A method for evaluating the AC-DC fault ride-through capability of a flexible DC system based on combined weighting

Abstract

The present invention discloses a method for evaluating the AC-DC fault ride-through capability of a flexible DC system based on combined weighting, which includes the following steps: constructing a stable calculation sample set for evaluating the AC-DC fault ride-through capability; comprehensively considering the transient response process of the flexible DC system during a fault and its recovery capability after the fault is cleared, and also considering the support capability of the flexible DC system for the connected AC system, constructing an evaluation index system for the AC-DC fault ride-through capability of the flexible DC system; subjectively weighting and objectively weighting each evaluation index respectively to obtain the subjective weight and objective weight of each evaluation index; for each evaluation index, determining the optimal value of the combined weight of the evaluation index according to each subjective weight and objective weight; and according to the optimal values of the combined weights of each evaluation index, quantitatively evaluating the AC-DC fault ride-through capability of the flexible DC system for the stable calculation samples in the stable calculation sample set.

Description

Technical Field

[0001] The present invention relates to the technical field of power systems, and particularly relates to a method for evaluating the AC-DC fault ride-through capability of a flexible DC system based on combined weighting. Background Art

[0002] In the existing power transmission system, there is a problem of unbalanced development of new energy in different regions. A large amount of new energy electric energy mainly based on wind and light in some regions is transmitted to the load center over long distances on a large scale, which has become the main way to realize the comprehensive utilization of cross-regional new energy. However, some remote areas are at the end of the power grid, with a weak power grid structure and unable to provide sufficient support for the grid connection of new energy. It is necessary to adopt a flexible DC transmission dynamic compensation system to reactive power so as to adapt to the frequent fluctuations of new energy output. However, in a large-scale new energy transmission system via a flexible DC system, the occurrence of AC and DC faults may lead to the shutdown of power electronic devices in the converter station, further triggering cascading faults, which not only hinders the effective transmission and consumption of new energy electric energy, but also poses a threat to the safe and stable operation of the power system in severe cases. How to reliably and comprehensively evaluate the AC-DC fault ride-through capability of a flexible DC transmission system is one of the key challenges faced in the actual operation of the sending-end power grid.

[0003] At present, for the evaluation of the fault ride-through capability of a flexible DC transmission system, some methods have been proposed and applied in practice, but most of these methods have certain limitations. Traditional evaluation methods usually rely on static analysis, mainly focusing on parameters such as system power flow and node voltage after a fault occurs, and can provide certain system stability information. However, these methods ignore the dynamic behavior of the system in the initial stage and recovery process of the fault, and cannot comprehensively reflect the fault ride-through capability of the system. In addition, some methods establish accurate mathematical models, considering the dynamic response and transient process of the flexible DC transmission system after a fault occurs. Although these methods can simulate the short-term stability of the system and evaluate the fault ride-through capability, they often have a huge amount of calculation and are difficult to meet the evaluation requirements under large-scale power grids or complex working conditions. In addition, some studies have also introduced sensitivity analysis and multi-objective optimization strategies, aiming to explore the influence degree of various factors such as converter station control parameters when a system fault occurs. However, in the context of a multi-factor and complex system, it is difficult to correctly balance the importance of different indicators, which easily leads to one-sidedness of the evaluation results. Generally speaking, the existing evaluation methods mostly focus on local analysis in specific situations and lack comprehensive and systematic evaluation of the fault ride-through capability. Summary of the Invention

[0004] In view of this, the present invention provides a method for evaluating the AC-DC fault ride-through capability of a flexible DC system based on combined weighting, so as to at least solve the problem of the limitations in evaluating the fault ride-through capability of a flexible DC transmission system in dealing with complex systems in the prior art.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for evaluating the AC-DC fault ride-through ability of a flexible DC system based on combined weighting, comprising the following steps:

[0007] S1. Comprehensively considering various operation modes, fault scenarios, fault durations of the sending-end power grid, and different control modes of the sending-end flexible DC converter station, construct a stable calculation sample set for evaluating the AC-DC fault ride-through ability;

[0008] S2. Comprehensively considering the transient response process of the flexible DC system during the fault and the recovery ability after the fault clearance, and also considering the support ability of the flexible DC system to the connected AC system, construct an evaluation index system for the AC-DC fault ride-through ability of the flexible DC system;

[0009] S3. Subjectively and objectively weight each evaluation index in the evaluation index system for the AC-DC fault ride-through ability to obtain the subjective weight and objective weight of each evaluation index;

[0010] S4. For each evaluation index, determine the combined weight of the evaluation index according to each subjective weight and objective weight, and determine the optimal value of the combined weight with the minimum deviation value between the combined weight and the subjective weight and objective weight;

[0011] S5. According to the optimal value of the combined weight of each evaluation index, quantitatively evaluate the AC-DC fault ride-through ability of the flexible DC system for the stable calculation samples in the stable calculation sample set.

[0012] Preferably, the specific content of S1 includes:

[0013] Determine various operation modes of the sending-end power grid, where various operation modes include: setting different load levels, start-stop states of different generator sets, and different grid topologies, and record the operation mode as , , where represents the index of the operation mode of the sending-end power grid, is the total number of operation modes;

[0014] Simulate the fault scenarios in the vicinity of the sending-end flexible DC converter station, where the fault scenarios include three-phase short-circuit fault, single-phase short-circuit fault, DC line short-circuit, and DC line disconnection, and record the fault scenario as , where represents the index of the fault scenario, is the total number of fault scenarios;

[0015] Set different fault durations, and record the fault duration as , where The index indicating the fault duration is the total number of fault durations;

[0016] Set different control modes for the sending - end VSC - HVDC converter station, where the control modes include active - power - type and reactive - power - type control modes. Denote the control mode as where is the index of the converter - station control mode, and is the total number of converter - station control modes;

[0017] Batch - construct a stable - calculation sample set including different operation modes, fault scenarios, fault durations, and control modes of the sending - end VSC - HVDC converter station on the simulation platform , , where is the index of the stable - calculation sample set, and is the total number of stable - calculation samples.

[0018] Preferably, the specific content of the AC - DC fault - ride - through ability evaluation index system for the VSC - HVDC system in S2 includes: the AC fault - ride - through ability evaluation index and the DC fault - ride - through ability evaluation index;

[0019] AC fault - ride - through ability evaluation index Specifically:

[0020] After the fault occurs, the minimum value of the AC - side voltage relative to the AC rated voltage deviation degree:

[0021] ,

[0022] The maximum value of the AC - side voltage relative to the AC rated voltage deviation degree:

[0023] ,

[0024] During any period after the fault is cleared the integral value of the deviation of the AC - side voltage relative to the AC rated voltage :

[0025] ,

[0026] In the formula, is the fault - clearing time;

[0027] After the fault occurs, the minimum value of the DC - side voltage relative to the DC rated voltage Degree of deviation:

[0028] ,

[0029] Highest value of DC-side voltage Relative to the DC rated voltage Degree of deviation:

[0030] ,

[0031] During any period after fault clearing The DC-side voltage Relative to the DC rated voltage Integral value of the deviation:

[0032] ,

[0033] During the fault, the active power transmitted by the flexible DC system Relative to the steady-state value of the active power before the fault Maintenance ratio:

[0034] ,

[0035] In the formula, Is the moment when the fault occurs;

[0036] DC fault ride-through ability evaluation index Specifically:

[0037] During a period from the occurrence of the fault to after the fault clearing, the integral value of the DC fault current value Over time compared with the integral value of the steady-state DC current before the fault Over time ratio:

[0038] ,

[0039] After the fault occurs, the peak value of the DC fault current :

[0040] ,

[0041] Lowest value of DC-side voltage Relative to the DC rated voltage Degree of deviation:

[0042] ,

[0043] After the fault occurs, the highest value of the DC-side voltage Relative to the DC rated voltage Degree of deviation:

[0044] ,

[0045] At any time after the fault is cleared the DC side voltage relative to the DC rated voltage Integral value of the deviation:

[0046] ,

[0047] During the fault, the active power transmitted by the flexible DC system relative to the steady-state value of the active power before the fault Maintenance ratio:

[0048] .

[0049] Preferably, the specific content of subjectively weighting each evaluation index in S3 includes:

[0050] Subjectively weight the evaluation indexes by using the interval analytic hierarchy process (IAHP):

[0051] Construct a judgment interval for each pair of evaluation indexes, and construct an interval judgment matrix according to the judgment interval, where the judgment interval represents the importance range of the th evaluation index relative to the th evaluation index, represents the lower limit of the importance of the th evaluation index relative to the th evaluation index, represents the upper limit of the importance of the th evaluation index relative to the th evaluation index;

[0052] Conduct a consistency test on the constructed interval judgment matrix to ensure the rationality of the interval judgment matrix:

[0053] All the in the interval judgment matrix form a lower bound matrix, and all the form an upper bound matrix. Calculate the consistency test coefficient of the upper bound matrix and the consistency test coefficient of the lower bound matrix respectively. If and it means good consistency, where:

[0054] ,

[0055] ,

[0056] In the formula, represents the total number of evaluation indexes;

[0057] To check the consistency of the upper and lower bounds of the interval judgment matrix. If it is inconsistent, it means there are logical problems with the constructed interval judgment matrix, and then reconstruct or adjust the interval.

[0058] Based on the constructed interval judgment matrix, solve to obtain the subjective weight interval of each evaluation index, and select the midpoint of the interval as the subjective weight. 。

[0059] Preferably, the specific content of objectively assigning weights to each evaluation index in S3 includes:

[0060] Use the CRITIC objective weighting method to objectively assign values to the evaluation indexes:

[0061] Conduct time-domain simulation on the stable calculation sample set to obtain the data of each evaluation index of the flexible DC system under multiple scenarios, and standardize it to eliminate the influence of dimensions.

[0062] Calculate the standard deviation of each evaluation index according to the standardized data:

[0063] ,

[0064] In the formula, is the standard deviation of the th evaluation index, is the total number of stable calculation samples, is the value of the th evaluation index in the th sample, is the average value of the th evaluation index in all samples;

[0065] The correlation coefficient between each evaluation index:

[0066] ,

[0067] In the formula, is the correlation coefficient between the th evaluation index and the th evaluation index, is the covariance between the th and the th evaluation indexes, is the set of the th evaluation index in all samples;

[0068] The larger the standard deviation, the greater the difference of the evaluation index under different scenarios and the more information it contains;

[0069] The larger the correlation coefficient, the more the evaluation index And evaluation metrics The more information repetition it contains, the less useful information there is;

[0070] Calculate the evaluation metrics by combining the standard deviation and the correlation coefficient of the amount of information:

[0071] ,

[0072] wherein, is the amount of information of the th evaluation metric, is the total number of evaluation metrics;

[0073] The more the amount of information, the more useful information it contains. Then, solve the objective weight corresponding to each evaluation metric by combining the amount of information contained in the evaluation metrics:

[0074] ,

[0075] wherein, is the th objective weight of the evaluation metric.

[0076] Preferably, the specific content of S4 includes:

[0077] Take the minimum of the deviation between the combined weight and the subjective weight and the objective weight as the objective function, and obtain the optimal value of the combined weight through an optimization algorithm. The objective function is:

[0078] ,

[0079] wherein, represents the index of the evaluation metric, is the total number of evaluation metrics, is the optimal value of the combined weight obtained through the optimization algorithm.

[0080] Preferably, the specific content of S5 includes:

[0081] Calculate the comprehensive evaluation score of the AC fault ride-through ability and the DC fault ride-through ability for the stable calculation samples:

[0082] ,

[0083] ,

[0084] wherein, is the comprehensive evaluation score of the AC fault ride-through ability, the comprehensive evaluation score of the DC fault ride-through ability; Index for the evaluation index of AC fault ride-through capability Index for the evaluation index of DC fault ride-through capability Total number of evaluation indexes for AC fault ride-through capability Total number of evaluation indexes for DC fault ride-through capability

[0085] Compare the comprehensive scores under different control modes of the sending-end converter station, and further analyze the influence of the control mode on the AC and DC fault ride-through capabilities of the flexible DC system

[0086] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses a method for evaluating the AC and DC fault ride-through capabilities of a flexible DC system based on combined weighting, which has the following beneficial effects

[0087] By constructing an evaluation index system for AC and DC fault ride-through capabilities and adopting a combined weighting method, key performance indexes such as the steady-state characteristics, transient response, and fault recovery ability of the system are quantified and comprehensively analyzed; compared with the traditional method that only relies on subjective experience or numerical simulation for weighting, first of all, the present invention combines the professionalism of subjective experience weighting and the scientificity of objective information weighting, and makes the index weights more reasonable through an optimization algorithm, significantly improving the accuracy and applicability of the evaluation results; moreover, the evaluation index system of the present invention not only covers the voltage stability, dynamic response, and fault recovery ability on the AC side, but also considers the power maintenance ability and recovery time on the DC side, comprehensively reflecting the comprehensive performance of the flexible DC transmission system under AC and DC faults

[0088] At the same time, by using the combined weight optimization model based on the minimum information discrimination principle, the present invention effectively avoids the problem of information loss that may be caused by separate weighting, fully utilizes the expert's experience and knowledge, and quantifies the actual influence of each index on the fault ride-through ability

[0089] Through the present invention, power system operators can more comprehensively evaluate the fault adaptability of the flexible DC system, thereby optimizing the operation strategy, improving the safety and reliability of the system, and providing important technical support for the long-distance flexible DC transmission system with high-proportion new energy access BRIEF DESCRIPTION OF THE DRAWINGS

[0090] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts

[0091] Figure 1Flow chart of a method for evaluating the AC-DC fault ride-through capability of a flexible DC system based on combined weighting provided by the present invention;

[0092] Figure 2 Subjective-objective-combined weight comparison radar chart provided by an embodiment of the present invention, where Figure 2 (a) is a weight comparison chart of evaluation indexes for AC fault ride-through capability, Figure 2 (b) is a weight comparison chart of evaluation indexes for DC fault ride-through capability;

[0093] Figure 3 Scatter diagram of fault ride-through capability under different control modes generated by an embodiment of the present invention, where Figure 3 (a) is a scatter diagram of evaluation scores for AC fault ride-through capability under different control modes, Figure 3 (b) is a scatter diagram of evaluation scores for DC fault ride-through capability under different control modes. Detailed implementation manners

[0094] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0095] The present invention provides a method for evaluating the AC-DC fault ride-through capability of a flexible DC system based on combined weighting, as Figure 1 shown, including the following steps:

[0096] S1. Comprehensively considering various operation modes, fault scenarios, fault durations of the sending-end power grid, and different control modes of the sending-end flexible DC converter station, construct a stable calculation sample set for evaluating the AC-DC fault ride-through capability;

[0097] S2. Comprehensively considering the transient response process of the flexible DC system during the fault and the recovery ability after the fault clearance, and also considering the support ability of the flexible DC system to the connected AC system, construct an evaluation index system for the AC-DC fault ride-through capability of the flexible DC system;

[0098] S3. Subjectively and objectively weight each evaluation index in the evaluation index system for the AC-DC fault ride-through capability to obtain the subjective weight and objective weight of each evaluation index;

[0099] S4. For each evaluation index, determine the combined weight of the evaluation index according to each subjective weight and objective weight, and determine the optimal value of the combined weight with the minimum deviation value between the combined weight and the subjective weight and objective weight;

[0100] S5. Quantitatively evaluate the AC / DC fault ride-through capabilities of the stable calculation samples in the stable calculation sample set according to the optimal values of the combined weights of each evaluation index.

[0101] To further implement the above technical solution, the specific content of S1 includes:

[0102] Determine various operating modes of the sending-end power grid, where various operating modes include: setting different load levels, start-stop states of different generator sets, and different power grid topologies, and denote the operating mode as , , where represents the index of the operating mode of the sending-end power grid, is the total number of operating modes;

[0103] Simulate the fault scenarios in the vicinity of the sending-end flexible DC converter station, where the fault scenarios include three-phase short-circuit faults, single-phase short-circuit faults, DC line short-circuits, and DC line disconnections, and denote the fault scenario as , , where represents the index of the fault scenario, is the total number of fault scenarios;

[0104] Set different fault durations, and denote the fault duration as , , where represents the index of the fault duration, is the total number of fault durations;

[0105] Set different control modes for the sending-end flexible DC converter station, where the control modes include active power control modes and reactive power control modes, and denote the control mode as , , where represents the index of the converter station control mode, is the total number of converter station control modes;

[0106] Batch construct a stable calculation sample set including different operating modes, fault scenarios, fault durations, and control modes of the sending-end flexible DC converter station on the simulation platform , , , where represents the index of the stable calculation sample set, is the total number of stable calculation samples.

[0107] It should be noted that:

[0108] In this embodiment, 20 operation modes are constructed based on the PSD-BPA platform, simulating three-phase AC short-circuit faults occurring on three AC lines in the near area of the sending converter station, three-phase short-circuit faults on the AC side bus of the converter station, and single-pole grounding short-circuit faults on the flexible DC line. The fault duration is set in 6 groups [0.1s, 0.14s, 0.18s, 0.22s, 0.26s, 0.3s], and 3 control modes of the converter station are set in total [PQ control, PV control, VF control].

[0109] To further implement the above technical solution, the specific content of the AC-DC fault ride-through ability evaluation index system for the flexible DC system in S2 includes: AC fault ride-through ability evaluation index and DC fault ride-through ability evaluation index;

[0110] AC fault ride-through ability evaluation index Specifically:

[0111] After the fault occurs, the minimum value of the AC side voltage Relative to the AC rated voltage Degree of deviation:

[0112] ,

[0113] The maximum value of the AC side voltage Relative to the AC rated voltage Degree of deviation:

[0114] ,

[0115] During any period after the fault is cleared Inside, the AC side voltage Relative to the AC rated voltage Integral value of the deviation:

[0116] ,

[0117] In the formula, Is the fault clearing time;

[0118] After the fault occurs, the minimum value of the DC side voltage Relative to the DC rated voltage Degree of deviation:

[0119] ,

[0120] The maximum value of the DC side voltage Relative to the DC rated voltage Degree of deviation:

[0121] ,

[0122] During any period after fault clearance the integral value of the deviation of the DC-side voltage from the DC rated voltage is:

[0123] ,

[0124] During the fault, the active power transmitted by the flexible DC system compared with the steady-state value of the active power before the fault maintenance ratio:

[0125] ,

[0126] DC fault ride-through ability evaluation index Specifically:

[0127] During the period from fault occurrence to fault clearance, the integral value of the DC fault current over time compared with the integral value of the steady-state DC current before the fault over time ratio:

[0128] ,

[0129] After the fault occurs, the peak value of the DC fault current is:

[0130] ,

[0131] The minimum value of the DC-side voltage compared with the DC rated voltage degree of deviation:

[0132] ,

[0133] After the fault occurs, the maximum value of the DC-side voltage compared with the DC rated voltage degree of deviation:

[0134] ,

[0135] During any period after fault clearance the integral value of the deviation of the DC-side voltage from the DC rated voltage is:

[0136] ,

[0137] During the fault, the active power transmitted by the flexible DC system compared with the steady-state value of the active power before the fault maintenance ratio:

[0138] 。

[0139] It should be noted that:

[0140] In this embodiment, t in it takes 0.5 s, t in it takes 0.1 s.

[0141] To further implement the above technical solution, the specific content of subjectively assigning weights to each evaluation index in S3 includes:

[0142] Subjectively assign weights to the evaluation indexes by using the interval analytic hierarchy process (IAHP):

[0143] Construct a judgment interval for each pair of evaluation indexes, and construct an interval judgment matrix according to the judgment interval, where the judgment interval represents the importance range of the th evaluation index relative to the th evaluation index, represents the lower limit of the importance of the th evaluation index relative to the th evaluation index, represents the upper limit of the importance of the th evaluation index relative to the th evaluation index;

[0144] Conduct a consistency test on the constructed interval judgment matrix to ensure the rationality of the interval judgment matrix:

[0145] Form a lower bound matrix with all in the interval judgment matrix, and form an upper bound matrix with all . Calculate the upper bound matrix consistency test coefficient and the lower bound matrix consistency test coefficient respectively. If and , it means good consistency, where:

[0146] ,

[0147] ,

[0148] In the formula, represents the total number of evaluation indexes;

[0149] To test the consistency of the upper and lower bounds of the interval judgment matrix. If it is inconsistent, it means there are logical problems in the constructed interval judgment matrix, and the interval needs to be reconstructed or adjusted;

[0150] Based on the constructed interval judgment matrix, the subjective weight intervals of each evaluation index are solved, and the midpoint of the interval is selected as the subjective weight. 。

[0151] It should be noted that:

[0152] In this embodiment, first, an interval judgment matrix is constructed according to expert opinions, and then subsequent subjective weighting is completed.

[0153] To further implement the above technical solution, the specific content of objectively weighting each evaluation index in S3 includes:

[0154] Use the CRITIC objective weighting method to objectively assign values to the evaluation indexes:

[0155] Conduct time-domain simulation on the stable calculation sample set to obtain the data of each evaluation index of the flexible DC system under multiple scenarios, and standardize it to eliminate the influence of dimensions;

[0156] Calculate the standard deviation of each evaluation index according to the standardized data:

[0157] ,

[0158] In the formula, is the standard deviation of the th evaluation index, is the total number of stable calculation samples, is the value of the th sample for the th evaluation index, is the average value of the th evaluation index among all samples;

[0159] The correlation coefficient between each evaluation index:

[0160] ,

[0161] In the formula, is the correlation coefficient between the th evaluation index and the th evaluation index, is the covariance between the th and the th evaluation index, is the set of the th evaluation index in all samples;

[0162] The larger the standard deviation, the greater the difference of the evaluation index in different scenarios and the more information it contains;

[0163] The larger the correlation coefficient, the more the evaluation index And evaluation metrics The more information repetition it contains, the less useful information there is;

[0164] Calculate the evaluation metrics by combining the standard deviation and the correlation coefficient of the amount of information:

[0165] ,

[0166] In the formula, is the amount of information of the th evaluation metric, is the total number of evaluation metrics;

[0167] The more information there is, the more useful information it contains. Then, solve the objective weight corresponding to each evaluation metric by combining the amount of information contained in the evaluation metrics:

[0168] ,

[0169] In the formula, is the objective weight of the th evaluation metric.

[0170] To further implement the above technical solution, the specific content of S4 includes:

[0171] Take the deviation between the combined weight and the subjective weight and the objective weight as the objective function, and obtain the optimal value of the combined weight through an optimization algorithm. The objective function is:

[0172] ,

[0173] In the formula, represents the index of the evaluation metric, is the total number of evaluation metrics, is the optimal value of the combined weight obtained through the optimization algorithm.

[0174] It should be noted that:

[0175] The subjective-objective-combined weight comparison radar chart generated in this embodiment is as shown in Figure 2 . Figure 2 Plot the three weights of the same set of evaluation metrics (the subjective weight obtained by the interval analytic hierarchy process, the objective weight obtained based on the CRITIC method, and the combined weight obtained by the optimization algorithm with the minimum deviation between the subjective and objective weights) in the radar chart to reflect the differences under the three weight allocation methods, Figure 2 (a) is the weight comparison chart of the AC fault ride-through ability evaluation metric, Figure 2(b) is the comparison chart of the weights of the DC fault ride-through ability evaluation indexes; it can be seen from the figure that the combined weights are basically between the subjective and objective weights, effectively balancing the subjective and objective limitations in empowerment.

[0176] To further implement the above technical solution, the specific content of S5 includes:

[0177] Calculate the comprehensive evaluation scores of the AC fault ride-through ability and the DC fault ride-through ability for the steady-state calculation samples:

[0178] ,

[0179] ,

[0180] where, is the comprehensive evaluation score of the AC fault ride-through ability, the comprehensive evaluation score of the DC fault ride-through ability; is the index of the AC fault ride-through ability evaluation index, the index of the DC fault ride-through ability evaluation index; is the total number of AC fault ride-through ability evaluation indexes, is the total number of DC fault ride-through ability evaluation indexes;

[0181] Compare the comprehensive scores under different control modes of the sending-end converter station, further analyze the influence of the control mode on the AC and DC fault ride-through abilities of the flexible DC system, so as to enhance the fast response and recovery abilities of the flexible DC system under faults, and provide reliable technical support for the access of high-proportion new energy and cross-regional long-distance power transmission.

[0182] It should be noted that:

[0183] The scatter diagrams of the fault ride-through abilities under different control modes obtained in this embodiment are as Figure 3 shown, Figure 3 Based on the combined weights obtained previously, calculate the fault ride-through ability scores of each steady-state calculation sample, classify each sample according to the control mode adopted by the flexible DC converter station (PQ control: constant active power, constant reactive power; PV control: constant active power, constant AC voltage; VF control: constant AC voltage, frequency), and reflect the advantages and disadvantages of the control mode through the form of scatter diagrams. It can be seen from the results that in the embodiment of the present invention, when the PQ control mode is adopted, the AC and DC fault ride-through abilities of the flexible DC system are relatively higher.

[0184] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A method for evaluating the AC and DC fault ride-through capability of a flexible DC system based on combined weighting, characterized in that: The following steps are involved: S1. Comprehensively consider various operation modes, fault scenarios, fault durations of the sending-end power grid and different control modes of the sending-end flexible DC converter station, and construct a stable calculation sample set for AC / DC fault ride-through capability assessment; S2. Comprehensively consider the transient response process of the flexible DC system during the fault period and its recovery capability after the fault is cleared, and also consider the support capability of the flexible DC system to the connected AC system, and construct an AC / DC fault ride-through capability evaluation index system for the flexible DC system; S3. Subjectively and objectively weight each evaluation indicator in the AC / DC fault ride-through capability evaluation index system to obtain a subjective weight and an objective weight for each evaluation indicator; S4. For each evaluation indicator, determine the combined weight of the evaluation indicators according to each subjective weight and objective weight, and determine the optimal value of the combined weight by minimizing the deviation between the combined weight and the subjective weight and the objective weight; S5. According to the optimal value of the combined weight of each evaluation index, the stable calculation samples in the stable calculation sample set are quantitatively evaluated for the AC and DC fault ride-through capability of the flexible DC system.

2. According to the combined weighted method for evaluating the AC / DC fault ride-through capability of a flexible DC system according to claim 1, it is characterized in that: The specific contents of S1 include: Determine various operation modes of the sending-end power grid, including: setting different load levels, starting and stopping states of different generator sets and different power grid topologies. The operation modes are recorded as , ,in An index indicating the operation mode of the power grid at the sending end. is the total number of operating modes; The fault scenarios near the sending-end flexible DC converter station are simulated, including three-phase short circuit fault, single-phase short circuit fault, DC line short circuit and DC line disconnection. The fault scenarios are recorded as ,in The index of the fault scenario. is the total number of failure scenarios; Set different fault durations, and record the fault duration as ,in An index representing the duration of the fault, is the total number of fault durations; Different control modes of the sending-end flexible DC converter station are set, where the control modes include active power control mode and reactive power control mode. The control modes are recorded as ,in The index indicating the control mode of the converter station. is the total number of converter station control modes; Batch build stable calculation sample sets including different operation modes, fault scenarios, fault durations and control methods of the sending-end flexible DC converter station on the simulation platform , , ,in represents the index of the stable calculation sample set, The total number of samples is calculated for stability.

3. The method for evaluating the AC / DC fault ride-through capability of a flexible DC system based on combined weighting according to claim 1 is characterized in that: The specific contents of the AC / DC fault ride-through capability evaluation index system of the flexible DC system in S2 include: AC fault ride-through capability evaluation index and DC fault ride-through capability evaluation index; AC Fault Ride-Through Capability Evaluation Indicators Specifically: After the fault occurs, the lowest voltage on the AC side Relative to rated AC voltage The degree of deviation: ， Maximum AC voltage Relative to rated AC voltage The degree of deviation: ， Any time after the fault is cleared Internal, AC side voltage Relative to rated AC voltage The integral value of the deviation is: ， In the formula, It is the moment of fault clearing; After the fault occurs, the DC side voltage minimum value Relative to DC rated voltage The degree of deviation: ， Maximum DC voltage Relative to DC rated voltage The degree of deviation: ， Any time after the fault is cleared Internal, DC side voltage Relative to DC rated voltage The integral value of the deviation is: ， During a fault, the flexible DC system delivers active power Relative to the steady-state value of active power before the fault Maintenance ratio: ， In the formula, is the time when the fault occurs; DC Fault Ride-Through Capability Evaluation Index Specifically: The DC fault current value during the period from when the fault occurs to when the fault is cleared. The integral value over time and the steady-state value of DC current before the fault Ratio of the integrated values ​​over time: ， After the fault occurs, the DC fault current peak : ， Minimum DC voltage Relative to DC rated voltage The degree of deviation: ， After the fault occurs, the maximum voltage on the DC side is Relative to DC rated voltage The degree of deviation: ， Any time after the fault is cleared Internal, DC side voltage Relative to DC rated voltage The integral value of the deviation is: ， During a fault, the flexible DC system delivers active power Relative to the steady-state value of active power before the fault Maintenance ratio: 。 4. The method for evaluating the AC / DC fault ride-through capability of a flexible DC system based on combined weighting according to claim 3 is characterized in that: The specific contents of subjective weighting of each evaluation indicator in S3 include: The interval analytic hierarchy process (IAHP) is used to subjectively weight the evaluation indicators: Select any two evaluation indicators from the AC fault ride-through capability evaluation indicators or the DC fault ride-through capability evaluation indicators as a pair of evaluation indicators; For each pair of evaluation indicators, a judgment interval is constructed, and an interval judgment matrix is ​​constructed based on the judgment interval, where the judgment interval Indicates The evaluation index is relative to The importance range of the evaluation indicators is Indicates The evaluation index is relative to The lower limit of the importance of the evaluation index is Indicates The evaluation index is relative to The upper limit of the importance of the evaluation indicators; Perform consistency check on the constructed interval judgment matrix to ensure the rationality of the interval judgment matrix: All the interval judgment matrix Form the lower bound matrix, all Form an upper bound matrix and calculate the upper bound matrix consistency test coefficients respectively and the lower bound matrix consistency test coefficient ,like and This indicates good consistency, where: ， ， In the formula, Indicates the total number of evaluation indicators; To check the consistency of the upper and lower bounds of the interval judgment matrix. If they are inconsistent, it means that there is a logical problem in the constructed interval judgment matrix, and the interval should be reconstructed or adjusted; Based on the constructed interval judgment matrix, the subjective weight interval of each evaluation indicator is solved and the midpoint of the interval is selected as the subjective weight .

5. The method for evaluating the AC and DC fault ride-through capability of a flexible DC system based on combined weighting according to claim 1 is characterized in that: The specific contents of objectively weighting each evaluation indicator in S3 include: Use the CRITIC objective weighting method to objectively assign values ​​to evaluation indicators: Perform time-domain simulation on the stable calculation sample set to obtain data on various evaluation indicators of the flexible DC system under multiple scenarios, and standardize them to eliminate the dimensional effect; Calculate the standard deviation of each evaluation indicator based on the standardized data: ， In the formula, For the The standard deviation of the evaluation index, To stabilize the total number of samples, For the In the sample The value of the evaluation indicator, For the The average value of the evaluation indicators in all samples; Correlation coefficients among evaluation indicators: ， In the formula, For the The evaluation indicators and The correlation coefficient of the evaluation indicators is For the and The covariance of the evaluation indicators, For the The set of evaluation indicators in all samples; The larger the standard deviation, the greater the difference in the evaluation indicator in different scenarios, and the more information it contains; The larger the correlation coefficient, the better the evaluation index And evaluation indicators The more repetitive the information contained, the less useful information there is; Calculate the evaluation index by combining the standard deviation and correlation coefficient Amount of information: ， In the formula, For the The amount of information of the evaluation index, is the total number of evaluation indicators; The more information, the more useful information it contains. Then, the objective weight corresponding to each evaluation indicator is obtained by combining the information contained in the evaluation indicator: ， In the formula, For the The objective weight of each evaluation indicator.

6. The method for evaluating the AC and DC fault ride-through capability of a flexible DC system based on combined weighting according to claim 1 is characterized in that: The specific contents of S4 include: Combined weight and subjective weight and objective weight Deviation The minimum is used as the objective function, and the optimal value of the combined weight is obtained through the optimization algorithm. The objective function is: ， In the formula, represents the index of the evaluation metric, is the total number of evaluation indicators, To obtain the optimal value of the combined weight through the optimization algorithm.

7. The method for evaluating the AC and DC fault ride-through capability of a flexible DC system based on combined weighting according to claim 1 is characterized in that: The specific contents of S5 include: The comprehensive evaluation scores of AC fault ride-through capability and DC fault ride-through capability calculated for the stable calculation samples are as follows: ， ， In the formula, is the comprehensive evaluation score of AC fault ride-through capability. Comprehensive evaluation score of DC fault ride-through capability; is the index of AC fault ride-through capability evaluation index, Index of DC fault ride-through capability evaluation indicators; is the total number of AC fault ride-through capability evaluation indicators, is the total number of DC fault ride-through capability evaluation indicators; The comprehensive scores under different control modes of the sending-end converter station are compared, and the influence of the control mode on the AC / DC fault ride-through capability of the flexible DC system is further analyzed.

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