A method, device, equipment and medium for deploying substation monitoring equipment

Abstract

The present application provides a method, apparatus, equipment and medium for deploying substation monitoring equipment, which relates to the field of substation detection technology, including: obtaining multiple joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring equipment and the location of potential obstructions; determining multiple alternative deployment points and the deployment status parameters corresponding to each alternative deployment point; for any target monitoring point, analyzing the location of the target monitoring point, the location of potential obstructions and the location of each alternative deployment point to obtain an obstruction analysis result; inputting the analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits into a pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans. The present application can obtain a reasonable, stable deployment plan that meets the joint monitoring needs.

Description

Technical Field

[0001] The present application relates to the field of substation detection technology, and more specifically, to a method, apparatus, equipment, and medium for deploying substation monitoring equipment. Background Art

[0002] With the development of smart grids, online equipment status monitoring systems in smart substations must monitor equipment status in real time, including dissolved gas in oil, partial discharge, capacitive current, dielectric loss, bushing, and capacitance. They must provide accurate, real-time on-site information to adapt to the trend of increasing equipment self-description and self-diagnosis capabilities, and fully tap the potential of evolving from preventive maintenance to predictive maintenance.

[0003] Monitoring power grid and asset conditions requires deploying more sensors. However, it's important to recognize that using wired networks to monitor various smart devices in high-voltage environments like substations presents limitations in terms of wiring layout, network upgrades, installation and maintenance, and cost. Therefore, wireless sensor networks (WSNs) can be used to optimize and improve monitoring networks.

[0004] To ensure the safe operation of substations, conventional technologies typically deploy a number of monitoring devices and sensors to monitor the operating status of electrical equipment, environmental parameters, and other information within the substation. These devices include video surveillance cameras, temperature sensors, humidity sensors, and smoke detectors. These devices enable real-time monitoring of the substation's internal conditions and transmit the data to a control center for analysis and processing.

[0005] However, during the actual deployment process, several issues hindered monitoring effectiveness. For one thing, some substations failed to fully consider on-site environmental factors during the planning phase. For example, buildings or other facilities could obstruct the monitoring range, preventing effective coverage of certain key areas. Furthermore, due to a lack of comprehensive assessment of system reliability, the potential for monitoring equipment failure was not considered when selecting monitoring equipment, resulting in an irrational deployment plan. Furthermore, the requirements for joint monitoring could not be met, resulting in an irrational, unstable deployment plan that failed to accurately and comprehensively monitor substation status and could not be applied in actual substation monitoring scenarios. Summary of the Invention

[0006] The purpose of the embodiments of the present application is to provide a substation monitoring equipment deployment method, device, equipment and medium to solve the above-mentioned problems existing in the prior art, to obtain a reasonable and stable deployment plan that meets the joint monitoring needs, and to comprehensively, accurately and stably monitor the status of the substation.

[0007] In a first aspect, the present invention provides a method for deploying substation monitoring equipment, the method comprising:

[0008] Acquire multiple joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the multiple target monitoring points of the substation;

[0009] Determine multiple candidate deployment points and deployment status parameters corresponding to each candidate deployment point based on the monitoring range of each monitoring device and each target monitoring point;

[0010] For any target monitoring point, analyze the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point to obtain an obstruction analysis result to determine whether there is an obstruction between the target monitoring point and each candidate deployment point;

[0011] The analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits are input into the pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans.

[0012] In an optional embodiment, the determining of multiple candidate deployment points based on the monitoring range of each monitoring device and each target monitoring point includes:

[0013] For any target monitoring point, based on the location of the target monitoring point and the monitoring range of each monitoring device, determine the candidate deployment range of the monitoring device corresponding to the target monitoring point;

[0014] A plurality of candidate deployment points are selected from the candidate deployment ranges of the monitoring devices to be deployed corresponding to the target monitoring points.

[0015] In an optional embodiment, the deployment status parameter includes a failure probability; the failure probability is used to represent the probability of failure of the monitoring device when the monitoring device is deployed at the alternative deployment point;

[0016] The method for determining the deployment status parameters corresponding to each candidate deployment point includes:

[0017] For any candidate deployment point, according to the location of the candidate deployment point, the deployment state parameters corresponding to the candidate deployment point at the location are matched from pre-built candidate deployment points at different locations and corresponding deployment state parameters.

[0018] In an optional embodiment, the analyzing the position of the target monitoring point, the position of the potential obstruction, and the positions of each candidate deployment point includes:

[0019] For any candidate deployment point, if the position of any potential obstruction is located on the line between the position of the candidate deployment point and the position of the target monitoring point, then there is an obstruction between the target monitoring point and the candidate deployment position.

[0020] In an optional embodiment, the deployment state parameter further includes a deployment state decision variable; wherein the deployment state decision variable is used to indicate whether to deploy the monitoring device at the alternative deployment point;

[0021] The method for determining the deployment plan of the preset number of monitoring devices includes:

[0022] The initial value of the deployment state decision variable of each candidate deployment point is set to the ratio of the preset number of monitoring devices to the number of candidate deployment points;

[0023] Randomly select multiple candidate deployment points from all candidate deployment points to obtain a first candidate deployment point;

[0024] Calculating the optimal deployment state decision variables of each first alternative deployment point;

[0025] Return to the execution step: randomly select multiple alternative deployment points from all alternative deployment points until the optimal deployment state decision variables of all alternative deployment points are obtained;

[0026] Based on the optimal deployment state decision variables of all alternative deployment points, a deployment plan for a preset number of monitoring devices is determined.

[0027] In an optional embodiment, the mathematical expression of the substation deployment solution optimization model is as follows:

[0028]

[0029] Where A represents the total expected monitoring benefit of the target substation; N represents the set of target monitoring points; N′ represents the set of joint monitoring points; represents the set of all non-empty subsets of N; a N′ represents the joint monitoring benefit corresponding to any joint monitoring point; p N′ represents the probability of any joint monitoring point being jointly monitored; m represents the number of alternative deployment points; K represents the preset number of monitoring equipment; θ i Represents the deployment state decision variable of the i-th alternative deployment point.

[0030] In a second aspect, the present invention provides a substation monitoring equipment deployment device, the device comprising:

[0031] an acquisition unit, configured to acquire a plurality of joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the plurality of target monitoring points of the substation;

[0032] a determination unit, configured to determine, based on a monitoring range of each monitoring device and each target monitoring point, a plurality of candidate deployment points and a deployment status parameter corresponding to each candidate deployment point;

[0033] An analysis unit is configured to analyze, for any target monitoring point, the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point, and obtain an obstruction analysis result as to whether there is an obstruction between the target monitoring point and each candidate deployment point;

[0034] The output unit is used to input the analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits into the pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans.

[0035] In a third aspect, the present invention provides an electronic device, comprising a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus;

[0036] Memory for storing computer programs;

[0037] The processor is configured to implement any of the methods described in the foregoing embodiments when executing the program stored in the memory.

[0038] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of the aforementioned embodiments is implemented.

[0039] The monitoring equipment deployment scheme of this application fully considers occlusion, monitoring equipment reliability and joint monitoring needs, constructs a substation deployment scheme optimization model with the goal of maximizing the total monitoring benefit and the total number of monitoring equipment as a constraint, and uses a simulated annealing algorithm combined with relaxation and rounding to obtain the optimal deployment scheme for monitoring equipment, achieving the maximization of the total expected monitoring benefit. It can provide further guidance for the application of wireless sensor networks in the field of substation monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 A flowchart of a method for deploying substation monitoring equipment provided in an embodiment of the present application;

[0042] Figure 2 A schematic diagram of a substation target monitoring point provided in an embodiment of the present application;

[0043] Figure 3 An architectural diagram of a method for deploying substation monitoring equipment provided in an embodiment of the present application;

[0044] Figure 4 A schematic diagram of alternative deployment points for substation monitoring equipment provided in an embodiment of the present application;

[0045] Figure 5 A schematic diagram of a substation monitoring equipment deployment solution provided in an embodiment of the present application;

[0046] Figure 6 A schematic diagram of the structure of a substation monitoring equipment deployment device provided in an embodiment of the present application;

[0047] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0049] The substation monitoring equipment deployment method provided in the embodiment of the present application can be applied in a server or in a terminal with strong computing power. The server can be a physical server, a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and basic cloud computing services such as big data and artificial intelligence platforms. The terminal can be a user equipment (UE) such as a mobile phone, smart phone, laptop, digital broadcast receiver, personal digital assistant (PDA), tablet computer (PAD), handheld device, vehicle-mounted device, wearable device, computing device or other processing device connected to a wireless modem, mobile station (MS), mobile terminal, etc. The terminal and the server can be directly or indirectly connected through wired or wireless communication methods, which is not limited in this application.

[0050] The preferred embodiments of the present application are described below in conjunction with the drawings in the specification. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present application and are not used to limit the present application. In addition, the embodiments and features in the embodiments of the present application can be combined with each other if there is no conflict.

[0051] Figure 1 This is a flow chart of a method for deploying substation monitoring equipment provided by an embodiment of the present application. Figure 1 As shown, the method may include:

[0052] Step S110: Obtain multiple joint monitoring points of the target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring equipment, and the location of potential obstructions; based on the monitoring range of each monitoring equipment and each target monitoring point, determine multiple alternative deployment points and the deployment status parameters corresponding to each alternative deployment point.

[0053] In an embodiment of the present application, the monitoring equipment includes an image or video acquisition device and various sensors that can monitor the operation and health status of the substation.

[0054] In this embodiment of the present application, a target substation is provided with multiple target monitoring points. Furthermore, the substation's environment and other facilities may obstruct monitoring of the target monitoring points. Facilities that obstruct monitoring of the target monitoring points are referred to as potential obstructions. A joint monitoring point includes at least two of the multiple target monitoring points in the substation.

[0055] For example, suppose target substation A has five target monitoring points (target monitoring points 1-5). The target substation is expected to monitor all five target monitoring points. Furthermore, joint monitoring of target monitoring points 1 and 2 may yield a joint monitoring benefit. Therefore, target substation A's joint monitoring points are assigned to target monitoring points 1 and 2, and the joint monitoring benefits of these joint monitoring points are also assigned. In practice, the joint monitoring points and their corresponding joint monitoring benefits can be determined based on the substation's actual conditions or manually set.

[0056] In the embodiment of the present application, multiple candidate deployment points are determined based on the monitoring range of each monitoring device and each target monitoring point, including:

[0057] For any target monitoring point, based on the location of the target monitoring point and the monitoring range of each monitoring device, the alternative deployment range of the monitoring device corresponding to the target monitoring point is determined; from the alternative deployment range of each monitoring device to be deployed corresponding to each target monitoring point, multiple alternative deployment points are selected.

[0058] In an embodiment of the present application, after obtaining the alternative deployment range of the monitoring equipment corresponding to each target monitoring point, a comprehensive alternative deployment range including the alternative deployment range corresponding to each target monitoring point can be obtained; by discretely selecting a preset number of points within the comprehensive alternative deployment range, the alternative deployment point can be obtained.

[0059] In an embodiment of the present application, the deployment status parameters include: failure probability and deployment status decision variables; wherein, the failure probability is used to characterize the probability of failure of the monitoring device when the monitoring device is deployed at the alternative deployment point; the deployment status decision variable is used to characterize whether the monitoring device is deployed at the alternative deployment point.

[0060] In the embodiment of the present application, the location that can cover the largest area and is unobstructed is preferably selected as the alternative deployment point; however, it is not guaranteed that all target monitoring points can be monitored.

[0061] In the embodiment of the present application, determining the candidate deployment points includes:

[0062] Determine boundary conditions based on the location of potential obstructions; divide the target substation into several small cells (for example, a 1m*1m square grid); for each cell, evaluate its suitability as an alternative deployment point (taking into account factors such as line of sight obstruction and signal interference); eliminate locations that are obviously unsuitable for installation based on the location of potential obstructions (such as obstacles and power lines); among the remaining cells, prioritize those located near key monitoring areas as initial candidate points; and use clustering algorithms or genetic algorithms to obtain multiple alternative deployment points.

[0063] In the embodiment of the present application, a clustering algorithm is used to obtain multiple candidate deployment points, including:

[0064] All feasible candidate points are divided into a preset number of clusters, and the centroid of each cluster is selected as the candidate deployment point; a preset number of center points are initialized randomly or based on a certain rule; the distance from each candidate point to each center point is calculated and assigned to the nearest center point to form a cluster; the center point position of each cluster is updated to the average value of all points in the cluster; the above process is repeated until convergence, that is, the center point no longer changes significantly, and multiple candidate deployment points are obtained.

[0065] In actual applications, due to the different locations of different alternative deployment points, the working environment faced by the monitoring equipment when deployed at the alternative deployment points is different, and the monitoring equipment has random failure characteristics. Therefore, the failure probability is set for each alternative deployment point in advance according to the location of the different alternative deployment points.

[0066] In other embodiments of the present application, the deployment status parameters may change according to the type of monitoring device, that is, the deployment status parameters are matched according to the location of the candidate deployment point and the type of monitoring device.

[0067] In an embodiment of the present application, a method for determining the deployment status parameters corresponding to each candidate deployment point includes:

[0068] For any candidate deployment point, according to the location of the candidate deployment point, the deployment state parameters corresponding to the candidate deployment point at the location are matched from pre-built candidate deployment points at different locations and corresponding deployment state parameters.

[0069] Step S120: For any target monitoring point, analyze the position of the target monitoring point, the position of the potential obstruction, and the position of each candidate deployment point to obtain an obstruction analysis result of whether there is an obstruction between the target monitoring point and each candidate deployment position point.

[0070] In an embodiment of the present application, the position of the target monitoring point, the position of the potential obstruction, and the position of each candidate deployment point are analyzed, including:

[0071] For any candidate deployment point, if the position of any potential obstruction is located on the line between the position of the candidate deployment point and the position of the target monitoring point, then there is an obstruction between the target monitoring point and the candidate deployment position.

[0072] Step S130: Input the analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits into the pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans.

[0073] In an embodiment of the present application, the substation deployment plan optimization model is constrained by the preset number of monitoring equipment and the range of deployment status decision variable values ​​of alternative deployment points; the objective function is to maximize the total expected monitoring benefit; the range of deployment status decision variable values ​​of alternative deployment points is {0,1}.

[0074] In the embodiment of the present application, the substation deployment solution optimization model is as follows:

[0075]

[0076] Where A represents the total expected monitoring benefit of the target substation; N represents the set of target monitoring points, N = {1, 2, ..., j, ..., n}, and n represents the number of target monitoring points; represents the set of all non-empty subsets of N, that is, represents the exponentiation set operation, represents the empty set; N′ represents the set of joint monitoring points; a N′ It represents the joint monitoring benefit corresponding to any joint monitoring point, which is a preset value; p N′ represents the probability of any joint monitoring point being jointly monitored; m represents the number of alternative deployment points; K represents the preset number of monitoring equipment; θ i Represents the deployment state decision variable of the i-th alternative deployment point.

[0077] In the embodiment of the present application, the probability calculation formula of any joint monitoring point being jointly monitored is as follows:

[0078]

[0079] p M′ =∏ i∈M′ p i θ i ∏ i′∈M-M′ (1-p i′ θ i′ ) (5);

[0080] Where M represents the set of candidate deployment points, M = {1, 2, ..., i, ..., m}, m represents the number of candidate deployment points; M′ represents any subset of the full set of deployment points M; Indicates whether the joint monitoring point set N′ is jointly monitored in the scenario where the deployment point subset M′ is normal and the deployment point subset MM′ is invalid; p M′ represents the probability that the deployment point subset M′ is normal while the deployment point set MM′ is invalid; θ i represents the deployment state decision variable of the candidate deployment point numbered i, 1≤i≤m; when θ i = 1, the sensor is deployed at the candidate deployment point numbered i. When θi =0, indicating no deployment; It represents the occlusion relationship between the target monitoring point numbered j and the candidate deployment point numbered i, obtained from the analysis results of each target monitoring point and the corresponding occlusion object. when When , it means that there is no obstruction between the target monitoring point numbered j and the candidate deployment point numbered i. When , it means there is occlusion; Indicates whether the target monitoring point numbered j is within the monitoring range of the candidate deployment point numbered i; p i represents the normal probability of the alternative deployment point numbered i, which is obtained by 1-the failure probability of the alternative deployment point numbered i; θ i′ represents the deployment state decision variable of the candidate deployment point numbered i', 1≤i'≤m; when θ i′ = 1, the sensor is deployed at the candidate deployment point numbered i'. i′ =0, indicating no deployment; p i′ The normal probability of the alternative deployment point numbered i' is obtained by 1-the failure probability of the alternative deployment point numbered i'.

[0081] In the embodiments of this application, The value range of is {0,1}. When , it means that when the deployment point subset M′ is normal and the deployment point set MM′ fails, the monitoring point subset N′ is jointly monitored. When , it means that it is not jointly monitored.

[0082] In the embodiment of the present application, the full set of deployment points is M, and M' and MM' both represent subsets of M. Therefore, M can be called the full set of deployment points, and M' and MM' can be called deployment point subsets.

[0083] In one embodiment of the present application, M represents a set of alternative deployment points, M′ represents any subset of the full set of deployment points M, that is, any alternative deployment scheme; MM′ represents a set of deployment points where monitoring devices are not deployed in the corresponding alternative deployment scheme; the scenario in which the deployment point subset M′ is normal and the deployment point subset MM′ fails is a scenario in which the corresponding alternative deployment scheme is normal, but the deployment points where monitoring devices are not deployed in the corresponding alternative deployment scheme fail.

[0084] In the embodiment of the present application, whether the target monitoring point numbered j is within the monitoring range of the candidate deployment point numbered i is calculated as follows:

[0085]

[0086] Where I(·) represents the indicator function; represents the distance between the target monitoring point numbered j and the candidate deployment point numbered i; R represents the monitoring range of the monitoring equipment; (x j ,y j ,z j ) represents the position of the target monitoring point numbered j; (x i ,y i ,z i ) represents the location of the alternative deployment point numbered i.

[0087] In an embodiment of the present application, a method for determining a deployment plan for a preset number of monitoring devices includes:

[0088] The initial value of the deployment state decision variable of each alternative deployment point is set to the ratio of the preset number of monitoring devices to the number of alternative deployment points; a plurality of alternative deployment points are randomly selected from all the alternative deployment points to obtain the first alternative deployment points; the optimal deployment state decision variable of each first alternative deployment point is calculated; the execution step is returned to: a plurality of alternative deployment points are randomly selected from all the alternative deployment points until the optimal deployment state decision variables of all the alternative deployment points are obtained; and a deployment plan for a preset number of monitoring devices is determined based on the optimal deployment state decision variables of all the alternative deployment points.

[0089] In one embodiment of the present application, calculating the optimal deployment state decision variable for each first candidate deployment point includes:

[0090] The initial values ​​of the deployment state decision variables of other alternative deployment points except the first alternative deployment points, the analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment state parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefit are introduced into the substation deployment plan optimization model to obtain the optimal deployment state decision variables of each first alternative deployment point.

[0091] In the above-mentioned embodiment of the present application, when calculating the optimal deployment state decision variables of each first alternative deployment point, all joint monitoring points and corresponding joint monitoring benefits are brought into the substation deployment plan optimization model to obtain the optimal deployment state decision variables of each first alternative deployment point.

[0092] In another embodiment of the present application, calculating the optimal deployment state decision variable for each first candidate deployment point includes:

[0093] The joint monitoring points including the target monitoring points corresponding to the first alternative deployment points are used as the target joint monitoring points. The initial values ​​of the deployment state decision variables of the alternative deployment points other than the first alternative deployment points, the analysis results of the target monitoring points and the corresponding obstructions, the deployment state parameters of the alternative deployment points and the corresponding deployment state parameters, the monitoring range of the monitoring equipment, the target joint monitoring points and the corresponding joint monitoring benefits are introduced into the substation deployment plan optimization model to obtain the optimal deployment state decision variables of the first alternative deployment points.

[0094] In the above-mentioned embodiment of the present application, when calculating the optimal deployment state decision variables of each first alternative deployment point, the corresponding target monitoring point is determined according to each first alternative deployment point; the joint monitoring point containing the target monitoring point is used as the target joint monitoring point participating in the calculation, and the target joint monitoring point and the corresponding joint monitoring benefit are brought into the substation deployment plan optimization model, thereby obtaining the optimal deployment state decision variables of each first alternative deployment point.

[0095] In the embodiment of the present application, the initial values ​​of the deployment state decision variables of the other candidate deployment points except the first candidate deployment points, the analysis results of the target monitoring points and the corresponding obstructions, the candidate deployment points and the corresponding deployment state parameters, the monitoring range of the monitoring equipment, the target joint monitoring points and the corresponding joint monitoring benefits are introduced into the substation deployment plan optimization model, including:

[0096] According to the position of each candidate deployment point and the position of each target monitoring point, determine whether each target monitoring point is within the monitoring range of each candidate deployment point, that is, substitute the position of each candidate deployment point and the position of each target monitoring point into formula (6) and formula (7);

[0097] Based on the analysis results of each target monitoring point and the corresponding obstruction, whether each target monitoring point is within the monitoring range of each candidate deployment point, and the initial values ​​of the deployment state decision variables of other candidate deployment points except the first candidate deployment points, calculate whether the joint monitoring point set N′ is jointly monitored, that is, bring it into formula (4) to obtain the formula for each first candidate deployment point;

[0098] Based on the failure probability of each candidate deployment point and the initial values ​​of the deployment state decision variables of the other candidate deployment points except the first candidate deployment points, the probability that the deployment point set M′ is normal and the deployment point set MM′ is ineffective is calculated. That is, it is substituted into formula (5) to obtain the formula for the optimal deployment state decision variables of each first candidate deployment point.

[0099] Based on the calculation results of whether the joint monitoring point set N′ is jointly monitored and the probability that the deployment point set M′ is normal and the deployment point set MM′ is ineffective, the probability of any joint monitoring point being jointly monitored is calculated; that is, the formula for each first candidate deployment point is substituted into formula (3) to obtain the formula for the optimal deployment state decision variable for each first candidate deployment point;

[0100] According to the probability of any joint monitoring point being jointly monitored, different joint monitoring points and corresponding joint monitoring benefits, the total expected monitoring benefit of the target substation is calculated; that is, all joint monitoring points and corresponding joint monitoring benefits, as well as the formulas for each first candidate deployment point are substituted into formula (1) to obtain the formula for the optimal deployment state decision variable for each first candidate deployment point;

[0101] By combining the above formula and formula (2) and solving them, we can obtain the optimal deployment state decision variables of each first candidate deployment point.

[0102] In an embodiment of the present application, a preset number of monitoring device deployment schemes are determined based on the optimal deployment state decision variables of all candidate deployment points, including:

[0103] Get the initial value of the temperature parameter, the number of iterations, and the maximum number of new solutions that are not accepted continuously of the configured simulated annealing algorithm, that is, initialize the simulated annealing algorithm;

[0104] All candidate deployment points are sorted from largest to smallest according to the corresponding optimal deployment state decision variables, and a preset number (the preset number of monitoring devices) of candidate deployment points are selected from the sorted candidate deployment points to obtain second candidate deployment points and an initial deployment plan consisting of the second candidate deployment points;

[0105] Score the initial deployment plan based on the configured evaluation criteria;

[0106] Randomly perturb the initial deployment plan to obtain a first deployment plan, and score the first deployment plan according to the configured evaluation criteria;

[0107] If the difference between the score of the initial deployment plan and the score of the first deployment plan is greater than 0, the first deployment plan will be used as the new initial deployment plan. Otherwise, the probability Accept the first deployment plan as the new initial deployment plan;

[0108] If L consecutive first deployment plans are not accepted, the first deployment plan is output as the optimal deployment plan and the process ends; otherwise, the initial value of the temperature parameter is reduced, and the optimal deployment state decision variables of all alternative deployment points are recalculated.

[0109] In an embodiment of the present application, if the optimal deployment state decision variable values ​​of multiple alternative deployment points are the same, resulting in the inability to select a preset number of alternative deployment points, an alternative deployment point with a larger or smaller number can be selected from multiple alternative deployment points with the same optimal deployment state decision variable, or a random selection can be made.

[0110] In the embodiment of the present application, when multiple candidate deployment points are randomly selected from all candidate deployment points subsequently, the candidate deployment point whose optimal deployment state decision variable has been calculated as the first candidate deployment point will not be excluded.

[0111] For example, there are 100 candidate deployment points and the preset number of monitoring devices is 10. The initial value of the deployment state decision variable for each candidate deployment point is 10 / 100=0.1. Two candidate deployment points are randomly selected from the 100 candidate deployment points to obtain the first candidate deployment point. At this time, the values ​​of the other 98 candidate deployment points remain unchanged, and the sum of the values ​​of the other 98 candidate deployment points is 9.8. Since the substation deployment plan optimization model is constrained by the preset number of monitoring devices, that is, the sum of the deployment state decision variable values ​​of all candidate deployment points is 10, the sum of the deployment state decision variable values ​​of the two first candidate deployment points is 10-9.8=0.2.

[0112] At this point, the target monitoring points and the corresponding obstruction analysis results, the candidate deployment points and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, the joint monitoring points (which can also be target joint monitoring points) and the corresponding joint monitoring benefits are introduced into the substation deployment plan optimization model, resulting in a quadratic function with only two variables; these two variables are the deployment state decision variables of the two first candidate deployment points. At this point, the substation deployment plan optimization model is converted into a quadratic function of the deployment state decision variable values ​​of the two first candidate deployment points, and the solution of the substation deployment plan optimization model is converted into solving the maximum value problem of the quadratic function on a closed interval, thereby obtaining the optimal deployment state decision variables of the two first candidate deployment points.

[0113] Then, randomly select two alternative deployment points from the 100 alternative deployment points (not excluding the two calculated above) to obtain the new first alternative deployment point. Repeat the above process until all alternative deployment points correspond to an optimal deployment state decision variable. Sort the 100 alternative deployment points from large to small according to the value of their optimal deployment state decision variable, and select the first K or first 10 as the second alternative deployment points. The deployment plan with the first 10 as the second alternative deployment points and the last 90 as the alternative deployment points is used as the initial solution of the simulated annealing algorithm. Solve the simulated annealing algorithm to obtain a deployment plan for a preset number of monitoring devices.

[0114] In an embodiment of the present application, the above-mentioned substation deployment scheme optimization model is a nonlinear 0-1 programming model, and the present application adopts a simulated annealing algorithm combining relaxation and rounding to solve it.

[0115] In other embodiments of the present application, the monitoring types of different monitoring devices may be obtained; the failure probability of the monitoring devices may be determined based on the monitoring types of the different monitoring devices; and the monitoring relationship between the monitoring devices of different monitoring types and each target monitoring point may be determined; that is:

[0116] Acquire multiple joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the multiple target monitoring points of the substation;

[0117] Based on the monitoring range, monitoring type and target monitoring points of each monitoring device, multiple alternative deployment points and the deployment state parameters corresponding to each alternative deployment point are determined; the deployment state parameters include failure probability and deployment state decision variables; the deployment state decision variable is the decision variable for whether the alternative deployment point numbered i should deploy the g-th sensor

[0118] For any target monitoring point, analyze the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point to obtain an obstruction analysis result to determine whether there is an obstruction between the target monitoring point and each candidate deployment point;

[0119] The analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range and monitoring type of the monitoring equipment, and each joint monitoring point and the corresponding joint monitoring benefit are input into a pre-built substation deployment plan optimization model to obtain a deployment plan with a preset number of monitoring devices. The substation deployment plan optimization model uses the preset number, monitoring range, and monitoring type of monitoring equipment as constraints and the total monitoring benefit of the substation as the objective function.

[0120] In the above embodiment of the present application, the monitoring range and type of the monitoring device may be different. Assume that there are G different types of monitoring devices, where the monitoring range, total number and failure probability of the g-th type of monitoring device are R g , K g and At this time, when the g-th monitoring device is deployed at the candidate deployment point numbered i, its failure probability is At the same time, the monitoring relationship f between the g-th monitoring device and the target monitoring point numbered j can be defined g,j , where f g,j ∈{0,1}, when f g,j= 0, indicating that the g-th sensor cannot monitor the monitoring point numbered j. g,j =1, it means that the g-th sensor can monitor the monitoring point numbered j. Finally, the decision variable for whether the candidate deployment point numbered i should deploy the g-th sensor can be defined as Based on the above definition, a substation monitoring system deployment model under different types of sensors can be established, and the simulated annealing algorithm combined with relaxation and rounding can be used to solve it.

[0121] like Figures 2 to 3 As shown, in this embodiment of the present application, the substation monitoring equipment deployment method further includes:

[0122] Step 1: Task scenario characterization method, targeting the scenario of using multiple sensors to monitor the operation and health of a substation. In this scenario, sensors have random failure characteristics, the substation environment can block sensor monitoring, and different subsets of substation monitoring points have different joint monitoring benefits.

[0123] The following processes are included:

[0124] 1. Use Ω to represent the entire mission area. All candidate deployment points, monitoring points, and obstructions are located within this mission area. In this example, Ω is Figure 4 A square area with a side length of 35m;

[0125] 2. Number the monitoring points to form a monitoring point number set:

[0126] N={1,2,...,j,...,n}(8),

[0127] In formula (8), N represents the set of n monitoring point numbers. In this example, n = 7, and the monitoring points are Figure 4 The triangle in the middle indicates that the monitoring point number is marked in the triangle;

[0128] 3. The location of the monitoring point numbered j is: (x j ,y j ,z j ),1≤j≤n. In this example, it is assumed that all monitoring points are located in the same plane. Figure 4 The position of the middle triangle indicates the position of the corresponding monitoring point;

[0129] 4. Use represents the set of all non-empty subsets of N, that is, in, represents the exponentiation set operation, represents the empty set;

[0130] 5. The joint monitoring benefit of the monitoring point subset N′ is: Note that a single monitoring point can be viewed as In this example, a {1} =a {4} =a {6} =a {7} =1,a {2} =a {3} =a {5} =1.5, a {2,3} =a {1 ,5} =a {4,6,7} =1.2, other a {2,3} =a {1,5} =a {4,6,7} =1.2 are both 0;

[0131] 6. Number the candidate deployment points to form a candidate deployment point number set:

[0132] M={1,2,...,i,...,m} (9),

[0133] In formula (9), M represents a set of m candidate deployment point numbers. In this example, m = 14, and the candidate deployment points are Figure 4 The circle in the figure indicates the number of the alternative deployment point.

[0134] 7. The location of the alternative deployment point numbered i is: (x i ,y i ,z i ),1≤i≤m. In this example, it is assumed that all candidate deployment points are located in the same plane. Figure 4 The position of the middle circle indicates the position of the corresponding alternative deployment point;

[0135] 8. The normal probability of the alternative deployment point numbered i is: p i ,1≤i≤m. In this example, p1=p3=p5=0.9, and other p i Both are 0.95;

[0136] 9. The monitoring range of the sensor is R. In this example, R = 12;

[0137] 10. The total number of sensors is K. In this example, K = 5;

[0138] 11. The occlusion relationship between the monitoring point numbered j and the candidate deployment point numbered i is: in, when When , it means there is no obstruction between the monitoring point numbered j and the candidate deployment point numbered i. In this example, the obstruction is indicated by Figure 4The shaded rectangle in the middle indicates that when the line connecting the monitoring point numbered j and the candidate deployment point numbered i does not pass through any obstructions, on the contrary,

[0139] Step 2: A reliability calculation model for monitoring subsets of substation monitoring points is developed to calculate the probability of joint monitoring of different subsets of substation monitoring points under a given sensor deployment scheme. This includes the following steps:

[0140] 1. The decision variable for whether to deploy a sensor at the candidate deployment point numbered i is: θ i ,1≤i≤m. Among them, when When , the candidate deployment point numbered i deploys the sensor, When , it means not to deploy;

[0141] 2. Use p M′ represents the probability that the deployment point set M′ is normal and the deployment point set MM′ is invalid, then:

[0142]

[0143] 3. The distance between the monitoring point numbered j and the alternative deployment point numbered i:

[0144]

[0145] In formula (11), represents the distance between the monitoring point numbered j and the candidate deployment point numbered i;

[0146] 4. Whether the monitoring point numbered j is within the monitoring range of the candidate deployment point numbered i:

[0147]

[0148] In formula (12), Indicates whether the monitoring point numbered j is within the monitoring range of the candidate deployment point numbered i. Where I(·) represents the indicator function;

[0149] 5. Use Indicates whether the monitoring point subset N′ is jointly monitored when the deployment point set M′ is normal and the deployment point set MM′ is failed. Then:

[0150]

[0151] In formula (13), it is easy to see that The value range of is {0,1}. When , it means that when the deployment point set M′ is normal and the deployment point set MM′ is invalid, the monitoring point subset N′ is jointly monitored. When , it means it is not jointly monitored;

[0152] 6. Use to express the probability that the subset N′ of monitoring points is jointly monitored given the sensor deployment scheme:

[0153]

[0154] Step 3: A substation monitoring system deployment model is developed, which aims to maximize the total expected monitoring benefit, takes the total number of sensors as a constraint, and uses a simulated annealing algorithm combined with relaxation and rounding to solve the optimal sensor deployment plan. This includes the following steps:

[0155] 1. The value range constraint of the decision variable for whether to deploy a sensor at the candidate deployment point numbered i:

[0156] θ i ∈{0,1},1≤i≤m (15);

[0157] 2. Constraints on the total number of sensors:

[0158]

[0159] 3. Set the objective function to maximize the total expected monitoring benefit:

[0160]

[0161] 4. Summarize formula (16) and formula (17) to obtain the substation monitoring system deployment model as shown below:

[0162]

[0163] 5. Formula (18) is a nonlinear 0-1 programming model. The present invention uses a simulated annealing algorithm that combines relaxation and rounding to solve it. The specific steps of the algorithm are:

[0164] 1) Relax formula (18) to transform it into the following model:

[0165]

[0166]

[0167] 2) The present invention uses the following 3) to 6) to solve formula (19);

[0168] 3) Initialize each θ i are equal to As the current solution;

[0169] 4) Repeat step 5 for t = 1, ..., T. In this example, T = 200.

[0170] 5) Randomly select two candidate deployment points i1 and i2, and the θ i While keeping the same, find the optimal solution for these two deployment points. and Note that formula (19) is now transformed into the problem of solving the maximum value of a quadratic function on a closed interval, so the optimal and

[0171] 6) Obtain the optimal solution of formula (19)

[0172] 7) Set the deployment point according to Arrange them in descending order, deploy sensors at the first K deployment points, and do not deploy sensors at other deployment points;

[0173] 8) Using the deployment scheme described in 7) as the initial solution of the simulated annealing algorithm;

[0174] 9) Give the temperature parameter Q of the simulated annealing algorithm a sufficiently large initial value Q0. In this example, Q0 = 100;

[0175] 10) Given the number of iterations U of the simulated annealing algorithm itself. In this example, U = 30;

[0176] 11) Given L. In this example, L = 4;

[0177] 12) For u = 1, ..., U, perform 13) to 16);

[0178] 13) Randomly perturb the current solution to generate a new solution;

[0179] 14) Calculate the difference ΔA between the solution after transformation and the objective function before transformation;

[0180] 15) If △A>0, accept the new solution as the current solution, otherwise use the probability Accept the new solution as the current solution;

[0181] 16) If L consecutive new solutions are not accepted, the current solution is output as the optimal solution and the process ends.

[0182] Otherwise go to 17);

[0183] 17)Q decreases and goes to 12).

[0184] In this example, the maximum value of the objective function can be obtained as 10.3, and the following can be obtained: Figure 5The optimal sensor deployment scheme shown in Figure 1. The solid circles represent candidate deployment points for sensor deployment.

[0185] Corresponding to the above method, the embodiment of the present application also provides a substation monitoring equipment deployment device, such as Figure 6 As shown, the substation monitoring equipment deployment device includes:

[0186] An acquisition unit 610 is configured to acquire a plurality of joint monitoring points of a target substation, and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the plurality of target monitoring points of the substation;

[0187] A determining unit 620 is configured to determine a plurality of candidate deployment points and a deployment status parameter corresponding to each candidate deployment point based on a monitoring range of each monitoring device and each target monitoring point;

[0188] An analysis unit 630 is configured to analyze, for any target monitoring point, the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point, and obtain an obstruction analysis result of whether there is an obstruction between the target monitoring point and each candidate deployment point;

[0189] Output unit 640 is used to input the analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits into a pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans.

[0190] The functions of each functional unit of the substation monitoring equipment deployment device provided in the above embodiments of the present application can be achieved through the above method steps. Therefore, the specific working process and beneficial effects of each unit in the substation monitoring equipment deployment device provided in the embodiments of the present application will not be repeated here.

[0191] The present application also provides an electronic device, such as Figure 7 As shown, it includes a processor 710 , a communication interface 720 , a memory 730 and a communication bus 740 , wherein the processor 710 , the communication interface 720 , and the memory 730 communicate with each other via the communication bus 740 .

[0192] Memory 730, for storing computer programs;

[0193] The processor 710 is configured to execute the program stored in the memory 730 by performing the following steps:

[0194] Acquire multiple joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the multiple target monitoring points of the substation;

[0195] Determine multiple candidate deployment points and deployment status parameters corresponding to each candidate deployment point based on the monitoring range of each monitoring device and each target monitoring point;

[0196] For any target monitoring point, analyze the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point to obtain an obstruction analysis result to determine whether there is an obstruction between the target monitoring point and each candidate deployment point;

[0197] The analysis results of each target monitoring point and the corresponding obstruction, each alternative deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits are input into the pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans.

[0198] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is used in the figure, but this does not mean that there is only one bus or only one type of bus.

[0199] The communication interface is used for communication between the above electronic device and other devices.

[0200] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage. Alternatively, the memory may be at least one storage device located away from the processor.

[0201] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, and discrete hardware components.

[0202] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments to solve the problems can be found in Figure 1 The various steps in the embodiment shown are implemented, therefore, the specific working process and beneficial effects of the electronic device provided by the embodiment of the present application are not repeated here.

[0203] In another embodiment provided in the present application, a computer-readable storage medium is also provided, which stores instructions. When the computer-readable storage medium is run on a computer, the computer executes the substation monitoring equipment deployment method described in any of the above embodiments.

[0204] In another embodiment provided by the present application, a computer program product including instructions is also provided, which, when executed on a computer, enables the computer to execute the substation monitoring equipment deployment method described in any one of the above embodiments.

[0205] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the embodiments of the present application can be implemented in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the embodiments of the present application can be implemented in the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0206] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0207] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0208] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0209] Although preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0210] Obviously, those skilled in the art can make various changes and modifications to the embodiments of the present application without departing from the spirit and scope of the embodiments of the present application. Thus, if these modifications and variations of the embodiments of the present application fall within the scope of the claims and their equivalents, the embodiments of the present application are also intended to include these modifications and variations.

Claims

1. A method for deploying substation monitoring equipment, characterized in that: The method comprises: Acquire multiple joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the multiple target monitoring points of the substation; Determining, based on the monitoring range of each monitoring device and each target monitoring point, multiple candidate deployment points and deployment state parameters corresponding to each candidate deployment point; wherein the deployment state parameters include: a deployment state decision variable; the deployment state decision variable is used to indicate whether to deploy the monitoring device at the candidate deployment point; For any target monitoring point, analyze the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point to obtain an obstruction analysis result to determine whether there is an obstruction between the target monitoring point and each candidate deployment point; Input the analysis results of each target monitoring point and the corresponding obstruction, each candidate deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits into the pre-built substation deployment plan optimization model to obtain a deployment plan for a preset number of monitoring equipment; The analyzing the position of the target monitoring point, the position of the potential obstruction, and the position of each candidate deployment point includes: for any candidate deployment point, if the position of any potential obstruction is located on the line connecting the position of the candidate deployment point and the position of the target monitoring point, then there is an obstruction between the target monitoring point and the candidate deployment point; The method for determining the deployment plan of the preset number of monitoring devices includes: The initial value of the deployment state decision variable of each alternative deployment point is set to the ratio of the preset number of monitoring devices to the number of alternative deployment points; a plurality of alternative deployment points are randomly selected from all the alternative deployment points to obtain the first alternative deployment points; the optimal deployment state decision variable of each first alternative deployment point is calculated; the execution step is returned to: a plurality of alternative deployment points are randomly selected from all the alternative deployment points until the optimal deployment state decision variables of all the alternative deployment points are obtained; and a deployment plan for a preset number of monitoring devices is determined based on the optimal deployment state decision variables of all the alternative deployment points.

2. The method according to claim 1, wherein The method of determining multiple candidate deployment points based on the monitoring range of each monitoring device and each target monitoring point includes: For any target monitoring point, based on the location of the target monitoring point and the monitoring range of each monitoring device, determine the candidate deployment range of the monitoring device corresponding to the target monitoring point; A plurality of candidate deployment points are selected from the candidate deployment ranges of the monitoring devices to be deployed corresponding to the target monitoring points.

3. The method according to claim 2, wherein The deployment status parameter also includes a failure probability; the failure probability is used to characterize the probability of failure of the monitoring device when the monitoring device is deployed at the alternative deployment point; The method for determining the deployment status parameters corresponding to each candidate deployment point includes: For any candidate deployment point, according to the location of the candidate deployment point, the deployment state parameters corresponding to the candidate deployment point at the location are matched from pre-built candidate deployment points at different locations and corresponding deployment state parameters.

4. The method according to claim 3, wherein The mathematical expression of the substation deployment optimization model is as follows: ； Where A represents the total expected monitoring benefit of the target substation; N represents the set of target monitoring points; represents the set of joint monitoring points; express The set of all non-empty subsets of ; Indicates the joint monitoring benefit corresponding to any joint monitoring point; represents the probability of any joint monitoring point being jointly monitored; m represents the number of alternative deployment points; K represents the preset number of monitoring devices; Represents the deployment state decision variable of the i-th alternative deployment point.

5. A substation monitoring equipment deployment device using the substation monitoring equipment deployment method according to any one of claims 1 to 4, characterized in that: The device comprises: an acquisition unit, configured to acquire a plurality of joint monitoring points of a target substation and the joint monitoring benefits corresponding to each joint monitoring point, a preset number of monitoring devices, and the locations of potential obstructions; wherein the joint monitoring points include at least two of the plurality of target monitoring points of the substation; a determination unit, configured to determine, based on a monitoring range of each monitoring device and each target monitoring point, a plurality of candidate deployment points and a deployment status parameter corresponding to each candidate deployment point; An analysis unit is configured to analyze, for any target monitoring point, the position of the target monitoring point, the position of potential obstructions, and the positions of each candidate deployment point, and obtain an obstruction analysis result as to whether there is an obstruction between the target monitoring point and each candidate deployment point; The output unit is used to input the analysis results of each target monitoring point and the corresponding obstruction, each candidate deployment point and the corresponding deployment status parameters, the monitoring range of the monitoring equipment, each joint monitoring point and the corresponding joint monitoring benefits into the pre-built substation deployment plan optimization model to obtain a preset number of monitoring equipment deployment plans; The analyzing unit is specifically configured to: for any candidate deployment point, if the position of any potential obstruction is located on the line between the position of the candidate deployment point and the position of the target monitoring point, then there is an obstruction between the target monitoring point and the candidate deployment position point; The output unit is specifically used to: set the initial value of the deployment state decision variable of each alternative deployment point to the ratio of the preset number of monitoring devices to the number of alternative deployment points; randomly select multiple alternative deployment points from all alternative deployment points to obtain first alternative deployment points; calculate the optimal deployment state decision variable of each first alternative deployment point; return to the execution step: randomly select multiple alternative deployment points from all alternative deployment points until the optimal deployment state decision variables of all alternative deployment points are obtained; and determine a preset number of monitoring device deployment plans based on the optimal deployment state decision variables of all alternative deployment points.

6. An electronic device, characterized in that: The electronic device includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus; Memory for storing computer programs; A processor, configured to implement the method according to any one of claims 1 to 4 when executing a program stored in a memory.

7. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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