A flexible direct-current converter valve reliability evaluation method and system based on sub-module cross communication

Abstract

The application discloses a flexible direct-current converter valve reliability evaluation method and system based on sub-module cross communication, which is applied to the technical field of high-voltage flexible direct-current transmission engineering, and comprises the following steps: performing fault logic construction processing on a plurality of sub-modules of a target flexible direct-current converter valve to obtain a sub-module fault tree; determining sub-module fault probability simulation parameters based on the sub-module fault tree; inputting the sub-module fault probability simulation parameters into a constructed reliability estimation model for processing to obtain reliability evaluation parameters of the target flexible direct-current converter valve; and generating a reliability evaluation result of the target flexible direct-current converter valve by using the reliability evaluation parameters and feature distribution parameters of the target flexible direct-current converter valve. The method provided in the application can solve the technical problem that the redundancy configuration of sub-modules and the dynamic process of random failure of a large number of sub-modules cannot be accurately considered in the prior art.

Description

Technical Field

[0001] This invention relates to the field of high-voltage flexible DC transmission engineering technology, and in particular to a method and system for evaluating the reliability of flexible DC converter valves based on submodule cross-communication. Background Technology

[0002] Converter valves are core components of flexible DC transmission systems, undertaking crucial tasks such as AC / DC conversion, power transmission control, and reactive power support. Currently, the reliability of converter valves in flexible DC transmission projects is critical to the overall reliability of the entire system.

[0003] In existing technologies, most reliability block diagram methods are used to assess the reliability of converter valves. This method simplifies the converter valve into a block diagram connected by logical relationships such as series and parallel connections, and treats the whole as a black box to assess the reliability of the converter valve. However, this method ignores the problem of redundant configuration of sub-modules and the dynamic process of random failure of a large number of sub-modules, and therefore cannot accurately assess the reliability of the converter valve. Summary of the Invention

[0004] This invention provides a method and system for evaluating the reliability of flexible DC converter valves based on submodule cross-communication. It solves the technical problems in the prior art that cannot accurately consider the redundant configuration of submodules and the dynamic process of random failure of a large number of submodules. It realizes a more accurate and dynamic evaluation of the reliability of converter valves, thereby providing more reliable data support for the design and operation and maintenance of flexible DC transmission systems.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a reliability evaluation method for flexible DC converter valves based on submodule cross-communication, the method comprising: Fault logic is constructed and processed for several sub-modules of the target flexible DC converter valve to obtain the sub-module fault tree; Based on the submodule fault tree, submodule failure probability simulation parameters are determined, wherein the submodule failure probability simulation parameters include at least the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for normal operation of the bridge arm; The simulation parameters of the submodule failure probability are input into the constructed reliability prediction model for processing to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm. The reliability evaluation result of the target flexible DC converter valve is generated using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

[0006] As one preferred embodiment, the fault logic construction process for several sub-modules of the target flexible DC converter valve is performed to obtain a sub-module fault tree, including: Failure Mode and Effects Analysis (FMEA) was used to process several sub-modules of the target flexible DC converter valve to obtain a list of failure modes. The fault mode list is processed to construct a fault tree, resulting in the fault tree of the submodule.

[0007] As one preferred embodiment, determining the submodule failure probability simulation parameters based on the submodule fault tree includes: Obtain fault parameter data of several sub-modules in the target flexible DC converter valve; Qualitative analysis is performed on the fault tree of the submodule to obtain the minimum cut set; Based on the principle of inclusion-exclusion, the fault parameter data of the minimum cut set and several sub-modules are processed to obtain the fault probability simulation parameters of the sub-modules.

[0008] As one preferred embodiment, the process of constructing the reliability prediction model includes: Obtain the total number of actual sub-modules of the target flexible DC converter valve and the minimum number of sub-modules required to maintain normal operation; Based on simulation technology, the total number of actual submodules and the minimum number of submodules are processed to obtain the reliability prediction model.

[0009] As one preferred embodiment, the step of generating the reliability evaluation result of the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve includes: The reliability assessment parameters are compared and analyzed to obtain the reliability level of the target flexible DC converter valve; Uncertainty analysis is performed on the characteristic distribution parameters to obtain the influence confidence interval; Based on the influence confidence interval and the reliability level of the target flexible DC converter valve, the reliability evaluation result of the target flexible DC converter valve is obtained.

[0010] Another embodiment of the present invention provides a reliability evaluation system for flexible DC converter valves based on submodule cross-communication, the system comprising: A construction module is used to construct fault logic for several sub-modules of the target flexible DC converter valve, and obtain the fault tree of the sub-modules. The determination module is used to determine the submodule failure probability simulation parameters based on the submodule fault tree, wherein the submodule failure probability simulation parameters include at least the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for normal operation of the bridge arm; The processing module is used to input the simulation parameters of the submodule failure probability into the constructed reliability prediction model for processing, so as to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm. The generation module is used to generate a reliability evaluation result for the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

[0011] As one preferred embodiment, the fault logic construction process for several sub-modules of the target flexible DC converter valve is performed to obtain a sub-module fault tree, including: Failure Mode and Effects Analysis (FMEA) was used to process several sub-modules of the target flexible DC converter valve to obtain a list of failure modes. The fault mode list is processed to construct a fault tree, resulting in the fault tree of the submodule.

[0012] As one preferred embodiment, determining the submodule failure probability simulation parameters based on the submodule fault tree includes: Obtain fault parameter data of several sub-modules in the target flexible DC converter valve; Qualitative analysis is performed on the fault tree of the submodule to obtain the minimum cut set; Based on the principle of inclusion-exclusion, the fault parameter data of the minimum cut set and several sub-modules are processed to obtain the fault probability simulation parameters of the sub-modules.

[0013] As one preferred embodiment, the process of constructing the reliability prediction model includes: Obtain the total number of actual sub-modules of the target flexible DC converter valve and the minimum number of sub-modules required to maintain normal operation; Based on simulation technology, the total number of actual submodules and the minimum number of submodules are processed to obtain the reliability prediction model.

[0014] As one preferred embodiment, the step of generating the reliability evaluation result of the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve includes: The reliability assessment parameters are compared and analyzed to obtain the reliability level of the target flexible DC converter valve; Uncertainty analysis is performed on the characteristic distribution parameters to obtain the influence confidence interval; Based on the influence confidence interval and the reliability level of the target flexible DC converter valve, the reliability evaluation result of the target flexible DC converter valve is obtained.

[0015] Compared with the prior art, the beneficial effects of the embodiments of the present invention are at least one of the following: This invention constructs a fault tree for several sub-modules of a target flexible DC converter valve by performing fault logic construction processing. Based on the sub-module fault tree, simulation parameters for sub-module fault probability are determined. These simulation parameters include at least the sub-module fault probability, the number of bridge arm sub-modules, and the minimum number of sub-modules required for normal operation of the bridge arm. The simulation parameters are then input into a pre-constructed reliability prediction model for processing to obtain reliability evaluation parameters for the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform cyclic processing on the sub-module groups and to judge the target flexible DC converter valve. The judgment process is based on the sub-module fault probability, the number of bridge arm sub-modules, and the minimum number of sub-modules required for normal operation of the bridge arm. Finally, the reliability evaluation result of the target flexible DC converter valve is generated using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

[0016] Compared with existing technologies, this invention constructs a submodule fault tree to finely characterize the internal fault logic of the converter valve, thereby overcoming the shortcomings of the reliability block diagram method, which treats the converter valve as a black box, at the model level. It directly reflects the redundant configuration of the submodule. Subsequently, it extracts key parameters (submodule failure probability, total number of bridge arm submodules, and minimum number required for normal operation) to quantify this redundant design. Then, it uses Monte Carlo simulation as the core processing method, and through random sampling and cyclic simulation, it dynamically reproduces the gradual process of random failure of submodules in actual operation and judges the system status in real time.

[0017] The core of this solution is Monte Carlo simulation, which uses a large number of random samples to dynamically simulate the random failures that may occur in each submodule during its service life and their cumulative effects. It can capture the changes in system state over time and achieve dynamic evaluation, and the results are more in line with engineering practice. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the reliability evaluation method for a flexible DC converter valve based on submodule cross-communication in one embodiment of the present invention. Figure 2This is a schematic diagram of the structure of a flexible DC converter valve reliability evaluation system based on submodule cross-communication in one embodiment of the present invention; Figure label: Among them, 11 is the construction module; 12 is the determination module; 13 is the processing module; and 14 is the generation module. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0020] In the description of this invention, it should be noted that, unless otherwise defined, all technical and scientific terms used in this invention have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0021] One embodiment of the present invention provides a reliability evaluation method for flexible DC converter valves based on submodule cross-communication. For details, please refer to [link to relevant documentation]. Figure 1 , Figure 1 The diagram shown is a flowchart illustrating a method for evaluating the reliability of a flexible DC converter valve based on submodule cross-communication, according to one embodiment of the present invention. The method includes: S1: Perform fault logic construction on several sub-modules of the target flexible DC converter valve to obtain the sub-module fault tree; S2: Based on the submodule fault tree, determine the submodule fault probability simulation parameters, wherein the submodule fault probability simulation parameters include at least the submodule fault probability, the number of bridge arm submodules, and the minimum number of submodules required for normal operation of the bridge arm; S3: Input the simulation parameters of the submodule failure probability into the constructed reliability prediction model for processing to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm. S4: Generate the reliability evaluation result of the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

[0022] Furthermore, fault logic construction processing is performed on several sub-modules of the target flexible DC converter valve to obtain a sub-module fault tree, including: processing several sub-modules of the target flexible DC converter valve using failure mode and effects analysis technology to obtain a fault mode list; and performing fault tree construction processing on the fault mode list to obtain the sub-module fault tree.

[0023] Specifically, failure mode and effects analysis (FMEA) techniques are used to process several sub-modules of the target flexible DC converter valve to obtain a list of failure modes. Each sub-module is decomposed into its basic components, such as insulated gate bipolar transistors (IGBTs), capacitors, sensors, control units, and power supplies. For each component, all possible failure modes are systematically analyzed and recorded, such as IGBT breakdown, capacitor capacitance decay, and sensor signal drift. For each failure mode, the causes, local effects on the component itself, and how these effects propagate upwards to ultimately lead to the system-level failure of the sub-module are further analyzed. This process generates a comprehensive and structured list of failure modes.

[0024] Define the top event of a submodule's complete loss of functionality as the root node of the fault tree. Then, starting from the top event, perform deductive analysis from top to bottom, find all fault modes or fault combinations that can directly lead to the occurrence of the top event from the fault mode list, and connect them using logic gates such as AND gates and OR gates. This process iterates downwards level by level until the end of all branches is the most basic fault event that does not need to be further decomposed, thus obtaining the submodule fault tree.

[0025] Furthermore, based on the submodule fault tree, the simulation parameters for submodule fault probability are determined, including: acquiring fault parameter data of several submodules in the target flexible DC converter valve; performing qualitative analysis on the submodule fault tree to obtain a minimum cut set; and processing the minimum cut set and the fault parameter data of several submodules based on the principle of inclusion-exclusion to obtain the simulation parameters for submodule fault probability.

[0026] Specifically, reliability data of components corresponding to the underlying basic events of the submodule fault tree are collected from component manufacturers' datasheets, historical maintenance records, laboratory accelerated life tests, or industry standard databases. Examples include the failure rate of insulated gate bipolar transistors and the mean time between failures (MTBF) of capacitors.

[0027] Using a fault tree analysis algorithm, starting from the top event representing a submodule failure, all logic gates are traversed from top to bottom to find the minimum combination of basic events that can lead to the top event. Each minimal cut set is the smallest set in which the simultaneous failure of a group of components will inevitably cause the submodule to lose its function. By accurately locating the critical path and weak points of submodule reliability, the complex fault tree is simplified into a set of the most critical failure combinations.

[0028] Then, using the minimal cut sets and the obtained component failure probability data, the probability of each minimal cut set occurring is calculated.

[0029] Since there may be overlapping basic events between different minimal cut sets, and their occurrence is not mutually exclusive, directly adding them together would overestimate the probability of system failure. Therefore, it is necessary to apply the probability theory method of inclusion-exclusion principle, and use alternating addition and subtraction operations to accurately calculate the probability of the union of all minimal cut sets, thereby obtaining the overall failure probability of the submodule.

[0030] By overcoming the overlap effect between minimal cut sets, the overall failure probability of the submodule can be accurately calculated. This calculated probability value is the accurate and reliable simulation parameter for the submodule failure probability required for subsequent Monte Carlo simulation.

[0031] The simulation parameters of the submodule failure probability are input into the constructed reliability prediction model for processing to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm.

[0032] Specifically, set the total number of cycles, for example, 100,000 times, with each cycle simulating a specific operating time or a complete life cycle of the converter valve.

[0033] It should be noted that at the start of each loop, all submodules are in a normal state.

[0034] Next, in each loop, the fault status of each submodule is sampled. The model generates a random number between zero and one for the submodule. If the random number is less than the preset fault probability of the submodule, the submodule is determined to have failed in this loop; otherwise, the submodule remains normal.

[0035] The established reliability prediction model will count the number of normal submodules on each bridge arm, compare the counted number of normal submodules with the minimum number of submodules required for the normal operation of that bridge arm, and if the number of normal submodules on a bridge arm is lower than its minimum requirement, then the bridge arm is determined to have failed.

[0036] The status of the entire converter valve is determined by the status of the bridge arms. In a typical flexible DC converter valve, all bridge arms are usually required to be normal in order to ensure the overall function of the system. Therefore, if any bridge arm is determined to be in failure, this cycle is recorded as a system-level failure of the entire converter valve.

[0037] After all cycles are completed, the model performs data statistics. Reliability assessment parameters are calculated by statistically analyzing the results of all cycles. For example, the reliability of the converter valve is equal to the proportion of cycles in which no system failure occurs to the total number of cycles. Parameters such as mean time between failures (MTBF) are obtained by statistically averaging the time of the first system failure in each cycle.

[0038] In addition, the total number of actual sub-modules of the target flexible DC converter valve and the minimum number of sub-modules required to maintain normal operation are obtained; based on simulation technology, the total number of actual sub-modules and the minimum number of sub-modules are processed to obtain the reliability prediction model.

[0039] Specifically, based on the engineering design drawings and technical specifications of the converter valve, the total number of sub-modules installed on each bridge arm is directly extracted and denoted as N.

[0040] At the same time, based on its control and protection strategy and power transmission requirements, the minimum number of sub-modules required to ensure the normal operation of the bridge arm and the entire converter valve is determined, denoted as K.

[0041] The difference between N and K directly quantifies the number of faulty submodules that the system can tolerate, i.e., redundancy capacity, which is the basis for accurately assessing reliability.

[0042] Based on simulation technology, the total number and minimum number of submodules are processed to obtain a reliability prediction model. Specifically, a computer simulation model is constructed with N and K as key input parameters. The core logic of this model is to determine whether the number of normally functioning submodules is always greater than or equal to K under random failures. Monte Carlo simulation technology is implemented as the processing engine of this model. It simulates the dynamic change in the number of available submodules in a bridge arm containing N submodules due to random failures during actual operation through a large number of random sampling cycles.

[0043] Furthermore, the reliability evaluation result of the target flexible DC converter valve is generated using the reliability assessment parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve. This includes: performing comparative analysis on the reliability assessment parameters to obtain the reliability level of the target flexible DC converter valve; performing uncertainty analysis on the characteristic distribution parameters to obtain the influence confidence interval; and obtaining the reliability evaluation result of the target flexible DC converter valve based on the influence confidence interval and the reliability level of the target flexible DC converter valve.

[0044] Specifically, key indicators calculated by Monte Carlo simulation, such as system reliability or mean time between failures, are compared with industry standards, design specifications, or benchmark values ​​of similar advanced equipment. Through this horizontal or vertical comparison, the relative position of the converter valve's reliability within a specific range can be objectively determined, such as whether it meets the standard or is at a leading level.

[0045] Next, statistical methods are used to handle the random fluctuations of characteristic parameters such as submodule failure rate and environmental stress factor, calculate the standard deviation and confidence level of each parameter, and deduce the diffusion range of the uncertainty of these parameters on the final reliability assessment result through the error propagation model to form a confidence interval.

[0046] To integrate reliability level and confidence interval analysis, if the reliability level is in the high part of the confidence interval and the interval width is narrow, the evaluation result is considered to have high credibility; if the level is too low or the interval is too wide, additional data or model adjustments are required.

[0047] In another embodiment, the failure modes and criteria of the converter valve and submodule group are first analyzed to determine the evaluation boundaries, objectives, and key input parameters. Secondly, a precise fault logic model is established at the submodule group level to quantify the probability of its three output states. Subsequently, at the bridge arm system level, based on these state probabilities, statistical simulation is used to evaluate the reliability of the entire redundant system. The specific implementation of the method includes the following three main stages and five steps: Phase 1: System Definition and Failure Analysis (I) System Failure Mode and Criterion Analysis First, the evaluation object is defined. The MMC converter valve system consists of a three-phase, six-arm bridge, with each arm containing n submodules and one arm reactor, where k is the minimum number of submodules required to maintain arm function, and the redundancy is nk. Second, based on the redundancy design of cross-communication between submodules, its failure modes are analyzed, namely: submodules are bypassed and disconnected due to hardware, control, or communication failures. Finally, the system failure criteria are defined: when the total number of submodules disconnected due to failure in any arm exceeds the redundancy nk, that arm is considered to have failed; when any arm fails, the entire converter valve system is considered to have failed. This step determines the evaluation boundaries, objectives, and key input parameters.

[0048] Phase Two: Submodule Group-Level Reliability Quantification (Based on Fault Tree Analysis) (II) Fault Tree Logic Model Establishment Based on the submodule topology and the logical structure between submodule groups, fault tree logic models are established for submodule groups with one submodule removed and submodule groups with two submodules removed, respectively. This step only qualitatively analyzes the logical relationships of fault propagation and does not involve numerical calculations.

[0049] (III) Fault Tree Calculation Based on the two fault tree logic models established in step (II), the failure rate data of each basic component (such as IGBT, capacitor, optical fiber, etc.) are input. The probability R1 of one submodule being removed and the probability R2 of two submodules being removed are obtained using quantitative fault tree analysis methods (such as the minimum cut set method). Then, through logical operations, the probability r1 = R1 - R2 of only one submodule being removed and the probability r2 = R2 of two submodules being removed are obtained. This step provides crucial and accurate input parameters for subsequent system-level evaluation.

[0050] Phase 3: System-level reliability assessment (based on Monte Carlo simulation) (iv) Reliability simulation of bridge arm submodule system Using r1 and r2, output from step (iii), as core input parameters, a large number of random scenarios are simulated using the Monte Carlo method with random numbers assigned. In each scenario, each submodule group is randomly assigned a fault state (0, 1, or 2 faulty submodules) based on r1 and r2, and the total number of faulty submodules in the entire bridge arm is counted. Finally, the failure probability of the bridge arm submodule system is calculated by counting the number of system failures. This step effectively transforms a complex deterministic combinatorial problem into a solvable stochastic statistical problem.

[0051] (v) Overall System Reliability Assessment Based on the failure probability of the combined arm submodule system and the reliability of the arm reactor, the reliability of the entire converter valve is calculated using a series system model.

[0052] The innovation of this invention is reflected in the evaluation model and process: By nesting and coordinating the precise quantification at the component level using the fault tree method and the efficient statistics at the system level using the Monte Carlo method, a complete and targeted reliability evaluation chain is constructed, thereby realizing an accurate and feasible evaluation of the reliability of MMC converter valve systems that consider cross-communication.

[0053] This is not a simple combination of two methods, but an organic whole designed to solve a specific technical problem.

[0054] Another embodiment of the present invention provides a reliability evaluation system for flexible DC converter valves based on submodule cross-communication. For details, please refer to [link to relevant documentation]. Figure 2 , Figure 2 The diagram shown is a structural schematic of a flexible DC converter valve reliability evaluation system based on submodule cross-communication in one embodiment of the present invention. The system includes: Module 11 is used to construct fault logic for several sub-modules of the target flexible DC converter valve to obtain the sub-module fault tree; The determination module 12 is used to determine the submodule failure probability simulation parameters based on the submodule fault tree, wherein the submodule failure probability simulation parameters include at least the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for normal operation of the bridge arm; The processing module 13 is used to input the simulation parameters of the submodule failure probability into the constructed reliability prediction model for processing, so as to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm. The generation module 14 is used to generate a reliability evaluation result of the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

[0055] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. A reliability evaluation method for flexible DC converter valves based on submodule cross-communication, characterized in that, include: Fault logic is constructed and processed for several sub-modules of the target flexible DC converter valve to obtain the sub-module fault tree; Based on the submodule fault tree, submodule failure probability simulation parameters are determined, wherein the submodule failure probability simulation parameters include at least the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for normal operation of the bridge arm; The simulation parameters of the submodule failure probability are input into the constructed reliability prediction model for processing to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm. The reliability evaluation result of the target flexible DC converter valve is generated using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

2. The reliability evaluation method for flexible DC converter valves based on submodule cross-communication as described in claim 1, characterized in that, The fault logic construction process for several sub-modules of the target flexible DC converter valve is performed to obtain a sub-module fault tree, including: Failure Mode and Effects Analysis (FMEA) was used to process several sub-modules of the target flexible DC converter valve to obtain a list of failure modes. The fault mode list is processed to construct a fault tree, resulting in the fault tree of the submodule.

3. The reliability evaluation method for flexible DC converter valves based on submodule cross-communication as described in claim 1, characterized in that, The step of determining the submodule failure probability simulation parameters based on the submodule fault tree includes: Obtain fault parameter data of several sub-modules in the target flexible DC converter valve; Qualitative analysis is performed on the fault tree of the submodule to obtain the minimum cut set; Based on the principle of inclusion-exclusion, the fault parameter data of the minimum cut set and several sub-modules are processed to obtain the fault probability simulation parameters of the sub-modules.

4. The reliability evaluation method for flexible DC converter valves based on submodule cross-communication as described in claim 1, characterized in that, The process of constructing the reliability prediction model includes: Obtain the total number of actual sub-modules of the target flexible DC converter valve and the minimum number of sub-modules required to maintain normal operation; Based on simulation technology, the total number of actual submodules and the minimum number of submodules are processed to obtain the reliability prediction model.

5. The reliability evaluation method for flexible DC converter valves based on submodule cross-communication as described in claim 1, characterized in that, The process of generating a reliability evaluation result for the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve includes: The reliability assessment parameters are compared and analyzed to obtain the reliability level of the target flexible DC converter valve; Uncertainty analysis is performed on the characteristic distribution parameters to obtain the influence confidence interval; Based on the influence confidence interval and the reliability level of the target flexible DC converter valve, the reliability evaluation result of the target flexible DC converter valve is obtained.

6. A reliability evaluation system for flexible DC converter valves based on submodule cross-communication, characterized in that, include: A construction module is used to construct fault logic for several sub-modules of the target flexible DC converter valve, and obtain the fault tree of the sub-modules. The determination module is used to determine the submodule failure probability simulation parameters based on the submodule fault tree, wherein the submodule failure probability simulation parameters include at least the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for normal operation of the bridge arm; The processing module is used to input the simulation parameters of the submodule failure probability into the constructed reliability prediction model for processing, so as to obtain the reliability evaluation parameters of the target flexible DC converter valve. The processing is configured to use Monte Carlo simulation to perform submodule group cyclic processing on the submodule and to judge the target flexible DC converter valve. The judgment process is based on the submodule failure probability, the number of bridge arm submodules, and the minimum number of submodules required for the normal operation of the bridge arm. The generation module is used to generate a reliability evaluation result for the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve.

7. The flexible DC converter valve reliability evaluation system based on submodule cross-communication as described in claim 6, characterized in that, The fault logic construction process for several sub-modules of the target flexible DC converter valve is performed to obtain a sub-module fault tree, including: Failure Mode and Effects Analysis (FMEA) was used to process several sub-modules of the target flexible DC converter valve to obtain a list of failure modes. The fault mode list is processed to construct a fault tree, resulting in the fault tree of the submodule.

8. The flexible DC converter valve reliability evaluation system based on submodule cross-communication as described in claim 6, characterized in that, The step of determining the submodule failure probability simulation parameters based on the submodule fault tree includes: Obtain fault parameter data of several sub-modules in the target flexible DC converter valve; Qualitative analysis is performed on the fault tree of the submodule to obtain the minimum cut set; Based on the principle of inclusion-exclusion, the fault parameter data of the minimum cut set and several sub-modules are processed to obtain the fault probability simulation parameters of the sub-modules.

9. The flexible DC converter valve reliability evaluation system based on submodule cross-communication as described in claim 6, characterized in that, The process of constructing the reliability prediction model includes: Obtain the total number of actual sub-modules of the target flexible DC converter valve and the minimum number of sub-modules required to maintain normal operation; Based on simulation technology, the total number of actual submodules and the minimum number of submodules are processed to obtain the reliability prediction model.

10. The flexible DC converter valve reliability evaluation system based on submodule cross-communication as described in claim 6, characterized in that, The process of generating a reliability evaluation result for the target flexible DC converter valve using the reliability evaluation parameters and the obtained characteristic distribution parameters of the target flexible DC converter valve includes: The reliability assessment parameters are compared and analyzed to obtain the reliability level of the target flexible DC converter valve; Uncertainty analysis is performed on the characteristic distribution parameters to obtain the influence confidence interval; Based on the influence confidence interval and the reliability level of the target flexible DC converter valve, the reliability evaluation result of the target flexible DC converter valve is obtained.

Images