CN116629548A

CN116629548A - Method, device, equipment and storage medium for processing transformer substation accidents

Info

Publication number: CN116629548A
Application number: CN202310604707.2A
Authority: CN
Inventors: 周智明; 陈庚; 郑安然; 李欣
Original assignee: Guangdong Power Grid Co Ltd; Dongguan Power Supply Bureau of Guangdong Power Grid Co Ltd
Current assignee: Guangdong Power Grid Co Ltd; Dongguan Power Supply Bureau of Guangdong Power Grid Co Ltd
Priority date: 2023-05-25
Filing date: 2023-05-25
Publication date: 2023-08-22

Abstract

The embodiment of the invention discloses a transformer substation accident processing method, device, equipment and storage medium. The method comprises the following steps: collecting working data of a transformer substation in real time through each cooperative robot; under the condition that the target abnormal working data exist in each working data, determining a target accident matched with the target abnormal working data and a target disposal strategy corresponding to the target accident; and issuing the target treatment strategy to a target cooperative robot which acquires the target abnormal working data so that the target cooperative robot processes the target accident based on the target treatment strategy. According to the scheme provided by the embodiment of the invention, the accident of the transformer substation can be rapidly and accurately processed.

Description

Method, device, equipment and storage medium for processing transformer substation accidents

Technical Field

The embodiment of the invention relates to the technical field of transformer substations, in particular to a transformer substation accident processing method, device, equipment and storage medium.

Background

With the continuous development of artificial intelligence technology, intelligent robots are widely used in various industries.

At present, the intelligent robot applied to the transformer substation is single in function and generally has only a patrol function. How to rapidly and accurately process the accidents of the transformer substation through the intelligent robot is an important problem of the research in the industry.

Disclosure of Invention

The embodiment of the invention provides a method, a device, equipment and a storage medium for processing accidents of a transformer substation, which are used for rapidly and accurately processing the accidents of the transformer substation.

According to an aspect of the embodiment of the invention, there is provided a method for handling a substation accident, including:

collecting working data of a transformer substation in real time through each cooperative robot;

under the condition that the target abnormal working data exist in each working data, determining a target accident matched with the target abnormal working data and a target disposal strategy corresponding to the target accident;

and issuing the target treatment strategy to a target cooperative robot which acquires the target abnormal working data so that the target cooperative robot processes the target accident based on the target treatment strategy.

According to another aspect of the embodiment of the present invention, there is provided a device for handling a substation event, including:

the working data acquisition module is used for acquiring working data of the transformer substation in real time through the cooperative robots;

a treatment policy determining module, configured to determine, when it is determined that target abnormal working data exists in each working data, a target incident that matches the target abnormal working data and a target treatment policy corresponding to the target incident;

and the accident handling module is used for issuing the target handling strategy to the target cooperative robot which collects the target abnormal working data so that the target cooperative robot handles the target accident based on the target handling strategy.

According to another aspect of an embodiment of the present invention, there is provided an electronic apparatus including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the method for handling the transformer substation accident according to any one of the embodiments of the present invention.

According to another aspect of the embodiments of the present invention, there is provided a computer readable storage medium storing computer instructions for causing a processor to implement the method for handling a substation event according to any of the embodiments of the present invention when executed.

According to the technical scheme, working data of a transformer substation are collected in real time through the cooperative robots; under the condition that the target abnormal working data exist in each working data, determining a target accident matched with the target abnormal working data and a target disposal strategy corresponding to the target accident; and issuing the target treatment strategy to a target cooperative robot which acquires the target abnormal working data, so that the target cooperative robot processes the target accident based on the target treatment strategy, and the accident of the transformer substation can be rapidly and accurately processed.

It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the invention, nor is it intended to be used to limit the scope of the embodiments of the invention. Other features of embodiments of the present invention will become apparent from the description that follows.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a method for handling a substation accident according to a first embodiment of the present invention;

fig. 2 is a flowchart of a method for handling a substation accident according to a second embodiment of the present invention;

fig. 3 is a schematic structural diagram of a handling device for a substation accident according to a third embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device for implementing a method for handling a substation event according to an embodiment of the present invention.

Detailed Description

In order to make the embodiments of the present invention better understood by those skilled in the art, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the embodiments of the present invention.

It should be noted that the terms "first," "second," and the like in the description and the claims of the embodiments of the present invention and the above-described drawings are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.

Example 1

Fig. 1 is a flowchart of a method for handling a substation accident according to a first embodiment of the present invention, where the method may be applied to a case where an intelligent robot is used to quickly and accurately handle an accident occurring in a substation, where the method may be performed by a device for handling a substation accident, where the device for handling a substation accident may be implemented in a form of hardware and/or software, and where the device for handling a substation accident may be configured in an electronic device such as a computer, a server, or a tablet computer. Specifically, referring to fig. 1, the method specifically includes the following steps:

and 110, collecting working data of the transformer substation in real time through the cooperative robots.

The number of the cooperative robots in this embodiment may be 3 or 5, which is not limited in this embodiment.

In this embodiment, the collaborative robot may include at least one of: the exploration robot, the data robot, the operation robot, the logistics robot, the repair robot, the test robot, and the like are not limited in this embodiment. Wherein, each working data collected by each cooperative robot can comprise at least one of the following: substation measurement and control information, protection information, fault recording information, environment monitoring system information, on-line monitoring information, equipment ledger information, equipment history defect information, equipment maintenance recording information and the like, which are not limited in this embodiment.

In an optional implementation manner in this embodiment, each working data of the substation may be collected in real time by each cooperative robot, and each data may be fed back to the processing system of the substation accident in real time, and after the processing system of the substation accident receives these working data, it may be further determined that there are all abnormal working data, an accident type corresponding to the abnormal working data, and the like.

Step 120, in the case that it is determined that the target abnormal working data exists in each working data, determining a target accident matched with the target abnormal working data and a target treatment policy corresponding to the target accident.

In an optional implementation manner of this embodiment, after receiving each working data of the substation collected in real time by each collaborative robot, it may further determine whether there is any target abnormal working data in each obtained working data, where the target abnormal working data may be any one or more abnormal working data, for example, abnormal substation measurement and control information, abnormal protection information, abnormal fault record information, abnormal environment monitoring system information, abnormal online monitoring information, abnormal equipment ledger information, abnormal equipment history defect information, or abnormal equipment maintenance record information, which is not limited in this embodiment.

In an optional implementation manner of this embodiment, determining that the target abnormal working data exists in each working data may include: comparing each working data with a preset condition; and determining target abnormal working data according to the comparison result.

The preset condition may be a threshold condition, for example, the size of the working data exceeds a set threshold, that is, the abnormal working data; the time condition may be, for example, that the working data generated outside the set time is abnormal working data, and the present embodiment is not limited thereto.

In this embodiment, each piece of work data collected by each cooperative robot may be sequentially compared with a preset condition, and one or more pieces of work data that do not satisfy the preset condition may be determined as target abnormal work data.

In the present embodiment, in the case where it is determined that the target abnormal work data exists in the respective work data, the target incidents that match the target abnormal work data and the treatment policies corresponding to the target incidents may be further determined.

Optionally, in an optional implementation manner of this embodiment, determining the target accident that matches the target abnormal working data may include: determining accident occurrence time matched with the target abnormal working data; determining a target accident matched with the target abnormal working data according to the accident occurrence time and the data type of the target abnormal working data; wherein the target incident comprises at least one of: equipment tripping accidents, combustion accidents, explosion accidents, typhoon accidents, collapse accidents and flood accidents.

In an optional implementation manner of this embodiment, the accident occurrence time and the data type of the target abnormal working data may be determined according to the time when the collaborative robot collects the target abnormal working data, so as to determine the target accident; the data type of the target abnormal working data is matched with the type of the target accident.

Further, after determining that the target accident is obtained, a target treatment policy may be further determined according to the target accident. In an alternative implementation of the present embodiment, a treatment policy matching each incident may be established in advance, and after determining the target incident, the treatment policy matching the target incident may be determined quickly according to the relationship established in advance.

And 130, issuing the target treatment strategy to a target cooperative robot which acquires the target abnormal working data so that the target cooperative robot processes the target accident based on the target treatment strategy.

In an optional implementation manner of this embodiment, after determining that the target treatment policy corresponding to the target accident is obtained, the determined target policy may be issued to the target cooperative robot that collects the target abnormal working data, so that the target cooperative robot may process the target accident based on the target treatment policy received by the target cooperative robot.

Example two

Fig. 2 is a flowchart of a method for handling a substation accident according to a second embodiment of the present invention, where the technical solutions in this embodiment are further refined, and the technical solutions in this embodiment may be combined with each of the alternatives in one or more embodiments. As shown in fig. 2, the method for handling the substation accident may include the following steps:

step 210, collecting working data of the transformer substation in real time through the cooperative robots.

Step 220, determining a target accident matched with the target abnormal working data under the condition that the target abnormal working data exist in the working data.

Step 230, determining a target treatment strategy corresponding to the target accident.

In an optional implementation manner of this embodiment, after determining that the target accident matching the target abnormal working data is obtained, a target treatment policy corresponding to the target accident may be further determined. Optionally, in this embodiment, determining a target treatment policy corresponding to the target accident may include: a target treatment strategy corresponding to the target incident is determined based on each machine learning model trained in advance.

Wherein each machine learning model is trained from the work data of each historical incident and the treatment strategy matched with each historical incident.

Optionally, in this embodiment, determining, based on each machine learning model trained in advance, a target treatment policy corresponding to the target accident may include: determining each parameter information of the target accident and a target machine learning model matched with the target accident; and sequentially inputting the parameter information into the target machine learning model to obtain a target treatment strategy corresponding to the target accident.

It should be noted that, in this embodiment, during the training process of each machine learning model, the initial model may be obtained by letting the artificial intelligence model learn a large number of existing accident handling plans according to the conventional accident exercise scheme provided by the training personnel as a data source.

In the training process of each machine learning model, factors such as different fault devices, different power grid load flows, different occurrence times, different weather environments, presence or absence of personnel, presence or absence of external special power grid conditions, presence or absence of historical defects and the like which occur at accident time can be included as specific parameters of the model. And inputting the parameters into the model, and repeatedly checking the model perfection, suitability and the like.

In the embodiment, the training objective of each machine learning model is to enable the substation accident handling system to select a proper robot type and function according to different scenes and requirements, and flexibly and adaptively handle the substation accident through an optimal handling strategy;

in another alternative implementation manner of this embodiment, the integrity and correctness of the strategy may be marked by a reverse algorithm through a manual evaluation manner.

In this embodiment, each machine learning model covers various types of accidents that may occur in the transformer substation, such as accident situations of tripping, burning, explosion, typhoon, collapse, flooding, and the like; when the accident of the transformer substation occurs, parameters of each machine learning model cover various equipment, environment, power grid and human factors which influence the accident development, rescue and maintenance treatment; each machine learning model can cover the application and development of various intelligent terminals of the transformer substation. Providing the most suitable processing scheme according to the configuration conditions of various types of exploration robots, rescue robots, disposal robots and maintenance robots; each machine learning model can be trained to an optimal version of robot treatment strategy through iteration along with development of the power industry, change of equipment types and upgrading of the intelligent terminal.

And step 240, issuing the target treatment strategy to a target cooperative robot which collects the target abnormal working data so that the target cooperative robot processes the target accident based on the target treatment strategy.

Optionally, in this embodiment, the target treatment policy may be issued to the target cooperative robot that collects the target abnormal working data through a preset communication channel, so that the target collection policy may be issued to the target cooperative robot that collects the target abnormal working data quickly and accurately.

According to the scheme of the embodiment, the target treatment strategy corresponding to the target accident can be determined based on the pre-trained machine learning models, and the target treatment strategy corresponding to the target accident can be rapidly and accurately determined, so that a great amount of time and manpower resources are saved.

In order to better understand the embodiments of the present invention, a specific example is used to describe a method for handling a substation accident according to the embodiments of the present invention, where the method mainly includes:

and (3) collecting signals in the initial stage of the accident:

(1) When the accident total signal of the transformer substation occurs, the transformer substation accident handling system intervenes in accident handling.

(2) According to a preset communication mode, the substation accident handling system starts to page emergency handling contacts and notifies accident signals.

(3) The substation accident handling system retrieves all signals of the substation automation system in a specific time period before and after the accident total signal.

(4) And deducing the time of occurrence of the accident and the interval of occurrence of the accident according to the preset combination condition according to all the acquired signal data.

(5) The monitoring signal sources comprise, but are not limited to, transformer substation measurement and control information, protection information, fault wave recording information, environment monitoring system information, on-line monitoring information, equipment account information, equipment history defect information and equipment maintenance record information.

(6) And carrying out logic checking back calculation on the retrieved signals according to a preset signal logic combination rule, and primarily judging the types of accidents as equipment tripping, equipment fire or other equipment and power grid abnormality.

(7) And feeding back the primary accident information of the system screening integration to an emergency center monitoring interface according to a preset communication channel.

Further, the transformer substation accident handling system is adapted to a data model of various information source systems (such as a transformer substation measurement and control device, a protection device, a fault wave recording device, an environment monitoring system, an online monitoring system, a data center and a service management platform) of the transformer substation, has a unified communication data protocol and has a reliable communication channel; the communication channel has redundancy and reusability and a hot standby loop channel, and when a single communication channel fails, different data source devices can still reliably communicate with the substation accident handling system; the substation accident handling system is communicated with each information source system by a heartbeat in a fixed period, and the state of a channel is monitored; the transformer substation accident handling system performance redundancy configuration, the server is used for cold and hot standby, and the power supply adopts double-loop standby power supply.

Treatment policy invocation deployment:

(1) Based on the preliminary accident information, matching and calling the most proper disposal strategy in the strategy library, and beginning accident disposal according to the strategy.

(2) And each link of the treatment strategy partially requires the manager of the emergency command center to confirm according to the importance of the step. And selecting a proper robot mode, such as an autonomous mode or a remote control mode, according to the operation state and the environmental condition of the transformer substation.

(3) The operation condition of the robot is fed back to a monitoring center or related personnel in real time through wireless communication or other modes, and the action strategy of the robot is adjusted according to the requirement.

(4) Different accident events, depending on the difference in training results, may differ in their actual treatment methods, but generally follow the following procedure.

Intelligent terminal exploration robot group field exploration:

(1) Hardware part: and carrying various detection instruments or sensors by using carrying mechanical equipment such as unmanned aerial vehicles, walking robots and the like to collect and analyze the actual conditions on site. Detection instrumentation includes, but is not limited to: a visible light camera, an infrared thermal imager, a charged detection device, a gas analysis device and the like; the following were analyzed one by one according to the procedure.

(1) Collecting gas in the accident range of the site by using a gas detection instrument, and analyzing the content of harmful gas and the content of oxygen;

(2) measuring the temperature of the equipment by using a thermal imager, and analyzing whether the equipment has overheat, burning and explosion conditions and possibility; checking whether life signs exist on the site or not, and whether wounded persons exist or not;

(3) judging whether equipment collapse, damage, combustion, explosion and other conditions exist on site by using a visible light camera:

(4) detecting whether the ground of the accident site has potential or not by using a charged detection device, and reminding accident handling personnel of step voltage risk if the ground has potential;

(5) a weather detection device is used for detecting whether the accident site has extremely severe weather such as rain, snow, hail, strong wind and the like.

In this embodiment, the exploration group robot may remain on site to maintain the monitoring state according to the analysis result of the fault condition, the requirement of the treatment strategy, and the requirement of the manual instruction. The electric quantity supply can be kept sufficient by the logistic support robot by adopting an instant power change technology.

(2) Software part: and according to the detection data, combining the collection condition of the initial accident signals, thereby further judging and determining the specific cause of the accident and the accurate accident range. According to the detection data, the accident hazard and loss degree are analyzed and judged, and according to the on-site acquisition condition, a conclusion is given whether the rescue personnel are suitable for approaching rescue and maintenance, and possible danger is early warned in time to avoid secondary accidents.

In this embodiment, a unified communication data protocol is provided between each exploration robot and between the robot and the substation accident handling system, so that a reliable communication channel is provided; the communication between robots and between the robots and the system should have enough reliability, redundancy multiplexing and low delay; each exploration robot is provided with an operation state instant power-changing borrowing port, so that the logistics robots can change power, and the on-line state is kept at all times; the substation accident handling system monitors and adjusts the operation condition of the robot in real time through wireless communication or other modes, and accuracy and reliability are improved.

In the embodiment, unified communication data protocols are arranged between the rescue robots and between the robots and the transformer substation accident handling system, and reliable communication channels are provided; the communication between robots and between the robots and the system should have enough reliability, redundancy multiplexing and low delay; each rescue robot is provided with an operation state instant power-changing borrowing port, so that the logistics robots can change power, and the online state is kept at any time; the substation accident handling system monitors and adjusts the operation condition of the robot in real time through wireless communication or other modes, so that the accuracy and the reliability are improved; the rescue robot has enough mechanical strength, shell strength and waterproof strength; operating a handling robot group operating device:

on-site cleaning, equipment repair and power grid mode recovery:

(1) According to the transformer substation accident handling system, a repair robot is selected and controlled to be matched with a proper tool to repair damaged equipment according to the accident situation and the intelligent handling strategy mastered by the steps through wireless signals or other modes. The repairing robot has the functions of moving, grabbing, cutting, welding and the like, and the tool comprises elements such as insulating materials, wires, switches, hardware fittings and the like;

(2) Through the transformer substation accident handling system, performance tests are carried out on the repaired equipment through wireless signals or other modes, and the equipment is confirmed to have operation conditions.

(3) After confirming that the operation conditions are met, the operation robot group remotely operates the equipment to restore the normal operation mode, and the transformer substation is restored to the operation mode before the accident.

Accident information and disposal information arrangement:

(1) When the accident is controlled or ended, the operation of the robot is stopped, the robot is returned to the safety area, and the charging standby state of the robot is restored.

(2) The transformer substation accident handling system sorts all information of the accident, including the cause, the influence range and the achievement of the accident, whether personnel casualties exist or not and the action condition of each group of robots, and outputs a disposal report.

According to the scheme provided by the embodiment of the invention, when an accident occurs in the transformer substation, the tasks such as inspection, investigation and treatment are replaced or assisted by personnel, so that the processing efficiency, safety and quality of the accident event of the transformer substation can be improved, the manpower resources are saved, and the risk is reduced.

In the technical scheme of the embodiment of the invention, the acquisition, storage, application and the like of the related user personal information (such as face information, voice information and the like) accord with the regulations of related laws and regulations, and the public order welcome is not violated.

Example III

Fig. 3 is a schematic structural diagram of a handling device for a transformer substation accident according to a third embodiment of the present invention. As shown in fig. 3, the apparatus includes: a working data acquisition module 310, a disposition policy determination module 320, and an incident handling module 330.

A working data acquisition module 310, configured to acquire, in real time, each working data of the substation through each collaborative robot;

a treatment policy determining module 320, configured to determine, when it is determined that there is target abnormal working data in each working data, a target incident that matches the target abnormal working data and a target treatment policy corresponding to the target incident;

the accident handling module 330 is configured to issue the target handling policy to a target cooperative robot that collects the target abnormal working data, so that the target cooperative robot handles the target accident based on the target handling policy.

According to the scheme of the embodiment, the working data of the transformer substation are collected in real time through the working data acquisition module; determining, by a treatment policy determining module, a target incident matching the target abnormal working data and a target treatment policy corresponding to the target incident when it is determined that the target abnormal working data exists in each working data; and the accident handling module issues the target handling strategy to a target cooperative robot which collects the target abnormal working data, so that the target cooperative robot handles the target accident based on the target handling strategy, and the accident of the transformer substation can be handled rapidly and accurately.

In an optional implementation of this embodiment, the collaborative robot includes at least one of:

exploration robots, data robots, operations robots, logistics robots, repair robots, and test robots;

the operational data includes at least one of:

substation measurement and control information, protection information, fault wave recording information, environment monitoring system information, on-line monitoring information, equipment account information, equipment history defect information and equipment maintenance record information.

In an optional implementation manner of this embodiment, the treatment policy determining module 320 is specifically configured to compare each of the working data with a preset condition;

and determining target abnormal working data according to the comparison result.

In an optional implementation manner of this embodiment, the treatment policy determining module 320 is further specifically configured to determine an accident occurrence time that matches the target abnormal working data;

determining a target accident matched with the target abnormal working data according to the accident occurrence time and the data type of the target abnormal working data;

wherein the target incident comprises at least one of:

equipment tripping accidents, combustion accidents, explosion accidents, typhoon accidents, collapse accidents and flood accidents.

In an optional implementation manner of this embodiment, the treatment policy determining module 320 is further specifically configured to determine, based on each machine learning model trained in advance, a target treatment policy corresponding to the target accident;

each machine learning model is trained from the work data of each historical incident and the treatment strategy matched with each historical incident.

In an optional implementation manner of this embodiment, the treatment policy determining module 320 is further specifically configured to determine parameter information of the target accident, and a target machine learning model matched with the target accident;

and sequentially inputting the parameter information into the target machine learning model to obtain a target treatment strategy corresponding to the target accident.

In an optional implementation manner of this embodiment, the accident handling module 330 is specifically configured to issue, through a preset communication channel, the target treatment policy to a target cooperative robot that collects the target abnormal working data.

The transformer substation accident processing device provided by the embodiment of the invention can execute the transformer substation accident processing method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

Example IV

Fig. 4 shows a schematic diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic equipment may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the embodiments of the invention described and/or claimed herein.

As shown in fig. 4, the electronic device 10 includes at least one processor 11, and a memory, such as a Read Only Memory (ROM) 12, a Random Access Memory (RAM) 13, etc., communicatively connected to the at least one processor 11, in which the memory stores a computer program executable by the at least one processor, and the processor 11 may perform various appropriate actions and processes according to the computer program stored in the Read Only Memory (ROM) 12 or the computer program loaded from the storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 may also be stored. The processor 11, the ROM 12 and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to bus 14.

Various components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, etc.; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, an optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, digital Signal Processors (DSPs), and any suitable processor, controller, microcontroller, etc. The processor 11 performs the various methods and processes described above, such as the process of a substation event.

In some embodiments, the substation event handling method may be implemented as a computer program tangibly embodied on a computer readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the substation event handling method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to perform the substation event handling method in any other suitable way (e.g. by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

A computer program for implementing the methods of embodiments of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of embodiments of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), blockchain networks, and the internet.

The computing system may include clients and servers. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the embodiments of the present invention may be performed in parallel, sequentially or in a different order, so long as the desired result of the technical solution of the embodiments of the present invention can be achieved, which is not limited herein.

The above detailed description should not be construed as limiting the scope of the embodiments of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the embodiments of the present invention should be included in the scope of the embodiments of the present invention.

Claims

1. A method for handling a substation event, comprising:

2. The method of claim 1, wherein the collaborative robot comprises at least one of:

the operational data includes at least one of:

3. The method of claim 1, wherein said determining that there is target abnormal working data in each of said working data comprises:

comparing each working data with a preset condition;

4. The method of claim 1, wherein the determining a target incident that matches the target abnormal operation data comprises:

determining accident occurrence time matched with the target abnormal working data;

wherein the target incident comprises at least one of:

5. The method of claim 4, wherein the determining a target treatment policy corresponding to the target incident comprises:

determining a target treatment strategy corresponding to the target accident based on each machine learning model trained in advance;

6. The method of claim 5, wherein the determining a target treatment strategy corresponding to the target incident based on pre-trained machine learning models comprises:

determining each parameter information of the target accident and a target machine learning model matched with the target accident;

7. The method of claim 1, wherein the issuing the target treatment strategy to the target collaborative robot that collected the target abnormal operation data comprises:

and issuing the target treatment strategy to the target cooperative robot which acquires the target abnormal working data through a preset communication channel.

8. A device for handling a substation event, comprising:

9. An electronic device, the electronic device comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,,

the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of handling a substation event of any of claims 1-7.

10. A computer readable storage medium, characterized in that it stores computer instructions for causing a processor to implement the method for handling a substation event according to any of claims 1-7 when executed.