Distribution method, device and equipment for monitoring points of power transmission line and storage medium

Abstract

The embodiment of the invention provides a distribution method and device for monitoring points of a power transmission line, equipment and a storage medium. The method comprises the following steps: acquiring geographic information, meteorological information and power grid information of a target area; wherein the target area is pre-divided into a plurality of grids, and each grid comprises a power transmission line; determining an icing high-risk grid in the grids; determining an icing risk index of each grid according to the geographic information, the meteorological information and the power grid information; according to the icing risk index of each grid, performing optimization processing on the icing high-risk grid to obtain a target grid; wherein the target grid is the distribution position of the monitoring points. The method is used for achieving the effects of improving the distribution rationality of the monitoring points and reducing the distribution cost.

Description

Technical Field

[0001] The present application relates to the technical field of ice monitoring, and in particular to a method, apparatus, equipment, and storage medium for distributing monitoring points on a power transmission line. Background Art

[0002] Icing on transmission lines can increase the weight of the lines, causing towers to tilt or collapse, and potentially triggering faults such as short circuits and tripping. Therefore, by rationally placing monitoring points along the transmission lines and installing various ice monitoring devices (sensors, cameras, etc.), ice monitoring can be performed on transmission lines. This allows for real-time monitoring of ice thickness, weight, and other parameters, providing timely warnings to avoid major accidents and ensure a stable power supply.

[0003] In related technologies, monitoring points are deployed on transmission lines facing mountainous scenarios. The method usually uses ice thickness data to determine the high-risk ice grids and then deploys monitoring points in the high-risk ice grids. However, this method requires deployment of monitoring points in all high-risk grids, but may not be necessary in some high-risk grids with relatively low risks, resulting in unreasonable deployment and high deployment costs. Summary of the Invention

[0004] The embodiments of the present application provide a method, apparatus, device, and storage medium for distributing monitoring points on a transmission line, so as to improve the rationality of distributing the monitoring points and reduce the cost of distributing the monitoring points.

[0005] In a first aspect, an embodiment of the present application provides a method for distributing monitoring points on a power transmission line, comprising:

[0006] Obtaining geographic information, meteorological information, and power grid information of a target area; wherein the target area is pre-divided into a plurality of grids, each grid including a transmission line;

[0007] Determining a high-risk icing grid in the grid;

[0008] Determining an icing risk index for each grid based on the geographic information, meteorological information, and power grid information;

[0009] According to the icing risk index of each grid, the high-risk icing grid is optimized to obtain a target grid; wherein the target grid is the location of the monitoring point.

[0010] In one possible implementation, the geographic information includes altitude information, slope information, and slope aspect information; the meteorological information includes humidity information, wind speed information, and wind direction information; and the power grid information includes historical ice thickness. Determining the icing risk index for each grid based on the geographic information, meteorological information, and power grid information includes:

[0011] For each grid, determine the slope coefficient of the grid based on the slope information and the slope direction information of the grid in the geographic information and the wind direction information of the grid in the meteorological information;

[0012] An icing risk index of the grid is determined according to the slope coefficient of the grid, the humidity information and wind speed information of the grid in the meteorological information, the altitude information of the grid in the geographic information, and the historical icing thickness of the grid in the power grid information.

[0013] In a possible implementation, determining the icing risk index of the grid based on the slope coefficient of the grid, the humidity information and wind speed information of the grid in the meteorological information, the altitude information of the grid in the geographic information, and the historical icing thickness of the grid in the power grid information includes:

[0014] Determine the percentage of humidity oversaturation duration based on the humidity information of the grid; and determine the percentage of maximum wind speed based on the wind speed information of the grid;

[0015] Determine the altitude ratio based on the altitude information of the grid;

[0016] An icing risk index of the grid is determined according to the proportion of humidity supersaturation time, the proportion of maximum wind speed, the slope coefficient, and the historical icing thickness.

[0017] In a possible implementation, the grid information further includes a conductor model of a transmission line; and optimizing the high-risk icing grid according to the icing risk index of each grid to obtain a target grid includes:

[0018] Determining the layout cost of each grid based on the conductor model of the transmission line in the power grid information;

[0019] Determining a candidate grid based on the icing risk index of each grid, the layout cost of each grid, and a preset objective function; wherein the objective function represents a function that maximizes monitoring benefits;

[0020] The target grid is determined according to the candidate grids and the grids with high icing risk.

[0021] In one possible implementation, the objective function represents a function that maximizes the difference between the total monitoring benefit and the total deployment cost; wherein the total monitoring benefit represents the sum of the benefits when deploying points within a grid; and the total deployment cost represents the sum of the deployment costs when deploying points within a grid.

[0022] In a possible implementation, determining the target grid according to the candidate grid and the grid with high icing risk includes:

[0023] The target grid is determined based on the candidate grids and preset constraints, wherein the constraints represent the placement of points in a grid with a high risk of icing.

[0024] In a possible implementation manner, before determining a grid with a high risk of icing among the grids, the method includes:

[0025] According to the slope information in the geographic information, grids with slope information greater than or equal to a preset slope threshold are removed; and according to the preset communication coverage range, grids without communication coverage are removed.

[0026] In a second aspect, an embodiment of the present application provides a device for distributing monitoring points on a transmission line, comprising:

[0027] An acquisition module, configured to acquire geographic information, meteorological information, and power grid information of a target area; wherein the target area is pre-divided into a plurality of grids, each grid including a transmission line;

[0028] A first determining module is used to determine a high-risk icing grid among the grids;

[0029] A second determination module is used to determine an icing risk index of each grid based on the geographic information, meteorological information and power grid information;

[0030] The processing module is used to optimize the high-risk icing grid according to the icing risk index of each grid to obtain a target grid; wherein the target grid is the location of the monitoring point.

[0031] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a memory, a processor;

[0032] The memory stores computer-executable instructions;

[0033] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0034] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the above first aspect and / or various possible implementations of the first aspect.

[0035] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0036] The present invention provides a method, apparatus, device, and storage medium for distributing monitoring points on power transmission lines. The electronic device can utilize the target area's geographic information, meteorological information, and power grid information to determine the icing risk index for each grid. Based on the icing risk index for each grid, the device optimizes the grids with the highest icing risk, ultimately obtaining the target grid for monitoring point distribution. This method, based on the quantification of risk indices based on multi-source information fusion, makes icing risk assessment more accurate, accurately identifies truly high-risk grids, and optimizes monitoring point distribution, avoiding blindly distributing points across all high-risk grids. This improves the rationality of distribution and reduces distribution costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0038] Figure 1 Schematic diagram of the process of distributing monitoring points of transmission lines provided in this application Figure 1 ;

[0039] Figure 2 Schematic diagram of the process of distributing monitoring points of transmission lines provided in this application Figure 2 ;

[0040] Figure 3 A schematic diagram of the structure of the monitoring point distribution device for the transmission line provided in this application;

[0041] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this application.

[0042] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0043] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0044] In the related art, when distributing monitoring points on power transmission lines facing mountainous scenarios, it is usually necessary to use ice thickness data to determine the high-risk grids for ice coverage, and then distribute monitoring points in the high-risk grids for ice coverage to monitor the ice coverage of the high-risk grids in real time. However, this method requires distribution of monitoring points in all high-risk grids, but it may not be necessary to distribute monitoring points in some high-risk grids with relatively low risks, resulting in unreasonable distribution of monitoring points and high distribution costs. Therefore, an embodiment of the present application provides a method for distributing monitoring points on power transmission lines, which comprehensively evaluates the ice risk index of each grid by combining geographic information, meteorological information and power grid information, and uses the ice risk index to optimize the high-risk grids for ice coverage to obtain the grids that need distribution of monitoring points. In this way, high-risk grids can be optimized according to the risk index, and priority can be given to distributing monitoring points in grids with higher risk indexes and more critical grids, avoiding blind distribution of monitoring points in some high-risk grids with relatively low risks, concentrating resources on truly high-risk areas, improving the utilization efficiency of monitoring resources, and reducing costs.

[0045] The execution subject of the embodiment of the present application can be an electronic device with processing capabilities, such as a computer, server, etc.; it can also be a monitoring system for monitoring the power distribution network, which is not limited in the embodiment of the present application.

[0046] The following uses electronic devices as an example to describe in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems. The following specific embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The following embodiments of the present application are described in conjunction with the accompanying drawings.

[0047] Figure 1 Schematic diagram of the process of distributing monitoring points of transmission lines provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0048] S101: Obtain geographic information, meteorological information, and power grid information of a target area.

[0049] Exemplarily, the target area represents a mountainous area where monitoring points for transmission lines need to be deployed. The target area is pre-divided into multiple grids based on a preset resolution, and each grid includes a transmission line.

[0050] Geographic information is used to reflect the topographic characteristics of the target area and may include topographic information such as altitude, slope, and aspect. For example, electronic devices can use satellite remote sensing images and digital elevation models (DEMs) to extract high-precision topographic data to obtain this geographic information.

[0051] Meteorological information is used to characterize the weather in the target area and may include humidity, wind speed, wind direction, temperature, etc. For example, the electronic device may obtain meteorological information by acquiring real-time monitoring data from a weather station, or by obtaining meteorological information through a preset weather forecast data interface of a meteorological department.

[0052] Grid information is used to characterize the transmission lines in the target area. It may include the topological network of the transmission lines, the type of conductors used in the transmission lines, and the historical ice thickness of the transmission lines. For example, electronic devices can obtain this grid information from a transmission line management system or records.

[0053] It is understandable that after the target area is divided into grids, the geographic information, meteorological information and power grid information of the target area can also reflect the geographic information, meteorological information and power grid information of each grid.

[0054] S102. Determine a high-risk icing grid in the grid.

[0055] For example, a high-ice risk grid indicates a grid with a high probability of ice accumulation and the potential for severe damage from ice accumulation. The electronic device can predict the ice thickness of each grid based on the grid's meteorological information. If the ice thickness is greater than or equal to a preset threshold, the grid is determined to be a high-ice risk grid. Alternatively, the electronic device can pre-set a grid risk classification model, input the grid's meteorological and geographic information into the grid risk classification model, output the grid's risk classification, and then identify the high-ice risk grid from each grid. The grid risk classification model can be a neural network model.

[0056] S103. Determine an icing risk index for each grid based on geographic information, meteorological information, and power grid information.

[0057] For example, the icing risk index is a quantitative value that comprehensively reflects the likelihood and severity of icing and the damage caused by icing for each grid, based on geographic information, meteorological information, and power grid information. An icing risk index model can be pre-built in the electronic device. The grid's geographic information, meteorological information, and power grid information are input into the icing risk index model, which then outputs the icing risk index for the grid. The icing risk index model reflects the mapping relationship between geographic information, meteorological information, power grid information, and the icing risk index.

[0058] S104: Optimize the high-risk icing grids according to the icing risk index of each grid to obtain a target grid.

[0059] For example, the target grids are the locations of monitoring points. The electronic device can screen high-risk grids based on the icing risk index of each grid, selecting high-risk grids with icing risk indices greater than or equal to a preset threshold as target grids. Alternatively, an objective function can be designed based on the icing risk index of each grid, and constraints can be designed based on the high-risk grids. Target optimization processing can then be performed based on the objective function and constraints to obtain a target grid that meets the objective function and constraints.

[0060] In the method for placing monitoring points on transmission lines provided in an embodiment of the present application, electronic equipment can utilize the target area's geographic information, meteorological information, and power grid information to determine the icing risk index for each grid. Based on the icing risk index for each grid, the system then optimizes grids with high icing risk to obtain the target grid for monitoring point placement. This method, through the quantification of risk indices based on multi-source information fusion, makes icing risk assessment more accurate, accurately identifies truly high-risk grids, and optimizes monitoring point placement, avoiding blindly placing points across all high-risk grids, improving the rationality of placement, and reducing deployment costs.

[0061] Figure 2 Schematic diagram of the process of distributing monitoring points of transmission lines provided in this application Figure 2 ,like Figure 2 As shown, this embodiment Figure 1 Based on the embodiment, a method for distributing monitoring points on a transmission line is described in detail. The method includes:

[0062] S201: Acquire geographic information, meteorological information, and power grid information of a target area.

[0063] It should be noted that this step is similar to the aforementioned step S101 and will not be repeated here.

[0064] S202: Remove grids with slope information greater than or equal to a preset slope threshold according to the slope information in the geographic information; and remove grids without communication coverage according to the preset communication coverage range.

[0065] For example, slope information represents the inclination of the terrain within a grid. A slope greater than or equal to a threshold value is detrimental to the installation and operation of monitoring equipment. Communication coverage is used to represent the communication status of a grid; grids without communication coverage cannot transmit monitoring information. Based on the slope information of each grid in the acquired geographic information, the electronic device can remove a grid if it determines that the slope information of the grid is greater than or equal to a preset slope threshold. If the grid does not fall within the preset communication coverage range, the grid is removed.

[0066] S203: Determine the high-risk icing grids in the grid.

[0067] It should be noted that this step is similar to the aforementioned step S102 and will not be repeated here.

[0068] S204 : For each grid, determine the slope coefficient of the grid according to the slope information and slope direction information of the grid in the geographic information and the wind direction information of the grid in the meteorological information.

[0069] Exemplarily, the slope aspect information refers to the direction of the slope, usually expressed as an angle, for example, 0° represents the north direction. It is understandable that the slope aspect is related to airflow and light, which in turn can affect the degree of icing. Wind direction information indicates the direction of the wind, described as an angle. The combination of wind direction and slope aspect can affect the icing process. The slope coefficient is a quantitative coefficient used to characterize the degree of influence of terrain and meteorological conditions on the risk of icing. The electronic device can be pre-set with a mapping relationship between slope information, slope aspect information, wind direction information and slope coefficient, and then after obtaining the above data, it can be substituted into the mapping relationship to obtain the slope coefficient of the grid.

[0070] In an example, the mapping relationship can be expressed as shown in the following formula:

[0071] S slope =cos(ε-∈)sinθ

[0072] Among them, S slope represents the slope coefficient, ε represents the wind direction information, ∈ represents the slope information, and θ represents the slope information.

[0073] For example, cos(ε-∈) represents the angle between wind direction and slope aspect, reflecting the wind's effect on promoting or inhibiting icing on slopes. For example, when the wind direction and slope aspect are consistent, cos(ε-∈) = 1, indicating that the wind has the strongest effect on the slope, favoring the accumulation of water vapor on the slope and the formation of icing. When the wind direction and slope aspect are perpendicular, cos(ε-∈) = 0, indicating that the wind has a smaller effect on the slope, which is not conducive to the accumulation of water vapor on the slope. sinθ reflects the degree to which the slope promotes icing formation. The larger the slope θ, the larger the value of sinθ, indicating a steeper slope. Steeper slopes are more likely to cause water vapor to cool and condense during its ascent, while also affecting air flow, making it easier for water vapor to accumulate near the slope, thereby increasing the possibility of icing. Therefore, the slope coefficient comprehensively considers the combined effects of wind direction, slope aspect, and slope on icing formation, quantifying the relative icing risk of a grid under different terrain and meteorological conditions.

[0074] By introducing the slope coefficient, it is possible to better adapt to the accurate determination of the icing risk index in complex geographical and meteorological environments such as mountainous areas, and improve the rationality of subsequent deployment.

[0075] S205 , determining an icing risk index of the grid based on the slope coefficient of the grid, the humidity information and wind speed information of the grid in the meteorological information, the altitude information of the grid in the geographic information, and the historical icing thickness of the grid in the power grid information.

[0076] For example, an icing risk index model can be pre-built in the electronic device. The grid's humidity information, wind speed information, altitude information, and historical ice thickness are input into the icing risk index model, which then outputs the grid's icing risk index. The icing risk index model reflects the mapping relationship between humidity information, wind speed information, altitude information, historical ice thickness, and the icing risk index.

[0077] In some possible implementations, the proportion of humidity oversaturation duration is determined based on the humidity information of the grid; and the proportion of maximum wind speed is determined based on the wind speed information of the grid; the proportion of altitude is determined based on the altitude information of the grid; and the icing risk index of the grid is determined based on the proportion of humidity oversaturation duration, the proportion of maximum wind speed, the slope coefficient and the historical ice thickness.

[0078] For example, the proportion of humidity oversaturation time represents the proportion of humidity oversaturation time (the time when the humidity is greater than or equal to a preset threshold) in the total time, which is used to reflect the degree of influence of humidity conditions on icing risk. The greater the proportion of humidity oversaturation time, the higher the icing risk when other conditions remain unchanged.

[0079] The maximum wind speed ratio represents the ratio of the maximum wind speed to the critical wind speed threshold, where the critical wind speed threshold represents the minimum wind speed at which icing occurs. Because higher wind speeds accelerate water vapor transport and facilitate icing formation, the greater the maximum wind speed exceeds the critical wind speed threshold, the greater the ratio, indicating a greater contribution to icing risk.

[0080] The altitude percentage represents the normalized altitude information. Generally, the higher the altitude, the lower the temperature, and the more likely water vapor is to condense into ice. The historical ice cover thickness represents the historical ice cover conditions.

[0081] Therefore, the electronic device can determine the percentage of humidity oversaturation duration based on the ratio of the humidity oversaturation duration to the total duration in the humidity information of the grid; determine the maximum wind speed percentage based on the ratio of the maximum wind speed in the grid to the preset critical wind speed threshold; normalize the grid's altitude to obtain the altitude percentage; and then substitute this into the preset icing risk index model to output the icing risk index for the grid. For example, the icing risk index model can be shown as the following formula:

[0082]

[0083] Where R represents the icing risk index, Twet Indicates the humidity supersaturation time, T total Indicates the total duration, W max Indicates the maximum wind speed, W threshold represents the critical wind speed threshold, H represents the altitude information, X represents the historical ice thickness, and α, β, γ, δ, and ρ represent weight coefficients.

[0084] S206: Determine the layout cost of each grid based on the conductor model of the transmission line in the power grid information.

[0085] For example, the conductor model of a transmission line is used to reflect the structure, cross-sectional area, material, and other characteristics of the conductor. Different conductors are suitable for different monitoring equipment, and the maintenance costs of the equipment are different. The deployment cost represents the cost required to install and maintain monitoring equipment in each grid, and can include equipment procurement, installation and construction, and subsequent operation and maintenance costs. The electronic equipment can be pre-set with a correspondence between conductor model and deployment cost or a cost calculation model. Then, based on the conductor model of the transmission line in each grid, the corresponding relationship can be queried or substituted into the model to calculate the corresponding deployment cost.

[0086] S207 : Determine candidate grids according to the icing risk index of each grid, the layout cost of each grid, and a preset objective function.

[0087] For example, the objective function is used to measure the pros and cons of a monitoring point placement scheme and can be a function that represents the maximization of monitoring benefits, where the monitoring benefits represent the benefits after monitoring points are placed in the grid. Candidate grids represent grids that have been screened through the objective function and have preliminary potential for being used as monitoring point placements. The electronic device can set the objective function, substitute the icing risk index and placement cost of each grid into the objective function, and use an optimization algorithm such as a linear programming algorithm or a non-dominated sorting genetic algorithm II (NSGA-II) to solve the problem. The combination of values ​​that maximizes the objective function and determines whether the grid should be placed is obtained, thereby determining the candidate grids.

[0088] In some possible implementations, the objective function represents a function that maximizes the difference between the total monitoring benefit and the total deployment cost; wherein the total monitoring benefit represents the sum of the benefits when deploying the points within the grid; and the total deployment cost represents the sum of the deployment costs when deploying the points within the grid. For example, the objective function can be expressed as shown in the following formula:

[0089]

[0090] Where i represents the grid; represents the profit coefficient corresponding to the unit icing risk index; R i represents the icing risk index of the i-th grid; xi Indicates whether to distribute points in grid i, x i ∈{0,1}, 0 means no point distribution, 1 means point distribution; C i represents the layout cost of the i-th grid; λ represents the cost penalty coefficient; N represents the total number of grids; represents the total benefit of monitoring; Represents the total cost of deployment.

[0091] S208. Determine a target grid based on the candidate grids and the grids with high icing risk.

[0092] In some possible implementations, the electronic device can design the objective function's constraints based on the high-risk icing grid, and then obtain the final target grid based on the constraints and the objective function. For example, the constraints can be expressed as shown in the following formula:

[0093]

[0094] Among them, Ω i represents a high-risk icing grid. This constraint condition specifies the point distribution in the high-risk icing grid. Combining the aforementioned objective function and this constraint condition, we can obtain a target grid that satisfies both the objective function and is a high-risk icing grid, which is used as the final point distribution grid.

[0095] The present application provides a method for distributing monitoring points on a transmission line. After obtaining geographic information, meteorological information, and power grid information of a target area, the electronic device first uses the geographic information to remove unreachable grids. Based on the slope information, aspect information, and wind direction information, the slope coefficient of each grid is determined. The icing risk index of each grid is determined based on the slope coefficient, humidity information, wind speed information, altitude information, and historical ice thickness. Then, based on the cost of distributing points on each grid and the icing risk index of each grid, candidate grids are determined based on a preset objective function. The final target grid is obtained by combining the grids with high icing risk. In this way, the feasibility of monitoring equipment installation and data transmission is ensured by first removing unreachable grids such as those with slopes exceeding a threshold and those without communication coverage. Secondly, the icing risk index is determined in combination with the slope coefficient, which improves the accuracy of determining the icing risk index in complex geographic and meteorological environments such as mountainous areas. Finally, the candidate grids and target grids are determined in combination with the icing risk index and the distribution cost. With the maximization of monitoring benefits as the guide, the distribution grids are reasonably set to reduce the distribution cost.

[0096] Figure 3 This is a schematic diagram of the structure of the monitoring point layout device for the transmission line provided by this application, as shown in Figure 3 As shown, the monitoring point arrangement device 300 for a transmission line provided in this embodiment includes:

[0097] An acquisition module 301 is configured to acquire geographic information, meteorological information, and power grid information of a target area, wherein the target area is pre-divided into a plurality of grids, each grid including a power transmission line;

[0098] A first determining module 302 is configured to determine a high-risk icing grid among the grids;

[0099] A second determining module 303 is configured to determine an icing risk index for each grid based on the geographic information, meteorological information, and power grid information;

[0100] The processing module 304 is configured to optimize the high-risk icing grid according to the icing risk index of each grid to obtain a target grid; wherein the target grid is the location of the monitoring points.

[0101] In one possible implementation, the geographic information includes altitude information, slope information, and slope direction information; the meteorological information includes humidity information, wind speed information, and wind direction information; and the power grid information includes historical ice thickness. The second determining module 303 is specifically configured to:

[0102] For each grid, determine the slope coefficient of the grid based on the slope information and the slope direction information of the grid in the geographic information and the wind direction information of the grid in the meteorological information;

[0103] The icing risk index of the grid is determined according to the slope coefficient of the grid, the humidity information and wind speed information of the grid in the meteorological information, the altitude information of the grid in the geographic information, and the historical ice thickness of the grid in the power grid information.

[0104] In a possible implementation, the second determining module 303 is specifically configured to:

[0105] Determine the percentage of humidity oversaturation duration based on the humidity information of the grid; and determine the percentage of maximum wind speed based on the wind speed information of the grid;

[0106] Determine the altitude ratio based on the altitude information of the grid;

[0107] An icing risk index of the grid is determined according to the proportion of humidity supersaturation time, the proportion of maximum wind speed, the slope coefficient, and the historical icing thickness.

[0108] In a possible implementation, the power grid information further includes a conductor model of the transmission line; the processing module 304 is specifically configured to:

[0109] Determining the layout cost of each grid based on the conductor model of the transmission line in the power grid information;

[0110] Determining a candidate grid based on the icing risk index of each grid, the layout cost of each grid, and a preset objective function; wherein the objective function represents a function that maximizes monitoring benefits;

[0111] The target grid is determined according to the candidate grids and the grids with high icing risk.

[0112] In one possible implementation, the objective function represents a function that maximizes the difference between the total monitoring benefit and the total deployment cost; wherein the total monitoring benefit represents the sum of the benefits when deploying points within a grid; and the total deployment cost represents the sum of the deployment costs when deploying points within a grid.

[0113] In a possible implementation, the processing module 304 is specifically configured to:

[0114] The target grid is determined based on the candidate grids and preset constraints, wherein the constraints represent the placement of points in a grid with a high risk of icing.

[0115] In a possible implementation, before the first determining module 302 is configured to determine the grids with high ice risk among the grids, the apparatus further includes a removing module configured to:

[0116] According to the slope information in the geographic information, grids with slope information greater than or equal to a preset slope threshold are removed; and according to the preset communication coverage range, grids without communication coverage are removed.

[0117] The device for distributing monitoring points on a power transmission line provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effects are similar and will not be described in detail in this embodiment.

[0118] Figure 4 This is a schematic diagram of the structure of the electronic device provided in this application. Figure 4 As shown, the electronic device 400 provided in this embodiment includes: at least one processor 401 and a memory 402. Optionally, the electronic device 400 further includes a communication component 403. The processor 401, the memory 402 and the communication component 403 are connected via a bus.

[0119] In a specific implementation process, at least one processor 401 executes the computer-executable instructions stored in the memory 402, so that the at least one processor 401 performs the above method.

[0120] The specific implementation process of the processor 401 can be found in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here in this embodiment.

[0121] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the present invention may be directly executed by a hardware processor or by a combination of hardware and software modules in the processor.

[0122] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (NVM), such as at least one disk memory.

[0123] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be classified into address buses, data buses, and control buses. For ease of illustration, the buses in the drawings of this application are not limited to just one bus or just one type of bus.

[0124] The present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0125] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above method is implemented.

[0126] The above-mentioned readable storage medium can be implemented by any type of volatile or non-volatile memory device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0127] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0128] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0129] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0130] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0131] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program code.

[0132] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0133] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A method for distributing monitoring points on a transmission line, characterized in that: include: Obtaining geographic information, meteorological information, and power grid information of a target area; wherein the target area is pre-divided into a plurality of grids, each grid including a transmission line; Determining a high-risk icing grid in the grid; Determining an icing risk index for each grid based on the geographic information, meteorological information, and power grid information; According to the icing risk index of each grid, the high-risk icing grid is optimized to obtain a target grid; wherein the target grid is the location of the monitoring point.

2. The method according to claim 1, characterized in that The geographic information includes altitude information, slope information, and slope direction information; the meteorological information includes humidity information, wind speed information, and wind direction information; the power grid information includes historical ice thickness; and determining the ice risk index of each grid based on the geographic information, meteorological information, and power grid information includes: For each grid, determine the slope coefficient of the grid based on the slope information and the slope direction information of the grid in the geographic information and the wind direction information of the grid in the meteorological information; An icing risk index of the grid is determined according to the slope coefficient of the grid, the humidity information and wind speed information of the grid in the meteorological information, the altitude information of the grid in the geographic information, and the historical icing thickness of the grid in the power grid information.

3. The method according to claim 2, characterized in that Determining an icing risk index of the grid based on the slope coefficient of the grid, the humidity information and wind speed information of the grid in the meteorological information, the altitude information of the grid in the geographic information, and the historical icing thickness of the grid in the power grid information includes: Determine the percentage of humidity oversaturation duration based on the humidity information of the grid; and determine the percentage of maximum wind speed based on the wind speed information of the grid; Determine the altitude ratio based on the altitude information of the grid; An icing risk index of the grid is determined according to the proportion of humidity supersaturation time, the proportion of maximum wind speed, the slope coefficient, and the historical icing thickness.

4. The method according to claim 1, wherein The grid information also includes the conductor model of the transmission line; and optimizing the high-risk icing grid according to the icing risk index of each grid to obtain a target grid, including: Determining the layout cost of each grid based on the conductor model of the transmission line in the power grid information; Determining a candidate grid based on the icing risk index of each grid, the layout cost of each grid, and a preset objective function; wherein the objective function represents a function that maximizes monitoring benefits; The target grid is determined according to the candidate grids and the grids with high icing risk.

5. The method according to claim 4, characterized in that The objective function represents a maximization function of the difference between the total monitoring benefit and the total deployment cost; wherein, the total monitoring benefit represents the sum of the benefits when deploying points within the grid; the total deployment cost represents the sum of the deployment costs when deploying points within the grid.

6. The method according to claim 4, characterized in that The determining the target grid according to the candidate grid and the grid with high icing risk includes: The target grid is determined based on the candidate grids and preset constraints, wherein the constraints represent the placement of points in a grid with a high risk of icing.

7. The method according to any one of claims 1 to 6, characterized in that Before determining the high-risk grids for icing in the grid, the following procedures shall be followed: According to the slope information in the geographic information, grids with slope information greater than or equal to a preset slope threshold are removed; and according to the preset communication coverage range, grids without communication coverage are removed.

8. A device for distributing monitoring points on a power transmission line, characterized in that: include: An acquisition module, configured to acquire geographic information, meteorological information, and power grid information of a target area; wherein the target area is pre-divided into a plurality of grids, each grid including a transmission line; A first determining module is used to determine a high-risk icing grid among the grids; A second determination module is used to determine an icing risk index of each grid based on the geographic information, meteorological information and power grid information; The processing module is used to optimize the high-risk icing grid according to the icing risk index of each grid to obtain a target grid; wherein the target grid is the location of the monitoring point.

9. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 7 when executed by a processor.

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