Method for configuration and evaluation of ac-dc distribution system network architecture considering configuration possibilities

Abstract

The application discloses a method for AC-DC power distribution system network configuration and evaluation considering configuration possibility, relates to the technical field of power system operation and planning, and comprises the following steps: obtaining the node short-circuit ratio of each converter, and constructing a dynamic short-circuit ratio sequence based on the short-circuit ratio; establishing an initial equivalent parameter set of virtual impedance parameters of the converter, and taking the virtual impedance parameters as fixed reference values; constructing a nonlinear mapping relationship between the dynamic short-circuit ratio sequence and the virtual impedance, and correcting the virtual impedance according to the nonlinear mapping relationship to obtain dynamic equivalent parameters changing with the short-circuit ratio; and performing stability evaluation on the AC-DC power distribution system based on the dynamic equivalent parameters, and outputting an evaluation result; and the application solves the problem that the existing network configuration and evaluation method ignores the coupling relationship between the SCR and the virtual impedance, thereby causing insufficient stability evaluation precision.

Description

Technical Field

[0001] This invention relates to the field of power system operation and planning technology, and more specifically, to a method for configuring and evaluating AC / DC power distribution network considering configuration possibilities. Background Technology

[0002] With the large-scale integration of distributed renewable energy sources and the development of AC / DC hybrid distribution systems, the penetration rate of power electronic equipment in distribution networks is continuously increasing. To enhance system flexibility and renewable energy absorption capacity, voltage source converters (VSCs) are widely used in photovoltaic, energy storage, and flexible DC interfaces, and are gradually becoming a key component of AC / DC distribution systems.

[0003] In existing technologies, to simplify the planning and evaluation process of AC / DC distribution networks, converters are typically represented as equivalent static node models. For example, on the AC side, they are equivalent to PQ or PV nodes, and on the DC side, they are equivalent to constant power or constant voltage nodes. Power flow calculations and network optimization are then performed based on this equivalent model. Furthermore, when considering converter control characteristics, fixed virtual impedance or fixed droop coefficient parameters are often used to simplify their dynamic behavior, and system stability analysis and configuration scheme evaluation are conducted accordingly.

[0004] However, under weak grid conditions with a high proportion of power electronics, the system short-circuit ratio (SCR) decreases significantly, and the grid strength changes. At this time, key parameters of the converter, such as virtual impedance and droop control, will exhibit obvious dynamic adjustment characteristics as the SCR changes. Existing methods usually ignore this dynamic mapping relationship and still use fixed parameters for equivalent modeling.

[0005] This simplification process leads to distortion of the converter equivalent node model under weak grid conditions, making it impossible for the grid structure and capacity configuration scheme obtained in the planning stage to accurately reflect the dynamic stability characteristics in actual operation. This results in inconsistency between the planning results and the actual operating state, affecting the accuracy of system stability assessment and engineering applicability. Summary of the Invention

[0006] To overcome the aforementioned deficiencies of the prior art, embodiments of the present invention provide a method for configuring and evaluating AC / DC power distribution system grids that considers configuration possibilities. By introducing changes in the grid short-circuit ratio into the dynamic construction process of converter equivalent parameters, the method solves the problem of insufficient accuracy in stability evaluation caused by neglecting the coupling relationship between SCR and virtual impedance in existing grid configuration and evaluation methods.

[0007] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, this application provides a method for configuring and evaluating an AC / DC power distribution system network that considers configuration possibilities. The method includes: obtaining the node short-circuit ratio of each converter and constructing a dynamic short-circuit ratio sequence based on the short-circuit ratio; establishing an initial equivalent parameter set of virtual impedance parameters for the converters and using the virtual impedance parameters as fixed reference values; constructing a nonlinear mapping relationship between the dynamic short-circuit ratio sequence and the virtual impedance, and correcting the virtual impedance according to the nonlinear mapping relationship to obtain dynamic equivalent parameters that vary with the short-circuit ratio; performing a stability evaluation of the AC / DC power distribution system based on the dynamic equivalent parameters, and outputting the evaluation results.

[0008] In one embodiment, obtaining the node short-circuit ratio of each converter includes: collecting the voltage and current of each access node, calculating the short-circuit capacity of the node, and obtaining the short-circuit ratio based on the ratio of the short-circuit capacity to the equivalent capacity of the converter.

[0009] In one embodiment, constructing a dynamic short-circuit ratio sequence based on the short-circuit ratio includes: continuously sampling the short-circuit ratio of each access node to obtain short-circuit ratio time-series data; aligning the short-circuit ratio time-series data in time and dividing it into multiple data sub-series according to time windows; determining continuity based on the statistical characteristic differences of data sub-series in adjacent time windows, splicing data sub-series that meet the continuity condition, and correcting and updating data sub-series that do not meet the continuity condition; and reconstructing the corrected and updated data sub-series in time order to generate a dynamic short-circuit ratio sequence.

[0010] In one embodiment, the data subsequence that does not meet the continuity condition is corrected and updated, including: acquiring the real-time topology operation status of the AC / DC power distribution system and calculating the Thevenin equivalent impedance of the target converter access node; acquiring the operation control status information of the converter and correcting the Thevenin equivalent impedance to obtain the corrected equivalent impedance; recalculating the node short-circuit capacity based on the corrected equivalent impedance to obtain the corrected short-circuit ratio and replacing the original short-circuit ratio data in the corresponding time window to complete the update of the data subsequence.

[0011] In one embodiment, an initial equivalent parameter set of virtual impedance parameters of the converter is established, and the virtual impedance parameters are used as fixed reference values. This includes: according to the operating parameters and control strategy type of the converter, the converter is equivalent to a virtual impedance structure containing resistive and reactive components at the grid connection point, and the virtual impedance parameters are initially calibrated to form an initial equivalent parameter set; the initial equivalent parameter set is then locked as a fixed reference parameter.

[0012] In one embodiment, a nonlinear mapping relationship is constructed between the dynamic short-circuit ratio sequence and the virtual impedance, and the virtual impedance is corrected based on the nonlinear mapping relationship. This includes: normalizing the dynamic short-circuit ratio sequence to obtain a standardized short-circuit ratio sequence; establishing a nonlinear mapping function between the standardized short-circuit ratio sequence and the virtual impedance adjustment coefficient that satisfies a monotonically inverse proportional relationship constraint, and calculating the corresponding virtual impedance adjustment coefficient based on the standardized short-circuit ratio sequence; dynamically correcting the initial virtual impedance based on the virtual impedance adjustment coefficient to obtain a time-varying virtual impedance, and updating the converter equivalent parameter set to obtain dynamic equivalent parameters.

[0013] In one embodiment, updating the converter equivalent parameter set includes: decomposing the time-varying virtual impedance into a resistive virtual impedance component and a reactive virtual impedance component; in a current-controlled converter, superimposing the resistive virtual impedance component onto the current control loop, and superimposing the reactive virtual impedance component onto the dq-axis decoupling compensation channel; in a voltage-controlled converter, calculating the virtual voltage drop based on the time-varying virtual impedance, and superimposing the virtual voltage drop onto the voltage reference value; and adjusting the virtual impedance adjustment coefficient according to the short-circuit ratio so that the converter output equivalent impedance adaptively adjusts with the change of the short-circuit ratio.

[0014] In one embodiment, updating the converter equivalent parameter set to obtain dynamic equivalent parameters further includes: obtaining the time-varying virtual impedance after feedback correction by the current control loop or voltage control loop, and extracting its equivalent resistance parameter, equivalent reactance parameter, and equivalent damping coefficient; calculating the correction amount of the equivalent resistance parameter, equivalent reactance parameter, and equivalent damping coefficient according to the current short-circuit ratio and the rate of change of the time-varying virtual impedance; and superimposing each of the correction amounts onto each initial parameter in the initial equivalent parameter set to generate the updated dynamic equivalent parameter set.

[0015] In one embodiment, the stability assessment of the AC / DC power distribution system is performed based on dynamic equivalent parameters, and the assessment results are output. This includes: unifying the equivalent parameters of each converter node based on the dynamic equivalent parameter set, and calculating the system stability index; determining the stable state of the system at different operating times based on the stability index, and marking weak nodes and weak lines; based on the distribution of weak nodes and weak lines, combined with the changing trend of dynamic equivalent parameters, performing spatial location and temporal evolution analysis of system stability risks to form a stability risk distribution sequence; and generating and outputting the stability evaluation results based on the stability risk distribution sequence.

[0016] In one embodiment, spatial location and temporal evolution analysis are performed on system stability risks to form a stability risk distribution sequence. This includes: extracting the time series of dynamic equivalent parameters of weak nodes and weak lines, determining the electrical coupling relationship between nodes based on topological connections, and grouping nodes with coupling relationships into risk association units; constructing stability risk intensity indicators within each risk association unit, and performing spatial location analysis and temporal evolution analysis; and fusing the spatial location results with the temporal evolution results to form a stability risk distribution sequence.

[0017] As can be seen from the above technical solutions, the embodiments of this application have the following advantages: Taking the changes in grid strength caused by dynamic variations in the short-circuit ratio as a starting point, this study constructs a dynamic short-circuit ratio sequence to reflect the characteristics of strong and weak grids in AC / DC distribution systems under different operating conditions in real time. Based on this, a dynamic correction mechanism is introduced using virtual impedance with traditional fixed parameters to establish a nonlinear mapping relationship between the short-circuit ratio and the virtual impedance. This allows the equivalent parameters of the converter to adaptively adjust with changes in grid strength, overcoming the problems of distortion in the equivalent node model and deviation of stability assessment results from actual operating conditions caused by using fixed virtual impedance parameters in existing grid planning and evaluation methods. Furthermore, by using the corrected dynamic equivalent parameters to conduct stability assessments of AC / DC distribution systems, the dynamic coupling relationship between the converter and the grid, as well as the system's stable operating capability under different short-circuit ratio conditions, can be more accurately characterized. This improves the consistency between stability assessment results and actual operating conditions, providing a more reliable technical basis for optimizing the grid structure of AC / DC distribution systems, formulating distributed power access schemes, and making energy storage configuration decisions. Ultimately, this enhances the rationality and operational safety of distribution system planning and configuration in scenarios with a high proportion of renewable energy access. Attached Figure Description

[0018] 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 only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the AC / DC power distribution system grid configuration and evaluation method considering configuration possibilities, provided in an embodiment of this application.

[0020] Figure 2 This is a schematic diagram of the dynamic short-circuit ratio sequence generation result provided in an embodiment of this application.

[0021] Figure 3 The dynamic equivalent parameter change curves provided in the embodiments of this application. Detailed Implementation

[0022] To enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] Reference Figure 1 As shown in the schematic diagram, the AC / DC power distribution system grid configuration and evaluation method considering configuration possibilities provided by the present invention includes the following steps: S1 acquires the electrical operation data of each converter in the AC / DC power distribution system and the node short-circuit ratio (SCR).

[0024] In this embodiment, the electrical operation data and node short-circuit ratio of each converter in the AC / DC power distribution system are obtained, including: The topological connection relationship of the AC / DC power distribution system is obtained based on the power distribution automation system or PMU measurement device, and the access node position of each converter in the AC bus or DC bus is determined. Based on the location of the access node, electrical quantities are collected for each converter. The electrical quantities include at least node voltage, phase angle, output current, active power and reactive power. Based on the measured values ​​of node voltage and current, the short-circuit capacity of each access node is obtained through the equivalent short-circuit capacity calculation method. The short-circuit capacity is calculated using the following formula:

[0025] In the formula, Let i be the short-circuit capacity. Let i be the voltage reference value at node i. Let be the short-circuit current at node i.

[0026] The short-circuit ratio is calculated based on the short-circuit capacity and the equivalent operating power level of the corresponding node. The short-circuit ratio is obtained by the ratio of the short-circuit capacity to the equivalent capacity of the converter, and a set of short-circuit ratio parameters corresponding to each converter is formed. The electrical quantities and the short-circuit ratio parameter are timestamped and abnormal sampling points are removed by a sliding time window to obtain a unified time-series running dataset for dynamic analysis.

[0027] For example, statistical consistency analysis is performed on the collected time series data within a sliding time window to calculate the deviation between the current sampling point and the mean of the samples within the time window. When the deviation exceeds a set threshold, the sampling point is identified as an abnormal sampling point and removed to obtain a continuous and consistent time series data sequence.

[0028] S2, Based on the short-circuit ratio, construct a dynamic short-circuit ratio sequence that reflects changes in grid strength.

[0029] In this embodiment, a dynamic short-circuit ratio sequence reflecting changes in grid strength is constructed based on the short-circuit ratio, including: Based on the short-circuit ratio parameter set of each access node, the short-circuit ratio is continuously sampled according to a preset sampling period to obtain short-circuit ratio time-series data. The short-circuit ratio timing data is time-aligned so that the short-circuit ratio data of different converter nodes are expressed synchronously under a unified time base. Based on the aligned short-circuit ratio time-series data, the data is segmented within a preset sliding time window to form multiple short-circuit ratio data subsequences within consecutive time windows. Statistical features are extracted from the short-circuit ratio data subsequence within each time window. The statistical features include at least the mean, variance, and rate of change, in order to characterize the fluctuation characteristics of the power grid intensity within the local time window. Based on the statistical characteristics of adjacent time windows, a characteristic change metric is calculated between adjacent time windows. The characteristic change metric is used to characterize the magnitude of change in power grid intensity within adjacent time periods, and the continuity between windows is determined based on the characteristic change metric. The specific formula for calculating the feature change metric is as follows:

[0030] In the formula, This is a measure of characteristic change. It is the average of all short-circuit ratio samples within the i-th time window. It is the average of all short-circuit ratio samples within the (i+1)th time window. The degree of dispersion of the short-circuit ratio data within the i-th time window. The degree of dispersion of the short-circuit ratio data within the (i+1)th time window. This represents the average trend of the short-circuit ratio over time within the i-th time window. This represents the average trend of the short-circuit ratio over time within the (i+1)th time window. , , These are the corresponding weighting coefficients.

[0031] Optionally, the weighting coefficients are allocated proportionally based on the proportion of normalized variance of each feature in the historical data, and by satisfying... The final value is obtained by linear normalization.

[0032] When the feature change metric is less than or equal to a preset change threshold, it is determined that the continuity condition is met between adjacent time windows, and the corresponding SCR data subsequences are directly connected. The specific calculation formula for the preset change threshold is as follows:

[0033] In the formula, To preset the change threshold, These are preset coefficients.

[0034] When the characteristic change metric value is greater than the preset change threshold, it is determined that the continuity condition is not met, and the short-circuit ratio data subsequence is updated using a correction method based on grid topology reconstruction and control state coupling. Based on the SCR data subsequences that have been connected or updated, they are reconstructed and updated in chronological order to generate a dynamic short-circuit ratio sequence that evolves continuously over time, in order to characterize the time-varying process of the grid strength of the AC / DC distribution system.

[0035] Furthermore, the short-circuit ratio data subsequence is updated using a correction method based on grid topology reconfiguration and control state coupling, including: Obtain the real-time topology operating status of the AC / DC power distribution system, and construct the node admittance matrix based on the topology operating status; Based on the node admittance matrix, the target converter access node is simplified into an equivalent network, and the Thevenin equivalent impedance of the node is calculated. The Thevenin equivalent impedance is calculated using the following formula:

[0036] In the formula, This is the Thevenin equivalent impedance. The target node's self-admittance. , For the mutual admittance between the node and the rest of the system. For the remaining network admittance matrices.

[0037] The converter operation control status information is obtained, and the equivalent impedance is corrected according to the control status to obtain the corrected equivalent impedance. The control status information includes the grid-following type GFL, the grid-connected type GFM, and the current limiting control status. The specific calculation formula for the corrected equivalent impedance is as follows:

[0038]

[0039] In the formula, This is the corrected equivalent impedance. This is the control state correction factor. To track the percentage of GFL (Global Field Network) operations, The percentage of network-mode (GFM) operations. The intensity index of the current limiting state (0~1). , , These are preset empirical coefficients.

[0040] The node short-circuit capacity is recalculated based on the corrected equivalent impedance, and the corrected short-circuit ratio at the corresponding time is further calculated. The specific formula for recalculating the node short-circuit capacity is as follows:

[0041] In the formula, This is the corrected short-circuit capacity.

[0042] The short-circuit ratio data subsequence within the corresponding time window is updated based on the corrected short-circuit ratio.

[0043] To verify the ability of the constructed dynamic short-circuit ratio sequence to characterize the changes in grid strength, this embodiment selects a typical scenario of fluctuating new energy access for simulation analysis, and statistically obtains the dynamic evolution results of SCR over time, such as... Figure 2 As shown.

[0044] Figure 2 This diagram illustrates the dynamic short-circuit ratio sequence generation results, where the horizontal axis represents operating time and the vertical axis represents the node short-circuit ratio (SCR). The first segment of the curve corresponds to the normal operating state, the middle segment corresponds to the distributed power source fluctuation access and local topology switching process, and the last segment corresponds to the operating stage after control state adjustment. Figure 2 It is evident that the SCR exhibits a significant transition when the power grid topology changes. After topology reconstruction and control state coupling correction, the dynamic short-circuit ratio sequence can continuously reflect the power grid strength evolution process, avoiding unreasonable abrupt changes caused by traditional statistical splicing methods.

[0045] It should be noted that by constructing a time series analysis framework based on the short-circuit ratio and introducing a feature extraction and continuity discrimination mechanism using a sliding time window, the dynamic characterization of grid strength changes is achieved. Furthermore, when the sequence does not meet the continuity condition, an equivalent impedance correction method based on the coupling of grid topology reconfiguration and converter control state is introduced, transforming the short-circuit ratio from a purely statistical sequence into a physically consistent sequence driven by both grid structure and control behavior. This effectively avoids the equivalent distortion problem caused by neglecting topology changes and control effects in traditional methods, improves the accuracy and dynamic adaptability of grid strength assessment under weak grid conditions, and enhances the engineering reliability of AC / DC distribution system grid planning and stability analysis results.

[0046] S3. Establish an initial equivalent parameter set for the virtual impedance parameters of the converter, and use the virtual impedance parameters as fixed reference values.

[0047] In this example, an initial equivalent parameter set for the virtual impedance parameters of the converter is established, and the virtual impedance parameters are used as fixed reference values, including: Obtain the operating parameters of each converter in the AC / DC power distribution system. The operating parameters include at least the converter's rated capacity, output voltage level, grid connection point short-circuit ratio, and equivalent control bandwidth. Based on the operating parameters, the output characteristics of the converter are characterized by equivalent impedance, and the converter at the grid connection point is equivalent to a virtual impedance structure composed of resistive and reactive components. The initial structure parameters of the virtual impedance are determined according to the converter control strategy type, wherein the control strategy type includes at least the grid-following control strategy GFL and the grid-forming control strategy GFM, and each corresponds to a different initial impedance composition ratio. The virtual impedance corresponding to the mesh control strategy GFL is expressed as follows:

[0048] The virtual impedance expression for the network-based control strategy GFM is as follows:

[0049] In the formula, To correspond with the virtual impedance of the GFL mesh control strategy, The virtual impedance corresponding to the network-type control strategy GFM. This is the virtual impedance scaling factor (empirical or calibrated value) under GFL control. This is the proportional gain under GFM control. As the reference impedance, This refers to the control bandwidth of the converter.

[0050] Based on the control strategy type and the short-circuit ratio range at the grid connection point, the virtual impedance parameters are initially calibrated to form an initial equivalent parameter set containing the resistive virtual impedance component and the reactive virtual impedance component. The initial calibration is calculated using the following formula:

[0051] In the formula, This is the initial virtual impedance after initial calibration. This is the virtual impedance (calculated by GFL or GFM) that has not been initially calibrated. This refers to the short-circuit ratio at the grid connection point.

[0052] The initial equivalent parameter set is locked as a fixed reference parameter across the entire time scale, so that the virtual impedance parameter remains constant before dynamic correction, and is used for parameter mapping and dynamic adjustment under subsequent SCR variation conditions.

[0053] It should be noted that by introducing a virtual impedance normalization modeling method based on basic electrical parameters such as rated capacity and voltage, and combining the control strategy type and short-circuit ratio for initial calibration, the dynamic control behavior of the converter is uniformly equivalent to a fixed set of virtual impedance parameters with a clear physical source. This provides a stable and consistent reference benchmark for subsequent nonlinear mapping based on changes in the short-circuit ratio, and effectively avoids the problems of instability of the equivalent model and inconsistent analysis results caused by the fluctuation of virtual impedance with operating conditions in traditional methods.

[0054] S4. Construct a nonlinear mapping relationship between the dynamic short-circuit ratio sequence and the virtual impedance, and adaptively correct the virtual impedance parameters of the converter based on the nonlinear mapping relationship to obtain the dynamic equivalent parameters of the converter that vary with the short-circuit ratio.

[0055] In this embodiment, a nonlinear mapping relationship between the dynamic short-circuit ratio sequence and the virtual impedance is constructed, and the virtual impedance parameters of the converter are adaptively corrected based on the nonlinear mapping relationship to obtain the dynamic equivalent parameters of the converter that vary with the short-circuit ratio, including: Obtain the dynamic short-circuit ratio sequence generated in step S2, and normalize the dynamic short-circuit ratio sequence to obtain a standardized short-circuit ratio sequence, wherein the normalization method is based on a linear mapping between a preset maximum short-circuit ratio and a minimum short-circuit ratio. The standardized short-circuit ratio sequence is calculated using the following formula:

[0056] In the formula, For the standardized short-circuit ratio sequence, This is a dynamic short-circuit ratio sequence. , These are the preset maximum short-circuit ratio and minimum short-circuit ratio, respectively.

[0057] Based on the initial virtual impedance obtained in step S3, a constraint is set that the virtual impedance and the grid strength satisfy a monotonically inverse proportional relationship, that is, the virtual impedance adjustment coefficient decreases when the standardized short-circuit ratio sequence increases, where the grid strength is characterized by the standardized short-circuit ratio sequence. A nonlinear mapping function is constructed between the standardized short-circuit ratio sequence and the virtual impedance adjustment coefficient. This nonlinear mapping function is in exponential or piecewise power function form, and is expressed as follows:

[0058] In the formula, This is the virtual impedance adjustment coefficient. b and c are preset fitting coefficients, which can be obtained by fitting historical short-circuit ratio and equivalent impedance data using the least squares method, and are used to adjust the sensitivity of virtual impedance to changes in grid strength.

[0059] Based on the virtual impedance adjustment coefficient, the initial virtual impedance is dynamically corrected to obtain the time-varying virtual impedance:

[0060] In the formula, The time-varying virtual impedance refers to the equivalent virtual impedance of the converter at time t, which characterizes the converter's equivalent constraint capability on current and voltage under different grid strength (SCR variation) conditions.

[0061] The time-varying virtual impedance is fed back to the converter current control loop or voltage control loop to adjust the converter output equivalent impedance characteristics, so that it enhances the damping support capability when the SCR decreases and reduces the damping constraint when the SCR increases. Based on the virtual impedance updated after control feedback, the equivalent parameter set of the converter is updated to obtain the dynamic equivalent parameters, realizing the closed-loop dynamic mapping relationship between virtual impedance and grid short-circuit ratio, and used for subsequent AC / DC power distribution system stability assessment and grid planning analysis.

[0062] Furthermore, the time-varying virtual impedance is fed back to the converter current control loop or voltage control loop to adjust the converter output equivalent impedance characteristics, thereby enhancing damping support when the SCR decreases and reducing damping constraints when the SCR increases. This includes: The time-varying virtual impedance is decomposed into a resistive virtual impedance component and a reactive virtual impedance component, and then converted into an equivalent impedance feedback signal. The equivalent impedance feedback signal is used to construct an additional damping channel for the converter control loop. In a current-controlled converter, the virtual impedance component of the resistor is superimposed on the output of the current proportional controller as a series virtual resistor, and the virtual impedance component of the reactance is superimposed on the dq-axis cross-coupling compensation channel as a decoupling compensation term, thereby correcting the current control law to: d-axis current:

[0063] q-axis current:

[0064] In the formula, , These are the corrected d-axis and q-axis current reference values. , This is the original current reference value. , The actual output d-axis and q-axis currents of the converter. This refers to the virtual impedance component of the resistor. And feedforward compensation is performed on the dq axis cross-coupling term through the reactance virtual impedance component, thereby forming an equivalent impedance feedback adjustment mechanism; In a voltage-controlled converter, the time-varying virtual impedance is converted into a voltage drop:

[0065] And add it to the voltage reference value:

[0066] In the formula, This is the virtual impedance voltage drop. For the converter output current, This is the corrected voltage reference value. Set voltage value; This results in the converter output exhibiting a dynamic equivalent output impedance characteristic that varies with the current. Based on the current or voltage output after virtual impedance feedback correction, the converter output power response satisfies the damping characteristic relationship. That is, by increasing the virtual impedance component of the resistor, the active power damping term is enhanced, and by increasing the virtual impedance component of the reactance, the reactive voltage support term is enhanced, so that the system oscillation energy decays over time. When the short-circuit ratio is lower than the preset threshold, the power grid is determined to be in a weak state. Then, by increasing the virtual impedance adjustment coefficient, the time-varying virtual impedance is increased, thereby improving the output equivalent impedance and damping level of the converter, so as to enhance the voltage support capability and system stability under weak power grid conditions. The specific calculation formula for increasing the virtual impedance adjustment coefficient is as follows:

[0067] In the formula, The virtual impedance is increased by incremental adjustment and the gain enhancement term of the nonlinear mapping function is used to achieve the upward adjustment.

[0068] When the short-circuit ratio is higher than the preset threshold, the power grid is determined to be in a strong power state. Then, by reducing the virtual impedance adjustment coefficient, the time-varying virtual impedance is reduced, thereby reducing the converter output equivalent impedance and damping level, so as to reduce the control constraints on the strong power grid and improve the dynamic response speed of the system. The specific calculation formula for reducing the virtual impedance adjustment coefficient is as follows:

[0069] In the formula, The virtual impedance is reduced by decreasing the adjustment amount and using the attenuation term of the nonlinear mapping function.

[0070] Optionally, the preset threshold can be set by statistically analyzing the distribution characteristics of the short-circuit ratio (SCR) in the historical operating data of the converter connected to the grid, and selecting the critical quantile or empirical stability boundary value that can distinguish between stable grid operation and weak grid oscillation state as the preset threshold, which can be determined in engineering through conventional data statistics.

[0071] The virtual impedance adjustment coefficient is updated in real time based on the change of short-circuit ratio, and the updated time-varying virtual impedance is fed back to the current control loop or voltage control loop, so that the converter output impedance forms a closed-loop adjustment relationship with the change of SCR, realizing high damping and high support for weak grids and low damping and high response for strong grids, thereby constructing a dynamic damping support mechanism that is adaptive to grid strength.

[0072] It should be noted that by decomposing the time-varying virtual impedance into resistive and reactive components and embedding them into the converter's current control loop and voltage control loop respectively, the virtual impedance is transformed from an abstract adjustment quantity into a feedback signal that can directly affect the control law, thereby constructing a closed-loop regulation mechanism based on equivalent impedance. At the same time, a dynamic adjustment coefficient driven by the short-circuit ratio is introduced, enabling the virtual impedance to adaptively increase or decrease with changes in grid strength. Under weak grid conditions, it automatically increases resistance and reactance support to enhance damping and voltage stability, and under strong grid conditions, it automatically decreases impedance to improve dynamic response speed. This achieves dynamic adjustability of the converter's output characteristics and enhanced grid adaptability, significantly improving the stability and robustness of the AC / DC distribution system in scenarios with a high proportion of renewable energy access.

[0073] Furthermore, based on the virtual impedance update of the converter after control feedback, the dynamic equivalent parameters are obtained, including: Obtain the time-varying virtual impedance after feedback correction by the current control loop or voltage control loop, and use it as the input reference quantity for updating the equivalent parameters of the converter; Based on the time-varying virtual impedance, its electrical parameters are decomposed to obtain the converter's equivalent resistance parameters (used to characterize active power dissipation characteristics), equivalent reactance parameters (used to characterize reactive power support characteristics), and equivalent damping coefficient (used to characterize the system's oscillation attenuation capability). Based on the short-circuit ratio and the rate of change of virtual impedance after control feedback, the equivalent parameters are dynamically corrected to obtain the parameter update amount, specifically including: The short-circuit ratio and the rate of change of virtual impedance are normalized separately (maximum-minimum normalization method), and the driving factor is updated based on the normalization results to construct equivalent parameters.

[0074] In the formula, The driving factor for updating equivalent parameters is a comprehensive influence quantity composed of changes in grid strength and control dynamic disturbances. The normalized short-circuit ratio, This represents the normalized rate of change of virtual impedance. , These are the weighting parameters used to adjust the influence of the short-circuit ratio on the system and the influence of the virtual impedance change rate, respectively.

[0075] Based on the driving factor, the equivalent parameter update amounts are structured and smoothed to obtain the parameter update amounts: Specifically, the structured allocation of the equivalent parameter update amount is as follows:

[0076]

[0077]

[0078] In the formula, This is the update amount of the equivalent resistance. This is the equivalent reactance replacement amount. This is the update amount of the equivalent damping coefficient. , , These are the preset mapping coefficients.

[0079] The parameter update amount is added to the initial equivalent parameter set to obtain the dynamic equivalent parameter set.

[0080] To verify the adaptive adjustment capability of the dynamic equivalent parameters, this embodiment statistically analyzed the changes in equivalent resistance, equivalent reactance, and equivalent damping coefficient during a typical operating cycle. The results are as follows: Figure 3 As shown.

[0081] Figure 3This indicates that during the SCR reduction phase, the equivalent resistance and equivalent damping coefficient increase synchronously to improve the system damping level; during the SCR recovery phase, the parameters gradually return to the stable range, demonstrating that the proposed dynamic parameter update mechanism can achieve adaptive adjustment according to changes in grid strength.

[0082] It should be noted that by introducing an equivalent parameter update mechanism based on control feedback virtual impedance, the converter operating state is normalized and integrated with the grid short-circuit ratio and dynamic disturbance characteristics for modeling. A driving factor is constructed to achieve coordinated adjustment of equivalent resistance, equivalent reactance and equivalent damping coefficient. This transforms the traditional static equivalent parameters into a dynamic parameter set that evolves in real time with the grid strength and control state, thereby significantly improving the modeling accuracy and stability assessment consistency of AC / DC distribution systems under weak grid and high-proportion renewable energy access conditions.

[0083] S5. The stability of the AC / DC power distribution system is evaluated based on the dynamic equivalent parameters, and the stability evaluation results are output for grid configuration and planning optimization.

[0084] In this embodiment, the stability of the AC / DC power distribution system is evaluated based on the dynamic equivalent parameters, and stability evaluation results are output for grid configuration and planning optimization, including: Obtain the set of dynamic equivalent parameters obtained in step S4, and use it as the basic parameter set for stability assessment of AC / DC power distribution system; Based on the dynamic equivalent parameter set, the equivalent parameters of each converter node in the AC / DC power distribution system are uniformly expressed, so that each node participates in the system stability assessment in the form of a combination of equivalent resistance, equivalent reactance and equivalent damping coefficient during the calculation process. The line impedance parameters and node equivalent parameters are uniformly standardized to form a time-varying and consistent expression of node electrical characteristics. Based on the consistent expression results, the system stability is calculated using multiple indices, including oscillation stability index, which characterizes the system's recovery capability after disturbance, damping level index, and voltage stability index. The oscillation stability index is obtained by statistically analyzing the amplitude of the power change rate to obtain the average power change intensity within each time window. Based on the average power change intensity, a power change rate attenuation coefficient between adjacent time windows is constructed, and the oscillation stability index is defined based on the attenuation coefficient. The specific calculation formula is as follows:

[0085]

[0086] In the formula, As an oscillation stability indicator, The attenuation coefficient is... To prevent extremely small positive numbers with a denominator of zero, Let be the average power change intensity within the i-th time window. The average power change intensity within the (i+1)th time window.

[0087] The damping level index is characterized by the ratio of the equivalent resistance parameter to the power fluctuation amplitude, and the voltage stability index is determined by the ratio of the node voltage offset to the preset allowable voltage range.

[0088] Based on the stability index, the stability state of the AC / DC power distribution system at different operating times t is determined. When the damping level index is lower than the preset damping level threshold or the voltage stability index exceeds the allowable range, the system is determined to be in a weakly stable or unstable operating state, and the corresponding weak nodes and weak lines are marked. The preset damping level threshold is obtained by sorting the statistical distribution of damping level indicators in historical operating data and selecting an empirical quantile or engineering operating limit that can distinguish between normal stable operating state and oscillating instability state as the default value; the allowable range is directly set according to the voltage deviation allowable standard in the power grid operation procedure or the statistical maximum offset range of historical node voltage fluctuations, and a fixed percentage range of rated voltage is used as the general engineering constraint range.

[0089] Based on the distribution results of the weak nodes and weak lines, and combined with the changing trend of dynamic equivalent parameters, spatial positioning and temporal evolution analysis of system stability risks are performed to form a stability risk distribution sequence, which is used to characterize the stability change law of the system under different SCR conditions and operating conditions. Based on the stability risk distribution sequence, the overall stability evaluation index of the system is calculated, and a comparative analysis is conducted on different grid structure schemes to obtain the stability ranking of each grid scheme. The stability evaluation index is calculated using the following formula:

[0090] in:

[0091] In the formula, The system overall stability evaluation index at time t is used to characterize the overall stability level of the AC / DC power distribution system. Let L be the weight coefficient corresponding to the i-th risk-related unit, and L be the total number of risk-related units in the system. Let be the stability risk intensity index corresponding to the i-th risk-related unit at time t.

[0092] The specific calculation formula for the weight coefficient corresponding to the risk association unit is as follows:

[0093] In the formula, This is the sum of the number of nodes and the number of lines contained in the i-th risk association unit. This represents the total number of nodes and lines contained in all risk-related units.

[0094] The stability evaluation results are output to the grid configuration and planning optimization module, which serves as a constraint or objective function input for grid topology adjustment, distributed power source access location optimization, and energy storage configuration scheme selection, thereby realizing AC / DC power distribution system planning optimization based on dynamic stability.

[0095] Furthermore, based on the distribution results of the weak nodes and weak lines, and combined with the changing trends of dynamic equivalent parameters, spatial location and temporal evolution analysis of system stability risks are performed to form a stability risk distribution sequence, including: Obtain the output set of weak nodes and set of weak lines, and extract the time series of dynamic equivalent parameters of the corresponding nodes, including equivalent resistance parameters, equivalent reactance parameters and equivalent damping coefficients, as the basic input data for risk analysis; Based on the topological connection relationship between the weak nodes and weak lines, the electrical coupling strength between the nodes is calculated. This electrical coupling strength is determined by the normalized mutual admittance of the equivalent impedance between the nodes, specifically:

[0096] In the formula, Let be the electrical coupling strength between node i and node j at time t, used to characterize the relative strength of the electrical mutual influence between the two nodes. Let be the mutual admittance between node i and node j, representing the coupling transmission capability between nodes through network topology and line impedance. Let be the self-admittance of node i, representing node i's equivalent electrical access capability to the external network or its own equivalent admittance characteristic. Let be the self-admittance of node j, representing node j's equivalent electrical access capability to the external network.

[0097] When the electrical coupling strength is greater than the preset coupling threshold, it is determined that node i and node j have a strong electrical coupling relationship and are grouped into the same risk-associated unit. The preset coupling threshold is determined by statistically sorting the electrical coupling strength of all nodes under historical operating conditions and selecting a fixed quantile (such as the upper quantile or the value corresponding to the mean doubled standard deviation) within the stable interval of engineering experience as the threshold.

[0098] Within each risk association unit, the parameter change trend characteristics are calculated based on the dynamic equivalent parameter time series, including the parameter change rate and fluctuation amplitude. The change rate is obtained by the difference between adjacent time points, and the fluctuation amplitude is characterized by the standard deviation within the sliding time window. Based on the aforementioned parameter change trend characteristics, a stability risk intensity index is constructed, specifically as follows:

[0099] In the formula, This is a stability risk intensity index for the system at time t, used to characterize the degree of stability degradation of the AC / DC power distribution system. This is the equivalent damping coefficient. The standard deviation of the equivalent impedance fluctuation within a time window is used to characterize the degree of network impedance instability. The voltage change rate is used to characterize the dynamic fluctuation speed of node voltage. , , These are the weighting coefficients.

[0100] The weighting coefficients are determined by normalizing each risk component (damping change, impedance fluctuation, and voltage change) in the historical operating data, allocating them proportionally according to their average contribution to the stability index in the historical samples, and then performing another linear normalization to make the sum of the three equal to 1. This can be directly determined by those skilled in the art based on conventional statistical analysis.

[0101] Based on the spatial distribution of the stability risk intensity, each risk-related unit is sorted, and high-risk areas are identified according to the degree to which they exceed a preset risk threshold, thereby obtaining the spatial hotspot distribution structure of system stability risk. The preset risk threshold is determined by statistically sorting the stability risk intensity RI(t) in historical operating data and selecting the RI(t) value corresponding to the quantile that minimizes the system's misjudgment rate within the safe operating range of the project as the threshold.

[0102] Based on the time dimension, the stability risk intensity of each risk-related unit is statistically processed by a sliding window to obtain a time-smoothed risk sequence. The sliding window uses a fixed-length time interval for mean filtering to weaken the impact of instantaneous disturbances. The spatial hotspot distribution structure is fused and mapped with the time-smoothed risk sequence to form a stable risk distribution sequence, which is used to characterize the spatial risk distribution and temporal evolution characteristics of AC / DC power distribution systems under different short-circuit ratio changes.

[0103] It should be noted that, using dynamic equivalent parameters as a unified analytical basis, the converter control characteristics, grid strength variation characteristics, and network topology characteristics are incorporated into the same stability assessment framework. Multi-dimensional quantitative analysis of the system's operating state is achieved through oscillation stability indices, damping level indices, and voltage stability indices. Furthermore, by combining weak node identification, electrical coupling relationship analysis, and risk-related unit division mechanisms, stability risk analysis is expanded from single-point analysis to regional and hierarchical analysis. Simultaneously, by constructing stability risk intensity indices and stability risk distribution sequences, the spatial propagation characteristics and temporal evolution of risks under different short-circuit ratios and operating conditions can be dynamically characterized, avoiding the shortcomings of traditional methods that rely solely on static operating points and fail to reflect the dynamic stability characteristics of the system. In addition, by establishing a system-wide stability evaluation index, local risk information is uniformly mapped to global stability evaluation results, providing quantitative decision-making basis for grid topology adjustments, distributed power source access location optimization, and energy storage configuration scheme selection. This improves the consistency between AC / DC distribution system grid planning results and actual operational stability, enhancing the system's safety, reliability, and planning rationality in scenarios with high proportions of renewable energy access.

[0104] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0105] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0106] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0107] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for configuration and evaluation of AC / DC power distribution system network architecture considering configuration possibilities, characterized in that, include: Obtain the node short-circuit ratio of each converter, and construct a dynamic short-circuit ratio sequence based on the short-circuit ratio; Establish an initial equivalent parameter set for the virtual impedance parameters of the converter, and use the virtual impedance parameters as fixed reference values; A nonlinear mapping relationship between the dynamic short-circuit ratio sequence and the virtual impedance is constructed, and the virtual impedance is corrected according to the nonlinear mapping relationship to obtain the dynamic equivalent parameter that varies with the short-circuit ratio. The stability of AC / DC power distribution systems is evaluated based on dynamic equivalent parameters, and the evaluation results are output.

2. The method according to claim 1, characterized in that, The process of obtaining the node short-circuit ratio of each converter includes: Collect the voltage and current of each access node and calculate the short-circuit capacity of that node; The short-circuit ratio is obtained based on the ratio of the short-circuit capacity to the equivalent capacity of the converter.

3. The method according to claim 1, characterized in that, Constructing a dynamic short-circuit ratio sequence based on the short-circuit ratio includes: The short-circuit ratio of each access node is continuously sampled to obtain short-circuit ratio time-series data; The short-circuit ratio time series data is time-aligned and divided into multiple data subsequences according to time windows; The continuity is determined by the statistical characteristics of the data subsequences in adjacent time windows. Data subsequences that meet the continuity condition are spliced ​​together, and data subsequences that do not meet the continuity condition are corrected and updated. The corrected and updated data subsequences are reconstructed in chronological order to generate a dynamic short-circuit ratio sequence.

4. The method according to claim 3, characterized in that, The step of correcting and updating data subsequences that do not meet the continuity condition includes: Obtain the real-time topology operation status of the AC / DC power distribution system and calculate the Thevenin equivalent impedance of the target converter access node; Obtain the operating control status information of the converter, correct the Thevenin equivalent impedance, and obtain the corrected equivalent impedance; The node short-circuit capacity is recalculated based on the corrected equivalent impedance to obtain the corrected short-circuit ratio, and the original short-circuit ratio data in the corresponding time window is replaced to complete the update of the data subsequence.

5. The method according to claim 1, characterized in that, The process of establishing an initial equivalent parameter set for the virtual impedance parameters of the converter, and using the virtual impedance parameters as fixed reference values, includes: Based on the converter's operating parameters and control strategy type, the converter at the grid connection point is equivalent to a virtual impedance structure containing resistive and reactive components, and the virtual impedance parameters are initially calibrated to form an initial equivalent parameter set. The initial equivalent parameter set is locked as a fixed reference parameter.

6. The method according to claim 1, characterized in that, The process of constructing a nonlinear mapping relationship between the dynamic short-circuit ratio sequence and the virtual impedance, and correcting the virtual impedance based on the nonlinear mapping relationship, includes: The dynamic short-circuit ratio sequence is normalized to obtain a standardized short-circuit ratio sequence. Establish a nonlinear mapping function that satisfies the monotonically inverse proportional relationship constraint between the standardized short-circuit ratio sequence and the virtual impedance adjustment coefficient, and calculate the corresponding virtual impedance adjustment coefficient based on the standardized short-circuit ratio sequence; The initial virtual impedance is dynamically corrected based on the virtual impedance adjustment coefficient to obtain the time-varying virtual impedance, and the converter equivalent parameter set is updated to obtain the dynamic equivalent parameters.

7. The method according to claim 6, characterized in that, The updated converter equivalent parameter set includes: The time-varying virtual impedance is decomposed into a resistive virtual impedance component and a reactive virtual impedance component. In a current-controlled converter, the virtual impedance component of the resistor is superimposed on the current control loop, and the virtual impedance component of the reactance is superimposed on the dq-axis decoupling compensation channel. In a voltage-controlled converter, the virtual voltage drop is calculated based on the time-varying virtual impedance, and the virtual voltage drop is then added to the voltage reference value. The virtual impedance adjustment coefficient is adjusted according to the short-circuit ratio, so that the equivalent impedance of the converter output can be adaptively adjusted as the short-circuit ratio changes.

8. The method according to claim 7, characterized in that, The process of updating the converter equivalent parameter set to obtain dynamic equivalent parameters also includes: Obtain the time-varying virtual impedance after feedback correction by the current control loop or voltage control loop, and extract its equivalent resistance parameters, equivalent reactance parameters and equivalent damping coefficient; Based on the current short-circuit ratio and the rate of change of time-varying virtual impedance, calculate the correction amounts for the equivalent resistance parameter, equivalent reactance parameter, and equivalent damping coefficient, respectively. Each of the aforementioned corrections is superimposed on the initial parameters in the initial equivalent parameter set to generate an updated dynamic equivalent parameter set.

9. The method according to claim 1, characterized in that, The stability assessment of the AC / DC power distribution system based on dynamic equivalent parameters, and the output of the assessment results, include: Based on the dynamic equivalent parameter set, the equivalent parameters of each converter node are uniformly expressed, and the system stability index is calculated. The stability of the system at different operating times is determined based on stability indicators, and weak nodes and weak lines are marked. Based on the distribution of weak nodes and weak lines, and combined with the changing trend of dynamic equivalent parameters, spatial location and temporal evolution analysis of system stability risks are performed to form a stability risk distribution sequence. Stability evaluation results are generated and output based on the stability risk distribution sequence.

10. The method according to claim 9, characterized in that, The spatial localization and temporal evolution analysis of system stability risks, forming a stability risk distribution sequence, includes: Extract the time series of dynamic equivalent parameters of weak nodes and weak lines, and determine the electrical coupling relationship between nodes based on the topological connection relationship. Nodes with coupling relationship are grouped into risk association units. Within each risk-related unit, a stability risk intensity index is constructed, and spatial positioning analysis and temporal evolution analysis are conducted. By integrating spatial positioning results with temporal evolution results, a stability risk distribution sequence is formed.

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