A power distribution terminal state self-evaluation method and device considering time-varying reliability

Abstract

This invention relates to a method and apparatus for self-evaluation of the state of a power distribution terminal considering time-varying reliability. The method includes: constructing a time-varying reliability model for functional modules in the power distribution terminal, wherein the functional modules are used to maintain the power distribution terminal in a normal working state; calculating the confidence level of fault types and functional modules, wherein the fault types are faults in the power distribution terminal caused by different functional modules; fusing the confidence levels and the time-varying reliability model to construct a reliability index for the power distribution terminal; and performing a state assessment of the power distribution terminal based on the reliability index. This invention can effectively assess the state of a power distribution terminal, and can also be applied analogously to other terminal equipment in the power distribution field, such as integrated primary and secondary distribution equipment.

Description

Technical Field

[0001] This invention relates to the field of intelligent operation and maintenance technology for power systems, and in particular to a method and apparatus for self-evaluation of the status of distribution terminals that considers time-varying reliability. Background Technology

[0002] Existing power grid companies need to continuously improve their intelligence levels in the coming years, fully utilizing modern information technologies such as big data, cloud computing, IoT, mobile, and AI to create a ubiquitous power IoT that enables comprehensive state perception, efficient information processing, and convenient and flexible applications. The ubiquitous power IoT will enhance the company's overall capabilities in four aspects: holographic perception, ubiquitous connectivity, open sharing, and integrated innovation, building upon the existing power grid operations. One of its key objectives is to access smart IoT devices across various business segments through a unified IoT platform, establishing unified channels, data models, and access methods for various power terminal access systems, enabling plug-and-play functionality and data sharing for all types of terminal devices.

[0003] With the increasing intelligence of distribution terminals, traditional distribution operation and maintenance technologies can no longer meet the needs of distribution automation development. Especially in the context of the ubiquitous power Internet of Things, the volume of business between distribution smart terminals is increasing, business interactions are becoming more frequent, and the sharing between terminals is strengthening, making distribution terminal operation and maintenance more complex. Based on the massive amounts of information generated by smart distribution terminals, there is an urgent need to study big data technology to carry out intelligent operation and maintenance of distribution smart terminals, improve operation and maintenance quality and efficiency, and ensure the safe and stable operation of the distribution network.

[0004] Meanwhile, with the continuous improvement of power distribution automation, the large-scale terminal access places higher demands on the quantity and quality of maintenance personnel. The limited number of maintenance personnel and the ever-expanding scale of equipment create significant pressure on maintenance work. Taking Jiangsu Province as an example, the province has over 200,000 power distribution terminals, with over 40,000 connected in Nanjing alone, highlighting a growing structural shortage of personnel. Due to the varying technical levels of maintenance personnel, their limited ability to mine effective information data, and poor defect diagnosis capabilities, terminal troubleshooting efficiency is low, failing to meet the needs of large-scale power distribution terminal applications. Therefore, it is urgent to explore efficient and intelligent maintenance methods to ensure rapid access and stable operation of large-scale terminals. As a widely used type of power distribution terminal, centralized substation terminals require significant research into their condition evaluation and fault analysis methods.

[0005] Status analysis of terminal equipment mainly falls into three research approaches: Analytic Hierarchy Process (AHP), Fault Tree Analysis (FTA), and Relationship Analysis. AHP assesses the overall terminal status by manually setting fault weights; however, this method relies heavily on subjective experience, neglecting the objective patterns of terminal failures, resulting in unstable evaluation results. Fault Tree Analysis evaluates terminal reliability by analyzing module failure rates and recovery rates; however, this method relies solely on fault data, lacks guidance from experienced maintenance personnel, and therefore has low reliability, failing to consider the changing characteristics of module reliability over time. Relationship Analysis, based on historical fault data, mines the relationships between faults and modules, establishing a rule base that can guide daily maintenance and fault diagnosis; however, this method lacks a systematic approach and cannot evaluate the overall status of the terminal equipment. All of these methods lack the integration of subjective experience and objective data analysis, and do not consider the changing characteristics of terminal reliability over time, making it impossible to eliminate potential equipment problems in batches or in a targeted manner. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a method and apparatus for self-evaluation of the state of a power distribution terminal that takes into account time-varying reliability, which can effectively evaluate the state of the power distribution terminal.

[0007] The technical solution adopted by this invention to solve its technical problem is: to provide a method for self-evaluation of the state of a distribution terminal considering time-varying reliability, comprising:

[0008] A time-varying reliability model is constructed for the functional modules in the power distribution terminal, wherein the functional modules are used to maintain the power distribution terminal in a normal working state;

[0009] Calculate the confidence level of fault type and functional module, wherein the fault type is a fault in the power distribution terminal caused by different functional modules;

[0010] The reliability index of the distribution terminal is constructed by integrating the confidence level and time-varying reliability model.

[0011] Based on the aforementioned reliability indicators, the status of the power distribution terminal is assessed.

[0012] The time-varying reliability model is constructed using a failure distribution function based on the Weibull distribution, the formula of which is: ,in, The runtime of the functional module. The scaling parameter of the failure distribution function. The shape parameter of the failure distribution function.

[0013] The formula for the time-varying reliability model is: ,in, For functional modules runtime For functional modules The failure distribution function, Regarding the functional modules The scaling parameter of the failure distribution function. For about functional modules The shape parameter of the failure distribution function.

[0014] The confidence levels of the fault types and functional modules are determined by the formula. To calculate, where, Indicates in Time Function Module With fault type Confidence values ​​between Indicates in Time accumulation function module Total number of historical fault data entries Indicates the fault type With functional modules The number of records that appear simultaneously in the total number of fault data entries. Indicates the fault type The number of entries appearing in the total number of fault data entries.

[0015] The reliability index formula for the power distribution terminal is: ,in, For the overall reliability of the power distribution terminal, Fault type For all faults, To cause the type of failure A collection of functional modules Indicates in Time Function Module With fault type Confidence values ​​between For functional modules In Reliability at any given moment.

[0016] The step of assessing the status of the power distribution terminal based on the reliability index further includes: updating the confidence level according to the status assessment result of the power distribution terminal, and calculating a new reliability index based on the updated confidence level.

[0017] The technical solution adopted by this invention to solve its technical problem is: to provide a power distribution terminal status self-evaluation device considering time-varying reliability, comprising:

[0018] Time-varying reliability model construction unit: used to construct time-varying reliability models for the functional modules in the power distribution terminal, wherein the functional modules are used to maintain the power distribution terminal in a normal working state;

[0019] Confidence calculation unit: used to calculate the confidence level of fault type and functional module, wherein the fault type is a fault in the power distribution terminal caused by different functional modules;

[0020] Reliability index construction unit: used to integrate the confidence level and time-varying reliability model to construct the reliability index of the power distribution terminal;

[0021] Evaluation unit: used to evaluate the status of the power distribution terminal based on the reliability indicators.

[0022] The reliability index formula for the power distribution terminal is: ,in, For the overall reliability of the power distribution terminal, Fault type For all faults, To cause the type of failure A collection of functional modules Indicates in Time Function Module With fault type Confidence values ​​between For functional modules In Reliability at any given moment.

[0023] The technical solution adopted by the present invention to solve its technical problem is: to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the steps of the above-mentioned self-evaluation method for the state of a power distribution terminal considering time-varying reliability.

[0024] The technical solution adopted by the present invention to solve its technical problem is: to provide a computer-readable storage medium on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the above-mentioned self-evaluation method for the state of a power distribution terminal considering time-varying reliability are implemented.

[0025] Beneficial effects

[0026] By adopting the above-mentioned technical solutions, this invention has the following advantages and positive effects compared with existing technologies: This invention constructs time-varying reliability models for each functional module of the power distribution terminal, analyzes the time-varying reliability of each functional module of the power distribution terminal (centralized substation terminal), and can update the functional modules and results according to actual operation and maintenance needs, thereby reflecting the overall reliability changes of the power distribution terminal. This invention integrates expert experience to calculate the confidence level of functional modules and fault types, supporting daily operation and maintenance and fault repair decisions for the power distribution terminal. Compared with traditional methods of establishing rule bases based on the correlation between modules and faults, this invention integrates subjective experience and objective data, and considers actual equipment operating scenarios, making the evaluation method more systematic and the evaluation results more credible. This invention forms reliability indicators for centralized substation terminals based on the relationship between the time-varying reliability and confidence level of functional modules. Compared with single fault tree model analysis methods that only consider the general reliability of each functional module, the method proposed in this invention can reflect the attenuation characteristics of each module over a long time scale, thereby more accurately describing the characteristics of the overall reliability of the centralized substation terminal changing over time and improving the level of lean management of equipment maintenance. This invention can also be applied by analogy to other terminal equipment in the power distribution field, such as integrated primary and secondary power distribution equipment. Attached Figure Description

[0027] Figure 1 This is a flowchart of a method according to an embodiment of the present invention;

[0028] Figure 2 This is a physical model diagram of the centralized station terminal structure according to an embodiment of the present invention;

[0029] Figure 3 This is a diagram showing the relationship between fault types and the confidence levels of the functions of each module in a centralized station terminal according to an embodiment of the present invention.

[0030] Figure 4 This is a time-varying reliability curve of the functional module considering periodic operation and maintenance in an embodiment of the present invention. Detailed Implementation

[0031] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0032] The embodiments of this invention relate to a self-evaluation method for the status of distribution terminals considering time-varying reliability. The distribution terminals in this embodiment include, but are not limited to, integrated primary and secondary pole-mounted switches, integrated primary and secondary distribution terminal equipment, and station terminals. Please refer to [link / reference]. Figure 1 ,include:

[0033] (1) This implementation takes the centralized station terminal in the primary and secondary integrated power distribution terminal equipment as an example. Based on the terminal physical structure and its historical data, operation and maintenance records and real-time operating status, and integrating professional operation and maintenance experience, a time-varying reliability model of each functional module of the centralized station terminal is constructed.

[0034] (2) Analyze the confidence levels of each fault type and each functional module of the centralized station terminal based on historical fault data of the centralized station terminal;

[0035] (3) Integrate time-varying reliability models and confidence levels to construct reliability indicators for centralized station terminals;

[0036] (4) Calculate the reliability index of the terminal based on the regular operation and maintenance situation, and evaluate the status of the centralized station terminal.

[0037] Step (1) is as follows:

[0038] 1) Firstly, based on the integrated primary and secondary power distribution terminal equipment, this implementation method takes a centralized substation terminal as an example to construct a physical model, as detailed in [link to details]. Figure 2 .

[0039] Specifically, the integrated primary and secondary intelligent power distribution terminal equipment is divided into feeder terminals, substation terminals, and transformer terminals. Substation terminals are further categorized into centralized and distributed types based on their layout. Centralized substation terminals refer to terminals where all components are installed in a centralized panel configuration. Distributed substation terminals consist of several bay units and a common unit. This implementation example uses a centralized substation terminal, whose ring main unit internal structure is as follows: Figure 2 As shown.

[0040] The centralized station terminal adopts a modular, standardized, and scalable design. Modules are connected via standardized wiring harnesses. The main components include a core unit, a power module, rectangular connectors, and a backup power supply. The power module supplies power to the core unit, while the backup power supply provides protection in case of line power failure. The centralized station terminal connects to primary equipment and other terminal modules via rectangular connectors. Within the core unit, the acquisition module collects and converts battery voltage, temperature and humidity, primary-side analog quantities (voltage and current), and primary-side status quantities (switch status). The CPU module executes specific algorithms to process various digital quantities. The control loop controls the opening and closing of primary-side switches. The time synchronization module supports master station protocols, BeiDou / GPS, and other time synchronization methods. The communication module includes local and remote communication modules, enabling connection with other local terminal modules and LCD screens, and transmitting remote signaling, telemetry, remote control, and electrical energy data to the master station. Simultaneously, the master station's control commands are transmitted to the centralized station terminal via fiber optic / wireless fiber optic cable, allowing operation of the primary equipment through the core unit.

[0041] 2) Construct time-varying reliability models for each functional module of the terminal based on historical fault data of the terminal and the manufacturer's estimated lifespan.

[0042] The loss of a device's / module's intended function is called a failure or malfunction. The causes of failure are varied, and the reasons for each type of failure may differ; the timing of the failure is uncertain. Failure of different modules can lead to the overall failure of the centralized station terminal equipment, and the normal operation of the centralized station terminal depends on each functional module.

[0043] Considering that the reliability of each functional module depends on the lifespan of the hardware and historical faults and maintenance, this implementation method combines the actual operation and maintenance data of the power distribution terminal in recent years and the experience of experts to model each functional module using the Weibull distribution model, in order to find the failure distribution law that can accurately reflect the failure mechanism of the module and is consistent with the analysis results of the failure data, thereby reflecting the reliability characteristics of the centralized station terminal over time.

[0044] The failure distribution function of the functional module conforming to the Weibull distribution is as follows:

[0045]

[0046] in, For module runtime, and These are the scale parameter and shape parameter of the failure distribution function (these two parameters are obtained by parameter fitting using the least squares method described below).

[0047] For each functional module, based on the manufacturer's estimated lifespan (in days), fault data within that estimated lifespan is obtained, and the cumulative number of faults is calculated on a daily basis. The maximum lifespan is then used as the benchmark. The total number of failures was For example, the first The failure distribution function on day 1 has a maximum value of 1. Then, on day 2... The failure distribution function corresponding to day is: That is, the total number of failures accumulated on that day divided by . For the first The number of failures per day was recorded, and a data table showing the running time and failure distribution function was generated as described in Table 1.

[0048] Table 1. Data on running time and failure distribution function

[0049]

[0050] Then, the parameters are fitted and solved using the least squares method. The idea behind the least squares method is as follows:

[0051] The transformation form of the failure distribution function for a single Welb distribution model is as follows:

[0052]

[0053] Taking the logarithm twice, we get:

[0054]

[0055] Among them, let , , ,

[0056] Therefore, the above expression can be transformed into:

[0057] Based on the least squares method, parameters and The solution can be obtained using the following formula:

[0058]

[0059]

[0060] in, For parameters , The number of For the first Parameters , For the first Parameters , , .

[0061] Then, the failure distribution function conforming to the Welb distribution. The parameters in can be solved using the following formula:

[0062]

[0063]

[0064] Time-varying reliability models for each functional module are constructed based on the failure distribution function of a single Welb distribution model:

[0065]

[0066] Among them, subscript express The physical quantities of the module. For functional modules The failure distribution function, For about functional modules The scaling parameter of the failure distribution function. For about functional modules The shape parameters of the failure distribution function (the parameters are obtained by the failure data fitting method based on the least squares method described above).

[0067] Step (2) is as follows:

[0068] Based on the fault symptoms, faults in centralized station terminal equipment can be categorized into remote signaling faults (frequent changes in remote signaling, etc.), remote control faults (failure to switch remote control on / off), telemetry faults (telemetry not refreshing, abnormal telemetry readings, etc.), terminal offline, frequent connection / disconnection, and other faults. The first three categories can be classified as functional faults of the centralized station terminal's "three remotes" (remote control, remote telemetry, and remote telemetry), while the remaining categories are equipment faults.

[0069] In actual operation, the causes of terminal failures may vary depending on factors such as region, environment, and equipment manufacturer. If the location of the centralized station terminal is not equipped with a 4G / 5G base station or has poor wireless signal quality, the probability of wireless communication module failure is relatively high. Furthermore, since centralized station terminals are generally equipped with backup power supplies, the probability of a power module failure causing overall terminal failure is usually low. Taking telemetry failure as an example, it may be caused by failures in the acquisition module (failure to sample signals / incorrect sampling values), communication module (communication blockage / packet loss when uploading to the main station), time synchronization module (failure to synchronize with the master clock, sampling different time values), CPU module, or power module (failure to supply power to the core unit). Therefore, this implementation method derives the confidence relationship between each failure type and each functional module of the centralized station terminal based on historical failure data of the centralized station terminal, as follows:

[0070]

[0071] in, Indicates in Time Function Module With fault type Confidence values ​​between Indicates in Time accumulation function module Total number of historical fault data entries Indicates the fault type With functional modules The number of items that also appear in the total number of fault data entries (fault data typically includes information such as fault type, maintenance measures, and modules). Indicates the fault type The number of records appearing in the total number of fault data entries. (Formula) The meaning expressed is in the fault type Of the number of times it appears, how many times is due to functional modules? This is caused by [the following], and thus the confidence level is calculated.

[0072] Step (3) is as follows:

[0073] The normal operation and proper use of functions of centralized station terminals depend closely on each functional module. Therefore, the reliability index of centralized station terminals can be modified to the product of the reliability of each functional module and the confidence level of its corresponding module and fault:

[0074]

[0075] This formula means that for each type of fault, we identify all modules that caused it. If all modules are reliable, then the fault will not occur. For centralized station terminals, if no faults occur, then the station is considered reliable. To ensure the overall reliability of centralized station terminals. Indicates the fault type. Indicates all faults. Types of faults A collection of modules.

[0076] Step (4) is as follows:

[0077] Based on the results of regular inspections and troubleshooting, if hardware replacement is required, such as batteries or communication modules, the calculation will be recalculated. The time-varying reliability model of this functional module Sync update confidence relationships This leads to a new reliability index for the weights. And the status evaluation of new centralized station terminals.

[0078] The present invention is further illustrated below through a specific embodiment:

[0079] Based on the operation and maintenance data of distribution terminals in the first quarter of 2022 and the historical records of functional module failures over the past four years provided by a power supply company in a certain region, an algorithm written in Python was used to process the data and analyze the reliability of primary and secondary integrated distribution terminal equipment (taking centralized station terminals as an example).

[0080] (1) Based on the failure history of the functional modules over the past 4 years, the time-varying reliability of each functional module was calculated. Table 3 shows the module failure data using the communication module as an example, where the manufacturer's estimated lifespan for the communication module is 3 years:

[0081] Table 2 Failure distribution function of communication module

[0082]

[0083] The time-varying reliability model parameters of each functional module are solved by the least squares method in step (1). The solution results are shown in Table 3: Table 3 Time-varying reliability model parameters of each functional module

[0084]

[0085] (2) Based on the operation and maintenance data of the distribution terminal in the first quarter of 2022 and the historical records of module failures over the past four years, combined with expert experience and mathematical statistics, the confidence relationships between each fault type and each functional module of the centralized substation terminal were obtained. See details. Figure 3 .

[0086] Specifically, Figure 3 Solid lines indicate fault types. The dashed lines represent functional modules. The connecting lines represent the relationship between fault types and faulty modules, and the numbers above the connecting lines represent the confidence level index calculated from... Figure 3 It is not difficult to see that most telemetry failures are caused by the communication module with the highest confidence level, followed by the CPU module and the acquisition module. Remote control, remote signaling failures, and frequent terminal offlines are mostly caused by communication module failures. In addition, remote control failures also depend on the reliability of the control loop, while remote signaling failures are related to the reliability of the acquisition module.

[0087] (3) The reliability indicators of centralized station terminals are constructed as follows (taking telemetry failure as an example):

[0088]

[0089] (4) Confidence indicators and functional module reliability need to be updated regularly based on real-time operation and maintenance data to reflect the recent status trends of centralized station terminals. If certain functional modules are replaced during operation and maintenance, the time-varying reliability indicators of those functional modules need to be initialized. If the communication module is replaced on day 365, the resulting reliability curve of the centralized station terminal is as follows: Figure 4 As shown, the reliability of the centralized station terminal improved to 0.98 after the communication module was replaced, which verifies that the maintenance and replacement of functional modules during operation and maintenance can improve the overall reliability of the centralized station terminal.

[0090] The second embodiment of the present invention relates to a distribution terminal condition self-evaluation device considering time-varying reliability, comprising:

[0091] Time-varying reliability model construction unit: used to construct time-varying reliability models for functional modules in the power distribution terminal;

[0092] Confidence calculation unit: used to calculate the confidence level of fault type and functional module, wherein the fault type is a fault in the power distribution terminal caused by different functional modules;

[0093] Reliability index construction unit: used to integrate the confidence level and time-varying reliability model to construct the reliability index of the power distribution terminal;

[0094] Evaluation unit: used to evaluate the status of the power distribution terminal based on the reliability indicators.

[0095] In the time-varying reliability model construction unit, the time-varying reliability model is constructed using a failure distribution function based on the Weibull distribution. The formula for the failure distribution function is: ,in, The runtime of the functional module. The scaling parameter of the failure distribution function. The shape parameter of the failure distribution function.

[0096] In the time-varying reliability model construction unit, the formula of the time-varying reliability model is: ,in, For functional modules runtime For functional modules The failure distribution function, For about functional modules The scaling parameter of the failure distribution function. For about functional modules The shape parameter of the failure distribution function.

[0097] In the confidence calculation unit, the fault type and the confidence level of the functional module are determined by the formula. To calculate, where, Indicates in Time Function Module With fault type Confidence values ​​between Indicates in Time accumulation function module Total number of historical fault data entries Indicates the fault type With functional modules The number of records that appear simultaneously in the total number of fault data entries. Indicates the fault type The number of entries appearing in the total number of fault data entries.

[0098] In the reliability index construction unit, the reliability index formula for the power distribution terminal is: ,in, For the overall reliability of the power distribution terminal, Fault type For all faults, To cause the type of failure A collection of functional modules Indicates in Time Function Module With fault type Confidence values ​​between For functional modules In Reliability at any given moment.

[0099] The method of assessing the status of the power distribution terminal based on the reliability index further includes an update unit: used to update the confidence level according to the status assessment result of the power distribution terminal, and calculate a new reliability index based on the updated confidence level.

[0100] The third embodiment of the present invention relates to an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the power distribution terminal state self-evaluation method considering time-varying reliability described in the above embodiments.

[0101] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of this application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0102] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0103] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0104] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0105] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0106] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A power distribution terminal state self-evaluation method considering time-varying reliability, characterized by, include: A time-varying reliability model is constructed for the functional modules in the power distribution terminal, wherein the functional modules are used to maintain the power distribution terminal in a normal working state; Calculate the confidence level between fault type and functional module, where the fault type refers to a fault in the distribution terminal caused by different functional modules; the confidence level between the fault type and functional module is calculated using the formula... To calculate, where, Indicates in Time Function Module With fault type Confidence values ​​between Indicates in Time-accumulation function module Total number of historical fault data entries Indicates the fault type With functional modules The number of records that appear simultaneously in the total number of fault data entries. Indicates the fault type The number of records appearing in the total number of fault data entries; The reliability index of the distribution terminal is constructed by integrating the confidence level and the time-varying reliability model; the formula for the reliability index of the distribution terminal is: ,in, For the overall reliability of the power distribution terminal, For all faults, To cause the type of failure A collection of functional modules Indicates in Time Function Module With fault type Confidence values ​​between For functional modules In Reliability at any given moment; Based on the aforementioned reliability indicators, the status of the power distribution terminal is assessed.

2. The method for self-evaluation of the state of a distribution terminal considering time-varying reliability according to claim 1, characterized in that, The time-varying reliability model is constructed using a failure distribution function based on the Weibull distribution, the formula of which is: ,in, The runtime of the functional module. The scaling parameter of the failure distribution function. The shape parameter of the failure distribution function.

3. The method for self-evaluation of distribution terminal status considering time-varying reliability according to claim 1, characterized in that, The formula for the time-varying reliability model is: ,in, For functional modules runtime For functional modules The failure distribution function, Regarding the functional modules The scaling parameter of the failure distribution function. Regarding the functional modules The shape parameter of the failure distribution function.

4. The method for self-evaluation of distribution terminal status considering time-varying reliability according to claim 1, characterized in that, The step of assessing the status of the power distribution terminal based on the reliability index further includes: updating the confidence level according to the status assessment result of the power distribution terminal, and calculating a new reliability index based on the updated confidence level.

5. A power distribution terminal condition self-evaluation device considering time-varying reliability, characterized in that, include: Time-varying reliability model construction unit: used to construct time-varying reliability models for the functional modules in the power distribution terminal, wherein the functional modules are used to maintain the power distribution terminal in a normal working state; Confidence Calculation Unit: Used to calculate the confidence level between fault type and functional module, wherein the fault type is a fault in the power distribution terminal caused by different functional modules; the confidence level between the fault type and functional module is calculated using the formula... To calculate, where, Indicates in Time Function Module With fault type Confidence values ​​between Indicates in Time-accumulation function module Total number of historical fault data entries Indicates the fault type With functional modules The number of records that appear simultaneously in the total number of fault data entries. Indicates the fault type The number of records appearing in the total number of fault data entries; Reliability index construction unit: used to fuse the confidence level and time-varying reliability model to construct the reliability index of the distribution terminal; the formula for the reliability index of the distribution terminal is: ,in, For the overall reliability of the power distribution terminal, For all faults, To cause the type of failure A collection of functional modules Indicates in Time Function Module With fault type Confidence values ​​between For functional modules In Reliability at any given moment; Evaluation unit: used to evaluate the status of the power distribution terminal based on the reliability indicators.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the self-evaluation method for the state of a distribution terminal considering time-varying reliability as described in any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the self-evaluation method for the state of a distribution terminal considering time-varying reliability as described in any one of claims 1 to 4.

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