CN117592817A - Power grid disaster processing method, device, equipment and medium - Google Patents
Power grid disaster processing method, device, equipment and medium Download PDFInfo
- Publication number
- CN117592817A CN117592817A CN202311690597.2A CN202311690597A CN117592817A CN 117592817 A CN117592817 A CN 117592817A CN 202311690597 A CN202311690597 A CN 202311690597A CN 117592817 A CN117592817 A CN 117592817A
- Authority
- CN
- China
- Prior art keywords
- grid
- disaster
- candidate
- preset
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000003672 processing method Methods 0.000 title abstract description 11
- 238000012545 processing Methods 0.000 claims abstract description 41
- 238000000034 method Methods 0.000 claims abstract description 29
- 239000011159 matrix material Substances 0.000 claims description 31
- 238000001556 precipitation Methods 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims 3
- 238000004590 computer program Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 10
- 230000006870 function Effects 0.000 description 7
- 230000008439 repair process Effects 0.000 description 7
- 238000004891 communication Methods 0.000 description 6
- 230000003287 optical effect Effects 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 239000013307 optical fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 235000017166 Bambusa arundinacea Nutrition 0.000 description 1
- 235000017491 Bambusa tulda Nutrition 0.000 description 1
- 241001330002 Bambuseae Species 0.000 description 1
- 235000015334 Phyllostachys viridis Nutrition 0.000 description 1
- 239000011425 bamboo Substances 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000004883 computer application Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000000638 solvent extraction Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- Databases & Information Systems (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Operations Research (AREA)
- Remote Sensing (AREA)
- Data Mining & Analysis (AREA)
- General Engineering & Computer Science (AREA)
- Alarm Systems (AREA)
Abstract
The embodiment of the disclosure relates to a power grid disaster processing method, a device, equipment and a medium, wherein the method comprises the following steps: dividing a target grid region into A.times.B candidate grid subregions according to a preset grid division strategy, wherein A and B are natural numbers larger than 0; acquiring a plurality of grid disaster parameter values of each candidate grid subarea in the A.times.B candidate grid subareas; determining disaster index values of each candidate grid subarea according to the grid disaster parameter values; determining a target candidate grid region meeting preset disaster processing conditions in the grid subregions of the A.times.B candidate grids according to the disaster index values; and executing preset power grid disaster processing operation on the target candidate power grid area. In the technical scheme, the area with large power grid disaster risk can be determined in advance so as to perform the processing of the power grid disaster in advance, and the method has important significance on the safety of the power grid.
Description
Technical Field
The disclosure relates to the technical field of computer application, and in particular relates to a power grid disaster processing method, device, equipment and medium.
Background
The disaster treatment of the power grid has important significance to the safety of the power grid, for example, a heavy rain disaster can generate serious harm to the power grid, long-time heavy rain can cause flood, submerge power facilities such as substations, cable ditches and the like, cause equipment faults and damages, a large amount of rainwater can cause landslide, cause line towers to collapse, and meanwhile, strong wind accompanied by heavy rain can cause tower falling, broken lines, tree bamboo to topple and crush lines and the like.
In the related art, in order to avoid power grid disasters, emergency repair equipment is arranged in advance, emergency repair can be performed on disaster-stricken equipment in time after disasters such as heavy rain occur, and power supply is quickly recovered, but because the number of the emergency repair equipment is limited, the area with large risk of the power grid heavy rain disasters is determined in advance, and the emergency repair equipment has important significance for reducing the threat of disasters such as heavy rain to the power grid to the greatest extent.
Disclosure of Invention
In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides a method, an apparatus, a device, and a medium for processing a power grid disaster, where a power grid disaster risk is large can be determined in advance, so as to perform advanced power grid disaster processing, which has an important meaning on power grid safety.
The embodiment of the disclosure provides a power grid disaster processing method, which comprises the following steps: dividing a target grid region into A.times.B candidate grid subregions according to a preset grid division strategy, wherein A and B are natural numbers larger than 0; acquiring a plurality of grid disaster parameter values of each candidate grid subarea in the A.times.B candidate grid subareas; determining disaster index values of the grid subareas of each candidate grid according to the grid disaster parameter values; determining a target candidate grid region meeting preset disaster treatment conditions in the A.times.B candidate grid subregions according to the disaster index values;
the embodiment of the disclosure also provides a power grid disaster treatment device, which comprises: the dividing module is used for dividing the target power grid area into A.times.B candidate power grid subareas according to a preset grid dividing strategy, wherein A and B are natural numbers larger than 0; the acquisition module is used for acquiring a plurality of grid disaster parameter values of each candidate grid subarea in the A.times.B candidate grid subareas; the first determining module is used for determining disaster index values of the grid subareas of each candidate power grid according to the grid disaster parameter values; the second determining module is used for determining a target candidate grid area meeting preset disaster processing conditions in the A-B candidate grid subareas according to the disaster index value; and the processing module is used for executing preset power grid disaster processing operation on the target candidate power grid area.
The embodiment of the disclosure also provides an electronic device, which comprises: a processor; a memory for storing the processor-executable instructions; the processor is configured to read the executable instructions from the memory and execute the instructions to implement the power grid disaster processing method provided by the embodiment of the disclosure.
The embodiment of the disclosure also provides a computer readable storage medium, wherein the storage medium stores a computer program, and the computer program is used for executing the power grid disaster processing method provided by the embodiment of the disclosure.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages:
according to the grid disaster processing scheme provided by the embodiment of the disclosure, a target grid area is divided into A x B candidate grid subareas according to a preset grid division strategy, wherein A and B are natural numbers larger than 0, a plurality of grid disaster parameter values of each candidate grid subarea in the A x B candidate grid subareas are obtained, a disaster index value of each candidate grid subarea is determined according to the plurality of grid disaster parameter values, a target candidate grid area meeting preset disaster processing conditions is determined in the A x B candidate grid subareas according to the disaster index value, and preset grid disaster processing operation is performed on the target candidate grid area. In the technical scheme, the area with large power grid disaster risk can be determined in advance so as to perform the processing of the power grid disaster in advance, and the method has important significance on the safety of the power grid.
Drawings
The above and other features, advantages, and aspects of embodiments of the present disclosure will become more apparent by reference to the following detailed description when taken in conjunction with the accompanying drawings. The same or similar reference numbers will be used throughout the drawings to refer to the same or like elements. It should be understood that the figures are schematic and that elements and components are not necessarily drawn to scale.
Fig. 1 is a schematic flow chart of a power grid disaster processing method provided in an embodiment of the disclosure;
fig. 2 is a schematic diagram of a power grid disaster processing scenario provided in an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a power grid disaster processing device according to an embodiment of the disclosure;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Detailed Description
Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure have been shown in the accompanying drawings, it is to be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but are provided to provide a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.
It should be understood that the various steps recited in the method embodiments of the present disclosure may be performed in a different order and/or performed in parallel. Furthermore, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the present disclosure is not limited in this respect.
The term "including" and variations thereof as used herein are intended to be open-ended, i.e., including, but not limited to. The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. Related definitions of other terms will be given in the description below.
It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different devices, modules, or units and are not used to define an order or interdependence of functions performed by the devices, modules, or units.
It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.
The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.
In order to solve the above-mentioned problems, the embodiments of the present disclosure provide a power grid disaster processing method, and the method is described below with reference to specific embodiments. Among the disasters mentioned in the embodiments of the present disclosure include, but are not limited to, disasters that may bring about potential safety hazards to the power grid, such as heavy rain, snow storm, and the like.
Fig. 1 is a flow chart of a power grid disaster processing method according to an embodiment of the present disclosure, where the method may be performed by a power grid disaster processing device, and the device may be implemented by software and/or hardware, and may generally be integrated in an electronic device. As shown in fig. 1, the method includes:
step 101, dividing a target grid region into A.times.B candidate grid sub-regions according to a preset grid division strategy, wherein A and B are natural numbers larger than 0.
The target grid region may be understood as a region to be evaluated for risk of a grid disaster, and in order to determine a region with a higher risk of the grid disaster in the target grid region, in an embodiment of the present disclosure, the target grid region is divided into a×b candidate grid subregions according to a preset grid region division policy, where a and B are natural numbers greater than 0.
In different application scenarios, the grid region division policies for dividing the target grid region are different, and in some possible embodiments, the grid region division policies are: dividing the target grid region into a plurality of B candidate grid sub-regions according to preset size information, for example, the preset size information is square size information with a side length of S, and the target grid region may be equally divided into a plurality of B candidate grid sub-regions, where a specific numerical value of a is related to an actual application scenario, for example, when the target grid region is 100KM by 200KM and S is 10KM, a by 20.
In the actual implementation process, in order to avoid the problem of difficult division caused by the size and shape diversity of the target grid region, the target grid region may be preprocessed according to a preset shape, for example, a minimum bounding box of the target grid region is generated according to the preset shape, and the region where the minimum bounding box is located is divided into a×b candidate grid subregions at equal intervals.
For example, as shown in fig. 2, after generating the bounding box Q2 of the target grid area Q1 according to a preset shape (in this embodiment, a rectangle) is generated, the bounding box Q2 is divided according to a preset interval to generate a×b candidate grid sub-areas. The preset interval can be set according to application scenes.
Step 102, obtaining a plurality of grid disaster parameter values of each candidate grid subarea in the A.times.B candidate grid subareas.
After splitting the target grid region into a plurality of candidate grid sub-regions, in order to evaluate the disaster coefficient of each candidate grid sub-region, a plurality of grid disaster parameter values of each candidate grid sub-region in the a×b candidate grid sub-regions are obtained, wherein in this embodiment, the grid disaster parameter values for evaluating the disaster coefficient of each candidate grid sub-region are a plurality of, thereby ensuring the accuracy of the evaluation.
It should be noted that, in different application scenarios, the parameters included in the plurality of grid disaster parameter values are different, and in some possible embodiments, considering the plurality of grid disaster parameter values of each candidate grid sub-area, the method includes: each candidate grid sub-region accumulates precipitation predicted values in a first preset time period (wherein the first preset time period may be a time period of 24 hours after the current time, etc., the accumulated precipitation predicted values may be obtained by learning the historical accumulated precipitation, etc.), each candidate grid sub-region accumulates average wind speed predicted values in a second preset time period (wherein the first preset time period may be a time period of 24 hours after the current time, etc., the average wind speed predicted values may be obtained by learning the historical average wind speed values, etc.), the average elevation value of each candidate grid sub-region, the accumulated voltage levels of all grid lines included in the grid sub-region to which the candidate grid belongs, the accumulated active power delivered by all grid lines included in the grid sub-region to which the candidate grid sub-region belongs, etc.
And step 103, determining disaster index values of each candidate grid subarea according to the grid disaster parameter values.
The disaster index value is used for evaluating the risk of occurrence of disasters of each candidate grid subarea.
In the different application scenarios, the manner of determining the disaster index value of each candidate grid sub-area according to the plurality of grid disaster parameter values is different, and the following is exemplified:
in some possible embodiments, according to the a×b candidate grid latticesAll grid disaster parameter values of the area construct a first matrix, wherein each row or each column in the first matrix may be a plurality of grid disaster parameter values of the corresponding candidate grid sub-area, for example, a plurality of grid disaster parameter values of each candidate grid sub-area, including: each candidate grid sub-region accumulates precipitation predictions (denoted as R) over a first preset period of time ij (mm) (i=1, 2, …, a; j=1, 2, …, B), where i in this embodiment is the ith row in a×b, j is the jth column in a×b), the average wind speed prediction value (W) for each candidate grid sub-region within a second preset time period ij (m/s) (i=1, 2, …, a; j=1, 2, …, B)), the average elevation value (noted as H) of each candidate grid sub-area ij (m) (i=1, 2, …, a; j=1, 2, …, B)), the voltage class accumulated value (denoted U) of all grid lines contained in the grid sub-area of the belonging grid ij (kV) (i=1, 2, …, a; j=1, 2, …, B)), the sum of the active power delivered by all grid lines contained in the grid sub-area of the belonging grid (noted P ij (mm) (i=1, 2, …, a; j=1, 2, …, B)), then the first matrix constructed may be:
for convenience of subsequent calculation, the first matrix C may be also noted as:
further, after determining the first matrix, calculating the first matrix according to a first preset formula to obtain a second matrix, where the first preset formula may be a formula for forming a product budget for a weight matrix of a plurality of grid disaster parameter values included in the first matrix, where the weight matrix includes a weight coefficient of each grid disaster parameter value in each candidate grid sub-area, and thus the second matrix is a matrix that considers a weight of each grid disaster parameter value in each candidate grid sub-area.
In some possible embodiments, if the second matrix to be calculated isThe first preset formula includes: />Wherein d kq C for the kth row and the qth column matrix element in the second matrix kq For the kth row and qth column matrix elements in the first matrix, k=1, 2. q=1, 2,..w, W is the number of grid disaster parameter values, e.g., when the plurality of grid disaster parameter values for each candidate grid sub-area, comprises: and when the precipitation quantity predicted value is accumulated in each candidate grid subarea in a first preset time period, the average wind speed predicted value is accumulated in each candidate grid subarea in a second preset time period, the average altitude value of each candidate grid subarea, the voltage grade accumulated value of all grid lines contained in the grid subarea, and the active power accumulated value transmitted by all grid lines contained in the grid subarea are equal to 5.
Furthermore, according to a second preset formula, calculating a second matrix to obtain disaster index values of each candidate grid subarea.
For example, when the second matrix is calculated for the weight matrix including the weight coefficient of each grid disaster parameter value in each candidate grid sub-area, the second preset formula is the sum of the product values corresponding to all grid disaster parameter values in each candidate grid sub-area after calculating the product value of the weight coefficient of each grid disaster parameter value and the corresponding grid disaster parameter value.
For example, when the second matrix is the D matrix, the second preset formula is:
wherein the E k For disaster index values corresponding to the candidate grid sub-areas,representation pairAnd rounding upwards, wherein disaster index values of the ith row and the jth column of the candidate grid subareas in the A-B candidate grid subareas are as follows:
I ij ＝E (i-1)·B+j 。
and 104, determining a target candidate grid region meeting preset disaster processing conditions in the grid subregions of the A.times.B candidate grids according to the disaster index values.
In one embodiment of the present disclosure, after determining the disaster index value, determining a target candidate grid area satisfying a preset disaster processing condition according to the disaster index value in the a×b candidate grid sub-areas, where the target candidate grid area may be understood as an area with a large disaster risk, and the like.
It should be noted that, in different application scenarios, the manner of determining the target candidate grid area satisfying the preset disaster processing condition in the a×b candidate grid sub-areas according to the disaster index value is different, and examples are as follows:
in some possible embodiments, the a×b candidate grid sub-areas are ordered according to the order of the disaster index values from high to low to generate an ordering result, and a preset number of candidate grid sub-areas are determined as target candidate grid areas according to the order of the front to back in the ordering result, where the preset number may be calibrated according to the scene requirement, for example, the preset number may be 7.
In some possible embodiments, a disaster index threshold may be set according to a scene requirement, and a candidate grid subarea with a disaster index value greater than the disaster index threshold is determined as a target candidate grid area.
And 105, executing preset power grid disaster processing operation on the target candidate power grid area.
In one embodiment of the present disclosure, after determining the target candidate grid region, a grid disaster treatment reminder for the target candidate grid region may be sent as a grid disaster treatment operation for the target candidate grid region.
In one embodiment of the disclosure, after determining the target candidate power grid region, a repair equipment arrangement reminding message may be sent to a preset disaster repair equipment platform as power grid disaster processing operation, so as to facilitate pre-arrangement of disaster repair equipment and the like in the target candidate power grid region.
In summary, according to the grid disaster processing scheme of the embodiment of the present disclosure, a target grid area is divided into a×b candidate grid sub-areas according to a preset grid division policy, where a and B are natural numbers greater than 0, a plurality of grid disaster parameter values of each candidate grid sub-area in the a×b candidate grid sub-areas are obtained, a disaster index value of each candidate grid sub-area is determined according to the plurality of grid disaster parameter values, a target candidate grid area satisfying a preset disaster processing condition is determined in the a×b candidate grid sub-areas according to the disaster index value, and a preset grid disaster processing operation is performed on the target candidate grid area. In the technical scheme, the area with large power grid disaster risk can be determined in advance so as to perform the processing of the power grid disaster in advance, and the method has important significance on the safety of the power grid.
In order to achieve the above embodiments, the present disclosure further provides a power grid disaster processing device.
Fig. 3 is a schematic structural diagram of a power grid disaster processing device according to an embodiment of the present disclosure, where the device may be implemented by software and/or hardware, and may be generally integrated in an electronic device to perform power grid disaster processing. As shown in fig. 3, the apparatus includes: a partitioning module 310, an acquisition module 320, a first determination module 330, a second determination module 340, a processing module 350, wherein,
the dividing module 310 is configured to divide the target grid area into a plurality of a×b candidate grid sub-areas according to a preset grid division policy, where a and B are natural numbers greater than 0;
an obtaining module 320, configured to obtain a plurality of grid disaster parameter values of each candidate grid sub-area of the a×b candidate grid sub-areas;
a first determining module 330, configured to determine a disaster index value of each candidate grid sub-area according to a plurality of grid disaster parameter values;
a second determining module 340, configured to determine, according to the disaster index value, a target candidate grid area satisfying a preset disaster processing condition from the a×b candidate grid sub-areas;
and the processing module 350 is configured to perform a preset power grid disaster processing operation on the target candidate power grid area.
The power grid disaster processing device provided by the embodiment of the disclosure can execute the power grid disaster processing method provided by any embodiment of the disclosure, and has corresponding functional modules and beneficial effects of the execution method, and is not described herein again.
To achieve the above embodiments, the present disclosure also proposes a computer program product comprising a computer program/instruction which, when executed by a processor, implements the grid disaster handling method in the above embodiments.
Fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the disclosure.
Referring now in particular to fig. 4, a schematic diagram of an electronic device 400 suitable for use in implementing embodiments of the present disclosure is shown. The electronic device 400 in the embodiments of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 4 is merely an example and should not be construed to limit the functionality and scope of use of the disclosed embodiments.
As shown in fig. 4, the electronic device 400 may include a processor (e.g., a central processing unit, a graphics processor, etc.) 401 that may perform various suitable actions and processes in accordance with programs stored in a read-only memory (ROM) 402 or programs loaded from a memory 408 into a Random Access Memory (RAM) 403. In the RAM 403, various programs and data necessary for the operation of the electronic device 400 are also stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
In general, the following devices may be connected to the I/O interface 405: input devices 406 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; an output device 407 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; a memory 408 including, for example, magnetic tape, hard disk, etc.; and a communication device 409. The communication means 409 may allow the electronic device 400 to communicate with other devices wirelessly or by wire to exchange data. While fig. 4 shows an electronic device 400 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a non-transitory computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via communications device 409, or from memory 408, or from ROM 402. When executed by the processor 401, performs the above-described functions defined in the grid disaster handling method of the embodiments of the present disclosure.
It should be noted that the computer readable medium described in the present disclosure may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having 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. In the context of this disclosure, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present disclosure, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.
In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.
The computer readable medium may be contained in the electronic device; or may exist alone without being incorporated into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: dividing a target grid region into A.times.B candidate grid subregions according to a preset grid division strategy, wherein A and B are natural numbers larger than 0, acquiring a plurality of grid disaster parameter values of each candidate grid subregion in the A.times.B candidate grid subregions, determining a disaster index value of each candidate grid subregion according to the plurality of grid disaster parameter values, determining a target candidate grid region meeting preset disaster processing conditions in the A.times.B candidate grid subregions according to the disaster index values, and executing preset grid disaster processing operation on the target candidate grid region. In the technical scheme, the area with large power grid disaster risk can be determined in advance so as to perform the processing of the power grid disaster in advance, and the method has important significance on the safety of the power grid.
The electronic device may write computer program code for performing the operations of the present disclosure in one or more programming languages, including, but not limited to, an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present disclosure may be implemented by means of software, or may be implemented by means of hardware. Wherein the names of the units do not constitute a limitation of the units themselves in some cases.
The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable 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. 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.
The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by persons skilled in the art that the scope of the disclosure referred to in this disclosure is not limited to the specific combinations of features described above, but also covers other embodiments which may be formed by any combination of features described above or equivalents thereof without departing from the spirit of the disclosure. Such as those described above, are mutually substituted with the technical features having similar functions disclosed in the present disclosure (but not limited thereto).
Moreover, although operations are depicted in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in sequential order. In certain circumstances, multitasking and parallel processing may be advantageous. Likewise, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of the present disclosure. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the subject matter has been described in language specific to structural features and/or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are example forms of implementing the claims.
Claims (10)
1. The power grid disaster treatment method is characterized by comprising the following steps of:
dividing a target grid region into A.times.B candidate grid subregions according to a preset grid division strategy, wherein A and B are natural numbers larger than 0;
acquiring a plurality of grid disaster parameter values of each candidate grid subarea in the A.times.B candidate grid subareas;
determining disaster index values of the grid subareas of each candidate grid according to the grid disaster parameter values;
determining a target candidate grid region meeting preset disaster treatment conditions in the A.times.B candidate grid subregions according to the disaster index values;
and executing preset power grid disaster processing operation on the target candidate power grid area.
2. The method of claim 1, wherein the dividing the target grid region into a-B candidate grid sub-regions according to a preset grid division strategy comprises:
dividing the target grid region into A.times.B candidate grid sub-regions according to preset size information.
3. The method of claim 1, wherein the plurality of grid disaster parameter values for each candidate grid sub-area comprises:
and accumulating a plurality of precipitation predicted values of each candidate grid subarea in a first preset time period, average wind speed predicted values of each candidate grid subarea in a second preset time period, average elevation values of each candidate grid subarea, voltage grade accumulated values of all grid lines contained in the grid subarea, and active power accumulated values transmitted by all grid lines contained in the grid subarea.
4. A method according to claim 1 or 3, wherein said determining a disaster index value for each candidate grid sub-area from said plurality of grid disaster parameter values comprises:
constructing a first matrix according to all grid disaster parameter values of the grid subareas of the A.times.B candidate grids;
calculating the first matrix according to a first preset formula to obtain a second matrix;
and calculating the second matrix according to a second preset formula to obtain disaster index values of each candidate grid subarea.
5. The method of claim 4, wherein the second matrix is:
the first preset formula includes:wherein said d kq C for the kth row and the qth column matrix element in the second matrix kq For the kth row and qth column matrix elements in the first matrix, k=1, 2; q=1, 2,..w, W is the number of the plurality of grid disaster parameter values.
6. The method of claim 5, wherein the second predetermined formula comprises:
wherein the E k For disaster index values corresponding to the candidate grid sub-areas,representation pairAnd (5) rounding upwards.
7. The method of claim 6, wherein the disaster index value of the ith row and jth column candidate grid sub-areas in the a x B candidate grid sub-areas is:
I ij ＝E (i-1)·B+j 。
8. the method of claim 1, wherein the determining a target candidate grid area satisfying a preset disaster treatment condition from among the a x B candidate grid sub-areas according to the disaster index value comprises:
sequencing the A.times.B candidate grid subareas according to the sequence from high to low of the disaster index values to generate sequencing results;
and determining a preset number of candidate grid subareas as the target candidate grid areas according to the sequence from front to back in the sequencing result.
9. A power grid disaster treatment device, characterized by comprising:
the dividing module is used for dividing the target power grid area into A.times.B candidate power grid subareas according to a preset grid dividing strategy, wherein A and B are natural numbers larger than 0;
the acquisition module is used for acquiring a plurality of grid disaster parameter values of each candidate grid subarea in the A.times.B candidate grid subareas;
the first determining module is used for determining disaster index values of the grid subareas of each candidate power grid according to the grid disaster parameter values;
the second determining module is used for determining a target candidate grid area meeting preset disaster processing conditions in the A-B candidate grid subareas according to the disaster index value;
and the processing module is used for executing preset power grid disaster processing operation on the target candidate power grid area.
10. An electronic device, the electronic device comprising:
a processor;
a memory for storing the processor-executable instructions;
the processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the method for handling a power grid disaster according to any one of claims 1 to 8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311690597.2A CN117592817A (en) | 2023-12-08 | 2023-12-08 | Power grid disaster processing method, device, equipment and medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311690597.2A CN117592817A (en) | 2023-12-08 | 2023-12-08 | Power grid disaster processing method, device, equipment and medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117592817A true CN117592817A (en) | 2024-02-23 |
Family
ID=89921873
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311690597.2A Pending CN117592817A (en) | 2023-12-08 | 2023-12-08 | Power grid disaster processing method, device, equipment and medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117592817A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118228161A (en) * | 2024-04-11 | 2024-06-21 | 武汉翌晟天成科技有限公司 | Method and system for analyzing and processing power grid disasters |
-
2023
- 2023-12-08 CN CN202311690597.2A patent/CN117592817A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118228161A (en) * | 2024-04-11 | 2024-06-21 | 武汉翌晟天成科技有限公司 | Method and system for analyzing and processing power grid disasters |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117592817A (en) | Power grid disaster processing method, device, equipment and medium | |
| CN110309961A (en) | Fire alarm method and apparatus | |
| CN115103210B (en) | Information processing method, device, terminal and storage medium | |
| CN113344737B (en) | Device control method, device, electronic device and computer readable medium | |
| CN113869599A (en) | Fish epidemic disease development prediction method, system, equipment and medium | |
| CN117541058A (en) | Forest fire risk assessment method and device and electronic equipment | |
| CN110633819B (en) | Crowd evacuation guiding method, device, medium and electronic equipment | |
| CN115359663B (en) | Mountain road disaster section disaster-resistant toughness calculation method and device and electronic equipment | |
| CN113837814B (en) | Method and device for predicting quantity of released resources, readable medium and electronic equipment | |
| CN111582456B (en) | Method, apparatus, device and medium for generating network model information | |
| CN110796144B (en) | License plate detection method, device, equipment and storage medium | |
| CN117592785A (en) | Risk processing method, device, equipment and medium for power grid line | |
| CN117805549A (en) | Fault reminding method, device, equipment and medium for power grid line | |
| CN116070947B (en) | Simulation early warning method, device, equipment and medium for safety production event | |
| CN117557101A (en) | Power grid storm flood disaster prediction method and device and electronic equipment | |
| CN115379243B (en) | CDN scheduling method, device, equipment and storage medium | |
| CN116577684A (en) | Battery remaining life prediction method, system, electronic device and storage medium | |
| CN116757443B (en) | Novel power line loss rate prediction method and device for power distribution network, electronic equipment and medium | |
| CN115689444B (en) | Logistics automatic monitoring method, device, equipment and medium based on historical cases | |
| CN111783390B (en) | Dimension label adjusting method and device and electronic equipment | |
| CN118536021A (en) | Real-time groundwater level dynamic monitoring system based on multiple sensors | |
| US20230009941A1 (en) | Method of processing data for target model, electronic device, and storage medium | |
| CN117196534A (en) | Method, device, system, equipment and medium for determining construction progress of photovoltaic power station | |
| CN116340632A (en) | Object recommendation method, device, medium and electronic equipment | |
| CN117748491A (en) | Processing method, device, equipment and medium of power grid dispatching instruction |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |