Dynamic control method, system and equipment for virtual impedance of power grid system and medium

Abstract

The invention belongs to the field of power grid system control, and discloses a power grid system virtual impedance dynamic control method, system and device and a medium. The control method comprises the following steps: judging whether the power grid system breaks down or not by acquiring power characteristics of electronic equipment in the power grid system, including content proportions of voltage harmonics and current harmonics, current amplitude changes and positive and negative sequence voltage amplitudes. When a fault occurs, normal virtual impedance is calculated and combined with response current of harmonic waves to obtain dynamic virtual impedance, and then self-adaptive virtual impedance is comprehensively obtained and switched to the impedance value. According to the method, rapid and accurate dynamic current limiting and reactive power supporting under the complex fault working condition are achieved, the adaptability and stability of power electronic equipment to power grid faults are improved, fault current is effectively restrained, equipment damage is prevented, and meanwhile the transient characteristic and reliability of a system are enhanced.

Description

Technical Field

[0001] This application belongs to the field of power grid system control, and specifically relates to a method, system, device and medium for dynamic control of virtual impedance in power grid systems. Background Technology

[0002] With the development of power systems, the grid-connected capacity of photovoltaic power generation and energy storage systems is continuously increasing, and the proportion of power electronic equipment in the power grid is also constantly rising. As the grid-connected power levels of power electronic equipment increase and their connection locations become more widespread, the power grid is increasingly exhibiting characteristics of a weak grid, and the grid voltage contains abundant background harmonics.

[0003] The internal impedance of the power grid can alter the gain of the control loop of grid-connected power electronic equipment, affecting control performance and potentially leading to unstable grid-connected current. Current virtual impedance strategies are mostly set to a fixed value. While virtual impedance is tested and adjusted to accommodate different operating conditions, it still cannot cover all types of faults in the power grid. Under certain specific fault conditions, the system consisting of grid-connected power electronic equipment and the power grid may exhibit low or even negative resistance, making it difficult to suppress or even amplifying the fault current, leading to equipment damage. Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method, system, device, and medium for dynamic control of virtual impedance in a power grid system. This solution improves the adaptability and stability of power electronic equipment to power grid faults, effectively suppresses fault currents, and prevents equipment damage.

[0005] To address the aforementioned technical problems, the first aspect of this disclosure proposes a dynamic control method for virtual impedance in a power grid system, the control method comprising: Obtain the power characteristics of electronic devices in the power grid system; Based on the proportion of voltage harmonics and current harmonics in the power characteristics, the change in current amplitude, and / or the magnitude of positive-sequence voltage and negative-sequence voltage, determine whether the power grid system is faulty; When the power grid system fails, the normal virtual impedance during normal operation of the power grid system is calculated, and the dynamic virtual impedance is calculated based on the harmonic response current during the power grid system failure. An adaptive virtual impedance is obtained by combining the normal virtual impedance and the dynamic virtual impedance, and the power grid system is controlled to switch the virtual impedance to the adaptive virtual impedance.

[0006] According to a preferred embodiment of this disclosure, obtaining the power characteristics of electronic devices in a power grid system includes: High-frequency sampling is performed on the electronic equipment in the power grid system to obtain joint time-frequency domain features; The harmonic components of voltage and current in the power grid system are extracted from the joint features in the time and frequency domain using time-frequency analysis, and are used as the voltage harmonics and the current harmonics.

[0007] According to a preferred embodiment of this disclosure, determining whether the power grid system is faulty based on the changes in current amplitude in the power characteristics includes: Transform the change of current amplitude over time in the electrical characteristics from the two-dimensional coordinate system to the dq coordinate system; The d-axis fluctuation amplitude of the current amplitude in the dq coordinate system is compared with a preset abnormal current value to determine whether the d-axis fluctuation amplitude is abnormal; and the relative deviation between the d-axis fluctuation amplitude and the q-axis fluctuation amplitude of the current amplitude in the dq coordinate system is calculated. When the d-axis fluctuation amplitude is abnormal and the relative deviation is higher than the preset deviation value, the power grid system is determined to be faulty.

[0008] According to a preferred embodiment of this disclosure, determining whether the power grid system is faulty based on the magnitudes of the positive-sequence voltage and negative-sequence voltage in the power characteristics includes: The positive sequence voltage is compared with a preset positive sequence voltage threshold to determine whether the voltage drops abnormally. The negative sequence voltage is compared with a preset negative sequence voltage threshold to determine whether an asymmetrical fault has occurred in the power grid system. When the voltage drops abnormally, or when an asymmetrical fault occurs in the power grid system, the power grid system fault is determined.

[0009] According to a preferred embodiment of this disclosure, determining whether the power grid system is faulty based on the proportion of voltage harmonics and current harmonics in the power characteristics includes: When the proportion of voltage harmonics in voltage and the proportion of current harmonics in current both exceed the harmonic proportion threshold, the power grid fault is determined.

[0010] According to a preferred embodiment of this disclosure, the step of calculating the dynamic virtual impedance based on the harmonic response current during a power grid system fault includes: When the power grid system is faulty, obtain the equivalent resistance value, equivalent inductance value, and harmonic angular velocity of the virtual impedance of the power grid system; The faults in the power grid system are calculated based on the equivalent resistance value, equivalent inductance value, and harmonic angular velocity.

[0011] According to a preferred embodiment of this disclosure, the step of synthesizing the normal virtual impedance and the dynamic virtual impedance to obtain the adaptive virtual impedance includes: The first linear combination coefficient of the normal virtual impedance and the second linear combination coefficient of the dynamic virtual impedance are dynamically adjusted using a fuzzy logic algorithm. The adaptive virtual impedance is obtained by weighting the normal virtual impedance and the dynamic virtual impedance using the first linear combination coefficient and the second linear combination coefficient.

[0012] To address the aforementioned technical problems, a second aspect of this disclosure proposes a dynamic control system for virtual impedance in a power grid system, the control system comprising: The data acquisition module is used to acquire the power characteristics of electronic devices in the power grid system; The fault diagnosis module is used to determine whether the power grid system is faulty based on the proportion of voltage harmonics and current harmonics, the change in current amplitude, and / or the magnitude of positive-sequence voltage and negative-sequence voltage in the power characteristics. The virtual impedance calculation module is used to calculate the normal virtual impedance of the power grid system during normal operation when the power grid system is faulty, and to calculate the dynamic virtual impedance based on the response current of the harmonics when the power grid system is faulty. An adaptive control module is used to synthesize the normal virtual impedance and the dynamic virtual impedance to obtain an adaptive virtual impedance, and to control the power grid system to switch the virtual impedance to the adaptive virtual impedance.

[0013] To address the aforementioned technical problems, a third aspect of this disclosure provides an electronic device, comprising: Processor; and A memory storing computer-executable instructions, which, when executed, cause the processor to perform the method described in any of the above embodiments.

[0014] To address the aforementioned technical problems, a fourth aspect of this disclosure provides a computer storage medium that stores one or more programs, which, when executed by a processor, implement the method described in any of the above embodiments.

[0015] Compared with existing technologies, this application has the following advantages: By acquiring the power characteristics of electronic equipment in the power grid system, including the proportion of voltage harmonics and current harmonics, current amplitude changes, and positive and negative sequence voltage amplitudes, it determines whether the power grid system is faulty. During a fault, the normal virtual impedance is calculated and combined with the harmonic response current to obtain the dynamic virtual impedance, which is then integrated to obtain an adaptive virtual impedance, and the system switches to this impedance value. This achieves rapid and accurate dynamic current limiting and reactive power support under complex fault conditions, improves the adaptability and stability of power electronic equipment to power grid faults, effectively suppresses fault currents, prevents equipment damage, and enhances the transient characteristics and reliability of the system.

[0016] Other features and advantages of this application will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the application. The objectives and other advantages of this application may be realized and obtained by means of the structures pointed out in the description, claims and drawings. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A schematic flowchart of a method for dynamic control of virtual impedance in a power grid system according to an embodiment of the present disclosure is shown. Figure 2 A schematic diagram of adaptive virtual impedance selection according to an embodiment of the present disclosure is shown; Figure 3 A schematic diagram illustrating simulation results of fixed virtual impedance and adaptive virtual impedance strategies according to embodiments of this disclosure is shown. Figure 4 A schematic diagram of a method for determining whether a power grid system is faulty according to an embodiment of the present disclosure is shown; Figure 5 A second schematic diagram of a method for determining whether a power grid system is faulty according to an embodiment of this disclosure is shown; Figure 6 A second schematic flowchart of a method for dynamic control of virtual impedance in a power grid system according to an embodiment of the present disclosure is shown. Figure 7 A schematic flowchart of a method for dynamic control of virtual impedance in a power grid system according to an embodiment of the present disclosure is shown in part three. Figure 8 A schematic diagram of a virtual impedance dynamic control system structure for a power grid system according to an embodiment of the present disclosure is shown. Figure 9 A schematic diagram of an electronic device structure according to an embodiment of the present disclosure is shown. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] The same reference numerals in the accompanying drawings denote the same or similar elements, components, or parts, and therefore repeated descriptions of the same or similar elements, components, or parts may be omitted below. It should also be understood that although qualifiers such as first, second, third, etc., indicating numbers may be used herein to describe various devices, elements, components, or parts, these devices, elements, components, or parts should not be limited by these qualifiers. That is, these qualifiers are only used to distinguish one from another. For example, a first device may also be referred to as a second device, without departing from the essence of the technical solution of this disclosure. Furthermore, the terms "and / or" and "and / or" refer to all combinations including the first or more of the listed items.

[0021] Please see Figure 1 , Figure 1 This is one of the flowcharts of a dynamic control method for virtual impedance in a power grid system provided in this disclosure, such as... Figure 1 As shown, the control methods include: S11. Obtain the power characteristics of electronic devices in the power grid system.

[0022] In this embodiment, high-frequency sampling technology is used to acquire the power characteristics of electronic equipment in the power grid system, including harmonic components of voltage and current, as well as the amplitude and phase information of positive and negative sequence voltage and current. This provides a data foundation for subsequent fault diagnosis and virtual impedance adjustment. Accurately capturing the changes in power characteristics of the power grid system under various operating conditions provides a precise basis for dynamic adaptive virtual impedance control strategies, thereby effectively improving the response speed and suppression capability of power electronic equipment to complex power grid faults.

[0023] Specifically, high-frequency sampling is performed on electronic equipment in the power grid system to obtain joint time-frequency domain features. Using time-frequency analysis, harmonic components of voltage and current in the power grid system are extracted from these joint features, serving as voltage harmonics and current harmonics. Joint time-frequency domain features refer to simultaneously extracting features from both the time domain (time dimension) and frequency domain (frequency dimension) of the signal and fusing them to more comprehensively describe the dynamic characteristics of the signal.

[0024] In this embodiment, the power electronic equipment can use high-frequency sampling of 10kHz or above, combined with the improved S-transform time-frequency analysis method, to accurately detect the 0.2-150th harmonic components of voltage and current through joint time-frequency domain feature extraction. This harmonic range can cover most of the harmonics under different operating conditions of the power system.

[0025] S12. Determine whether the power grid system is faulty based on the proportion of voltage and current harmonics in the power characteristics, the changes in current amplitude, and / or the magnitudes of positive and negative sequence voltages.

[0026] In this embodiment, based on the acquired power characteristics, a composite criterion is constructed, including analyzing whether the proportion of voltage and current harmonics exceeds a threshold, whether the current amplitude changes abnormally, and whether the amplitudes of positive and negative sequence voltages deviate from the normal range, to comprehensively determine whether the power grid system is in a fault state. This scheme can accurately and promptly identify the fault state of the power grid system, providing a reliable basis for subsequent dynamic adaptive virtual impedance adjustment, thereby effectively suppressing fault currents and ensuring the safe and stable operation of power electronic equipment and the power grid.

[0027] S13. When the power grid system is faulty, calculate the normal virtual impedance when the power grid system is operating normally, and calculate the dynamic virtual impedance based on the response current of the harmonics when the power grid system is faulty.

[0028] In this embodiment, when a power grid system fault occurs, the normal virtual impedance under normal system operation is first calculated as a reference value. Simultaneously, based on the harmonic response current data during the fault, a dynamic virtual impedance value adapted to the current fault state is calculated in real time using a specific algorithm. This scheme, by combining the reference value and the dynamic value, ensures the stability of the system under normal operation while achieving rapid response to faults, effectively suppressing the expansion of fault current, preventing equipment damage, and improving the adaptability of power electronic equipment to complex fault conditions.

[0029] In this embodiment, the power frequency virtual impedance value during normal grid operation (voltage and current frequency is 50Hz) has been calculated as Z0=R0+jw0L0. Where (Z0 is the virtual impedance value in the controller, R0 is the equivalent resistance value in the virtual impedance, L0 is the equivalent resistance value in the virtual impedance, and w0 is the grid angular velocity).

[0030] S14. The adaptive virtual impedance is obtained by combining the normal virtual impedance and the dynamic virtual impedance, and the power grid system is controlled to switch the virtual impedance to the adaptive virtual impedance.

[0031] In this embodiment, the pre-calculated normal virtual impedance during normal power grid operation is linearly combined with the dynamic virtual impedance calculated in real time based on the harmonic response current during a fault (the combination coefficients are determined through debugging or dynamically adjusted using fuzzy logic) to form an adaptive virtual impedance value that adapts to the current fault condition. This triggers a control command to seamlessly switch the system from the normal impedance mode to this adaptive impedance mode. By dynamically fusing normal and dynamic impedance characteristics, precise current limiting control is achieved throughout the fault process. This avoids system oscillations caused by impedance abrupt changes and ensures the rapid reactive power support capability of power electronic equipment for the power grid under complex fault scenarios, significantly improving operational stability in weak grid environments.

[0032] In this embodiment, regarding the selection of virtual impedance, based on the virtual impedance introduction method described in this invention, a suitable virtual impedance is selected to replace the normal virtual impedance according to the identified fault current harmonic characteristics. Several adaptive virtual impedance values ​​are calculated for selection based on the harmonic characteristics of this product under different fault conditions, as shown in the appendix. Figure 2 As shown, this project calculated 20 adaptive virtual impedance values ​​(Z). v0 Z v2 ...Z vn It can basically cover situations where harmonics from 0.2 to 150 occur.

[0033] In this embodiment, simulation tests are performed on an RTDS platform. Different frequencies and combinations of harmonics are injected into a simulated power grid through the simulation platform. The harmonic current suppression effects of a fixed impedance strategy and an adaptive impedance strategy are compared and contrasted, with comparisons made for the 5th, 10th, 20th, 50th, and 100th harmonics. Figure 3 As shown, the dynamic adaptive virtual impedance control strategy can significantly improve the harmonic suppression effect of the converter. Furthermore, no stability issues occurred during the test.

[0034] In this embodiment, the presence of a fault in the power grid system is determined by acquiring the power characteristics of electronic equipment in the power grid system, including the proportion of voltage harmonics and current harmonics, changes in current amplitude, and positive and negative sequence voltage amplitudes. During a fault, the normal virtual impedance is calculated and combined with the response current of harmonics to derive the dynamic virtual impedance. This results in a comprehensive adaptive virtual impedance, which is then switched to. This achieves rapid and accurate dynamic current limiting and reactive power support under complex fault conditions, improving the adaptability and stability of power electronic equipment to power grid faults, effectively suppressing fault currents, preventing equipment damage, and enhancing the transient characteristics and reliability of the system.

[0035] like Figure 4 The diagram illustrates one method for determining whether a power grid system is faulty, including the following steps: S21. Transform the change of current amplitude over time in the power characteristics from the two-dimensional coordinate system to the dq coordinate system.

[0036] In this embodiment, the time-varying current amplitude in the power characteristics is transformed from a two-dimensional stationary coordinate system (αβ coordinate system) to a dq rotating coordinate system through coordinate transformation. Utilizing the decoupling characteristics of the d-axis (active) and q-axis (reactive) components in the dq coordinate system, steady-state and transient characteristics of the current amplitude are extracted. This transformation simplifies the fault characteristic analysis process, making the extraction of current fluctuation amplitudes (Δid, Δiq) more accurate. It provides a clear and decoupled judgment basis for subsequent fault assessment based on dq-axis component thresholds (e.g., Δid > N%*In and Δiq / Δid > 0.3), improving the sensitivity and reliability of fault identification.

[0037] In this embodiment, the dp coordinate system means a two-phase rotating coordinate system, also known as a synchronous rotating coordinate system or Park coordinate system. It is a reference coordinate system that rotates synchronously with the motor's magnetic field or voltage vector, which is transformed from a three-phase stationary coordinate system (abc) or a two-phase stationary coordinate system (αβ).

[0038] S22. Compare the d-axis fluctuation amplitude of the current amplitude in the dq coordinate system with the preset abnormal current value to determine whether the d-axis fluctuation amplitude is abnormal; and calculate the relative deviation between the d-axis fluctuation amplitude and the q-axis fluctuation amplitude of the current amplitude in the dq coordinate system.

[0039] In this embodiment, the d-axis fluctuation component (Δid) of the current amplitude is extracted in the dq coordinate system and compared with a preset current anomaly threshold (N%*In) to determine the abnormal state. Simultaneously, the relative deviation (Δiq / Δid) between the d-axis and q-axis fluctuation amplitudes is calculated as an auxiliary criterion. Rapid initial fault assessment is achieved through d-axis threshold comparison, and the analysis of the relative deviation between the dq axes distinguishes between symmetrical and asymmetrical fault types, improving fault identification accuracy and providing precise fault characteristic input for subsequent dynamic adjustment of virtual impedance.

[0040] S23. When the d-axis fluctuation amplitude is abnormal and the relative deviation is higher than the preset deviation value, a power grid system fault is determined.

[0041] In this embodiment, in the dq coordinate system, when the amplitude of the d-axis current fluctuation exceeds a preset threshold and the relative deviation between the amplitudes of the d-axis and q-axis fluctuations exceeds a set value, a positive fault assessment condition is triggered, and the power grid system is determined to have entered a fault state. By comparing thresholds using dual criteria, normal fluctuations and fault states are effectively distinguished, avoiding misjudgments based on single parameters, improving the accuracy and reliability of fault identification, and providing a precise trigger signal for subsequent dynamic virtual impedance adjustment.

[0042] Specifically, in the dq coordinate system, determine whether Δid > N%*I nFurthermore, a positive fault assessment is triggered when Δiq / Δid > 0.3, where Δid is the d-axis current fluctuation amplitude, Δiq is the q-axis current fluctuation amplitude, N is the proportional threshold, and I... n This is the rated current.

[0043] like Figure 5 The second schematic diagram illustrates a method for determining whether a power grid system is faulty, and includes the following steps: S31. Compare the positive sequence voltage with the preset positive sequence voltage threshold to determine whether the voltage drops abnormally.

[0044] In this embodiment, the positive-sequence voltage component of the power grid system is extracted, and its actual value is compared with a pre-set positive-sequence voltage safety threshold. Voltage dips are identified by determining whether the actual value is below the threshold. This solution can quickly and accurately detect power grid voltage dip faults, providing a reliable basis for subsequent protection device actions or virtual impedance adjustments, effectively preventing equipment damage due to voltage anomalies, and improving the operational stability of the power grid under fault conditions.

[0045] S32. Compare the negative sequence voltage with the preset negative sequence voltage threshold to determine whether an asymmetrical fault has occurred in the power grid system.

[0046] In this embodiment, the negative sequence voltage component is extracted from the power characteristics of the power grid system. Its actual measured value is directly compared with a pre-set negative sequence voltage safety threshold. Based on the comparison result (whether the actual value exceeds the threshold), it is determined whether an asymmetrical fault exists in the power grid. This scheme accurately identifies asymmetrical faults using the negative sequence voltage characteristic, featuring high detection sensitivity and fast response speed. It provides timely evidence for subsequent fault isolation or dynamic compensation measures, effectively improving the stability of power grid operation and power quality.

[0047] S33. When the voltage drops abnormally, or when an asymmetrical fault occurs in the power grid system, determine the fault in the power grid system.

[0048] In this embodiment, voltage drop and asymmetric fault are identified by judging the amplitude of positive sequence voltage U+ and negative sequence voltage U-. When the positive sequence voltage U+ is lower than 0.9pu, it is considered that an abnormal voltage drop has occurred, and when the negative sequence voltage is higher than 0.05pu, it is considered that an asymmetric fault has occurred.

[0049] The third method for determining whether a power grid system is faulty includes the following steps: when the proportion of voltage harmonics in voltage and the proportion of current harmonics in current both exceed the harmonic proportion threshold, a power grid fault is determined.

[0050] In this embodiment, harmonic analysis is performed on the voltage and current in the power grid system separately. The proportion of voltage harmonics in the voltage and the proportion of current harmonics in the current are calculated. These two proportions are compared with pre-set harmonic proportion thresholds. If both exceed the corresponding thresholds, a power grid fault is determined. This scheme, through a composite criterion of exceeding dual harmonic proportion limits, can accurately identify power grid faults caused by harmonic pollution, effectively avoiding misjudgments based on a single parameter. It provides a reliable basis for subsequent harmonic suppression measures or fault isolation operations, ensuring the safe and stable operation of the power grid.

[0051] In this embodiment, when the proportion of voltage and current harmonics exceeds M%, where M is the harmonic proportion threshold, the virtual impedance adjustment strategy is triggered.

[0052] Please see Figure 6 , Figure 6 This is a schematic diagram of the second part of the flowchart of a dynamic control method for virtual impedance in a power grid system provided in this disclosure, such as... Figure 6 As shown, the control methods include: S41. Obtain the equivalent resistance, equivalent inductance, and harmonic angular velocity of the virtual impedance of the power grid system when a fault occurs.

[0053] In this embodiment, at a specific moment when a fault occurs in the power grid system, the equivalent resistance and equivalent inductance values ​​characterizing the virtual impedance are extracted through real-time monitoring and calculation. Simultaneously, harmonic angular velocity parameters related to the system's harmonic frequencies are acquired, providing crucial data support for subsequent fault analysis and dynamic control. This scheme, by simultaneously acquiring the resistance, inductance components, and harmonic angular velocities of the virtual impedance, can accurately quantify the system's dynamic characteristics under fault conditions, providing multi-dimensional input for the virtual impedance adaptive adjustment algorithm.

[0054] S42. The faults in the power grid system are calculated based on the equivalent resistance value, equivalent inductance value, and harmonic angular velocity.

[0055] In this embodiment, based on the acquired virtual impedance equivalent resistance value, equivalent inductance value, and harmonic angular velocity during a power grid system fault, a pre-defined fault characteristic calculation model (such as an algorithm for correlating impedance parameters with harmonic frequencies and impedance angle change analysis) is used to comprehensively calculate and process these parameters, thereby deriving and determining fault-related information such as the fault type, location, or severity of the power grid system. This scheme overcomes the limitations of single-parameter judgment by integrating multi-dimensional electrical parameters for comprehensive calculation and analysis, enabling more accurate and comprehensive identification of power grid faults. This provides a reliable basis for subsequent targeted fault isolation, system recovery, and optimized control strategies, effectively improving the reliability and stability of power grid operation.

[0056] Specifically, based on the expected harmonic response current Im under different fault conditions, the virtual impedance value Z at that frequency is calculated.n =U m / I m =R n +jw n L n Among them, Z n The virtual impedance value under harmonic conditions, R n The equivalent resistance value in the virtual impedance during a power grid system fault, L n The equivalent resistance value in the virtual impedance, w n The harmonic angular velocity. The harmonic response voltage U. m Harmonic response current I m Based on equipment commissioning requirements, it is generally controlled as I. m <2%I n .

[0057] Please see Figure 7 , Figure 7 This is the third flowchart of a method for dynamic control of virtual impedance in a power grid system provided in this disclosure, as shown below. Figure 7 As shown, the control methods include: S51. The first linear combination coefficient of the normal virtual impedance and the second linear combination coefficient of the dynamic virtual impedance are dynamically adjusted using a fuzzy logic algorithm.

[0058] In this embodiment, a fuzzy logic algorithm is used, taking the real-time operating status of the power grid (such as voltage fluctuations, current distortion rate, power factor, etc.) as input variables. Fuzzy inference is performed through a preset fuzzy rule base, and weighted coefficients adapted to the current operating conditions are dynamically generated based on the inference results. These coefficients are then weighted and summed for both the normal and dynamic virtual impedances, achieving real-time adaptive adjustment of the combined coefficients. This scheme overcomes the limitations of fixed coefficient combinations. Through the flexible decision-making mechanism of fuzzy logic, the virtual impedance characteristics can smoothly transition between steady-state and transient operating conditions, ensuring economical operation of the system under normal conditions while improving dynamic response capabilities during fault periods.

[0059] S52. The adaptive virtual impedance is obtained by weighting the normal virtual impedance and the dynamic virtual impedance using the first linear combination coefficient and the second linear combination coefficient.

[0060] In this embodiment, the first linear combination coefficient, dynamically determined by a fuzzy logic algorithm, is multiplied by the normal virtual impedance, and the second linear combination coefficient is multiplied by the dynamic virtual impedance. The two products are then summed and weighted to calculate a weighted average, thus synthesizing an adaptive virtual impedance that simultaneously considers both normal and dynamic characteristics. This scheme achieves dynamic optimization of the virtual impedance through a dual-coefficient weighting mechanism, enabling the system to maintain efficient operation in steady state and quickly switch to a strong disturbance rejection mode during transient faults. It effectively balances economic efficiency and reliability requirements, significantly improving control accuracy and stability under complex power grid conditions.

[0061] Specifically, during grid faults, in order to inject sufficient supporting current into the grid, the power generation equipment needs to appropriately adjust the power frequency virtual impedance value Z. 0n =K1·Z0. The actual virtual impedance value Z is calculated after linear combination. v =Z 0n +K2·Z n = K1·Z0+K2·Z n The linear combination coefficients K1 and K2 can be determined through debugging or dynamically adjusted using fuzzy logic.

[0062] Please see Figure 8 , Figure 8 This disclosure provides a dynamic control system for virtual impedance in a power grid system. The control system includes: a data acquisition module 11, a fault judgment module 12, a virtual impedance calculation module 13, and an adaptive control module 14.

[0063] In this embodiment, the data acquisition module 11 is used to acquire the power characteristics of electronic devices in the power grid system.

[0064] In this embodiment, the fault judgment module 12 is used to determine whether the power grid system is faulty based on the proportion of voltage harmonics and current harmonics in the power characteristics, the change in current amplitude, and / or the magnitude of positive sequence voltage and negative sequence voltage.

[0065] In this embodiment, the virtual impedance calculation module 13 is used to calculate the normal virtual impedance of the power grid system during normal operation when the power grid system is faulty, and to calculate the dynamic virtual impedance based on the response current of the harmonics when the power grid system is faulty.

[0066] In this embodiment, the adaptive control module 14 is used to obtain an adaptive virtual impedance by combining the normal virtual impedance and the dynamic virtual impedance, and to control the power grid system to switch the virtual impedance to the adaptive virtual impedance.

[0067] In this embodiment, the data acquisition module 11 is specifically used to perform high-frequency sampling on electronic devices in the power grid system to obtain joint time-frequency domain features; and to extract the harmonic components of voltage and current in the power grid system from the joint time-frequency domain features using time-frequency analysis, as voltage harmonics and current harmonics.

[0068] In this embodiment, the fault judgment module 12 is specifically used to transform the change of current amplitude over time in the power characteristics from a two-dimensional coordinate system to a dq coordinate system; compare the d-axis fluctuation amplitude of the current amplitude in the dq coordinate system with a preset abnormal current value to determine whether the d-axis fluctuation amplitude is abnormal; and calculate the relative deviation between the d-axis fluctuation amplitude and the q-axis fluctuation amplitude of the current amplitude in the dq coordinate system; when the d-axis fluctuation amplitude is abnormal and the relative deviation is higher than a preset deviation value, a power grid system fault is determined.

[0069] In this embodiment, the fault judgment module 12 is specifically used to compare the positive sequence voltage with a preset positive sequence voltage threshold to determine whether the voltage drops abnormally; compare the negative sequence voltage with a preset negative sequence voltage threshold to determine whether an asymmetrical fault has occurred in the power grid system; and determine the power grid system fault when the voltage drops abnormally or an asymmetrical fault occurs in the power grid system.

[0070] In this embodiment, the fault judgment module 12 is specifically used to determine a power grid fault when the proportion of voltage harmonics in voltage and the proportion of current harmonics in current both exceed the harmonic proportion threshold.

[0071] In this embodiment, the virtual impedance calculation module 13 is specifically used to obtain the equivalent resistance value, equivalent inductance value, and harmonic angular velocity of the virtual impedance of the power grid system when a power grid system fault occurs; and to calculate the power grid system fault based on the equivalent resistance value, equivalent inductance value, and harmonic angular velocity.

[0072] In this embodiment, the adaptive control module 14 is specifically used to dynamically adjust the first linear combination coefficient of the normal virtual impedance and the second linear combination coefficient of the dynamic virtual impedance using a fuzzy logic algorithm; and to obtain the adaptive virtual impedance by weighting the normal virtual impedance and the dynamic virtual impedance using the first linear combination coefficient and the second linear combination coefficient.

[0073] like Figure 9 As shown, this embodiment of the present disclosure provides an electronic device, including a processor 1110, a communication interface 1120, a memory 1130, and a communication bus 1140, wherein the processor 1110, the communication interface 1120, and the memory 1130 communicate with each other through the communication bus 1140. Memory 1130 is used to store computer programs; When the processor 1110 executes the program stored in the memory 1130, it implements any of the above methods.

[0074] The electronic device provided in this embodiment of the present disclosure has a processor 1110 that obtains the power characteristics of the electronic device in the power grid system by executing a program stored in the memory 1130; determines whether the power grid system is faulty based on the proportion of voltage harmonics and current harmonics in the power characteristics, the change in current amplitude, and / or the magnitude of positive-sequence voltage and negative-sequence voltage; calculates the normal virtual impedance when the power grid system is operating normally, and calculates the dynamic virtual impedance based on the response current of the harmonics when the power grid system is faulty; obtains an adaptive virtual impedance by combining the normal virtual impedance and the dynamic virtual impedance, and controls the power grid system to switch the virtual impedance to the adaptive virtual impedance.

[0075] The communication bus 1140 mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus 1140 can be divided into an address bus, a data bus, and a component bus, etc. For ease of illustration, it is represented by only one thick line in the figure, but this does not indicate that there is only one bus or one type of bus.

[0076] The communication interface 1120 is used for communication between the above-mentioned electronic device and other devices.

[0077] The memory 1130 may include random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Optionally, the memory 1130 may also be at least one storage device located remotely from the aforementioned processor 1110.

[0078] The processor 1110 mentioned above can be a general-purpose processor 1110, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0079] This disclosure provides a computer-readable storage medium storing one or more programs that can be executed by one or more processors 1110 to implement the methods of any of the above embodiments.

[0080] In the above embodiments, implementation can be achieved, in whole or in part, by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this disclosure is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0081] Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for dynamic control of virtual impedance in a power grid system, characterized in that, The control method includes: Obtain the power characteristics of electronic devices in the power grid system; Based on the proportion of voltage harmonics and current harmonics in the power characteristics, the change in current amplitude, and / or the magnitude of positive-sequence voltage and negative-sequence voltage, determine whether the power grid system is faulty; When the power grid system fails, the normal virtual impedance during normal operation of the power grid system is calculated, and the dynamic virtual impedance is calculated based on the harmonic response current during the power grid system failure. An adaptive virtual impedance is obtained by combining the normal virtual impedance and the dynamic virtual impedance, and the power grid system is controlled to switch the virtual impedance to the adaptive virtual impedance.

2. The control method according to claim 1, characterized in that, The acquisition of the power characteristics of electronic devices in the power grid system includes: High-frequency sampling is performed on the electronic equipment in the power grid system to obtain joint time-frequency domain features; The harmonic components of voltage and current in the power grid system are extracted from the joint features in the time and frequency domain using time-frequency analysis, and are used as the voltage harmonics and the current harmonics.

3. The control method according to claim 1, characterized in that, Determining whether the power grid system is faulty based on the changes in current amplitude in the power characteristics includes: Transform the change of current amplitude over time in the electrical characteristics from the two-dimensional coordinate system to the dq coordinate system; The d-axis fluctuation amplitude of the current amplitude in the dq coordinate system is compared with a preset abnormal current value to determine whether the d-axis fluctuation amplitude is abnormal; and the relative deviation between the d-axis fluctuation amplitude and the q-axis fluctuation amplitude of the current amplitude in the dq coordinate system is calculated. When the d-axis fluctuation amplitude is abnormal and the relative deviation is higher than the preset deviation value, the power grid system is determined to be faulty.

4. The control method according to claim 1, characterized in that, Determining whether the power grid system is faulty based on the magnitudes of the positive-sequence and negative-sequence voltages in the power characteristics includes: The positive sequence voltage is compared with a preset positive sequence voltage threshold to determine whether the voltage drops abnormally. The negative sequence voltage is compared with a preset negative sequence voltage threshold to determine whether an asymmetrical fault has occurred in the power grid system. When the voltage drops abnormally, or when an asymmetrical fault occurs in the power grid system, the power grid system fault is determined.

5. The control method according to claim 1, characterized in that, Based on the proportions of voltage and current harmonics in the power characteristics, determine whether the power grid system is faulty, including: When the proportion of voltage harmonics in voltage and the proportion of current harmonics in current both exceed the harmonic proportion threshold, the power grid fault is determined.

6. The control method according to claim 1, characterized in that, The calculation of the dynamic virtual impedance based on the harmonic response current during a power grid system fault includes: When the power grid system is faulty, obtain the equivalent resistance value, equivalent inductance value, and harmonic angular velocity of the virtual impedance of the power grid system; The faults in the power grid system are calculated based on the equivalent resistance value, equivalent inductance value, and harmonic angular velocity.

7. The control method according to any one of claims 1 to 6, characterized in that, The process of obtaining the adaptive virtual impedance by combining the normal virtual impedance and the dynamic virtual impedance includes: The first linear combination coefficient of the normal virtual impedance and the second linear combination coefficient of the dynamic virtual impedance are dynamically adjusted using a fuzzy logic algorithm. The adaptive virtual impedance is obtained by weighting the normal virtual impedance and the dynamic virtual impedance using the first linear combination coefficient and the second linear combination coefficient.

8. A dynamic control system for virtual impedance in a power grid system, characterized in that, The control system includes: The data acquisition module is used to acquire the power characteristics of electronic devices in the power grid system; The fault diagnosis module is used to determine whether the power grid system is faulty based on the proportion of voltage harmonics and current harmonics, the change in current amplitude, and / or the magnitude of positive-sequence voltage and negative-sequence voltage in the power characteristics. The virtual impedance calculation module is used to calculate the normal virtual impedance of the power grid system during normal operation when the power grid system is faulty, and to calculate the dynamic virtual impedance based on the response current of the harmonics when the power grid system is faulty. An adaptive control module is used to synthesize the normal virtual impedance and the dynamic virtual impedance to obtain an adaptive virtual impedance, and to control the power grid system to switch the virtual impedance to the adaptive virtual impedance.

9. An electronic device, characterized in that, include: processor; as well as A memory storing computer-executable instructions, which, when executed, cause the processor to perform the method according to any one of claims 1-7.

10. A computer storage medium, characterized in that, in, The computer storage medium stores one or more programs that, when executed by a processor, implement the method of any one of claims 1-7.

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