Method and apparatus for drawing distributed map of ice covering-prone regions of power grid

Abstract

Disclosed are a method and apparatus for drawing a distributed map of ice covering-prone regions of a power grid. The method comprises: obtaining regional basic data corresponding to a region to be drawn, and creating a corresponding grid region map; on the basis of the regional basic data, determining, in the grid region map, influencing factor data under a plurality of influence types; in response to significance scores inputted for the influencing factor data, constructing an ice covering susceptibility degree matrix, and executing a consistency test; if the consistency test succeeds, performing normalization on a feature vector corresponding to a maximum feature root of the ice covering susceptibility degree matrix, and extracting influence weights corresponding to the influence types; and, on the basis of the influence weights and the influencing factor data, separately calculating an ice covering susceptibility index of each cell in the grid region map, and drawing a distributed map of ice covering-prone regions. Therefore, a more accurate distributed map of ice covering-prone regions is provided for transmission line operation and maintenance units, so that the operation and maintenance units can more accurately foresee and locate key regions for winter icing disaster prevention and control.

Description

A method and device for drawing a distribution map of areas prone to icing in power grids Technical Field

[0001] The present invention relates to the technical field of distribution map drawing, and in particular to a method and device for drawing a distribution map of an area prone to icing in a power grid. Background Art

[0002] Contemporary society's demand for electricity is ever-increasing, and the power system has become the backbone of modern life and industrial production. However, grid towers are prone to ice accumulation in winter, affecting the stable operation of the power grid. Power outages caused by grid ice accumulation not only harm the public interest but also have a significant impact on economic activities, medical facilities, and infrastructure. To ensure the continuity and reliability of the power system, it is necessary to accurately identify areas prone to grid ice accumulation to provide a reference for power companies and maintenance personnel to make operational and maintenance decisions and allocate manpower. Traditional grid ice zone mapping methods cannot accurately describe the distribution of areas prone to ice accumulation, which limits the stability and reliability of the power system.

[0003] Extensive research has been conducted on grid ice zone mapping, but this research focuses on the thickness of ice deposits that occur when transmission towers are covered with ice. Based on this, we categorize ice coverage into seven levels: 0mm, 5mm, 10mm, 15mm, 20mm, 30mm, and above 30mm. Distribution maps of different ice coverage levels are then drawn for the study area.

[0004] While the research results have played an important guiding role in the design phase of transmission lines, they are less applicable during the operation and maintenance phase. They only map the ice thickness generated when icing disasters occur, but cannot accurately delineate areas particularly prone to winter icing disasters. This lack of foresight prevents transmission line operators from accurately locating key areas for winter icing disaster prevention and control, hindering their personnel allocation and decision-making on prevention and control measures.

[0005] Summary of the Invention

[0006] The present invention provides a method and device for drawing a distribution map of areas prone to icing in power grids, which solves the technical problem that the existing technology only draws the thickness of ice generated when icing disasters occur, cannot accurately divide areas that are extremely prone to icing disasters in winter, lacks foresight, and makes it impossible for transmission line operation and maintenance units to accurately locate key areas for prevention and control of icing disasters in winter, affecting the reasonable allocation of personnel and decision-making on prevention and control measures of the operation and maintenance units.

[0007] The present invention provides a method for drawing a distribution map of power grid icing-prone areas, comprising:

[0008] Obtain the basic regional data corresponding to the area to be drawn and create the corresponding raster area map;

[0009] Determining, in the grid area map, influencing factor data under a plurality of preset influencing types based on the area basic data;

[0010] constructing an icing susceptibility matrix in response to the input significance scores for each of the impact types and performing a consistency check;

[0011] If the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted;

[0012] The icing susceptibility index of each pixel in the grid area map is calculated according to each of the influencing weights and each of the influencing factor data, and a distribution map of icing-prone areas is drawn.

[0013] Optionally, the impact type includes a meteorological factor type, a hydrological factor type, a terrain factor type, and a tower factor type; and the step of determining, in the grid area map, the impact factor data under a plurality of preset impact types based on the regional basic data includes:

[0014] Extracting meteorological monitoring data, water network map, ice-covered tower point data and regional digital elevation data from the regional basic data;

[0015] Determine, in the grid area map, an average temperature and humidity distribution map under the meteorological factor type based on the meteorological monitoring data and the ice-covered tower point data;

[0016] Classify the water system network map according to a preset step size, and determine a water system classification map under the hydrological factor type in the grid area map;

[0017] Determining a terrain distribution result under the terrain factor type in the grid area map according to the regional digital elevation data;

[0018] According to the regional digital elevation data and the ice-covered tower point data, the height level corresponding to each tower is determined one by one in the grid area map.

[0019] Optionally, the method further includes:

[0020] If the meteorological monitoring data and the ice-covered tower point data do not exist in the regional basic data, a preset geographic information system is called to obtain the meteorological monitoring data and ice-covered tower point data corresponding to the area to be mapped and vectorize them.

[0021] Optionally, the ice-covered tower point data includes tower point coordinates corresponding to each tower; the meteorological monitoring data includes average temperature and average humidity corresponding to each tower point coordinate; and the step of determining, in the grid area map, an average temperature and humidity distribution map under the meteorological factor type based on the meteorological monitoring data and the ice-covered tower point data includes:

[0022] Loading the coordinates of each of the tower points, the average temperature, and the average humidity into the grid area map;

[0023] Calculating the spatial distances between each grid position point of the grid area map and each of the tower point coordinates, and calculating the sum of all the spatial distances;

[0024] Calculating the ratio between each of the spatial distances and the distance sum value to obtain the distance weight corresponding to each of the grid position points;

[0025] Substituting the average temperature and the distance weight into a preset temperature calculation formula according to each grid position point and vectorizing the result to obtain an average temperature distribution map;

[0026] According to each grid position point, each average humidity and each distance weight is substituted into a preset humidity calculation formula and vectorized to obtain an average humidity distribution map.

[0027] Optionally, the regional digital elevation data includes a horizontal change rate of a pixel value and a vertical change rate of a pixel value corresponding to a grid at each grid position point in the grid region map; and the step of determining a terrain distribution result under the terrain factor type in the grid region map based on the regional digital elevation data includes:

[0028] Calculate the slope and slope direction corresponding to each grid position point according to the horizontal change rate of the pixel value and the vertical change rate of the pixel value corresponding to each grid;

[0029] Based on the slope and the aspect being matched to a preset slope and aspect table, the slope grade and the aspect grade of each grid are determined;

[0030] Obtain the main wind direction corresponding to each grid from a preset wind rose diagram;

[0031] Calculating the slope difference between the main wind direction and each of the slope directions;

[0032] Based on the comparison result of each aspect difference and a preset angle threshold, the aspect type corresponding to each grid is determined.

[0033] Optionally, the regional digital elevation data includes tower height values ​​corresponding to towers; and the step of determining the height level corresponding to each tower one by one in the grid area map based on the regional digital elevation data in combination with the ice-covered tower point data comprises:

[0034] Calculate the height difference between the maximum tower height value and the minimum tower height value;

[0035] Calculating the ratio between the call height difference and the preset number of levels to obtain the call height level interval;

[0036] According to the matching result between the call height value of each tower and the call height level interval, the call height level corresponding to each tower is determined one by one in the grid area map.

[0037] Optionally, the icing susceptibility matrix is:

[0038] Among them, a ji is the relative importance of factor i to factor j,

[0039] Optionally, the step of calculating the icing susceptibility index of each pixel in the grid area map according to each of the influence weights and each of the influencing factor data, and drawing a distribution map of icing-prone areas, includes:

[0040] The influencing factor vector is formed by using the data of each influencing factor;

[0041] Calculating the dot product value between each of the influencing weights and the influencing factor vector to obtain the icing susceptibility index corresponding to each pixel in the grid area map;

[0042] Classifying the icing susceptibility index into a predetermined number of icing levels using an equal division method;

[0043] The color corresponding to each ice coverage level is drawn in each pixel to generate a distribution map of ice coverage prone areas.

[0044] Optionally, the method further includes:

[0045] If the consistency check fails, selecting at least one target relative importance from the icing susceptibility matrix;

[0046] The relative importance of the target is reduced according to a preset attenuation gradient until the consistency check passes.

[0047] The present invention also provides a device for drawing a distribution map of power grid icing-prone areas, comprising:

[0048] The data acquisition module is used to obtain the basic regional data corresponding to the area to be drawn and create the corresponding grid area map;

[0049] An influencing factor data determining module, configured to determine influencing factor data under a plurality of preset influencing types in the grid area map based on the area basic data;

[0050] a matrix construction and consistency check module for constructing an icing susceptibility matrix in response to the input significance scores for each of the impact types and performing a consistency check;

[0051] an impact weight extraction module, configured to normalize the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix and extract the impact weight corresponding to each impact type if the consistency check passes;

[0052] The distribution map drawing module is used to calculate the ice susceptibility index of each pixel in the grid area map according to each of the influencing weights and each influencing factor data, and draw a distribution map of the ice prone area.

[0053] It can be seen from the above technical solutions that the present invention has the following advantages:

[0054] The present invention obtains regional basic data corresponding to the area to be mapped and creates a corresponding grid area map. Based on the regional basic data, influencing factor data under multiple preset impact types are determined in the grid area map. In response to the input significance scores for each influencing factor data, an icing susceptibility matrix is ​​constructed and a consistency check is performed. If the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted. Based on each impact weight and each influencing factor data, the icing susceptibility index of each pixel in the grid area map is calculated, and a distribution map of icing-prone areas is drawn. This provides a more accurate distribution map of icing-prone areas for transmission line operation and maintenance units, enabling them to accurately predict and locate key areas for winter icing disaster prevention and control. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0056] FIG1 is a flowchart of a method for drawing a distribution map of areas prone to icing in a power grid according to an embodiment of the present invention;

[0057] FIG2 is a flowchart of a method for drawing a distribution map of areas prone to icing in a power grid according to another embodiment of the present invention;

[0058] FIG3 is a diagram of a power grid icing susceptibility evaluation index system provided by an embodiment of the present invention;

[0059] FIG4 is a data flow diagram of a method for drawing a distribution map of areas prone to icing in a power grid according to an embodiment of the present invention;

[0060] FIG5 is a structural block diagram of a device for drawing a distribution map of areas prone to icing in a power grid provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0061] An embodiment of the present invention provides a method and device for drawing a distribution map of areas prone to icing in a power grid, which is used to solve the technical problem that only the thickness of ice generated when an icing disaster occurs is drawn, and the areas where icing disasters are extremely likely to occur in winter cannot be accurately divided. This lacks foresight, resulting in the inability of transmission line operation and maintenance units to accurately locate key areas for prevention and control of icing disasters in winter, affecting the reasonable allocation of personnel and decision-making on prevention and control measures of the operation and maintenance units.

[0062] In order to make the purpose, features, and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0063] Please refer to FIG1 , which is a flowchart of the steps of a method for drawing a distribution map of areas prone to icing in a power grid according to an embodiment of the present invention.

[0064] The present invention provides a method for drawing a distribution map of power grid icing-prone areas, comprising:

[0065] Step 101: Obtain basic regional data corresponding to the area to be mapped and create a corresponding grid area map;

[0066] Regional basic data refers to the relevant data of various ice cover factors corresponding to the area to be mapped, including but not limited to digital elevation model (DEM), water network map, meteorological monitoring point data, ice-covered tower point data and wind rose diagram.

[0067] A grid area map refers to a plan view obtained by dividing a two-dimensional plan view of the area to be drawn into grids according to preset specifications, wherein each grid includes at least one pixel and also includes grid location points or tower points.

[0068] In an embodiment of the present invention, a user or an external terminal can delineate the area to be mapped that is covered by the power grid system from a geographic information system or other data source, obtain regional basic data corresponding to the area to be mapped, and create a corresponding raster area map as the data basis for subsequently drawing a distribution map of areas prone to icing.

[0069] Step 102: determining influencing factor data under multiple preset influencing types in the grid area map based on the regional basic data;

[0070] After obtaining the regional basic data, the required data are extracted from the reconstruction according to multiple preset impact types, and the ice-prone factors under different impact types are analyzed respectively, and the impact factor data under multiple preset impact types are determined in the grid area map.

[0071] It should be noted that impact types include meteorological factors, hydrological factors, topographic factors, and tower factors. Impact factor data refers to the distribution maps or level data corresponding to each impact type, including but not limited to temperature and humidity distribution maps, water system classification maps, slope, aspect, aspect type, and height level.

[0072] Step 103: constructing an icing susceptibility matrix in response to the input significance scores for each impact type, and performing a consistency check;

[0073] In this embodiment, after determining the data for each influencing factor, it is displayed on the display screen. After receiving the significance score input for each influencing factor data, each significance score is combined with the pairwise comparison method to construct a pairwise comparison matrix of each layer of evaluation indicators against the previous layer, thereby obtaining an ice susceptibility matrix.

[0074] After completing the construction of the icing susceptibility matrix, there may be scaling errors between influencing factors, such as factor A is more important than factor B, factor B is more important than factor C, but factor C is more important than factor A. Therefore, a consistency test is needed to measure the degree of inconsistency in the icing susceptibility matrix.

[0075] In the specific implementation, the consistency check process is as follows:

[0076] According to the basic principles of the hierarchical analysis method, the ice susceptibility matrix A has the following relationship: Ab=λb

[0077] Where b is the eigenvector corresponding to the largest eigenroot λ of the constructed matrix A. The consistency test is analyzed using the random consistency ratio CR value:

[0078] Among them, CI is the judgment matrix deviation consistency index:

[0079] Where n is the total number of influencing factor data.

[0080] RI is the average random consistency index as shown in Table 1 below:

[0081] Table 1

[0082] If the CR value is less than 0.1, the consistency test has passed. Otherwise, the judgment matrix needs to be adjusted and recalculated (lower the scores of the main factors that caused the consistency test to fail until the consistency test passes. Set the attenuation coefficient to 0.5 and reduce the scores by the attenuation coefficient until the consistency test passes, then stop reducing the scores). After the consistency test passes, the eigenvector b is normalized and mapped between [0, 1]. The element values ​​in the eigenvector b represent the weights of different influence types.

[0083] Step 104: If the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted;

[0084] In this embodiment, if the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix can be normalized and the corresponding impact weights can be extracted according to each impact type.

[0085] Step 105 , calculating the icing susceptibility index of each pixel in the grid area map according to each influencing weight and each influencing factor data, and drawing an icing prone area distribution map.

[0086] After obtaining the influence weights, the dot product of the influence factor vectors formed by the data of each influencing factor is calculated, thereby calculating the icing susceptibility index corresponding to each pixel in each grid area. The data in the grid area map is then used as the grid data source, combined with the multiple levels of the icing susceptibility index, such as the five levels (from high to low) of extremely high icing susceptibility, high icing susceptibility, medium icing susceptibility, low icing susceptibility, and extremely low icing susceptibility) to create an icing susceptibility area distribution map corresponding to the area to be mapped.

[0087] In an embodiment of the present invention, basic regional data corresponding to the area to be mapped is obtained and a corresponding grid region map is created; based on the basic regional data, influencing factor data under multiple preset impact types is determined in the grid region map; an icing susceptibility matrix is ​​constructed in response to the significance scores input for each influencing factor data, and a consistency check is performed; if the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted; based on each impact weight and each influencing factor data, the icing susceptibility index of each pixel in the grid region map is calculated, and an icing susceptibility region distribution map is drawn. This provides a more accurate icing susceptibility region distribution map for transmission line operation and maintenance units, enabling them to accurately foresee and locate key areas for winter icing disaster prevention and control.

[0088] Please refer to FIG. 2 , which is a flowchart of the steps of a method for drawing a distribution map of areas prone to icing in a power grid according to an embodiment of the present invention.

[0089] The present invention provides a method for drawing a distribution map of power grid icing-prone areas, comprising:

[0090] Step 201: Obtain basic regional data corresponding to the area to be mapped, and create a corresponding grid area map;

[0091] In this embodiment, the specific implementation process of step 201 is similar to the implementation process of step 101 and will not be repeated here.

[0092] Optionally, the impact type includes a meteorological factor type, a hydrological factor type, a terrain factor type, and a tower factor type.

[0093] Step 202, extracting meteorological monitoring data, water network map, ice-covered tower point data and regional digital elevation data from regional basic data;

[0094] Meteorological monitoring data refers to the meteorological data in the online monitoring terminal monitoring data of the transmission towers of the power supply operation and maintenance unit in the area to be mapped (hereinafter referred to as the study area), especially the winter monitoring data (the time span is from November each year to February of the following year).

[0095] The ice-covered tower location data refers to the online monitoring terminal and manual ice observation data of the transmission towers of the power supply operation and maintenance unit in the study area, including the ice location, ice occurrence frequency and ice thickness.

[0096] Regional digital elevation data refers to the DEM data of the study area, with a required accuracy of 30m. It is used to analyze the topographic factors of the study area.

[0097] A water network map refers to a schematic diagram that records the location of rivers and their flow directions in the area to be mapped.

[0098] In this embodiment, the influencing factor data include an average temperature and humidity distribution map, a water system classification map, a terrain distribution result, and a call height level.

[0099] In another example of the present invention, the method further comprises the following steps:

[0100] If there is no meteorological monitoring data and ice-covered pole tower point data in the regional basic data, the preset geographic information system is called to obtain the meteorological monitoring data and ice-covered pole tower point data corresponding to the area to be mapped and vectorize them.

[0101] In this example, due to human error or data source defects, vector diagrams of meteorological monitoring data and ice-covered tower point data may not exist in the regional basic data. Therefore, if these data are not available in the current regional basic data, the preset geographic information system is used to obtain the meteorological monitoring data and ice-covered tower point data corresponding to the area to be mapped and vectorize them to obtain the corresponding vector diagrams.

[0102] Step 203, determining an average temperature and humidity distribution map under the meteorological factor type in the grid area map based on the meteorological monitoring data and the ice-covered tower point data;

[0103] Furthermore, the ice-covered tower location data includes the tower point coordinates corresponding to each tower; the meteorological monitoring data includes the average temperature and average humidity corresponding to each tower point coordinate; step 203 may include the following sub-steps:

[0104] Load the coordinates, average temperature and average humidity of each tower point in the grid area map;

[0105] Calculate the spatial distance between each grid position point in the grid area map and the coordinates of each tower point respectively, and calculate the distance and value of all spatial distances;

[0106] Calculate the ratio between each spatial distance and distance value, and obtain the distance weight corresponding to each grid position point;

[0107] Substitute the average temperature and distance weights of each grid point into the preset temperature calculation formula and vectorize them to obtain the average temperature distribution map;

[0108] According to each grid location point, each average humidity and each distance weight are substituted into the preset humidity calculation formula and vectorized to obtain the average humidity distribution map.

[0109] Load the coordinates of each tower point, average temperature level and average humidity level in the grid area map, use distance as a weight distribution variable, and calculate the spatial distance from each grid position point to all tower point coordinates. Calculate the spatial distance dl between each grid position point in the grid area map and each tower point coordinate, and calculate the distance and value of all spatial distances.

[0110] Among them, (X j ,Y j ,Z j ) is the grid point coordinate, (X k ,Y k ,Z k ) are the coordinates of the tower point.

[0111] The distance weight w of each grid position point to each tower point l for:

[0112] Among them, o is the number of tower points.

[0113] After obtaining the distance weight, the average temperature and the distance weight can be substituted into the preset temperature calculation formula according to each grid position point and vectorized to obtain the average temperature distribution map; the average humidity and the distance weight can be substituted into the preset humidity calculation formula according to each grid position point and vectorized to obtain the average humidity distribution map.

[0114] Specifically, the temperature calculation formula is similar to the humidity calculation formula. The following is for the grid position point coordinates (X j ,Y j ,Z j ) grid location point, its average temperature or average humidity is:

[0115] Among them, T j is the average temperature or average humidity of the grid location, wx is the distance weight of the i-th grid location, i=j; T(X i ,Y i ,Z i ) is the average temperature or average humidity of the i-th tower point coordinate.

[0116] After obtaining the average temperature and average humidity of the grid location points, they are vectorized with the average humidity and average temperature of the existing towers to form average temperature distribution maps and average humidity distribution maps.

[0117] It should be noted that the average temperature and average humidity may have multiple values, which can be classified into different levels by matching the preset level distribution table. The preset level distribution table can use the equal division method to divide the average temperature and average humidity into six levels respectively. The equal division method is specifically for the data set {n1n2…n m}, then the level division interval value is where n max ∈n1n2…n m}, n min ∈{n1n2…n m}.

[0118] Step 204: classify the water system network map according to a preset step size, and determine the water system classification map under the hydrological factor type in the grid area map;

[0119] In practice, transmission lines crossing rivers are severely affected by icing in winter. Therefore, a water network map of the study area was collected and four buffer zones were drawn, each with a 50-meter distance as the demarcation point. These buffer zones were 100, 150, 200, and 250 meters. This resulted in a water network classification map that identifies the impact of icing on transmission lines, indicating that the closer the transmission line is to the river, the higher the likelihood of icing.

[0120] Step 205, determining the terrain distribution result under the terrain factor type in the grid area map based on the regional digital elevation data;

[0121] In one example of the present invention, the regional digital elevation data includes the horizontal change rate of the pixel value and the vertical change rate of the pixel value corresponding to each grid position point in the grid region map; step 205 includes the following sub-steps:

[0122] According to the horizontal change rate and vertical change rate of the pixel value corresponding to each grid, the slope and slope direction corresponding to each grid position point are calculated respectively;

[0123] Based on the slope and aspect matching the preset slope and aspect tables, the slope grade and aspect grade of each grid are determined;

[0124] Obtain the main wind direction corresponding to each grid from the preset wind rose diagram;

[0125] Calculate the main wind direction and the aspect difference between each slope direction;

[0126] Based on the comparison results of each aspect difference and the preset angle threshold, the aspect type corresponding to each grid is determined.

[0127] In this embodiment, the regional digital elevation data includes the horizontal and vertical pixel value change rates corresponding to each grid point within the grid region map. Based on the horizontal and vertical pixel value change rates corresponding to each grid point, the slope and aspect corresponding to each grid point are calculated.

[0128] The slope of the grid location point is calculated as follows:

[0129] The slope aspect spect of the grid location point is calculated as follows:

[0130] Among them, x represents the horizontal change rate of the pixel value in the grid where the grid position point is located, and y represents the vertical change rate of the pixel value in the grid where the grid position point is located.

[0131] Specifically, the slope and aspect table can be constructed as follows: Using 5° as the cutoff value, the slope is divided into six categories: 0-5°, 6-10°, 11-15°, 16-20°, 21-25°, and 26° or higher. Using 45° as the cutoff value, the aspect is divided into eight categories: 0-45°, 45°-90°, 90°-135°, 135°-180°, 180°-225°, 225°-270°, 270°-315°, and 315°-360° or higher.

[0132] After calculating the slope aspect, since its aspect type cannot be determined, the prevailing wind direction corresponding to each grid can be obtained from the preset wind rose diagram. The aspect difference between the prevailing wind direction and each slope aspect is calculated. Based on the comparison results of each slope aspect difference and the preset angle threshold, the aspect type corresponding to each grid is determined.

[0133] For example, the main wind direction of the wind rose diagram is Z. When Z-spect is greater than 90°, the slope type is leeward slope; when Z-spect is less than 90°, the slope type is windward slope.

[0134] Step 206, determining the corresponding height level of each tower in the grid area map based on the regional digital elevation data and the ice-covered tower point data;

[0135] In one example of the present invention, the regional digital elevation data includes tower height values ​​corresponding to towers; step 206 may include the following sub-steps:

[0136] Calculate the height difference between the maximum tower height value and the minimum tower height value;

[0137] Calculate the ratio between the call height difference and the preset number of levels to obtain the call height level interval;

[0138] According to the matching results between the call height values ​​of each tower and the call height level interval, the call height level corresponding to each tower is determined one by one in the grid area map.

[0139] In this embodiment, it can be considered that during the actual operation of the transmission line, towers at the same geographical location may have different heights, resulting in different icing conditions at different heights. Therefore, the tower height and the elevation of the geographical location where the tower is located are considered as one of the factors affecting the occurrence of icing disasters. The height difference between the maximum tower height value and the minimum tower height value can be calculated; the ratio between the height difference and the preset number of levels can be calculated to obtain the height level interval; and according to the matching results between each tower height value and the height level interval, the height level corresponding to each tower can be determined one by one in the grid area map.

[0140] Among them, the call height levels can be divided into three levels: 30m call height, 50m call height, and call height above 50m. The intervals of the call height divisions can use the above-mentioned equal division method.

[0141] Step 207 , constructing an icing susceptibility matrix in response to the input significance scores for each impact type, and performing a consistency check;

[0142] The Analytic Hierarchy Process (AHP) is a multi-criteria decision analysis method. It helps decision makers make decisions when faced with complex and changing problems and quantitatively assesses the relative importance of different decision factors. The core idea of ​​AHP is to decompose a large, complex decision problem into multiple levels and then quantitatively compare and integrate the elements at each level to find the optimal decision.

[0143] In this example, the AHP method is applied to the mapping of areas prone to icing in power grids. Based on the actual winter operation and maintenance of transmission lines, a comprehensive consideration of topographical, hydrological, meteorological, and tower factors is used to construct an AHP method suitable for evaluating the susceptibility of power grid icing. The AHP model consists of a target layer, a criterion layer, and a solution layer, as shown in Figure 3. The target layer includes the primary decision-making objectives, the criterion layer includes the criteria for evaluating the solution, and the solution layer includes the available decision options.

[0144] In practice, the significance scores of the influencing factors can be calculated by frontline O&M personnel from the power supply O&M units in the region (the scores are obtained by assigning a relative significance value from 1 to 9 to different icing susceptibility factors). Using the paired comparison method, a matrix is ​​constructed to compare the icing susceptibility of each layer of evaluation indicators to the previous layer.

[0145] Optionally, the icing susceptibility matrix is:

[0146] Among them, a ji is the relative importance of factor i to factor j,

[0147] In this embodiment, the consistency check process is similar to the specific implementation process of step 203 and will not be repeated here.

[0148] Step 208: If the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted;

[0149] When the consistency check passes, the feature vector b is normalized and mapped between [0, 1]. The element values ​​in the feature vector b represent the influence weights of different influence types.

[0150] In another example of the present invention, the method further comprises the following steps:

[0151] If the consistency check fails, then at least one target relative importance is selected from the icing susceptibility matrix;

[0152] Reduce the relative importance of the target according to the preset attenuation gradient until the consistency test passes.

[0153] In the specific implementation, the score of the main factor that causes the consistency test to fail is reduced until the consistency test passes. Set the attenuation coefficient to 0.5, and reduce the score by the attenuation coefficient until the consistency test passes, and stop reducing the score. The icing susceptibility matrix can be corrected by the maximum improvement direction algorithm. For example, automatic correction using the maximum improvement direction algorithm can meet the consistency requirements, and only one data item in the judgment matrix needs to be corrected. Generally, no further processing of the judgment matrix data is required. Alternatively, automatic correction using the maximum improvement direction algorithm can meet the consistency requirements, but the number of data items that need to be corrected is greater than 1. Determine further processing measures based on the percentage of data that needs to be corrected. In the yaahp judgment matrix check results, this type of judgment matrix has icons of different colors, and corresponding processing suggestions are given based on the percentage of data that needs to be corrected.

[0154] Step 209 , calculating the icing susceptibility index of each pixel in the grid area map according to each influencing weight and each influencing factor data, and drawing an icing prone area distribution map.

[0155] In one example of the present invention, step 209 may include the following sub-steps:

[0156] The influencing factor vector is formed by using the data of each influencing factor;

[0157] Calculate the dot product between each influencing weight and the influencing factor vector to obtain the ice susceptibility index corresponding to each pixel in the grid area map;

[0158] The icing susceptibility index is classified into a predetermined number of icing levels using an equal division method;

[0159] The color corresponding to each ice cover level is drawn in each pixel to generate a distribution map of ice cover prone areas.

[0160] In this embodiment, after the influence weight is obtained, the influence factor vector can be formed by using the data of each influence factor, and the dot product value between each influence weight and the influence factor vector is calculated to obtain the ice susceptibility index FB corresponding to each pixel in the grid area map: FB = b·d

[0161] Among them, d is the vector composed of influencing factor data, and b is the influence weight.

[0162] The overlay analysis function in Arcgis 10.0 was used to calculate the FB value and obtain the icing susceptibility index. Similarly, the icing susceptibility index values ​​were divided into five levels using the equal division method. The distribution map of icing-prone areas, ranked from high to low, is shown as follows: extremely high icing susceptibility, high icing susceptibility, moderate icing susceptibility, low icing susceptibility, and extremely low icing susceptibility. The detailed process is shown in Figure 4.

[0163] In an embodiment of the present invention, basic regional data corresponding to the area to be mapped is obtained and a corresponding grid area map is created. Based on the basic regional data, influencing factor data under multiple preset impact types is determined within the grid area map. In response to the input significance scores for each influencing factor data, an icing susceptibility matrix is ​​constructed and a consistency check is performed. If the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted. Based on the impact weights and the influencing factor data, the icing susceptibility index for each pixel in the grid area map is calculated, and a distribution map of icing-prone areas is drawn. This provides transmission line operators with a more accurate distribution map of icing-prone areas, enabling them to accurately predict and locate key areas for winter icing disaster prevention and control. Unlike traditional ice and snow cover monitoring methods, the present invention uses the analytic hierarchy process to comprehensively consider multiple factors, including hydrological conditions, meteorological conditions, topographic conditions, and tower height. This helps more accurately identify areas prone to icing in the power grid and provides more comprehensive security. The present invention provides highly personalized decision support based on the calculation results of the susceptibility index. This allows power companies and maintenance personnel to formulate appropriate preventive measures based on actual conditions to minimize the risk of power outages caused by ice and snow. By comprehensively considering multiple factors, the present invention provides a more intelligent analysis of the susceptibility of power grid icing, allowing decision makers to better understand the weak links of the power system and take timely measures to mitigate risks. The present invention uses GIS technology to visualize the information of prone areas as a distribution map of areas prone to icing on the power grid. This provides clear visual information, making it easier for decision makers to understand the distribution of prone areas, thereby helping them to make decisions and preventive measures. The purpose of the present invention is to reduce the adverse effects of ice and snow cover on the power system and reduce power outages and losses. By providing more accurate information on areas prone to ice and snow cover, it is expected to reduce the risks of the power system, improve power supply reliability, and provide higher quality power services to society.

[0164] Please refer to FIG5 , which shows a structural block diagram of a device for drawing a distribution map of areas prone to icing in a power grid according to an embodiment of the present invention.

[0165] The present invention also provides a device for drawing a distribution map of power grid icing-prone areas, comprising:

[0166] The data acquisition module 501 is used to obtain the basic regional data corresponding to the area to be mapped and create a corresponding grid area map;

[0167] An influencing factor data determining module 502 is configured to determine influencing factor data under a plurality of preset influencing types in a grid region map based on the regional basic data;

[0168] A matrix construction and consistency check module 503 is configured to construct an ice susceptibility matrix in response to the input significance scores for each impact type and perform a consistency check;

[0169] The impact weight extraction module 504 is configured to normalize the eigenvector corresponding to the maximum eigenroot of the icing susceptibility matrix and extract the impact weight corresponding to each impact type if the consistency check passes;

[0170] The distribution map drawing module 505 is used to calculate the ice susceptibility index of each pixel in the grid area map according to each influencing weight and each influencing factor data, and draw an ice susceptibility area distribution map.

[0171] Optionally, the impact type includes a meteorological factor type, a hydrological factor type, a terrain factor type, and a tower factor type; the impact factor data determination module 502 includes:

[0172] The data extraction submodule is used to extract meteorological monitoring data, water network maps, ice-covered tower point data and regional digital elevation data from regional basic data;

[0173] The average temperature and humidity distribution map determination submodule is used to determine the average temperature and humidity distribution map under the meteorological factor type in the grid area map based on the meteorological monitoring data and the ice-covered tower point data;

[0174] The water system classification map determination submodule is used to classify the water system network map according to the preset step size, and determine the water system classification map under the hydrological factor type in the grid area map;

[0175] A terrain distribution result determination submodule is used to determine the terrain distribution result under the terrain factor type in the raster area map based on the regional digital elevation data;

[0176] The call height level determination submodule is used to determine the call height level corresponding to each tower one by one in the grid area map based on the regional digital elevation data combined with the ice-covered tower point data.

[0177] Optionally, the device further comprises:

[0178] The vectorization module is used to call the preset geographic information system to obtain the meteorological monitoring data and ice-covered tower point data corresponding to the area to be mapped and vectorize them if there is no meteorological monitoring data and ice-covered tower point data in the regional basic data.

[0179] Optionally, the ice-covered tower location data includes the tower point coordinates corresponding to each tower; the meteorological monitoring data includes the average temperature and average humidity corresponding to each tower point coordinate; and the average temperature and humidity distribution map determination submodule is specifically used to:

[0180] Load the coordinates, average temperature and average humidity of each tower point in the grid area map;

[0181] Calculate the spatial distance between each grid position point in the grid area map and the coordinates of each tower point respectively, and calculate the distance and value of all spatial distances;

[0182] Calculate the ratio between each spatial distance and distance value, and obtain the distance weight corresponding to each grid position point;

[0183] Substitute the average temperature and distance weights of each grid point into the preset temperature calculation formula and vectorize them to obtain the average temperature distribution map;

[0184] According to each grid location point, each average humidity and each distance weight are substituted into the preset humidity calculation formula and vectorized to obtain the average humidity distribution map.

[0185] Optionally, the regional digital elevation data includes a horizontal change rate of a pixel value and a vertical change rate of a pixel value corresponding to each grid position point in the grid region map; the terrain distribution result determination submodule is specifically used to:

[0186] According to the horizontal change rate and vertical change rate of the pixel value corresponding to each grid, the slope and slope direction corresponding to each grid position point are calculated respectively;

[0187] Based on the slope and aspect matching the preset slope and aspect tables, the slope grade and aspect grade of each grid are determined;

[0188] Obtain the main wind direction corresponding to each grid from the preset wind rose diagram;

[0189] Calculate the main wind direction and the aspect difference between each slope direction;

[0190] Based on the comparison results of each aspect difference and the preset angle threshold, the aspect type corresponding to each grid is determined.

[0191] Optionally, the regional digital elevation data includes tower height values ​​corresponding to towers; the height level determination submodule is specifically configured to:

[0192] Calculate the height difference between the maximum tower height value and the minimum tower height value;

[0193] Calculate the ratio between the call height difference and the preset number of levels to obtain the call height level interval;

[0194] According to the matching results between the call height values ​​of each tower and the call height level interval, the call height level corresponding to each tower is determined one by one in the grid area map.

[0195] Optionally, the icing susceptibility matrix is:

[0196] Among them, a ji is the relative importance of factor i to factor j,

[0197] Optionally, the distribution map drawing module 505 is specifically configured to:

[0198] The influencing factor vector is formed by using the data of each influencing factor;

[0199] Calculate the dot product between each influencing weight and the influencing factor vector to obtain the ice susceptibility index corresponding to each pixel in the grid area map;

[0200] The icing susceptibility index is classified into a predetermined number of icing levels using an equal division method;

[0201] The color corresponding to each ice cover level is drawn in each pixel to generate a distribution map of ice cover prone areas.

[0202] Optionally, the device further comprises:

[0203] A target relative importance selection module is used to select at least one target relative importance from the icing susceptibility matrix if the consistency check fails;

[0204] The adjustment loop module is used to reduce the relative importance of the target according to the preset attenuation gradient until the consistency test passes.

[0205] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and modules can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0206] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0207] The modules described as separate components may or may not be physically separate, and the components shown as modules may or may not be physical modules, that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules may be selected to achieve the purpose of the present embodiment according to actual needs.

[0208] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing module, each module may exist physically separately, or two or more modules may be integrated into a single module. The integrated modules may be implemented in the form of hardware or software functional modules.

[0209] If the integrated module is implemented in the form of a software functional module 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 all or 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 an electronic device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0210] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that the technical solutions described in the above embodiments can still be modified, or some of the technical features thereof can be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for drawing a distribution map of power grid icing prone areas, characterized in that: include: Get the basic regional data corresponding to the area to be drawn, and create the corresponding grid area map; Determining, in the grid area map, influencing factor data under a plurality of preset influencing types according to the area basic data; constructing an icing susceptibility matrix in response to the input significance scores for each of the impact types, and performing a consistency check; If the consistency check passes, the eigenvector corresponding to the maximum eigenroot of the ice susceptibility matrix is ​​normalized, and the impact weight corresponding to each impact type is extracted; The icing susceptibility index of each pixel in the grid area map is calculated according to each of the influencing weights and each of the influencing factor data, and a distribution map of icing-prone areas is drawn.

2. The method according to claim 1, characterized in that The influence types include meteorological factor types, hydrological factor types, terrain factor types and tower factor types; the step of determining the influence factor data under a plurality of preset influence types in the grid area map according to the regional basic data includes: Extracting meteorological monitoring data, water network map, ice-covered tower point data and regional digital elevation data from the regional basic data; According to the meteorological monitoring data and the ice-covered pole tower point data, determine the average temperature and humidity distribution map under the meteorological factor type in the grid area map; Classify the water system network map according to a preset step size, and determine the water system classification map under the hydrological factor type in the grid area map; Determine, in the grid area map, a terrain distribution result under the terrain factor type according to the regional digital elevation data; According to the regional digital elevation data and the ice-covered tower point data, the height level corresponding to each tower is determined one by one in the grid area map.

3. The method according to claim 2, characterized in that The method further comprises: If the meteorological monitoring data and the ice-covered pole tower point data do not exist in the regional basic data, the preset geographic information system is called to obtain the meteorological monitoring data and the ice-covered pole tower point data corresponding to the area to be mapped and vectorize them.

4. The method according to claim 2, characterized in that: The ice-covered tower point data includes the tower point coordinates corresponding to each tower; the meteorological monitoring data includes the average temperature and average humidity corresponding to each tower point coordinate; the step of determining the average temperature and humidity distribution map under the meteorological factor type in the grid area map according to the meteorological monitoring data and the ice-covered tower point data includes: Loading the coordinates of each of the tower points, the average temperature and the average humidity into the grid area map; Calculating the spatial distances between each grid position point of the grid area map and each tower point coordinate, and calculating the distances and values ​​of all the spatial distances; Calculate the ratio between each of the spatial distances and the distance sum value, and obtain the distance weight corresponding to each of the grid position points; Substituting each of the average temperatures and each of the distance weights into a preset temperature calculation formula according to each of the grid position points and vectorizing the formula to obtain an average temperature distribution map; According to each grid position point, each average humidity and each distance weight are substituted into a preset humidity calculation formula and vectorized to obtain an average humidity distribution map.

5. The method according to claim 2, characterized in that: The regional digital elevation data includes the horizontal change rate of the pixel value and the vertical change rate of the pixel value corresponding to the grid where each grid position point in the grid regional map is located; the step of determining the terrain distribution result under the terrain factor type in the grid regional map according to the regional digital elevation data includes: Calculate the slope and slope direction corresponding to each grid position point according to the horizontal change rate of the pixel value and the vertical change rate of the pixel value corresponding to each grid; Based on the slope and the aspect matching the preset slope and aspect tables respectively, determining the slope grade and aspect grade of each grid; Obtain the main wind direction corresponding to each grid from a preset wind rose diagram; Calculating the slope difference between the main wind direction and each of the slope directions; Based on the comparison result between each of the aspect differences and a preset angle threshold, the aspect type corresponding to each of the grids is determined.

6. The method according to claim 2, characterized in that The regional digital elevation data includes tower height values ​​corresponding to the towers; the step of determining the height level corresponding to each tower one by one in the grid area map according to the regional digital elevation data combined with the ice-covered tower point data includes: Calculate the height difference between the maximum tower height value and the minimum tower height value; Calculate the ratio between the call height difference and the preset number of levels to obtain the call height level interval; According to the matching result between the call height value of each tower and the call height level interval, the call height level corresponding to each tower is determined one by one in the grid area map.

7. The method according to claim 1, characterized in that The icing susceptibility matrix is: Among them, a ji is the relative importance of factor i to factor j, 8. The method according to claim 1, characterized in that The step of calculating the ice susceptibility index of each pixel in the grid area map according to each of the influence weights and each of the influence factor data, and drawing an ice susceptibility area distribution map, comprises: The influencing factor vector is formed by using the data of each influencing factor; Calculate the dot product value between each of the influencing weights and the influencing factor vector to obtain the ice susceptibility index corresponding to each pixel in the grid area map; Classifying the icing susceptibility index into a predetermined number of icing levels using an equal division method; The color corresponding to each ice coverage level is drawn in each pixel to generate a distribution map of ice coverage prone areas.

9. The method according to claim 1, characterized in that: The method further comprises: If the consistency check fails, selecting at least one target relative importance from the ice susceptibility matrix; The relative importance of the target is reduced according to a preset attenuation gradient until the consistency check passes.

10. A device for drawing a distribution map of power grid icing prone areas, characterized in that: include: The data acquisition module is used to obtain the basic regional data corresponding to the area to be drawn and create the corresponding grid area map; An influencing factor data determination module, configured to determine influencing factor data under a plurality of preset influencing types in the grid area map according to the area basic data; A matrix construction and consistency check module, for constructing an ice susceptibility matrix in response to the significance scores input for each of the impact types, and performing a consistency check; An impact weight extraction module, for normalizing the eigenvector corresponding to the maximum eigenroot of the ice susceptibility matrix and extracting the impact weight corresponding to each impact type if the consistency check passes; The distribution map drawing module is used to calculate the ice susceptibility index of each pixel in the grid area map according to each of the influencing weights and each of the influencing factor data, and draw a distribution map of the ice prone area.

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