Images