A Dynamic Safety Assessment Method for Cable Line Systems Considering Coupling Effects

Abstract

This invention relates to a dynamic safety assessment method for cable line systems considering coupling effects, comprising the following steps: selecting equipment in the cable line system for safety assessment, and selecting monitoring variables from the dimensions of electrical signals, equipment status, and operating environment; based on the selected monitoring variables, constructing an interaction matrix reflecting the coupling effects between the monitoring variables, and calculating the equipment fault function under each dimension based on the interaction matrix; based on the equipment fault function under each dimension, constructing a comprehensive fault probability function for the equipment; based on the pre-constructed topological relationships between the equipment and the comprehensive fault probability function of the equipment, constructing a comprehensive fault probability function for the cable line system; and constructing a system dynamic flow graph based on the comprehensive fault probability function to achieve the safety assessment of the cable line system. Compared with the prior art, this invention overcomes the defect of the fuzzy comprehensive evaluation method where the indicators are mutually independent.

Description

Technical Field

[0001] This invention relates to the field of cable line system safety assessment, and in particular to a dynamic safety assessment method for cable line systems that considers coupling effects. Background Technology

[0002] In recent years, an increasing number of online monitoring devices for electrical and non-electrical equipment have been put into use in 110kV and high-voltage cables. However, this large amount of monitoring data often lacks effective analysis and utilization, and the various monitoring devices operate independently and in isolation, greatly affecting the application value of these online monitoring devices. Comprehensive analysis of cable system monitoring data can better prevent safety accidents.

[0003] Chinese patent application CN202410240558 discloses a cable operation monitoring method and system based on the Internet of Things (IoT). It establishes a cable safety monitoring platform based on IoT technology, builds a cable correlation model by acquiring historical cable data, and analyzes cables with abnormal operating conditions using real-time collected cable data and environmental parameters. However, this method judges cable system anomalies based on the slope of the curve between cable operating status and physical performance parameters, failing to comprehensively analyze different cable operating states and neglecting to consider the impact of each monitoring piece of information on cable system safety.

[0004] Chinese patent application publication number CN116579648A discloses a cable evaluation method and system based on adaptive adjustment of external factors. The embodiment discloses a cable evaluation method and system that can adaptively adjust the evaluation threshold according to environmental parameters, thereby accurately and effectively evaluating the cable's operating status. By determining the adjustment category corresponding to the environmental parameters and adjusting the evaluation threshold, this scheme optimizes the threshold adjustment mechanism of the cable online monitoring system, improves the accuracy and efficiency of monitoring, makes the cable monitoring process more reasonable, and can provide more multi-dimensional monitoring information. However, it can only perform single threshold judgment, the evaluation method is singular, and it cannot achieve integrated analysis of electrical and non-electrical monitoring information or realize comprehensive online evaluation of cables.

[0005] Traditional safety assessment methods often focus on the failure analysis of individual devices, neglecting the coupling effects between devices. Summary of the Invention

[0006] The purpose of this invention is to overcome the defects of the prior art by providing a dynamic safety assessment method for cable line systems that considers coupling effects, so as to solve or partially solve the problem of the independence between online monitoring devices and power equipment and the difficulty in integrating monitoring information.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] This invention provides a method for dynamic safety assessment of cable line systems considering coupling effects, comprising the following steps:

[0009] Select equipment in the cable line system for safety assessment, and select monitoring variables from the dimensions of electrical signals, equipment status, and operating environment;

[0010] Based on the selected monitoring variables, an interaction matrix reflecting the coupling and influence relationship between the monitoring variables is constructed, and the equipment fault function under each dimension is calculated based on the interaction matrix.

[0011] Based on the equipment failure function under each dimension, a comprehensive failure probability function for the equipment is constructed.

[0012] Based on the pre-built topological relationships between devices and the comprehensive fault probability function of the devices, a comprehensive fault probability function of the cable line system is constructed.

[0013] Based on the comprehensive fault probability function, a system dynamics flow graph is constructed to realize the safety assessment of the cable line system.

[0014] As a preferred technical solution, the construction of the interaction matrix reflecting the coupling influence relationship between the monitored variables is achieved by the following formula:

[0015]

[0016] Where n1 is the number of monitored variables under the device status dimension, J ij Let X be the status monitoring variable of the i-th device. i For X j The degree of influence, D i and E i B represents the sum of the influence of the i-th variable on other variables and the sum of the influence of the i-th variable on other variables. i Let be the weight of the i-th status monitoring variable in the equipment safety assessment.

[0017] As a preferred technical solution, the calculation of the device fault function in each dimension based on the interaction matrix includes the following steps:

[0018] For the electrical signal dimension, a fault probability function for each monitored variable is constructed, and the fault probability function for the electrical signal dimension is calculated based on the component failure probability theory.

[0019] For the device state dimension, the failure rate is calculated based on the interaction matrix to obtain the failure probability function for the device state dimension;

[0020] For the operational environment dimension, a fault probability function is constructed based on a piecewise function.

[0021] As a preferred technical solution, the process of constructing the comprehensive failure probability function of the equipment includes the following steps:

[0022] Based on the equipment failure function under each dimension, a comprehensive failure probability function for equipment used for safety assessment is constructed based on a series model.

[0023] As a preferred technical solution, the construction of the comprehensive fault probability function of the cable line system includes the following steps:

[0024] Based on the pre-built topological relationships between devices and the comprehensive failure probability function of the devices, and taking into account the coupling effect of multiple device failures, a comprehensive failure probability function of the cable line system is constructed based on the reliability formula of the series system.

[0025] As a preferred technical solution, the system dynamics flow graph includes multiple nodes and the relationships between the nodes, wherein the nodes represent the equipment and monitoring variables of the cable line system.

[0026] As a preferred technical solution, the security assessment method further includes the following steps:

[0027] Build a security assessment system based on the Spring Cloud microservice framework.

[0028] As a preferred technical solution, the construction process of the security assessment system includes the following steps:

[0029] Build the system's application architecture and physical architecture;

[0030] By designing the database, the system realizes the functions of monitoring, querying and preprocessing electrical and non-electrical characteristic data, performs status verification of data acquisition devices, pushes alarms for verification anomalies, and enables the access of real-time monitoring information of cable systems, display of system dynamics models, and configuration of ledgers.

[0031] Complete the development and implementation of the safety protection model for the cable line system, realize the chain-like safety protection function of the system, and issue alarm information when the monitoring results show abnormalities.

[0032] As a preferred technical solution, the equipment for safety assessment includes a cable body, a cable terminal, and a cable intermediate joint.

[0033] As a preferred technical solution, the monitoring variables in the electrical signal dimension include load current, operating voltage, and switching signals; the monitoring variables in the equipment status dimension include circulating current, core grounding current, partial discharge, equipment temperature, and SF6 gas pressure; and the monitoring variables in the operating environment dimension include water level, humidity, and temperature.

[0034] Compared with the prior art, the present invention has at least one of the following beneficial effects:

[0035] (1) Using the system dynamics method, a holographic safety assessment model for cable lines was built by comprehensively considering the three dimensions of electrical signal monitoring variables, equipment status monitoring variables and operating environment monitoring variables in the cable line system, thus realizing a comprehensive assessment of the safe operation status of the cable line system.

[0036] (2) Based on the changes in real-time monitoring data, the changes in the probability of cable equipment failure are directly reflected, thereby realizing the dynamic quantitative analysis of the safe operation status of cable equipment using the operating data of the cable line system.

[0037] (3) It makes up for the defect that the indicators of the fuzzy comprehensive evaluation method are independent of each other, takes into account the coupling effect between multiple monitoring variables, and links the status of equipment together; it reflects the advantages of systematic analysis and processing of complex cable lines. By establishing the correlation analysis of different functional layers or hierarchical structures, it realizes the three-layer evaluation and alarm function of rapid fault judgment, rapid fault location and rapid fault identification, which greatly improves the safety of cable lines.

[0038] (4) Using system dynamics as a carrier, the relationship between the monitoring variables of cable equipment and the entire cable line system was established, which solved the problem of data silos in some online monitoring devices, realized data sharing between equipment departments and dispatching departments, and extended the research focus to equipment operation safety, realizing the expansion from single health status assessment and single electrical signal assessment of equipment to collaborative analysis of the two and the operating environment. Attached Figure Description

[0039] Figure 1 This is a framework diagram of the holographic safety assessment model for cable lines in the embodiment;

[0040] Figure 2 This is a schematic diagram of the layered structure of the cable line system in the embodiment;

[0041] Figure 3 This is a schematic diagram illustrating the principle of the interaction matrix in the embodiment;

[0042] Figure 4 This is a schematic diagram illustrating the process of constructing the system dynamics safety assessment equations in the embodiment;

[0043] Figure 5 This is a schematic diagram illustrating the coupling of multiple factors in the embodiment;

[0044] Figure 6 This is a system dynamics flow diagram of the cable line system in the embodiment;

[0045] Figure 7 This is a schematic diagram of the application architecture of the cable line safety assessment system in the embodiment. Detailed Implementation

[0046] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0047] Example 1

[0048] To address the problem of independent online monitoring devices and power equipment, and the difficulty in integrating monitoring information, this embodiment provides a dynamic safety assessment method for cable line systems that considers coupling effects. This method enables coupled assessment among multiple variables, prevents cable system safety accidents caused by concurrent accidental factors, and effectively improves the safety level of power grid operation.

[0049] See Figure 1 This is a framework diagram of a holographic safety assessment model for cable lines. System dynamics safety assessment of cable systems considering coupling effects refers to a safety assessment integrating electrical and non-electrical variables. First, the cable system is analyzed, selecting key equipment and identifying key electrical and non-electrical monitoring variables from three dimensions: electrical signals, equipment status, and operating environment. Then, relevant thresholds and parameters are determined using methods such as literature review, design guidelines, and historical data, and fault probability functions for different types of monitoring variables are established. Next, the fault probability function of the cable equipment is obtained through the equipment fault probability functions from different dimensions, ultimately yielding the fault probability function of the cable line system. Finally, a system dynamics flow diagram considering coupling effects is constructed to assess the safe operating status of the cable line system.

[0050] This method includes the following steps:

[0051] Step S1: Select important equipment for the safety assessment of the cable line system, and select key monitoring variables for the equipment from three dimensions.

[0052] See Figure 2 This is a schematic diagram of the layered structure of a cable line system. The most representative and critical equipment in the cable line system are selected as: cable body, cable terminal, and cable joint.

[0053] The most representative key monitoring variables of the equipment were selected from three dimensions.

[0054] Key variables encompass three dimensions: electrical signals, equipment status, and operating environment. For example... Figure 2As shown, the key variables in the electrical signal dimension are load current, operating voltage, and switching signals; the key variables in the equipment status dimension are circulating current, core grounding current, partial discharge, equipment temperature, and SF6 gas pressure; and the key variables in the operating environment dimension are water level, humidity, and temperature.

[0055] Step S2 involves using an interaction matrix to determine the coupling effects of multiple monitoring variables and constructing a three-dimensional equipment fault function for the monitoring variables. This step includes the following sub-steps:

[0056] Step S201: Construct the fault probability function for the electrical signal dimension. If the load current and operating voltage of cable equipment exceed certain values, it will cause the temperature of the conductor and its accessories to rise, or even burn out. Therefore, the load current and operating voltage should be strictly controlled below the maximum allowable range. A switch signal value of 1 indicates normal equipment operation, while 0 indicates equipment failure. Therefore, the fault probability functions for the three electrical signal dimensions—load current, operating voltage, and switch signal—are pf1(t), pf2(t), and pf3(t), respectively:

[0057]

[0058]

[0059] In the formula These are the operating threshold values ​​for the load current and operating voltage of the cable equipment s, respectively. These represent the load current and operating voltage values ​​of cable equipment s at time t, respectively. s (t) represents the switching signal value of equipment s in the station at time t.

[0060] Based on the component failure probability theory, and using the results from equations (1), (2), and (3), the failure probability function pf(t) in the electrical signal dimension is obtained as follows:

[0061] pf(t)=1-(1-pf1(t))(1-pf2(t))(1-pf3(t))(4)

[0062] Step S202: Construct the fault probability function of the device state dimension;

[0063] The health index measures the health status of equipment and serves as a bridge between the probability of equipment failure and monitored variables. The impact of this variable on the equipment is represented by the deviation between different equipment health status indices and standard values, denoted as HI.

[0064]

[0065] In the formula Let be the working threshold for the i-th equipment status monitoring variable of cable equipment s; It is the value of the i-th device status monitoring variable at time t.

[0066] This design uses an interaction matrix to determine the impact of different equipment status monitoring variables on the equipment under the coupled influence of multiple variables. The schematic diagram of the interaction matrix is ​​shown below. Figure 3 As shown. The formula for determining the weights of each variable is as follows:

[0067]

[0068] In the formula: n1 is the number of equipment status monitoring variables; J ij Let X be the status monitoring variable of the i-th device. i For X j Degree of influence; D i and E i These represent the sum of the influence of the i-th variable on other variables and the sum of the degree to which it is influenced; B i Let be the weight of the i-th status monitoring variable in the equipment safety assessment.

[0069] Based on equations (5) and (8), the formula for the equipment operating health index is as follows:

[0070]

[0071] The equipment undergoes an aging process during actual operation, therefore the equipment failure rate l(t) is:

[0072] l(t)=Ke -100C·μ(t)·HI'(t) (10)

[0073] In the formula, K and C are proportionality coefficients, and μ(t) is the equipment aging coefficient.

[0074] Research indicates that a typical failure rate (lconst) corresponds to a health index of 0.8 for the equipment, while the minimum failure rate (lmin) corresponds to a perfect health state, i.e., a health index of 1. By analyzing historical data, the average failure rate of the cable equipment can be determined, and the minimum failure rate is set between 10% and 20% of the average failure rate. Based on equation (10), the relationship between the failure rate and the probability of failure is obtained, leading to the failure probability function of the equipment condition monitoring variable.

[0075] pl(t) = 1 - e -l(t) (11)

[0076] In the formula, pl(t) is the probability of equipment failure at time t.

[0077] Step S203: Construct the fault probability function for the runtime environment dimension.

[0078] Most environmental factor function designs employ low-complexity and practical exponential models, achieving ideal results in scientific research analysis. To rationally construct the failure probability function of operating environment indicators, a piecewise function is introduced to improve the existing exponential empirical function, namely...

[0079]

[0080] In the formula, M represents the undetermined coefficients of the model, which can be obtained based on objective historical data and expert experience; y min The initial value at which equipment within the station is affected; y max λ represents the maximum value during normal operation of the equipment. j (t) represents the equipment failure rate caused by the j-th environmental variable at time t.

[0081] The probability of equipment failure caused by the external environment is obtained by the piecewise exponential function of environmental variables in equation (12) as follows:

[0082]

[0083] In the formula: pe j (t) represents the probability of equipment failure caused by the j-th environmental variable at time t.

[0084] The impact of the overall operating environment on the equipment is summarized as follows: The failure probability function pe(t) based on the operating environment dimension is:

[0085]

[0086] In the formula, n2 represents the number of environmental monitoring variables.

[0087] Step S3: Analyze the relationship between the monitoring variables across the three dimensions to construct the failure probability function for the cable equipment.

[0088] The key variables selected in step S1 are important factors in the safe operation level of the equipment. Anomalies in any of the dimensions of electrical signals, equipment status, and operating environment will trigger alarms, and the indicators are interdependent. The failure probability function X for multi-dimensional monitoring of cable equipment is obtained from the execution results of steps S201-S203 based on the cascade model. g1 (t) is

[0089] X g1 (t)=1-(1-pf g (t))(1-pl g (t))(1-pe g (t)) (15)

[0090] The fault probability function between monitoring variables and equipment across different dimensions is too complex. Therefore, using the cable itself as an example, it is presented in a flowchart format, such as... Figure 4As shown.

[0091] Step S4: Based on the topological relationship and series model between cable equipment, construct the comprehensive fault probability function of the cable line system.

[0092] Cable line systems are multi-device series systems. Venn diagrams are used to illustrate the approach to safety assessment, such as... Figure 5 As shown. If any device in the series system is in a fault state, the entire cable line system will be in a fault state. The fault probability of the key device is calculated by equation (15) in step S3. Considering the coupling effect of multiple device faults, the fault probability of the cable line system is established according to the reliability formula of the series system as follows:

[0093]

[0094] In the formula X qg x(t) represents the failure probability of the g-th device q, and x(q) represents the total number of devices q in the cable line system.

[0095] Step S5: Construct a system dynamics flow diagram for the safety assessment of the cable line system, and conduct a safety assessment of the cable line system.

[0096] Based on the functional relationship between the equipment failure probability function and the cable line system failure probability function in step S4, a system dynamics flow graph is constructed, such as... Figure 6 As shown, the system dynamics flow graph includes multiple nodes and the relationships between them. Nodes represent the equipment and monitoring variables of the cable line system.

[0097] Step S6: Combining technologies such as Vensim and Python, and using the Spring Cloud microservice framework, design and develop a cable line safety assessment system. This step includes the following sub-steps:

[0098] Step S601: Build the application architecture and physical architecture of the intelligent cable coupling safety protection intelligent monitoring application system, and determine the main functions of the application system.

[0099] Step S602 involves database design to implement monitoring, querying, and preprocessing functions for collected electrical and non-electrical characteristic data, verifying the status of the data acquisition device, sending alarms for verification anomalies, and enabling functions such as access to real-time monitoring information of the cable system, display of the system dynamics model, and ledger configuration.

[0100] Step S603: Utilize Vensim and Python technologies to develop and implement the cable line system safety protection model, realizing the chain-like safety protection function of the cable line system. Issue alarm information when monitoring results show abnormalities. Its system application architecture is as follows: Figure 7 As shown.

[0101] Compared with traditional methods, this method has the following advantages:

[0102] (1) Using the system dynamics method, a holographic safety assessment model for cable lines was built by comprehensively considering the three dimensions of electrical signal monitoring variables, equipment status monitoring variables and operating environment monitoring variables in the cable line system, thus realizing a comprehensive assessment of the safe operation status of the cable line system.

[0103] (2) It can directly reflect the changes in the probability of cable equipment failure based on the changes in real-time monitoring data, thereby realizing dynamic quantitative analysis of the safe operation status of cable equipment using the operating data of the cable line system.

[0104] (3) It makes up for the defect that the indicators of the fuzzy comprehensive evaluation method are independent of each other, takes into account the coupling effect between multiple monitoring variables, and links the status of equipment together; it reflects the advantages of systematic analysis and processing of complex cable lines. By establishing the correlation analysis of different functional layers or hierarchical structures, it realizes the three-layer evaluation and alarm function of rapid fault judgment, rapid fault location and rapid fault identification, which greatly improves the safety of cable lines.

[0105] (4) Using system dynamics as a framework, the relationship between the monitoring variables of cable equipment and the entire cable line system was established, solving the problem of data silos in some online monitoring devices and realizing data sharing between the equipment department and the dispatching department. Furthermore, the research focus was extended to equipment operation safety, realizing the expansion from single equipment health status assessment and single electrical signal assessment to the collaborative analysis of both and the operating environment.

[0106] Example 2

[0107] This embodiment provides an electronic device, including: one or more processors and a memory, wherein the memory stores one or more programs, the one or more programs including instructions for executing the dynamic safety assessment method for cable line systems considering coupling effects as described in Embodiment 1.

[0108] Example 3

[0109] This embodiment provides a computer-readable storage medium including one or more programs executable by one or more processors of an electronic device, the one or more programs including instructions for performing a dynamic safety assessment method for cable line systems considering coupling effects as described in Embodiment 1.

[0110] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A method for dynamic safety assessment of cable line systems considering coupling effects, characterized in that, Includes the following steps: Select equipment in the cable line system for safety assessment, and select monitoring variables from the dimensions of electrical signals, equipment status, and operating environment; Based on the selected monitoring variables, an interaction matrix reflecting the coupling and influence relationship between the monitoring variables is constructed, and the equipment fault function under each dimension is calculated based on the interaction matrix. Based on the equipment failure function under each dimension, a comprehensive failure probability function for the equipment is constructed. Based on the pre-built topological relationships between devices and the comprehensive fault probability function of the devices, a comprehensive fault probability function of the cable line system is constructed. Based on the comprehensive fault probability function, a system dynamics flow graph is constructed to achieve a safety assessment of the cable line system. The interaction matrix reflecting the coupling influence between monitored variables is constructed using the following formula: in, n 1 represents the number of monitored variables under the device status dimension. For the first i Status monitoring variables of individual devices right The extent of the impact and Respectively i The sum of the influence of each variable on other variables and the sum of the influence of each variable on other variables For the first i The weights of each condition monitoring variable in the equipment safety assessment The calculation of the device fault function for each dimension based on the interaction matrix includes the following steps: For the electrical signal dimension, a fault probability function for each monitored variable is constructed, and the fault probability function for the electrical signal dimension is calculated based on the component failure probability theory. For the device state dimension, the failure rate is calculated based on the interaction matrix to obtain the failure probability function for the device state dimension; For the operational environment dimension, a fault probability function is constructed based on a piecewise function.

2. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 1, characterized in that, The process of constructing the comprehensive failure probability function of the equipment includes the following steps: Based on the equipment failure function under each dimension, a comprehensive failure probability function for equipment used for safety assessment is constructed based on a series model.

3. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 1, characterized in that, The construction of the comprehensive fault probability function of the cable line system includes the following steps: Based on the pre-built topological relationships between devices and the comprehensive failure probability function of the devices, and taking into account the coupling effect of multiple device failures, a comprehensive failure probability function of the cable line system is constructed based on the reliability formula of the series system.

4. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 1, characterized in that, The system dynamics flow graph includes multiple nodes and the relationships between the nodes, wherein the nodes represent the equipment and monitoring variables of the cable line system.

5. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 1, characterized in that, The security assessment method also includes the following steps: Build a security assessment system based on the Spring Cloud microservice framework.

6. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 5, characterized in that, The construction process of the security assessment system includes the following steps: Build the system's application architecture and physical architecture; By designing the database, the system realizes the functions of monitoring, querying and preprocessing electrical and non-electrical characteristic data, performs status verification of data acquisition devices, pushes alarms for verification anomalies, and enables the access of real-time monitoring information of cable systems, display of system dynamics models, and configuration of ledgers. Complete the development and implementation of the safety protection model for the cable line system, realize the chain-like safety protection function of the system, and issue alarm information when the monitoring results show abnormalities.

7. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 1, characterized in that, The equipment used for safety assessment includes the cable body, cable termination, and cable joint.

8. The method for dynamic safety assessment of cable line systems considering coupling effects according to claim 1, characterized in that, The monitoring variables in the electrical signal dimension include load current, operating voltage, and switching signals; the monitoring variables in the equipment status dimension include circulating current, core grounding current, partial discharge, equipment temperature, and SF6 gas pressure; and the monitoring variables in the operating environment dimension include water level, humidity, and temperature.

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