Cable line system dynamics safety assessment method considering coupling influence

Abstract

The invention relates to a cable line system dynamics safety assessment method considering coupling influence. The method comprises the following steps: selecting equipment for safety assessment in a cable line system, and selecting monitoring variables from electrical signals, equipment states and operating environment dimensions; based on the selected monitoring variables, constructing an interaction matrix reflecting a coupling influence relationship between the monitoring variables, and based on the interaction matrix, calculating an equipment fault function under each dimension; based on the equipment fault function under each dimension, constructing a comprehensive fault probability function of the equipment; constructing a comprehensive fault probability function of the cable line system based on a pre-constructed topological relation between the equipment and the comprehensive fault probability function of the equipment; and building a system dynamics flow graph based on the comprehensive fault probability function, and realizing safety evaluation of the cable line system. Compared with the prior art, the defect that indexes of a fuzzy comprehensive evaluation method are mutually independent is overcome.

Description

Technical Field

[0001] The invention relates to the field of cable line system safety assessment, and in particular to a cable line system dynamics safety assessment method considering coupling effects. Background Art

[0002] In recent years, more and more online monitoring devices for electrical and non-electrical equipment have been put into use in 110kV and high-voltage cables, but these large amounts of monitoring data often lack effective analysis and utilization, and each monitoring device is independent of each other and operates in an isolated manner, which greatly affects the application value of various online monitoring devices. Comprehensive analysis of cable system monitoring data can better prevent the occurrence of safety accidents.

[0003] Chinese patent application CN202410240558 discloses a cable operation supervision method and system based on the Internet of Things, establishes a cable safety supervision platform based on the Internet of Things technology, establishes a cable association model by acquiring cable historical data information, and uses real-time collected cable data information and environmental parameters to analyze cables with abnormal operating conditions. However, this method judges the abnormality of the cable system by the slope of the curve between the cable operating status and the physical performance parameters, does not comprehensively analyze the different operating states of the cable, and does not consider the impact of each monitoring information on the safety of the cable system separately.

[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, which can adaptively adjust the evaluation threshold according to environmental parameters, and then accurately and effectively evaluate the cable operation status. By determining the adjustment category corresponding to the environmental parameters and adjusting the evaluation threshold, the 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 dimensional monitoring information. However, only a single threshold judgment can be performed, and the evaluation method is single, and it is impossible to realize the integrated analysis of electrical monitoring information and non-electrical monitoring information and realize the online comprehensive evaluation of cables.

[0005] Traditional safety assessment methods focus on the fault analysis of a single device and ignore the coupling effects between devices. Summary of the invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and provide a cable line system dynamic safety assessment method taking into account the coupling effect, so as to solve or partially solve the problem that the online monitoring device and the power equipment are independent of each other and the monitoring information is difficult to integrate.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] The present invention provides a cable line system dynamics safety assessment method considering coupling effects, comprising the following steps:

[0009] Select equipment for safety assessment in the cable line system 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 influence relationship between the monitoring variables is constructed, and the equipment failure function under each dimension is calculated based on the interaction matrix;

[0011] Based on the equipment failure function in each dimension, a comprehensive failure probability function of the equipment is constructed;

[0012] Constructing a comprehensive fault probability function of the cable line system based on the pre-constructed topological relationship between the devices and the comprehensive fault probability function of the devices;

[0013] A system dynamics flow diagram is constructed based on the comprehensive fault probability function to achieve 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 implemented by the following formula:

[0015]

[0016] Among them, n1 is the number of monitoring variables in the device status dimension, J ij is the status monitoring variable X of the i-th device i X j The degree of influence, D i and E i are the sum of the influence of the i-th variable on other variables and the sum of the influence, B i is the weight of the i-th state monitoring variable for equipment safety assessment.

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

[0018] For the electrical signal dimension, the fault probability function of each monitoring variable is constructed, and the fault probability function of 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 a failure probability function of the device state dimension;

[0020] For the operating environment dimension, a failure probability function of the environment dimension is constructed based on the 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 of the equipment for safety assessment is constructed based on the 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 relationship between devices and the comprehensive fault probability function of the devices, the coupling influence of multi-device failures is comprehensively considered, and the comprehensive fault probability function of the cable line system is constructed based on the series system reliability formula.

[0025] As a preferred technical solution, the system dynamics flow diagram 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 safety assessment method further includes the following steps:

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

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

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

[0030] By designing the database, the monitoring, query and preprocessing functions of the collected electrical and non-electrical characteristic data can be realized, the status of the data acquisition device can be verified, and the alarm can be pushed for the abnormal verification information, so as to realize the access of the real-time monitoring information of the cable system, the display of the system dynamics model, and the configuration of the ledger;

[0031] Complete the development and implementation of the cable line system security protection model, realize the system's chain security protection function, and issue alarm information when 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 switch signal, 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 operating 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 dynamic quantitative analysis of the safe operating status of cable equipment using the operating data of the cable line system.

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

[0038] (4) Using the system dynamics method as a carrier, the relationship between the monitoring variables of the cable equipment and the entire cable line system was established, which solved the problem of data islands in some online monitoring devices, realized data sharing between the equipment department and the dispatching department, and extended the research focus to the safety of equipment operation, realizing the expansion from single health status assessment of equipment and single electrical signal assessment to coordinated analysis of the two and the operating environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a framework diagram of the cable line holographic safety assessment model in the embodiment;

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

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

[0042] Figure 4 A schematic diagram of a process for constructing a system dynamics safety assessment equation in an embodiment;

[0043] Figure 5 This is a schematic diagram of multi-factor coupling in the embodiment;

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

[0045] Figure 7 Schematic diagram of the application architecture of the cable line safety assessment system in the embodiment. DETAILED DESCRIPTION

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

[0047] Example 1

[0048] In order to solve the problem that online monitoring devices and power equipment are independent of each other and monitoring information is difficult to integrate, this embodiment provides a cable line system dynamic safety assessment method that takes into account coupling effects, realizes coupling assessment between multiple variables, prevents cable system safety accidents caused by concurrent accidental factors, and effectively improves the safety level of power grid operation.

[0049] See also Figure 1 This is the framework diagram of the holographic safety assessment model for cable lines. The system dynamics safety assessment of the cable system considering the coupling effect refers to a safety assessment that integrates electrical variables and non-electrical variables. First, the cable system is analyzed, the important equipment of the cable line system is selected, and the electrical and non-electrical key monitoring variables of the equipment are selected from the three dimensions of electrical signals, equipment status and operating environment; then the relevant thresholds and parameters are determined through literature, design guidelines and historical data-based methods, and the failure probability function of different types of monitoring variables for equipment is established; secondly, the failure probability function of the cable equipment is obtained through the equipment failure probability function of different dimensions, and finally the failure probability function of the cable line system is obtained; finally, the system dynamics flow chart of the cable line system safety assessment considering the coupling effect is established to realize the safe operation status assessment of the cable line system.

[0050] This method comprises the following steps:

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

[0052] See also Figure 2 This is a schematic diagram of the hierarchical structure of the cable line system. The most representative and critical equipment of the cable line system are: cable body, cable terminal and cable intermediate joint;

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

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

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

[0056] Step S201, construct the fault probability function of the electrical signal dimension; if the load current and operating voltage of the cable equipment exceed a certain value, the temperature of the conductor and its accessories will rise, or even burn, so the load current and operating voltage should be strictly controlled below the maximum allowable range; if the switch signal value is 1, it means the equipment is normal, and if it is 0, it means the equipment is faulty. Therefore, the fault probability functions of the three electrical signal dimensions of load current, operating voltage and switch signal are pf1(t), pf2(t), and pf3(t), respectively:

[0057]

[0058]

[0059] In the formula are the operating thresholds of the load current and operating voltage of the cable equipment s, are the load current and operating voltage of cable equipment s at time t, a s (t) is the switch signal value of device s in the station at time t.

[0060] According to the component failure probability theory, based on the results of 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, constructing a failure probability function of the device status dimension;

[0063] The health index measures the health status of the equipment and is a bridge between the probability of equipment failure and the monitored variables. The deviation between the health status indicators of different equipment and the standard value is used to represent the impact of the variable on the equipment, which is represented by HI:

[0064]

[0065] In the formula is the working threshold of the i-th device status monitoring variable of cable device s; 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 influence of multiple variables. The interaction matrix principle diagram is as follows Figure 3 The formula for determining the weight of each variable is as follows:

[0067]

[0068] Where: n1 is the number of equipment status monitoring variables; J ij is the i-th equipment status monitoring variable X i X j The degree of influence; D i and E i are the sum of the influence of the ith variable on other variables and the sum of the influence; B i is the weight of the i-th state monitoring variable for equipment safety assessment.

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

[0070]

[0071] There is an aging process in the actual operation of the equipment, so the equipment failure rate l(t) is

[0072] l(t)=Ke -100C·μ(t)·HI'(t) (10)

[0073] Where K and C are proportional coefficients, and μ(t) is the equipment aging coefficient.

[0074] According to the investigation, the typical failure rate (lconst) corresponds to a health index of 0.8, while the minimum failure rate (lmin) corresponds to a perfect health state of the equipment, that is, a health index of 1. By analyzing historical data, the average failure rate of cable equipment can be determined, and the minimum failure rate is set to between 10% and 20% of the average failure rate. According to formula (10), the relationship between the failure rate and the probability of failure is obtained, and the failure probability function of the equipment status monitoring variable is obtained as follows:

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

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

[0077] Step S203, constructing a failure probability function of the operating environment dimension.

[0078] The function design of environmental factors mostly adopts low-complexity and practical exponential models, and has achieved ideal results in scientific research analysis. In order to reasonably construct the failure probability function of operating environment indicators, a piecewise function is introduced to improve the existing exponential empirical function, that is,

[0079]

[0080] Where M is the unknown coefficient of the model, which can be obtained based on objective historical data and expert experience; min y is the starting value of the equipment affected in the station; max is the maximum value for normal operation of the equipment; j (t) is the equipment failure rate caused by the jth environmental variable at time t.

[0081] The failure probability of the external environment on the equipment is obtained by the piecewise exponential function of the environmental variable in formula (12):

[0082]

[0083] Where: pe j (t) is the probability of equipment failure caused by the jth environmental variable at time t.

[0084] Considering the impact of the operating environment on the equipment, the failure probability function pe(t) of the operating environment dimension is obtained as follows:

[0085]

[0086] Where n2 is the number of operating environment monitoring variables.

[0087] Step S3, comprehensively analyzing the relationship between the monitoring variables in the three dimensions and constructing the failure probability function of the cable equipment.

[0088] The key variables selected in step S1 are important factors in the safe operation level of the equipment. Any abnormality in the electrical signal, equipment status and operating environment will cause an alarm, and the indicators are coupled with each other. The failure probability function X of the cable equipment multi-dimensional monitoring is obtained according to the series model based on the execution results of steps S201-S203. g1 (t) is

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

[0090] The failure probability function between different dimension monitoring variables and equipment is too complicated, so it is shown in the form of a process, taking the cable body as an example. Figure 4shown.

[0091] Step S4, constructing a comprehensive fault probability function of the cable line system according to the topological relationship and series connection model between the cable devices.

[0092] The cable line system is a multi-device series system. The Venn diagram is used to illustrate the idea of ​​safety assessment, such as Figure 5 As shown. If any device in the series system is in a faulty state, the entire cable line system is in a faulty state, where the failure probability of the key device is calculated by equation (15) in step S3. Taking into account the coupling effect of multiple device failures, the failure probability of the cable line system is established according to the series system reliability formula as follows:

[0093]

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

[0095] Step S5, constructing a system dynamics flow diagram for cable line system safety assessment to conduct safety assessment on the cable line system.

[0096] According to the functional relationship between the equipment failure probability function in step S4 and the cable line system failure probability function, a system dynamics flow diagram is constructed, such as Figure 6 The system dynamics flow diagram includes a plurality of nodes and the relationships between the nodes, wherein the nodes represent the equipment and monitoring variables of the cable line system.

[0097] Step S6, combining Vensim, Python and other technologies, using the SpringCloud microservice framework, design and develop a cable line safety assessment system. This step includes the following sub-steps:

[0098] Step S601, construct 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, design the database to realize the monitoring, query and preprocessing functions of collecting electrical and non-electrical characteristic data, perform status verification of the data acquisition device, push alarms for verification abnormalities, and realize the access of real-time monitoring information of the cable system, display of the system dynamics model, ledger configuration and other functions.

[0100] Step S603, using Vensim and Python technology to complete the development and implementation of the cable line system security protection model, realize the chain security protection function of the cable line system, and issue alarm information when the monitoring results show abnormalities. The system application architecture is as follows Figure 7 shown.

[0101] Compared with the traditional method, this method has the following beneficial effects:

[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 operating 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 operating status of cable equipment using the operating data of the cable line system.

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

[0105] (4) Using the system dynamics method as a carrier, the relationship between the monitoring variables of the cable equipment and the entire cable line system was established, solving the data island problem of some online monitoring devices and realizing data sharing between the equipment department and the dispatching department. In addition, the research focus was extended to the safety of equipment operation, realizing the expansion from the single health status assessment of the equipment and the single electrical signal assessment to the coordinated analysis of the two 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, and the one or more programs include instructions for executing the cable line system dynamic safety assessment method considering coupling effects as described in Example 1.

[0108] Example 3

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

[0110] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A cable line system dynamics safety assessment method considering coupling effects, characterized in that: The steps include: Select equipment for safety assessment in the cable line system 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 influence relationship between the monitoring variables is constructed, and the equipment failure function under each dimension is calculated based on the interaction matrix; Based on the equipment failure function in each dimension, a comprehensive failure probability function of the equipment is constructed; Constructing a comprehensive fault probability function of the cable line system based on the pre-constructed topological relationship between the devices and the comprehensive fault probability function of the devices; A system dynamics flow diagram is constructed based on the comprehensive fault probability function to achieve safety assessment of the cable line system.

2. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The construction of the interaction matrix reflecting the coupling influence relationship between the monitored variables is implemented by the following formula: Among them, n1 is the number of monitoring variables in the device status dimension, J ij is the status monitoring variable X of the i-th device i X j The degree of influence, D i and E i are the sum of the influence of the i-th variable on other variables and the sum of the influence, B i is the weight of the i-th state monitoring variable for equipment safety assessment.

3. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The calculation of the equipment failure function in each dimension based on the interaction matrix comprises the following steps: For the electrical signal dimension, the failure probability function of each monitoring variable is constructed, and the failure probability function of 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 a failure probability function of the device state dimension; For the operating environment dimension, a failure probability function of the environment dimension is constructed based on the piecewise function.

4. A cable line system dynamics safety assessment method 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 of the equipment for safety assessment is constructed based on the series model.

5. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The construction of the comprehensive fault probability function of the cable line system comprises the following steps: Based on the pre-built topological relationship between devices and the comprehensive fault probability function of the devices, the coupling influence of multi-device failures is comprehensively considered, and the comprehensive fault probability function of the cable line system is constructed based on the series system reliability formula.

6. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The system dynamics flow graph includes a plurality of nodes and relationships between the nodes, wherein the nodes represent equipment and monitoring variables of the cable line system.

7. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The safety assessment method further comprises the following steps: Build a security assessment system based on the SpringCloud microservice framework.

8. A cable line system dynamics safety assessment method considering coupling effects according to claim 7, characterized in that: The construction process of the safety assessment system includes the following steps: Build the system's application architecture and physical architecture; By designing the database, the monitoring, query and preprocessing functions of the collected electrical and non-electrical characteristic data can be realized, the status of the data acquisition device can be verified, and the alarm can be pushed for the abnormal verification information, so as to realize the access of the real-time monitoring information of the cable system, the display of the system dynamics model, and the configuration of the ledger; Complete the development and implementation of the cable line system security protection model, realize the system's chain security protection function, and issue alarm information when monitoring results show abnormalities.

9. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The equipment for safety assessment comprises a cable body, a cable terminal and a cable intermediate joint.

10. A cable line system dynamics safety assessment method considering coupling effects according to claim 1, characterized in that: The monitoring variables of the electrical signal dimension include load current, operating voltage and switch signal, the monitoring variables of the equipment status dimension include circulating current, core grounding current, partial discharge, equipment temperature and SF6 gas pressure, and the monitoring variables of the operating environment dimension include water level, humidity and temperature.

Images