A method and system for automatically analyzing the self-healing rate of distribution network feeder faults

Abstract

The present invention discloses a method and system for automatically analyzing the self-healing rate of a distribution network feeder fault, which relates to the technical field of distribution network analysis, and obtains real-time data and historical data of each feeder in an adjustment set, constructs a judgment matrix for the feeder, and after sorting and analyzing the feeders according to the judgment matrix, prioritizes all feeders in the adjustment set, and generates a resource allocation strategy for the feeder according to the sorting result. In the process of self-healing of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders are self-healed, a self-healing index is generated for the feeder in combination with the self-healing rate of the feeder at multiple time points. After comprehensively analyzing the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. The analysis system sorts by priority, and the scheme ensures that high-priority feeders obtain more resource support, reasonably allocates limited resources, and has high adaptability and can flexibly cope with complex scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network analysis, and in particular to a method and system for automatically analyzing the self-healing rate of a distribution network feeder fault. Background Art

[0002] Due to load growth, fluctuations in electricity demand and uneven load distribution, distribution network feeders are prone to overload. Overload will not only increase line losses and shorten equipment life, but may also cause more serious faults such as tripping. Feeder power outages caused by equipment failure, line abnormalities, external force damage or natural disasters will have a major impact on users' electricity consumption, especially in sensitive load areas (such as hospitals and industrial parks), causing significant losses. Through intelligent algorithms and automated equipment, the distribution network can automatically adjust its operating mode, such as load transfer, topology reconstruction, etc., to achieve rapid self-healing when overload or power outage occurs.

[0003] The prior art has the following defects:

[0004] 1. In existing technologies, resource allocation (such as power grid control capability, etc.) mostly adopts fixed or empirical rules, which are difficult to adjust dynamically. Resource allocation is often guided by a single indicator (such as the number of users), ignoring the comprehensive consideration of load characteristics, regional importance and historical fault records, reducing the overall recovery efficiency of the distribution network;

[0005] 2. In multi-feeder fault scenarios, existing technologies lack the ability to conduct unified analysis of all faulty feeders, and rely more on line-by-line processing or zone scheduling, failing to establish an overall optimization perspective. Line-by-line processing may delay the repair of key lines, and zone scheduling may lead to uneven recovery progress in various regions, affecting user satisfaction and grid stability.

[0006] Based on this, the present invention proposes a method and system for automatically analyzing the self-healing rate of distribution network feeder faults. Through priority sorting, the scheme ensures that high-priority feeders obtain more resource support, reasonably allocates limited resources, and has high adaptability and can flexibly respond to complex scenarios. Summary of the invention

[0007] The object of the present invention is to provide a method and system for automatically analyzing the self-healing rate of a distribution network feeder fault, so as to solve the deficiencies in the background technology.

[0008] In order to achieve the above object, the present invention provides the following technical solution: a method for automatically analyzing the self-healing rate of a distribution network feeder fault, the analysis method comprising the following steps:

[0009] After receiving the regional information of the distribution network failure, the analysis system obtains the information of the feeders involved in the failure in the region, establishes an adjustment set for all the feeders involved in the failure, obtains the real-time data and historical data of each feeder in the adjustment set, and builds a judgment matrix for the feeders based on the real-time data and historical data;

[0010] After sorting and analyzing the feeders according to the judgment matrix, all feeders in the adjustment set are prioritized, and a resource allocation strategy for the feeders is generated based on the sorting results;

[0011] During the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders have completed self-healing, a self-healing index is generated for the feeder based on the self-healing rates of the feeders at multiple time points. After a comprehensive analysis of the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. A management strategy is generated based on the determination result and sent to the administrator.

[0012] In a preferred embodiment, obtaining real-time data and historical data of each feeder in the adjustment set, and constructing a judgment matrix for the feeder based on the real-time data and historical data, includes the following steps:

[0013] Real-time data includes load data, equipment status, fault information, and self-healing process;

[0014] Historical data includes load history, equipment failure records, recovery history, maintenance and inspection records;

[0015] The evaluation dimensions are obtained based on real-time data and historical data. The evaluation dimensions include load conditions, equipment health status, importance level, historical failure times, and load type. A judgment matrix is ​​constructed after generating weights for each evaluation dimension.

[0016] In a preferred embodiment, all feeders in the adjustment set are prioritized, including the following steps:

[0017] All evaluation dimensions in the judgment matrix are weighted to obtain the priority index of the feeder, which is expressed as: , where is the priority index, is the number of evaluation dimensions of the feeder, For the The weight of the evaluation dimension, For the Evaluation dimension values;

[0018] After obtaining the priority indexes of all feeders, all feeders in the adjustment set are sorted from large to small according to the priority index, and the resource allocation strategy of the feeders is generated according to the positive order of the adjustment set.

[0019] In a preferred embodiment, the evaluation dimensions include load fluctuation amplitude, fault impact index and instantaneous overcurrent index;

[0020] The calculation logic of the load fluctuation amplitude is as follows: obtain the load values ​​of the feeder at multiple time points within the monitoring period, calculate the load standard deviation based on the load values ​​at multiple time points, and use the load standard deviation as the load fluctuation amplitude;

[0021] The calculation logic of the fault impact index is as follows: obtain the number of interrupted users caused by the feeder fault, and divide the number of interrupted users by the total number of distribution network users to obtain the fault impact index;

[0022] The calculation logic of the instantaneous overcurrent index is: obtain the instantaneous current of the equipment in the feeder, and divide the instantaneous current by the rated current of the equipment to obtain the instantaneous overcurrent index.

[0023] In a preferred embodiment, after comprehensively analyzing the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed, including the following steps:

[0024] The self-healing index and priority index of each feeder are obtained, and the self-healing index and priority index of all feeders are calculated comprehensively to obtain the management coefficient of the distribution network. The expression is: , where is the management coefficient, is the number of feeders in the distribution network, Indicates management factor of feeders, and , where is the priority index, is the self-healing index, , is the adjustment coefficient, and , Greater than 0;

[0025] After obtaining the management coefficient, the management coefficient is compared with the management threshold. The management threshold is used to determine whether the distribution network needs to be managed. If the management coefficient is less than or equal to the management threshold, it is determined that the distribution network does not need to be managed. If the management coefficient is greater than the management threshold, it is determined that the distribution network needs to be managed.

[0026] In a preferred embodiment, after all feeders have completed self-healing, a self-healing index is generated for the feeders in combination with the self-healing rates of the feeders at multiple time points, including the following steps:

[0027] Obtain the self-healing rate of the feeder at multiple time points, and calculate the self-healing rate standard deviation and self-healing rate mean based on the self-healing rates at multiple time points. The expression is: , where is the standard deviation of the self-healing rate, is the mean self-healing rate, is the number of time points, For the feeder The self-healing rate at each time point is used to calculate the self-healing index based on the self-healing rate standard deviation and the self-healing rate mean. The expression is: , where The self-healing index.

[0028] In a preferred embodiment, during the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained periodically, including the following steps:

[0029] After the resource allocation strategy is determined, each feeder starts the self-healing process. The self-healing process consists of one or more time intervals. Each time interval is subdivided into the initial recovery time set for each feeder according to the repair work content and requirements. The time interval for collecting feeder recovery progress data is based on the estimated repair difficulty or historical data.

[0030] During the self-healing process, the device status, load recovery status, and fault repair progress are monitored in real time, and the self-healing rate is obtained and updated regularly. The calculation logic of the self-healing rate is: the number of faulty modules currently recovered is divided by the total number of faulty modules;

[0031] At each point in time, the system will update the self-healing rate based on the collected data. The update process includes: recalculating the self-healing rate according to the number of repaired devices and the restored load ratio information. If the self-healing rate reaches the predetermined target, it will automatically adjust resource allocation or confirm the success of self-healing. If the self-healing rate does not reach the expected target, it will automatically issue an alarm and adjust the repair plan or resource allocation.

[0032] In a preferred embodiment, generating a weight for each evaluation dimension includes the following steps:

[0033] Obtain the maximum load index, equipment failure rate, number of backup paths, and self-healing success rate for each evaluation dimension;

[0034] The importance factor is calculated based on the maximum load index, equipment failure rate, number of backup paths, and self-healing success rate. The expression is: , where is the importance factor, is the maximum load index, is the equipment failure rate, is the number of backup paths, The success rate of self-healing, , , , are the proportional coefficients of maximum load index, equipment failure rate, number of backup paths and self-healing success rate, respectively, and , , , All are greater than 0;

[0035] After obtaining the importance factors of all evaluation dimensions, sum the importance factors of all evaluation dimensions to obtain the denominator value, and divide the importance factor by the denominator value to obtain the weight of each evaluation dimension.

[0036] In a preferred embodiment, after receiving the regional information of the distribution network failure, the analysis system obtains the feeder information involved in the failure in the region, and establishes an adjustment set for all feeders involved in the failure, including the following steps:

[0037] The analysis system receives information about the area where the distribution network has failed. The distribution network monitoring system detects and reports the fault location through automated equipment and analyzes all feeders involved in the fault in the area based on the topological information of the fault area.

[0038] All feeders involved in the fault and their related information, including load and equipment status, are constructed into an adjustment set. The content of the adjustment set includes the status of each feeder, load data, equipment health status, importance level, load type and historical fault records.

[0039] An automatic analysis system for self-healing rate of distribution network feeder faults, comprising a set establishment module, a sorting module, and a management module;

[0040] Set establishment module: after receiving the area where the distribution network has a fault, obtain the feeder information involved in the fault in the area, and establish an adjustment set for all feeders involved in the fault;

[0041] Sorting module: obtains the real-time data and historical data of each feeder in the adjustment set, builds a judgment matrix for the feeder based on the real-time data and historical data, sorts the feeders according to the judgment matrix, sorts the priorities of all feeders in the adjustment set, and generates a resource allocation strategy for the feeder based on the sorting results;

[0042] Management module: When each feeder performs self-healing according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders have completed self-healing, a self-healing index is generated for the feeder based on the self-healing rates of the feeders at multiple time points. After a comprehensive analysis of the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. A management strategy is generated based on the judgment result and sent to the administrator.

[0043] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0044] The present invention obtains the real-time data and historical data of each feeder in the adjustment set, constructs a judgment matrix for the feeder based on the real-time data and historical data, sorts and analyzes the feeders according to the judgment matrix, and then prioritizes all feeders in the adjustment set, and generates a resource allocation strategy for the feeder based on the sorting result. During the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders are self-healed, a self-healing index is generated for the feeder based on the self-healing rate of the feeder at multiple time points. After a comprehensive analysis of the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. The analysis system uses priority sorting, and the solution ensures that high-priority feeders obtain more resource support, reasonably allocates limited resources, and has high adaptability and can flexibly respond to complex scenarios.

[0045] After obtaining the priority indexes of all feeders, the present invention can ensure that the system prioritizes the feeders that need the most attention and restoration by sorting all feeders in the adjustment set (according to the priority index from large to small). Next, the resource allocation strategy for the feeders is generated according to the positive order of the adjustment set to ensure that limited resources (such as repair personnel, spare parts, backup power supplies, etc.) are reasonably allocated to the feeders that need them most, to ensure that system resources are allocated most effectively, and to give priority to restoring the feeders that have the greatest impact on the power grid, thereby improving the self-healing ability and recovery efficiency of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0047] Figure 1 The figure is a flow chart of the method of the present invention. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] Example 1: Please refer to Figure 1 As shown, the present embodiment provides a method for automatically analyzing the self-healing rate of a distribution network feeder fault, and the analysis method includes the following steps:

[0050] After receiving the regional information of the distribution network failure, the analysis system obtains the feeder information involved in the fault in the area, establishes an adjustment set for all the feeders involved in the fault, obtains the real-time data and historical data of each feeder in the adjustment set, and builds a judgment matrix for the feeder based on the real-time data and historical data; after sorting and analyzing the feeders according to the judgment matrix, all the feeders in the adjustment set are prioritized, and a resource allocation strategy for the feeder is generated based on the sorting results; during the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders are self-healed, a self-healing index is generated for the feeder based on the self-healing rates of the feeders at multiple time points. After comprehensively analyzing the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed, and a management strategy is generated based on the judgment result and sent to the administrator.

[0051] This application obtains the real-time data and historical data of each feeder in the adjustment set, builds a judgment matrix for the feeder based on the real-time data and historical data, sorts and analyzes the feeders according to the judgment matrix, prioritizes all feeders in the adjustment set, and generates a resource allocation strategy for the feeder based on the sorting results. During the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders are self-healed, the self-healing index is generated for the feeder based on the self-healing rate of the feeder at multiple time points. After a comprehensive analysis of the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. The analysis system sorts by priority, and the solution ensures that high-priority feeders obtain more resource support, reasonably allocates limited resources, and has high adaptability and can flexibly respond to complex scenarios.

[0052] Embodiment 2: After receiving the regional information of the distribution network failure, the analysis system obtains the feeder information involved in the failure in the region and establishes an adjustment set for all feeders involved in the failure, including the following steps:

[0053] The system receives information about the area where the distribution network has failed. The distribution network monitoring system usually detects and reports the fault location through automation equipment (such as protection devices, remote monitoring units, etc.). Based on the topological information of the fault area, all feeders involved in the fault in the area are analyzed. This includes feeders directly affected by the fault and alternative feeders that may need to be considered due to the spread of the fault (such as backup paths, redundant lines, etc.). For example, if a transformer or main feeder fails, the related branches and branch lines may also be affected, and even some users may have their power supply interrupted.

[0054] All feeders involved in the fault and their related information (such as load, equipment status, etc.) are constructed into an adjustment set. The content of the adjustment set includes the status of each feeder (faulty or normal), load data, equipment health status, importance level, load type (such as industrial, civil, etc.), historical fault records, etc.

[0055] Assume that the location of the distribution network fault is in a city area with multiple feeders and branch lines. The system receives the fault information, and the distribution network monitoring system detects that the transformer has failed through automation equipment (such as protection devices, remote monitoring units, etc.) and reports the fault location. The specific steps are as follows:

[0056] The distribution network monitoring system receives fault alarms through protection devices, remote monitoring units and other equipment. Assume that the fault occurs at the main transformer (transformer T1) in area A at 12:15. Transformer T1 is the main power source in the area. The distribution network monitoring system analyzes all feeders involved in the fault based on the power network topology of area A.

[0057] Main feeder F1: The main feeder to which the transformer is directly connected and is directly affected by the fault.

[0058] Branches F2 and F3: Branch lines of the main feeder F1, which may lose power supply due to a fault in the main feeder F1.

[0059] Backup feeder F4: Backup line F4, connected to another transformer T2, may take on part of the load and supply some users in area A.

[0060] Redundant line F5: Redundant line F5 is designed to support part of the load of main feeder F1 and is automatically activated in case of failure.

[0061] The content of the adjustment set (information of each feeder) is shown in Table 1:

[0062] Table 1 Feeder fault topology information table

[0063]

[0064] By analyzing the above fault topology information, the system organizes all the feeders involved in the fault and their related data into an adjustment set. The adjustment set includes the status of each feeder (faulty or normal), load data, equipment health status, importance level, load type, historical fault records, etc.

[0065] Obtaining the real-time data and historical data of each feeder in the adjustment set, and building a judgment matrix for the feeder based on the real-time data and historical data, including the following steps:

[0066] Before constructing a judgment matrix, you first need to collect real-time and historical data from multiple sources to ensure that the assessment is based on the latest and most comprehensive information.

[0067] Real-time data includes:

[0068] Load data: Collect the current load data of each feeder (such as current, voltage, power, power factor, etc.) to determine whether the load is within the normal range or close to an overload state.

[0069] Equipment status: Collect the real-time health status, switch status and fault records of all relevant equipment (such as transformers, switches, circuit breakers, etc.) to evaluate whether the equipment is working properly.

[0070] Fault information: Obtain the fault type (such as short circuit, overload, grounding, etc.), occurrence time and fault area in real time to confirm the impact of the fault on the feeder.

[0071] Self-healing process: monitor whether the feeder has self-healed after a fault occurs. If so, record the recovery progress.

[0072] Historical data includes:

[0073] Load history: Collect the load data of the feeder over a period of time in the past, evaluate its load fluctuation, and the number of historical load overloads.

[0074] Equipment fault records: Obtain information such as the number of historical faults, types, and handling methods of the feeder to evaluate the reliability of the equipment.

[0075] Restoration history: Analyze the recovery time, self-healing ability, and success rate of feeders in past faults as a reference for restoration strategies.

[0076] Maintenance and inspection records: Obtain the maintenance and inspection history of the equipment to determine the long-term reliability of the feeder and related equipment.

[0077] Based on the above real-time data and historical data, the following main evaluation dimensions are determined (these dimensions will be used to build a judgment matrix for the feeder):

[0078] Load conditions: current load and historical load fluctuations of the feeder.

[0079] Evaluation criteria: whether the load is close to overload and whether the load change is abnormal.

[0080] Device health status: The current operating status and health status of the device.

[0081] Evaluation criteria: whether the equipment has any faults or abnormal operation, and the historical failure rate of the equipment.

[0082] Importance level: The role of the feeder in the power grid and the importance of the power supply area.

[0083] Evaluation criteria: Whether the feeder supplies power to critical loads and whether it affects important users (such as hospitals, industrial enterprises, etc.).

[0084] Restoration History: The historical fault recovery capability of the feeder.

[0085] Evaluation criteria: historical fault recovery time, self-healing rate, repair difficulty, etc.

[0086] Historical fault times: historical fault times of the feeder and the handling methods.

[0087] Evaluation criteria: failure frequency, whether failure is likely to occur.

[0088] Load Type: The type of load served by the feeder (industrial, civil, commercial, etc.).

[0089] Evaluation criteria: importance of the load, and the recovery speed requirements of different types of loads.

[0090] According to the above evaluation dimensions, a judgment matrix is ​​constructed after generating weights for each evaluation dimension. The judgment matrix is ​​usually constructed by scoring each feeder in each dimension and comprehensively considering the impact of each dimension on the feeder priority.

[0091] Generating weights for each evaluation dimension includes the following steps:

[0092] Obtain the maximum load index, equipment failure rate, number of backup paths, and self-healing success rate for each evaluation dimension;

[0093] The importance factor is calculated based on the maximum load index, equipment failure rate, number of backup paths, and self-healing success rate. The expression is: , where is the importance factor, is the maximum load index, is the equipment failure rate, is the number of backup paths, The success rate of self-healing, , , , are the proportional coefficients of maximum load index, equipment failure rate, number of backup paths and self-healing success rate, respectively, and , , , Both are greater than 0.

[0094] After obtaining the importance factors of all evaluation dimensions, sum the importance factors of all evaluation dimensions to obtain the denominator value, and divide the importance factor by the denominator value to obtain the weight of each evaluation dimension.

[0095] The maximum load index refers to the ratio of the maximum load of a feeder or a region within a certain period of time to its rated load. The load data of the feeder is obtained in real time through the distribution network monitoring system, and the maximum load is determined based on historical data. The larger the maximum load index, the greater the power supply pressure of the feeder, which requires more attention and self-healing measures, so its weight should be higher;

[0096] The equipment failure rate indicates the frequency of equipment failures within a certain period of time. It can be obtained through the equipment's historical maintenance records, fault alarm system, or distribution network monitoring system. The higher the failure rate, the poorer the equipment stability, and more self-healing resources are needed to repair these devices. Therefore, the dimension weight of equipment with high failure rate should be larger;

[0097] The number of backup paths refers to the ability of a feeder to provide support through redundant lines or backup power supply paths when a fault occurs. This information can be obtained through the distribution network topology map and the distribution network protection equipment management system. The more backup paths there are, the greater the chance of recovery and self-healing ability after a fault, so the weight of this dimension is smaller. Conversely, feeders with fewer backup paths have greater self-healing requirements and should have a higher weight;

[0098] The self-healing success rate refers to the proportion of the system that successfully restores power supply through automated equipment (such as automatic reclosing, automatic distribution devices, etc.) after a fault occurs. It is obtained through historical self-healing records or data from the distribution network monitoring system. The higher the self-healing success rate, the stronger the system's self-healing ability is, and it may not require much additional intervention. Therefore, the weight of this dimension is smaller. Conversely, feeders with low self-healing success rates require more self-healing strategies and attention, and the weight should be greater.

[0099] After sorting and analyzing the feeders according to the judgment matrix, all feeders in the adjustment set are prioritized, and a resource allocation strategy for the feeders is generated according to the sorting results, including the following steps:

[0100] All evaluation dimensions in the judgment matrix are weighted to obtain the priority index of the feeder, which is expressed as: , where is the priority index, is the number of evaluation dimensions of the feeder, The weight of the evaluation dimension, For the Evaluation dimension values;

[0101] After obtaining the priority indexes of all feeders, all feeders in the adjustment set are sorted from large to small according to the priority index, and the resource allocation strategy of the feeders is generated according to the positive order of the adjustment set. The resource allocation strategy is:

[0102] After obtaining the priority index of all feeders, all feeders are sorted from large to small according to the priority index. The higher the priority index of a feeder, the higher its urgency and importance in the process of fault recovery, management or optimization;

[0103] The allocation of resources must follow certain principles to ensure that limited resources can give priority to meeting the needs of high-priority feeders. When allocating resources, consider the following factors:

[0104] Priority allocation of fault repair resources: More fault repair resources are allocated to feeders with higher priorities.

[0105] Priority allocation of load recovery resources: For feeders with higher load recovery requirements, corresponding recovery resources are allocated preferentially.

[0106] Use of backup power and redundant paths: Provide backup power support or activate redundant paths for high-priority feeders.

[0107] Allocation of personnel and equipment: Allocation of appropriate maintenance personnel and equipment based on the repair difficulty, fault type, importance level, etc. of each feeder.

[0108] Assuming that the total amount of system resources is limited, proportional allocation or priority allocation is required. For feeders with higher priority, try to ensure that they can obtain the required resources in a timely manner, especially repair and load recovery resources. For feeders with lower priority, resource allocation can be appropriately reduced or delayed. Dynamically adjust resource allocation strategies based on real-time data and system feedback. For example, if the faults of some high-priority feeders are more complex and require more repair personnel and time, the system will automatically adjust resource allocation to ensure the optimization of repair effect and time.

[0109] After obtaining the priority index of all feeders, this application can ensure that the system prioritizes the feeders that need the most attention and restoration by sorting all feeders in the adjustment set (according to the priority index from large to small). Next, the resource allocation strategy for the feeders is generated according to the positive order of the adjustment set to ensure that limited resources (such as repair personnel, spare parts, backup power supplies, etc.) are reasonably allocated to the feeders that need them most, ensuring that system resources are allocated most effectively, and giving priority to restoring the feeders that have the greatest impact on the power grid, thereby improving the self-healing ability and recovery efficiency of the distribution network.

[0110] In this application, the evaluation dimensions include load fluctuation amplitude, fault impact index and instantaneous overcurrent index, namely ;

[0111] The calculation logic of the load fluctuation amplitude is as follows: obtain the load values ​​of the feeder at multiple time points within the monitoring period, calculate the load standard deviation based on the load values ​​at multiple time points, and use the load standard deviation as the load fluctuation amplitude. The larger the load fluctuation amplitude, the greater the load fluctuation of the feeder within the monitoring period, and the more priority management is needed;

[0112] The calculation logic of the fault impact index is as follows: obtain the number of interrupted users caused by feeder faults, and divide the number of interrupted users by the total number of distribution network users to obtain the fault impact index. The larger the fault impact index, the more users are affected by the feeder, and the more priority management is needed;

[0113] The calculation logic of the instantaneous overcurrent index is: obtain the instantaneous current of the equipment in the feeder, divide the instantaneous current by the rated current of the equipment to obtain the instantaneous overcurrent index. The larger the instantaneous overcurrent index, the larger the instantaneous overcurrent of the feeder, and the more priority management is needed.

[0114] During the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained periodically, including the following steps:

[0115] After the resource allocation strategy is determined, the self-healing process of each feeder begins. The system will sort by priority and perform self-healing operations on feeders with higher priority first. The self-healing process usually consists of one or more time intervals, and each time interval will be subdivided according to the content and needs of the repair work. For example: the initial recovery time set by the system for each feeder is usually based on the estimated repair difficulty or historical data. The time interval for regularly collecting feeder recovery progress data can be minutes, hours, etc., depending on the accuracy requirements of the system and the complexity of the repair process;

[0116] During the self-healing process, the system regularly obtains and updates the self-healing rate by real-time monitoring of equipment status, load recovery, fault repair progress, etc. The self-healing rate is calculated by dividing the number of faulty modules currently recovered by the total number of faulty modules. The number of faulty modules currently recovered refers to the number of modules that have been repaired and restored to normal power supply (such as transformers, distribution lines, etc.), and the total number of faulty modules refers to the total number of faulty modules in the entire feeder system.

[0117] At each point in time, the system will update the self-healing rate based on the collected data. The update process includes:

[0118] The self-healing rate is recalculated based on the number of devices repaired, the proportion of restored load, and other information. If the self-healing rate reaches the predetermined target (such as 90% or 100%), the system will automatically adjust resource allocation or confirm the success of self-healing. If the self-healing rate does not meet expectations, the system can automatically issue an alarm and adjust the repair plan or resource allocation.

[0119] The system monitors whether the self-healing progress is as planned and compares the difference between the actual self-healing rate and the expected self-healing rate (such as estimated time and recovery progress). If the self-healing rate is much lower than expected, the system will trigger a warning and make adjustments based on the actual situation:

[0120] If the self-healing rate of some feeders is low, the system can allocate more resources to these feeders or adjust the repair strategy (for example, switch to backup power or start redundant lines). According to the self-healing progress, the resource requirements or repair time of subsequent steps are adjusted to ensure that the repair work is as short as possible and efficient.

[0121] The self-healing rate data at each time point will be collected and a report will be generated. The report includes: the real-time self-healing rate of each feeder. The details of the repair progress and load recovery. If the self-healing progress lags behind, the cause of the fault, the scope of impact and the subsequent treatment plan will be recorded.

[0122] When the self-healing rate of all feeders reaches the predetermined target (e.g. 100%), the system will confirm that the self-healing work is complete. After that, the system will conduct a final verification:

[0123] The system will re-check the equipment status and load conditions of the feeder to ensure that all repair work is completed and there are no subsequent failures. Finally, the self-healing success rate of each feeder is generated and marked as "completed" or "pending further processing".

[0124] When all feeders have completed self-healing, a self-healing index is generated for the feeders based on the self-healing rates of the feeders at multiple time points, including the following steps:

[0125] Obtain the self-healing rate of the feeder at multiple time points, and calculate the self-healing rate standard deviation and self-healing rate mean based on the self-healing rates at multiple time points. The expression is:

[0126] , where is the standard deviation of the self-healing rate, is the mean self-healing rate, is the number of time points, For the feeder The spontaneous recovery rate at each time point;

[0127] The self-healing index is calculated based on the self-healing rate standard deviation and the self-healing rate mean. The expression is:

[0128] , where The self-healing index.

[0129] After comprehensively analyzing the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. A management strategy is generated based on the judgment result and sent to the administrator, including the following steps:

[0130] The self-healing index and priority index of each feeder are obtained, and the self-healing index and priority index of all feeders are calculated comprehensively to obtain the management coefficient of the distribution network. The expression is: , where is the management coefficient, is the number of feeders in the distribution network, Indicates management factor of feeders, and , where is the priority index, is the self-healing index, , is the adjustment coefficient, and , Greater than 0;

[0131] After obtaining the management coefficient, compare the management coefficient with the management threshold. The management threshold is used to determine whether the distribution network needs to be managed. If the management coefficient is less than or equal to the management threshold, it is determined that the distribution network does not need to be managed. If the management coefficient is greater than the management threshold, it is determined that the distribution network needs to be managed. The generated management strategy is:

[0132] Based on the comparison between the management coefficient and the management threshold, the system will generate a corresponding management strategy. The content of the management strategy may include the following aspects depending on different situations:

[0133] When the management coefficient is less than or equal to the management threshold: no management is required, and the distribution network is in good condition. At this time, the system can continue to monitor the operation of the distribution network to ensure its continued stability. Continue to track and monitor, no immediate action is required. Management policy example: "The distribution network is operating normally, continue to monitor, and no further management is required."

[0134] When the management coefficient is greater than the management threshold: the distribution network needs to be managed and corresponding optimization measures need to be taken. At this time, the following operations may be required: adjust the load distribution and balance the load. Enhance the response speed of fault repair and improve the repair efficiency. Start the backup power supply or redundant path. Focus on monitoring areas with high equipment failure rates. Conduct special inspections to assess potential failure risks.

[0135] Management policy examples: "There are abnormalities in the distribution network operation, and it is necessary to start load balancing and optimize the allocation of repair resources." "The failure rate is high. It is recommended to strengthen equipment monitoring and increase backup power support." "Based on the insufficient self-healing rate, it is recommended to speed up the repair progress and start the redundant power supply."

[0136] Based on the management strategy, the system will generate execution instructions and send them to the distribution network management personnel or automation system to guide them to take appropriate measures. These instructions may include: adjusting resource allocation. Increasing the response priority of repair personnel and equipment. Starting backup paths and backup power sources. Starting further monitoring and troubleshooting.

[0137] Examples of execution instructions: "Prioritize the allocation of repair resources to areas with serious faults and increase backup power support." "Start equipment health monitoring and inspect areas with high fault rates." "Accelerate load transfer to ensure stable power supply in high-load areas."

[0138] Embodiment 3: A distribution network feeder fault self-healing rate automatic analysis system described in this embodiment includes a collection establishment module, a sorting module, and a management module;

[0139] Set establishment module: after receiving the area where the distribution network has a fault, obtain the feeder information involved in the fault in the area, establish an adjustment set for all feeders involved in the fault, and send the adjustment set to the sorting module;

[0140] Sorting module: obtains the real-time data and historical data of each feeder in the adjustment set, builds a judgment matrix for the feeder based on the real-time data and historical data, sorts the feeders according to the judgment matrix, sorts all the feeders in the adjustment set, and generates a resource allocation strategy for the feeder based on the sorting results. The resource allocation strategy is sent to the management module;

[0141] Management module: When each feeder performs self-healing according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders have completed self-healing, a self-healing index is generated for the feeder based on the self-healing rates of the feeders at multiple time points. After a comprehensive analysis of the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. A management strategy is generated based on the judgment result and sent to the administrator.

[0142] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0143] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0144] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A method for automatically analyzing the self-healing rate of distribution network feeder faults, characterized in that: The analytical method comprises the following steps: After receiving the regional information of the distribution network failure, the analysis system obtains the information of the feeders involved in the failure in the region, establishes an adjustment set for all the feeders involved in the failure, obtains the real-time data and historical data of each feeder in the adjustment set, and builds a judgment matrix for the feeders based on the real-time data and historical data; After sorting and analyzing the feeders according to the judgment matrix, all feeders in the adjustment set are prioritized, and a resource allocation strategy for the feeders is generated based on the sorting results; During the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders are self-healed, the self-healing index of the feeder is generated by combining the self-healing rates of the feeder at multiple time points. The expression is: , where is the self-healing index, is the standard deviation of the self-healing rate, The self-healing rate is the average value. After comprehensively analyzing the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed, including the following steps: The self-healing index and priority index of all feeders are calculated comprehensively to obtain the management coefficient of the distribution network. The expression is: , where is the management coefficient, is the number of feeders in the distribution network, Indicates management factor of feeders, and , where is the priority index, is the self-healing index, , is the adjustment coefficient, and , If it is greater than 0, the evaluation dimension is obtained based on real-time data and historical data, and all the evaluation dimensions in the judgment matrix are weighted to obtain the priority index of the feeder; After obtaining the management coefficient, compare the management coefficient with the management threshold. The management threshold is used to determine whether the distribution network needs to be managed. If the management coefficient is less than or equal to the management threshold, it is determined that the distribution network does not need to be managed. If the management coefficient is greater than the management threshold, it is determined that the distribution network needs to be managed. A management policy is generated based on the judgment result and sent to the administrator.

2. The method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 1 is characterized in that: Obtaining the real-time data and historical data of each feeder in the adjustment set, and building a judgment matrix for the feeder based on the real-time data and historical data, including the following steps: Real-time data includes load data, equipment status, fault information, and self-healing process; Historical data includes load history, equipment failure records, recovery history, maintenance and inspection records; The evaluation dimensions are obtained based on real-time data and historical data. The evaluation dimensions include load conditions, equipment health status, importance level, historical failure times, and load type. A judgment matrix is ​​constructed after generating weights for each evaluation dimension.

3. The method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 2 is characterized in that: Prioritize all feeders in the adjustment set, including the following steps: All evaluation dimensions in the judgment matrix are weighted to obtain the priority index of the feeder, which is expressed as: , where is the priority index, is the number of evaluation dimensions of the feeder, For the The weight of the evaluation dimension, For the Evaluation dimension values; After obtaining the priority indexes of all feeders, all feeders in the adjustment set are sorted from large to small according to the priority index, and the resource allocation strategy of the feeders is generated according to the positive order of the adjustment set.

4. The method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 3 is characterized in that: The evaluation dimensions include load fluctuation amplitude, fault impact index and instantaneous overcurrent index; The calculation logic of the load fluctuation amplitude is as follows: obtain the load values ​​of the feeder at multiple time points within the monitoring period, calculate the load standard deviation based on the load values ​​at multiple time points, and use the load standard deviation as the load fluctuation amplitude; The calculation logic of the fault impact index is as follows: obtain the number of interrupted users caused by the feeder fault, and divide the number of interrupted users by the total number of distribution network users to obtain the fault impact index; The calculation logic of the instantaneous overcurrent index is: obtain the instantaneous current of the equipment in the feeder, and divide the instantaneous current by the rated current of the equipment to obtain the instantaneous overcurrent index.

5. The method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 4 is characterized in that: The calculation logic of the self-healing rate standard deviation and the self-healing rate mean is: obtain the self-healing rate of the feeder at multiple time points, and calculate the self-healing rate standard deviation and the self-healing rate mean according to the self-healing rates at multiple time points. The expression is: , where is the standard deviation of the self-healing rate, is the mean self-healing rate, is the number of time points, For the feeder The spontaneous recovery rate at each time point.

6. A method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 5, characterized in that: During the self-healing process of each feeder according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained periodically, including the following steps: After the resource allocation strategy is determined, each feeder starts the self-healing process. The self-healing process consists of one or more time intervals. Each time interval is subdivided into the initial recovery time set for each feeder according to the repair work content and requirements. The time interval for collecting feeder recovery progress data is based on the estimated repair difficulty or historical data. During the self-healing process, the device status, load recovery status, and fault repair progress are monitored in real time, and the self-healing rate is obtained and updated regularly. The calculation logic of the self-healing rate is: the number of faulty modules currently recovered is divided by the total number of faulty modules; At each point in time, the system will update the self-healing rate based on the collected data. The update process includes: recalculating the self-healing rate according to the number of repaired devices and the restored load ratio information. If the self-healing rate reaches the predetermined target, it will automatically adjust resource allocation or confirm the success of self-healing. If the self-healing rate does not reach the expected target, it will automatically issue an alarm and adjust the repair plan or resource allocation.

7. A method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 6, characterized in that: Generating weights for each evaluation dimension includes the following steps: Obtain the maximum load index, equipment failure rate, number of backup paths, and self-healing success rate for each evaluation dimension; The importance factor is calculated based on the maximum load index, equipment failure rate, number of backup paths, and self-healing success rate. The expression is: , where is the importance factor, is the maximum load index, is the equipment failure rate, is the number of backup paths, The success rate of self-healing, , , , are the proportional coefficients of maximum load index, equipment failure rate, number of backup paths and self-healing success rate, respectively, and , , , All are greater than 0; After obtaining the importance factors of all evaluation dimensions, sum the importance factors of all evaluation dimensions to obtain the denominator value, and divide the importance factor by the denominator value to obtain the weight of each evaluation dimension.

8. The method for automatically analyzing the self-healing rate of a distribution network feeder fault according to claim 7 is characterized in that: After receiving the regional information of the distribution network failure, the analysis system obtains the feeder information involved in the failure in the region and establishes an adjustment set for all feeders involved in the failure, including the following steps: The analysis system receives information about the area where the distribution network has failed. The distribution network monitoring system detects and reports the fault location through automated equipment and analyzes all feeders involved in the fault in the area based on the topological information of the fault area. All feeders involved in the fault and their related information, including load and equipment status, are constructed into an adjustment set. The content of the adjustment set includes the status of each feeder, load data, equipment health status, importance level, load type and historical fault records.

9. A distribution network feeder fault self-healing rate automatic analysis system, used to implement the analysis method according to any one of claims 1 to 8, characterized in that: Including collection establishment module, sorting module and management module; Set establishment module: after receiving the area where the distribution network has a fault, obtain the feeder information involved in the fault in the area, and establish an adjustment set for all feeders involved in the fault; Sorting module: obtains the real-time data and historical data of each feeder in the adjustment set, builds a judgment matrix for the feeder based on the real-time data and historical data, sorts the feeders according to the judgment matrix, sorts the priorities of all feeders in the adjustment set, and generates a resource allocation strategy for the feeder based on the sorting results; Management module: When each feeder performs self-healing according to the resource allocation strategy, the self-healing rate of the feeder at each time point is obtained regularly. When all feeders have completed self-healing, a self-healing index is generated for the feeder based on the self-healing rates of the feeders at multiple time points. After a comprehensive analysis of the self-healing indexes of all feeders, it is determined whether the distribution network needs to be managed. A management strategy is generated based on the judgment result and sent to the administrator.

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