Method and system for predicting stability carrying capacity of flexible dc dense feed-in receiving end power grid

Abstract

The application relates to the technical field of power system operation control, and particularly provides a flexible direct-current dense feeding receiving-end power grid stability bearing capacity prediction method and system. The method covers control parameter perturbation fluctuation range by constructing a transient voltage frequency coupling strength characteristic quantity robust calculation model, can capture the coupling instability risk under extreme working conditions, and solves the problems of optimistic evaluation result of nominal parameters and insufficient robustness. On this basis, a safety boundary envelope function corresponding to the total feeding power and the characteristic quantity safety threshold is fitted, the dynamic change of the system coupling characteristics under different power levels is adapted, and the working condition adaptation accuracy of the safety boundary is improved. In the iterative search process, the characteristic quantity corresponding to the trial power is calculated successively, compared with the safety threshold under the corresponding power, and the search interval is adjusted, so that the upper limit of the bearing capacity is solved to fit the actual operation characteristics, and finally the prediction accuracy is improved while the evaluation conservatism is ensured, which can provide reliable support for power grid operation dispatching.

Description

Technical Field

[0001] The embodiments in this specification relate to the field of power system operation and control technology, and in particular to a method and system for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid. Background Technology

[0002] With the continuous growth in demand for cross-regional consumption of new energy, flexible DC transmission technology, with its advantages of strong controllability and adaptability to weak AC systems, has been widely used in long-distance, large-capacity power transmission projects. The network configuration of multiple flexible DC lines densely fed into the same receiving-end AC grid is becoming increasingly common. In receiving-end grids with a high proportion of flexible DC feeds, the control links of multiple converter stations interact with the dynamic characteristics of the AC grid, forming complex transient voltage and frequency coupling effects. As the scale of fed active power continues to increase, the risk of interactive instability between AC and DC systems gradually becomes prominent, directly restricting the DC power acceptance capacity of the receiving-end grid. Therefore, accurately assessing the stable carrying capacity of the receiving-end grid for flexible DC feed power is an important prerequisite for ensuring the safe operation of the grid and optimizing DC power dispatch.

[0003] Currently, for the stability carrying capacity assessment of multi-infeed AC / DC systems, the industry generally adopts a technical approach that combines modeling analysis and time-domain simulation: based on the nominal control parameters of the converter station, a coupling analysis model of the AC / DC system is established to quantify the interactive coupling strength, and then the safety constraints such as transient voltage deviation and frequency offset are verified through transient simulation to delineate the feasible operating range of the system, and then the maximum feed-in power that the grid can carry is obtained.

[0004] However, in practical engineering applications, existing technologies still have significant limitations: First, coupling characteristic analysis often uses nominal control parameter values ​​as a benchmark, without considering the fluctuations and dispersion of control parameters in actual operation. This makes it difficult to cover harsh operating conditions when parameters deviate from nominal values, resulting in insufficient robustness of the evaluation results and potential instability risks being overlooked. Second, safety boundary calibration is usually based on simulation verification under fixed control parameter scenarios, without fully considering the dynamic changes in system coupling characteristics under different feed power levels. The operating condition adaptability of the safety threshold is insufficient, making it difficult to meet engineering requirements in terms of the accuracy of safety boundary assessment. Third, iterative solutions for the upper limit of carrying capacity often use a uniform safety judgment threshold, without dynamically adjusting the judgment benchmark based on the actual coupling characteristics under different power conditions. The final carrying capacity result deviates from the actual operating characteristics of the system, making it difficult to simultaneously ensure operational safety and the economy of power acceptance. Summary of the Invention

[0005] In view of this, embodiments of this specification provide a method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid. One or more embodiments of this specification also relate to a system for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid, a computing device, a computer-readable storage medium, and a computer program, to address the technical deficiencies existing in the prior art.

[0006] According to a first aspect of the embodiments of this specification, a method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid is provided, comprising: The basic data of the flexible DC dense feed into the receiving-end power grid are acquired and preprocessed to obtain a structured input dataset; A robust computational model for transient voltage-frequency coupling strength features is constructed based on a structured input dataset. Based on the robust calculation model of transient voltage frequency coupling strength characteristic, the safety boundary envelope function corresponding to the safety threshold of the characteristic is obtained by fitting within the preset total feed power search interval. An iterative search is performed within the total feed power search interval, and the transient voltage-frequency coupling strength characteristic corresponding to the test power is calculated successively; the test power is the median value of the total feed power search interval. After comparing the transient voltage frequency coupling strength characteristic with the safety threshold of the characteristic corresponding to the safety boundary envelope function, the total feed-in power search interval is adjusted. After the total feed-in power search interval converges, the upper limit of the receiving end grid stability carrying capacity is obtained. The load factor is calculated based on the current total active power and the upper limit of the stability carrying capacity of the receiving-end power grid. The state classification is determined based on the graded safety threshold and the load factor, and the corresponding stability carrying capacity prediction results are output.

[0007] In one possible implementation, a robust computational model for transient voltage-frequency coupling strength features is constructed based on a structured input dataset, including: Based on the receiving-end power grid network topology parameters and flexible DC feed point information in the structured input dataset, multi-port Thevenin equivalent processing is performed on the receiving-end AC power grid to obtain the AC power grid port admittance matrix; Based on the control mode parameters and outer loop controller coefficients of each converter station in the structured input dataset, a frequency domain impedance model of each converter station is constructed. The frequency domain impedance models of all converter stations are combined to form the diagonal impedance matrix on the converter station side. By combining the AC grid port admittance matrix and the converter station side diagonal impedance matrix, a closed-loop hysteresis matrix for a multi-infeed AC / DC system is constructed. Using the minimum singular value of the closed-loop hysteresis matrix as a quantitative indicator of the system's interactive instability risk, and combining the control parameter perturbation range of the structured input dataset to construct a global parameter optimization solution logic, a robust calculation model for transient voltage-frequency coupling strength features is formed. Among them, the robust calculation model for transient voltage-frequency coupling strength features outputs the global minimum value of the minimum singular value within the control parameter perturbation range as the transient voltage-frequency coupling strength feature, and outputs the worst interactive control scenario corresponding to the minimum value.

[0008] In one possible implementation, based on a robust calculation model of transient voltage-frequency coupling strength characteristics, a safety boundary envelope function corresponding to the total feed power and the safety threshold of the characteristic is fitted within a preset total feed power search interval, including: Set a total feed-in power search interval, and select multiple discrete power levels within the total feed-in power search interval; the lower limit of the total feed-in power search interval is the sum of the active power of each flexible DC feed-in channel; The discrete power levels are allocated according to the proportion of active power in each flexible DC feed channel, and the active power setpoint of each channel corresponding to each discrete power level is obtained. The active power setpoint of the channel is solved by a robust calculation model of transient voltage frequency coupling strength characteristics, and the worst interactive control scenario corresponding to the active power setpoint of the channel is obtained. For the worst-case interactive control scenario, a transient simulation of the receiving-end power grid is performed. Based on the preset voltage amplitude safety constraints and frequency offset safety constraints, the feasibility of discrete power levels is determined, and a set of safe and feasible points is obtained. Nonlinear regression fitting is performed on the set of safe and feasible points to obtain the safety boundary envelope function; the safety boundary envelope function is the mapping relationship between the total feed power and the safety threshold of the characteristic quantity.

[0009] In one possible implementation, discrete power levels are allocated according to the proportion of active power in each flexible DC feed channel, resulting in active power setpoints for each channel corresponding to each discrete power level, including: Obtain the current operating active power of each flexible DC feed channel; Calculate the ratio of the current operating active power of each flexible DC feed channel to the total current operating active power of all flexible DC feed channels, and obtain the power allocation weight corresponding to each channel. For each discrete power level, the total feed-in power value corresponding to the discrete power level is used as the allocation base, and multiplied by the power allocation weight to obtain the active power setting value of each flexible DC feed-in channel under the discrete power level.

[0010] In one possible implementation, an iterative search is performed within the total feed power search interval, successively calculating the transient voltage-frequency coupling strength characteristic corresponding to the trial power, including: The iterative search interval for the total feed-in power is set with the current total active power as the lower bound of the search and the sum of the rated capacities of all flexible DC converter stations as the upper bound of the search. In each iteration, the total power at the midpoint of the iteration search interval is taken as the test power. The test power is allocated to each feed channel according to the proportion of the current active power of each flexible DC converter station, so as to obtain the active power set value of each channel under the test power. The active power setpoint of each channel under the test power is input into the robust calculation model of transient voltage frequency coupling strength characteristic quantity, and the transient voltage frequency coupling strength characteristic quantity corresponding to the test power is obtained by solving.

[0011] In one possible implementation, the total feed-in power search interval is adjusted after comparing the transient voltage frequency coupling strength characteristic with the safety threshold of the characteristic corresponding to the safety boundary envelope function. Once the total feed-in power search interval converges, the upper limit of the receiving-end grid stability carrying capacity is obtained, including: Set the convergence tolerance and input the trial power of the current iteration into the safety boundary envelope function to obtain the safety threshold of the feature quantity corresponding to the trial power; The transient voltage frequency coupling strength characteristic corresponding to the test power is compared with the characteristic value safety threshold. If the transient voltage frequency coupling strength characteristic is less than or equal to the characteristic safe threshold, the test power is determined to be within a safe and feasible range, and the lower bound of the total feed-in power search interval is updated to the test power. If the transient voltage frequency coupling strength characteristic is greater than the characteristic safe threshold, the test power is determined to be out of safe range, and the upper bound of the total feed-in power search interval is updated to the test power. Repeat the process until the width of the total feed-in power search interval is less than the convergence tolerance. Output the total feed-in active power corresponding to the lower bound of the total feed-in power search interval to obtain the upper limit of the receiving-end grid stability carrying capacity.

[0012] In one possible implementation, the load factor is calculated based on the current total active power and the upper limit of the receiving-end grid's stability carrying capacity. Then, a state classification is determined based on the graded safety threshold and the load factor, and the corresponding stability carrying capacity prediction result is output, including: The total active power currently in operation is obtained by summing the current active power of each flexible DC converter station. Calculate the ratio of the current total active power to the upper limit of the stable carrying capacity of the receiving-end power grid to obtain the load factor; Extract the load factor values ​​corresponding to all safe and feasible points during the fitting process of the safety boundary envelope function, and calculate the mean and standard deviation of the load factor values; A first safety threshold and a second safety threshold are set based on the mean and standard deviation; the first safety threshold is less than the second safety threshold. The load factor is compared with the first safety threshold and the second safety threshold, and the operating safety level of the receiving-end power grid is determined based on the comparison results. Based on the determined operational safety level, output the corresponding stability carrying capacity prediction results and supporting operational decision information.

[0013] According to a second aspect of the embodiments of this specification, a flexible DC dense feed-in receiving-end power grid stability carrying capacity prediction system is provided, comprising: The data acquisition and preprocessing unit is used to acquire basic data of the flexible DC dense feed into the receiving-end power grid and preprocess it to obtain a structured input dataset; Robust computation model building unit, used to build a robust computation model of transient voltage frequency coupling strength features based on structured input dataset; The safety boundary fitting unit is used to fit the safety boundary envelope function corresponding to the total feed power and the safety threshold of the feature quantity within a preset total feed power search interval based on the robust calculation model of transient voltage frequency coupling strength feature quantity. The iterative search solution unit is used to perform iterative search within the total feed-in power search interval, calculate the transient voltage frequency coupling strength characteristic quantity corresponding to the test power one by one, compare the transient voltage frequency coupling strength characteristic quantity with the characteristic quantity safety threshold corresponding to the safety boundary envelope function, and then adjust the search interval. After the search interval converges, the upper limit of the receiving end grid stability carrying capacity is obtained. The graded assessment output unit is used to calculate the load factor based on the current total active power and the upper limit of the stability carrying capacity of the receiving-end power grid, and to make a state graded judgment based on the graded safety threshold and the load factor, and output the corresponding level of stability carrying capacity prediction results.

[0014] According to a third aspect of the embodiments of this specification, a computing device is provided, comprising: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the above-mentioned method for predicting the stable carrying capacity of the receiving-end power grid of flexible DC dense feed-in.

[0015] According to a fourth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the above-described method for predicting the stable carrying capacity of a flexible DC dense feed-in receiving-end power grid.

[0016] According to a fifth aspect of the embodiments of this specification, a computer program is provided, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the above-described method for predicting the stability carrying capacity of the receiving-end power grid of flexible DC dense feed-in.

[0017] As can be seen from the above technical solutions, this application provides a method and system for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid. The method constructs a robust calculation model of transient voltage-frequency coupling strength characteristics, covering the range of control parameter perturbation fluctuations, which can capture the coupling instability risk under extreme operating conditions and solve the problems of overly optimistic nominal parameter evaluation results and insufficient robustness. On this basis, the method fits the safety boundary envelope function corresponding to the total feed-in power and the safety threshold of the characteristics, adapting to the dynamic changes of system coupling characteristics under different power levels and improving the operating condition adaptation accuracy of the safety boundary. During the iterative search process, the characteristic quantity corresponding to the trial power is calculated one by one, and the search interval is dynamically compared with the safety threshold under the corresponding power and adjusted, so that the upper limit of carrying capacity solution fits the actual operating characteristics. Finally, while ensuring the conservatism of the evaluation, the prediction accuracy is improved, which can provide reliable support for power grid operation and dispatch. Attached Figure Description

[0018] Figure 1 This is a flowchart of a method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid, provided in one embodiment of this specification. Figure 2 This is a flowchart illustrating the construction of a robust calculation model for transient voltage frequency coupling strength characteristics provided in one embodiment of this specification; Figure 3 This is a flowchart illustrating the construction of a security boundary envelope function according to one embodiment of this specification; Figure 4 This is a flowchart illustrating the calculation of transient voltage frequency coupling strength characteristics provided in one embodiment of this specification; Figure 5 This is a flowchart illustrating the calculation of the upper limit of the stable carrying capacity of the receiving-end power grid, provided in one embodiment of this specification. Figure 6 This is a schematic diagram of the process for generating stable bearing capacity prediction results based on a safety threshold-based hierarchical assessment, provided in one embodiment of this specification. Figure 7 This is a schematic diagram of the structure of a flexible DC dense feed-in receiving-end power grid stability carrying capacity prediction system provided in one embodiment of this specification; Figure 8 This is a structural block diagram of a computing device provided in one embodiment of this specification. Detailed Implementation

[0019] Many specific details are set forth in the following description to provide a full understanding of this specification. However, this specification can be implemented in many other ways than those described herein, and those skilled in the art can make similar extensions without departing from the spirit of this specification. Therefore, this specification is not limited to the specific implementations disclosed below.

[0020] The terminology used in one or more embodiments of this specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the one or more embodiments of this specification. The singular forms “a” and “the” as used in one or more embodiments of this specification and the appended claims are also intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in one or more embodiments of this specification refers to and includes any or all possible combinations of one or more associated listed items.

[0021] It should be understood that although the terms first, second, etc., may be used to describe various information in one or more embodiments of this specification, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, first may also be referred to as second without departing from the scope of one or more embodiments of this specification, and similarly, second may also be referred to as first. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to a determination."

[0022] This specification provides a method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid. This specification also relates to a system for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid, a computing device, and a computer-readable storage medium, which will be described in detail in the following embodiments.

[0023] See Figure 1 , Figure 1 A flowchart is shown for a method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to an embodiment of this specification, which specifically includes the following steps.

[0024] Step 101: Obtain the basic data of the flexible DC dense feed into the receiving-end power grid and perform preprocessing to obtain a structured input dataset.

[0025] The basic data for obtaining flexible DC dense feed-in to the receiving-end power grid includes the network topology information of the receiving-end power grid, the rated voltage level of the AC bus at each flexible DC feed-in point, the rated capacity and current active power of each flexible DC converter station, the installed capacity and inertial time constant of each synchronous generator unit in the receiving-end power grid, the active load measurement values ​​of each load node in the receiving-end power grid, and the control mode parameters currently used by each flexible DC converter station. The control mode parameters include the active power reference value under constant active power control mode, the reactive power reference value under constant reactive power control mode, the DC voltage reference value under constant DC voltage control mode, and the AC voltage reference value under constant AC voltage control mode.

[0026] Preprocessing methods specifically include: The telemetry and teleindication point tables of each converter station control system are read from the real-time database of the receiving-end power grid energy management system, and the active power reference value under constant active power control mode is extracted. Reactive power reference value under constant reactive power control mode DC voltage reference value in constant DC voltage control mode and AC voltage reference value in constant AC voltage control mode subscript Indicates the first A flexible DC feed channel.

[0027] For converter stations currently operating in non-constant AC voltage control mode, their AC voltage reference value is... The current measured voltage value of the AC bus of the converter station is assigned to eliminate parameter gaps caused by the lack of control mode in subsequent calculations; at the same time, the outer loop proportional coefficient of each converter station is extracted from the waveform recording file of the converter station control and protection device. , , , and outer loop integral time constant , , , The perturbation range of the control parameters is constructed as a range of plus or minus 20 percent of the nominal value of each parameter. This range covers the numerical variation boundary of the parameters during the smooth switching of the control mode of the converter station. The perturbation range and the current control mode parameters of each converter station are stored together as a structured input dataset.

[0028] Step 102: Construct a robust computational model for transient voltage-frequency coupling strength features based on the structured input dataset.

[0029] Among them, the robust calculation model of transient voltage frequency coupling strength characteristic is a calculation model that takes into account the influence of control parameter perturbation and can solve the coupling characteristic under the worst working conditions within the parameter fluctuation range. The output results are conservative and robust.

[0030] For example, based on the grid topology parameters in the structured input dataset, taking each flexible DC feed point as a port, multi-port Thevenin equivalence is performed on the receiving-end AC grid to obtain the AC-side port admittance matrix; based on the control and operating parameters of each converter station, a frequency domain impedance model of each converter station is established, and the models are combined to form the diagonal impedance matrix of the converter station side; the two types of matrices are combined to construct the closed-loop hysteresis matrix of the multi-feed AC / DC system; the minimum singular value of the closed-loop hysteresis matrix is ​​used as the coupling strength quantification index, and a global parameter optimization solution logic is constructed in combination with the perturbation interval of the control parameters to form a robust calculation model of transient voltage-frequency coupling strength characteristics; the robust calculation model of transient voltage-frequency coupling strength characteristics can output the global minimum value of the minimum singular value within the perturbation interval as the coupling strength characteristic, and simultaneously output the corresponding parameter combination.

[0031] Step 103: Based on the robust calculation model of transient voltage frequency coupling strength characteristics, fit the safety boundary envelope function corresponding to the safety threshold of the total feed power and the characteristic within the preset total feed power search interval.

[0032] The total feed power search interval is used to scan the range of total feed power values ​​for solving the upper limit of stable load capacity, including the lower limit of total feed power and the upper limit of total feed power.

[0033] The characteristic quantity safety threshold corresponds to the critical value of the coupling strength characteristic quantity that satisfies the transient voltage and frequency safety constraints at a certain input power level, and is the benchmark for determining power feasibility.

[0034] The safety boundary envelope function is a fitting function that characterizes the continuous mapping relationship between the total feed power and the corresponding safety threshold, and can quickly obtain the safety threshold at any power level.

[0035] Specifically, the lower bound of the total feed-in power search interval is set as the current total active power, and the upper bound is the sum of the rated capacities of all converter stations. Within the search interval, 20 discrete power levels are selected at equal intervals. Based on the proportion of the current active power of each converter station, each discrete total power level is allocated to each feed-in channel to obtain the corresponding active power setpoint. For each discrete power level, a robust computational model is used to solve for the corresponding coupling strength characteristics and the worst-case control scenario. Under this worst-case scenario, time-domain transient simulation is performed to verify whether the transient voltage deviation and frequency offset meet safety standards, and all power characteristic data pairs that satisfy the constraints are selected. A quadratic polynomial is used to perform nonlinear regression fitting on the safe and feasible data pairs to obtain the mapping function between the total feed-in power and the safety threshold of the characteristic quantities, i.e., the safety boundary envelope function.

[0036] By calibrating the safety thresholds under different power levels through discrete scanning and simulation verification, the dynamic differences in system coupling characteristics caused by power variations are adapted. The fitted continuous envelope function can quickly output the safety judgment benchmark under any power, improving the evaluation accuracy of the safety boundary.

[0037] Step 104: Perform an iterative search within the total feed power search interval, and calculate the transient voltage-frequency coupling strength characteristic corresponding to the test power one by one.

[0038] The test power is the midpoint of the total feed power search range.

[0039] For example, an iterative search is performed using a bisection method, with an iterative convergence tolerance of 0.5MW. The first iteration uses a preset total feed-in power search interval as the initial range, taking the total power at the midpoint between the upper and lower bounds of the interval as the test power. Based on the proportion of current active power at each converter station, the test power is allocated to each feed-in channel, obtaining the active power setpoint for each channel under this test power. The channel active power setpoint is then input into a robust calculation model to solve for the coupling strength characteristic corresponding to the test power. Each iteration repeats the above process of test power selection, allocation, and characteristic calculation.

[0040] By adopting a midpoint trial binary search method, the target value can be quickly converged in fewer iterations, balancing computational efficiency and solution accuracy. The characteristic quantity corresponding to each trial power is calculated successively, ensuring that the coupling characteristics of each verification point are fully matched with the actual working conditions, and avoiding the evaluation bias caused by fixed characteristic quantities.

[0041] Step 105: After comparing the transient voltage frequency coupling strength characteristic with the safety threshold of the characteristic corresponding to the safety boundary envelope function, adjust the total feed-in power search interval. After the total feed-in power search interval converges, obtain the upper limit of the receiving end grid stability carrying capacity.

[0042] Among them, the upper limit of stable carrying capacity is the maximum value of the total active power fed into the receiving-end grid by flexible DC, under the premise of meeting transient voltage and frequency safety constraints.

[0043] Specifically, the trial power of the current iteration is substituted into the safety boundary envelope function to calculate the safety threshold of the characteristic quantity corresponding to this power level. The coupling strength characteristic quantity corresponding to the trial power is compared with the safety threshold: if the characteristic quantity is less than or equal to the safety threshold, it means that the trial power is within a safe and feasible range, and the lower bound of the search interval is updated to the trial power; if the characteristic quantity is greater than the safety threshold, it means that the trial power has exceeded the safe range, and the upper bound of the search interval is updated to the trial power. The process of iterative calculation, threshold comparison, and boundary adjustment is repeated until the width of the search interval is less than the preset convergence tolerance, and the lower bound value of the current search interval is output as the upper limit of the receiving-end power grid stability carrying capacity.

[0044] Step 106: Calculate the load factor based on the current total active power and the upper limit of the receiving end grid's stable carrying capacity, and determine the state classification based on the graded safety threshold and the load factor, and output the corresponding level of stable carrying capacity prediction results.

[0045] Among them, the load factor is the ratio of the current total active power to the upper limit of stable load capacity, which is used to intuitively characterize the current grid's load margin for DC feed-in power.

[0046] The graded safety threshold is a load rate critical value used to classify the operational safety level. It is set based on the power grid operation safety requirements and corresponds to different risk levels.

[0047] For example, the current operating active power of all flexible DC converter stations is statistically analyzed and summed to obtain the total operating active power. This total active power is then divided by the upper limit of the stable carrying capacity to obtain the load factor. Two preset safety thresholds are established: the first threshold is 0.7, and the second threshold is 0.9. If the load factor is ≤0.7, the system is considered to be in a safe operating state; if 0.7 < load factor ≤0.9, the system is considered to be in a warning operating state; and if the load factor >0.9, the system is considered to be in a high-risk operating state. Based on the assessment results, the corresponding level of stable carrying capacity prediction is output, along with auxiliary information such as load margin and power increase potential.

[0048] By converting absolute power values ​​into relative margin indicators through load factor, it is easier for operators to accurately grasp the system's safety status; the graded judgment mechanism can quickly distinguish risk levels, providing a clear decision-making basis for power grid dispatch and operation, and improving the engineering applicability of prediction results.

[0049] In some embodiments, such as Figure 2As shown, a robust computational model for transient voltage-frequency coupling strength features is constructed based on a structured input dataset, including: Step 201: Based on the receiving-end power grid network topology parameters and flexible DC feed point information in the structured input dataset, perform multi-port Thevenin equivalent processing on the receiving-end AC power grid to obtain the AC power grid port admittance matrix.

[0050] Step 202: Based on the control mode parameters and outer loop controller coefficients of each converter station in the structured input dataset, construct the frequency domain impedance model of each converter station.

[0051] Step 203: Combine the frequency domain impedance models of all converter stations to form the diagonal impedance matrix on the converter station side.

[0052] Step 204: Combine the AC grid port admittance matrix and the converter station side diagonal impedance matrix to construct the closed-loop hysteresis matrix of the multi-infeed AC / DC system.

[0053] Step 205: Using the minimum singular value of the closed-loop hysteresis matrix as a quantitative indicator of the system's interactive instability risk, and combining it with the control parameter perturbation interval to construct a global parameter optimization solution logic, a robust calculation model of transient voltage frequency coupling strength characteristic quantity is formed.

[0054] Among them, the robust calculation model of transient voltage frequency coupling strength feature is used to output the global minimum value of the minimum singular value within the perturbation range of the control parameters as the transient voltage frequency coupling strength feature, and outputs the worst interactive control scenario corresponding to the minimum value.

[0055] Specifically, multi-port Thevenin equivalents are performed on the receiving-end AC power grid network to obtain the AC power grid port impedance matrix. impedance matrix for dimensional transfer function matrix, This represents the total number of flexible DC feed channels.

[0056] In the impedance matrix Then, for the impedance matrix The transformation yields the AC power grid port admittance matrix. .

[0057] Furthermore, constructing the frequency domain impedance model for each converter station is essential for constructing the first... Frequency domain impedance model of a converter station in the dq rotating coordinate system ,in Indicates the first The perturbation vector of the control parameters of each converter station, and the frequency domain impedance model expression are as follows: (1) in, and These are the equivalent proportional coefficient and integral coefficient under the corresponding control mode, respectively; The transfer function of the phase-locked loop. This is the transfer function for the feedforward filter.

[0058] The frequency domain impedance models of each converter station are arranged in order of feed port. The frequency domain impedance of a single converter station is used as the diagonal element at the corresponding position. The off-diagonal elements between different converter stations are set to zero. A diagonal impedance matrix with the same order as the number of feed channels is constructed for the converter station side. Each diagonal element of the matrix corresponds to the port impedance characteristic of a flexible DC converter station. The expression of the diagonal impedance matrix is ​​as follows: (2) After obtaining the diagonal impedance matrix, the port admittance matrix on the AC grid side is... Diagonal impedance matrix of the converter station side By performing simultaneous equations and matrix multiplication, the open-loop back ratio matrix of the multi-infeed AC / DC system is obtained. Based on this, an identity matrix of the same order as the open-loop back ratio matrix is ​​constructed. Further derivation yields the closed-loop hysteresis matrix of the multi-infeed AC / DC system as follows: (3) in, for The identity matrix. The closed-loop hysteresis matrix fully integrates the network characteristics of the AC power grid and the control dynamic characteristics of multiple flexible DC converter stations. It can comprehensively reflect the interactive coupling effect of AC and DC systems under multi-infeed scenarios, transforming complex system stability problems into matrix characteristic analysis problems.

[0059] After obtaining the closed-loop hysteresis matrix, the minimum singular value of the closed-loop hysteresis matrix is ​​selected as the quantitative index of the system's interactive instability risk. The smaller the value of this index, the stronger the coupling effect between the system's transient voltage and frequency, the lower the stability margin, and the higher the interactive instability risk.

[0060] For example, using the minimum singular value of the closed-loop hysteresis matrix as a quantitative indicator of the system's interactive instability risk, and combining it with the control parameter perturbation interval to construct a global parameter optimization solution logic, a robust calculation model for the transient voltage-frequency coupling strength characteristic is formed. The calculation formula for the transient voltage-frequency coupling strength robust characteristic is as follows: (4) in, This represents the operation of finding the minimum singular value of a matrix. The imaginary unit, To consider the frequency domain closed-loop hysteresis matrix after control parameter perturbation A global optimization algorithm is used to solve the problem, and the complete calculation process of matrix modeling, singular value calculation, and global parameter optimization is encapsulated and integrated to form a robust calculation model of transient voltage-frequency coupling strength feature. The robust calculation model of transient voltage-frequency coupling strength feature can automatically traverse all feasible operating conditions within the control parameter perturbation interval, locate the worst interactive control scenario that makes the system coupling the strongest and the stability margin the lowest, and output the corresponding global minimum value as the robust coupling strength feature. This effectively solves the defects of traditional nominal parameter evaluation results being too optimistic and unable to cover the instability risk of extreme operating conditions, and ensures the conservatism and robustness of the feature calculation results.

[0061] In some embodiments, such as Figure 3 As shown, based on the robust calculation model of transient voltage-frequency coupling strength characteristics, the safety boundary envelope function corresponding to the safety threshold of the characteristic quantity is obtained by fitting within the preset total feed power search interval, including: Step 301: Set the total feed power search interval and select multiple discrete power levels within the total feed power search interval.

[0062] The lower limit of the total feed-in power search range is the sum of the active power of each flexible DC feed-in channel.

[0063] Specifically, the total feed-in power search interval is used to scan the range of total DC feed-in power values ​​for calibrating the stability boundary of the AC / DC system, including two boundaries: a lower power limit and a higher power limit. The lower limit is the sum of the actual active power of each flexible DC channel currently in operation, and the upper limit is the sum of the rated active power of all flexible DC converter stations. The discrete power level consists of multiple sets of total power sampling points uniformly / according to rules within the total feed-in power search interval. Each set of discrete power levels represents a set of total feed-in operating conditions of the system to be verified.

[0064] For example, the current active power of three flexible DC converter stations is 80MW, 120MW, and 200MW. The sum of these three is 400MW, which is used as the lower limit of the total feed-in power search interval. The rated capacities of the three converter stations are 150MW, 200MW, and 300MW, which are summed to 650MW, which is used as the upper limit of the interval. The total feed-in power search interval [400MW, 650MW] is then determined. Within the interval, 20 sets of total power values ​​are uniformly sampled at equal intervals of 12.5MW, which are used as 20 discrete power levels to complete the selection of sampling points.

[0065] The current actual total operating power is used as the lower limit of the range to match the real-time operating conditions of the power grid and avoid selecting low-power samples that have no engineering significance; the upper limit is taken as the rated capacity of all converter stations to fully cover the system power carrying capacity limit; the discrete power levels are extracted at equal intervals to uniformly cover the entire power range and ensure that there is no local accuracy loss in the safety boundary of the subsequent fitting.

[0066] Step 302: Allocate discrete power levels according to the proportion of active power in each flexible DC feed channel to obtain the channel active power setting value corresponding to each discrete power level.

[0067] The active power ratio of a single flexible DC feeder channel is the ratio of its current operating active power to the total current active power of all channels. This ratio serves as the power allocation weight, ensuring that the proportion of multiple DC feeders is consistent with the actual operating conditions. The active power setpoint of a single flexible DC converter station is the target active power delivered under a certain discrete total feeder power level. It is a single-channel input operating condition parameter calculated by simulation and robust model.

[0068] In some embodiments, discrete power levels are allocated according to the proportion of active power in each flexible DC feed channel to obtain the channel active power setpoint corresponding to each discrete power level, including: Obtain the current operating active power of each flexible DC feed channel; Calculate the ratio of the current operating active power of each flexible DC feed channel to the total current operating active power of all flexible DC feed channels, and obtain the power allocation weight corresponding to each channel. For each discrete power level, the total feed-in power value corresponding to the discrete power level is used as the allocation base, and multiplied by the power allocation weight to obtain the active power setting value of each flexible DC feed-in channel under the discrete power level.

[0069] For example, the current operating power of the three channels is 80MW, 120MW, and 200MW, with a total active power of 400MW. The weights allocated to each flexible DC feed channel are calculated to be 0.2, 0.3, and 0.5. Take a discrete power level of 500MW and multiply it by the corresponding weights to obtain the active power setpoints for each channel of 100MW, 150MW, and 250MW. Repeat this allocation calculation for all 20 discrete power levels, and output a set of three-channel active power setpoints for each group of discrete power levels.

[0070] The system allocates total power based on the actual active power ratio during operation, maintains the ratio of multiple DC feeds in a constant manner, and scans the operating conditions to closely approximate the actual power dispatching method of the power grid, avoiding boundary distortion caused by manually changing the feed ratio. It automatically calculates the set values ​​of each channel in batches, realizing the standardized conversion from total power to channel-specific operating conditions, and providing standardized input for subsequent model solving.

[0071] Step 303: Solve the channel active power setpoint using the robust calculation model of transient voltage frequency coupling strength characteristic quantity to obtain the worst interactive control scenario corresponding to the channel active power setpoint.

[0072] Among them, the robust calculation model of transient voltage frequency coupling strength characteristic can solve the system coupling characteristic within the perturbation range of control parameters.

[0073] The worst-case interactive control scenario is a set of converter station control parameters that minimizes the singular value of the closed-loop hysteresis matrix to the global minimum within the perturbation range of the control parameters under the current active power setpoint. This represents the extreme operating condition with the highest risk of AC / DC coupling instability at this power level.

[0074] For example, robust calculation models of the frequency coupling strength characteristics of the input transient voltage for channel active power setpoints of 100MW, 150MW, and 250MW corresponding to a discrete power level of 500MW are used to complete the Thevenin equivalent model of the power grid multi-port, converter station frequency domain impedance modeling, and closed-loop hysteresis matrix construction, based on the formula. The system iterates through the perturbation range of the control parameters globally and outputs a set of proportional and integral parameters of the PI controllers of each converter station. This set of parameters represents the worst interactive control scenario under this power condition.

[0075] The worst-case scenario matching is solved for each discrete power level, and the differences in system coupling characteristics under different total power are distinguished to ensure that the safety boundary calibration is robust and conservative.

[0076] Step 304: Perform transient simulation of the receiving-end power grid for the worst-case interactive control scenario, and determine the feasibility of discrete power levels based on preset voltage amplitude safety constraints and frequency offset safety constraints to obtain a set of safe and feasible points.

[0077] Among them, the receiving-end power grid transient simulation is a numerical simulation process that uses electromagnetic transient / electromechanical transient simulation tools, substitutes the channel active power setpoint and the worst-case interactive control parameters, and simulates the dynamic changes in voltage and frequency after power grid disturbance.

[0078] Voltage amplitude safety constraints and frequency deviation safety constraints are safety thresholds specified in power system dispatch standards, such as AC bus voltage per unit value of 0.9~1.1 pu and system frequency deviation not exceeding ±0.2 Hz, which serve as the basis for determining operating condition safety.

[0079] The set of safe and feasible points is a set of numerical data pairs consisting of discrete power levels and corresponding coupling strength characteristics that simultaneously satisfy voltage and frequency safety constraints. It serves as the basic sample library for fitting the safety boundary.

[0080] For example, the active power setpoint and worst-case control parameters corresponding to the discrete power of 500MW are imported into the electromechanical transient simulation program, and a three-phase short-circuit disturbance fault simulation transient process is set. The simulation disturbance is set to a three-phase metallic short-circuit fault occurring at the outlet of the largest capacity synchronous generator set in the receiving-end grid, and the fault is cleared after 100 milliseconds. The minimum amplitude of the AC bus voltage at each flexible DC feed-in landing point is recorded during the simulation. and the absolute value of the maximum frequency offset of the receiving-end power grid system When both conditions are met and When Hertz, the binary pair Marked as a safe and feasible point, where, This is the rated voltage of the AC bus.

[0081] The 20 discrete power levels were simulated and evaluated one by one. Samples that did not meet the constraints were eliminated, and all qualified samples were collected to form a set of safe and feasible points.

[0082] Transient simulations are conducted based on the worst-case interactive control scenario. Power feasibility is verified under the highest-risk operating condition, and sufficient safety margins are reserved in the calibrated safety boundaries. National standard voltage and frequency constraints are uniformly adopted as the judgment criteria, and the judgment logic is objective and consistent. Qualified operating condition data are collected in batches to form a standardized sample dataset, ensuring that the data basis for regression fitting is complete and effective.

[0083] Step 305: Perform nonlinear regression fitting on the set of safe and feasible points to obtain the safe boundary envelope function.

[0084] The safety boundary envelope function represents the mapping relationship between the total feed power and the safety threshold of the characteristic quantity.

[0085] Nonlinear regression fitting is a data processing method that uses polynomial and exponential nonlinear functions to fit curves to the discrete critical value data of total feed power characteristics in the set of safe and feasible points.

[0086] The characteristic quantity safety threshold is the critical transient voltage-frequency coupling strength characteristic quantity value at which the system just satisfies the transient voltage and frequency safety constraints under a certain total input power level.

[0087] The safety boundary envelope function is a continuous nonlinear mapping function generated by fitting. By inputting any total feed power, the safety threshold of the characteristic quantity corresponding to that power can be quickly output.

[0088] For example, 16 lattice samples are extracted from the set of safe and feasible points (4 sets of discrete power were removed due to simulation exceeding limits). With the total feed-in power as the independent variable and the corresponding safety threshold as the dependent variable, a quadratic polynomial is used to perform nonlinear regression fitting. Solving for the coefficients of each term of the polynomial yields the continuous safety boundary envelope function. The function input is the total feed-in power within any range of 400~650MW. It can directly output the critical coupling characteristic quantity corresponding to this power. .

[0089] By transforming discrete sampled samples into continuous mapping functions, the safety threshold of characteristic quantities under any total power can be quickly queried without repeatedly performing robust calculations and transient simulations, which greatly reduces the calculation time for subsequent iterative solutions to the upper limit of the load capacity. Nonlinear fitting closely matches the nonlinear variation law of power and coupling characteristic quantities in AC / DC systems, which significantly improves the accuracy of safety boundary determination compared to linear fitting.

[0090] In one possible implementation, the process of fitting the safety boundary envelope function to the point set consisting of each safe and feasible point using the least squares support vector regression method is further defined as follows: Selecting the radial basis kernel function: (5) in, The kernel width parameter. Denotes the Euclidean norm; , respectively the first The and the first The total feed-in active power value corresponding to each safe and feasible point.

[0091] When constructing an optimization problem to solve the regression function, firstly, the original optimization problem of least squares support vector regression is: (6) The constraints are: (7) in, For the number of safe and feasible points, This is a regularization parameter used to balance fitting accuracy and model complexity. This represents the fitting error variable.

[0092] Introducing Lagrange multipliers We can obtain the system of linear equations for the dual problem, and solve it to obtain the regression function: (8) in, For the bias term, the predicted values ​​and confidence intervals of the regression function at each point within the input power range are calculated. The upper bound of the confidence interval is taken as the safety boundary envelope function value to provide a conservative safety threshold; the radial basis function kernel width parameter... Values , The standard deviation of the input power value is used as the regularization parameter to determine the safe and feasible point. The value is 10.

[0093] In some embodiments, such as Figure 4 As shown, an iterative search is performed within the total feed power search interval, successively calculating the transient voltage-frequency coupling strength characteristic corresponding to the test power, including: Step 401: Set the iterative search interval for the total feed-in power, with the current total active power as the lower limit of the search and the sum of the rated capacities of all flexible DC converter stations as the upper limit of the search. Step 402: In each iteration, the total power at the midpoint of the iteration search interval is taken as the test power. The test power is allocated to each feed channel according to the proportion of the current active power of each flexible DC converter station, so as to obtain the active power set value of each channel under the test power. Step 403: Input the active power setpoint of each channel under the test power into the robust calculation model of transient voltage frequency coupling strength characteristic quantity, and solve to obtain the transient voltage frequency coupling strength characteristic quantity corresponding to the test power.

[0094] Specifically, the iterative search interval is used to solve the range of total feed power values ​​for the upper limit of stable carrying capacity through iterative narrowing. It is defined by the lower and upper bounds of the search and is the numerical boundary of the bisection iterative solution.

[0095] The lower bound of the search is the starting lower limit of the power for the iterative search, which is the current total active power, that is, the sum of the current active power of all flexible DC feed channels, representing the power benchmark of the system's current actual operation.

[0096] The upper bound of the search is the upper limit of the power for iterative search, which is the sum of the rated capacities of all flexible DC converter stations, representing the physical limit boundary of the DC power that the receiving-end power grid can theoretically accept.

[0097] The transient voltage-frequency coupling strength characteristic quantity is a quantitative indicator representing the degree of transient voltage and frequency interaction coupling between multiple flexible DC lines and the receiving-end power grid under corresponding power conditions. The corresponding formula is... The smaller the value, the higher the risk of interaction instability.

[0098] For example, the current active power of all flexible DC converter stations is counted and summed to obtain the current total active power of 400MW, which is set as the lower limit of the power for iterative search; the rated active capacity of each converter station is summarized as 150MW, 200MW, and 300MW, and summed to obtain 650MW, which is set as the upper limit of the power for iterative search. Thus, the initial iterative search interval of the total feed-in power is determined to be [400MW, 650MW].

[0099] In the first iteration, the current search interval is [400MW, 650MW]. The arithmetic mean of the upper and lower bounds of the interval, 525MW, is taken as the test power for this round. The current active power ratio of each channel, 0.2, 0.3, and 0.5, is used as the allocation weight. The test power of 525MW is used as the allocation base. The weights of each channel are multiplied by the weights of each channel to calculate the active power setpoints of the three feedback channels under the test power, which are 105MW, 157.5MW, and 262.5MW, respectively. After each iteration interval update, the above midpoint selection and power allocation process is repeated.

[0100] The active power setpoints of each channel corresponding to the test power of 525MW are input into the robust calculation model of transient voltage-frequency coupling strength characteristics. The robust calculation model of transient voltage-frequency coupling strength characteristics automatically completes the AC grid port equivalence, converter station frequency domain impedance update, and closed-loop hysteresis matrix construction under the corresponding operating conditions. It performs global optimization within the control parameter perturbation interval and finally outputs the transient voltage-frequency coupling strength characteristic value corresponding to the test power, and simultaneously outputs the corresponding worst control parameter combination.

[0101] Using the midpoint of the interval as the test power in a binary iterative method can quickly narrow the search range in fewer iterations, balancing solution efficiency and computational accuracy. The total test power is allocated according to the current active power ratio, so that the power ratio of each channel is always consistent with the actual operating conditions and is consistent with the power allocation rules in the safety boundary fitting stage, ensuring that the characteristic quantity calculation results are comparable and practical for engineering.

[0102] In some embodiments, such as Figure 5 As shown, after comparing the transient voltage frequency coupling strength characteristic with the safety threshold of the characteristic corresponding to the safety boundary envelope function, the total feed-in power search interval is adjusted. After the total feed-in power search interval converges, the upper limit of the receiving-end grid stability carrying capacity is obtained, including: Step 501: Set the convergence tolerance and input the trial power of the current iteration into the safety boundary envelope function to obtain the feature quantity safety threshold corresponding to the trial power; Step 502: Compare the transient voltage frequency coupling strength characteristic corresponding to the test power with the characteristic safe threshold; Step 503: If the transient voltage frequency coupling strength characteristic is less than or equal to the characteristic safe threshold, the test power is determined to be within a safe and feasible range, and the lower bound of the total feed-in power search interval is updated to the test power. Step 504: If the transient voltage frequency coupling strength characteristic is greater than the characteristic safe threshold, it is determined that the test power exceeds the safe range, and the upper bound of the total feed-in power search interval is updated to the test power. Step 505: Repeat until the width of the total feed-in power search interval is less than the convergence tolerance, output the total feed-in active power corresponding to the lower bound of the total feed-in power search interval, and obtain the upper limit of the receiving-end grid stability carrying capacity.

[0103] The convergence tolerance is a precision control parameter used to determine the termination of the iterative search. It characterizes the maximum allowable deviation between the final iterative result and the actual upper limit of the load capacity; the smaller the value, the higher the solution accuracy. In this embodiment, the convergence tolerance... .

[0104] The characteristic quantity safety threshold is the critical transient voltage-frequency coupling strength characteristic quantity value that, under a certain total input power level, the system just satisfies the transient voltage and frequency safety constraints. The safe and feasible range is the total feed-in power range in which the system transient voltage and frequency indicators meet safety constraints and there is no risk of AC / DC interactive instability.

[0105] Specifically, the preset iteration convergence tolerance is 0.5MW; the trial power of the current iteration round is taken as 525MW, and it is substituted into the already fitted safety boundary envelope function. The characteristic quantity safety threshold corresponding to the trial power is calculated as 0.12 through function mapping, which is used as the safety judgment benchmark for this iteration round.

[0106] The transient voltage frequency coupling strength characteristic corresponding to the test power of 525MW was solved by the robust calculation model and the result was 0.10. This value was compared with the corresponding characteristic safety threshold of 0.12 to clarify the relationship between the two.

[0107] After comparison, the transient voltage frequency coupling strength characteristic value of 0.10 corresponding to the test power of 525MW is less than the characteristic value safety threshold of 0.12, and it is determined that the test power is within the safe and feasible range; the lower bound of the original total feed-in power search interval [400MW, 650MW] is updated from 400MW to 525MW, and the updated search interval is [525MW, 650MW].

[0108] In the next iteration, the midpoint 587.5MW of the updated interval [525MW, 650MW] is taken as the test power. The corresponding coupling strength feature is calculated to be 0.14. Substituting it into the safety boundary envelope function, the corresponding safety threshold is 0.11. After comparison, the feature is found to be greater than the safety threshold, and it is determined that the test power exceeds the safety range. The upper limit of the search interval is updated from 650MW to 587.5MW, and the updated search interval is [525MW, 587.5MW].

[0109] The iterative process of selecting trial power, calculating feature quantities, comparing thresholds, and updating interval boundaries is executed repeatedly. After multiple iterations, the total feed-in power search interval is updated to [562.2MW, 562.6MW]. The calculated interval width is 0.4MW, which is less than the preset convergence tolerance of 0.5MW, so the search interval is determined to be converged. The lower bound of the current search interval, 562.2MW, is output as the upper limit of the stable carrying capacity of the receiving-end power grid.

[0110] In each iteration, the allocation of power values ​​at the search midpoint is not based on average distribution, but rather on a weighted allocation according to the proportion of the current active power of each converter station to the total operating power. This ensures that the power growth path is consistent with the actual feed-in distribution, and that the search always proceeds along the true scheduling direction. For the allocated power section, the entire process of establishing the closed-loop hysteresis matrix, optimizing the control parameter perturbation space, and calculating characteristic quantities is fully invoked to obtain the dynamically updated transient voltage-frequency coupling strength characteristic quantity at that power level. Simultaneously, the safety boundary envelope function is invoked to calculate the characteristic quantity threshold corresponding to that power level, and the two are compared to determine the safety feasibility of that power point.

[0111] Each step of the binary search is based on the worst-case interactive control scenario re-identified under the current trial power, rather than using a fixed scenario from the initial operating point. This ensures that the safety judgment benchmark evolves synchronously with the power level, fully covering the impact of changes in the control interaction pattern caused by significant power shifts. When the calculated feature value is less than or equal to the feature value threshold, the power is deemed safe and feasible, and the search lower bound is moved upwards; otherwise, it is deemed infeasible, and the search upper bound is moved downwards, gradually converging the iteration interval.

[0112] In some embodiments, such as Figure 6 As shown, the load factor is calculated based on the current total active power and the upper limit of the receiving-end grid's stability carrying capacity. Then, based on the graded safety threshold and the load factor, a state classification is determined, and the corresponding stability carrying capacity prediction results are output, including: Step 601: Sum the current operating active power of each flexible DC converter station to obtain the current total operating active power; Step 602: Calculate the ratio of the current total active power to the upper limit of the stable carrying capacity of the receiving-end power grid to obtain the load factor; Step 603: Extract the load rate values ​​corresponding to all safe and feasible points during the fitting process of the safety boundary envelope function, and calculate the mean and standard deviation of the load rate values; Step 604: Set the first safety threshold and the second safety threshold based on the mean and standard deviation; Among them, the first safety threshold is less than the second safety threshold; Step 605: Compare the load-bearing rate with the first safety threshold and the second safety threshold, and determine the operating safety level of the receiving-end power grid based on the comparison results; Step 606: Based on the determined operational safety level, output the corresponding stability bearing capacity prediction results and supporting operational decision information.

[0113] Specifically, the current operating active power of a flexible DC converter station is the measured value of the active power transmitted by a single flexible DC converter station under real-time operating conditions, and the current total operating active power is the sum of the current operating active power of all flexible DC feed-in channels. The upper limit of the receiving-end grid's stable carrying capacity is the maximum value of the total active power fed into the flexible DC system that the receiving-end grid can accept under the premise of meeting transient voltage and frequency safety constraints; it is the critical upper limit of the system's power carrying capacity.

[0114] The load factor is the ratio of the current total active power to the upper limit of stable load capacity. It represents the current grid's saturation level for DC power input in a relative proportion. The closer the value is to 1, the smaller the load margin.

[0115] For example, real-time active power data of each flexible DC converter station is collected from the power grid energy management system. After data calibration, the current active power of the three flexible DC converter stations are 80MW, 120MW, and 200MW, respectively. The three sets of power values ​​are summed to calculate the total current active power as 400MW. Using the upper limit of the receiving-end grid stability carrying capacity of 562.2MW obtained through iterative solution as the denominator and the current total active power of 400MW as the numerator, the ratio 400 / 562.2≈0.711 is calculated. This value is the load factor under the current operating conditions.

[0116] From the set of safe and feasible points during the safety boundary fitting stage, the total power values ​​corresponding to all 16 groups of safe and feasible discrete power are extracted. Each group's total power is divided by the upper limit of the stable bearing capacity, 562.2MW, to obtain 16 samples of load rates at safe and feasible points. Statistical calculations are performed on the sample data to obtain the mean and standard deviation of the load rate, denoted as [reference needed]. and Set the first security threshold as The second safety threshold is .

[0117] When the actual load factor is less than the first safety threshold At this time, the system has sufficient stability margin, and the feed-in power margin can be increased. ; When the actual load factor is within and During this period, the system is in a critical stable state and outputs a control parameter coordination check command. The specific check content is the outer loop proportional coefficient of each converter station. Sensitivity analysis was performed to reduce the adjustment proportionally. When the actual load factor is greater than or equal to When the system's carrying capacity is insufficient, an early warning signal is triggered, and a suggested reduction value for active power at each converter station is output. ,in For the first The current operating active power of each converter station.

[0118] The first and second safety thresholds are determined through statistical calculations of the set of safe and feasible points formed during the construction of the safety boundary envelope function. These two thresholds originate from the actual data distribution characteristics of the system maintaining transient stability at different power levels, and possess clear statistical and physical significance. When the actual load rate is less than the first safety threshold, it indicates that the system is operating in a low-load region of the statistical distribution of the set of safe and feasible points, with sufficient stability margin. The additional power margin that can be fed in is obtained by directly subtracting the upper limit of the carrying capacity from the current total generated power.

[0119] When the actual load rate falls between the two thresholds, it corresponds to the intermediate transition region of the statistical distribution. The system needs to check the coordination of control parameters. Specifically, this involves performing a sensitivity calculation on the outer loop proportional coefficient of each converter station by proportionally reducing it, in order to identify whether there is potential to expand the stability domain through parameter fine-tuning. When the actual load rate is greater than or equal to the second safety threshold, it corresponds to falling into the high-risk tail region of the statistical distribution. An early warning needs to be triggered and a reduction suggestion needs to be given. The active power reduction value of each converter station is allocated according to the current actual generated power multiplied by the relative proportion of the actual load rate exceeding the second threshold, ensuring that the total reduction is consistent with the current output weight of each converter station while eliminating the risk of exceeding the limit.

[0120] Corresponding to the above method embodiments, this specification also provides an embodiment of a flexible DC dense feed-in receiving-end power grid stability carrying capacity prediction system. Figure 7 A schematic diagram of a flexible DC dense feed-in receiving-end power grid stability carrying capacity prediction system according to one embodiment of this specification is shown. Figure 7 As shown, the device includes: The data acquisition and preprocessing unit 710 is used to acquire basic data of the flexible DC dense feed into the receiving-end power grid and preprocess it to obtain a structured input dataset. Robust computation model building unit 720 is used to build a robust computation model of transient voltage frequency coupling strength features based on a structured input dataset; The safety boundary fitting unit 730 is used to fit the safety boundary envelope function corresponding to the total feed power and the safety threshold of the feature quantity within a preset total feed power search interval based on the robust calculation model of transient voltage frequency coupling strength feature quantity. The iterative search solution unit 740 is used to perform iterative search within the total feed-in power search interval, calculate the transient voltage frequency coupling strength characteristic quantity corresponding to the test power one by one, compare the transient voltage frequency coupling strength characteristic quantity with the characteristic quantity safety threshold corresponding to the safety boundary envelope function and adjust the search interval. After the search interval converges, the upper limit of the receiving end grid stability carrying capacity is obtained. The graded assessment output unit 750 is used to calculate the load factor based on the current total active power and the upper limit of the stability carrying capacity of the receiving end power grid, and to make a state graded judgment based on the graded safety threshold and the load factor, and output the corresponding level of stability carrying capacity prediction results.

[0121] The above is a schematic scheme of a flexible DC dense infeed receiving-end power grid stability carrying capacity prediction system according to this embodiment. It should be noted that the technical solution of this flexible DC dense infeed receiving-end power grid stability carrying capacity prediction system belongs to the same concept as the technical solution of the aforementioned flexible DC dense infeed receiving-end power grid stability carrying capacity prediction method. Details not described in detail in the technical solution of the flexible DC dense infeed receiving-end power grid stability carrying capacity prediction system can be found in the description of the technical solution of the aforementioned flexible DC dense infeed receiving-end power grid stability carrying capacity prediction method.

[0122] Figure 8 A structural block diagram of a computing device 800 according to one embodiment of this specification is shown. The components of the computing device 800 include, but are not limited to, a memory 810 and a processor 820. The processor 820 is connected to the memory 810 via a bus 830, and a database 850 is used to store data.

[0123] The computing device 800 also includes an access device 840, which enables the computing device 800 to communicate via one or more networks 860. Examples of these networks include Public Switched Telephone Network (PSTN), Local Area Network (LAN), Wide Area Network (WAN), Personal Area Network (PAN), or combinations of communication networks such as the Internet. The access device 840 may include one or more of any type of wired or wireless network interface (e.g., a network interface card (NIC)), such as an IEEE 802.11 Wireless Local Area Network (WLAN) wireless interface, a Wi-MAX (Worldwide Interoperability for Microwave Access) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, or a Near Field Communication (NFC) interface.

[0124] In one embodiment of this specification, the above-described components of the computing device 800 and Figure 8 Other components, not shown, can also be connected to each other, for example, via a bus. It should be understood that... Figure 8 The block diagram of the computing device shown is for illustrative purposes only and is not intended to limit the scope of this specification. Those skilled in the art can add or replace other components as needed.

[0125] The computing device 800 can be any type of stationary or mobile computing device, including mobile computers or mobile computing devices (e.g., tablet computers, personal digital assistants, laptop computers, notebook computers, netbooks, etc.), mobile phones (e.g., smartphones), wearable computing devices (e.g., smartwatches, smart glasses, etc.) or other types of mobile devices, or stationary computing devices such as desktop computers or personal computers (PCs). The computing device 800 can also be a mobile or stationary server.

[0126] The processor 820 executes computer-executable instructions, which, when executed by the processor, implement the steps of the above-described method for predicting the stable carrying capacity of the receiving-end power grid under flexible DC dense infeed. The above is a schematic representation of a computing device according to this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the above-described method for predicting the stable carrying capacity of the receiving-end power grid under flexible DC dense infeed belong to the same concept. Details not described in detail in the technical solution of the computing device can be found in the description of the technical solution of the above-described method for predicting the stable carrying capacity of the receiving-end power grid under flexible DC dense infeed.

[0127] An embodiment of this specification also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described method for predicting the stable carrying capacity of the receiving-end power grid in a flexible DC dense feed-in configuration.

[0128] The above is an illustrative scheme of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium belongs to the same concept as the technical solution of the above-described method for predicting the stability carrying capacity of the flexible DC dense feed-in receiving-end power grid. For details not described in detail in the technical solution of the storage medium, please refer to the description of the technical solution of the above-described method for predicting the stability carrying capacity of the flexible DC dense feed-in receiving-end power grid.

[0129] An embodiment of this specification also provides a computer program, wherein when the computer program is executed in a computer, the computer is instructed to perform the steps of the above-described method for predicting the stability carrying capacity of the receiving-end power grid of flexible DC dense feed-in.

[0130] The above is an illustrative scheme of a computer program according to this embodiment. It should be noted that the technical solution of this computer program and the technical solution of the above-described method for predicting the stability carrying capacity of the receiving-end power grid through dense DC infeeding belong to the same concept. For details not described in detail in the technical solution of the computer program, please refer to the description of the technical solution of the above-described method for predicting the stability carrying capacity of the receiving-end power grid through dense DC infeeding.

[0131] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0132] Computer instructions include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. Computer-readable media can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in computer-readable media can be appropriately added to or removed according to the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0133] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments in this specification are not limited to the described order of actions, because according to the embodiments in this specification, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in this specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to the embodiments in this specification.

[0134] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0135] The preferred embodiments disclosed above are merely illustrative of this specification. The optional embodiments do not exhaustively describe all details, nor do they limit the invention to specific implementations. Clearly, many modifications and variations can be made based on the embodiments described in this specification. These embodiments are selected and specifically described in this specification to better explain the principles and practical applications of the embodiments, thereby enabling those skilled in the art to better understand and utilize this specification. This specification is limited only by the claims and their full scope and equivalents.

Claims

1. A method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid, characterized in that, include: The basic data of the flexible DC dense feed into the receiving-end power grid are acquired and preprocessed to obtain a structured input dataset; A robust calculation model for transient voltage-frequency coupling strength features is constructed based on the structured input dataset. Based on the robust calculation model of transient voltage frequency coupling strength characteristic, the safety boundary envelope function corresponding to the safety threshold of the characteristic is obtained by fitting within the preset total feed power search interval. An iterative search is performed within the total feed power search interval, and the transient voltage-frequency coupling strength characteristic corresponding to the test power is calculated successively; the test power is the median value of the total feed power search interval. After comparing the transient voltage frequency coupling strength characteristic with the safety threshold of the characteristic corresponding to the safety boundary envelope function, the total feed-in power search interval is adjusted. After the total feed-in power search interval converges, the upper limit of the receiving-end grid stability carrying capacity is obtained. The load factor is calculated based on the current total active power and the upper limit of the stable carrying capacity of the receiving-end power grid. The state classification is determined based on the graded safety threshold and the load factor, and the corresponding level of stable carrying capacity prediction result is output.

2. The method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to claim 1, characterized in that, The robust computational model for transient voltage-frequency coupling strength features constructed based on the structured input dataset includes: Based on the receiving-end power grid network topology parameters and flexible DC feed point information in the structured input dataset, multi-port Thevenin equivalent processing is performed on the receiving-end AC power grid to obtain the AC power grid port admittance matrix; Based on the control mode parameters and outer loop controller coefficients of each converter station in the structured input dataset, a frequency domain impedance model of each converter station is constructed. The frequency domain impedance models of all converter stations are combined to form the diagonal impedance matrix on the converter station side; By combining the AC grid port admittance matrix and the converter station side diagonal impedance matrix, a closed-loop hysteresis matrix of the multi-infeed AC / DC system is constructed. Using the minimum singular value of the closed-loop hysteresis matrix as a quantitative indicator of the system's interactive instability risk, and combining it with the control parameter perturbation range of the structured input dataset, a global parameter optimization solution logic is constructed to form a robust calculation model for transient voltage-frequency coupling strength features. This robust calculation model outputs the global minimum value of the minimum singular value within the control parameter perturbation range as the transient voltage-frequency coupling strength feature, and outputs the worst-case interactive control scenario corresponding to the minimum value.

3. The method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to claim 1, characterized in that, Based on the robust calculation model of the transient voltage frequency coupling strength characteristic, a safe boundary envelope function corresponding to the total feed power and the characteristic safety threshold is fitted within a preset total feed power search interval, including: A total feed-in power search interval is set, and multiple discrete power levels are selected within the total feed-in power search interval; the lower limit of the total feed-in power search interval is the sum of the active power of each flexible DC feed-in channel; The discrete power levels are allocated according to the proportion of active power in each flexible DC feed channel, and the active power setpoint of each channel corresponding to each discrete power level is obtained. The active power setpoint of the channel is solved by the robust calculation model of the transient voltage frequency coupling strength characteristic, and the worst interactive control scenario corresponding to the active power setpoint of the channel is obtained. For the worst-case interactive control scenario, a transient simulation of the receiving-end power grid is performed. Based on the preset voltage amplitude safety constraints and frequency offset safety constraints, the feasibility of discrete power levels is determined to obtain a set of safe and feasible points. The set of safe and feasible points is fitted with nonlinear regression to obtain the safety boundary envelope function; the safety boundary envelope function is the mapping relationship between the total feed power and the safety threshold of the characteristic quantity.

4. The method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to claim 3, characterized in that, The discrete power levels are allocated according to the proportion of active power in each flexible DC feed channel, resulting in the channel active power setpoints corresponding to each discrete power level, including: Obtain the current operating active power of each flexible DC feed channel; Calculate the ratio of the current operating active power of each flexible DC feed channel to the total current operating active power of all flexible DC feed channels to obtain the power allocation weight corresponding to each channel; For each discrete power level, the total feed-in power value corresponding to the discrete power level is used as the allocation base, and multiplied by the power allocation weight to obtain the active power setting value of each flexible DC feed-in channel under the discrete power level.

5. The method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to claim 1, characterized in that, The iterative search performed within the total feed-in power search interval, successively calculating the transient voltage-frequency coupling strength characteristic corresponding to the test power, includes: The iterative search interval for the total feed-in power is set with the current total active power as the lower bound of the search and the sum of the rated capacities of all flexible DC converter stations as the upper bound of the search. In each iteration, the total power at the midpoint of the iteration search interval is taken as the test power. The test power is allocated to each feed channel according to the proportion of the current active power of each flexible DC converter station, so as to obtain the active power setting value of each channel under the test power. The active power setpoint of each channel under the test power is input into the robust calculation model of the transient voltage frequency coupling strength characteristic, and the transient voltage frequency coupling strength characteristic corresponding to the test power is obtained by solving the model.

6. The method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to claim 1, characterized in that, After comparing the transient voltage frequency coupling strength characteristic with the safety threshold of the characteristic corresponding to the safety boundary envelope function, the total feed-in power search interval is adjusted. Once the total feed-in power search interval converges, the upper limit of the receiving-end grid stability carrying capacity is obtained, including: Set a convergence tolerance and input the trial power of the current iteration into the safety boundary envelope function to obtain the feature quantity safety threshold corresponding to the trial power; The transient voltage frequency coupling strength characteristic corresponding to the test power is compared with the safety threshold of the characteristic; If the transient voltage frequency coupling strength characteristic is less than or equal to the characteristic safe threshold, then the test power is determined to be within a safe and feasible range, and the lower bound of the total feed-in power search interval is updated to the test power. If the transient voltage frequency coupling strength characteristic is greater than the characteristic safe threshold, then the test power is determined to be out of safe range, and the upper bound of the total feed-in power search interval is updated to the test power. Repeat the process until the width of the total feed-in power search interval is less than the convergence tolerance, then output the total feed-in active power corresponding to the lower bound of the total feed-in power search interval to obtain the upper limit of the receiving-end grid stability carrying capacity.

7. The method for predicting the stability carrying capacity of a flexible DC dense feed-in receiving-end power grid according to claim 1, characterized in that, The process of calculating the load factor based on the current total active power and the upper limit of the receiving-end power grid's stable carrying capacity, and determining the state classification based on the graded safety threshold and the load factor, and outputting the corresponding level of stable carrying capacity prediction results, includes: The total active power currently in operation is obtained by summing the current active power of each flexible DC converter station. Calculate the ratio of the current total active power to the upper limit of the stable carrying capacity of the receiving-end power grid to obtain the load factor; Extract the load rate values ​​corresponding to all safe and feasible points during the fitting process of the safety boundary envelope function, and calculate the mean and standard deviation of the load rate values; A first safety threshold and a second safety threshold are set based on the mean and the standard deviation; the first safety threshold is less than the second safety threshold. The load-bearing rate is compared with the first safety threshold and the second safety threshold, and the operating safety level of the receiving-end power grid is determined based on the comparison results. Based on the determined operational safety level, output the corresponding stability carrying capacity prediction results and supporting operational decision information.

8. A flexible DC dense feed-in receiving-end power grid stability carrying capacity prediction system, characterized in that, include: The data acquisition and preprocessing unit is used to acquire basic data of the flexible DC dense feed into the receiving-end power grid and preprocess it to obtain a structured input dataset; A robust computational model building unit is used to build a robust computational model of transient voltage-frequency coupling strength features based on the structured input dataset. The safety boundary fitting unit is used to fit the safety boundary envelope function corresponding to the total feed power and the safety threshold of the feature quantity within a preset total feed power search interval based on the robust calculation model of the transient voltage frequency coupling strength feature quantity. The iterative search solution unit is used to perform iterative search within the total feed-in power search interval, calculate the transient voltage frequency coupling strength characteristic quantity corresponding to the test power one by one, adjust the search interval after comparing the transient voltage frequency coupling strength characteristic quantity with the characteristic quantity safety threshold corresponding to the safety boundary envelope function, and obtain the upper limit of the receiving end power grid stability carrying capacity after the search interval converges. The graded assessment output unit is used to calculate the load factor based on the current total active power and the upper limit of the stable carrying capacity of the receiving end power grid, and to make a state graded determination based on the graded safety threshold and the load factor, and output the corresponding level of stable carrying capacity prediction result.

9. A computing device, characterized in that, include: Memory and processor; The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the method for predicting the stable carrying capacity of the receiving-end power grid as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing computer-executable instructions, characterized in that, When the computer-executable instructions are executed by the processor, they implement the steps of the method for predicting the stable carrying capacity of the receiving-end power grid as described in any one of claims 1 to 7.

Images