Digital electric power circuit relocation design method and system

Abstract

The invention is suitable for the technical field of electric power circuit relocation and transformation digitization, and provides a digital electric power circuit relocation and transformation design method which comprises the following steps: rasterizing a target relocation and transformation area, and performing cost assignment on each grid to obtain the cost expectation of each grid; according to the cost expectation of each grid, a low-cost area composed of low-cost grids in the target migration and modification area is determined; determining a starting grid and a target grid of a target path in the target relocation and relocation area based on the existing power line and the target relocation and relocation area; and searching a plurality of migration and modification paths between the starting grid and the target grid in the target migration and modification area by using an ant colony algorithm which introduces the low-cost area. The invention further provides a digital power line relocation design system. Through combination of rasterization processing, cost-benefit analysis, an intelligent algorithm and decision support, an efficient and economical solution can be provided for an electric power line relocation project.

Description

Technical Field

[0001] The present invention belongs to the technical field of digital power line relocation, and in particular relates to a digital power line relocation design method and system. Background Art

[0002] With the rapid development of road and bridge projects, especially the construction of railway bridges, the relocation of power and communication lines is likely to occur during construction projects.

[0003] In the related technologies of power line relocation, the traditional method is to complete it on paper map and then conduct on-site survey, and form the final path through continuous survey and adjustment. However, the above method requires a very long time period and there are still large errors. With the rapid development of computer technology, some relocation schemes designed by computer technology have also appeared for the digital relocation of power lines. However, this scheme is limited to converting paper drawings into electronic drawings. This single digitalization of power line relocation cannot provide construction personnel with auxiliary relocation decisions and has the problem of relatively single functions. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a digital power line relocation design method and system, aiming to solve the problem that traditional power line relocation digital technology cannot provide auxiliary relocation decision-making for construction personnel and has relatively single functions.

[0005] To achieve the above object, the present invention provides the following technical solutions.

[0006] An embodiment of the present invention provides a digital power line relocation design method, comprising the following steps: The target relocation area is rasterized, and each grid is assigned a cost value to obtain the expected cost of each grid. The expected cost is used to characterize the cost of the power line relocation project in the area where the grid is located. According to the expected cost of each grid, determine the low-cost area composed of low-cost grids in the target relocation area; Based on the existing power lines and the target relocation area, determining the starting grid and the target grid of the target path in the target relocation area; An ant colony algorithm with low-cost regions is used to search for multiple migration paths between the starting grid and the target grid in the target migration area, the cost data of each migration path is calculated and compared, and a power line migration design scheme is determined and output based on the comparison result.

[0007] Furthermore, the step of rasterizing the target migration area includes: Obtain remote sensing images of the target relocation area and convert the remote sensing images into grayscale images; The grayscale image is rasterized to obtain a grayscale image formed by splicing regularly arranged initial grids, and each initial grid is subjected to adaptive quadtree image segmentation in turn to obtain an adaptive resolution grid region map.

[0008] Furthermore, the step of performing adaptive quadtree image segmentation on each initial grid to obtain an adaptive resolution grid region map includes: Set the smallest grid size in the entire grid map to Lm, and define all initial grids as the first generation grids; For each grid, if the size of the current grid is greater than Lm, continue the segmentation judgment; if it is equal to or less than Lm, stop the segmentation and go to the next step; Determine whether the grayscale value variance of the current grid is greater than the preset variance threshold Vf; if it is greater than Vf, segmentation is required; if it is less than or equal to Vf, further check the grayscale value variance of the 4×4 sub-grids in the grid; If the grayscale value variances of the 4×4 sub-grids in the grid are all less than the mean threshold Vs, the current grid is not segmented and proceeds to the next step; if the grayscale value variance of at least one sub-grid is greater than Vs, segmentation is required; Perform quadtree segmentation on the grid to be segmented, and divide it into 4 second-generation sub-grids of the same size; these sub-grids belong to the same generation, and the current grid becomes the previous generation grid of these 4 sub-grids; then, judge whether the gray value variance of these 4 second-generation sub-grids is greater than the preset variance threshold Vf in turn to determine whether further segmentation is required; For the grids that have completed the segmentation judgment, if there are other grids of the same generation that have not been segmented, continue to judge whether the gray value variance of these grids is greater than the preset variance threshold Vf; if all grids of the same generation have completed the judgment, the same judgment process is performed on the grids of the previous generation; The above process is repeated until each grid of the entire image does not meet the segmentation judgment condition, and an adaptive resolution grid area map is obtained.

[0009] Furthermore, the step of assigning a cost to each grid includes: A hierarchical analysis model is established based on the factors affecting the cost of power line relocation and line selection to obtain the expected cost of each grid, wherein the factors affecting the cost of power line relocation and line selection include: environmental factors, social factors, construction factors and operation and maintenance factors; The grid cost expectation is taken as the target layer, the environmental factors, social factors, construction factors and operation and maintenance factors are taken as the factor layer, and the evaluation index is taken as the evaluation index layer to construct a hierarchical basic model; The hierarchical basic model is constructed as a hierarchical analysis model using the analytical hierarchy process (AHP). The evaluation indicators under each factor layer are quantitatively evaluated according to the 0.1 to 0.9 scale in the analytical hierarchy process (AHP) to obtain the evaluation data. Then, the priority relationship matrix is ​​constructed based on the fuzzy analytical hierarchy process (FAHP) to solve the weights of the evaluation indicators under each factor layer through the priority relationship matrix, and the comprehensive weights of each evaluation indicator on the target line selection cost are solved. The cost expectation of the grid is obtained according to the comprehensive weights.

[0010] Furthermore, the cost expectation of the grid is expressed as: ; Where R represents the expected cost of the grid; Indicates the ideal value of labor cost; represents the ideal value of material cost; p represents the total number of labor cost factors considered; q represents the total number of material cost factors considered.

[0011] Furthermore, the step of searching for multiple migration paths between the starting grid and the target grid in the target migration area by using the ant colony algorithm with low-cost area introduced includes: Set the initial parameters of the ant colony algorithm, including the number of ants, maximum number of iterations, pheromone concentration, and heuristic information; Each ant starts from the starting grid of the target relocation area, begins searching and traversing to optimize the path, and selects the grid with the highest transfer probability as the transfer grid; After each optimization iteration, the pheromone concentration is updated and a new round of search is started to make the ant colony return to the starting grid. After reaching the predetermined number of iterations, the search is ended and multiple optimal paths are found as migration paths.

[0012] Furthermore, the step of selecting the grid with the largest transfer probability as the transfer grid includes: The transition probability formula of the low-cost area is used to calculate the transition probability of the wth ant from grid u to grid v. The transition probability formula is expressed as: ; ; In the formula, represents the transfer probability of the wth ant from grid u to grid v at time t; represents the amount of information transferred by ants under the condition of expected cost; represents the pheromone concentration function; represents the heuristic information function; It represents the expected transfer degree of ants at time t under the condition of expected cost; Indicates whether the path between grid u and grid v at time t falls within the low-cost area. Introducing the low-cost area can improve the efficiency of ant colony search and prevent the ant colony from falling into the local optimal solution. Indicates whether the ant path at time t falls within the low-cost area under the condition of expected cost; , represent pheromone concentration factor and heuristic information factor respectively.

[0013] Furthermore, in the step of updating the pheromone concentration, the pheromone concentration is updated with each iteration, and the updating method of the pheromone concentration is expressed as follows: ; Among them, ρ is the volatility rate of pheromone, and ρ is a constant between 0 and 1, which indicates the proportion of pheromone reduction over time; It indicates the pheromone left by the mth ant when it completes the search in the kth iteration and passes through grid u to grid v. The calculation method is expressed as: ; Where c(m) represents the cost of the path searched by ant m; Q represents the correction coefficient.

[0014] Another embodiment of the present invention provides a digital power line relocation design system, including the following modules: The regional processing module is used to perform grid processing on the target relocation area, assign a cost to each grid, and obtain the expected cost of each grid. The expected cost is used to characterize the cost of the power line relocation project in the area where the grid is located; A region selection module is used to determine a low-cost region composed of low-cost grids in the target relocation region according to the expected cost of each grid; A grid determination module, used to determine the starting grid and the target grid of the target path in the target relocation area based on the existing power lines and the target relocation area; The line relocation design module is used to search for multiple relocation paths between the starting grid and the target grid in the target relocation area by using an ant colony algorithm that introduces a low-cost area, calculate and compare the cost data of each relocation path, and determine and output the power line relocation design plan based on the comparison result.

[0015] Compared with the prior art, the digital power line relocation design method and system of the present invention have the following beneficial effects: First, the present invention performs grid processing on the target relocation area, assigns a cost to each grid, and obtains the expected cost of each grid, which is used to characterize the cost of the power line relocation project in the area where the grid is located; by performing grid processing on the target relocation area and assigning a cost expectation to each grid, the impact of each grid on the cost of the power line relocation project can be quantified; Second, the present invention determines the low-cost area composed of low-cost grids in the target relocation area according to the cost expectation of each grid; by determining the low-cost area composed of low-cost grids, it helps to concentrate resources and efforts on relocation work in these areas, thereby reducing overall costs and improving efficiency; Third, the present invention uses an ant colony algorithm introduced into a low-cost area to search for multiple migration paths between the starting grid and the target grid in the target migration area. In this scheme, the introduction of the ant colony algorithm for path search can provide decision makers with multiple feasible migration plans. Based on the cost-effectiveness comparison results, the optimal power line migration design plan can be determined to achieve the dual goals of cost control and engineering quality.

[0016] In summary, the digital power line relocation design method of the present invention can provide an efficient and economical solution for power line relocation projects by combining raster processing, cost-benefit analysis, intelligent algorithms and decision support. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention.

[0018] Figure 1 A flowchart of a digital power line relocation design method according to the present invention; Figure 2 A sub-flow chart of the digital power line relocation design method of the present invention; Figure 3 Another sub-flow chart of the digital power line relocation design method of the present invention; Figure 4 A structural block diagram of a digital power line relocation design system of the present invention; Figure 5 The present invention provides a structural block diagram of a computer device. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] At present, in the relevant technologies of power line relocation, the traditional method is to complete it on a paper map and then conduct on-site surveys. Through continuous surveys and adjustments, the final path is formed. However, the above method requires a very long time period and there are still large errors. With the rapid development of computer technology, there are some relocation schemes designed using computer technology for digital relocation of power lines. However, this scheme is limited to converting paper drawings into electronic drawings. This single digitalization of power line relocation cannot provide construction personnel with auxiliary relocation decisions and has the problem of relatively single functions.

[0021] To solve the above problems, the present invention performs grid processing on the target relocation area, assigns a cost to each grid, and obtains the expected cost of each grid, which is used to characterize the cost of the power line relocation project in the area where the grid is located; according to the cost expectation of each grid, a low-cost area composed of low-cost grids in the target relocation area is determined; based on the existing power lines and the target relocation area, the starting grid and the target grid of the target path in the target relocation area are determined; an ant colony algorithm that introduces a low-cost area is used to search for multiple relocation paths between the starting grid and the target grid in the target relocation area, the cost data of each relocation path is calculated and compared, and the power line relocation design plan is determined based on the comparison result and output.

[0022] The digital power line relocation design method of the present invention can provide an efficient and economical solution for power line relocation projects by combining raster processing, cost-benefit analysis, intelligent algorithms and decision support.

[0023] The specific implementation of a digital power line relocation design method and system of the present invention is described in detail below in conjunction with specific embodiments.

[0024] Please refer to Figure 1 In one embodiment of the present invention, a digital power line relocation design method is provided, comprising the following steps: S101, gridding the target relocation area, assigning a cost to each grid, and obtaining the expected cost of each grid; the expected cost is used to represent the cost of the power line relocation project in the area where the grid is located; Please refer to Figure 2 In the embodiment of the present invention, the step of rasterizing the target migration area includes: S201, obtaining a remote sensing image of the target relocation area, and converting the remote sensing image into a grayscale image; In step S201, first, it is necessary to obtain remote sensing images of the target relocation area. The images come from satellites, aircraft or other remote sensing platforms. Before converting the remote sensing images into grayscale images, preprocessing is performed to improve the image quality: if the remote sensing images are multispectral, they can be converted into color images by color synthesis methods. This includes true color synthesis and false color synthesis, where true color synthesis uses the same band combination as human vision, while false color synthesis uses different band combinations to highlight specific ground features; Furthermore, the step of converting the remote sensing image into a grayscale image in the embodiment of the present invention includes: mapping the grayscale value of the original image to a new grayscale range through linear mapping; preferably, the histogram equalization adopted is a nonlinear transformation method, which enhances the contrast of the image by adjusting the histogram distribution of the image, making the histogram distribution of the image more uniform, thereby improving the visual effect of the image; and enhancing the image by changing the grayscale distribution of image pixels to highlight specific ground features.

[0025] S202, rasterizing the grayscale image to obtain a grayscale image formed by regularly arranged initial grids, and performing adaptive quadtree image segmentation on each initial grid in turn to obtain an adaptive resolution grid area map; wherein, the step of performing adaptive quadtree image segmentation on each initial grid to obtain an adaptive resolution grid area map includes: setting the smallest grid size in the entire grid map to Lm, and defining all initial grids as first-generation grids; for each grid, if the size of the current grid is greater than Lm, continuing to perform segmentation judgment; if it is equal to or less than Lm, stopping segmentation and entering the next step; judging whether the grayscale value variance of the current grid is greater than a preset variance threshold Vf; if it is greater than Vf, segmentation is required; if it is less than or equal to Vf, further checking the grayscale value variance of the 4×4 sub-grids in the grid; if the grayscale value variance of the 4×4 sub-grids in the grid is less than the mean threshold V s, the current grid is not segmented and goes to the next step; if the gray value variance of at least one sub-grid is greater than Vs, segmentation is required; quadtree segmentation is performed on the grid to be segmented, and it is divided into 4 second-generation sub-grids of the same size; these sub-grids belong to the same generation, and the current grid becomes the previous generation grid of these 4 sub-grids; then, the gray value variance of these 4 second-generation sub-grids is judged in turn to see whether it is greater than the preset variance threshold Vf to determine whether further segmentation is required; for the grid that has completed the segmentation judgment, if there are other grids of the same generation that have not been segmented, continue to judge whether the gray value variance of these grids is greater than the preset variance threshold Vf; if all grids of the same generation have completed the judgment, the same judgment process is performed on the grids of the previous generation; the above process is repeated until each grid of the entire image does not meet the segmentation judgment condition, and an adaptive resolution grid area map is obtained.

[0026] See also Figure 3 In the embodiment of the present invention, the step of assigning a cost to each grid includes: S301, establishing a hierarchical analysis model based on factors affecting the cost of power line relocation and line selection, and obtaining the expected cost of each grid, wherein the factors affecting the cost of power line relocation and line selection include: environmental factors, social factors, construction factors and operation and maintenance factors; In the power line relocation project, cost control is an important link. In order to evaluate and control costs more scientifically, the present invention establishes a hierarchical analysis model (AHP), which takes into account multiple factors affecting costs, including environmental factors, social factors, construction factors and operation and maintenance factors. These factors constitute the factor layer of the model, and the cost expectation of power line relocation line selection is the target layer. Through this model, each influencing factor can be quantitatively evaluated to obtain the cost expectation of each grid; S302, taking the grid cost expectation as the target layer, taking the environmental factors, social factors, construction factors and operation and maintenance factors as the factor layer, taking the evaluation index as the evaluation index layer, and constructing a hierarchical basic model; S303. The hierarchical basic model is constructed as a hierarchical analysis model using the analytical hierarchy process (AHP). The evaluation indicators under each factor layer are quantitatively evaluated according to the 0.1 to 0.9 scale in the analytical hierarchy process (AHP) to obtain evaluation data. Then, a priority relationship matrix is ​​constructed for the evaluation data based on the fuzzy analytical hierarchy process (FAHP). The weights of the evaluation indicators under each factor layer are solved through the priority relationship matrix, and the comprehensive weights of each evaluation indicator on the target line selection cost are solved. The cost expectation of the grid is obtained according to the comprehensive weights.

[0027] In an embodiment of the present invention, the importance of each evaluation indicator relative to other indicators is scored according to the 0.1 to 0.9 scale in AHP, and these scores reflect the subjective judgment of experts or decision makers on the importance of each indicator; based on quantitative evaluation, a priority relationship matrix is ​​constructed, which describes the relative importance of each evaluation indicator; through the priority relationship matrix, the weights of the evaluation indicators under each factor layer are solved using the eigenvalue method or the normalization method, and these weights reflect the degree of influence of each indicator on the target layer (cost expectation); the weights of each factor layer are combined with the weights of the evaluation indicator layer, and the comprehensive weights of each evaluation indicator on the target line selection cost are calculated, and finally the cost expectation of each grid is obtained according to these comprehensive weights.

[0028] Furthermore, in an embodiment of the present invention, the cost expectation of the grid is expressed as: ; Where R represents the expected cost of the grid; Indicates the ideal value of labor cost; represents the ideal value of material cost; p represents the total number of labor cost factors considered; q represents the total number of material cost factors considered.

[0029] Please continue to refer to Figure 1 In an embodiment of the present invention, the digital power line relocation design method provided by the present invention further includes the following steps: S102, determining a low-cost area composed of low-cost grids in the target relocation area according to the expected cost of each grid; S103, determining a starting grid and a target grid of a target path in the target relocation area based on the existing power lines and the target relocation area; S104, using an ant colony algorithm with low-cost areas introduced to search for multiple migration paths between the starting grid and the target grid in the target migration area, calculating and comparing cost data of each migration path, and determining and outputting a power line migration design plan based on the comparison result.

[0030] Furthermore, the step of using the ant colony algorithm introduced with the low-cost area to search for multiple migration paths between the starting grid and the target grid in the target migration area includes: setting various initial parameters of the ant colony algorithm, including the number of ants, the maximum number of iterations, the pheromone concentration and the heuristic information; each ant starts from the starting grid of the target migration area, starts searching and traversing to optimize the path, and selects the grid with the largest transfer probability as the transfer grid; after each optimization iteration, updates the pheromone concentration, starts a new round of search, and makes the ant colony return to the starting grid, and ends the search after reaching a predetermined number of iterations, and finds multiple optimal paths as migration paths.

[0031] Furthermore, the step of selecting the grid with the largest transfer probability as the transfer grid includes: The transition probability formula of the low-cost area is used to calculate the transition probability of the wth ant from grid u to grid v. The transition probability formula is expressed as: ; ; In the formula, represents the transfer probability of the wth ant from grid u to grid v at time t; represents the amount of information transferred by ants under the condition of expected cost; represents the pheromone concentration function; represents the heuristic information function; It represents the expected transfer degree of ants at time t under the condition of expected cost; Indicates whether the path between grid u and grid v at time t falls within the low-cost area. Introducing the low-cost area can improve the efficiency of ant colony search and prevent the ant colony from falling into the local optimal solution. Indicates whether the ant path at time t falls within the low-cost area under the condition of expected cost; , represent pheromone concentration factor and heuristic information factor respectively.

[0032] Furthermore, in the step of updating the pheromone concentration, the pheromone concentration is updated with each iteration, and the updating method of the pheromone concentration is expressed as follows: ; Among them, ρ is the volatility rate of pheromone, and ρ is a constant between 0 and 1, which indicates the proportion of pheromone reduction over time; It indicates the pheromone left by the mth ant when it completes the search in the kth iteration and passes through grid u to grid v. The calculation method is expressed as: ; Where c(m) represents the cost of the path searched by ant m; Q represents the correction coefficient.

[0033] Therefore, the present invention uses an ant colony algorithm introduced into a low-cost area to search for multiple migration paths between the starting grid and the target grid in the target migration area. In this scheme, the introduction of the ant colony algorithm for path search can provide decision makers with multiple feasible migration plans. Based on the cost-effectiveness comparison results, the optimal power line migration design plan can be determined to achieve the dual goals of cost control and engineering quality.

[0034] In summary, the digital power line relocation design method of the present invention can provide an efficient and economical solution for power line relocation projects by combining raster processing, cost-benefit analysis, intelligent algorithms and decision support.

[0035] Please refer to Figure 4 In another embodiment of the invention, a digital power line relocation design system is provided, comprising the following modules: The area processing module 401 is used to perform grid processing on the target relocation area, assign a cost to each grid, and obtain the expected cost of each grid. The expected cost is used to characterize the cost of the power line relocation project in the area where the grid is located; The region selection module 402 is used to determine a low-cost region composed of low-cost grids in the target relocation region according to the expected cost of each grid; A grid determination module 403, for determining a starting grid and a target grid of a target path in a target relocation area based on existing power lines and a target relocation area; The line relocation design module 404 is used to search for multiple relocation paths between the starting grid and the target grid in the target relocation area by using the ant colony algorithm with the low-cost area introduced, calculate and compare the cost data of each relocation path, determine and output the power line relocation design plan based on the comparison result.

[0036] Please refer to Figure 5 In another embodiment of the present disclosure, a computer device is provided. The computer device 500 of the embodiment of the present disclosure includes a memory and a processor. The memory stores a computer program. When the computer program is executed by the processor, the digital power line relocation design method of any one of the above embodiments is implemented; the computer device may also include: an input system and an output system; the processor, memory, input system and output system may be connected via a bus or other means, and the input system may receive input digital or character information, and generate signal input related to the migration of the digital power line relocation design.

[0037] The output system may include display devices such as display screens.

[0038] Furthermore, the present invention also provides a computer-readable storage medium, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor, the steps of the digital power line relocation design method provided above are implemented.

[0039] 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0040] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, the functional units in the various embodiments 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. The above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0041] In a typical configuration of an embodiment of the present invention, the terminal, the device of the service network and the computing device include one or more processors (CPU), an input / output interface, a network interface and a memory.

[0042] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0043] Computer readable media include permanent and non-permanent, removable and non-removable media and can store information by any method or technology. The information can be computer readable instructions, data structures, program modules or other data.

[0044] Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-transitory media such as modulated data signals and carrier waves.

[0045] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0046] 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 may still be modified, or some or all of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention.

[0047] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A digital power line relocation design method, characterized in that: The following steps are involved: The target relocation area is rasterized, and each grid is assigned a cost value to obtain the expected cost of each grid. The expected cost is used to characterize the cost of the power line relocation project in the area where the grid is located. According to the expected cost of each grid, determine the low-cost area composed of low-cost grids in the target relocation area; Based on the existing power lines and the target relocation area, determining the starting grid and the target grid of the target path in the target relocation area; An ant colony algorithm with low-cost regions is used to search for multiple migration paths between the starting grid and the target grid in the target migration area, the cost data of each migration path is calculated and compared, and a power line migration design scheme is determined and output based on the comparison result.

2. The digital power line relocation design method according to claim 1 is characterized in that: The step of rasterizing the target relocation area includes: Obtain remote sensing images of the target relocation area and convert the remote sensing images into grayscale images; The grayscale image is rasterized to obtain a grayscale image formed by splicing regularly arranged initial grids, and each initial grid is subjected to adaptive quadtree image segmentation in turn to obtain an adaptive resolution grid region map.

3. The digital power line relocation design method according to claim 2 is characterized in that: The step of performing adaptive quadtree image segmentation on each initial grid to obtain an adaptive resolution grid region map comprises: Set the smallest grid size in the entire grid map to Lm, and define all initial grids as the first generation grids; For each grid, if the size of the current grid is greater than Lm, continue the segmentation judgment; if it is equal to or less than Lm, stop the segmentation and go to the next step; Determine whether the grayscale value variance of the current grid is greater than the preset variance threshold Vf; if it is greater than Vf, segmentation is required; if it is less than or equal to Vf, further check the grayscale value variance of the 4×4 sub-grids in the grid; If the grayscale value variances of the 4×4 sub-grids in the grid are all less than the mean threshold Vs, the current grid is not segmented and proceeds to the next step; if the grayscale value variance of at least one sub-grid is greater than Vs, segmentation is required; Perform quadtree segmentation on the grid to be segmented, and divide it into 4 second-generation sub-grids of the same size; these sub-grids belong to the same generation, and the current grid becomes the previous generation grid of these 4 sub-grids; then, judge whether the gray value variance of these 4 second-generation sub-grids is greater than the preset variance threshold Vf in turn to determine whether further segmentation is required; For the grids that have completed the segmentation judgment, if there are other grids of the same generation that have not been segmented, continue to judge whether the gray value variance of these grids is greater than the preset variance threshold Vf; if all grids of the same generation have completed the judgment, the same judgment process is performed on the grids of the previous generation; The above process is repeated until each grid of the entire image does not meet the segmentation judgment condition, and an adaptive resolution grid area map is obtained.

4. The digital power line relocation design method according to claim 3 is characterized in that: The step of assigning a cost to each grid comprises: A hierarchical analysis model is established based on the factors affecting the cost of power line relocation and line selection to obtain the expected cost of each grid, wherein the factors affecting the cost of power line relocation and line selection include: environmental factors, social factors, construction factors and operation and maintenance factors; The grid cost expectation is taken as the target layer, the environmental factors, social factors, construction factors and operation and maintenance factors are taken as the factor layer, and the evaluation index is taken as the evaluation index layer to construct a hierarchical basic model; The hierarchical basic model is constructed as a hierarchical analysis model using the analytical hierarchy process (AHP). The evaluation indicators under each factor layer are quantitatively evaluated according to the 0.1 to 0.9 scale in the analytical hierarchy process (AHP) to obtain the evaluation data. Then, the priority relationship matrix is ​​constructed based on the fuzzy analytical hierarchy process (FAHP) to solve the weights of the evaluation indicators under each factor layer through the priority relationship matrix, and the comprehensive weights of each evaluation indicator on the target line selection cost are solved. The cost expectation of the grid is obtained according to the comprehensive weights.

5. The digital power line relocation design method according to claim 4, characterized in that: The cost expectation of the grid is expressed as: ； Where R represents the expected cost of the grid; Indicates the ideal value of labor cost; represents the ideal value of material cost; p represents the total number of labor cost factors considered; q represents the total number of material cost factors considered.

6. The digital power line relocation design method according to claim 5, characterized in that: The step of searching for multiple migration paths between the starting grid and the target grid in the target migration area by using the ant colony algorithm introduced into the low-cost area includes: Set the initial parameters of the ant colony algorithm, including the number of ants, maximum number of iterations, pheromone concentration, and heuristic information; Each ant starts from the starting grid of the target relocation area, begins searching and traversing to optimize the path, and selects the grid with the highest transfer probability as the transfer grid; After each optimization iteration, the pheromone concentration is updated and a new round of search is started to make the ant colony return to the starting grid. After reaching the predetermined number of iterations, the search is ended and multiple optimal paths are found as migration paths.

7. The digital power line relocation design method according to claim 6, characterized in that: The step of selecting the grid with the largest transfer probability as the transfer grid comprises: The transition probability formula of the low-cost area is used to calculate the transition probability of the wth ant from grid u to grid v. The transition probability formula is expressed as: ； ； In the formula, represents the transfer probability of the wth ant from grid u to grid v at time t; represents the amount of information transferred by ants under the condition of expected cost; represents the pheromone concentration function; represents the heuristic information function; It represents the expected transfer degree of ants at time t under the condition of expected cost; Indicates whether the path between grid u and grid v at time t falls within the low-cost area. Introducing the low-cost area can improve the efficiency of ant colony search and prevent the ant colony from falling into the local optimal solution. Indicates whether the ant path at time t falls within the low-cost area under the condition of expected cost; , represent pheromone concentration factor and heuristic information factor respectively.

8. The digital power line relocation design method according to claim 7, characterized in that: In the step of updating the pheromone concentration, the pheromone concentration is updated with each iteration, and the updating method of the pheromone concentration is expressed as: ; Among them, ρ is the volatility rate of pheromone, and ρ is a constant between 0 and 1, which indicates the proportion of pheromone reduction over time; It indicates the pheromone left by the mth ant when it completes the search in the kth iteration and passes through grid u to grid v. The calculation method is expressed as: ； Where c(m) represents the cost of the path searched by ant m; Q represents the correction coefficient.

9. A system for implementing the digital power line relocation design method according to any one of claims 1 to 8, characterized in that: The system includes the following modules: The regional processing module is used to perform grid processing on the target relocation area, assign a cost to each grid, and obtain the expected cost of each grid. The expected cost is used to characterize the cost of the power line relocation project in the area where the grid is located; A region selection module is used to determine a low-cost region composed of low-cost grids in the target relocation region according to the expected cost of each grid; A grid determination module, used to determine the starting grid and the target grid of the target path in the target relocation area based on the existing power lines and the target relocation area; The line relocation design module is used to search for multiple relocation paths between the starting grid and the target grid in the target relocation area by using an ant colony algorithm that introduces a low-cost area, calculate and compare the cost data of each relocation path, and determine and output the power line relocation design plan based on the comparison result.

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