CN113708493A - Cloud edge cooperation-based power distribution terminal operation and maintenance method and device and computer equipment - Google Patents

Cloud edge cooperation-based power distribution terminal operation and maintenance method and device and computer equipment Download PDF

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Publication number
CN113708493A
CN113708493A CN202110987962.0A CN202110987962A CN113708493A CN 113708493 A CN113708493 A CN 113708493A CN 202110987962 A CN202110987962 A CN 202110987962A CN 113708493 A CN113708493 A CN 113708493A
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China
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processed
information
power distribution
distribution terminal
target
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CN202110987962.0A
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CN113708493B (en
Inventor
侯祖锋
郭宗宝
郭文鑫
肖鸣晖
赵瑞锋
徐春华
梁苑
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Guangdong Power Grid Co Ltd
Zhuhai Power Supply Bureau of Guangdong Power Grid Co Ltd
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Guangdong Power Grid Co Ltd
Zhuhai Power Supply Bureau of Guangdong Power Grid Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
    • H02J13/00016—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/001—Methods to deal with contingencies, e.g. abnormalities, faults or failures
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
    • Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
    • Y04S40/124—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment using wired telecommunication networks or data transmission busses

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)
  • Supply And Distribution Of Alternating Current (AREA)

Abstract

The application relates to a power distribution terminal operation and maintenance method and device based on cloud edge cooperation, computer equipment and a storage medium. The method comprises the steps of obtaining information of equipment to be processed and operation information to be processed of a power distribution terminal to be processed from a data center, inputting a target state evaluation model, obtaining predicted fault information of the power distribution terminal to be processed, which is output by the target state evaluation model, determining a target power distribution terminal to be processed, which needs to be maintained, according to the predicted fault information, forming a corresponding list of power distribution terminals to be processed, and determining a target operation and maintenance strategy of the list, so that the target power distribution terminal to be processed is controlled to execute the target operation and maintenance strategy. Compare in traditional fortune dimension that carries out distribution terminal through the manual work, this scheme utilization high in the clouds server and state evaluation model carry out state detection and fortune dimension to the distribution terminal of edge side to the efficiency of distribution terminal fortune dimension has been improved.

Description

Cloud edge cooperation-based power distribution terminal operation and maintenance method and device and computer equipment
Technical Field
The application relates to the technical field of power distribution automation, in particular to a power distribution terminal operation and maintenance method and device based on cloud edge cooperation, computer equipment and a storage medium.
Background
Electric power is one of important resources for maintaining daily work and life of people, an important device in an electric power system is a power distribution terminal, and the power distribution terminal plays an important role in a power distribution automation system as a data acquisition device in the power distribution network automation system. Therefore, the operation and maintenance of the power distribution terminal is one of the most important tasks in the operation and management of the distribution network, and the operation and maintenance level of the power distribution terminal directly affects the operation reliability of the power distribution automation system.
The operation and maintenance mode of the target to the power distribution terminal is usually carried out through a personnel inspection mode, however, along with the comprehensive popularization of power distribution automation construction, the power distribution terminal has exhibited the characteristics of large quantity, wide distribution and the like, and the quantity and the coverage area are also rapidly increased. The operation and maintenance efficiency of the conventional operation and maintenance modes such as periodic inspection and field fault treatment by personnel is low, and the requirement of distribution automation operation and maintenance management and control is difficult to meet.
Therefore, the existing operation and maintenance method of the power distribution terminal has the defect of low efficiency.
Disclosure of Invention
In view of the foregoing, it is necessary to provide a power distribution terminal operation and maintenance method and apparatus based on cloud edge coordination, a computer device, and a storage medium, which can improve operation and maintenance efficiency.
A power distribution terminal operation and maintenance method based on cloud edge cooperation is applied to a cloud server, and comprises the following steps:
acquiring to-be-processed equipment information and to-be-processed operation information of a to-be-processed power distribution terminal from a data center; the data center is arranged on the cloud server and used for receiving and storing to-be-processed equipment information and to-be-processed operation information sent by the to-be-processed power distribution terminal;
inputting the information of the equipment to be processed and the information of the operation to be processed into a target state evaluation model, and acquiring the predicted fault information of the power distribution terminal to be processed, which is output by the target state evaluation model; the target state evaluation model is obtained by training based on a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information; each of the historical fault information corresponds to a set of sample device information and sample operational information;
and determining a target power distribution terminal to be processed which needs to be maintained according to the predicted fault information, forming a target power distribution terminal list to be processed, determining a target operation and maintenance strategy of the target power distribution terminal list to be processed, and controlling the target power distribution terminal to be processed in the target power distribution terminal list to execute the target operation and maintenance strategy.
In one embodiment, the method further comprises:
obtaining a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information corresponding to a sample power distribution terminal;
inputting the sample equipment information and the sample operation information into a state evaluation model to be trained, and acquiring sample prediction fault information output by the state evaluation model to be trained;
judging whether the similarity value of the sample prediction fault information and the historical fault information corresponding to the sample equipment information and the sample operation information is smaller than a preset similarity threshold value or not;
if not, adjusting the to-be-trained state evaluation model according to the similarity value, and returning to the step of inputting the sample equipment information and the sample operation information into the to-be-trained state evaluation model;
if so, ending the circulation, and taking the current state evaluation model to be trained as a target state evaluation model.
In one embodiment, after acquiring the information of the to-be-processed device and the information of the to-be-processed operation of the to-be-processed power distribution terminal from the data center, the method further includes:
acquiring historical patrol information corresponding to the power distribution terminal to be processed;
determining routing inspection parameters corresponding to the power distribution terminal to be processed according to the historical routing inspection information;
and detecting whether abnormal operation information exists in the to-be-processed operation information of the to-be-processed power distribution terminal according to the routing inspection parameters and a preset period, if so, generating corresponding alarm information and a target operation and maintenance strategy according to the abnormal operation information, and controlling the to-be-processed power distribution terminal to execute the target operation and maintenance strategy.
4. The method of claim 1, the predicted failure information comprising a predicted failure probability; the determining the target to-be-processed power distribution terminal to be maintained according to the predicted fault information to form a target to-be-processed power distribution terminal list, which comprises the following steps:
if the predicted fault probability is larger than or equal to a preset fault threshold value, determining that the to-be-processed power distribution terminal corresponding to the predicted fault information is a target to-be-processed power distribution terminal;
and generating a target to-be-processed power distribution terminal list according to the to-be-processed equipment information of the target to-be-processed power distribution terminal.
In one embodiment, the controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance policy includes:
controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to perform self-checking self-recovery and/or software upgrading so as to enable the target to-be-processed power distribution terminal to recover normal operation;
after the controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance strategy, the method further includes:
acquiring target to-be-processed equipment information and target to-be-processed operation information of the target to-be-processed power distribution terminal after the target operation and maintenance strategy is executed;
inputting the target to-be-processed equipment information and the target to-be-processed operation information into a target state evaluation model, and acquiring target prediction fault information output by the target state evaluation model;
and if the target prediction fault information has preset high-risk fault information, generating corresponding fault early warning information so that a worker can check the target power distribution terminal to be processed based on the fault early warning information.
In one embodiment, after obtaining the predicted fault information of the power distribution terminal to be processed output by the target state evaluation model, the method further includes:
according to the type of the to-be-processed equipment information of the to-be-processed power distribution terminal, clustering the predicted fault information to obtain a predicted fault information cluster corresponding to the to-be-processed equipment information;
and if the quantity of the same type of predicted fault information in the predicted fault information cluster is larger than a preset value, generating a corresponding operation and maintenance strategy according to the to-be-processed equipment information.
In one embodiment, the acquiring information of the to-be-processed device and the to-be-processed operation information of the to-be-processed power distribution terminal from the data center includes:
acquiring at least one of the equipment type, manufacturer, model, commissioning time, channel type and the power distribution area of the power distribution terminal to be processed from a data center as the information of the equipment to be processed;
and acquiring at least one of the operation state, the battery state, the communication state and the alarm information of the power distribution terminal to be processed from the data center as the operation information to be processed.
The utility model provides a distribution terminal fortune dimension device based on cloud limit is in coordination, is applied to high in the clouds server, the device includes:
the acquisition module is used for acquiring the information of the equipment to be processed and the operation information to be processed of the power distribution terminal to be processed from the data center; the data center is arranged on the cloud server and used for receiving and storing to-be-processed equipment information and to-be-processed operation information sent by the to-be-processed power distribution terminal;
the prediction module is used for inputting the information of the equipment to be processed and the information of the operation to be processed into a target state evaluation model and acquiring the predicted fault information of the power distribution terminal to be processed, which is output by the target state evaluation model; the target state evaluation model is obtained by training based on a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information; each of the historical fault information corresponds to a set of sample device information and sample operational information;
and the operation and maintenance module is used for determining a target to-be-processed power distribution terminal to be maintained according to the predicted fault information, forming a target to-be-processed power distribution terminal list, determining a target operation and maintenance strategy of the target to-be-processed power distribution terminal list, and controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance strategy.
A computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when executing the computer program.
A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
According to the power distribution terminal operation and maintenance method, device, computer equipment and storage medium based on cloud edge cooperation, the to-be-processed equipment information and the to-be-processed operation information of the to-be-processed power distribution terminal are obtained from the data center and input into the target state evaluation model, the predicted fault information of the to-be-processed power distribution terminal output by the target state evaluation model is obtained, the target to-be-processed power distribution terminal needing to be maintained is determined according to the predicted fault information, a corresponding to-be-processed distribution list terminal list is formed, the target operation and maintenance strategy of the list is determined, and therefore the target to-be-processed power distribution terminal is controlled to execute the target operation and maintenance strategy. Compare in traditional fortune dimension that carries out distribution terminal through the manual work, this scheme utilization high in the clouds server and state evaluation model carry out state detection and fortune dimension to the distribution terminal of edge side to the efficiency of distribution terminal fortune dimension has been improved.
Drawings
Fig. 1 is an application environment diagram of a power distribution terminal operation and maintenance method based on cloud edge coordination in an embodiment;
fig. 2 is a schematic flow chart of a power distribution terminal operation and maintenance method based on cloud edge coordination in an embodiment;
fig. 3 is a schematic flow chart of a power distribution terminal operation and maintenance method based on cloud-edge coordination in another embodiment;
fig. 4 is a block diagram illustrating a structure of a power distribution terminal operation and maintenance device based on cloud edge coordination in an embodiment;
FIG. 5 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The cloud edge coordination-based power distribution terminal operation and maintenance method can be applied to the application environment shown in fig. 1. The power distribution terminal 102 communicates with the cloud server 104 through a network. Distribution terminal 102 can set up in the distribution network system, distribution terminal 102 can store the data center in sending its data collection to cloud server 104, can also be provided with operation and maintenance application and distribution network main website application in cloud server 104, thereby cloud server 104 is based on foretell application, according to the relevant information of distribution terminal 102 who stores in the data center, carry out the state evaluation to distribution terminal 102, and cloud server 104 can also be according to the long-range operation and maintenance that carries out of result to corresponding distribution terminal 102 of state evaluation, thereby realize the collaborative distribution terminal operation and maintenance of cloud limit. The cloud server 104 may be implemented by an independent server or a server cluster composed of a plurality of servers.
In an embodiment, as shown in fig. 2, a power distribution terminal operation and maintenance method based on cloud-edge coordination is provided, which is described by taking the method applied to the cloud server in fig. 1 as an example, and includes the following steps:
step S202, acquiring to-be-processed equipment information and to-be-processed operation information of the to-be-processed power distribution terminal from a data center; the data center is arranged on the cloud server and used for receiving and storing the to-be-processed equipment information and the to-be-processed operation information sent by the to-be-processed power distribution terminal.
The data center may be a database disposed in the cloud server 104, and may be configured to store related data sent by the power distribution terminal 102. The cloud server 104 may be disposed in a cloud and communicate with the plurality of power distribution terminals 102 on the edge side, for example, the power distribution terminals 102 may send acquired data to a data center in the cloud server 104, and the data sent by the power distribution terminals 102 may be to-be-processed device information and to-be-processed operation information of the power distribution terminals 102 themselves. The cloud server 104 may obtain information of the to-be-processed device and information of the to-be-processed operation of the to-be-processed power distribution terminal from the data center. For example, the intelligent operation and maintenance application and the distribution network master station application in the cloud server 104 both obtain the information of the device to be processed and the operation information to be processed from the data center, and the intelligent operation and maintenance application and the distribution network master station application may also issue respective control instructions to the power distribution terminal 102.
The information of the to-be-processed devices and the information of the to-be-processed operations of the power distribution terminal 102 stored in the data center of the cloud server 104 may be various. For example, in one embodiment, acquiring the to-be-processed device information and the to-be-processed operation information of the to-be-processed power distribution terminal from the data center includes: acquiring at least one of the equipment type, manufacturer, model, commissioning time, channel type and belonging power distribution area of the power distribution terminal to be processed from the data center as information of the equipment to be processed; and acquiring at least one of the operation state, the battery state, the communication state and the alarm information of the power distribution terminal to be processed from the data center as the operation information to be processed. In this embodiment, the information of the to-be-processed device sent by the power distribution terminal 102 to the data center may include, but is not limited to, static information such as a device type, a manufacturer, a model, commissioning time, a channel type, and a belonging area; the to-be-processed operation information can include, but is not limited to, real-time information such as an operation state, a battery state, a communication state, alarm information and the like; the data transmitted from the power distribution terminal 102 to the data center may further include history information such as an operation record, a patrol record, and a maintenance record of the power distribution terminal 102. The data center of the cloud server 104 may receive and store the above information, so that the cloud server 104 may perform operation and maintenance on the power distribution terminal 102 based on the relevant data in the data center.
In addition, it should be noted that the cloud server 104 may be configured with corresponding distribution network operation managers, and the distribution network operation managers may perform the operation of the power distribution terminal and the management of the distribution network master station by accessing the cloud server 104 in the cloud platform.
Step S204, inputting the information of the equipment to be processed and the operation information to be processed into a target state evaluation model, and acquiring the predicted fault information of the power distribution terminal to be processed, which is output by the target state evaluation model; the target state evaluation model is obtained by training based on a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information; each historical failure information corresponds to a set of sample device information and sample run information.
The target state evaluation model may be a neural network model for evaluating the health state and the operating state of the power distribution terminal 102, and the target state evaluation model may be trained based on a plurality of sample device information, a plurality of sample operating information, and a plurality of historical fault information of a plurality of power distribution terminals 102, and each historical fault information corresponds to a set of sample device information and sample operating information. Cloud server 104 may utilize the target state model to predict the operational and health status of power distribution terminal 102. For example, the cloud server 104 may input the acquired to-be-processed device information and to-be-processed operation information into a target state evaluation model, and the target state evaluation model may output predicted fault information of the to-be-processed power distribution terminal 102 corresponding to the device information and the operation information of the input model, where the predicted fault information may include a predicted fault type that may occur in the power distribution terminal 102 and an occurrence probability of the predicted fault type. The target state evaluation model may be trained by mining an association relationship between sample equipment information, sample operation information, and historical fault information. For example, when a fault occurs, the device information and the operation information of the power distribution terminal 102 are necessarily in a certain state, and the cloud server 104 may mine an association relationship therebetween; the historical fault information can include various types of faults, the cloud server 104 can perform statistical processing on historical data of the power distribution terminal, identify the problems that the power distribution terminal is not refreshed for a long time, frequently shakes in remote signaling, is continuously offline for a long time, frequently drops, fails in remote control and the like, and provide data support for judging the operation state of the terminal; therefore, the cloud server 104 can utilize a data mining algorithm to deeply mine the association relationship between the historical information of the power distribution terminal fault and the operation state information of the power distribution terminal 102, the equipment information of the power distribution terminal 102 and the information such as measurement of no refreshing for a long time, frequent jitter of remote signaling, continuous offline for a long time, frequent disconnection, remote control failure and the like, and provide support for the evaluation of the health state of the power distribution terminal.
Step S206, determining a target power distribution terminal to be processed which needs to be maintained according to the predicted fault information, forming a target power distribution terminal to be processed list, determining a target operation and maintenance strategy of the target power distribution terminal to be processed list, and controlling the target power distribution terminal to be processed in the target power distribution terminal to be processed list to execute the target operation and maintenance strategy.
The predicted fault information may be fault information that may occur in the power distribution terminal 102 to be processed and output by the target state evaluation model. The cloud server 104 may determine, based on the predicted fault information, target to-be-processed power distribution terminals 102 that need to be maintained, and form a corresponding target to-be-processed power distribution terminal list. For example, the predicted fault information of each power distribution terminal 102 does not necessarily represent that the power distribution terminal 102 fails, the cloud server 104 may use the power distribution terminal 102 that may fail as the target to-be-processed power distribution terminal 102 and add the target to-be-processed power distribution terminal list, and the cloud server 104 may further determine a corresponding target operation and maintenance policy based on the predicted fault information of each target to-be-processed power distribution terminal 102 in the target to-be-processed power distribution terminal list, and the cloud server 104 may remotely control the target to-be-processed power distribution terminal 102 in the target to-be-processed power distribution terminal list to execute the target operation and maintenance policy, so that the cloud-side cooperative operation and maintenance of the power distribution terminal 102 on the edge side on the cloud side may be implemented.
According to the power distribution terminal operation and maintenance method based on cloud edge cooperation, the to-be-processed equipment information and the to-be-processed operation information of the to-be-processed power distribution terminal are obtained from the data center and input into the target state evaluation model, the predicted fault information of the to-be-processed power distribution terminal output by the target state evaluation model is obtained, the target to-be-processed power distribution terminal needing to be maintained is determined according to the predicted fault information, a corresponding to-be-processed distribution list terminal list is formed, the target operation and maintenance strategy of the list is determined, and therefore the target to-be-processed power distribution terminal is controlled to execute the target operation and maintenance strategy. Compare in traditional fortune dimension that carries out distribution terminal through the manual work, this scheme utilization high in the clouds server and state evaluation model carry out state detection and fortune dimension to the distribution terminal of edge side to the efficiency of distribution terminal fortune dimension has been improved.
In one embodiment, further comprising: obtaining a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information corresponding to a sample power distribution terminal; inputting sample equipment information and sample operation information into a to-be-trained state evaluation model, and acquiring sample prediction fault information output by the to-be-trained state evaluation model; judging whether the similarity value of the sample prediction fault information and historical fault information corresponding to the sample equipment information and the sample operation information is smaller than a preset similarity threshold value or not; if not, adjusting the to-be-trained state evaluation model according to the similarity value, and returning to the step of inputting the sample equipment information and the sample operation information into the to-be-trained state evaluation model; if so, ending the circulation, and taking the current state evaluation model to be trained as the target state evaluation model.
In this embodiment, the cloud server 104 may train the state evaluation model to be trained to obtain a target state evaluation model. The cloud server 104 may obtain sample device information, sample operation information, and historical fault information of a plurality of sample power distribution terminals participating in training, so as to obtain a plurality of sample device information, a plurality of sample operation information, and a plurality of historical fault information, and each historical fault information corresponds to a set of sample device information and sample operation information. The cloud server 104 may input one sample device information and sample operation information into the to-be-trained state evaluation model, the to-be-trained state evaluation model may output and output sample predicted fault information predicted based on the sample device information and the sample operation information, the cloud server 104 may obtain the sample predicted fault information, and the cloud server 104 may determine a similarity value between the sample predicted fault information and historical fault information corresponding to a set of sample device information and sample operation information of the to-be-trained state evaluation model input, and if the similarity value is greater than or equal to a preset similarity threshold, the cloud server 104 may determine that the to-be-trained state evaluation model is not trained, adjust relevant parameters in the to-be-trained state evaluation model according to the similarity value, and return to the step of inputting the sample device information and the sample operation information into the to-be-trained state evaluation model, the cloud server 104 may then train the next time the to-be-trained state evaluation model using the new set of sample device information and sample operation information. When the similarity value is smaller than the preset similarity threshold, the cloud server 104 may determine that the training is completed, end the training, and use the state evaluation model obtained by the current training as the target state evaluation model.
The device information, the operation information, and the historical fault information may include various types of information, and the cloud server 104 may mine a relationship therebetween through a training target state evaluation model. For example, the cloud server 104 may use a big data analysis algorithm to study association rules and evolution rules between the power distribution terminal device failure and information such as self running state parameters, commissioning time, manufacturers, models, channel types, measurement non-refreshing for a long time, frequent jitter of remote signaling, long-time continuous offline, frequent offline, and remote control failure, and establish a power distribution terminal health state evaluation and prediction model, that is, the state evaluation model, and use a machine learning and association analysis algorithm to adjust parameters and weights to obtain a target state evaluation model, so that the cloud server 104 may use the target state evaluation model to predict the failure information of the power distribution terminal 102.
Through this embodiment, the cloud server 104 can obtain the target state evaluation model based on a plurality of sample device information, a plurality of sample operation information and a plurality of historical fault information training, so that the cloud server 104 can utilize the target state evaluation model to perform operation and maintenance on the power distribution terminal 102 to be processed, and the operation and maintenance efficiency of the power distribution terminal is improved.
In one embodiment, after acquiring the information of the to-be-processed device and the information of the to-be-processed operation of the to-be-processed power distribution terminal from the data center, the method further includes: acquiring historical patrol information corresponding to a power distribution terminal to be processed; determining routing inspection parameters corresponding to the power distribution terminal to be processed according to the historical routing inspection information; and detecting whether abnormal operation information exists in the to-be-processed operation information of the to-be-processed power distribution terminal according to the routing inspection parameters and a preset period, if so, generating corresponding alarm information and a target operation and maintenance strategy according to the abnormal operation information, and controlling the to-be-processed power distribution terminal to execute the target operation and maintenance strategy.
In this embodiment, the cloud server 104 can automatically inspect the power distribution terminal 102 on the edge side, so as to perform daily monitoring on the state of the power distribution terminal 102 and perform early warning on abnormal states. The power distribution terminal 102 may determine a polling mode that needs to be performed on the power distribution terminal 102 based on the historical polling information, for example, the power distribution terminal 102 may obtain the historical polling information of the power distribution terminal 102 to be processed, and analyze the historical polling information to obtain polling parameters corresponding to the power distribution terminal 102 to be processed, so that the cloud server 104 may detect whether abnormal operation information, such as shutdown or offline, exists in the operation information of the power distribution terminal 102 to be processed according to the polling parameters and according to a preset period; if the abnormal operation information exists, the cloud server 104 may generate corresponding warning information and a target operation and maintenance policy according to the abnormal operation information, and control the abnormal power distribution terminal 102 to execute the target operation and maintenance policy.
For example, the cloud server 104 may learn a work record sheet of a previous manual inspection by using a machine learning method, extract an inspection work item, and generate an inspection parameter according to the extracted inspection work item, so that the cloud server 104 may periodically check the states of all power distribution terminals according to the inspection parameter, and perform early warning on an abnormal terminal. The cloud server 104 can monitor and daily operate and maintain the state of the power distribution terminal 102, the cloud server 104 monitors the operating state of the power distribution terminal in real time, and when the power distribution terminal is in abnormal conditions such as shutdown and disconnection, an alarm signal is sent, for example, alarm information is sent to the terminal of related staff, so that the related staff can process the alarm information. In addition, in some embodiments, the cloud server 104 may also perform batch setting and updating on the power distribution terminals 102 on the edge side. The cloud server 104 may perform batch parameter setting on the power distribution terminals at the cloud, and may also perform batch operation program updating on the power distribution terminals at the cloud. For example, when the plurality of power distribution terminals 102 are in the abnormal state, the cloud server 104 may perform parameter setting and program updating on the plurality of power distribution terminals 102 in batch, so that the power distribution terminals 102 recover to the normal operation state.
Through this embodiment, the cloud server 104 can regularly patrol and inspect the power distribution terminal 102 and early warn the abnormality, so that the operation and maintenance efficiency of the power distribution terminal 102 is improved.
In one embodiment, determining a target to-be-processed power distribution terminal to be maintained according to the predicted fault information, and forming a target to-be-processed power distribution terminal list includes: if the predicted fault probability is larger than or equal to the preset fault threshold value, determining the power distribution terminal to be processed corresponding to the predicted fault information as a target power distribution terminal to be processed; and generating a target to-be-processed power distribution terminal list according to the to-be-processed equipment information of the target to-be-processed power distribution terminal.
In this embodiment, the predicted fault information may include a predicted fault probability of the power distribution terminal 102 to be processed. Cloud server 104 may determine a list of target pending power distribution terminals based on the predicted failure probability. The cloud server 104 may detect whether a predicted failure probability output by the target state evaluation model is greater than or equal to a preset failure threshold, if so, the cloud server 104 may determine that the power distribution terminal to be processed 102 corresponding to the predicted failure probability is the target power distribution terminal to be processed 102, and there may be a plurality of target power distribution terminals to be processed 102, and the cloud server 104 may generate a target power distribution terminal to be processed list based on the information of the equipment to be processed of the target power distribution terminal to be processed 102, that is, the cloud server 104 adds the equipment identifier of the target power distribution terminal to be processed 102 to the target power distribution terminal to be processed list.
The target state evaluation model may include a health state evaluation and a fault prediction process for the power distribution terminal 102. For example, the cloud server 104 may evaluate the current health status of the power distribution terminal 102 according to the operating status parameters of the current power distribution terminal 102 and other relevant information by using a power distribution terminal health status evaluation model, i.e., the above-mentioned target status evaluation model. And predicting the probability of the fault and what kind of fault of the terminal in the future period by using a power distribution terminal health prediction model, namely the target state evaluation model. Therefore, the cloud server 104 can actively operate and maintain the power distribution terminal 102 based on the probability of the fault, that is, the cloud server 104 lists the power distribution terminal 102 which may have the fault into a focus attention list according to the state evaluation and the fault prediction, so as to form the target to-be-processed power distribution terminal list.
Through the embodiment, the cloud server 104 can determine the target to-be-processed power distribution terminal 102 which needs active operation and maintenance based on the predicted failure probability, so that the operation and maintenance efficiency of the power distribution terminal 102 is improved.
In one embodiment, controlling the target to-be-processed power distribution terminals in the target to-be-processed power distribution terminal list to execute the target operation and maintenance strategy includes: and controlling the target to-be-processed power distribution terminals in the target to-be-processed power distribution terminal list to perform self-checking self-recovery and/or software upgrading so as to enable the target to-be-processed power distribution terminals to recover normal operation.
In this embodiment, the cloud server 104 may actively operate and maintain each target to-be-processed power distribution terminal 102 in the target to-be-processed power distribution terminal list, for example, the cloud server 104 may remotely control the target to-be-processed power distribution terminal 102 to perform self-test self-recovery operation, and the cloud server 104 may also remotely control the target to-be-processed power distribution terminal 102 to perform running software upgrade, so that the target to-be-processed power distribution terminal 102 recovers a normal running state.
In addition, after controlling the target to-be-processed power distribution terminal 102 to execute the corresponding target operation and maintenance strategy, the cloud server 104 may further perform state evaluation and fault prediction on the target to-be-processed power distribution terminal 102 after executing the target operation and maintenance strategy based on the target state evaluation model. For example, in one embodiment, after controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance policy, the method further includes: acquiring target to-be-processed equipment information and target to-be-processed operation information of a target to-be-processed power distribution terminal after executing a target operation and maintenance strategy; inputting target equipment information to be processed and target operation information to be processed into a target state evaluation model, and acquiring target prediction fault information output by the target state evaluation model; and if the target prediction fault information has preset high-risk fault information, generating corresponding fault early warning information and sending the fault early warning information to a terminal of a worker, so that the worker can check the target power distribution terminal to be processed based on the fault early warning information.
In this embodiment, the predicted fault information may further include a predicted fault type, the cloud server 104 may obtain target to-be-processed device information and target to-be-processed operation information of the executed target to-be-processed power distribution terminal 102 after the target to-be-processed power distribution terminal 102 executes the target operation and maintenance policy, and input the target to-be-processed device information and the target to-be-processed operation information into the target state evaluation model, and the target state evaluation model may perform state evaluation and fault prediction on the target to-be-processed operation information and the target to-be-processed device information, so that the cloud server 104 may obtain the target predicted fault information output by the target state evaluation model and detect whether there is preset high-risk fault information, where the high-risk fault information may be preset, and if there is, the cloud server 104 may generate corresponding fault early warning information and send the corresponding fault early warning information to a terminal of a worker, so that the relevant staff can inspect the target power distribution terminal to be processed 102 based on the fault warning information. For example, the server 102 may add both the power distribution terminal 102 in the abnormal state in the automatic inspection and the power distribution terminal 102 predicted by the target state evaluation model to the target to-be-processed power distribution terminal list, perform self-checking and self-recovery operation on the terminals in the target to-be-processed power distribution terminal list remotely, and continue to evaluate and predict by using the target state evaluation model. The cloud server 104 can also remotely perform running software upgrading on the terminals in the target to-be-processed power distribution terminal list, and continue to perform evaluation and prediction by using the target state evaluation model. When the cloud server 104 still has a high risk terminal after the active operation and maintenance, personnel can be arranged to perform on-site inspection and maintenance.
Through the embodiment, the cloud server 104 can remotely perform operation and maintenance on the power distribution terminal 102 to be processed on the edge side based on the target operation and maintenance strategy, so that the operation and maintenance efficiency of the power distribution terminal is improved.
In one embodiment, after obtaining the predicted fault information of the power distribution terminal to be processed output by the target state evaluation model, the method further includes: according to the type of the to-be-processed equipment information of the to-be-processed power distribution terminal, clustering the predicted fault information to obtain a predicted fault information cluster corresponding to the to-be-processed equipment information; and if the quantity of the same type of predicted fault information in the predicted fault information cluster is larger than a preset value, generating a corresponding operation and maintenance strategy according to the information of the equipment to be processed.
In this embodiment, the cloud server 104 may further perform cluster analysis on the power distribution terminal 102 that may have a fault, and the power distribution terminal 102 may perform cluster processing on the predicted fault information according to the type of the to-be-processed device information of the to-be-processed power distribution terminal 102 after obtaining the predicted fault information of the to-be-processed power distribution terminal 102, so as to obtain a predicted fault information cluster corresponding to the to-be-processed device information. The types of the to-be-processed device information may include multiple types, for example, the to-be-processed device information may be a model of the power distribution terminal 102, and since the model may include multiple types, the predicted fault information cluster may also be multiple. Each predicted fault information cluster can contain multiple types of predicted fault information, and when the cloud server 104 detects that the number of the same types of predicted fault information in the predicted fault information clusters is larger than a preset value, the cloud server 104 can determine that the fault information is a common defect of the power distribution terminal 102 of the type, so that the cloud server 104 can generate a corresponding operation and maintenance strategy according to the to-be-processed device information, and the power distribution terminal 102 corresponding to the to-be-processed device information is upgraded and maintained in a unified manner. For example, the cluster analysis may be a familial feature analysis, and the cloud server 104 identifies the familial feature in the power distribution terminal 102 by performing cluster and association analysis on the device defects, and then proposes an operation and maintenance strategy and plan based on the familial feature. For example, through defect familial analysis, it is found that the number of times of a certain type of fault occurring to a certain type of power distribution terminal 102 of a certain model or a certain lot number is too large, and accordingly, a plan for batch unified upgrade maintenance can be provided for the same type of terminals.
Through the embodiment, the cloud server 104 can determine a common fault possibly occurring in the device information based on the device information of the power distribution terminal 102, so that the power distribution terminals 102 of the same type are uniformly maintained, and the operation and maintenance efficiency of the power distribution terminals is improved.
In an embodiment, as shown in fig. 3, fig. 3 is a schematic flowchart of a power distribution terminal operation and maintenance method based on cloud edge coordination in another embodiment. The method comprises the following steps: the server 102 may obtain status data of the power distribution terminal from the data center, including static information such as a device type, a manufacturer, a model, commissioning time, a channel type, a region to which the power distribution terminal belongs, real-time information such as an operation state, a battery state, a communication state, and alarm information, and historical information such as an operation record, an inspection record, and a maintenance record. Cloud server 104 may also employ big data technology to perform preprocessing and statistical analysis on the data. For example, when the cloud server 104 finds that the batch of terminals are disconnected, analyzing network characteristics of the disconnected power distribution terminals, judging whether the reason of the disconnection is a terminal fault or a communication network fault, and generating equipment defect warning information; monitoring the collected terminal running state, and giving an alarm when abnormality occurs. The cloud server 104 can also identify the problems of long-time non-refreshing of the power distribution terminal, frequent remote signaling jitter, long-time continuous offline, frequent offline, remote control failure and the like by performing statistical processing on historical data of the power distribution terminal, and provide data support for judging the operation state of the terminal. The cloud server 104 can further utilize a data mining algorithm to deeply mine the association relationship between the historical information of the power distribution terminal fault and the terminal running state information and the information of long-time non-refreshing measurement, frequent shaking of remote signaling, long-time continuous offline, frequent offline, remote control failure and the like, so as to provide support for the evaluation of the health state of the power distribution terminal.
Cloud server 104 may perform intelligent operations and maintenance on power distribution terminal 102. For example, the cloud server 104 may perform state monitoring and daily operation and maintenance on the power distribution terminal 102, specifically, monitor the operation state of the power distribution terminal in real time, and send an alarm signal when the power distribution terminal is in abnormal conditions such as shutdown and disconnection. The cloud server 104 can perform batch parameter setting on the power distribution terminals at the cloud; and the cloud server 104 may perform batch running program updates on the power distribution terminals at the cloud. The cloud server 104 may also perform automatic inspection on the power distribution terminal 102, specifically, learn a work record sheet of the previous manual inspection by using a machine learning method, and extract inspection work items. And generating inspection parameters according to the extracted inspection work items. And then the states of all the power distribution terminals are checked at regular time according to the polling parameters. And an early warning is given to the abnormal terminal. The cloud server 104 may further perform health status evaluation on the power distribution terminal 102, specifically including researching association rules and evolution rules between the power distribution terminal equipment failure and self-running state parameters, commissioning time, manufacturer, model, channel type, and information such as measurement non-refresh for a long time, frequent jitter of remote signaling, long-time continuous offline, frequent offline, and remote control failure, by using a big data analysis algorithm. The cloud server 104 may further establish a power distribution terminal health state evaluation and prediction model, i.e., the above-mentioned target state evaluation model, and adjust the parameters and weights by using a machine learning and association analysis algorithm. And evaluating the current health state of the terminal according to the current operating state parameters and other related information by using the power distribution terminal health state evaluation model. And the probability of the terminal having faults and what kind of faults occur in a future period of time is predicted by using a power distribution terminal health prediction model.
The cloud server 104 may also perform active operation and maintenance on the power distribution terminal 102, specifically including listing a terminal that may have a fault into a focus attention list, that is, the target to-be-processed power distribution terminal list, according to fault early warning in the automatic inspection and state evaluation and fault prediction in the target state evaluation model. The cloud server 104 remotely performs self-test self-recovery operation on the terminals in the key attention list, and continues to evaluate and predict by adopting the target state evaluation model. The cloud server 104 can remotely perform running software upgrading on the terminals in the key attention list, continue to perform evaluation and prediction by using the target state evaluation model, and arrange personnel to perform on-site inspection and maintenance on the terminals still with high risk. Cloud server 104 may also perform clustering and correlation analysis on the defects of the terminal devices to identify the familial features thereof, and provide an operation and maintenance strategy and plan based on the familial features. For example, through defect familial analysis, the frequency of certain type of faults occurring on a terminal of a certain type of a certain model or a certain batch number of a certain manufacturer is found to be excessive, so that a plan for batch unified upgrade and maintenance can be provided for terminals of the same type.
According to the embodiment, the power distribution terminal is centrally operated and maintained by adopting a cloud edge cooperation technology, remote operation and maintenance application of the power distribution terminal is deployed at the cloud end, and a unified data base of the cloud end is utilized, so that information interaction links are reduced, and the consistency and accuracy of data are ensured; the operation and maintenance application is used as one of application functions of the cloud master station, and the workload of switching distribution network operation management personnel among a plurality of systems is reduced. Meanwhile, an intelligent operation and maintenance technology is adopted to automatically inspect the power distribution terminal, a health state evaluation model of the power distribution terminal is established, operation and maintenance are performed as required, an overhaul strategy is optimized, operation and maintenance workload is reduced, and the fault rate of the power distribution terminal is reduced, so that the operation and maintenance efficiency of the power distribution terminal 102 is improved.
It should be understood that although the various steps in the flowcharts of fig. 2-3 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-3 may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed in turn or alternately with other steps or at least some of the other steps or stages.
In one embodiment, as shown in fig. 4, there is provided a power distribution terminal operation and maintenance device based on cloud edge coordination, including: an acquisition module 500, a prediction module 502, and an operation and maintenance module 504, wherein:
the acquiring module 500 is configured to acquire to-be-processed device information and to-be-processed operation information of the to-be-processed power distribution terminal from a data center; the data center is arranged on the cloud server and used for receiving and storing the to-be-processed equipment information and the to-be-processed operation information sent by the to-be-processed power distribution terminal.
The prediction module 502 is configured to input the to-be-processed device information and the to-be-processed operation information into a target state evaluation model, and obtain predicted fault information of the to-be-processed power distribution terminal output by the target state evaluation model; the target state evaluation model is obtained by training based on a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information; each of the historical failure information corresponds to a set of sample device information and sample operational information.
And the operation and maintenance module 504 is configured to determine a target to-be-processed power distribution terminal to be maintained according to the predicted fault information, form a target to-be-processed power distribution terminal list, determine a target operation and maintenance policy of the target to-be-processed power distribution terminal list, and control the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance policy.
In one embodiment, the above apparatus further comprises: the training module is used for acquiring a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information corresponding to the sample power distribution terminal; inputting the sample equipment information and the sample operation information into a state evaluation model to be trained, and acquiring sample prediction fault information output by the state evaluation model to be trained; judging whether the similarity value of the sample prediction fault information and the historical fault information corresponding to the sample equipment information and the sample operation information is smaller than a preset similarity threshold value or not; if not, adjusting the to-be-trained state evaluation model according to the similarity value, and returning to the step of inputting the sample equipment information and the sample operation information into the to-be-trained state evaluation model; if so, ending the circulation, and taking the current state evaluation model to be trained as a target state evaluation model.
In one embodiment, the above apparatus further comprises: the inspection module is used for acquiring historical inspection information corresponding to the power distribution terminal to be processed; determining routing inspection parameters corresponding to the power distribution terminal to be processed according to the historical routing inspection information; and detecting whether abnormal operation information exists in the to-be-processed operation information of the to-be-processed power distribution terminal according to the routing inspection parameters and a preset period, if so, generating corresponding alarm information and a target operation and maintenance strategy according to the abnormal operation information, and controlling the to-be-processed power distribution terminal to execute the target operation and maintenance strategy.
In an embodiment, the operation and maintenance module 504 is specifically configured to determine, if the predicted failure probability is greater than or equal to a preset failure threshold, that the to-be-processed power distribution terminal corresponding to the predicted failure information is a target to-be-processed power distribution terminal; and generating a target to-be-processed power distribution terminal list according to the to-be-processed equipment information of the target to-be-processed power distribution terminal.
In an embodiment, the operation and maintenance module 504 is specifically configured to control the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to perform self-test self-recovery and/or software upgrade, so that the target to-be-processed power distribution terminal recovers normal operation.
In one embodiment, the above apparatus further comprises: the checking module is used for acquiring target equipment to be processed information and target operation information to be processed of the target power distribution terminal to be processed after the target operation and maintenance strategy is executed; inputting the target to-be-processed equipment information and the target to-be-processed operation information into a target state evaluation model, and acquiring target prediction fault information output by the target state evaluation model; and if the target prediction fault information has preset high-risk fault information, generating corresponding fault early warning information and sending the fault early warning information to a terminal of a worker, so that the worker can check the target power distribution terminal to be processed based on the fault early warning information.
In one embodiment, the above apparatus further comprises: the clustering module is used for clustering the predicted fault information according to the type of the to-be-processed equipment information of the to-be-processed power distribution terminal to obtain a predicted fault information cluster corresponding to the to-be-processed equipment information; and if the quantity of the same type of predicted fault information in the predicted fault information cluster is larger than a preset value, generating a corresponding operation and maintenance strategy according to the to-be-processed equipment information.
In an embodiment, the obtaining module 500 is specifically configured to obtain, from a data center, at least one of a device type, a manufacturer, a model, commissioning time, a channel type, and a power distribution area of the power distribution terminal to be processed, as the information of the device to be processed; and acquiring at least one of the operation state, the battery state, the communication state and the alarm information of the power distribution terminal to be processed from the data center as the operation information to be processed.
For specific limitations of the power distribution terminal operation and maintenance device based on cloud edge coordination, reference may be made to the above limitations of the power distribution terminal operation and maintenance method based on cloud edge coordination, which are not described herein again. All or part of each module in the cloud edge coordination-based power distribution terminal operation and maintenance device can be realized through software, hardware and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing operation and maintenance related data based on the power distribution terminal. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize a power distribution terminal operation and maintenance method based on cloud edge cooperation.
Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, and includes a memory and a processor, where the memory stores a computer program, and the processor implements the cloud edge coordination-based power distribution terminal operation and maintenance method when executing the computer program.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, and the computer program, when executed by a processor, implements the cloud edge coordination-based power distribution terminal operation and maintenance method described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (10)

1. A power distribution terminal operation and maintenance method based on cloud edge cooperation is applied to a cloud server, and comprises the following steps:
acquiring to-be-processed equipment information and to-be-processed operation information of a to-be-processed power distribution terminal from a data center; the data center is arranged on the cloud server and used for receiving and storing to-be-processed equipment information and to-be-processed operation information sent by the to-be-processed power distribution terminal;
inputting the information of the equipment to be processed and the information of the operation to be processed into a target state evaluation model, and acquiring the predicted fault information of the power distribution terminal to be processed, which is output by the target state evaluation model; the target state evaluation model is obtained by training based on a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information; each of the historical fault information corresponds to a set of sample device information and sample operational information;
and determining a target power distribution terminal to be processed which needs to be maintained according to the predicted fault information, forming a target power distribution terminal list to be processed, determining a target operation and maintenance strategy of the target power distribution terminal list to be processed, and controlling the target power distribution terminal to be processed in the target power distribution terminal list to execute the target operation and maintenance strategy.
2. The method of claim 1, further comprising:
obtaining a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information corresponding to a sample power distribution terminal;
inputting the sample equipment information and the sample operation information into a state evaluation model to be trained, and acquiring sample prediction fault information output by the state evaluation model to be trained;
judging whether the similarity value of the sample prediction fault information and the historical fault information corresponding to the sample equipment information and the sample operation information is smaller than a preset similarity threshold value or not;
if not, adjusting the to-be-trained state evaluation model according to the similarity value, and returning to the step of inputting the sample equipment information and the sample operation information into the to-be-trained state evaluation model;
if so, ending the circulation, and taking the current state evaluation model to be trained as a target state evaluation model.
3. The method according to claim 1, wherein after acquiring the information of the to-be-processed equipment and the information of the to-be-processed operation of the to-be-processed power distribution terminal from the data center, the method further comprises:
acquiring historical patrol information corresponding to the power distribution terminal to be processed;
determining routing inspection parameters corresponding to the power distribution terminal to be processed according to the historical routing inspection information;
and detecting whether abnormal operation information exists in the to-be-processed operation information of the to-be-processed power distribution terminal according to the routing inspection parameters and a preset period, if so, generating corresponding alarm information and a target operation and maintenance strategy according to the abnormal operation information, and controlling the to-be-processed power distribution terminal to execute the target operation and maintenance strategy.
4. The method of claim 1, wherein the predicted failure information comprises a predicted failure probability;
the determining the target to-be-processed power distribution terminal to be maintained according to the predicted fault information to form a target to-be-processed power distribution terminal list, which comprises the following steps:
if the predicted fault probability is larger than or equal to a preset fault threshold value, determining that the to-be-processed power distribution terminal corresponding to the predicted fault information is a target to-be-processed power distribution terminal;
and generating a target to-be-processed power distribution terminal list according to the to-be-processed equipment information of the target to-be-processed power distribution terminal.
5. The method of claim 1, wherein the controlling the target pending power distribution terminals in the target pending power distribution terminal list to execute the target operation and maintenance policy comprises:
controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to perform self-checking self-recovery and/or software upgrading so as to enable the target to-be-processed power distribution terminal to recover normal operation;
after the controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance strategy, the method further includes:
acquiring target to-be-processed equipment information and target to-be-processed operation information of the target to-be-processed power distribution terminal after the target operation and maintenance strategy is executed;
inputting the target to-be-processed equipment information and the target to-be-processed operation information into a target state evaluation model, and acquiring target prediction fault information output by the target state evaluation model;
and if the target prediction fault information has preset high-risk fault information, generating corresponding fault early warning information and sending the fault early warning information to a terminal of a worker, so that the worker can check the target power distribution terminal to be processed based on the fault early warning information.
6. The method according to claim 1, wherein after obtaining the predicted fault information of the power distribution terminal to be processed output by the target state evaluation model, the method further comprises:
according to the type of the to-be-processed equipment information of the to-be-processed power distribution terminal, clustering the predicted fault information to obtain a predicted fault information cluster corresponding to the to-be-processed equipment information;
and if the quantity of the same type of predicted fault information in the predicted fault information cluster is larger than a preset value, generating a corresponding operation and maintenance strategy according to the to-be-processed equipment information.
7. The method according to claim 1, wherein the obtaining of the information of the to-be-processed equipment and the information of the to-be-processed operation of the to-be-processed power distribution terminal from the data center comprises:
acquiring at least one of the equipment type, manufacturer, model, commissioning time, channel type and the power distribution area of the power distribution terminal to be processed from a data center as the information of the equipment to be processed;
and acquiring at least one of the operation state, the battery state, the communication state and the alarm information of the power distribution terminal to be processed from the data center as the operation information to be processed.
8. The utility model provides a distribution terminal fortune dimension device based on cloud limit is in coordination, its characterized in that is applied to high in the clouds server, the device includes:
the acquisition module is used for acquiring the information of the equipment to be processed and the operation information to be processed of the power distribution terminal to be processed from the data center; the data center is arranged on the cloud server and used for receiving and storing to-be-processed equipment information and to-be-processed operation information sent by the to-be-processed power distribution terminal;
the prediction module is used for inputting the information of the equipment to be processed and the information of the operation to be processed into a target state evaluation model and acquiring the predicted fault information of the power distribution terminal to be processed, which is output by the target state evaluation model; the target state evaluation model is obtained by training based on a plurality of pieces of sample equipment information, a plurality of pieces of sample operation information and a plurality of pieces of historical fault information; each of the historical fault information corresponds to a set of sample device information and sample operational information;
and the operation and maintenance module is used for determining a target to-be-processed power distribution terminal to be maintained according to the predicted fault information, forming a target to-be-processed power distribution terminal list, determining a target operation and maintenance strategy of the target to-be-processed power distribution terminal list, and controlling the target to-be-processed power distribution terminal in the target to-be-processed power distribution terminal list to execute the target operation and maintenance strategy.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114399112A (en) * 2022-01-14 2022-04-26 成都秦川物联网科技股份有限公司 User evaluation obtaining method and system for natural gas energy metering
CN114937043A (en) * 2022-07-26 2022-08-23 中国工业互联网研究院 Equipment defect detection method, device, equipment and medium based on artificial intelligence
CN115085380A (en) * 2022-06-28 2022-09-20 海南电网有限责任公司电力科学研究院 Remote operation and maintenance system of distribution automation terminal
CN115277473A (en) * 2022-06-28 2022-11-01 中国南方电网有限责任公司 Remote operation and maintenance method and device for edge gateway, computer equipment and storage medium
CN115378841A (en) * 2022-08-03 2022-11-22 深圳前海环融联易信息科技服务有限公司 Method and device for detecting state of equipment accessing cloud platform, storage medium and terminal
CN116016120A (en) * 2023-01-05 2023-04-25 中国联合网络通信集团有限公司 Fault processing method, terminal device and readable storage medium
CN116109295A (en) * 2023-04-07 2023-05-12 华能济南黄台发电有限公司 Maintenance decision method based on power distribution terminal
CN117057786A (en) * 2023-10-11 2023-11-14 中电科大数据研究院有限公司 Intelligent operation and maintenance management method, system and storage medium for data center

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012249340A (en) * 2011-05-25 2012-12-13 Meidensha Corp Remote maintenance device for digital protection relay system
CN112367046A (en) * 2020-11-11 2021-02-12 兰州理工大学 Cloud edge cooperative remote operation and maintenance system suitable for distributed photovoltaic of remote areas
CN112381306A (en) * 2020-11-20 2021-02-19 广西电网有限责任公司防城港供电局 Intelligent operation and maintenance management and control platform for power distribution network
CN112527613A (en) * 2020-11-30 2021-03-19 北京航天智造科技发展有限公司 Equipment fault maintenance method and device based on cloud edge cooperation
CN112669172A (en) * 2020-12-31 2021-04-16 国电南瑞南京控制系统有限公司 Power distribution network regional autonomous rapid response method and system based on dynamic fusion of edge data

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012249340A (en) * 2011-05-25 2012-12-13 Meidensha Corp Remote maintenance device for digital protection relay system
CN112367046A (en) * 2020-11-11 2021-02-12 兰州理工大学 Cloud edge cooperative remote operation and maintenance system suitable for distributed photovoltaic of remote areas
CN112381306A (en) * 2020-11-20 2021-02-19 广西电网有限责任公司防城港供电局 Intelligent operation and maintenance management and control platform for power distribution network
CN112527613A (en) * 2020-11-30 2021-03-19 北京航天智造科技发展有限公司 Equipment fault maintenance method and device based on cloud edge cooperation
CN112669172A (en) * 2020-12-31 2021-04-16 国电南瑞南京控制系统有限公司 Power distribution network regional autonomous rapid response method and system based on dynamic fusion of edge data

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114399112A (en) * 2022-01-14 2022-04-26 成都秦川物联网科技股份有限公司 User evaluation obtaining method and system for natural gas energy metering
CN115085380A (en) * 2022-06-28 2022-09-20 海南电网有限责任公司电力科学研究院 Remote operation and maintenance system of distribution automation terminal
CN115277473A (en) * 2022-06-28 2022-11-01 中国南方电网有限责任公司 Remote operation and maintenance method and device for edge gateway, computer equipment and storage medium
CN114937043A (en) * 2022-07-26 2022-08-23 中国工业互联网研究院 Equipment defect detection method, device, equipment and medium based on artificial intelligence
CN114937043B (en) * 2022-07-26 2022-10-25 中国工业互联网研究院 Equipment defect detection method, device, equipment and medium based on artificial intelligence
CN115378841A (en) * 2022-08-03 2022-11-22 深圳前海环融联易信息科技服务有限公司 Method and device for detecting state of equipment accessing cloud platform, storage medium and terminal
CN115378841B (en) * 2022-08-03 2024-01-26 深圳前海环融联易信息科技服务有限公司 Method and device for detecting state of equipment accessing cloud platform, storage medium and terminal
CN116016120A (en) * 2023-01-05 2023-04-25 中国联合网络通信集团有限公司 Fault processing method, terminal device and readable storage medium
CN116109295A (en) * 2023-04-07 2023-05-12 华能济南黄台发电有限公司 Maintenance decision method based on power distribution terminal
CN117057786A (en) * 2023-10-11 2023-11-14 中电科大数据研究院有限公司 Intelligent operation and maintenance management method, system and storage medium for data center
CN117057786B (en) * 2023-10-11 2024-01-02 中电科大数据研究院有限公司 Intelligent operation and maintenance management method, system and storage medium for data center

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