Power distribution network section fault locating method and system under incomplete alarm information

Abstract

The application belongs to the field of power system grid protection, and provides a distribution network section fault positioning method and system under the condition of incomplete alarm information, which comprises the following steps: establishing a grid element connection tree by using the grid topology structure of a distribution management system, and determining key nodes of the grid; comprehensively analyzing a distribution automation system, a use system, a marketing management system and a weather forecast system according to the importance of fault alarm information, and determining the priority of the comprehensive judgment of multiple systems; sorting the fault possibility of the key nodes of the grid based on the real-time obtained alarm information according to the priority of the comprehensive judgment of multiple systems; and based on the sorting result of the fault possibility of the key nodes of the grid, the key nodes of the grid are repaired one by one to determine the position of the section fault of the distribution network. The application is based on the grid topology after the fault of the distribution network, and fully considers various certain and uncertain information to position the section fault of the distribution network.

Description

Technical Field

[0001] This invention belongs to the field of power grid protection technology, specifically relating to a method and system for locating faults in distribution network sections when alarm information is incomplete. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] The distribution network directly faces users, and its power supply quality directly impacts user feedback. Statistics show that over 80% of power system faults originate in the distribution network. Distribution network faults are numerous and difficult to locate; therefore, distribution network fault analysis has always been a crucial power grid operation measure, ensuring socio-economic development and improving people's quality of life. Distribution network segment location not only allows staff to gain a rough understanding of the fault's impact but also, based on the identified outage area, allows for further determination of the switch status for final fault isolation and verification of the fault location accuracy. Therefore, timely fault segment location after a distribution network fault improves staff's understanding of the fault and increases work efficiency, thereby improving the accuracy of various operations during fault handling and significantly shortening fault handling time, ultimately enhancing the overall reliability of the distribution network's power supply.

[0004] Because the power distribution network directly faces users, it often causes large-scale power outages and loss of fault information when disasters such as earthquakes and floods occur.

[0005] by Figure 1 The following example illustrates the fault location principle of current power distribution automation. When a fault occurs, the recloser, acting as a power switch, controls the circuit breaker CB1 to trip. Subsequently, the sectionalizing switches S1 and S2 along the line open due to voltage loss. After a delay, the recloser recloses for the first time, and the circuit breaker CB1 closes. The voltage-time type sectionalizing switch, acting as a sectionalizing switch, automatically closes after being energized on one side. When it closes to the fault point, it causes a second trip of the recloser and sectionalizing switches. Because the sectionalizing switch connected to the faulty section does not maintain its closed position for the set time limit, it is locked in the open state. At the same time, the downstream sectionalizing switch connected to the faulty section is also locked in the open state based on the residual voltage blocking mechanism. After a delay, the recloser recloses for the second time, restoring power supply to the entire section of the faulty line. Afterward, the tie switch closes to restore power supply to the non-faulty sections.

[0006] As described above, in the current fault location principle of power distribution automation, if the FTU equipment for detecting voltage is unable to locate the faulty section due to natural disasters such as earthquakes and hurricanes, the communication terminal will be unable to do so. Summary of the Invention

[0007] To address the aforementioned issues, this invention proposes a method and system for locating faults in distribution network sections when alarm information is incomplete. Based on the power grid topology after a distribution network fault, this invention fully considers various deterministic and uncertain information to locate faults in distribution network sections.

[0008] According to some embodiments, the first solution of the present invention provides a method for locating faults in a distribution network section when alarm information is incomplete, and adopts the following technical solution:

[0009] Methods for locating faults in distribution network sections when alarm information is incomplete include:

[0010] By utilizing the power grid topology of the power distribution management system, a connection tree of power grid components is established to identify key nodes in the power grid.

[0011] Based on the importance of the fault alarm information, a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecast system is conducted to determine the priority of the multi-system comprehensive judgment.

[0012] Based on the comprehensive judgment priority of multiple systems, the probability of failure of key nodes in the power grid is ranked according to the alarm information acquired in real time.

[0013] Based on the fault probability ranking results of key power grid nodes, key power grid nodes are inspected one by one to determine the location of faults in distribution network sections.

[0014] Furthermore, the establishment of a power grid component connection tree using the power grid topology of the power distribution management system includes:

[0015] Based on the power grid topology, a breadth-first traversal is performed along the lines, with the substation busbar as the root.

[0016] When encountering a power grid branch, create the corresponding tree branch;

[0017] The traversal continues until a tie switch is found, completing the traversal of the power grid topology and obtaining the power grid component connection tree.

[0018] Furthermore, based on the importance of the fault alarm information, a comprehensive analysis is conducted on the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecasting system to determine the priority of the multi-system comprehensive judgment, specifically as follows:

[0019] Based on the importance of the fault alarm information, the power distribution automation system M3, the data acquisition system M2, the marketing management system M1, and the weather forecast system M5 are ranked in order of importance as follows: M3>M2>M1>M5.

[0020] Based on the importance ranking results of the power distribution automation system M3, the data acquisition system M2, the marketing management system M1, and the weather forecast system M5, the priority of the multi-system comprehensive judgment is determined.

[0021] Furthermore, the priority is determined by a comprehensive multi-system approach, specifically as follows:

[0022] Priority 1: When four systems alarm simultaneously, it is determined to be priority 1; priority 1 specifically includes M1, M2, M3, and M5;

[0023] Priority 2: When any three of the four systems alarm simultaneously, it is determined to be priority 2; specifically, priority 2 includes M2, M3, M5 > M1, M2, M3 > M1, M3, M5 > M1, M2, M5;

[0024] Priority 3: When any two of the four systems alarm simultaneously, it is determined to be priority 3; the priority 3 specifically includes M2, M3>M3, M5>M2, M5>M1, M3>M1, M2>M1, and M5;

[0025] Priority 4: When any one of the four systems alarms, it is determined to be priority 4. Priority 4 specifically includes M3>M2>M1>M5.

[0026] Furthermore, the method of prioritizing key power grid nodes based on multi-system integrated judgment and ranking the probability of failure according to real-time acquired alarm information is as follows:

[0027] Real-time acquisition of alarm information from the power grid marketing management system, electricity consumption data acquisition system, and power distribution automation system;

[0028] The probability of failure at key power grid nodes is ranked by comparing the alarm information from the real-time power grid marketing management system, electricity consumption data acquisition system, and distribution automation system with the overall priority judgment of multiple systems.

[0029] The results of ranking the failure probabilities of key nodes in the power grid were determined.

[0030] Furthermore, the method also includes:

[0031] When the power system control center experiences information flow problems, it acquires alarm information from the marketing management system, the user acquisition system, and the distribution automation system.

[0032] The probability of a fault occurring in each section is determined using a Markov model of the power distribution network.

[0033] When the probability of a line fault exceeds the threshold, the alarm message is deemed correct, and fault inspection is performed based on the alarm message.

[0034] If the probability of a line fault occurring is less than the threshold, the alarm message is considered incorrect.

[0035] Furthermore, the probability of a fault occurring in a section is determined using a Markov model of the distribution network, specifically:

[0036] Using the power grid marketing management system, electricity consumption data acquisition system and distribution automation system as Markov chains in the Markov model, respectively, we perform probabilistic modeling of distribution network line faults to form a distribution network Markov model.

[0037] Using a Markov model of the distribution network to determine the probability of a fault occurring in a section;

[0038] Specifically, determining the probability of a fault occurring in a section using a Markov model of the distribution network involves:

[0039] The probability of a section failure is P = u1u2u3 / (u1u2u3 + v1u2u3 + u1v2u3 + u1u2v3);

[0040] Where u1 represents the percentage of user complaints received after a section fault out of the total number of faults, v1 represents the percentage of no user complaints received after a section fault out of the total number of faults; u2 represents the percentage of user electricity consumption collected as zero after a section fault out of the total number of user electricity consumption collections, v2 represents the percentage of user electricity consumption collection failures after a section fault out of the total number of user electricity consumption collections; u3 represents the percentage of sectionalizing switch tripping out of the total number of sectionalizing switch actions after a section fault, v3 represents the percentage of sectionalizing switch closing out of the total number of sectionalizing switch actions after a section fault.

[0041] According to some embodiments, the second aspect of the present invention provides a fault location system for a distribution network section when alarm information is incomplete, employing the following technical solution:

[0042] A fault location system for distribution network sections when alarm information is incomplete, including:

[0043] The power grid critical node identification module is configured to use the power grid topology of the distribution management system to establish a power grid component connection tree and identify the power grid critical nodes.

[0044] The multi-system integrated judgment priority determination module is configured to perform a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecasting system based on the importance of the fault alarm information, and determine the multi-system integrated judgment priority.

[0045] The fault probability ranking module is configured to rank the fault probabilities of key power grid nodes based on multi-system comprehensive judgment priority and real-time alarm information.

[0046] The section fault location module is configured to inspect each key node of the power grid one by one based on the fault probability ranking results of the key nodes of the power grid, and determine the location of the fault in the distribution network section.

[0047] According to some embodiments, a third aspect of the present invention provides a computer-readable storage medium.

[0048] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for locating faults in a power distribution network section when alarm information is incomplete, as described in the first aspect above.

[0049] According to some embodiments, a fourth aspect of the present invention provides a computer device.

[0050] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the method for locating faults in a power distribution network section when alarm information is incomplete, as described in the first aspect above.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0052] Currently, fault location in distribution networks relies on confirmed fault information. However, in extreme situations, such as hurricanes or earthquakes, fault alarm information may be incomplete. In such cases, this invention utilizes information from various systems, including marketing management systems, data acquisition systems, distribution automation systems, distribution management systems, and weather forecasting systems, to comprehensively assess distribution lines. When communication failures occur in the power grid system, incomplete alarm information prevents perfectly accurate diagnostic results. Therefore, this invention calculates the probability of faults in potentially faulty distribution lines and prioritizes inspections based on fault probability, prioritizing lines with higher probability of faulting. This ensures that faulty lines are located optimally, avoiding blind manual inspections, shortening power outage time, and ultimately improving power supply reliability.

[0053] This invention integrates the current supporting marketing management system, user acquisition system, distribution automation system, distribution management system, and weather forecasting system to locate the fault in the distribution network when FTU information is missing. Based on the power grid topology after the distribution network fault, it fully considers various deterministic and uncertain information to locate the fault in the distribution network. Attached Figure Description

[0054] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0055] Figure 1 This is a diagram of the power grid topology used in the current fault location principle of power distribution automation.

[0056] Figure 2 yes Figure 1 A schematic diagram of the component connection tree generated by the power grid topology;

[0057] Figure 3 This is a schematic diagram of the Markov model described in an embodiment of the present invention;

[0058] Figure 4 This is a flowchart of the method for locating faults in a power distribution network section when alarm information is incomplete, as described in an embodiment of the present invention. Detailed Implementation

[0059] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0060] It should be noted that the following detailed description is illustrative and intended to provide further explanation of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0061] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0062] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0063] Example 1

[0064] like Figure 4As shown, this embodiment provides a method for fault location in a power distribution network section when alarm information is incomplete. This embodiment uses the application of this method to a server as an example for illustration. It can be understood that this method can also be applied to a terminal, or to a system including a terminal, a server, and a system, and can be implemented through the interaction between the terminal and the server. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network servers, cloud communication, middleware services, domain name services, CDN security services, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and the server can be directly or indirectly connected through wired or wireless communication, which is not limited in this application. In this embodiment, the method includes the following steps:

[0065] By utilizing the power grid topology of the power distribution management system, a connection tree of power grid components is established to identify key nodes in the power grid.

[0066] Based on the importance of the fault alarm information, a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecast system is conducted to determine the priority of the multi-system comprehensive judgment.

[0067] Based on the comprehensive judgment priority of multiple systems, the probability of failure of key nodes in the power grid is ranked according to the alarm information acquired in real time.

[0068] Based on the fault probability ranking results of key power grid nodes, key power grid nodes are inspected one by one to determine the location of faults in distribution network sections.

[0069] This embodiment integrates the current supporting marketing management system, user acquisition system, distribution automation system, distribution management system, and weather forecasting system to locate the fault section in the distribution network when FTU information is missing.

[0070] Among them, the Marketing Management System M1 uses the 95598 telephone hotline to provide customers with feedback on power outage areas; the Data Collection System M2 uses user meters to collect user electricity consumption information; the Distribution Automation System M3 uses FTU to collect the status of each switch; the Distribution Management System M4 uses the distribution topology to provide component connection relationships; and the Weather Forecast System M5 provides local weather conditions.

[0071] by Figure 1 Taking the illustrated line as an example, this embodiment provides a detailed explanation of a method for locating faults in a distribution network section when alarm information is incomplete, including:

[0072] Step 1: Establish the power grid component connection tree.

[0073] Using the power grid topology of the power distribution management system, a connection tree for power grid components is established, including:

[0074] Based on the power grid topology, a breadth-first traversal is performed along the lines, with the substation busbar as the root.

[0075] When encountering a power grid branch, create the corresponding tree branch;

[0076] The traversal continues until a tie switch is found, completing the traversal of the power grid topology and obtaining the power grid component connection tree.

[0077] by Figure 1 Taking the illustrated line as an example, a component connection tree is established based on the topology provided by the power distribution management system M4. This invention is based on the premise that the power distribution network topology will not change under extreme weather conditions such as earthquakes and hurricanes, and is a deterministic factor. The establishment method is to use the substation bus as the root of the tree, perform a breadth-first traversal along the line, and establish the corresponding tree branch when a power grid branch is encountered, until the tie switch is found.

[0078] For example, Figure 1 The corresponding power grid component connection tree is as follows: Figure 2 As shown. The problem is transformed into determining which of the critical nodes L1, L2, and L3 experienced a segment fault given the system information M1, M2, M3, M4, and M5.

[0079] Step 2: Based on the importance of the fault alarm information, conduct a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecast system to determine the priority of the multi-system comprehensive judgment;

[0080] Within this system, items of the same priority are prioritized from left to right. Since the M4 distribution management system only provides topology information, which is stored permanently in the dispatch center, it is not included in the priority ranking.

[0081] The importance of all information provided by the alarm system was ranked as follows: The information provided by the distribution automation system M3 is the most important because it provides the opening and closing information of circuit breakers and switches at both ends of the line, which is directly related to the line. Next is the user acquisition system M2, which indicates the indirect relationship between user electricity consumption and the line; therefore, this system is placed in a secondary position. Next is the marketing management system M1 because user complaint calls are too uncertain, and users themselves cannot distinguish whether the power outage is caused by a line problem or their own home. Finally, the weather forecast system M5 is considered, because weather is only one factor contributing to line failures.

[0082] Specifically, based on the importance of the fault alarm information, the power distribution automation system M3, the data acquisition system M2, the marketing management system M1, and the weather forecast system M5 are ranked in order of importance as follows: M3>M2>M1>M5.

[0083] Therefore, the priority of multi-system comprehensive judgment is obtained as follows:

[0084] Priority 1: When four systems alarm simultaneously, it is determined to be priority 1; priority 1 specifically includes M1, M2, M3, and M5;

[0085] Priority 2: When any three of the four systems alarm simultaneously, it is determined to be priority 2; specifically, priority 2 includes M2, M3, M5 > M1, M2, M3 > M1, M3, M5 > M1, M2, M5;

[0086] Priority 3: When any two of the four systems alarm simultaneously, it is determined to be priority 3; the priority 3 specifically includes M2, M3>M3, M5>M2, M5>M1, M3>M1, M2>M1, and M5;

[0087] Priority 4: When any one of the four systems alarms, it is determined to be priority 4. Priority 4 specifically includes M3>M2>M1>M5.

[0088] Step 3: Based on a comprehensive multi-system assessment of priorities, the probability of failure at key power grid nodes is ranked according to the real-time alarm information acquired. Specifically:

[0089] Real-time acquisition of alarm information from the power grid marketing management system, electricity consumption data acquisition system, and power distribution automation system;

[0090] The probability of failure at key power grid nodes is ranked by comparing the alarm information from the real-time power grid marketing management system, electricity consumption data acquisition system, and distribution automation system with the overall priority judgment of multiple systems.

[0091] The results of ranking the failure probabilities of key nodes in the power grid were determined.

[0092] Based on the alarm information received by key nodes L1, L2, and L3, the probability of the fault is ranked. For example, if L2 receives information from the distribution automation system M3 indicating that both sectionalizing switches have tripped, from the user meter reading M2 indicating that the user's electricity meter is at zero, from the marketing management system M1 indicating a user alarm, and from the weather forecast system M5 indicating missing information, then L2 meets priority 2. Simultaneously, if L3 receives an alarm from the marketing management system M1 indicating that user 95598 has tripped, then L3 meets priority 4. Since priority 2 is higher than priority 4, personnel are first dispatched to inspect the L2 section of the line.

[0093] Step 4: Based on the fault probability ranking results of key power grid nodes, inspect each key power grid node one by one to determine the location of faults in the distribution network section.

[0094] Specifically, the method described in this embodiment further includes:

[0095] When the power system control center experiences information flow problems, it acquires alarm information from the marketing management system, the user acquisition system, and the distribution automation system.

[0096] The probability of a fault occurring in each section is determined using a Markov model of the distribution network.

[0097] When the probability of a line fault exceeds the threshold, the alarm message is deemed correct, and fault inspection is performed based on the alarm message.

[0098] If the probability of a line fault occurring is less than the threshold, the alarm message is considered incorrect.

[0099] Conflict resolution methods. Under extreme weather conditions, power systems frequently experience information gaps, leading to conflicts. For example, some lines may trip, but the trip signal may not be transmitted, causing the control center to mistakenly believe the lines are intact. However, the marketing management system may receive user complaints about power outages, resulting in an information conflict.

[0100] To resolve this type of conflict, this invention utilizes a Markov model to probabilistically model line faults. Figure 3 In the Markov model of the line shown, u1 represents the percentage of user complaints received after a section fault, out of the total number of faults; v1 represents the percentage of no user complaints received after a section fault; u2 represents the percentage of zero user electricity consumption collected after a section fault, out of the total number of user electricity consumption collections; v2 represents the percentage of failed user electricity consumption collections after a section fault; u3 represents the percentage of sectionalizing switch tripping after a section fault, out of the total number of sectionalizing switch actions; v3 represents the percentage of sectionalizing switch closing after a section fault, out of the total number of sectionalizing switch actions. Since weather conditions are not directly related to line faults and are only used as an auxiliary criterion, M5 is not included in the Markov model.

[0101] The probability of a fault occurring in a section is determined using a Markov model of the distribution network, specifically as follows:

[0102] Using the power grid marketing management system, electricity consumption data acquisition system and distribution automation system as Markov chains in the Markov model, respectively, we perform probabilistic modeling of distribution network line faults to form a distribution network Markov model.

[0103] Using a Markov model of the distribution network to determine the probability of a fault occurring in a section;

[0104] Specifically, determining the probability of a fault occurring in a section using a Markov model of the distribution network involves:

[0105] The probability of a section failure is P = u1u2u3 / (u1u2u3 + v1u2u3 + u1v2u3 + u1u2v3);

[0106] Where u1 represents the percentage of user complaints received after a section fault out of the total number of faults, v1 represents the percentage of no user complaints received after a section fault out of the total number of faults; u2 represents the percentage of user electricity consumption collected as zero after a section fault out of the total number of user electricity consumption collections, v2 represents the percentage of user electricity consumption collection failures after a section fault out of the total number of user electricity consumption collections; u3 represents the percentage of sectionalizing switch tripping out of the total number of sectionalizing switch actions after a section fault, v3 represents the percentage of sectionalizing switch closing out of the total number of sectionalizing switch actions after a section fault.

[0107] When a section fault occurs on the Markov chain where the power grid marketing management system is located, a probability judgment is made based on whether user complaints have been received; when a section fault occurs on the Markov chain where the electricity consumption data collection system is located, a probability judgment is made based on whether user electricity consumption has been collected; when a section fault occurs on the Markov chain where the distribution automation system is located, a probability judgment is made based on the opening and closing status of the sectionalizing switch.

[0108] Solving the Markov model, the segment failure probability is P = u1u2u3 / (u1u2u3+v1u2u3+u1v2u3+u1u2v3).

[0109] Based on maintenance data statistics, we take u1 = 0.832, v1 = 0.168, u2 = 0.976, v2 = 0.024, u3 = 0.989, v3 = 0.011. The fault threshold is set at 70%. If M1, M2, and M3 all correctly reflect the fault, according to the formula, the fault probability P for this section is 80.8%, indicating a fault on this line. Personnel should be dispatched to locate the fault along this line.

[0110] For example, if a fault occurs in L2, the sectionalizing switches S1 and S2 at both ends trip. However, due to communication problems, the dispatch center still shows S1 and S2 as closed. That is, the distribution automation system M3 does not trigger an alarm. Simultaneously, L2 receives a complaint call from the marketing management system M1 via the 95598 hotline, which retrieves data from the user meter reading M2, showing zero electricity consumption. Using a Markov model,

[0111] The probability of accepting M1 and M2 is

[0112] P1=u1u2v3 / (u1u2u3+v1u2u3+u1v2u3+u1u2v3)=0.899%;

[0113] The probability of accepting M3 is

[0114] P2=v1v2u3 / (u1u2u3+v1u2u3+u1v2u3+u1u2v3)=0.4%

[0115] P1>P2 indicates that the M3 information in the power distribution automation system is incorrect.

[0116] In case of conflict: According to the Markov model, the probability of each possibility is calculated. The one with the higher probability is accepted and fault inspection is carried out based on the alarm information; otherwise, the one with the lower probability is considered to be an information error.

[0117] Example 2

[0118] This embodiment provides a fault location system for a distribution network section when alarm information is incomplete, including:

[0119] The power grid critical node identification module is configured to use the power grid topology of the distribution management system to establish a power grid component connection tree and identify the power grid critical nodes.

[0120] The multi-system integrated judgment priority determination module is configured to perform a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecasting system based on the importance of the fault alarm information, and determine the multi-system integrated judgment priority.

[0121] The fault probability ranking module is configured to rank the fault probabilities of key power grid nodes based on multi-system comprehensive judgment priority and real-time alarm information.

[0122] The section fault location module is configured to inspect each key node of the power grid one by one based on the fault probability ranking results of the key nodes of the power grid, and determine the location of the fault in the distribution network section.

[0123] The examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in Embodiment 1 above. It should be noted that the above modules, as part of the system, can be executed in a computer system such as a set of computer-executable instructions.

[0124] The descriptions of each embodiment in the above embodiments have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0125] The proposed system can be implemented in other ways. For example, the system embodiments described above are merely illustrative, and the division of modules described above is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed.

[0126] Example 3

[0127] This embodiment provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the method for locating faults in a power distribution network section when alarm information is incomplete, as described in Embodiment 1 above.

[0128] Example 4

[0129] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the steps in the method for locating faults in a power distribution network section when alarm information is incomplete, as described in Embodiment 1 above.

[0130] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0131] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0132] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0133] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0134] 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 program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0135] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for locating faults in a distribution network section when alarm information is incomplete, characterized in that, include: By utilizing the power grid topology of the power distribution management system, a connection tree of power grid components is established to identify key nodes in the power grid. Based on the importance of the fault alarm information, a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecast system is conducted to determine the priority of the multi-system comprehensive judgment. Based on the comprehensive judgment priority of multiple systems, the probability of failure of key nodes in the power grid is ranked according to the alarm information acquired in real time. Based on the fault probability ranking results of key power grid nodes, key power grid nodes are inspected one by one to determine the location of faults in distribution network sections. When the power system control center experiences information flow problems, it acquires alarm information from the marketing management system, the user acquisition system, and the distribution automation system. The probability of a fault occurring in each section is determined using a Markov model of the distribution network, specifically as follows: Using the power grid marketing management system, electricity consumption data acquisition system and distribution automation system as Markov chains in the Markov model, respectively, we perform probabilistic modeling of distribution network line faults to form a distribution network Markov model. Using a Markov model of the distribution network to determine the probability of a fault occurring in a section; Specifically, determining the probability of a fault occurring in a section using a Markov model of the distribution network involves: The section failure probability is P = u1u2u3 / ( u1u2u3 + v1u2u3 + u1v2u3 + u1u2v3); Where u1 represents the percentage of user complaints received after a section fault, out of the total number of faults; v1 represents the percentage of no user complaints received after a section fault; u2 represents the percentage of zero user electricity consumption collected after a section fault, out of the total number of user electricity consumption data collected; v2 represents the percentage of failed user electricity consumption data collection after a section fault; u3 represents the percentage of sectionalizing switch tripping after a section fault, out of the total number of sectionalizing switch actions; v3 represents the percentage of sectionalizing switch closing after a section fault, out of the total number of sectionalizing switch actions. When the probability of a line fault exceeds the threshold, the alarm message is deemed correct, and fault inspection is performed based on the alarm message. If the probability of a line fault occurring is less than the threshold, the alarm message is considered incorrect.

2. The method for locating faults in a distribution network section when alarm information is incomplete, as described in claim 1, is characterized in that... The process of establishing a power grid component connection tree using the power grid topology of the power distribution management system includes: Based on the power grid topology, a breadth-first traversal is performed along the lines, with the substation busbar as the root. When encountering a power grid branch, create the corresponding tree branch; The traversal continues until a tie switch is found, completing the traversal of the power grid topology and obtaining the power grid component connection tree.

3. The method for locating faults in a distribution network section when alarm information is incomplete, as described in claim 1, is characterized in that... Based on the importance of fault alarm information, a comprehensive analysis is conducted on the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecasting system to determine the priority of multi-system comprehensive judgment. Specifically: Based on the importance of the fault alarm information, the power distribution automation system M3, the data acquisition system M2, the marketing management system M1, and the weather forecast system M5 are ranked in order of importance as follows: M3>M2>M1>M5. Based on the importance ranking results of the power distribution automation system M3, the data acquisition system M2, the marketing management system M1, and the weather forecast system M5, the priority of the multi-system comprehensive judgment is determined.

4. The method for locating faults in a distribution network section when alarm information is incomplete, as described in claim 3, is characterized in that... The priority is determined by a comprehensive assessment of multiple systems, specifically as follows: Priority 1: When four systems alarm simultaneously, it is determined to be priority 1; priority 1 specifically includes M1, M2, M3, and M5; Priority 2: When any three of the four systems alarm simultaneously, it is determined to be priority 2; specifically, priority 2 includes M2, M3, M5 > M1, M2, M3 > M1, M3, M5 > M1, M2, M5; Priority 3: When any two of the four systems alarm simultaneously, it is determined to be priority 3; the priority 3 specifically includes M2, M3>M3, M5>M2, M5>M1, M3>M1, M2>M1, and M5; Priority 4: When any one of the four systems alarms, it is determined to be priority 4. Priority 4 specifically includes M3>M2>M1>M5.

5. The method for locating faults in a distribution network section when alarm information is incomplete, as described in claim 1, is characterized in that... The method of prioritizing key power grid nodes based on multi-system integrated judgment and ranking the probability of failure according to real-time alarm information is as follows: Real-time acquisition of alarm information from the power grid marketing management system, electricity consumption data acquisition system, and power distribution automation system; The probability of failure at key power grid nodes is ranked by comparing the alarm information from the real-time power grid marketing management system, electricity consumption data acquisition system, and distribution automation system with the overall priority judgment of multiple systems. The results of ranking the failure probabilities of key nodes in the power grid were determined.

6. A distribution network section fault location system for incomplete alarm information using the method for fault location in distribution network sections as described in any one of claims 1-5, characterized in that, include: The power grid critical node identification module is configured to use the power grid topology of the distribution management system to establish a power grid component connection tree and identify the power grid critical nodes. The multi-system integrated judgment priority determination module is configured to perform a comprehensive analysis of the power distribution automation system, the data acquisition system, the marketing management system, and the weather forecasting system based on the importance of the fault alarm information, and determine the multi-system integrated judgment priority. The fault probability ranking module is configured to rank the fault probabilities of key power grid nodes based on multi-system comprehensive judgment priority and real-time alarm information. The section fault location module is configured to inspect each key node of the power grid one by one based on the fault probability ranking results of the key nodes of the power grid, and determine the location of the fault in the distribution network section.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps in the method for locating faults in a distribution network section when the alarm information is incomplete as described in any one of claims 1-5.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps in the method for locating faults in a power distribution network section when the alarm information is incomplete, as described in any one of claims 1-5.

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