Risk assessment method and device for GIS flashover fault

Abstract

The invention provides a GIS flashover fault risk assessment method and device, and belongs to the technical field of electric power engineering. The method comprises the steps that the defect type of the GIS flashover fault, the potential of a region where the GIS flashover fault is located and the scale magnitude of the GIS flashover fault are acquired; determining the defect form of the GIS flashover fault according to the defect type, the regional potential and the scale magnitude; determining at least two defect quantitative indexes of the GIS flashover fault according to the flashover evolution characteristics of the defect form, the physical process of abnormal discharge and the interface characteristics; obtaining values of at least two defect quantitative indexes corresponding to the defect form through a preset database; and fusing the values of the at least two defect quantitative indexes of the GIS flashover fault to obtain a risk assessment result of the GIS flashover fault. According to the method provided by the invention, risk assessment can be carried out on the GIS flashover fault more accurately.

Description

Technical Field

[0001] The present disclosure belongs to the technical field of power engineering, and particularly relates to a method and device for risk assessment of GIS flashover faults, an electronic device, a computer-readable storage medium, and a computer program product. Background Art

[0002] Ultra (extra) high voltage GIS is a core device in the power system. In recent years, GIS flashover faults have occurred many times in ultra high voltage substations and converter stations. According to statistics, in a certain year, the equipment outages caused by GIS flashover faults in a certain company's ultra high voltage reached 33 times (23 times in substations and 10 times in converter stations). GIS flashover faults will directly cause equipment damage and related line outages. The repair time of ultra high voltage GIS faults usually lasts up to 1 week. During the fault, it often leads to the abandonment of new energy, the reduction of channel transmission capacity, the short-term pressure on the safe operation of the power grid, the impact on the reliable power supply, and the resulting adverse social impacts. The reasons for GIS flashover faults are divided into foreign object discharge, poor assembly process, and component defects. The corresponding defects mainly include metal particles, internal defects of insulating parts, loosening and displacement of metal components. How to timely detect and warn of internal defects before GIS flashover and deal with them to avoid the expansion of fault impact or unnecessary temporary power outages is a difficult problem that needs to be solved urgently in current equipment management. Summary of the Invention

[0003] The present invention aims to at least solve one of the technical problems existing in the prior art, and provides a calculation method, a calculation device, a computer-readable storage medium, and a computer program product that can calculate the grid short-circuit ratio online in real time. The solution provided by the present disclosure can...

[0004] To achieve the above object, in a first aspect, the present disclosure provides a method for risk assessment of GIS flashover faults, the method including:

[0005] Obtain the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault is located, and the scale magnitude of the GIS flashover fault;

[0006] Determine the defect form of the GIS flashover fault according to the defect type, regional potential, and scale magnitude;

[0007] Determine at least two defect quantification indexes of the GIS flashover fault according to the flashover evolution characteristics of the defect form, the physical process and interface characteristics of abnormal discharge;

[0008] Obtain the values of at least two of the defect quantification indexes corresponding to the defect form through a preset database;

[0009] Fuse the values of at least two of the defect quantification indexes of the GIS flashover fault to obtain the risk assessment result of the GIS flashover fault.

[0010] In some embodiments, the types of defects include: corona, surface flashover, suspension, air gap, and particles;

[0011] The regional potential is divided into a high-potential region, a medium-potential region, and a low-potential region. Among them, the potential of the high-potential region is greater than that of the medium-potential region, and the potential of the medium-potential region is greater than that of the low-potential region;

[0012] The scale magnitudes are divided into a large-scale magnitude, a medium-scale magnitude, and a small-scale magnitude. Among them, the large-scale magnitude is sub-centimeter level, the medium-scale magnitude is millimeter level, and the small-scale magnitude is sub-millimeter level.

[0013] In some embodiments, according to the following table, determine the defect form of the GIS flashover fault:

[0014]

[0015] In some embodiments, the defect quantification indicators include an allowable voltage dimension indicator, an allowable time dimension indicator, and an allowable overvoltage dimension indicator.

[0016] In some embodiments, based on the flashover evolution characteristics of the defect form, the physical process of abnormal discharge, and the interface characteristics, determine at least two defect quantification indicators of the GIS flashover fault, including:

[0017] Based on the flashover evolution characteristics of the defect form, the physical process of abnormal discharge, and the interface characteristics, determine the discharge amount of partial discharge generated by the defect, the development speed of insulation deterioration of the defect, and the flashover probability of the defect under transient overvoltage;

[0018] Based on the discharge amount, the development speed, and the flashover probability, determine at least two defect quantification indicators of the GIS flashover fault.

[0019] In some embodiments, the method further includes:

[0020] Build an experimental model reflecting the GIS flashover fault;

[0021] By changing the defect form of the experimental model, simulate the process of the GIS flashover fault from the initiation of partial discharge to the occurrence of the flashover fault, and obtain the relevant parameters corresponding to each defect form;

[0022] According to the relevant parameters of each defect form, calculate at least two defect quantification indicators corresponding to the defect form, and obtain the preset database, where the preset database is a defect quantification indicator distribution database of the defect form.

[0023] Second aspect, embodiments of the present disclosure further provide a risk assessment device for GIS flashover faults, the device comprising:

[0024] A first acquisition module, configured to acquire the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault is located, and the scale magnitude of the GIS flashover fault;

[0025] A first determination module, configured to determine the defect form of the GIS flashover fault according to the defect type, regional potential, and scale magnitude;

[0026] A second determination module, configured to determine at least two defect quantification indicators of the GIS flashover fault according to the flashover evolution characteristics of the defect form, the physical process of abnormal discharge, and the interface characteristics;

[0027] A second acquisition module, configured to obtain the values of at least two of the defect quantification indicators corresponding to the defect form through a preset database;

[0028] A fusion module, configured to fuse the values of at least two of the defect quantification indicators of the GIS flashover fault to obtain a risk assessment result of the GIS flashover fault.

[0029] Third aspect, the present disclosure further provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, it implements the calculation method of the first aspect above.

[0030] Fourth aspect, the present disclosure further provides a computer-readable storage medium, which stores a computer program for executing the calculation method of the first aspect above.

[0031] Fifth aspect, the present disclosure further provides a computer program product, comprising computer programs / instructions, and when the computer programs / instructions are executed by a processor, the steps of the calculation method of the first aspect above are implemented. Embodiments of the present disclosure determine the specific defect form of the GIS fault through multiple dimensions, and combine the flashover evolution characteristics of the defect form, the physical process of abnormal discharge, and the interface characteristics to determine multiple defect quantification indicators corresponding to the defect form, so as to obtain a risk assessment result based on the multiple defect quantification indicators. The risk assessment method for GIS flashover faults provided by the present disclosure can more accurately determine the priority of fault defect maintenance and inspection in GIS devices, improve the understanding and prediction ability of potential fault risks in GIS devices, reduce the risk of unexpected power outages, and optimize resource allocation, thereby improving the reliability and safety of the power system. Description of the Drawings

[0032] To more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present disclosure. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0033] Figure 1 It is a flowchart of a risk assessment method for GIS flashover faults provided by an embodiment of the present disclosure;

[0034] Figures 2 - 3 They are respectively schematic diagrams of the distribution of two defect quantification indexes of tip-type defects provided by the present disclosure;

[0035] Figure 4 It is a structural block diagram of a risk assessment device for GIS flashover faults provided by an embodiment of the present disclosure;

[0036] Figure 5 It is a schematic diagram of the entity structure of an electronic device provided by an embodiment of the present disclosure. Detailed implementation manners

[0037] To enable those skilled in the art to better understand the technical solutions of the present invention, the following further describes the present invention in detail and completely in conjunction with the accompanying drawings and specific implementation manners. Obviously, the described embodiments are only some embodiments of the present disclosure, rather than all embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present disclosure.

[0038] After investigation, the following characteristics exist in the internal flashover faults of GIS:

[0039] (1) The internal flashover of GIS is closely related to the form of defects

[0040] According to statistics, in recent years, a total of 284 flashover faults have occurred in the ultra-high voltage GIS of a certain company. After comprehensive analysis and judgment by experts, up to 91.2% of the fault cases are judged to be related to the form of defects. For example, in a certain year at a certain substation, there were small air gaps in the pot-type insulators of 500kV HGIS, and arcs were generated at the weak insulation part of the low potential, and finally through-discharge occurred.

[0041] (2) The flashover risks of different defect forms are different

[0042] Analysis of multiple internal defects and fault cases in GIS shows that the internal flashover risks of different forms of defects are also different, and it is necessary to study the internal flashover risk assessment method for different defect forms. For example, in a certain month and year, a strong suspended UHF signal characteristic occurred in the 500 kV HGIS of a substation. After disassembly and analysis, it was found that the low-potential particle catcher was loose, which was likely to cause internal discharge faults. Since its commissioning, there have been significant persistent insulation-type partial discharge signals in the support insulators of the branch bus in the 1000 kV GIS string of a substation. However, the equipment has been operating without faults for many years, and the flashover risk is relatively low.

[0043] Based on the above characteristics of GIS internal flashover, on the one hand, the embodiments of the present disclosure provide a risk assessment method for GIS flashover faults.

[0044] Figure 1 The flowchart of a risk assessment method for GIS flashover faults provided by the embodiments of the present disclosure is shown in Figure 1 As shown, the method specifically includes the following steps:

[0045] S11. Obtain the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault is located, and the scale magnitude of the GIS flashover fault.

[0046] Specifically, the defect type of the GIS flashover fault refers to various defect types that may cause flashover phenomena in GIS.

[0047] In some embodiments, the defect types of the GIS flashover fault include: corona, surface flashover, suspension, air gap, and microparticles.

[0048] In some embodiments, the regional potential is divided into a high-potential area, a medium-potential area, and a low-potential area. Among them, the potential of the high-potential area is greater than the potential of the medium-potential area, and the potential of the medium-potential area is greater than the potential of the low-potential area.

[0049] In some embodiments, the scale magnitude is divided into a large scale magnitude, a medium scale magnitude, and a small scale magnitude. Among them, the large scale magnitude is sub-centimeter level, the medium scale magnitude is millimeter level, and the small scale magnitude is sub-millimeter level.

[0050] S12. Determine the defect form of the GIS flashover fault according to the defect type, regional potential, and scale magnitude.

[0051] Specifically, the defect form of the GIS flashover fault refers to the specific physical form or state that may cause flashover in GIS. For example, metal microparticles, contaminants on the surface of insulators, internal air gaps or cracks, etc. The defect form of the GIS flashover fault refers to physical defects that can be directly observed or detected actively.

[0052] In some embodiments, each defect type of GIS flashover faults may include one or more defect forms of GIS flashover faults.

[0053] In the embodiments of the present disclosure, based on historical fault cases of ultra - extra high voltage GIS, three dimensions, namely defect type, regional potential, and scale magnitude, are determined to describe the defect form.

[0054] The embodiments of the present disclosure classify the defect forms of GIS faults through three dimensions, which can more accurately determine the defects in GIS equipment, improve the ability to understand and predict the potential fault risks of GIS equipment, and reduce the risk of unexpected power outages.

[0055] S13. Determine at least two defect quantification indicators of the GIS flashover fault according to the flashover evolution characteristics, physical process of abnormal discharge, and interface characteristics of the defect form.

[0056] Specifically, the flashover evolution in GIS is a complex process involving the interaction of multiple physical mechanisms and factors. Among them, the flashover evolution characteristics of GIS defect forms include surface charge accumulation and flashover, the influence of metal particles, the influence of gas adsorption layers, the characteristics of flashover paths, local discharge signal characteristics, changes in flashover voltage, and heterogenous electric field distortion, etc. Different defect forms in GIS faults have different corresponding evolution processes. For example, for the defect form with the defect type of particles, more attention is paid to the influence of metal particles during the flashover evolution process. Therefore, the defect quantification indicators determined for the defect form corresponding to this GIS fault are related to the influence of metal particles. Another example is that for the defect form with the defect type of air gap, more attention may be paid to the influence of gas adsorption layers during the flashover evolution process. Therefore, the defect quantification indicators determined for the defect form corresponding to this GIS fault are related to the influence of gas adsorption layers, and so on.

[0057] The physical process of abnormal discharge in GIS faults includes the generation of partial discharge, charge movement and electromagnetic wave propagation, floating potential body discharge, metal tip discharge, metal particle discharge on the insulation surface, etc. Different defect forms in GIS faults may have different corresponding physical processes of abnormal discharge, and their corresponding defect quantification indicators are also different. The embodiments of the present disclosure can determine specific defect quantification indicators according to the physical process of abnormal discharge in GIS faults.

[0058] In GIS faults, the characteristics of the interfaces corresponding to different defects are different. Among them, the interface characteristics of the defect form include gas interface characteristics, solid interface characteristics, etc., and the corresponding defect quantification indicators for different interface characteristics are also different.

[0059] Among them, the defect quantification indicators corresponding to different defect forms in GIS faults may be different or may be at least partially the same.

[0060] In the embodiments of the present disclosure, by determining the defect quantification indexes based on the flashover evolution process corresponding to the specific defect form in the GIS fault, the physical process of abnormal discharge, and the corresponding interface characteristics, the GIS fault corresponding to this defect form can be more accurately quantified and evaluated, improving the understanding and prediction ability of the potential fault risks of GIS equipment, reducing the risk of unexpected power outages, and optimizing resource allocation, thereby improving the reliability and safety of the power system.

[0061] S14. Obtain the values of at least two of the defect quantification indexes corresponding to the defect form through a preset database.

[0062] Specifically, the preset database is a distribution database of defect quantification indexes for the defect form and can be used as a reference database for on-site GIS fault calculation.

[0063] S15. Fuse the values of at least two of the defect quantification indexes of the GIS flashover fault to obtain the risk assessment result of the GIS flashover fault.

[0064] Specifically, after obtaining the defect quantification indexes corresponding to the defect form, it is necessary to fuse multiple defect quantification indexes to obtain the final flashover risk.

[0065] In the embodiments of the present disclosure, the specific defect form of the GIS fault is determined through multiple dimensions, and combined with the flashover evolution characteristics, the physical process of abnormal discharge, and the interface characteristics of the defect form, multiple defect quantification indexes corresponding to this defect form are determined. Thus, based on these multiple defect quantification indexes, a risk assessment result is obtained. The risk assessment method for GIS flashover faults provided by the present disclosure can more accurately determine the priority of fault defect maintenance and inspection in GIS equipment, improve the understanding and prediction ability of the potential fault risks of GIS equipment, reduce the risk of unexpected power outages, and optimize resource allocation, thereby improving the reliability and safety of the power system.

[0066] In some embodiments, step S12 specifically determines the defect form of the GIS flashover fault according to the following table:

[0067]

[0068] Specifically, it can be intuitively seen from the above table the defect forms corresponding to the combinations of each dimension in the three dimensions of defect type, regional potential, and scale magnitude.

[0069] As shown in the above table, in some embodiments, for a GIS flashover fault with a corona defect type and a high potential region in the regional potential region, based on the degree of concavity and convexity of the conductor surface, the defect form of this GIS fault is determined to be one of conductor bulge, uneven conductor surface, and conductor burr. Among them, the degree of concavity and convexity of the conductor surface corresponding to the three defect forms of conductor bulge, uneven conductor surface, and conductor burr decreases in sequence. Optionally, a first range, a second range, and a third range are preset. If the degree of concavity and convexity of the conductor surface corresponding to this GIS flashover fault is within the first range, it is determined that the defect form of this GIS flashover fault is a conductor bulge; if the degree of concavity and convexity of the conductor surface corresponding to this GIS flashover fault is within the second range, it is determined that the defect form of this GIS flashover fault is an uneven conductor surface; if the degree of concavity and convexity of the conductor surface corresponding to this GIS flashover fault is within the third range, it is determined that the defect form of this GIS flashover fault is a conductor burr. Among them, the degree of concavity and convexity corresponding to the first range is greater than the degree of concavity and convexity corresponding to the second range, and the degree of concavity and convexity corresponding to the second range is greater than the degree of concavity and convexity corresponding to the third range.

[0070] In some embodiments, cracks are classified into cracked, having fine cracks, and having microcracks based on the size of the cracks. Among them, the crack sizes corresponding to cracked, having fine cracks, and having microcracks also decrease in sequence. Similarly, a fourth range, a fifth range, and a sixth range are preset. If the crack corresponding to this GIS flashover fault is within the fourth range, it is determined that the defect form of this GIS flashover fault is cracked; if the crack corresponding to this GIS flashover fault is within the fifth range, it is determined that the crack of this GIS flashover fault is having fine cracks; if the crack corresponding to this GIS flashover fault is within the sixth range, it is determined that the crack of this GIS flashover fault is having microcracks. Among them, the crack size corresponding to the fourth range is greater than the crack size corresponding to the fifth range, and the crack corresponding to the fifth range is greater than the crack corresponding to the sixth range. It can be understood that the position of the crack of a specific GIS fault also needs to be determined based on the defect type, the regional potential where the fault occurs, and the scale order of the fault. Here, only cracked, having fine cracks, and having microcracks are described.

[0071] In some embodiments, the falling objects are classified into fragments, debris, and dust based on their size. Among them, the sizes of fragments, debris, and dust decrease in sequence. Similarly, a seventh range, an eighth range, and a ninth range are preset. If the size of the falling object corresponding to the GIS flashover fault is within the fourth range, it is determined that the falling object in the GIS flashover fault is a fragment; if the size of the falling object corresponding to the GIS flashover fault is within the eighth range, it is determined that the falling object in the GIS flashover fault is debris; if the falling object corresponding to the GIS flashover fault is within the ninth range, it is determined that the falling object in the GIS flashover fault is dust. Among them, the size of the falling object corresponding to the seventh range is greater than the size of the falling object corresponding to the eighth range, and the size of the falling object corresponding to the eighth range is greater than the size of the falling object corresponding to the ninth range. It can be understood that the falling position of the falling object of a specific GIS fault also needs to be determined based on the defect type, the regional potential where the fault occurs, and the scale magnitude of the fault. Here, only fragments, debris, and dust are described.

[0072] Referring to the above table, taking the loosening fault of the three - combined metal insert as an example, this fault mainly occurs near the three - combination of the high - voltage end shield ball and the pot - type insulator. The metal insert on the pot - type insulator is not tightly fixed. This part of the defect usually causes floating discharge represented by a relatively large discharge amount. Compared with the loosening or falling off of the shield cover, the scale magnitude of this defect form is smaller. Therefore, based on the three classification dimensions, it is classified as a defect in the floating type, medium - scale, and high - potential region. Dust, metal fragments, or metal debris are common defect forms in GIS. Foreign objects such as dust may be scattered on the surface of the pot - type insulator, the high - voltage conductor, or the three - combination point. For each potential region, the present disclosure has made a detailed classification. At the same time, in terms of scale magnitude, metal fragments and metal debris can be generated by mechanical friction caused by equipment vibration, and their sizes are relatively large, usually in the sub - centimeter and millimeter levels. Dust is usually affected by the operating environment of the GIS equipment. For example, in a certain place where there is often strong wind and few vegetation, and there are often sand and dust weather. Correspondingly, when the GIS equipment is installed or disassembled for inspection, dust will be deposited. Its size is relatively small, usually in the sub - millimeter level.

[0073] The embodiments of the present disclosure divide the defect forms from three dimensions: the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault occurs, and the scale magnitude of the GIS flashover fault, making the divided defect forms more refined, which can more accurately determine the priority of fault defect maintenance and inspection in GIS equipment, improve the understanding and prediction ability of the potential fault risks of GIS equipment, reduce the risk of unexpected power outages, and optimize resource allocation, thereby improving the reliability and safety of the power system.

[0074] In some embodiments, the defect quantification indexes include an allowable voltage dimension index, an allowable time dimension index, and an allowable over - voltage dimension index.

[0075] Specifically, during actual operation, the process of abnormal discharge developing until insulation flashover in GIS flashover faults is mainly affected by the discharge amount of defects, the discharge development speed, and the accidental probability of overvoltage. For different defect shapes, appropriate defect quantification indicators need to be selected to comprehensively quantify and evaluate the flashover risks of different forms of defects.

[0076] Among them, the allowable voltage dimension (A1) can quantitatively represent the discharge amount when partial discharge occurs in the defect. It is quantified by using the ratio of the partial discharge inception voltage PDIV of the defect to the breakdown voltage BDV (A1 = PDIV / BDV). The value range of this index is 0 - 1, and this quantification index reflects the discharge amount of partial discharge.

[0077] The allowable time dimension (A2) can quantitatively represent the development speed of insulation deterioration caused by the defect. It is quantified by using the ratio of the discharge amount dQ per unit time of the defect to the total discharge amount Q during the discharge process, and the allowable time dimension A2 = dQ / Q. The value range of this index is 0 - 1, and different defect forms are affected by the discharge development speed to different extents.

[0078] The allowable overvoltage dimension (A3) can quantitatively represent the flashover probability of the defect under transient overvoltage. It is quantified by using the cumulative distribution of the time-delay Weibull shape parameter (A3 = Weibull(α)). The Weibull distribution is the theoretical basis for reliability analysis and life testing, and the value range of this index is 0 - 1. Defect forms with an impact coefficient greater than 1 have a higher tolerance to overvoltage events, and breakdown or flashover may not occur even when the overvoltage exceeds the rated operating voltage of the equipment.

[0079] In some embodiments, step S13 specifically includes the following steps:

[0080] S131. Determine the discharge amount of partial discharge generated by the defect, the development speed of insulation deterioration of the defect, and the flashover probability of the defect under transient overvoltage according to the flashover evolution characteristics of the defect form, the physical process of abnormal discharge, and the interface characteristics.

[0081] S132. Determine at least two defect quantification indicators for the GIS flashover fault according to the discharge amount, the development speed, and the flashover probability.

[0082] Specifically, optionally, the defect categories of insulation defects in GIS equipment include tip type, surface type, floating type, air gap type, and particle type.

[0083] Among them, tip type defects usually refer to metal tips or protrusions in GIS equipment. Due to their sharp shapes, they will cause strong electric field distortion near them, increasing the risk of partial discharge.

[0084] Surface-type defects involve unevenness or damage on the surface of insulators in GIS equipment, which may lead to surface discharge. This type of discharge usually occurs on the surface of solid insulation, such as the surface of insulators.

[0085] Suspended-type defects refer to the discharge between immovable metal objects inside GIS and adjacent equipment under the action of an electric field. This type of discharge has a relatively high amplitude, the discharge pulse amplitude is stable, and the adjacent discharge time intervals are basically the same.

[0086] Air-gap-type defects involve air gaps inside insulators in GIS equipment. These air gaps may cause partial discharge, especially when there are cracks or other defects in the insulators.

[0087] Particle-type defects mainly refer to metal particles in GIS equipment. These particles may be generated during production, assembly, or operation, and they may move under the action of an electric field and cause partial discharge.

[0088] In some embodiments, based on the defect form of the GIS flashover fault, the defect category corresponding to this defect form can be determined.

[0089] Table 1.2 is a correspondence table between defect quantification indicators and defect categories provided by the present disclosure.

[0090] Referring to Table 1.2 below, the allowable voltage dimension (A1) is not applicable to the risk calculation of defect forms with high discharge amounts and easy discharge saturation at the inception discharge voltage (such as suspended type), and the allowable voltage dimension is applicable to the risk calculation of tip-type, surface-type, air-gap-type, and particle-type defects. Embodiments of the present disclosure can determine which category of defect this defect form belongs to based on the discharge amount of the partial discharge generated by the defect, and then determine whether to use the allowable voltage dimension as one of the defect quantification indicators.

[0091] Since defects related to solid insulation are not allowed to exist for a long time, while defects related to gas insulation are the opposite. Therefore, referring to Table 1.2 below, the allowable time dimension (A2) is applicable to the risk calculation of surface-type and air-gap-type defects. Embodiments of the present disclosure can determine which defect this defect form belongs to based on the development speed of the defect, and then determine whether to use the allowable time dimension as one of the defect quantification indicators.

[0092] Referring to Table 1.2 below, the allowable overvoltage dimension (A3) is not applicable to the risk calculation of surface-type and air-gap-type defects, and is applicable to the risk calculation of tip-type, suspended-type, and particle-type defect categories. Embodiments of the present disclosure can determine which defect this defect form belongs to based on the flashover probability of the defect, and then determine whether to use the allowable overvoltage dimension as one of the defect quantification indicators.

[0093] Table 1.2 Correspondence table between defect quantification indicators and defect categories

[0094] Allowable voltage dimension index Allowable time dimension index Allowable overvoltage dimension index Tip type √ √ Surface type √ √ Suspended type √ Air gap type √ √ Particle type √ √

[0095] In some embodiments, the method not only includes steps S11 to S15, but also includes the step of obtaining a preset database, which specifically includes the following steps:

[0096] S16. Build an experimental model that reflects the flashover fault of GIS.

[0097] S17. By changing the defect form of the experimental model, simulate the process of GIS flashover fault from partial discharge initiation to flashover fault, and obtain the relevant parameters corresponding to each defect form.

[0098] S18. Calculate at least two defect quantification indexes corresponding to the defect form according to the relevant parameters of each defect, and obtain the preset database, where the preset database is a defect quantification index distribution database of defect forms.

[0099] Specifically, Figures 2 - 3 They are respectively schematic diagrams of the distribution of two defect quantification indexes of the tip-type defect provided by the present disclosure.

[0100] By building a full-scale experimental model that can reflect the flashover fault of GIS, the process of internal defects from partial discharge initiation to flashover fault can be simulated under the same conditions as the on-site environment, and a full-scale GIS defect abnormal discharge to flashover risk test can be carried out. Furthermore, the values of relevant parameters during the occurrence of GIS flashover fault can be obtained, and the values of defect quantification indexes corresponding to the GIS flashover fault can be obtained based on the relevant parameters.

[0101] Specifically, each defect form corresponds to a defect category, and different defect forms may correspond to the same defect category. Continuously calculating the corresponding defect quantification indexes according to different defect forms can obtain the numerical distribution of a certain category of defects, and thus obtain the values of all defect quantity indexes corresponding to the defect form. For this defect form, the defect quantification index distribution formed by the full-scale test described above is the reference database that can be used for on-site risk calculation.

[0102] Among them, changing the defect form can be specifically achieved by fixing the defect type unchanged and changing the defect potential region and scale magnitude. Of course, the defect form can also be changed through other forms. For example, fixing the regional potential and changing the defect type and scale magnitude, etc. The present disclosure does not make any limitations in this regard.

[0103] Referring to Figures 2 - 3 , for the tip-type defect, it includes the allowable voltage dimension A1 and the allowable overvoltage dimension A3.

[0104] In some embodiments, step S15 involves fusing the values of at least two defect quantification indicators of the GIS flashover fault to obtain the risk assessment result of the GIS flashover fault. Specifically, it includes: fusing the values of at least two defect quantification indicators of the GIS flashover fault through a multiple regression model to obtain the risk assessment result of the GIS flashover fault.

[0105] Specifically, after obtaining the defect quantification indicator values corresponding to the defect forms through a preset database, it is necessary to fuse multiple defect quantification indicators to output the final flashover risk. Among them, the multiple regression model is a mathematical model in statistics used to study the relationship between one dependent variable and multiple independent variables. The multiple regression model includes the weights of each indicator and the unexplained error term (normal distribution), and the model parameters are estimated by minimizing the sum of the squares of the error terms. After the multiple regression model is established, it is necessary to conduct diagnostics to test whether the model assumptions are met, and its effectiveness can be tested through methods such as residual analysis and variance factor inflation. The multiple regression model can help us understand the influence of different independent variables on the dependent variable and provide prediction and decision-making support. In the stage of fusing defect quantification indicators, multi-dimensional analysis indicators ultimately need to obtain a certain definite risk assessment indicator. This process involves multi-criteria evaluation and weight allocation of each indicator. Using the multiple regression model can comprehensively consider the decision-making levels of multi-dimensional indicators and achieve the fusion of multi-index risk quantification assessment.

[0106] A risk assessment method for GIS flashover faults provided by the present disclosure is based on ultra-high voltage and extra-high voltage GIS fault cases, determines three dimensions of defect type, regional potential, and scale magnitude to describe the defect form; proposes defect quantification indicators suitable for different defect categories based on multi-dimensional defect form classification; selects appropriate defect quantification indicators based on the flashover evolution characteristics of different forms of defects and the physical processes and interface characteristics of abnormal discharges; forms a distribution database of defect quantification indicators corresponding to the defect form based on GIS test sample data; obtains the values of defect quantification indicators corresponding to the defect form through the database, and uses a multinomial logistic regression model to complete the fusion of defect quantification indicators to achieve the ranking of flashover risks. The purpose of the present disclosure is to improve the understanding and prediction ability of the potential fault risks of GIS equipment, thereby improving the reliability and safety of the power system. Through multi-dimensional quantitative risk assessment, the priorities of maintenance and inspection can be determined more accurately, the risk of unexpected power outages can be reduced, and resource allocation can be optimized.

[0107] In a second aspect, based on the same inventive concept, an embodiment of the present disclosure also provides a risk assessment device for GIS flashover faults.

[0108] Figure 4The block diagram of a risk assessment device 400 for GIS flashover faults provided by an embodiment of the present disclosure. As Figure 4 shown, the device 400 includes a first acquisition module 401, a first determination module 402, a second determination module 403, a second acquisition module 404, and a fusion module 405.

[0109] Among them, the first acquisition module 401 is used to acquire the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault is located, and the scale magnitude of the GIS flashover fault.

[0110] The first determination module 402 is used to determine the defect form of the GIS flashover fault according to the defect type, regional potential, and scale magnitude.

[0111] The second determination module 403 is used to determine at least two defect quantification indicators of the GIS flashover fault according to the flashover evolution characteristics of the defect form, the physical process and interface characteristics of abnormal discharge.

[0112] The second acquisition module 404 is used to obtain the values of at least two of the defect quantification indicators corresponding to the defect form through a preset database.

[0113] The fusion module 405 is used to fuse the values of at least two of the defect quantification indicators of the GIS flashover fault to obtain the risk assessment result of the GIS flashover fault.

[0114] In some embodiments, the defect type includes: corona, surface flashover, suspension, air gap, and particle.

[0115] In some embodiments, the regional potential is divided into a high potential area, a medium potential area, and a low potential area. Among them, the potential of the high potential area is greater than the potential of the medium potential area, and the potential of the medium potential area is greater than the potential of the low potential area.

[0116] In some embodiments, the scale magnitude is divided into a large scale magnitude, a medium scale magnitude, and a small scale magnitude. Among them, the large scale magnitude is sub - centimeter level, the medium scale magnitude is millimeter level, and the small scale magnitude is sub - millimeter level.

[0117] In some embodiments, the first determination module 402 is specifically used to determine the defect form of the GIS flashover fault according to the following table:

[0118]

[0119] In some embodiments, the defect quantification indicators include an allowable voltage dimension indicator, an allowable time dimension indicator, and an allowable over - voltage dimension indicator.

[0120] In some embodiments, the second determination module 403 includes a first determination sub-module and a second determination sub-module.

[0121] Among them, the first determination sub-module is configured to determine the discharge amount of partial discharge generated by the defect, the development speed of insulation deterioration of the defect, and the flashover probability of the defect under transient overvoltage according to the flashover evolution characteristics of the defect form, the physical process of abnormal discharge, and the interface characteristics.

[0122] The second determination sub-module is configured to determine at least two defect quantification indicators of the GIS flashover fault according to the discharge amount, the development speed, and the flashover probability.

[0123] In some embodiments, the apparatus 400 not only includes a first acquisition module 401, a first determination module 402, a second determination module 403, a second acquisition module 404, and a fusion module 405, but also includes a generation module, and the generation module is configured to generate a preset database.

[0124] In some embodiments, the generation module includes a construction module, a simulation module, and a calculation module.

[0125] Among them, the construction module is configured to construct an experimental model reflecting the GIS flashover fault.

[0126] The simulation module is configured to simulate the process of the GIS flashover fault from the initiation of partial discharge to the occurrence of the flashover fault by changing the defect form of the experimental model, and obtain the relevant parameters corresponding to each defect form.

[0127] The calculation module is configured to calculate at least two defect quantification indicators corresponding to each defect form according to the relevant parameters, and obtain the preset database, where the preset database is a defect quantification indicator distribution database of the defect form.

[0128] It can be understood that for the specific details and corresponding technical effects of the apparatus 400 provided in the embodiments of the present disclosure, reference can be made to the embodiments of any of the risk assessment methods in the first aspect above, and details will not be repeated here.

[0129] In a third aspect, an embodiment of the present disclosure further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the method described in any item of the first aspect above is implemented.

[0130] Specifically, Figure 5 is a schematic diagram of the entity structure of the electronic device provided in the embodiment of the present disclosure, as Figure 5As shown, the electronic device 005 includes a processor 501, a memory 502, and a bus 503. Among them, the processor 501 and the memory 502 communicate with each other through the bus 503.

[0131] The processor 501 is used to call program instructions in the memory 502 to execute the methods provided in the above method embodiments.

[0132] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium storing a computer program of the method described in any one of the above first aspects.

[0133] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product including a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps of the method described in any one of the above first aspects are implemented.

[0134] Those skilled in the art should understand that the embodiments of the present disclosure can be provided as a method, a system, or a computer program product. Therefore, the present disclosure can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure can adopt 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.

[0135] The present disclosure is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in one Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0136] These computer program instructions can also be stored in a computer-readable memory capable of guiding a computer or other programmable data processing devices to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured product including instruction means, and the instruction means implements the specified functions in one Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0137] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are executed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions for implementing the functions specified in one process or a plurality of processes and / or blocks Figure 1 one or more processes and / or blocks Figure 1 steps for the functions specified in one block or a plurality of blocks.

[0138] Specific embodiments are applied in the present disclosure to elaborate the principles and implementation manners of the present disclosure. The description of the above embodiments is only used to help understand the method and its core idea of the present disclosure; at the same time, for those of ordinary skill in the art, according to the idea of the present disclosure, there will be changes in the specific implementation manners and application scopes. In summary, the content of this specification should not be construed as a limitation to the present disclosure.

Claims

1. A risk assessment method for GIS flashover faults, characterized in that, The method includes: Obtaining the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault is located, and the scale magnitude of the GIS flashover fault; Determining the defect form of the GIS flashover fault according to the defect type, regional potential, and scale magnitude; Determining at least two defect quantification indexes of the GIS flashover fault according to the flashover evolution characteristics, physical process of abnormal discharge, and interface characteristics of the defect form; Obtaining the values of at least two of the defect quantification indexes corresponding to the defect form through a preset database; Fusing the values of at least two of the defect quantification indexes of the GIS flashover fault to obtain the risk assessment result of the GIS flashover fault.

2. The method according to claim 1, characterized in that The defect types include: corona, surface flashover, suspension, air gap, and particle; The regional potential is divided into a high potential area, a medium potential area, and a low potential area. Among them, the potential of the high potential area is greater than the potential of the medium potential area, and the potential of the medium potential area is greater than the potential of the low potential area; The scale magnitude is divided into a large scale magnitude, a medium scale magnitude, and a small scale magnitude. Among them, the large scale magnitude is sub - centimeter level, the medium scale magnitude is millimeter level, and the small scale magnitude is sub - millimeter level.

3. The method according to claim 2, wherein Determine the defect form of the GIS flashover fault according to the following table:

4. The method according to claim 1, wherein The defect quantification indexes include an allowable voltage dimension index, an allowable time dimension index, and an allowable over - voltage dimension index.

5. The method according to claim 4, characterized in that, The determining at least two defect quantification indexes of the GIS flashover fault according to the flashover evolution characteristics, physical process of abnormal discharge, and interface characteristics of the defect form includes: Determining the discharge amount of partial discharge generated by the defect, the development speed of insulation deterioration of the defect, and the flashover probability of the defect under transient over - voltage according to the flashover evolution characteristics, physical process of abnormal discharge, and interface characteristics of the defect form; Determining at least two defect quantification indexes of the GIS flashover fault according to the discharge amount, the development speed, and the flashover probability.

6. The method according to claim 1, characterized in that, The method further includes: Building an experimental model reflecting the GIS flashover fault; Simulating the process of the GIS flashover fault from the start of partial discharge to the occurrence of flashover fault by changing the defect form of the experimental model, and obtaining the relevant parameters corresponding to each defect form; Calculating at least two defect quantification indexes corresponding to each defect form according to the relevant parameters of each defect form to obtain the preset database, where the preset database is a defect quantification index distribution database of defect forms.

7. A risk assessment device for GIS flashover faults, characterized in that, The device includes: A first acquisition module, configured to acquire the defect type of the GIS flashover fault, the regional potential where the GIS flashover fault is located, and the scale magnitude of the GIS flashover fault; A first determination module, configured to determine the defect form of the GIS flashover fault according to the defect type, regional potential, and scale magnitude; A second determination module, configured to determine at least two defect quantification indexes of the GIS flashover fault according to the flashover evolution characteristics, physical process of abnormal discharge, and interface characteristics of the defect form; A second acquisition module, configured to obtain values of at least two of the defect quantification metrics corresponding to the defect form through a preset database; A fusion module, configured to fuse values of at least two of the defect quantification metrics of the GIS flashover fault to obtain a risk assessment result of the GIS flashover fault.

8. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program for executing the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, the steps of the method according to any one of claims 1 to 6 are implemented.

Images