Intelligent power grid fault early warning and recovery system for electric power

Abstract

The invention relates to the technical field of Internet of Things and automation, in particular to an intelligent power grid fault early warning and recovery system for electric power, which comprises fault monitoring modules, a maintenance dispatching module and a patrol arrangement module, and is characterized in that the fault monitoring modules are arranged in branch circuits and are used for displaying fault information when the branch circuits of the power grid have faults; the maintenance dispatching module is used for dispatching idle workers to carry out maintenance when the branch circuit of the power grid fails; the patrol arrangement module is used for carrying out patrol arrangement on different branch circuits according to the number of faults of the branch circuits of the power grid, the stability and reliability of the power system are improved, the utilization rate of maintenance resources is improved through an intelligent dispatching mode, the timeliness and accuracy of maintenance are ensured, and the maintenance efficiency is improved. The data-based patrol arrangement mode is more scientific and reasonable, the patrol efficiency can be remarkably improved, and unnecessary patrol times and manpower waste are reduced.

Description

Technical Field

[0001] The present invention relates to the field of Internet of Things and automation technology, and in particular to a smart grid fault early warning and recovery system for electric power. Background Art

[0002] With the continuous development of power systems and the improvement of their intelligence level, the construction of smart grids has become an important trend in the power industry. Smart grids integrate advanced communication technologies, information technologies, and control technologies to achieve comprehensive monitoring and optimization of power production, transmission, distribution, and use. However, existing fault monitoring methods are relatively backward and can often only be detected after a fault occurs, which results in a long response time for fault handling and affects the stability and reliability of the power system. Traditional monitoring methods mainly rely on manual inspections and regular inspections, which are not only inefficient, but also difficult to achieve real-time monitoring and early warning of power systems. Maintenance dispatch and inspection arrangements lack intelligence and automation. After a fault occurs, the dispatch and inspection arrangements of maintenance personnel often rely on manual decision-making and experience judgment, which leads to a waste of maintenance resources and low inspection efficiency. At the same time, due to the lack of real-time knowledge of the working status and location of maintenance personnel, the accuracy and timeliness of maintenance dispatch are difficult to guarantee. The existing smart grid fault early warning and recovery system has deficiencies in data processing and analysis. Traditional data processing methods can often only record and count faults simply, lacking in-depth mining and analysis of fault data, which limits the accuracy and reliability of fault warnings. The existing smart grid fault warning and recovery system has deficiencies in fault monitoring, maintenance dispatch, inspection arrangement, data processing and analysis, and system integration, which limits the improvement of the stability and reliability of the smart grid.

[0003] Therefore, a smart grid fault warning and recovery system for electric power is proposed. Summary of the invention

[0004] The present invention aims to solve the problem that the current traditional power grid fault monitoring means are relatively lagging, resulting in a long response time for fault handling, affecting the stability and reliability of the power system. The dispatch and inspection arrangements of maintenance personnel often rely on manual decision-making and experience judgment, which leads to a waste of maintenance resources and reduced inspection efficiency, as well as a lack of real-time knowledge of the working status and location of maintenance personnel, making it difficult to ensure the accuracy and timeliness of maintenance dispatch.

[0005] The technical solution adopted by the present invention to solve the technical problem is:

[0006] A smart grid fault early warning and recovery system for electric power, including a fault monitoring module, a maintenance dispatch module, and an inspection arrangement module.

[0007] The fault monitoring module is used to monitor the faults of the power grid branch circuit;

[0008] The maintenance dispatch module is used to dispatch idle workers for maintenance;

[0009] The inspection arrangement module is used to arrange inspections for different branch circuits.

[0010] Further, the fault monitoring module includes a plurality of power meters, a data processing unit and a mobile terminal;

[0011] A plurality of power meters are arranged in i branch circuits to monitor the real-time load power of the branch circuits at regular intervals, and then transmit the real-time load power data of the branch circuits monitored at each timing point to the data processing unit, and each timing point is a half-hour time interval for uploading data by the power meter;

[0012] The data processing unit is wirelessly connected to a plurality of power meters, and is used to divide a day into four cycles; and after receiving the real-time load power data of the branch circuit, calculate the fluctuation coefficient within the cycle of the branch circuit according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit; and is used to calculate the fluctuation value of each timing monitoring point of the branch circuit according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit; and is used to count the fluctuation value of each timing monitoring point of the branch circuit in the cycle according to the calculated fluctuation value The number of timing monitoring points that meet the requirement that the fluctuation value of each timing monitoring point is greater than the average value of the fluctuation coefficient; and the abnormality degree coefficient of the branch circuit is calculated according to the number data of the moments when the fluctuation value of each sampling point of the branch circuit in the period is greater than the average value of the fluctuation coefficient, the fluctuation coefficient of the branch circuit in the period and the fluctuation value of each timing monitoring point; and when it is detected that the abnormality degree coefficient of any branch circuit is greater than a preset abnormality degree coefficient threshold, it is judged that the corresponding branch circuit has an abnormality; and when it is judged that any corresponding branch circuit has an abnormality, it is generated the abnormality information of the corresponding branch circuit, and then the abnormality information of the corresponding branch circuit is transmitted to the mobile terminal;

[0013] The mobile terminal is in communication connection with the data processing unit and is used for displaying the branch line abnormality information after receiving the corresponding branch line abnormality information.

[0014] Furthermore, the calculation formula of the fluctuation coefficient within the period of the branch circuit is:

[0015]

[0016] Among them, γ i is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit, P rzIt is the theoretical power data of the branch circuit within the cycle measured in advance, and its unit is W, P ei_i It is the real-time load power data of each monitoring point within the cycle of the branch circuit, and its unit is W.

[0017] Furthermore, the formula for calculating the fluctuation value of each timing monitoring point according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit is:

[0018]

[0019] Among them, ω ji is the fluctuation value of each timing monitoring point, P rz It is the theoretical power data of the branch circuit within the cycle measured in advance, and its unit is W, P ei_i It is the real-time load power data of each monitoring point within the cycle of the branch circuit, and its unit is W.

[0020] Further, according to the calculated fluctuation value of each timing monitoring point, the number of timing monitoring points in the branch circuit that satisfy the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the period is counted as follows:

[0021]

[0022] Wherein, k1 is the number of timing monitoring points in the branch circuit that satisfy the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the cycle according to the calculated fluctuation value of each timing monitoring point. is the fluctuation value of each timing monitoring point of the branch circuit, γ i It is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit.

[0023] Furthermore, the calculation formula of the abnormality degree coefficient of the branch circuit is:

[0024]

[0025] Among them, G j is the abnormality coefficient of the branch circuit, i is the number of timing monitoring points, is the fluctuation value of each timing monitoring point, k1 is the number of timing monitoring points in the branch circuit that meet the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the cycle according to the calculated fluctuation value of each timing monitoring point, γ i It is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit.

[0026] Furthermore, the maintenance dispatch module includes a control center module.

[0027] The data processing unit is used to generate abnormal information of the branch circuit when it is determined that any branch circuit has an abnormality, and then transmit the abnormal information of the branch circuit to the control center module;

[0028] The mobile terminal is connected to the control center module for communication, and is used to distinguish the working status of the maintenance personnel into an offline state, a busy state, and an idle state; and is used to upload the working status data of the maintenance personnel; and is used to locate the location information of the maintenance personnel in real time, and then upload the location information of the maintenance personnel to the control center module in real time; and is used to update the working status of the maintenance personnel to a busy state after receiving the dispatch information and the abnormal branch line circuit location information;

[0029] The control center module is electrically connected to the data processing unit, and is used to update the work status and location information of the maintenance personnel uploaded by the mobile terminal module in real time; and is used to obtain the abnormal branch circuit location information according to the preset branch circuit location information after receiving the branch circuit abnormality information; and is used to compare the distance between the location information of all idle maintenance personnel and the abnormal branch circuit location information to confirm the idle maintenance personnel to be dispatched; and is used to generate dispatch information after confirming the dispatched idle maintenance personnel, and then transmit the dispatch information and the abnormal branch circuit location information to the mobile terminal of the maintenance personnel.

[0030] Furthermore, the inspection arrangement module includes a fault statistics unit and a data analysis module.

[0031] The data processing unit is used to generate corresponding branch circuit abnormality information when it is determined that there is an abnormality in the branch circuit, and then transmit the corresponding branch circuit abnormality information and abnormality degree coefficient to the fault statistics unit;

[0032] The fault statistics unit is connected to the data processing unit network, and is used to store the corresponding branch circuit abnormality information and abnormality degree coefficient after receiving the corresponding branch circuit abnormality information and abnormality degree coefficient;

[0033] The data analysis module is respectively connected to the fault statistics unit module and the control center module network, and is used to obtain the total data of the number of abnormalities and the abnormality index of the branch circuit in the fault statistics unit; and is used to calculate the inspection coefficient of the branch circuit according to the total data of the number of abnormalities and the abnormality index of the branch circuit; and is used to compare the inspection coefficient of the branch circuit with the preset inspection coefficient threshold range; and is used to generate the inspection arrangement plan of the branch circuit according to the comparison result, and then transmit the inspection arrangement plan of the branch circuit to the control center module;

[0034] The control center module is used to, upon receiving the inspection arrangement information of the branch circuit, prompt the user to arrange maintenance personnel to inspect the abnormal branch circuit according to the inspection arrangement information of the branch circuit.

[0035] Furthermore, the calculation formula of the patrol coefficient of the branch circuit is:

[0036]

[0037] Where X is the inspection coefficient of the branch circuit, ω1 and ω2 are weight coefficients, and ω1+ω2=1, m is the number of branch circuit anomalies, G j is the abnormality degree coefficient of the branch circuit.

[0038] Furthermore, the inspection coefficient of the branch circuit is compared with the preset inspection coefficient threshold range in the following manner:

[0039]

[0040] Among them, X is the inspection coefficient of the branch circuit, X1 is the preset first threshold of the inspection coefficient, X2 is the preset second threshold of the inspection coefficient, and X3 is the preset third threshold of the inspection coefficient. When the output result is 0, no inspection is arranged. When the output result is 1, idle maintenance personnel are arranged to inspect the branch circuit once a month. When the output result is 2, idle maintenance personnel are arranged to inspect the branch circuit once a week. When the output result is 3, idle maintenance personnel are arranged to inspect the branch circuit twice a week.

[0041] Compared with the prior art, the beneficial effects achieved by the present invention are:

[0042] 1. The system monitors the load power of the power grid branch circuit in real time, calculates the fluctuation coefficient and fluctuation value, and promptly identifies abnormal conditions. Once an abnormality is detected, the system will immediately trigger an early warning, significantly shortening the response time of fault handling, thereby improving the stability and reliability of the power system.

[0043] 2. According to the real-time working status and location information of the maintenance personnel, the nearest idle maintenance personnel are automatically selected for dispatch. This intelligent dispatch method not only improves the utilization rate of maintenance resources, but also ensures the timeliness and accuracy of maintenance.

[0044] 3. The inspection arrangement module automatically generates an inspection arrangement plan based on the number of faults and abnormality coefficients of each branch circuit. This data-based inspection arrangement method is more scientific and reasonable, which can significantly improve inspection efficiency and reduce unnecessary inspection times and manpower waste.

[0045] 4. The communication connection between the mobile terminal and the control center module enables the control center to grasp the working status and location information of the maintenance personnel in real time. This not only improves the accuracy of maintenance dispatch, but also facilitates the scheduling and management of maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments are briefly introduced below. The drawings described below only relate to some embodiments of the present invention, but are not intended to limit the present invention.

[0047] In the attached picture:

[0048] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION

[0049] The concept and technical effects of the present invention will be clearly and completely described below in conjunction with embodiments to fully understand the purpose, features and effects of the present invention.

[0050] See also Figure 1 ,

[0051] A smart grid fault early warning and recovery system for electric power, characterized by comprising a fault monitoring module, a maintenance dispatch module, and an inspection arrangement module.

[0052] The fault monitoring module is used to monitor the faults of the power grid branch circuit;

[0053] The maintenance dispatch module is used to dispatch idle workers for maintenance;

[0054] The inspection arrangement module is used to arrange inspections for different branch circuits.

[0055] In this embodiment, the fault monitoring module includes a plurality of power meters, a data processing unit and a mobile terminal;

[0056] A plurality of power meters are arranged in i branch circuits to monitor the real-time load power of the branch circuits at regular intervals, and then transmit the real-time load power data of the branch circuits monitored at each timing point to the data processing unit, and each timing point is a half-hour time interval for uploading data by the power meter;

[0057] The data processing unit is wirelessly connected to a plurality of power meters, and is used to divide a day into four cycles; and after receiving the real-time load power data of the branch circuit, calculate the fluctuation coefficient within the cycle of the branch circuit according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit; and is used to calculate the fluctuation value of each timing monitoring point of the branch circuit according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit; and is used to calculate the branch circuit meeting each timing monitoring point within the cycle according to the calculated fluctuation value of each timing monitoring point of the branch circuit. The number of timing monitoring points at which the fluctuation value of the timing monitoring point is greater than the average value of the fluctuation coefficient; and the abnormality degree coefficient of the branch circuit is calculated based on the number data of the moments at which the fluctuation value of each sampling point of the branch circuit within the cycle is greater than the average value of the fluctuation coefficient, the fluctuation coefficient of the branch circuit within the cycle and the fluctuation value of each timing monitoring point; and when it is detected that the abnormality degree coefficient of any branch circuit is greater than a preset abnormality degree coefficient threshold, it is judged that the corresponding branch circuit has an abnormality; and when it is judged that any corresponding branch circuit has an abnormality, the corresponding branch circuit abnormality information is generated, and then the corresponding branch circuit abnormality information is transmitted to the mobile terminal, and the data processing unit is a server;

[0058] The mobile terminal is in communication connection with the data processing unit and is used for displaying the branch line abnormality information after receiving the corresponding branch line abnormality information.

[0059] In this embodiment, the calculation formula of the fluctuation coefficient within the period of the branch circuit is:

[0060]

[0061] Among them, γ i is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit, P rz It is the theoretical power data of the branch circuit within the cycle measured in advance, and its unit is W, P ei_i It is the real-time load power data of each monitoring point within the cycle of the branch circuit, and its unit is W.

[0062] For example, when P rz =10500W, P ei_1 =12000W, P ei_2 =13000W, P ei_3 =12500W, the fluctuation coefficient of the third branch circuit within the cycle is calculated to be 0.2.

[0063] In this embodiment, the formula for calculating the fluctuation value of each timing monitoring point according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit is:

[0064]

[0065] in, is the fluctuation value of each timing monitoring point, P rz It is the theoretical power data of the branch circuit within the cycle measured in advance, and its unit is W, P ei_i It is the real-time load power data of each monitoring point within the cycle of the branch circuit, and its unit is W.

[0066] For example, when P rz =10500W, P ei_3 =12500W, the fluctuation value of the third timing monitoring point is calculated to be 0.16.

[0067] In this embodiment, the method of counting the number of timing monitoring points in the branch circuit that satisfy the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within a period according to the calculated fluctuation value of each timing monitoring point is as follows:

[0068]

[0069] Wherein, k1 is the number of timing monitoring points in the branch circuit that satisfy the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the cycle according to the calculated fluctuation value of each timing monitoring point. is the fluctuation value of each timing monitoring point of the branch circuit, γ i It is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit.

[0070] For example, when , k1=2.

[0071] In this embodiment, the calculation formula of the abnormality degree coefficient of the branch circuit is:

[0072]

[0073] Among them, G j is the abnormality coefficient of the branch circuit, i is the number of timing monitoring points, is the fluctuation value of each timing monitoring point, k1 is the number of timing monitoring points in the branch circuit that meet the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the cycle according to the calculated fluctuation value of each timing monitoring point, γ i It is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit.

[0074] For example, when k1=2, i=3, When , the abnormality degree coefficient of the branch circuit is calculated to be 0.33.

[0075] In this embodiment, the maintenance dispatch module includes a control center module.

[0076] The data processing unit is used to generate abnormal information of the branch circuit when it is determined that any branch circuit has an abnormality, and then transmit the abnormal information of the branch circuit to the control center module;

[0077] The mobile terminal is connected to the control center module for communication, and is used to distinguish the working status of the maintenance personnel into an offline state, a busy state, and an idle state; and is used to upload the working status data of the maintenance personnel; and is used to locate the location information of the maintenance personnel in real time, and then upload the location information of the maintenance personnel to the control center module in real time; and is used to update the working status of the maintenance personnel to a busy state after receiving the dispatch information and the abnormal branch line circuit location information;

[0078] The control center module is electrically connected to the data processing unit, and is used to update the work status and location information of the maintenance personnel uploaded by the mobile terminal module in real time; and is used to obtain the abnormal branch circuit location information according to the preset branch circuit location information after receiving the branch circuit abnormality information; and is used to compare the distance between the location information of all idle maintenance personnel and the abnormal branch circuit location information to confirm the dispatched idle maintenance personnel; and is used to generate dispatch information after confirming the dispatched idle maintenance personnel, and then transmit the dispatch information and the abnormal branch circuit location information to the mobile terminal of the maintenance personnel. The control center module is a server. For example, the dispatch information is to prompt the idle maintenance personnel to go to the abnormal branch circuit location information for inspection.

[0079] For example, the idle maintenance personnel to be dispatched are confirmed by comparing the distance between the location information of all idle maintenance personnel and the location information of the abnormal branch circuit, and priority is sorted according to the distance between the location information of the idle maintenance personnel and the location information of the abnormal branch circuit. The closer the distance, the higher the priority.

[0080] In this embodiment, the inspection arrangement module includes a fault statistics unit and a data analysis module.

[0081] The data processing unit is used to generate corresponding branch circuit abnormality information when it is determined that there is an abnormality in the branch circuit, and then transmit the corresponding branch circuit abnormality information and abnormality degree coefficient to the fault statistics unit;

[0082] The fault statistics unit is connected to the data processing unit network, and is used to store the corresponding branch circuit abnormality information and abnormality degree coefficient after receiving the corresponding branch circuit abnormality information and abnormality degree coefficient; and is used to count the number of branch circuit abnormalities and the sum of abnormality degree indexes within one month, and the fault statistics unit is a database;

[0083] The data analysis module is respectively connected to the fault statistics unit module and the control center module network, and is used to obtain the total data of the number of branch circuit abnormalities and the abnormality index in the fault statistics unit; and is used to calculate the inspection coefficient of the branch circuit according to the total data of the number of branch circuit abnormalities and the abnormality index; and is used to compare the inspection coefficient of the branch circuit with the preset inspection coefficient threshold range; and is used to generate the inspection arrangement plan of the branch circuit according to the comparison result, and then transmit the inspection arrangement plan of the branch circuit to the control center module. The data analysis module is a processor;

[0084] The control center module is used to, upon receiving the inspection arrangement information of the branch circuit, prompt the user to arrange maintenance personnel to inspect the abnormal branch circuit according to the inspection arrangement information of the branch circuit.

[0085] In this embodiment, the calculation formula of the patrol coefficient of the branch circuit is:

[0086]

[0087] Where X is the inspection coefficient of the branch circuit, ω1 and ω2 are weight coefficients, and ω1+ω2=1, m is the number of branch circuit anomalies, G j is the abnormality degree coefficient of the branch circuit.

[0088] For example, when ω1=0.7,ω2=0.3,m t =4, At this time, the inspection coefficient of the branch circuit is calculated to be 2.95.

[0089] In this embodiment, the inspection coefficient of the branch circuit is compared with the preset inspection coefficient threshold range in the following manner:

[0090]

[0091] Among them, X is the inspection coefficient of the branch circuit, X1 is the preset first threshold of the inspection coefficient, X2 is the preset second threshold of the inspection coefficient, and X3 is the preset third threshold of the inspection coefficient. When the output result is 0, no inspection is arranged. When the output result is 1, idle maintenance personnel are arranged to inspect the branch circuit once a month. When the output result is 2, idle maintenance personnel are arranged to inspect the branch circuit once a week. When the output result is 3, idle maintenance personnel are arranged to inspect the branch circuit twice a week.

[0092] In summary, the smart grid fault warning and recovery system proposed in the present invention effectively solves the problems of relatively lagging traditional power grid fault monitoring methods, maintenance personnel dispatch and inspection arrangements relying on manual decision-making, etc. through real-time fault monitoring, intelligent maintenance dispatch, optimized patrol arrangements, real-time grasp of maintenance personnel status, in-depth data analysis, and improved system integration and compatibility. It significantly improves the stability and reliability of the power system and reduces maintenance costs and manpower waste.

[0093] In the description of the 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.

[0094] The above embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, other embodiments obtained by those skilled in the art without creative work shall all fall within the scope of protection of the present invention.

Claims

1. A smart grid fault warning and recovery system for electric power, characterized in that: Including fault monitoring module, maintenance dispatch module, and inspection arrangement module. The fault monitoring module is used to perform fault monitoring on the power grid branch circuit; The maintenance dispatch module is used to dispatch idle workers to perform maintenance; The inspection arrangement module is used to arrange inspections for different branch circuits.

2. The smart grid fault early warning and recovery system for electric power according to claim 1, characterized in that: The fault monitoring module includes a plurality of power meters, a data processing unit and a mobile terminal; The multiple power meters are arranged in i branch circuits, and are used to monitor the real-time load power of the branch circuits at regular intervals, and then transmit the real-time load power data of the branch circuits monitored at each timing point to the data processing unit, and each timing point is a half-hour time interval for the power meter to upload data; The data processing unit is wirelessly connected to the multiple power meters, and is used to divide a day into four cycles; and is used to calculate the fluctuation coefficient within the cycle of the branch circuit according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point after receiving the real-time load power data of the branch circuit; and is used to calculate the fluctuation value of each timing monitoring point of the branch circuit according to the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit; And used to count the number of timing monitoring points of the branch circuit that meet the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within a period according to the calculated fluctuation value of each timing monitoring point of the branch circuit; And the abnormality degree coefficient of the branch circuit is calculated based on the quantity data of the moment when the fluctuation value of each sampling point of the branch circuit within the cycle is greater than the average value of the fluctuation coefficient, the fluctuation coefficient of the branch circuit within the cycle and the fluctuation value of each timing monitoring point; and is used to determine that an abnormality exists in the corresponding branch circuit when it is detected that the abnormality degree coefficient of any branch circuit is greater than a preset abnormality degree coefficient threshold; and used to generate corresponding branch circuit abnormality information when it is determined that any corresponding branch circuit has an abnormality, and then transmit the corresponding branch circuit abnormality information to the mobile terminal; The mobile terminal is in communication connection with the data processing unit, and is used for displaying the branch circuit abnormality information after receiving the corresponding branch circuit abnormality information.

3. The smart grid fault early warning and recovery system for electric power according to claim 2, characterized in that: The calculation formula of the fluctuation coefficient within the cycle of the branch circuit is: Among them, γ i is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit, P rz It is the theoretical power data of the branch circuit within the cycle measured in advance, and its unit is W, P ei_i It is the real-time load power data of each monitoring point within the cycle of the branch circuit, and its unit is W.

4. The smart grid fault early warning and recovery system for electric power according to claim 3, characterized in that: The formula for calculating the fluctuation value of each timing monitoring point based on the theoretical power data within the cycle of the branch circuit measured in advance and the real-time load power data of each timing monitoring point within the cycle of the branch circuit is: in, is the fluctuation value of each timing monitoring point, P rz It is the theoretical power data of the branch circuit within the cycle measured in advance, and its unit is W, P ei_i It is the real-time load power data of each monitoring point within the cycle of the branch circuit, and its unit is W.

5. The smart grid fault early warning and recovery system for electric power according to claim 4, characterized in that: The method of counting the number of timing monitoring points in the branch circuit that satisfy the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within a period according to the calculated fluctuation value of each timing monitoring point is: Wherein, k1 is the number of timing monitoring points in the branch circuit that satisfy the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the cycle according to the calculated fluctuation value of each timing monitoring point. is the fluctuation value of each timing monitoring point of the branch circuit, γ i It is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit.

6. The smart grid fault early warning and recovery system for electric power according to claim 5, characterized in that: The calculation formula of the abnormality degree coefficient of the branch circuit is: Among them, G j is the abnormality coefficient of the branch circuit, i is the number of timing monitoring points, is the fluctuation value of each timing monitoring point, k1 is the number of timing monitoring points in the branch circuit that meet the fluctuation value of each timing monitoring point greater than the average value of the fluctuation coefficient within the cycle according to the calculated fluctuation value of each timing monitoring point, γ i It is the fluctuation coefficient of each monitoring point within the cycle of the branch circuit.

7. The smart grid fault early warning and recovery system for electric power according to claim 2, characterized in that: The maintenance dispatch module includes a control center module, The data processing unit is used to generate abnormal information of the branch circuit when it is determined that any branch circuit has an abnormality, and then transmit the abnormal information of the branch circuit to the control center module; The mobile terminal is in communication connection with the control center module, and is used to distinguish the working status of the maintenance personnel into an offline state, a busy state, and an idle state; and is used to upload the working status data of the maintenance personnel; and is used to locate the location information of the maintenance personnel in real time, and then upload the location information of the maintenance personnel in real time to the control center module; and is used to update the working status of the maintenance personnel to a busy state after receiving the dispatch information and the abnormal branch line circuit location information; The control center module is electrically connected to the data processing unit, and is used to update the work status and location information of the maintenance personnel uploaded by the mobile terminal module in real time; and is used to obtain the abnormal branch circuit location information according to the preset branch circuit location information after receiving the branch circuit abnormality information; and is used to compare the distance between the location information of all idle maintenance personnel and the abnormal branch circuit location information to confirm the idle maintenance personnel to be dispatched; and is used to generate dispatch information after confirming the dispatched idle maintenance personnel, and then transmit the dispatch information and the abnormal branch circuit location information to the mobile terminal of the maintenance personnel.

8. The smart grid fault early warning and recovery system for electric power according to claim 7, characterized in that: The inspection arrangement module includes a fault statistics unit and a data analysis module. The data processing unit is used to generate corresponding branch circuit abnormality information when it is determined that there is an abnormality in a branch circuit, and then transmit the corresponding branch circuit abnormality information and abnormality degree coefficient to the fault statistics unit; The fault statistics unit is connected to the data processing unit network, and is used to store the corresponding branch circuit abnormality information and abnormality degree coefficient after receiving the corresponding branch circuit abnormality information and abnormality degree coefficient; The data analysis module is respectively connected to the fault statistics unit module and the control center module network, and is used to obtain the total data of the number of branch line circuit abnormalities and the abnormality degree index in the fault statistics unit; and used to calculate the inspection coefficient of the branch circuit according to the total data of the number of branch circuit anomalies and the abnormality index; and used to compare the inspection coefficient of the branch circuit with a preset inspection coefficient threshold range; and used to generate an inspection arrangement plan for the branch circuit according to the comparison result, and then transmit the inspection arrangement plan for the branch circuit to the control center module; The control center module is used to, upon receiving the inspection arrangement information of the branch circuit, prompt the user to arrange maintenance personnel to inspect the abnormal branch circuit according to the inspection arrangement information of the branch circuit.

9. The smart grid fault early warning and recovery system for electric power according to claim 8, characterized in that: The calculation formula of the inspection coefficient of the branch circuit is: Where X is the inspection coefficient of the branch circuit, ω1 and ω2 are weight coefficients, and ω1+ω2=1, m is the number of branch circuit anomalies, G j is the abnormality degree coefficient of the branch circuit.

10. The smart grid fault early warning and recovery system for electric power according to claim 9, characterized in that: The method of comparing the inspection coefficient of the branch circuit with the preset inspection coefficient threshold range is: Among them, X is the inspection coefficient of the branch circuit, X1 is the preset first threshold of the inspection coefficient, X2 is the preset second threshold of the inspection coefficient, and X3 is the preset third threshold of the inspection coefficient. When the output result is 0, no inspection is arranged. When the output result is 1, idle maintenance personnel are arranged to inspect the branch circuit once a month. When the output result is 2, idle maintenance personnel are arranged to inspect the branch circuit once a week. When the output result is 3, idle maintenance personnel are arranged to inspect the branch circuit twice a week.

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