Fault detection method and device of power grid system, computer equipment and storage medium

Abstract

The invention relates to a fault detection method and device of a power grid system, computer equipment and a storage medium. The method comprises the following steps: acquiring short-circuit information of a power grid system, wherein the short-circuit information comprises short-circuit current; inputting the short-circuit current into a preset fault probability model to obtain a fault probability; calculating a short-circuit current heat effect value based on the short-circuit information; based on a preset equipment damage degree evaluation threshold value, obtaining a damage degree value corresponding to the heat effect value; obtaining a loss range based on a network topology model, and obtaining a fault value based on the loss range and the damage degree value; and obtaining a fault result based on the fault value and the fault probability.

Description

Technical Field

[0001] This application relates to the field of power technology, and in particular to a fault detection method, device, computer equipment, and storage medium for a power grid system. Background Technology

[0002] In the long-term and complex operation of power grid systems, short-circuit faults, as a highly destructive type of fault, constantly threaten the safety and stability of the power grid. Short-circuit faults are usually caused by a variety of factors, including aging of electrical equipment leading to decreased insulation performance, damage to lines caused by external forces, insulation breakdown caused by harsh natural environments, and human error. Once a short-circuit fault occurs, the current instantly loses its original normal path and instead flows through the short-circuit point with extremely low resistance, forming a powerful short-circuit current.

[0003] In related technologies, some power grid systems use current sensors with poor accuracy and slow response speed, which cannot quickly capture the sudden changes in short-circuit current, resulting in delays and errors in the acquired current data. Summary of the Invention

[0004] Therefore, it is necessary to provide a fault detection method, device, computer equipment, and storage medium for a power grid system to address the aforementioned technical problems.

[0005] Firstly, this application provides a fault detection method for a power grid system. The method includes:

[0006] Obtain short-circuit information of the power grid system, wherein the short-circuit information includes short-circuit current;

[0007] The short-circuit current is input into a preset fault probability model to obtain the fault probability;

[0008] Based on the short-circuit information, the thermal effect value of the short-circuit current is calculated;

[0009] Based on a preset equipment damage assessment threshold, the damage level value corresponding to the thermal effect value is obtained;

[0010] The loss range is obtained based on the network topology model, and the fault value is obtained based on the loss range and the degree of damage.

[0011] Based on the fault value and the fault probability, the fault result is obtained.

[0012] In one embodiment, the method further includes:

[0013] If the fault result is greater than the preset fault result, the short-circuit current over-limit threshold is updated;

[0014] An alarm message is issued if the short-circuit current exceeds the updated short-circuit current over-limit threshold.

[0015] In one embodiment, the loss range obtained based on the network topology model, and the fault value obtained based on the loss range and the degree of damage, include:

[0016] Identify target users based on the scope of loss;

[0017] Based on the short-circuit time in the short-circuit information, the resource change data of the target user is obtained;

[0018] Based on the resource change data, the damage level value, and the preset weight, the fault value is obtained.

[0019] In one embodiment, the update process for the short-circuit current over-limit threshold includes:

[0020] Based on the fault probability, thermal effect value, fault value, and current, an objective function for the fault outcome is constructed.

[0021] The preset fault result is input into the objective function to obtain the updated short-circuit current over-limit threshold.

[0022] In one embodiment, the process of constructing the preset failure probability model includes:

[0023] Acquire historical fault data, which includes fault causes and fault types;

[0024] A fault probability model is constructed based on the historical fault data. The top event in the fault probability model includes the fault type, and the bottom event includes the fault cause. The top event and the bottom event are connected by logic gates.

[0025] In one embodiment, the process of constructing the network topology model includes:

[0026] Obtain the network structure of the power grid system, wherein the network structure includes nodes and branches;

[0027] Obtain the component parameters of the power grid system;

[0028] Based on the network structure and the component parameters, a network topology model is obtained.

[0029] Secondly, this application also provides a fault detection device for a power grid system, the device comprising:

[0030] An acquisition module is used to acquire short-circuit information of the power grid system, the short-circuit information including short-circuit current;

[0031] The calculation module is used to input the short-circuit current into a preset fault probability model to obtain the fault probability;

[0032] Based on the short-circuit information, the thermal effect value of the short-circuit current is calculated;

[0033] Based on a preset equipment damage assessment threshold, the damage level value corresponding to the thermal effect value is obtained;

[0034] The loss range is obtained based on the network topology model, and the fault value is obtained based on the loss range and the degree of damage.

[0035] The detection module is used to obtain the fault result based on the fault value and the fault probability.

[0036] Thirdly, this disclosure also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of a fault detection method for a power grid system.

[0037] Fourthly, this disclosure also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of a fault detection method for a power grid system.

[0038] Fifthly, this disclosure also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of a fault detection method for a power grid system.

[0039] The aforementioned fault detection methods for power grid systems have at least the following beneficial effects:

[0040] The embodiments provided in this disclosure, through the analysis of historical fault data of power equipment, can accurately calculate the failure probability of equipment under different operating conditions, providing a basis for fault prediction and maintenance of power equipment. Adjusting the short-circuit current over-limit threshold based on the fault results achieves effective control of power system risks, improving the safety and stability of the power system. Based on the assessment results of short-circuit hazards, the system can automatically take targeted countermeasures, promptly disconnecting some loads or adjusting the grid operation mode, effectively reducing the damage of short-circuit current to grid equipment, reducing the scope and duration of power outages, and minimizing economic losses.

[0041] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments or conventional technologies of this disclosure, the accompanying drawings used in the description of the embodiments or conventional technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is an application environment diagram of a fault detection method for a power grid system in one embodiment;

[0044] Figure 2 This is a flowchart illustrating a fault detection method for a power grid system in one embodiment;

[0045] Figure 3 This is a schematic diagram of a power grid system in one embodiment;

[0046] Figure 4 This is a schematic diagram of a power grid system network topology model in one embodiment;

[0047] Figure 5 This is a structural block diagram of a fault detection device for a power grid system in one embodiment;

[0048] Figure 6 This is an internal structural diagram of a computer device in one embodiment;

[0049] Figure 7 This is an internal structure diagram of a server in one embodiment. Detailed Implementation

[0050] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0051] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims. The terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, product, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, product, or apparatus. Without further limitation, the presence of other identical or equivalent elements in a process, method, product, or apparatus that includes said elements is not excluded. For example, the use of terms such as "first," "second," etc., is to denote names and does not indicate any specific order.

[0052] This disclosure provides a fault detection method for a power grid system, which can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0053] In some embodiments of this disclosure, such as Figure 2 As shown, a fault detection method for a power grid system is provided, which can be applied to... Figure 1 The method is illustrated using the server's processing of short-circuit information as an example. It is understood that this method can be applied to a server, and also to a system including both a terminal and a server, and is implemented through interaction between the terminal and the server. In a specific embodiment, the method may include the following steps:

[0054] S202: Obtain short-circuit information of the power grid system, wherein the short-circuit information includes short-circuit current.

[0055] The power grid system includes a data acquisition module, a data processing module, a communication module, a control module, a fault probability calculation module, an equipment damage assessment module, a power outage loss assessment module, a final risk assessment module, and a current threshold adjustment module. Figure 3 This is a schematic diagram of a power grid system in one embodiment.

[0056] The data acquisition module utilizes high-precision current sensors distributed throughout the power grid to collect real-time current data from various nodes and branches. These sensors possess high sensitivity and rapid response characteristics, capable of capturing instantaneous changes in short-circuit current. The acquired current data is then transmitted in real-time to the data processing module via a high-speed communication network. The data processing module receives the current data and first performs preprocessing such as filtering and noise reduction to ensure accuracy and reliability. Then, the data processing module uploads the current data to the system's control module via the communication module. The control module is electrically connected to the data storage module, which stores historical fault data of the equipment, the network structure of the power system, and parameter information of various components within the power system.

[0057] Short-circuit information in a power grid system can include short-circuit current, equipment resistance, and short-circuit duration.

[0058] S204: Input the short-circuit current into a preset fault probability model to obtain the fault probability; calculate the short-circuit current thermal effect value based on the short-circuit information; obtain the damage degree value corresponding to the thermal effect value based on a preset equipment damage degree assessment threshold; obtain the loss range based on the network topology model; and obtain the fault value based on the loss range and the damage degree value.

[0059] thermal effect value ,in This is the short-circuit current. For the device resistance, The short-circuit duration and thermal effect value are used to assess the degree of damage to the equipment, resulting in a damage severity value. .

[0060] Set a preset threshold for assessing the degree of equipment damage. ;

[0061] when hour, =1 indicates that the equipment was basically undamaged;

[0062] when hour, =2 indicates that the equipment has minor damage;

[0063] when hour, =3 indicates that the equipment is moderately damaged;

[0064] when hour, =4 indicates that the equipment is seriously damaged.

[0065] Suppose that for a certain device, =10000J, then in the example above, =20000J, then =2 indicates that the device suffered minor damage during this short circuit fault.

[0066] The equipment damage assessment module sends the calculated equipment damage level value to the power outage loss assessment module. The power outage loss assessment module determines the loss range based on the network topology model, and obtains the fault value, i.e. the severity of the consequences, based on the loss range and the damage level value.

[0067] S206: Based on the fault value and the fault probability, obtain the fault result.

[0068] Failure probability represents the likelihood of equipment failure under current short-circuit current and other conditions. Failure value is a quantitative indicator that combines the degree of equipment damage and the scope of power outage losses, reflecting the severity of the consequences once a failure occurs. ;in Indicates risk tolerance, i.e., the outcome of failure. Indicates the probability of equipment failure. This indicates the severity of the fault's consequences, i.e., the fault value. The fault outcome of a short-circuit fault on the power grid system is calculated by combining the fault probability and the fault value.

[0069] Among the aforementioned fault detection methods for power grid systems, the analysis of historical fault data of power equipment enables accurate calculation of the fault probability of equipment under different operating conditions, providing a basis for fault prediction and maintenance of power equipment. Adjusting the short-circuit current over-limit threshold based on the fault results achieves effective control over power system risks, improving the safety and stability of the power system. Based on the assessment results of short-circuit hazards, the system can automatically take targeted countermeasures, promptly disconnecting some loads or adjusting the grid operation mode, effectively reducing the damage of short-circuit current to grid equipment, reducing the scope and duration of power outages, and minimizing economic losses.

[0070] In some embodiments of this disclosure, the method further includes:

[0071] If the fault result is greater than the preset fault result, the short-circuit current over-limit threshold is updated;

[0072] An alarm message is issued if the short-circuit current exceeds the updated short-circuit current over-limit threshold.

[0073] The system determines whether the risk tolerance is within the system's set threshold, i.e., the relationship between the fault result and the preset fault result. If the fault result is less than the preset fault result, the current threshold adjustment module will not be activated; if the fault result is greater than the preset fault result, the current threshold adjustment module will be activated.

[0074] The current threshold adjustment module calculates the updated short-circuit current over-limit threshold based on its built-in formula, and then sends the updated short-circuit current over-limit threshold to the control module.

[0075] When the control module receives current information, it first determines whether the current is a short-circuit current. If it is, it compares the collected short-circuit current with the pre-set short-circuit current over-limit threshold in the system to determine if the short-circuit current exceeds the limit. If it does, the control module sends an alarm message to the power grid dispatching personnel via the communication module, reminding them to shut down the line to prevent equipment from being damaged by prolonged overcurrent and to avoid further escalation of the accident, such as causing a fire or explosion. Then, the dispatching personnel will arrive on-site to handle the faulty equipment. If the current does not exceed the limit, the control module sends a warning message to the power grid dispatching personnel via the communication module. The dispatching personnel will then strengthen the monitoring of the relevant equipment, including parameters such as current, voltage, and temperature. For example, by installing online monitoring devices, the operating status of the equipment can be monitored in real time, and potential problems can be detected promptly.

[0076] In some embodiments of this disclosure, obtaining the loss range based on the network topology model, and obtaining the fault value based on the loss range and the degree of damage, includes:

[0077] Identify target users based on the scope of loss;

[0078] Based on the short-circuit time in the short-circuit information, the resource change data of the target user is obtained;

[0079] Based on the resource change data, the damage level value, and the preset weight, the fault value is obtained.

[0080] The power outage loss assessment module is used to determine the number of affected users by defining the area based on the network topology model to assess the economic losses from power outages. It can be based on the power outage time Number of affected users Power outage time User's economic losses Calculation, i.e., economic losses from power outages Then, a weighted method is used to... and The severity of the overall consequences is considered. ,For example ,in and As weight. + =1; and Used to measure the relative importance of C1 and C2 in the overall severity of consequences C.

[0081] If the safety of equipment in a power system is paramount, the thermal effects of short-circuit currents can cause serious consequences. It might take a relatively large value, such as 0.6 or 0.7, accordingly. Then take the smaller value. Conversely, if the economic losses caused by a power outage are very significant, such as in areas with a high concentration of high-load, high-output industrial users, a power outage could result in huge economic losses. It might take a large value, such as 0.7 or 0.8, while Then take the smaller value.

[0082] In some embodiments of this disclosure, the updating process of the short-circuit current over-limit threshold includes:

[0083] Based on the fault probability, thermal effect value, fault value, and current, an objective function for the fault outcome is constructed.

[0084] The preset fault result is input into the objective function to obtain the updated short-circuit current over-limit threshold.

[0085] Equipment failure probability With current Existence Relationship (a and b are constants; a determines the baseline level of equipment failure probability under a specific current, while b reflects the degree of influence of current on failure probability); Short-circuit current thermal effect With current The relationship is (c represents the magnitude of the heat effect per unit current, while d reflects the rate at which the heat effect changes with current); economic losses from power outages. With current Functional relationships exist through system power flow calculations, etc. Current Changes in power can cause power outages in different areas. The varying extent and duration of these outages will result in different degrees of economic loss. (Function) This is a quantitative description of this changing relationship. For example, when the short-circuit current is small, it may only cause a small-scale local power outage, affecting a small number of users and resulting in relatively low economic losses. However, when the short-circuit current increases, the power outage area expands, affecting more users, and the economic losses increase significantly. This will accurately reflect this change.

[0086] The objective function of the fault result .make Solve The value of is the current threshold. That is, the short-circuit current exceeding the limit threshold.

[0087] In some embodiments of this disclosure, the process of constructing the preset fault probability model includes:

[0088] Acquire historical fault data, which includes fault causes and fault types;

[0089] A fault probability model is constructed based on the historical fault data. The top event in the fault probability model includes the fault type, and the bottom event includes the fault cause. The top event and the bottom event are connected by logic gates.

[0090] The fault probability calculation module collects historical fault data from the equipment. This historical fault data can include fault type, fault time, maintenance record information, and fault cause. Fault causes include component aging and insulation breakdown due to heavy rain, while fault types include transformer faults and circuit breaker faults. In the fault probability model, the top event represents the fault type and is the target of model analysis. The bottom events represent the fault causes that led to the top event and are the sources of the fault. Based on the causal relationship between fault causes and fault types in the historical fault data, logic gates are used to connect the top and bottom events, forming a fault tree structure. These logic gates include AND gates and OR gates.

[0091] Assuming top event Indicates equipment failure, bottom event This represents the various basic causes of equipment failure, and a fault tree structure function can be built using the relationships between logic gates. ,in It is the state vector of the underlying event. The value can be 0 (the bottom event does not occur) or 1 (the bottom event occurs). Assume the bottom event... The probability of occurrence is Then the top event Failure probability This can be obtained using the probability calculation formula for logic gates. For example, for a logic gate... The probability of failure of a top event connected to a bottom event by an AND gate is: For those by The failure probability of a top event connected to a bottom event via an OR gate is: .

[0092] In some embodiments of this disclosure, the process of constructing the network topology model includes:

[0093] Obtain the network structure of the power grid system, wherein the network structure includes nodes and branches;

[0094] Obtain the component parameters of the power grid system;

[0095] Based on the network structure and the component parameters, a network topology model is obtained.

[0096] Figure 4 This is a schematic diagram of a power grid system network topology model in one embodiment. The equipment damage assessment module is used to obtain the current power system network structure, determine the connection relationships of each node, branch, power source, and load. Node types may include slack nodes, which provide reference voltage and power balance; PV nodes control voltage and active power, with adjustable reactive power; PQ nodes fix active and reactive loads; branch types may include transmission lines and parallel components. The module also obtains the parameters of each component in the current power system, which may include generator reactance, transformer turns ratio and short-circuit impedance, line resistance and reactance, etc. Based on the network topology model and the parameters of each component, a network topology model is constructed, which can intuitively show the connection relationships between devices.

[0097] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0098] Based on the same inventive concept, this disclosure also provides a fault detection device for a power grid system to implement the aforementioned fault detection method for a power grid system. The solution provided by this device is similar to the implementation described in the above method; therefore, the specific limitations in the embodiments of the power grid system fault detection device provided below can be found in the limitations of the power grid system fault detection method described above, and will not be repeated here.

[0099] The apparatus may include a system (including a distributed system), software (application), module, component, server, client, etc., that uses the methods described in the embodiments of this specification, combined with necessary hardware implementation. Based on the same innovative concept, the apparatuses in one or more embodiments provided in this disclosure are as described in the following embodiments. Since the implementation schemes and methods for solving the problem by the apparatus are similar, the implementation of the specific apparatus in the embodiments of this specification can refer to the implementation of the foregoing methods, and repeated details will not be repeated. As used below, the terms "unit" or "module" can refer to a combination of software and / or hardware that implements a predetermined function. Although the apparatuses described in the following embodiments are preferably implemented in software, hardware implementations, or a combination of software and hardware, are also possible and contemplated.

[0100] In one embodiment, such as Figure 5 As shown, a fault detection device 500 for a power grid system is provided. The device can be the aforementioned server, or a module, component, device, or unit integrated into the server. The device 500 may include:

[0101] The acquisition module 502 is used to acquire short-circuit information of the power grid system, wherein the short-circuit information includes short-circuit current;

[0102] Calculation module 504 is used to input the short-circuit current into a preset fault probability model to obtain the fault probability;

[0103] Based on the short-circuit information, the thermal effect value of the short-circuit current is calculated;

[0104] Based on a preset equipment damage assessment threshold, the damage level value corresponding to the thermal effect value is obtained;

[0105] The loss range is obtained based on the network topology model, and the fault value is obtained based on the loss range and the degree of damage.

[0106] The detection module 506 is used to obtain the fault result based on the fault value and the fault probability.

[0107] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0108] The modules in the aforementioned fault detection device for power grid systems can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware form or independent of it, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0109] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 6 As shown, the computer device includes a processor, memory, and a network interface connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database stores short-circuit information. The network interface communicates with external terminals via a network connection. When executed by the processor, the computer program implements a fault detection method for a power grid system.

[0110] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a fault detection method for the power grid system. The display screen can be an LCD screen or an e-ink display screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0111] Those skilled in the art will understand that Figure 6 , Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the computer device to which the present disclosure is applied. A specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0112] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the methods described in any embodiment of this disclosure.

[0113] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the methods described in any embodiment of this disclosure.

[0114] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this disclosure can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this disclosure may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this disclosure may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0115] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The embodiments described above are merely illustrative of several implementations of this disclosure, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent disclosure. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this disclosure, and these all fall within the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be determined by the appended claims.

Claims

1. A fault detection method for a power grid system, characterized in that, The method includes: Obtain short-circuit information of the power grid system, wherein the short-circuit information includes short-circuit current; The short-circuit current is input into a preset fault probability model to obtain the fault probability; Based on the short-circuit information, the thermal effect value of the short-circuit current is calculated; Based on a preset equipment damage assessment threshold, the damage level value corresponding to the thermal effect value is obtained; The loss range is obtained based on the network topology model, and the fault value is obtained based on the loss range and the degree of damage. Based on the fault value and the fault probability, the fault result is obtained.

2. The method according to claim 1, characterized in that, The method further includes: If the fault result is greater than the preset fault result, the short-circuit current over-limit threshold is updated; An alarm message is issued if the short-circuit current exceeds the updated short-circuit current over-limit threshold.

3. The method according to claim 1, characterized in that, The loss range obtained based on the network topology model, and the fault value obtained based on the loss range and the degree of damage, include: Identify target users based on the scope of loss; Based on the short-circuit time in the short-circuit information, the resource change data of the target user is obtained; Based on the resource change data, the damage level value, and the preset weight, the fault value is obtained.

4. The method according to claim 2, characterized in that, The update process for the short-circuit current over-limit threshold includes: Based on the fault probability, thermal effect value, fault value, and current, an objective function for the fault outcome is constructed. The preset fault result is input into the objective function to obtain the updated short-circuit current over-limit threshold.

5. The method according to claim 1, characterized in that, The process of constructing the preset failure probability model includes: Acquire historical fault data, which includes fault causes and fault types; A fault probability model is constructed based on the historical fault data. The top event in the fault probability model includes the fault type, and the bottom event includes the fault cause. The top event and the bottom event are connected by logic gates.

6. The method according to claim 1, characterized in that, The process of constructing the network topology model includes: Obtain the network structure of the power grid system, wherein the network structure includes nodes and branches; Obtain the component parameters of the power grid system; Based on the network structure and the component parameters, a network topology model is obtained.

7. A fault detection device for a power grid system, characterized in that, The device includes: An acquisition module is used to acquire short-circuit information of the power grid system, the short-circuit information including short-circuit current; The calculation module is used to input the short-circuit current into a preset fault probability model to obtain the fault probability; Based on the short-circuit information, the thermal effect value of the short-circuit current is calculated; Based on a preset equipment damage assessment threshold, the damage level value corresponding to the thermal effect value is obtained; The loss range is obtained based on the network topology model, and the fault value is obtained based on the loss range and the degree of damage. The detection module is used to obtain the fault result based on the fault value and the fault probability.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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