CN115085198B - Perception decision method based on edge calculation - Google Patents
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Abstract
The invention discloses a perception decision method based on edge calculation, which can automatically perceive abnormal working units in a target power grid and automatically adjust the operation decision of the target power grid according to the abnormal working units. The problem of in the prior art, because the power grid system adopts the operation decision-making procedure that artifical preset, therefore when the equipment damaged condition appears, be difficult to in time adjust the operation decision-making of power grid system is solved.
Description
Technical Field
The invention relates to the field of power grid monitoring, in particular to a perception decision method based on edge calculation.
Background
The power grid system usually comprises a plurality of working units, such as a power transmission unit, a power transformation unit and a power distribution unit, wherein the working units respectively execute different functions, and the respective operation conditions of the working units depend on whether the power grid system can normally operate or not and on the normal and orderly operation of production and living of people, so that the operation decision of the power grid system is very important. The operation decision of the power grid can reflect the work tasks and execution modes of all the work units, at present, a manually preset operation decision program is usually adopted by a power grid system, and the operation decision program can be continuously executed until relevant workers reset. However, the devices in each working unit may be damaged or abnormal, and at this time, the operation decision of the power grid system needs to be adjusted immediately to ensure the normal operation of the power grid system. Therefore, when the existing power grid system is damaged, the operation decision of the power grid system is difficult to adjust in time.
Thus, there is still a need for improvement and development of the prior art.
Disclosure of Invention
The invention aims to solve the technical problem that in the prior art, because a power grid system adopts an operation decision program which is manually preset, the operation decision of the power grid system is difficult to adjust in time when equipment is damaged.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a perceptual decision method based on edge computation, where the method includes:
acquiring actual structural operation diagrams corresponding to a plurality of working units in a target power grid respectively, wherein the working units are used for executing different functions respectively, and each actual structural operation diagram is used for reflecting the interaction characteristics among a plurality of working devices corresponding to one working unit;
acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit;
determining operation deviation values corresponding to the working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the working units respectively;
determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value;
acquiring an environment monitoring data set corresponding to the target working unit, wherein the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises one or a plurality of edge terminals, and the edge terminals are respectively used for acquiring different types of environment monitoring data;
and when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units.
In an embodiment, the obtaining an actual structured operation diagram corresponding to each of a plurality of working units in a target power grid includes:
acquiring actual working data corresponding to a plurality of working units respectively, wherein the actual working data corresponding to each working unit is used for reflecting interactive data among a plurality of working devices corresponding to the working unit;
and determining the actual structured operation diagrams corresponding to the working units respectively according to the actual working data corresponding to the working units respectively.
In an embodiment, each of the actual structured operation graphs includes a plurality of nodes, the plurality of nodes respectively correspond to different working devices, and characteristics of a connection line between the plurality of nodes are used for reflecting interaction characteristics between the plurality of working devices.
In one embodiment, the determining, according to the standard structured operation diagram and the actual structured operation diagram corresponding to the plurality of working units, an operation deviation value corresponding to each of the plurality of working units includes:
determining a node deviation value corresponding to each node in each working unit according to the standard structured operation diagram and the actual structured operation diagram corresponding to each working unit, wherein each node deviation value is determined based on the difference between the standard structured operation diagram and the actual structured operation diagram of the characteristics of each connecting line corresponding to the node;
and determining the operation deviation value corresponding to each working unit according to the node deviation value corresponding to each node in each working unit.
In one embodiment, the environment monitoring data set includes area video data, area sound data, area temperature data, and area humidity data corresponding to the target work unit.
In an embodiment, the determining, according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units, an operation decision corresponding to the target power grid includes:
determining abnormal working equipment in the target working unit, wherein the node deviation value corresponding to the abnormal working equipment is greater than a second threshold value;
generating an updating work unit according to the target work unit and the abnormal work equipment, wherein the updating work unit comprises all the work equipment except the abnormal work equipment in the target unit;
adjusting the actual structured operation diagram corresponding to the target working unit according to the updating working unit to obtain an updated structured operation diagram corresponding to the updating working unit;
and determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the updated structured operation diagram respectively corresponding to all the working units except the target working unit.
In one embodiment, the plurality of working units comprise a power transmission unit, a power transformation unit and a power distribution unit; when the target working unit is a power transmission unit, the operation decision is a power transmission decision and a power transformation decision; when the target working unit is a power transformation unit, the operation decision is a power transmission decision, a power transformation decision and a power distribution decision; and when the target working unit is a power distribution unit, the operation decision is a power transformation decision and a power distribution decision.
In a second aspect, an embodiment of the present invention further provides a perceptual decision apparatus based on edge computation, where the apparatus includes:
the data acquisition module is used for acquiring actual structured operation diagrams corresponding to a plurality of working units in a target power grid respectively, wherein the working units are used for executing different functions respectively, and each actual structured operation diagram is used for reflecting the interaction characteristics among a plurality of working devices corresponding to one working unit;
acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit;
the target sensing module is used for determining operation deviation values corresponding to the working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the working units respectively;
determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value;
the operation decision module is used for acquiring an environment monitoring data set corresponding to the target working unit, wherein the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises one or a plurality of edge terminals, and the edge terminals are respectively used for acquiring different types of environment monitoring data;
and when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units.
In a third aspect, an embodiment of the present invention further provides a terminal, where the terminal includes a memory and one or more processors; the memory stores one or more programs; the program includes instructions for performing a perceptual decision method based on edge computation as described in any of the above; the processor is configured to execute the program.
In a fourth aspect, the present invention further provides a computer-readable storage medium, on which a plurality of instructions are stored, wherein the instructions are adapted to be loaded and executed by a processor to implement any of the above-mentioned steps of the edge-computation-based perceptual decision method.
The invention has the beneficial effects that: the embodiment of the invention can automatically sense the abnormal working unit in the target power grid and automatically adjust the operation decision of the target power grid according to the abnormal working unit. The problem of in the prior art, because the power grid system adopts the operation decision-making procedure that artifical preset, therefore when the equipment damaged condition appears, be difficult to in time adjust the operation decision-making of power grid system is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a perceptual decision method based on edge computation according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of internal modules of a perceptual decision device based on edge computation according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
The invention discloses a perception decision method based on edge calculation, which is further described in detail below by referring to the attached drawings and embodiments in order to make the purpose, technical scheme and effect of the invention clearer and clearer. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The power grid system usually comprises a plurality of working units, such as a power transmission unit, a power transformation unit and a power distribution unit, wherein the working units respectively execute different functions, and the respective operation conditions of the working units concern whether the power grid system can normally operate or not and also concern that the production and life energy of people is normally and orderly carried out, so that the operation decision of the power grid system is of great importance. The operation decision of the power grid can reflect the work tasks and execution modes of all the work units, at present, a manually preset operation decision program is usually adopted by a power grid system, and the operation decision program can be continuously executed until relevant workers reset. However, the devices in each working unit may be damaged or abnormal, and at this time, the operation decision of the power grid system needs to be adjusted immediately to ensure the normal operation of the power grid system. Therefore, when the equipment of the conventional power grid system is damaged, the operation decision of the power grid system is difficult to adjust in time.
Aiming at the defects of the prior art, the invention provides a perception decision method based on edge calculation, which comprises the steps of obtaining actual structural operation graphs corresponding to a plurality of working units in a target power grid respectively, wherein the working units are used for executing different functions respectively, and each actual structural operation graph is used for reflecting the interaction characteristics among a plurality of working devices corresponding to one working unit; acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit; determining operation deviation values corresponding to the working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the working units respectively; determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value; acquiring an environment monitoring data set corresponding to the target working unit, wherein the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises one or a plurality of edge terminals, and the edge terminals are respectively used for acquiring different types of environment monitoring data; and when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units. The method and the device can automatically sense the abnormal working unit in the target power grid and automatically adjust the operation decision of the target power grid according to the abnormal working unit. The problem of in the prior art, because the power grid system adopts the operation decision-making procedure that artifical preset, therefore when the equipment damaged condition appears, be difficult to in time adjust the operation decision-making of power grid system is solved.
As shown in fig. 1, the method comprises the steps of:
step S100, acquiring actual structural operation diagrams corresponding to a plurality of working units in a target power grid, wherein the plurality of working units are respectively used for executing different functions, and each actual structural operation diagram is used for reflecting interaction characteristics among a plurality of working devices corresponding to one working unit.
Specifically, in this embodiment, the target grid may be any grid system, the embodiment divides the target grid into different work units in advance based on the types of functions, and generates an actual structured operation diagram corresponding to each work unit based on the operation data of each work unit. Taking a power transmission unit as an example, the power transmission unit includes multiple power transmission related devices, and the power transmission related devices have certain data interaction with each other, so as to cooperatively complete a power transmission task of the power transmission unit, and an actual structured operation diagram corresponding to the power transmission unit is used for reflecting interaction characteristics between the power transmission related devices in the power transmission unit.
In one implementation, the step S100 specifically includes the following steps:
step S101, acquiring actual working data corresponding to a plurality of working units respectively, wherein the actual working data corresponding to each working unit is used for reflecting interactive data among a plurality of working devices corresponding to the working unit;
and S102, determining the actual structured operation diagrams corresponding to the working units respectively according to the actual working data corresponding to the working units respectively.
Specifically, each actual structured operation diagram in this embodiment reflects the interaction characteristics between the working devices in one working unit. Therefore, for each working unit, in this embodiment, interactive data between the working devices in the working unit needs to be obtained first, for example, the interactive data between the working devices may be obtained by monitoring a request data packet and a response data packet of each working device, and then data analysis is performed on the interactive data to obtain an interactive characteristic between the working devices, and finally an actual structural operation diagram corresponding to the working unit is generated, and the interaction condition of each working device in the working unit may be determined intuitively through the actual structural operation diagram, so as to determine whether the working unit is in a normal operation state.
In one implementation manner, each actual structured operation diagram includes a plurality of nodes, the plurality of nodes respectively correspond to different working devices, and characteristics of connection lines between the plurality of nodes are used for reflecting interaction characteristics between the plurality of working devices.
Specifically, the actual structured operation diagram in the embodiment is a dotted line connection diagram. For each working unit, each node in the actual structural operation diagram corresponding to the working unit has a one-to-one correspondence relationship with each working device corresponding to the working unit, and the line characteristic of the connecting line between two nodes in the actual structural operation diagram can reflect the interaction characteristics of the two nodes. For example, a line of different line characteristics may reflect different interaction frequencies between two nodes.
As shown in fig. 1, the method further comprises the steps of:
and S200, acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit.
In short, in this embodiment, only when it is found that the working units are in the abnormal operation state, the operation decision corresponding to the target power grid is determined again, so that this embodiment needs to determine whether each working unit is in the normal operation state first. Specifically, for each working unit, in this embodiment, a standard structured operation diagram corresponding to the working unit is generated in advance based on the interaction data between the corresponding working devices when the working unit is in the normal operation state. And subsequently, the standard structured operation diagram can be used as a judgment standard to judge whether the working unit is in a normal operation state.
As shown in fig. 1, the method further comprises the steps of:
and S300, determining operation deviation values corresponding to the plurality of working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the plurality of working units respectively.
Specifically, for each working unit, since the standard structured operation diagram of the working unit reflects the interactive characteristics between the working devices in the normal operation state, and the actual structured operation diagram of the working unit reflects the interactive characteristics between the working devices in the current operation state, the deviation between the current operation state and the normal operation state of the working unit can be calculated by comparing the standard structured operation diagram and the actual structured operation diagram, that is, the operation deviation value of the working unit can be obtained.
In one implementation, the step S300 specifically includes the following steps:
step S301, determining a node deviation value corresponding to each node in each working unit according to the standard structured operation diagram and the actual structured operation diagram corresponding to each working unit, wherein each node deviation value is determined based on the difference between the characteristics of each connecting line corresponding to the node in the standard structured operation diagram and the actual structured operation diagram;
step S302, determining the operation deviation value corresponding to each working unit according to the node deviation value corresponding to each node in each working unit.
Specifically, for each working unit, the operation deviation value of the working unit needs to be comprehensively determined based on the node deviation values of the nodes in the actual structured operation diagram. And the node deviation value corresponding to the node is comprehensively determined based on the characteristic deviations corresponding to the connecting lines respectively.
As shown in fig. 1, the method further comprises the steps of:
and S400, determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value.
Specifically, for each working unit, if the operation deviation value of the working unit is larger, it indicates that the difference between the current operation state and the normal operation state is larger. Since the operation state of the working unit is slightly fluctuated, which does not affect the normal function of the whole working unit, in this embodiment, a first threshold is preset, and if the operation deviation value of the working unit is greater than the first threshold, which indicates that the difference between the current operation state and the normal operation state of the working unit is too large, the working unit may be in an abnormal operation state at present, and needs to be subjected to key analysis as a target working unit.
As shown in fig. 1, the method further comprises the steps of:
step S500, an environment monitoring data set corresponding to the target working unit is obtained, wherein the monitoring data set is obtained based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises one or a plurality of edge terminals, and the edge terminals are respectively used for collecting different types of environment monitoring data.
Specifically, since there are many reasons for the abnormality of the target work unit, there are external environmental reasons and internal equipment reasons, it is necessary to obtain the environment monitoring data set of the target work unit to determine whether the external environment is normal. In this embodiment, a group of edge terminals is arranged in each working unit in advance, and each edge terminal in the group of edge terminals is used for collecting different types of environment monitoring data, such as environment temperature data, environment humidity data, and the like. Therefore, the corresponding environment monitoring data set can be obtained through the edge terminal group corresponding to the target working unit.
In one implementation, the environment monitoring data set includes area video data, area sound data, area temperature data, and area humidity data corresponding to the target work unit.
Specifically, the regional video data can reflect the current position and external state of each working device in the target working unit, so as to judge whether each working device has displacement or surface damage; the regional sound data can reflect whether suspicious noise occurs in the target working unit, so that whether a person intrudes illegally in the target working unit is judged; because the normal operation of each working device is influenced by overhigh environment temperature, whether the target working unit operates abnormally due to abnormal temperature can be judged according to the area temperature; because the normal operation of each working device is affected by the overhigh environment humidity, whether the target working unit operates abnormally due to the abnormal humidity can be judged according to the area humidity.
As shown in fig. 1, the method further comprises the steps of:
step S600, when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units.
In short, when the environment monitoring data set meets the preset environment standard, it is described that the external environment of the target working unit is normal, and the cause of the abnormal operation of the target working unit may be that the internal operation of the working device therein is abnormal, so in order to avoid that the target working unit affects the normal operation of the target power grid, in this embodiment, the operation decision of the target power grid needs to be re-determined according to the actual structural operation diagram and the target working unit corresponding to each working unit, respectively. It can be understood that, if the environmental monitoring data set does not meet the preset environmental standard, the cause of the abnormal operation of the target working unit may be the abnormal external environment, and at this time, the external environment of the target working unit may be adjusted first without re-determining the operation decision of the target power grid. After the external environment of the target working unit is adjusted, the operation deviation value of the target working unit needs to be determined again.
In an implementation manner, the determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units specifically includes the following steps:
step S601, determining abnormal working equipment in the target working unit, wherein the node deviation value corresponding to the abnormal working equipment is greater than a second threshold value;
step S602, generating an updating work unit according to the target work unit and the abnormal work equipment, wherein the updating work unit comprises all the work equipment except the abnormal work equipment in the target unit;
step S603, adjusting the actual structured operation diagram corresponding to the target working unit according to the updating working unit to obtain an updating structured operation diagram corresponding to the updating working unit;
step S604, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the updated structured operation diagram corresponding to each work unit except the target work unit.
Specifically, in order to determine an operation decision again, the present embodiment needs to determine a working device causing the abnormal operation of the target working unit, that is, an abnormal working device. In this embodiment, the definition of the abnormal operating device is that the node deviation value is greater than the second threshold, and it can be understood that the node deviation value may reflect a difference between a current operating state and a normal operating state of one operating device, so that if the node deviation value of one operating device is too large, it indicates that the operating state of the operating device is abnormal. And eliminating the abnormal working equipment in the target working unit to obtain an updated working unit corresponding to the target working unit because the abnormal working equipment cannot normally execute the task. It is understood that the working devices included in the updating working unit are all in a normal operating state. And then, adjusting the original actual structured working diagram according to the updating working unit to obtain an updated structured working diagram. And finally, re-determining the operation decision of the target power grid based on the actual structural operation diagram and the updated structural operation diagram of other normally-operated working units.
In one implementation, the plurality of working units comprise a power transmission unit, a power transformation unit and a power distribution unit; when the target working unit is a power transmission unit, the operation decision is a power transmission decision and a power transformation decision; when the target working unit is a power transformation unit, the operation decision is a power transmission decision, a power transformation decision and a power distribution decision; and when the target working unit is a power distribution unit, the operation decision is a power transformation decision and a power distribution decision.
Specifically, the system tasks of the target grid are generally divided into transmission, transformation, and distribution tasks, and thus the present embodiment divides the target grid into transmission units, transformation units, and distribution units based on the task type. When the target working unit is a power transmission unit, the power transmission function of the target power grid is possibly influenced, and the power transformation function of the target power grid is indirectly influenced, so that the original power transmission decision and power transformation decision of the target power grid need to be updated; when the target working unit is a power transformation unit, the power transformation function of the target power grid is possibly influenced, and the power transformation function of the target power grid indirectly influences the power transmission and distribution functions of the target power grid, so that the original power transmission decision, power transformation decision and power distribution decision of the target power grid need to be updated; when the target working unit is a power distribution unit, it indicates that the power distribution function of the target power grid may be affected, and because the power distribution function of the target power grid indirectly affects the power transformation and distribution functions of the target power grid, the original power transformation decision and power distribution decision of the target power grid need to be updated.
Based on the above embodiment, the present invention further provides a perceptual decision device based on edge calculation, as shown in fig. 2, the device includes:
the data acquisition module 01 is configured to acquire actual structured operation diagrams corresponding to a plurality of working units in a target power grid, where the plurality of working units are used to execute different functions, and each actual structured operation diagram is used to reflect an interaction characteristic between a plurality of working devices corresponding to one working unit;
acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit;
the target sensing module 02 is used for determining operation deviation values corresponding to the plurality of working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the plurality of working units respectively;
determining target working units according to the operation deviation values respectively corresponding to the working units, wherein the target working units are the working units with the operation deviation values larger than a first threshold value;
the operation decision module 03 is configured to acquire an environmental monitoring data set corresponding to the target working unit, where the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group includes one or more edge terminals, and the edge terminals are respectively configured to acquire different types of environmental monitoring data;
and when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit corresponding to the plurality of operation units respectively.
Based on the above embodiments, the present invention further provides a terminal, and a schematic block diagram thereof may be as shown in fig. 3. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is configured to provide computing and control capabilities. The memory of the terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a perceptual decision method based on edge computation. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.
It will be understood by those skilled in the art that the block diagram shown in fig. 3 is a block diagram of only a portion of the structure associated with the inventive arrangements and is not intended to limit the terminals to which the inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may have some components combined, or may have a different arrangement of components.
In one implementation, one or more programs are stored in a memory of the terminal and configured to be executed by one or more processors include instructions for performing a perceptual decision method based on edge computations.
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, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the present invention discloses a perception decision method based on edge calculation, which includes obtaining actual structural operation diagrams corresponding to a plurality of working units in a target power grid, where the plurality of working units are used to execute different functions, and each actual structural operation diagram is used to reflect an interaction characteristic between a plurality of working devices corresponding to one working unit; acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit; determining operation deviation values corresponding to the working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the working units respectively; determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value; acquiring an environment monitoring data set corresponding to the target working unit, wherein the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises one or a plurality of edge terminals, and the edge terminals are respectively used for acquiring different types of environment monitoring data; and when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units. The method and the device can automatically sense the abnormal working unit in the target power grid and automatically adjust the operation decision of the target power grid according to the abnormal working unit. The problem of in the prior art, because the power grid system adopts the operation decision-making procedure that artifical preset, therefore when the equipment damaged condition appears, be difficult to in time adjust the operation decision-making of power grid system is solved.
It will be understood that the invention is not limited to the examples described above, but that modifications and variations will occur to those skilled in the art in light of the above teachings, and that all such modifications and variations are considered to be within the scope of the invention as defined by the appended claims.
Claims (8)
1. A perceptual decision method based on edge computation, the method comprising:
acquiring actual structural operation diagrams corresponding to a plurality of working units in a target power grid respectively, wherein the working units are used for executing different functions respectively, and each actual structural operation diagram is used for reflecting the interaction characteristics among a plurality of working devices corresponding to one working unit;
acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit;
determining operation deviation values corresponding to the working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the working units respectively;
determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value;
acquiring an environment monitoring data set corresponding to the target working unit, wherein the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises a plurality of edge terminals, and the edge terminals are respectively used for acquiring different types of environment monitoring data;
when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units;
the determining operation deviation values respectively corresponding to the plurality of working units according to the standard structured operation diagram and the actual structured operation diagram respectively corresponding to the plurality of working units comprises:
determining a node deviation value corresponding to each node in each working unit according to the standard structured operation diagram and the actual structured operation diagram corresponding to each working unit, wherein each node deviation value is determined based on the difference between the characteristics of each connecting line corresponding to the node in the standard structured operation diagram and the actual structured operation diagram;
determining the operation deviation value corresponding to each working unit according to the node deviation value corresponding to each node in each working unit;
the determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units comprises:
determining abnormal working equipment in the target working unit, wherein the node deviation value corresponding to the abnormal working equipment is greater than a second threshold value;
generating an updating work unit according to the target work unit and the abnormal work equipment, wherein the updating work unit comprises all the work equipment except the abnormal work equipment in the target work unit;
adjusting the actual structured operation diagram corresponding to the target working unit according to the updating working unit to obtain an updated structured operation diagram corresponding to the updating working unit;
and determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the updated structured operation diagram respectively corresponding to all the working units except the target working unit.
2. The perception decision method based on edge computing according to claim 1, wherein the obtaining of the actual structured operation diagram corresponding to each of the plurality of working units in the target power grid includes:
acquiring actual working data corresponding to a plurality of working units respectively, wherein the actual working data corresponding to each working unit is used for reflecting interactive data among a plurality of working devices corresponding to the working unit;
and determining the actual structured operation diagrams corresponding to the working units respectively according to the actual working data corresponding to the working units respectively.
3. The perception decision method based on edge computing according to claim 2, wherein each of the actual structured operation graphs includes a plurality of nodes, the plurality of nodes respectively correspond to different working devices, and characteristics of connection lines between the plurality of nodes are used for reflecting interaction characteristics between the plurality of working devices.
4. The perceptual decision method based on edge computing as defined in claim 1, wherein the environment monitoring data set comprises regional video data, regional sound data, regional temperature data, and regional humidity data corresponding to the target work unit.
5. The perceptual decision method based on edge computing of claim 1, wherein the plurality of work units comprise a power transmission unit, a power transformation unit and a power distribution unit; when the target working unit is a power transmission unit, the operation decision is a power transmission decision and a power transformation decision; when the target working unit is a power transformation unit, the operation decision is a power transmission decision, a power transformation decision and a power distribution decision; and when the target working unit is a power distribution unit, the operation decision is a power transformation decision and a power distribution decision.
6. An apparatus for perceptual decision-making based on edge computation, the apparatus comprising:
the data acquisition module is used for acquiring actual structured operation diagrams corresponding to a plurality of working units in a target power grid respectively, wherein the working units are used for executing different functions respectively, and each actual structured operation diagram is used for reflecting the interaction characteristics among a plurality of working devices corresponding to one working unit;
acquiring standard structured operation diagrams corresponding to a plurality of working units respectively, wherein the standard structured operation diagram corresponding to each working unit is generated based on the standard operation state of the working unit;
the target sensing module is used for determining operation deviation values corresponding to the working units according to the standard structured operation diagram and the actual structured operation diagram corresponding to the working units respectively;
determining a target working unit according to the operation deviation values respectively corresponding to the working units, wherein the target working unit is a working unit of which the operation deviation value is greater than a first threshold value;
the operation decision module is used for acquiring an environment monitoring data set corresponding to the target working unit, wherein the monitoring data set is acquired based on an edge terminal group corresponding to the target working unit, the edge terminal group comprises a plurality of edge terminals, and the edge terminals are respectively used for acquiring different types of environment monitoring data;
when the environment monitoring data set meets a preset environment standard, determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units;
the determining operation deviation values respectively corresponding to the plurality of working units according to the standard structured operation diagram and the actual structured operation diagram respectively corresponding to the plurality of working units comprises:
determining a node deviation value corresponding to each node in each working unit according to the standard structured operation diagram and the actual structured operation diagram corresponding to each working unit, wherein each node deviation value is determined based on the difference between the characteristics of each connecting line corresponding to the node in the standard structured operation diagram and the actual structured operation diagram;
determining the operation deviation value corresponding to each working unit according to the node deviation value corresponding to each node in each working unit;
the determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the target operation unit respectively corresponding to the plurality of operation units comprises:
determining abnormal working equipment in the target working unit, wherein the node deviation value corresponding to the abnormal working equipment is greater than a second threshold value;
generating an updating work unit according to the target work unit and the abnormal work equipment, wherein the updating work unit comprises all the work equipment except the abnormal work equipment in the target work unit;
adjusting the actual structured operation diagram corresponding to the target working unit according to the updating working unit to obtain an updated structured operation diagram corresponding to the updating working unit;
and determining an operation decision corresponding to the target power grid according to the actual structured operation diagram and the updated structured operation diagram respectively corresponding to all the working units except the target working unit.
7. A terminal, comprising a memory and one or more processors; the memory stores one or more programs; the program comprises instructions for performing the edge-computation-based perceptual decision method of any one of claims 1-5; the processor is configured to execute the program.
8. A computer-readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to perform the steps of the edge-computing-based perceptual decision method of any one of claims 1 to 5.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104680260A (en) * | 2015-03-17 | 2015-06-03 | 云南电力调度控制中心 | Method and system for establishing power grid visualized perceptual model |
| CN113222370A (en) * | 2021-04-28 | 2021-08-06 | 深圳供电局有限公司 | Electric power system risk early warning method, device, equipment and storage medium |
| CN113642837A (en) * | 2021-07-02 | 2021-11-12 | 国网甘肃省电力公司信息通信公司 | Power grid dispatching system based on potential state perception |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9948100B2 (en) * | 2011-09-16 | 2018-04-17 | Varentec, Inc. | Zero droop voltage control for smart inverters |
| JP2023518258A (en) * | 2020-03-20 | 2023-04-28 | セクション．アイオー インコーポレイテッド | Systems, methods, computing platforms, and storage media for managing distributed edge computing systems utilizing adaptive edge engines |
| US20220253767A1 (en) * | 2021-02-09 | 2022-08-11 | Verizon Patent And Licensing Inc. | Computerized system and method for dynamic task management and execution |
| CN114856941A (en) * | 2022-05-18 | 2022-08-05 | 江苏科技大学 | Offshore wind power plant and unit fault diagnosis operation and maintenance system and diagnosis operation and maintenance method thereof |
-
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104680260A (en) * | 2015-03-17 | 2015-06-03 | 云南电力调度控制中心 | Method and system for establishing power grid visualized perceptual model |
| CN113222370A (en) * | 2021-04-28 | 2021-08-06 | 深圳供电局有限公司 | Electric power system risk early warning method, device, equipment and storage medium |
| CN113642837A (en) * | 2021-07-02 | 2021-11-12 | 国网甘肃省电力公司信息通信公司 | Power grid dispatching system based on potential state perception |
Non-Patent Citations (1)
| Title |
|---|
| 基于巡视文本挖掘的配电设备运行环境风险预测;周远翔 等;《高电压技术》;20220430;第48卷(第4期);第1213-1225页 * |
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