CN112308250A - Distribution network emergency repair scheduling system and method - Google Patents
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Abstract
The application provides a distribution network emergency repair scheduling system and a distribution network emergency repair scheduling method, wherein the system comprises the following steps: the distribution network running state monitoring module is used for acquiring distribution network historical state data and distribution network historical fault data; the equipment asset management module is used for acquiring the data of the distribution network equipment; the enterprise standing book module is used for acquiring personnel data of a team; the vehicle management module is used for acquiring emergency vehicle data; the voice calling module is used for acquiring fault repair data; the prediction analysis module is used for acquiring an emergency repair analysis result; the man-machine interaction module is used for displaying an emergency repair analysis result and judging a distribution network fault; and the emergency repair task management module is used for generating an emergency repair task according to the distribution network fault and sending the emergency repair task to the man-machine interaction module so that a scheduling commander can command and schedule the emergency repair task according to the emergency repair analysis result.
Description
Technical Field
The application relates to the technical field of data analysis, in particular to a distribution network emergency repair scheduling system and method.
Background
The electric power fault first-aid repair management relates to a plurality of service fields and business applications in a power grid enterprise, the management difficulty is high, and important information systems such as distribution networks, power distribution and scheduling closely related to electric power first-aid repair work are distributed, deployed and independently applied due to strong professional and high information safety requirements. When a fault occurs, emergency commander personnel generally cannot acquire and regulate related fault information in time, so that reasonable resource allocation cannot be carried out, the overall management level of distribution network fault emergency repair work and the emergency repair work efficiency are not high, the power failure time of a user is prolonged, and the power selling loss of a power grid enterprise is increased. Therefore, how to monitor and analyze whether the distribution network fails is crucial.
In the prior art, a traditional data analysis method is generally adopted, certain condition assumptions are made on the distribution network problem to be solved, and a data sample is obtained. And according to the condition hypotheses, checking the data sample to judge whether the distribution network has a fault problem and the like. However, although the prior art can effectively simplify the calculation, the original hypothesis cannot be denied by the result of the test, so the accuracy of the analysis depends on the reasonableness of the hypothesis, and the accuracy is low.
Disclosure of Invention
The application provides a distribution network emergency repair scheduling system and a distribution network emergency repair scheduling method, which aim to solve the problem of low accuracy in the prior art.
In order to solve the technical problem, the embodiment of the application discloses the following technical scheme:
in a first aspect, the present application provides a distribution network emergency repair scheduling system, which includes:
the distribution network running state monitoring module is used for acquiring distribution network historical state data and distribution network historical fault data;
the equipment asset management module is used for acquiring the data of the distribution network equipment;
the enterprise standing book module is used for acquiring personnel data of a team;
the vehicle management module is used for acquiring emergency vehicle data;
the voice calling module is used for acquiring fault repair data;
the prediction analysis module is used for acquiring an emergency repair analysis result according to the distribution network historical state data, the distribution network historical fault data, the distribution network equipment data, the team personnel data, the emergency vehicle data and the fault repair data;
the human-computer interaction module is used for displaying the emergency repair analysis result and judging the distribution network fault;
and the emergency repair task management module is used for generating an emergency repair task according to the distribution network fault and sending the emergency repair task to the man-machine interaction module so that a scheduling commander can command and schedule the emergency repair task according to the emergency repair analysis result.
Optionally, the prediction analysis module includes:
the fault prediction positioning model base comprises a plurality of fault prediction positioning models and is used for predicting and positioning the distribution network fault;
the system comprises a fault first-aid repair material allocation model base, a dispatching commander and a distribution management center, wherein the fault first-aid repair material allocation model base comprises a plurality of fault first-aid repair material allocation models and is used for predicting first-aid repair materials required by distribution network faults and recommending the first-aid repair materials to the dispatching commander;
the system comprises a fault emergency repair team personnel assignment model base, a scheduling commander and a network management system, wherein the fault emergency repair team personnel assignment model base comprises a plurality of fault emergency repair team personnel assignment models and is used for predicting an operation team corresponding to a professional type related to a distribution network fault and recommending the operation team to the scheduling commander;
and the fault repair model library comprises a plurality of fault repair models.
Optionally, the method for obtaining the fault prediction positioning model includes:
processing the distribution network state data, the distribution network historical fault data and the distribution network equipment data based on a big data analysis method to obtain a fault prediction positioning model;
the method for acquiring the fault first-aid repair material allocation model comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the emergency vehicle data based on a big data analysis method to obtain a fault first-aid repair material allocation model;
the method for acquiring the assignment model of the breakdown rush-repair team personnel comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the team personnel data based on a big data analysis method to obtain a fault emergency repair team personnel assignment model;
the method for acquiring the fault repairing model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the fault repair data based on a big data analysis method to obtain a fault repair model.
Optionally, the system further includes:
the distribution network GIS management module is used for acquiring distribution network line map information;
and the man-machine interaction module displays the progress of the emergency repair task in real time based on the distribution network line map information.
Optionally, the system further includes:
the voice and video communication module is connected with the human-computer interaction module and is used for communicating the dispatching commander with emergency repair personnel;
and the mobile emergency repair operation terminal is used for communicating emergency repair personnel and recording the progress of the emergency repair task.
In a second aspect, the application provides a distribution network emergency repair scheduling method, which is applied to a distribution network emergency repair scheduling system, and comprises the following steps:
obtain and join in marriage net emergency repair data, include: the system comprises a distribution network operation state monitoring module, a distribution network equipment asset management module, an enterprise ledger module, a vehicle management module, a voice call module and a data processing module, wherein the distribution network historical state data and the distribution network historical fault data are provided by the distribution network operation state monitoring module, the distribution network equipment data are provided by the equipment asset management module, the team personnel data are provided by the enterprise ledger module, the emergency vehicle data are provided by the vehicle management module, and the fault repair;
inputting the distribution network emergency repair data into a prediction analysis module to obtain an emergency repair analysis result;
displaying the emergency repair analysis result in a man-machine interaction module, and judging the distribution network fault;
generating an emergency repair task based on the distribution network fault;
and sending the emergency repair task to a man-machine interaction module, and commanding and scheduling the emergency repair task by scheduling commanders according to the emergency repair analysis result.
Optionally, the distribution network emergency repair data is input to the prediction analysis module to obtain an emergency repair analysis result, including:
processing the distribution network emergency repair data based on a prediction analysis module to obtain a fault prediction positioning model, a fault emergency repair material allocation model, a fault emergency repair team personnel allocation model and a fault repair reporting model;
predicting and positioning the distribution network fault based on the fault prediction positioning model;
predicting emergency repair materials required by the distribution network fault based on the fault emergency repair material allocation model;
and predicting the operation team corresponding to the distribution network fault based on the fault emergency repair team personnel assignment model.
Optionally, the method for obtaining the fault prediction positioning model includes:
processing the distribution network state data, the distribution network historical fault data and the distribution network equipment data based on a big data analysis method to obtain a fault prediction positioning model;
the method for acquiring the fault first-aid repair material allocation model comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the emergency vehicle data based on a big data analysis method to obtain a fault first-aid repair material allocation model;
the method for acquiring the assignment model of the breakdown rush-repair team personnel comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the team personnel data based on a big data analysis method to obtain a fault emergency repair team personnel assignment model;
the method for acquiring the fault repairing model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the fault repair data based on a big data analysis method to obtain a fault repair model.
Optionally, the method further includes:
acquiring distribution network line map information based on a distribution network GIS management module;
and sending the distribution network line map information to a human-computer interaction module, and displaying the progress of the emergency repair task in real time in a dynamic map mode.
Optionally, the method further includes:
dispatching commanders distribute the emergency repair tasks to emergency repair personnel according to the emergency repair analysis results, and communicate with the emergency repair personnel through a voice and video communication module;
emergency repair personnel communicate with each other through a mobile emergency repair operation terminal, and the progress of the emergency repair task is recorded.
Compared with the prior art, the beneficial effect of this application is:
the application provides a distribution network emergency repair scheduling system and a distribution network emergency repair scheduling method, wherein the scheduling method comprises the following steps: obtain and join in marriage net emergency repair data, include: the system comprises a distribution network operation state monitoring module, a distribution network equipment asset management module, an enterprise ledger module, a vehicle management module, a voice call module and a data processing module, wherein the distribution network historical state data and the distribution network historical fault data are provided by the distribution network operation state monitoring module, the distribution network equipment data are provided by the equipment asset management module, the team personnel data are provided by the enterprise ledger module, the emergency vehicle data are provided by the vehicle management module, and the fault repair; the distribution network emergency repair data are input to a prediction analysis module to obtain an emergency repair analysis result; displaying the emergency repair analysis result in a man-machine interaction module, and judging the distribution network fault; generating an emergency repair task based on the distribution network fault; and sending the emergency repair task to a man-machine interaction module, and commanding and scheduling the emergency repair task by scheduling commanders according to the emergency repair analysis result. The prediction analysis module analyzes the distribution network data by adopting a big data analysis method to obtain an emergency repair analysis result, eliminates the influence of subjective assumption of people in the traditional data analysis, can quickly find out problems in the complex distribution network data, and has higher accuracy.
Drawings
In order to more clearly explain the technical solution of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any creative effort.
Fig. 1 is an overall structure diagram of a distribution network emergency repair scheduling system provided in an embodiment of the present application;
fig. 2 is an overall flowchart of a distribution network emergency repair scheduling method provided in the embodiment of the present application.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The distribution network emergency repair dispatching system and method provided by the embodiment can be used for assisting commanding and dispatching personnel, on-site emergency repair personnel, background service personnel and the like in emergency operation, cooperatively developing distribution network emergency repair commanding and dispatching work, and comprehensively improving distribution network emergency repair operation efficiency.
Referring to fig. 1, an overall flowchart of a distribution network emergency repair scheduling system provided in the embodiment of the present application is shown.
Specifically, the system comprises a distribution network running state monitoring module, an equipment asset management module, an enterprise ledger module, a vehicle management module, a voice call module, a prediction analysis module, a human-computer interaction module and an emergency maintenance task management module.
The distribution network operation state monitoring module is used for acquiring distribution network historical state data and distribution network historical fault data.
Specifically, the distribution network running state monitoring module is used for monitoring the running state of a distribution network, and the monitoring data mainly comprise micro meteorological data such as voltage and current, power factors, the on-off state of a disconnecting switch breaker, temperature and humidity of a distribution network line, a station transformer and a household electric meter.
The equipment asset management module is used for acquiring data of distribution network equipment, and specifically is used for managing assets such as related equipment, tools and appliances for operation and maintenance of a distribution network, and the main parameters include asset types, specification models and key parameters of specific assets.
The enterprise standing book module is used for acquiring team personnel data, and particularly, the enterprise standing book module is mainly used for managing personnel information, organization information, team information and the like.
The vehicle management module is used for acquiring emergency vehicle data, specifically, the vehicle management module is mainly used for managing emergency platform terminal emergency repair vehicles, and vehicles of different types are suitable for different emergency repair tasks.
The voice calling module is used for acquiring fault repair data and is mainly responsible for customer fault repair, customer complaint processing and the like.
The prediction analysis module is used for acquiring an emergency repair analysis result according to the distribution network historical state data, the distribution network historical fault data, the distribution network equipment data, the team personnel data, the emergency vehicle data and the fault repair data.
And the man-machine interaction module is used for displaying the emergency repair analysis result and judging the distribution network fault. Specifically, the command dispatcher comprehensively judges the fault according to the sound and flicker fault information prompted by the human-computer interaction module and in combination with other display information.
The emergency repair task management module is used for generating an emergency repair task according to the distribution network fault, sending the emergency repair task to the man-machine interaction module, and commanding and scheduling the emergency repair task by scheduling commanders through the man-machine interaction module according to the emergency repair analysis result.
Specifically, the command dispatcher assigns the operation team and allocates emergency materials according to the operation team information, vehicle information, tools and appliances and other information which is automatically pushed after the model analysis is carried out by the prediction analysis module.
In one embodiment, the predictive analysis module includes:
and the fault prediction positioning model library comprises a plurality of fault prediction positioning models and is used for predicting and positioning the distribution network fault.
The system comprises a fault first-aid repair material allocation model base, wherein the fault first-aid repair material allocation model base comprises a plurality of fault first-aid repair material allocation models and is used for predicting first-aid repair materials required by distribution network faults and recommending the first-aid repair materials to dispatching commanders.
The system comprises a fault emergency repair team personnel assignment model base, wherein the fault emergency repair team personnel assignment model base comprises a plurality of fault emergency repair team personnel assignment models and is used for predicting operation teams corresponding to professional types related to distribution network faults and recommending the operation teams to a scheduling commander.
And the fault repair model library comprises a plurality of fault repair models. The fault repair reporting model can prevent the current fault from being repaired by multiple heads and improve the service quality of customers.
The prediction analysis module mainly manages the emergency repair task, tracks the task execution process, ensures the whole process controllability of the emergency repair operation and ensures the closed loop of the task.
In one embodiment, the method for obtaining the fault prediction positioning model comprises the following steps:
and processing the distribution network state data, the distribution network historical fault data and the distribution network equipment data based on a big data analysis method to obtain a fault prediction positioning model.
The method for acquiring the fault first-aid repair material allocation model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the emergency vehicle data based on a big data analysis method to obtain a fault first-aid repair material allocation model.
The method for acquiring the assignment model of the breakdown rush-repair team personnel comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the team personnel data based on a big data analysis method to obtain a fault emergency repair team personnel assignment model.
The method for acquiring the fault repair model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the fault repair data based on a big data analysis method to obtain a fault repair model.
In one embodiment, the scheduling system further comprises:
and the distribution network GIS management module is used for acquiring distribution network line map information, and particularly mainly managing distribution network layer information displayed in a map.
The man-machine interaction module displays the progress of the emergency repair task in real time based on map information of the distribution network line, and specifically displays the progress in a map mode uniformly according to positions of different information. The command dispatcher can make a voice video call with one or more people in the map.
In one embodiment, the scheduling system further comprises:
and the voice video communication module is connected with the man-machine interaction module and is used for communicating the dispatching commander with the emergency repair personnel. Specifically, the dispatching commander contacts related personnel of the rush-repair operation team through the voice and video communication module and issues an operation task notification.
And the mobile emergency repair operation terminal is used for communicating emergency repair personnel and recording the progress of the emergency repair task. Specifically, after receiving the notification, the operating personnel get the mobile emergency repair operating terminal, the emergency repair vehicle and other emergency repair materials, arrive at the emergency repair site according to the fault position, and the on-site emergency repair personnel can also carry out voice and video conversation through the mobile emergency repair operating terminal and display the voice and video conversation in the man-machine interaction module.
The embodiment of the application also provides a distribution network emergency repair scheduling method, as shown in fig. 2, the method is applied to a distribution network emergency repair scheduling system, and the method comprises the following steps:
s1, acquiring distribution network emergency repair data, including: the system comprises a distribution network operation state monitoring module, a distribution network equipment asset management module, an enterprise ledger module, a vehicle management module, a voice call module and a data processing module, wherein the distribution network historical state data and the distribution network historical fault data are provided by the distribution network operation state monitoring module, the distribution network equipment data are provided by the equipment asset management module, the team personnel data are provided by the enterprise ledger module, the emergency vehicle data are provided by the vehicle management module, and the fault repair;
s2, inputting the distribution network emergency repair data to a prediction analysis module to obtain an emergency repair analysis result;
s3, displaying the emergency repair analysis result in a man-machine interaction module, and judging a distribution network fault;
s4, generating an emergency repair task based on the distribution network fault;
and S5, sending the emergency repair task to a man-machine interaction module, and commanding and scheduling the emergency repair task by scheduling commanders according to the emergency repair analysis result.
In one embodiment, step S2 is specifically:
processing distribution network emergency repair data based on a prediction analysis module to obtain a fault prediction positioning model, a fault emergency repair material allocation model, a fault emergency repair team personnel allocation model and a fault repair reporting model;
predicting and positioning the distribution network fault based on the fault prediction positioning model;
predicting emergency repair materials required by the distribution network fault based on the fault emergency repair material allocation model;
and predicting the operation team corresponding to the distribution network fault based on the fault emergency repair team personnel assignment model.
Specifically, the method for acquiring the fault prediction positioning model comprises the following steps:
and processing the distribution network state data, the distribution network historical fault data and the distribution network equipment data based on a big data analysis method to obtain a fault prediction positioning model.
The method for acquiring the fault first-aid repair material allocation model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the emergency vehicle data based on a big data analysis method to obtain a fault first-aid repair material allocation model.
The method for acquiring the assignment model of the breakdown rush-repair team personnel comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the team personnel data based on a big data analysis method to obtain a fault emergency repair team personnel assignment model.
The method for acquiring the fault repair model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the fault repair data based on a big data analysis method to obtain a fault repair model.
In one embodiment, further comprising:
and acquiring distribution network line map information based on the distribution network GIS management module.
And sending the map information of the distribution network line to a human-computer interaction module, and displaying the progress of the emergency repair task in real time in a dynamic map mode.
In one embodiment, further comprising:
and dispatching commanders distribute emergency repair tasks to emergency repair personnel according to the emergency repair analysis results and communicate with the emergency repair personnel through the voice and video communication module.
Specifically, the background dispatching commander uses the human-computer interaction module to confirm distribution network fault, emergency repair material allocation and emergency repair team assignment, and monitors and displays real-time progress of emergency repair tasks and cooperation and interaction between emergency repair personnel on site.
The emergency repair personnel can also communicate with each other by moving the emergency repair operation terminal, and record the progress of the emergency repair task.
It should be noted that the mobile emergency repair operation terminal is provided with a mobile distribution network emergency repair app, which is carried by field operation personnel and mainly completes the process recording, control and cooperative operation of the whole emergency repair task; the electric power customer can also be through installing at the cell-phone end and moving net and salvageing app, knows the trouble in real time and salvagees the progress, can also advance the interdynamic with salvage personnel, and supplementary salvage personnel solve the on-the-spot problem.
According to the scheduling method, functions of rapid transmission and real-time sharing of fault information and emergency repair information, reasonable resource allocation in the emergency repair process and the like are achieved by utilizing a big data prediction analysis technology. The distribution network emergency repair business process is optimized on the whole, and the efficiency of each link of occurrence, reporting, diagnosis, positioning, isolation and repair of faults is improved. By the method, related emergency repair personnel are assisted to carry out emergency repair work in order, the working quality of emergency repair service personnel and the response efficiency of fault repair can be effectively improved, the emergency repair cost is reduced, and the power restoration time is shortened. Therefore, the production targets of reducing the power failure loss of users, improving the customer satisfaction, reducing the power selling loss of power grid enterprises and improving the power supply reliability of power grids are achieved.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The above description is only for the specific embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
It is noted that, in this specification, relational terms such as "first" and "second," and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a circuit structure, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such circuit structure, article, or apparatus. The term "comprising" a defined element does not, without further limitation, exclude the presence of other like elements in a circuit structure, article, or device that comprises the element.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims. The above-described embodiments of the present application do not limit the scope of the present application.
Claims (10)
1. The utility model provides a join in marriage net emergency repair dispatch system which characterized in that, the system includes:
the distribution network running state monitoring module is used for acquiring distribution network historical state data and distribution network historical fault data;
the equipment asset management module is used for acquiring the data of the distribution network equipment;
the enterprise standing book module is used for acquiring personnel data of a team;
the vehicle management module is used for acquiring emergency vehicle data;
the voice calling module is used for acquiring fault repair data;
the prediction analysis module is used for acquiring an emergency repair analysis result according to the distribution network historical state data, the distribution network historical fault data, the distribution network equipment data, the team personnel data, the emergency vehicle data and the fault repair data;
the human-computer interaction module is used for displaying the emergency repair analysis result and judging the distribution network fault;
and the emergency repair task management module is used for generating an emergency repair task according to the distribution network fault and sending the emergency repair task to the man-machine interaction module so that a scheduling commander can command and schedule the emergency repair task according to the emergency repair analysis result.
2. The scheduling system of claim 1 wherein the predictive analysis module comprises:
the fault prediction positioning model base comprises a plurality of fault prediction positioning models and is used for predicting and positioning the distribution network fault;
the system comprises a fault first-aid repair material allocation model base, a dispatching commander and a distribution management center, wherein the fault first-aid repair material allocation model base comprises a plurality of fault first-aid repair material allocation models and is used for predicting first-aid repair materials required by distribution network faults and recommending the first-aid repair materials to the dispatching commander;
the system comprises a fault emergency repair team personnel assignment model base, a scheduling commander and a network management system, wherein the fault emergency repair team personnel assignment model base comprises a plurality of fault emergency repair team personnel assignment models and is used for predicting an operation team corresponding to a professional type related to a distribution network fault and recommending the operation team to the scheduling commander;
and the fault repair model library comprises a plurality of fault repair models.
3. The dispatching system of claim 2, wherein the method for obtaining the fault prediction positioning model comprises:
processing the distribution network state data, the distribution network historical fault data and the distribution network equipment data based on a big data analysis method to obtain a fault prediction positioning model;
the method for acquiring the fault first-aid repair material allocation model comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the emergency vehicle data based on a big data analysis method to obtain a fault first-aid repair material allocation model;
the method for acquiring the assignment model of the breakdown rush-repair team personnel comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the team personnel data based on a big data analysis method to obtain a fault emergency repair team personnel assignment model;
the method for acquiring the fault repairing model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the fault repair data based on a big data analysis method to obtain a fault repair model.
4. The scheduling system of claim 1 wherein the system further comprises:
the distribution network GIS management module is used for acquiring distribution network line map information;
and the man-machine interaction module displays the progress of the emergency repair task in real time based on the distribution network line map information.
5. The scheduling system of claim 1 wherein the system further comprises:
the voice and video communication module is connected with the human-computer interaction module and is used for communicating the dispatching commander with emergency repair personnel;
and the mobile emergency repair operation terminal is used for communicating emergency repair personnel and recording the progress of the emergency repair task.
6. A distribution network emergency repair scheduling method is characterized in that the method is applied to a distribution network emergency repair scheduling system, and the method comprises the following steps:
obtain and join in marriage net emergency repair data, include: the system comprises a distribution network operation state monitoring module, a distribution network equipment asset management module, an enterprise ledger module, a vehicle management module, a voice call module and a data processing module, wherein the distribution network historical state data and the distribution network historical fault data are provided by the distribution network operation state monitoring module, the distribution network equipment data are provided by the equipment asset management module, the team personnel data are provided by the enterprise ledger module, the emergency vehicle data are provided by the vehicle management module, and the fault repair;
inputting the distribution network emergency repair data into a prediction analysis module to obtain an emergency repair analysis result;
displaying the emergency repair analysis result in a man-machine interaction module, and judging the distribution network fault;
generating an emergency repair task based on the distribution network fault;
and sending the emergency repair task to a man-machine interaction module, and commanding and scheduling the emergency repair task by scheduling commanders according to the emergency repair analysis result.
7. The method of claim 6, wherein the inputting the distribution network emergency repair data into a predictive analysis module to obtain an emergency repair analysis result comprises:
processing the distribution network emergency repair data based on a prediction analysis module to obtain a fault prediction positioning model, a fault emergency repair material allocation model, a fault emergency repair team personnel allocation model and a fault repair reporting model;
predicting and positioning the distribution network fault based on the fault prediction positioning model;
predicting emergency repair materials required by the distribution network fault based on the fault emergency repair material allocation model;
and predicting the operation team corresponding to the distribution network fault based on the fault emergency repair team personnel assignment model.
8. The method according to claim 7, wherein the method for obtaining the fault prediction localization model comprises:
processing the distribution network state data, the distribution network historical fault data and the distribution network equipment data based on a big data analysis method to obtain a fault prediction positioning model;
the method for acquiring the fault first-aid repair material allocation model comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the emergency vehicle data based on a big data analysis method to obtain a fault first-aid repair material allocation model;
the method for acquiring the assignment model of the breakdown rush-repair team personnel comprises the following steps:
processing the distribution network historical fault data, the distribution network equipment data and the team personnel data based on a big data analysis method to obtain a fault emergency repair team personnel assignment model;
the method for acquiring the fault repairing model comprises the following steps:
and processing the distribution network historical fault data, the distribution network equipment data and the fault repair data based on a big data analysis method to obtain a fault repair model.
9. The method of claim 6, further comprising:
acquiring distribution network line map information based on a distribution network GIS management module;
and sending the distribution network line map information to a human-computer interaction module, and displaying the progress of the emergency repair task in real time in a dynamic map mode.
10. The method of claim 6, further comprising:
dispatching commanders distribute the emergency repair tasks to emergency repair personnel according to the emergency repair analysis results, and communicate with the emergency repair personnel through a voice and video communication module;
emergency repair personnel communicate with each other through a mobile emergency repair operation terminal, and the progress of the emergency repair task is recorded.
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