Power grid safety supervision patrol path planning method and device, terminal and medium

Abstract

The invention discloses a power grid safety supervision patrol path planning method and device, a terminal and a medium, and the method comprises the steps: dividing a power grid into a plurality of regions according to the geographic features and equipment distribution features of a power grid system; the method comprises the following steps: acquiring power grid safety supervision patrol historical data, and determining patrol index data of each region according to the power grid safety supervision patrol historical data in combination with a preset patrol index function so as to measure the operation condition of power grid equipment in each region, thereby determining a to-be-patrolled region with relatively poor equipment operation condition in each region; and the planning path is generated according to the path planning cost data among the different to-be-patrolled areas, so that the patrolling is more targeted, the comprehensiveness and representativeness of the patrolling are ensured, invalid patrolling is reduced, and the patrolling efficiency is improved.

Description

Technical Field

[0001] This application relates to the technical field of power grid safety supervision and operation and maintenance, and particularly relates to a power grid safety supervision inspection path planning method, device, terminal and medium. Background Art

[0002] As a key infrastructure in modern society, the safe and stable operation of the power grid is of profound significance for ensuring power supply and promoting economic development. It is like the blood vessels of a city, providing continuous power for all walks of life and supporting the normal operation of society.

[0003] Traditional power grid safety supervision inspection methods mainly rely on manual experience. Inspectors need to rely on personal judgment and experience to plan inspection routes and determine inspection priorities. However, this method has many deficiencies. First, due to the lack of scientific data support and path planning, second, manual experience is often limited by personal cognitive levels and experience accumulation, making it difficult to cope with complex and changing power grid environments and equipment conditions. As a result, inspectors often have difficulty comprehensively and accurately grasping the operating conditions and potential risks of power grid equipment, prone to ineffective inspections, and there are technical problems of low inspection efficiency. Summary of the Invention

[0004] This application provides a power grid safety supervision inspection path planning method, device, terminal and medium, which is used to solve the technical problem of low efficiency of existing power grid safety supervision inspections.

[0005] To solve the above technical problem, the first aspect of this application provides a power grid safety supervision inspection path planning method, including:

[0006] Dividing the power grid into several regions according to the geographical characteristics and equipment distribution characteristics of the power grid system;

[0007] Obtaining the historical data of power grid safety supervision inspections, and then determining the inspection index data of each region according to the historical data of power grid safety supervision inspections and in combination with a preset inspection index function;

[0008] Determining several regions to be inspected from the above regions according to the inspection index data;

[0009] Equivalent the regions to be inspected as key nodes, and respectively calculate the path planning cost data of any key node and other key nodes through a preset cost function;

[0010] Generating a power grid safety supervision inspection planning path according to the path planning cost data.

[0011] Preferably, the inspection index function is specifically:

[0012]

[0013] In the formula, xc(a) represents the area inspection index to be inspected in area a, i represents the i-th type of power grid equipment, M represents the number of power grid equipment types, p(a,i) represents the normal operation time of equipment type i in area a, represents the total operation time of equipment type i in area a, represents the total number of maintenance times of equipment type i in area a within N historical time periods, and N represents the number of time periods of the collected safety inspection historical data, represents the weight coefficient of equipment type i.

[0014] Preferably, determining several areas to be inspected from the respective areas according to the inspection index data specifically includes:

[0015] According to the inspection index data corresponding to each area, in combination with a preset inspection index threshold, the area where the inspection index data is not less than the inspection index threshold is determined as the area to be inspected.

[0016] Preferably, the cost function is specifically:

[0017]

[0018] In the formula, u and v are two different key nodes, represents the cost index for moving from key node u to key node v, represents the average distance length from key node u to key node v in the historical data, represents the average consumption time length from key node u to key node v in the historical data, represents the weight coefficient of the average distance length, represents the weight coefficient of the average consumption time length.

[0019] Preferably, generating a power grid safety inspection planning path according to the path planning cost data specifically includes:

[0020] According to the path planning cost data, a power grid safety inspection planning path is generated according to the preset A* path planning logic.

[0021] Preferably, after generating the power grid safety inspection planning path, it further includes:

[0022] The power grid safety inspection planning path is optimized through a preset optimization objective function, and when the optimization termination condition is met, the optimized power grid safety inspection planning path is output.

[0023] Preferably, the optimization objective function is specifically:

[0024]

[0025]

[0026] Wherein, u and v are two different key nodes, J represents the number of key nodes, G(u, v) represents the comprehensive inspection duration index of the two key nodes u and v, B(u, v) represents the random path between the key nodes u and v, and Y(uv) represents the number of paths that meet the conditions between the key nodes u and v. represents the length of the path B(u, v). represents the average time consumed to complete the inspection through the path B(u, v) in the historical work safety inspection data. represents the number of times of completing the inspection through the path B(u, v) in the historical work safety inspection data. represents the trajectory index between the key nodes u and v. represents the weight coefficient of the distance length. represents the weight coefficient of the average time. represents the weight coefficient of the number of times of completing the inspection.

[0027] Meanwhile, the second aspect of the present application provides a power grid work safety inspection path planning device, including:

[0028] A power grid area division unit, configured to divide the power grid into several areas according to the geographical characteristics and equipment distribution characteristics of the power grid system;

[0029] An inspection index data determination unit, configured to obtain the historical data of the power grid work safety inspection, and then determine the inspection index data of each area according to the historical data of the power grid work safety inspection in combination with a preset inspection index function;

[0030] An inspection area determination unit, configured to determine several areas to be inspected from the various areas according to the inspection index data;

[0031] A path planning cost determination unit, configured to equivalently regard the area to be inspected as a key node, and respectively calculate the path planning cost data of any key node and other key nodes through a preset cost function;

[0032] An inspection path generation unit, configured to generate a power grid work safety inspection planning path according to the path planning cost data.

[0033] The third aspect of the present application provides a power grid work safety inspection path planning terminal, including: a memory and a processor;

[0034] The memory is used to store program codes, and the program codes are used to implement a power grid work safety inspection path planning method as provided in the first aspect of the present application;

[0035] The processor is used to read and execute the program code.

[0036] A fourth aspect of the present application provides a computer-readable storage medium, in which program code is stored. The program code is used to be read and executed by a processor to implement a power grid safety supervision inspection path planning method provided in the first aspect of the present application.

[0037] As can be seen from the above technical solutions, the present application has the following advantages:

[0038] The solution provided by the present application divides the power grid into several regions according to the geographical characteristics and equipment distribution characteristics of the power grid system; obtains the historical data of power grid safety supervision inspections, and then determines the inspection index data of each region according to the historical data of power grid safety supervision inspections and in combination with a preset inspection index function to measure the operating conditions of power grid equipment in each region. Thus, the regions to be inspected with relatively poor equipment operating conditions are determined in each region, and then a planned path is generated according to the path planning cost data between different regions to be inspected, making the inspection more targeted, ensuring the comprehensiveness and representativeness of the inspection, reducing ineffective inspections, and helping to improve the inspection efficiency. Description of the Drawings

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0040] Figure 1 It is a schematic flowchart of an embodiment of a power grid safety supervision inspection path planning method provided by the present application.

[0041] Figure 2 It is a schematic structural diagram of an embodiment of a power grid safety supervision inspection path planning device provided by the present application.

[0042] Figure 3 It is a schematic flowchart of an embodiment of a power grid safety supervision inspection path planning device provided by the present application. Detailed Embodiments

[0043] The present application provides a power grid safety supervision inspection path planning method, device, terminal and medium, which are used to solve the technical problem of low efficiency of existing power grid safety supervision inspections.

[0044] To make the invention objectives, features, and advantages of this application more obvious and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Obviously, the embodiments described below are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of this application.

[0045] First, a detailed description of an embodiment of a power grid safety inspection path planning method provided by this application is as follows:

[0046] Please refer to Figure 1 , a power grid safety inspection path planning method provided by an embodiment of this application includes:

[0047] Step 101: Divide the power grid into several regions according to the geographical features and equipment distribution features of the power grid system;

[0048] It should be noted that according to the solution of this embodiment, first, through GIS technology, the entire power grid is divided into several regions according to the geographical distribution features, equipment density, and current operating conditions of the power grid.

[0049] Step 102: Obtain the historical data of power grid safety inspection, and then determine the inspection index data of each region according to the historical data of power grid safety inspection and in combination with a preset inspection index function;

[0050] It should be noted that all the historical safety inspection data of power grid equipment included in different regions of the power grid are extracted from the power grid management system, including inspection time, specific equipment, problems found, handling measures and results. The operating conditions of power grid equipment in each region are evaluated according to the historical safety inspection data and the specific objectives of power grid safety inspection, and the inspection index data of each region are calculated through a preset inspection index function.

[0051] More specifically, the inspection index function mentioned in this embodiment is specifically:

[0052]

[0053] In the formula, xc(a) represents the area to-be-inspected index of area a, i represents the i-th type of power grid equipment, M represents the number of power grid equipment types, p(a,i) represents the normal operating time of equipment type i in area a, represents the total operating time of equipment type i in area a, represents the total number of maintenance times of equipment type i in area a within N historical time periods, N represents the number of time periods of the collected historical safety inspection data, represents the weight coefficient of equipment type i.

[0054] Step 103: Determine a number of areas to be inspected from each area according to the inspection index data;

[0055] It should be noted that according to the inspection index data corresponding to each area and in combination with the preset inspection index threshold, the areas where the inspection index data is not less than the inspection index threshold are selected as the areas that need to be inspected for work safety, that is, the areas to be inspected. Specifically, set the area inspection index threshold Q. When the area inspection index of a certain area is greater than or equal to the threshold Q, it is determined that the area is an area to be inspected.

[0056] Step 104: Equivalent the areas to be inspected to key nodes, and calculate the path planning cost data between any key node and other key nodes through a preset cost function;

[0057] It should be noted that all areas to be inspected are recorded as key nodes, the spatial attributes and geographical locations of each key node are determined, and real-time information query of each key node is realized through GIS navigation technology. Then, through the preset cost function, the path planning cost data between any key node and other key nodes are calculated respectively.

[0058] More specifically, the cost function mentioned in this embodiment is specifically:

[0059]

[0060] In the formula, u and v are two different key nodes, represents the cost index for moving from key node u to key node v, represents the average distance length from key node u to key node v in historical data, represents the average consumption time length from key node u to key node v in historical data, represents the weight coefficient of the average distance length, represents the weight coefficient of the average consumption time length.

[0061] Step 105: Generate a power grid work safety inspection planning path according to the path planning cost data.

[0062] It should be noted that based on the path planning cost data obtained from the above steps, the path planning from the starting point 0 of the power grid safety supervision inspection through all key nodes is determined by using the A* pathfinding algorithm. A list of nodes to be inspected is created by the A* pathfinding algorithm. The list of nodes to be inspected contains all the elements of set A. Select the node with the minimum cost index from the list of nodes to be inspected compared to the starting point 0 of the power grid safety supervision inspection as the current node. Assume this node is r. After determining the path between node r and the starting point 0 of the power grid safety supervision inspection, delete node r from the list of nodes to be inspected, and establish a list of inspected nodes. Initially, this list is empty. Save the information connecting the starting point 0 of the power grid safety supervision inspection and node r in the list of inspected nodes. Then, find the node with the minimum cost index compared to node r in the list of nodes to be inspected through the cost index, and repeat the above steps until the list of nodes to be inspected is empty. When the list of nodes to be inspected is empty, determine the initial trajectory connecting each node by backtracking the node connection information in the list of inspected nodes.

[0063] Among them, the determination method of the path set between different key nodes can be specifically referred to the following examples:

[0064] Determine the actual starting point of the power grid safety supervision inspection. A set A is obtained by randomly sorting the determined key nodes and the starting point of the power grid safety supervision inspection. Set A is expressed as A = {0, 1,..., j,..., J}, where 0 represents the starting point of the power grid safety supervision inspection, 1 represents the key node randomly sorted as 1, j represents the key node sorted as j, and set A includes a total of J key nodes. Determine all the paths between every two key nodes, and randomly sort them according to the path length to obtain set B. For each pair of key nodes (u, v), determine all the paths between them, and sort them according to the path length to obtain the path set B, expressed as B(u, v) = {1,..., c,..., Y(uv)}, and , where 1 represents the path with the shortest distance between key nodes u and v, c represents the c-th path between key nodes u and v, and Y(uv) represents the total number of Y(uv) paths between key nodes u and v. Preset the path deviation value D. Assume the distance of the longest path between key nodes u and v is zc, and the distance of the shortest path between key nodes u and v is zd, then , and the paths that do not meet this condition can be not counted.

[0065] In some embodiments, a power grid safety supervision inspection path planning method provided by the present application may further include:

[0066] Step 106: Optimize the power grid safety supervision inspection planning path through a preset optimization objective function, and output the optimized power grid safety supervision inspection planning path when the optimization termination condition is met.

[0067] It should be noted that an objective function is set with the goal of minimizing the total inspection duration, and the specific expression formula of this objective function is as follows:

[0068] ;

[0069] Among them, it means that u and v are two different key nodes in set A, J represents a total of J key nodes, G(u, v) represents the comprehensive inspection duration index of the two key nodes u and v, and the specific formula of the comprehensive inspection duration index is as follows:

[0070] ;

[0071] Among them, B(u, v) represents the random path between the key nodes u and v, Y(uv) represents that there are a total of Y(uv) paths that meet the conditions between the key nodes u and v, represents the length of the path B(u, v), represents the average time consumed to complete the inspection through the path B(u, v) in the historical work safety inspection data, represents the number of times of completing the inspection through the path B(u, v) in the historical work safety inspection data, represents the trajectory index between the key nodes u and v, represents the weight coefficient of the distance length, represents the weight coefficient of the average time, represents the weight coefficient of the number of times of completing the inspection. These weight coefficients can be determined according to specific situations and requirements, and are usually formulated and confirmed jointly by professionals or relevant interested parties.

[0072] Furthermore, when the determined initial trajectory includes the trajectory connecting the key nodes u and v, the trajectory index between the key nodes u and v, otherwise the trajectory index between the key nodes u and v.

[0073] According to the preset inspection time, the constraint conditions regarding the inspection path are determined, specifically including:

[0074] ;

[0075] Among them, B(t, u, v) refers to the set of paths that are prohibited from passing between the key nodes u and v at time t. This constraint condition means that when calculating the comprehensive inspection duration index, the paths where the key nodes u and v are prohibited from passing are not considered.

[0076] According to the path constraint conditions, use the genetic algorithm to solve the objective function aiming at minimizing the total inspection duration, and obtain a path with the shortest comprehensive inspection duration index considering the shortest arrival duration as the final inspection path. Allocate inspection personnel who can efficiently and safely complete the inspection tasks according to the length, difficulty, and equipment type of the inspection path. Consider factors such as weather conditions, traffic conditions, and equipment operating status, reasonably arrange the inspection time, and avoid conducting inspections during peak periods, bad weather, or working scenarios that affect the normal operation of equipment. Execute the inspection plan, record the data during the actual inspection process, compare the actual data with the estimated expected inspection duration, evaluate the effectiveness and efficiency of the inspection plan, and according to the analysis results, adjust the inspection strategy, optimize the model parameters, or improve the algorithm to provide more accurate and efficient guidance for future power grid safety supervision inspections.

[0077] The solution provided in this application reasonably divides the power grid management area through GIS technology, then sets the area inspection indicators to be inspected, and evaluates the operating conditions of the power grid equipment in each area based on historical data and specific objectives, making the inspection more targeted, ensuring the comprehensiveness and representativeness of the inspection, reducing ineffective inspections, and helping to improve the inspection efficiency; further, by setting the cost indicators between different key nodes and using the A* pathfinding algorithm, the optimal initial trajectory passing through all key nodes from the starting point 0 of the power grid safety supervision inspection can be efficiently determined, which helps to reduce the repetition and redundancy during the inspection process and improve the efficiency of path planning. By constructing the objective function for optimizing the power grid safety supervision inspection and solving the optimal inspection path, the shortest inspection path and the optimization of the comprehensive inspection duration index are ensured; further, by determining the path set between different key nodes and constructing the objective function for optimizing the power grid safety supervision inspection, the optimal inspection path is solved, significantly optimizing the inspection route, avoiding unnecessary detours, thus shortening the inspection time and improving the overall inspection efficiency. When constructing the objective function, not only the path length is considered, but also the average time and frequency in the historical safety supervision inspection data, as well as the trajectory index and weight coefficient are combined. This method of comprehensively considering multiple factors helps to ensure the comprehensiveness and accuracy of the inspection plan, enabling the inspection to cover key nodes and important areas in the power grid.

[0078] The above is a detailed description of an embodiment of the power grid safety supervision inspection path planning method provided in this application. The following is a detailed description of an embodiment of the power grid safety supervision inspection path planning device provided in this application.

[0079] Please refer to Figure 2 , a power grid safety supervision inspection path planning device provided in an embodiment of this application includes:

[0080] A power grid area division unit 201, configured to divide the power grid into several areas according to the geographical characteristics and equipment distribution characteristics of the power grid system;

[0081] An inspection index data determination unit 202, configured to obtain historical power grid safety inspection data, and then determine the inspection index data of each region according to the historical power grid safety inspection data in combination with a preset inspection index function;

[0082] An inspection area determination unit 203, configured to determine a plurality of areas to be inspected from each area according to the inspection index data;

[0083] A path planning cost determination unit 204, configured to equivalent the areas to be inspected as key nodes, and calculate the path planning cost data between any key node and other key nodes respectively through a preset cost function;

[0084] An inspection path generation unit 205, configured to generate a power grid safety inspection planning path according to the path planning cost data.

[0085] Furthermore, the device provided in this embodiment may further include:

[0086] A path optimization unit 206, configured to optimize the power grid safety inspection planning path through a preset optimization objective function, and output the optimized power grid safety inspection planning path when the optimization termination condition is met.

[0087] In addition, this application also provides a detailed description of an embodiment of a power grid safety inspection path planning terminal and an embodiment of a computer-readable storage medium.

[0088] As Figure 3 shown, a power grid safety inspection path planning terminal provided in an embodiment of this application, the implementation types of the terminal include but are not limited to: personal computers, industrial computers, servers, and embedded intelligent devices. The main components of the terminal include: a memory 33 and a processor 31;

[0089] The memory 33 is used to store program codes, and the program codes are used to implement a power grid safety inspection path planning method as described in the above embodiment;

[0090] The processor 31 is used to read and execute the program codes.

[0091] A computer-readable storage medium provided in an embodiment of this application, the computer-readable storage medium stores program codes, and the program codes are used to be read and executed by a processor to implement a power grid safety inspection path planning method as provided in the above embodiment.

[0092] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described terminal, device, and unit can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0093] In several embodiments provided in the present application, it should be understood that the disclosed terminals, 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 units is only a logical function division. In actual implementation, there may be other division methods. For example, 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 couplings, direct couplings, or communication connections shown and discussed with each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be electrical, mechanical, or other forms.

[0094] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects and do not necessarily have to be used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present application described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that comprises a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products, or devices.

[0095] It should be understood that in the present application, "at least one (item)" means one or more, and "a plurality" means two or more. "And / or" is used to describe the association relationship of associated objects and indicates that three relationships can exist. For example, "A and / or B" can mean: only A exists, only B exists, and both A and B exist at the same time. Among them, A and B can be singular or plural. The character " / " generally means that the associated objects before and after are in an "or" relationship. "At least one (one) of the following" or its similar expression means any combination of these items, including any combination of single item (one) or plural items (ones). For example, at least one (one) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0096] The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0097] In addition, in each embodiment of the present invention, each functional unit can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of a software functional unit.

[0098] If the above-mentioned integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, 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 causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0099] As described above, the above embodiments are only used to illustrate the technical solutions of the present application and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present application.

Claims

1. A method for planning a power grid safety inspection route, characterized in that: include: The power grid is divided into several regions according to the geographical characteristics and equipment distribution characteristics of the power grid system; Obtaining historical data of power grid safety inspections, and then determining inspection index data for each area based on the historical data of power grid safety inspections and in combination with a preset inspection index function; According to the inspection index data, a number of areas to be inspected are determined from the various areas; The area to be inspected is equivalent to a key node, and the path planning cost data of any key node and other key nodes are calculated respectively through a preset cost function; A power grid safety inspection planning path is generated based on the path planning cost data.

2. A power grid safety inspection route planning method according to claim 1, characterized in that: The inspection index function is specifically: ； In the formula, xc(a) represents the area inspection index of area a, i represents the i-th type of power grid equipment, M represents the number of power grid equipment types, p(a,i) represents the normal operation time of equipment type i in area a, represents the total running time of device type i in region a, It represents the total number of maintenance times of equipment type i in area a within N historical time periods, where N represents the number of time periods of the collected safety inspection historical data. Indicates the weight coefficient of device type i.

3. A power grid safety inspection route planning method according to claim 2, characterized in that: According to the inspection index data, a number of areas to be inspected are determined from the various areas, specifically including: According to the inspection index data corresponding to each area, combined with the preset inspection index threshold, the area whose inspection index data is not less than the inspection index threshold is determined as the area to be inspected.

4. A method for planning a power grid safety inspection route according to claim 1, characterized in that: The cost function is specifically: ； In the formula, u and v are two different key nodes. represents the cost indicator of moving from key node u to key node v, represents the average distance from key node u to key node v in historical data, It represents the average time taken to move from key node u to key node v in historical data. represents the weight coefficient of the average distance length, The weight coefficient representing the average elapsed time.

5. A method for planning a power grid safety inspection route according to claim 1, characterized in that: Generating a power grid safety inspection planning path according to the path planning cost data specifically includes: According to the path planning cost data and in accordance with the preset A* path planning logic, a power grid safety inspection planning path is generated.

6. A method for planning a power grid safety inspection route according to claim 1, characterized in that: After generating the power grid safety inspection planning path, it also includes: (optimization) The power grid safety inspection planning path is optimized through a preset optimization objective function, and when the optimization termination condition is met, the optimized power grid safety inspection planning path is output.

7. A method for planning a power grid safety inspection route according to claim 6, characterized in that: The optimization objective function is specifically: ； ； In the formula, u and v are two different key nodes, J represents the number of key nodes, G(u, v) represents the comprehensive inspection time index of the two key nodes u and v, B(u, v) represents the random path between key nodes u and v, and Y(uv) represents the number of paths between key nodes u and v that meet the conditions. represents the length of the path B(u, v), It represents the average time consumed to complete the inspection through path B(u, v) in the historical safety inspection data. represents the number of inspections completed through path B(u, v) in historical safety inspection data, represents the trajectory index between key nodes u and v, Represents the weight coefficient of distance length, represents the weight coefficient of the average time, The weight coefficient representing the number of completed inspections.

8. A power grid safety inspection route planning device, characterized in that: include: A power grid area division unit is used to divide the power grid into several areas according to the geographical characteristics and equipment distribution characteristics of the power grid system; An inspection index data determination unit is used to obtain power grid safety inspection historical data, and then determine the inspection index data of each area based on the power grid safety inspection historical data and a preset inspection index function; An inspection area determination unit, used to determine a number of areas to be inspected from the various areas according to the inspection index data; A path planning cost determination unit, used to treat the to-be-inspected area as a key node, and calculate the path planning cost data of any key node and other key nodes respectively through a preset cost function; The inspection path generation unit is used to generate a power grid safety inspection planning path according to the path planning cost data.

9. A power grid safety inspection route planning terminal, characterized in that: include: Memory and processor; The memory is used to store program codes, and the program codes are used to implement a power grid safety inspection route planning method according to claims 1 to 7; The processor is used for reading and executing the program code.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores program code, and the program code is used to be read and executed by a processor to implement a power grid safety inspection route planning method as described in claims 1 to 7.

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