A method, system, device and medium for deploying a line of equipment for artificially intervening in a severe convective weather disaster of a power grid

Abstract

The application provides a power grid strong convective disaster artificial intervention equipment defense line deployment method, system, device and medium, the method is based on the strong convective warning data and power grid operation data obtained to identify the power grid protection target currently in the risk path, and the comprehensive risk coefficient of each target is calculated to generate a protection target list, according to the set topology attribute of each target in the protection target list, a differentiated space mapping model is called to calculate the position, a theoretical interception position is generated, the neighborhood analysis and fusion optimization of the theoretical interception position are carried out to identify the protection gap, and the state information of the available mobile artificial intervention equipment in the region is planned for task assignment and path planning, the accurate and active protection of the key targets such as the transformer substation and the power transmission channel is realized, and the problems of passive disaster bearing of the traditional power grid weather disaster prevention, the mismatch between the weather modification operation and the power grid protection demand, and the insufficient timeliness of operation scheduling are solved.

Description

Technical Field

[0001] This invention relates to the field of artificial intervention in severe convective meteorological disasters in power grids, specifically to a method, system, equipment, and medium for deploying artificial intervention equipment for severe convective meteorological disasters in power grids. Background Technology

[0002] Severe convective weather has become one of the most significant threats to the safe operation of my country's power grid. Statistics show that transmission line tripping and equipment damage caused by severe convective weather account for over 60% of the total losses from meteorological disasters affecting the power grid. Currently, power grid disaster prevention measures mainly rely on static physical protection such as lightning rods and lightning wires, which is essentially a passive approach to disaster mitigation. Its core function is to reduce post-disaster losses, but it cannot intervene at the source or proactively eliminate severe weather systems before they form or move into critical areas. This passivity makes it difficult for the power grid to adapt to the dynamic evolution of meteorological risks, resulting in blind spots in the disaster prevention system and shortcomings in proactive measures. Therefore, developing key technologies capable of proactively mitigating or even suppressing severe weather processes, and promoting a shift in defense strategies from "passive acceptance" to "proactive elimination," is of great and urgent significance for fundamentally reducing the risk of power grid failures and improving system resilience and operational reliability.

[0003] After decades of development, weather modification technology has the capability to achieve hail suppression, rain enhancement, and lightning suppression through artificial intervention equipment such as rockets, artillery, aircraft, and drones. However, existing operational models have significant limitations: First, operational design mainly targets large-scale fixed areas such as agriculture and reservoirs, relying on pre-set fixed operation points. Its deployment logic is incompatible with the diverse, highly discrete, and topologically interconnected protection targets unique to the power grid, including "points" (substations), "lines" (transmission lines), and "areas" (regional load centers). It lacks spatial optimization deployment methods tailored to the physical connections and electrical importance of the power grid. Second, operational scheduling is typically based on relatively broad administrative regions and forecast conclusions, lacking minute- to hour-level rapid resource scheduling and path planning strategies for specific high-value power grid targets during the rapid formation, dissipation, and movement of severe convective weather, resulting in insufficient timeliness. Currently, research and application of artificial intervention technologies for severe convective weather disasters affecting the power grid are still in their infancy.

[0004] Therefore, solving the above-mentioned technical problems is of great significance. Summary of the Invention

[0005] To address the lack of spatial array optimization deployment methods for power grid physical connections and electrical importance in existing technologies, as well as the insufficient timeliness of rapid resource scheduling and path planning strategies, this invention proposes a method, system, equipment, and medium for deploying artificial intervention equipment defense lines for power grid severe convective disasters.

[0006] Firstly, a method for deploying artificial intervention equipment defense lines against severe convective weather in power grids is provided, including: Based on the acquired severe convection early warning data and power grid operation data, identify the power grid protection targets currently on the risk path, calculate the comprehensive risk coefficient of each target, and generate a list of protection targets; Based on the geometric topology attributes of each target in the protection target list, a differentiated spatial mapping model is invoked to calculate the array positions and generate theoretical interception array positions. The theoretical interception positions are analyzed and fused to identify protection gaps, and the status information of available mobile manual intervention equipment in the area is used to assign tasks and plan paths.

[0007] Secondly, a system for deploying artificial intervention equipment for power grid severe convective disasters is provided, including: The identification module is used to identify power grid protection targets currently on risk paths based on the acquired severe convection early warning data and power grid operation data, calculate the comprehensive risk coefficient of each target, and generate a list of protection targets; The settlement module is used to calculate the array positions by calling a differentiated spatial mapping model based on the geometric topology attributes of each target in the protection target list, and to generate theoretical interception array positions. The overall planning module is used to perform neighborhood analysis and fusion optimization on the theoretical interception positions to identify protection gaps, and to coordinate the status information of available mobile manual intervention equipment in the area for task assignment and path planning.

[0008] In another aspect, this application also provides an electronic device, comprising: at least one processor and a memory; the memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a method for deploying artificial intervention equipment defense lines for severe convective disasters in power grids, as described above, is implemented.

[0009] In another aspect, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed, implements the above-described method for deploying artificial intervention equipment defense lines for severe convective disasters in power grids.

[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a method, system, equipment, and medium for deploying artificial intervention equipment for power grid severe convective disasters. The method identifies power grid protection targets currently on risk paths based on acquired severe convective weather warning data and power grid operation data, calculates the comprehensive risk coefficient of each target to generate a protection target list, and uses a differentiated spatial mapping model to calculate the target positions based on the set topological attributes of each target in the list. This generates theoretical interception positions, performs neighborhood analysis and fusion optimization on these theoretical interception positions to identify protection gaps, and coordinates the status information of available mobile artificial intervention equipment within the area for task assignment and path planning. This achieves precise and proactive protection for key targets such as substations and transmission channels, solving problems such as passive disaster bearing in traditional power grid meteorological disaster prevention, mismatch between artificial weather modification operations and power grid protection needs, and insufficient timeliness of operation scheduling. Attached Figure Description

[0011] Figure 1 This is a schematic diagram illustrating the implementation steps of the method for deploying artificial intervention equipment for severe convective weather disasters in power grids according to the present invention. Figure 2 This is a flowchart of the deployment method for the defense line of artificial intervention equipment for severe convective weather disasters in power grids according to the present invention; Figure 3 This is a schematic diagram illustrating the specific process of the deployment method for the artificial intervention equipment defense line against severe convective weather in power grids according to the present invention. Figure 4 This is a schematic diagram of the composition of the power grid severe convective disaster artificial intervention equipment defense line deployment system of the present invention; Figure 5 This is a schematic diagram of the deployment system for the artificial intervention equipment defense line against severe convective weather in the power grid according to the present invention. Figure 6 This is a schematic diagram of an electronic device structure according to the present invention. Detailed Implementation

[0012] This invention provides a method, system, equipment, and medium for deploying artificial intervention equipment for power grid severe convective disasters, such as... Figure 1 As shown, it includes the following steps: Step 1: Dynamic identification of high-value targets in the power grid under severe convective disasters: Based on real-time severe convective early warning data and power grid topology and operation data, calculate the set of high-asset-value power grid targets currently on the risk path, overlay early warning information, calculate the real-time comprehensive risk coefficient of each target on the risk path, and generate a list of protection targets; Step 2: Differentiated Active Interception Array Generation Based on Power Grid Topology Characteristics: Based on the geometric topology attributes of the targets in the protection list, the spatial mapping model is used to calculate the array positions: For nodal targets, point-shaped interception arrays are constructed upwind; for linear targets, the defense mode is determined based on the angle between the thunderstorm movement wind direction and the line direction, and strip-shaped interception arrays parallel to the line direction or guard-type interception arrays located at the front end of the line are constructed respectively; finally, the theoretical optimal interception center coordinates and operating parameters for each target are output. Step 3: Protection Gap Analysis and Dynamic Scheduling of Mobile Equipment: Perform a neighborhood search on the theoretically optimal interception positions for each target to determine whether the protection coverage of adjacent positions overlaps; if the preset fusion conditions are met, merge multiple independent positions into a shared defense cluster and recalculate the coordinates of the center position of the cluster; then compare the optimized positions with fixed equipment to identify gaps and coordinate the dynamic task assignment of mobile equipment. Step 4: Dynamic adjustment of defense lines and generation of instructions: Real-time tracking of the evolution of severe convective systems. When preset triggering conditions are met, the interception positions are corrected or recalculated based on the latest meteorological conditions, and dynamic adjustment instructions are generated.

[0013] To better understand the present invention, the following description, in conjunction with the accompanying drawings and embodiments, will further illustrate the content of the present invention.

[0014] Example 1: A method for deploying artificial intervention equipment defense lines for severe convective disasters in power grids, such as Figure 2 As shown, it includes: Step S1: Based on the acquired severe convection early warning data and power grid operation data, identify the power grid protection targets currently on the risk path, calculate the comprehensive risk coefficient of each target, and generate a list of protection targets; Step S2: Based on the geometric topology attributes of each target in the protection target list, call the differentiated spatial mapping model to calculate the array positions and generate theoretical interception array positions; Step S3: Perform neighborhood analysis and fusion optimization on the theoretical interception positions to identify protection gaps, and coordinate the status information of available mobile manual intervention equipment in the area for task assignment and path planning.

[0015] In this embodiment, when performing step S1 to identify protection targets and generate a list of protection targets, since power grid assets include point-distributed sites and linearly distributed channels with significant differences in their physical forms, classifying and discretizing the targets into nodal and linear types can solve the problem of difficulty in uniformly quantifying protection objects under complex power grid topologies. This achieves accurate mapping and differentiated management of disaster risks for different types of power grid assets, specifically including: Based on the thunderstorm prediction trajectory in the acquired severe convection early warning data and the geographical coordinates of power grid facilities in the power grid operation data, the spatial positional relationship between each power grid facility and the thunderstorm prediction trajectory is calculated. Based on the spatial location relationship, power grid facilities located within the influence range of the thunderstorm prediction trajectory are identified as power grid protection targets on the risk path; The node-type target in the power grid protection target is determined as the smallest protection unit; The linear targets in the power grid protection targets are discretized to generate several continuous line segment units, which are then determined as the smallest protection unit. The basic risk coefficient is determined based on the voltage level, load weight, lightning strike probability and estimated arrival time of each minimum protection unit, and the neighborhood risk enhancement coefficient is determined based on the spatial topological relationship between each minimum protection unit. The comprehensive risk coefficient of each minimum protection unit is determined by the basic risk coefficient of each minimum protection unit and the risk enhancement coefficient of the neighborhood, and a list of protection targets is generated in descending order of the comprehensive risk coefficient. The nodal targets include substations and / or converter station nodes, and the linear targets include transmission lines.

[0016] Specifically, firstly, spatial geometric calculations are performed using the latitude and longitude sequence of thunderstorm prediction trajectories from severe convective weather warning data and the precise geographical coordinates of various facilities in power grid operation data to determine the degree of overlap and distance relationship between facilities and trajectories, thereby identifying the set of power grid protection targets truly on the risk path. Next, the smallest protection units are divided according to the geometric shape of the targets: nodal targets (including substations and converter stations) are directly used as the smallest protection unit based on their own physical structure, while linear targets (transmission lines) are discretized into several line segment units according to continuous span intervals, ensuring that each unit can independently participate in risk quantification. Subsequently, for each smallest protection unit, its voltage level weight parameters, load weight parameters, lightning strike probability, and estimated arrival time are extracted to calculate the basic risk coefficient. Simultaneously, the neighborhood risk enhancement coefficient is calculated based on the physical distance between units and electrical topology correlation. Finally, the two are superimposed to form a comprehensive risk coefficient, and the protection target list is output in descending order of value, prioritizing protection resources for high-risk core assets.

[0017] In this embodiment, when performing step S2, which involves calling the mapping model to calculate the array position, considering the differences in the encounter processes between severe convective weather systems and targets with different geometric features, the system can differentiate between point-like, lateral strip-like, and head-on defense modes. Furthermore, wind field data is introduced to calculate operational parameters, addressing the issue that a single defense mode cannot simultaneously protect substations and long-distance power lines. This achieves optimal matching between interception resources and the power grid's spatial layout, specifically including: Identify the geometric topology attributes of each target in the protection target list, the geometric topology attributes including node type attributes and line type attributes; For targets with nodal attributes, the point defense array solution model is invoked to construct point interception arrays for nodal power grid protection targets; For targets with linear attributes, the linear defense array solution model is invoked to construct lateral strip-shaped interception arrays and / or head-on blocking interception arrays for linear power grid protection targets; The point-shaped interception positions, the lateral strip-shaped interception positions, and / or the head-on blocking interception positions are determined as theoretical interception positions. Initial operational parameters are calculated based on the coordinates of each theoretical interception position and the thunderstorm height and wind field data in the severe convection warning data. The initial operational parameters include the firing elevation angle and the firing azimuth angle.

[0018] Specifically, the system automatically invokes the corresponding spatial mapping model based on the geometric topology attributes (node ​​type or linear type) of each target in the protection target list: for node type targets, a point-type defense position calculation model is used to generate a circular coverage area; for linear type targets, a linear defense position calculation model is used to generate strip-shaped or choke-type positions. Simultaneously, combining real-time thunderstorm height and wind field vectors from severe convection warning data, initial operational parameters are calculated for the coordinates of each theoretical interception position. These initial operational parameters include the firing elevation angle and firing azimuth angle to ensure precise matching between the catalyst dissemination path and the thunderstorm movement direction. This differentiated model invocation mechanism enables targeted deployment of different "point-to-line" configurations of the power grid, breaking through the limitations of traditional weather modification operations that only use a single fixed mode, fundamentally improving the accuracy of position matching with actual threats.

[0019] In this embodiment, when constructing the point-like interception array, since there is a time lag between the artificial intervention catalyst being applied and the production of its inhibitory effect, the problem of intervention failure caused by deployment positions that are too close or too far apart when protecting node targets such as substations can be solved by introducing a reaction time advance and an effective operating radius constraint. This ensures that the intervention action can accurately cover the core evolution of the thunderstorm cell, specifically including: Based on the obtained coordinates of the nodal power grid protection target, the speed and direction of the thunderstorm movement, and the time required for the catalyst to diffuse into the target cloud and complete the suppression reaction, the advance amount of the artificial intervention response time is determined. The optimal catalyst dissemination center coordinates are determined based on the aforementioned advance time of the artificial intervention reaction. Using the optimal catalyst dispersal center coordinates as the center and the minimum and maximum effective operating radii of the mobile manual intervention equipment as boundaries, a set of potential operational points for the deployment of mobile manual intervention equipment for nodal power grid protection targets is constructed, resulting in point-like interception array positions.

[0020] Specifically, firstly, based on the node coordinates, thunderstorm movement speed, direction of movement, and the reaction time required for the catalyst to complete cloud physical suppression from release to diffusion, the advance time for artificial intervention is determined. Then, based on this advance time, the optimal catalyst dispersal center coordinates are calculated in the opposite direction of the thunderstorm's arrival. Subsequently, using these center coordinates as the center and the minimum and maximum effective operating radii of the mobile artificial intervention equipment as boundaries, a set of potential operational points is constructed, thus forming a complete point-like interception array. This advance-driven center coordinate calculation and ring-shaped area construction ensures that the operational equipment has sufficient time and space margin before the thunderstorm arrives, solving the technical shortcomings of fixed operational points being unable to dynamically adapt to the thunderstorm's movement speed, and achieving precise, forward-deployed point-like defense for nodes such as substations.

[0021] In this embodiment, when constructing a linear target interception array, since the angle between the thunderstorm's movement direction and the line's direction directly affects the defense efficiency, the lateral or head-on defense mode can be switched by finely judging the angle interval. This solves the technical defects of insufficient protection width or excessive interception gaps in transmission corridors when facing threats from different wind directions, and improves the defense effectiveness of long-distance cross-regional lines. Specifically, this includes: Identify the highest-risk minimum protection unit with the highest comprehensive risk coefficient among the linear power grid protection targets, and obtain the final operation point corresponding to the high-risk minimum protection unit as the initial benchmark operation point; Based on the initial benchmark work point location, calculate the angle between the thunderstorm moving wind direction vector and the span direction vector of the high-risk minimum protection unit; If the included angle is within a preset first angle range, then a parallel lateral strip-shaped interception array is constructed upwind of the high-risk minimum protection unit. If the included angle is within the preset second angle range, a head-on blocking interception position is constructed at the entry point of the linear power grid protection target on the side facing the thunderstorm. The preset first angle range is 30° ≤ included angle ≤ 150°, and the preset second angle range is included angle < 30° or included angle > 150°.

[0022] Specifically, the span unit with the highest comprehensive risk coefficient is first identified as the minimum high-risk protection unit, and its corresponding final operating point is extracted as the initial benchmark operating point. Then, based on the position of the benchmark point, the angle between the thunderstorm moving wind direction vector and the span direction vector is calculated in real time. If the angle is in the range of 30° to 150°, the start and end span coordinates are shifted along the offset vector upwind at the benchmark point to form a lateral strip-shaped interception array parallel to the line direction. If the angle is less than 30° or greater than 150°, the system switches to the foremost entry point on the side of the line facing the thunderstorm to construct a concentrated head-on interception array. This adaptive angle determination and two-mode switching mechanism enable the linear protection to automatically select the optimal layout according to the angle of the thunderstorm, significantly improving the continuous interception efficiency of long-distance transmission channels.

[0023] In this embodiment, when performing task assignment and path planning in step S3, considering the limitations of fixed manual equipment in terms of limited coverage and fixed distribution, neighborhood analysis can be used to identify protection gaps and coordinate mobile resources. This solves the problem of optimizing the allocation of limited intervention equipment under complex geographical conditions, achieving the technical goal of filling weak links in power grid disaster prevention with the shortest response time. Specifically, this includes: A spatial neighborhood search is performed on each theoretical interception position, and adjacent positions with overlapping coverage areas are merged into a shared defense cluster. The coordinates of the center position of the shared defense cluster are then recalculated. Based on the comparison between the coordinates of the central array position and the coverage area of ​​the fixed manual intervention equipment in the region, the protective gap areas that cannot be covered by the fixed manual intervention equipment are identified. The required number of mobile manual intervention devices is calculated based on the effective interception length of the protected gap area projected in the direction of the thunderstorm and the effective protection radius of a single fixed manual intervention device. With the optimization objectives of minimizing response time and maximizing overall protection success rate, and while meeting the requirements for the number of mobile manual intervention equipment, the status information of available mobile manual intervention equipment in the area is coordinated to assign tasks to the mobile manual intervention equipment. Based on the real-time location, driving capability, and / or terrain conditions in the status information, the optimal transfer path is generated for the assigned mobile manual intervention equipment to reach the corresponding target position from its current location.

[0024] Specifically, firstly, a spatial neighborhood search is performed on all theoretical interception positions, merging adjacent positions with overlapping coverage into a shared defense cluster and recalculating the cluster center coordinates. Next, the optimized cluster center is overlaid and compared with the coverage of fixed manual intervention equipment within the region to identify gaps that the fixed equipment cannot cover. Then, based on the effective interception length projected onto the direction of the approaching thunderstorm and the effective protection radius of a single mobile piece of equipment, the required number of mobile equipment units is calculated. Finally, with the dual objectives of minimizing response time and maximizing overall protection success rate, the real-time location, mobility, and terrain data of each mobile piece of equipment are integrated to assign tasks and generate the optimal transfer path from the current location to the target position. This fusion optimization and gap-filling process enables global collaborative configuration of multiple equipment resources, solving the problems of coverage blind spots and inefficient scheduling caused by dispersed positions.

[0025] In this embodiment, after initial task assignment and path planning are completed, due to the rapid evolution and trajectory deviation characteristics of severe convective systems, the problem of static defense schemes lagging behind actual meteorological conditions can be solved by introducing dynamic triggering conditions and correction calculations. This achieves minute-level spatiotemporal synchronization between the defense line and the thunderstorm threat, ensuring the continuous effectiveness of intervention commands. Specifically, this includes: The evolution of the severe convective system is obtained based on the preset dynamic adjustment conditions of the defense line, and the preset dynamic adjustment trigger conditions of the defense line are monitored. When the triggering conditions are met, the system re-executes the process based on the latest strong convection warning data and power grid operation data, identifies the power grid protection targets currently on the risk path, calculates the comprehensive risk coefficient of each target, generates a list of protection targets sorted by risk priority, and obtains the corrected target position coordinates and corrected operation parameters. The target coordinates are compared with the theoretical interception array coordinates to determine the coordinate correction amount; The difference between the corrected operation parameters and the initial operation parameters is calculated to determine the amount of operation parameter correction; Based on the position coordinate correction and the operational parameter correction, a dynamic adjustment command is generated and sent to the corresponding mobile manual intervention equipment to perform position transfer or firing parameter correction.

[0026] Specifically, after completing the initial task assignment and path planning, a closed-loop dynamic adjustment mechanism is used to continuously acquire the evolution of the severe convective system based on preset dynamic adjustment conditions for the defense line, and to monitor whether the dynamic adjustment conditions for the defense line are triggered (trajectory deviation or risk level transition). Once the conditions are met, steps S1 to S3 are re-executed based on the latest early warning data and power grid operation data to obtain the corrected target position coordinates and operational parameters. Then, by calculating the difference between the target position coordinates and the initial operational parameters, the position coordinate correction amount and operational parameter correction amount (including firing elevation and azimuth adjustment) are determined respectively. Finally, a dynamic adjustment command containing equipment ID, new coordinates, transfer path, arrival time constraints, and parameter correction amounts is generated and sent to the corresponding mobile manual intervention equipment in real time to realize position transfer or firing data correction. This trigger-driven re-execution and correction amount generation mechanism solves the problem of position failure caused by the rapid generation and dissipation of meteorological systems, and realizes spatiotemporal synchronous active protection throughout the entire process.

[0027] Example 2: According to the present invention, a method for deploying artificial intervention equipment defense lines for severe convective disasters in power grids is provided, such as... Figure 3 As shown, the specific steps include the following: Step 21: Dynamic identification of high-value targets in the power grid under severe convective disasters. Based on real-time severe convective warning data and power grid topology and operation data, and based on preset rules, calculate the set of high-asset-value power grid targets currently on the risk path. Overlay the threat path, intensity and expected arrival time in the warning information, calculate the real-time risk coefficient of each target on the risk path, and output a list of protection targets sorted by risk level.

[0028] Step 22: Differentiated Active Interception Position Generation Based on Power Grid Topology Characteristics. Based on the geometric topological attributes of the targets in the protection list, a differentiated spatial mapping model is invoked to calculate the positions. For nodal targets such as substations, point-like defense positions are constructed by combining strong convection direction and wind field data; for linear targets such as transmission lines, the defense mode is determined based on the angle between the thunderstorm's moving wind direction and the line's orientation: if it is a lateral attack, a strip-shaped interception position parallel to the line is generated based on high-risk points; if it is a head-on attack, a choke-style interception position is constructed at the foremost entry point on the windward side of the line; finally, the theoretical optimal interception center coordinates, operational coverage radius, and firing parameters for each target are output.

[0029] Step 23: Protection Gap Analysis and Dynamic Scheduling of Mobile Equipment. A neighborhood search is performed on the theoretically optimal interception positions generated in Step 22 to determine if there is overlap in the protection coverage of adjacent positions. If the preset fusion conditions are met, multiple independent positions are merged into a shared defense cluster, and the coordinates of the cluster's center position are recalculated. Subsequently, the optimized positions are compared with fixed equipment to identify gaps, identifying protection gaps that fixed equipment cannot cover. With the dual optimization objectives of maximizing overall protection success rate and minimizing response time, the current position, ammunition status, and mobility of available mobile equipment within the area are considered to perform dynamic task assignment and path planning.

[0030] Step 24: Dynamic adjustment of the defense line and generation of instructions. The system tracks the actual evolution trajectory and intensity changes of the severe convective system in real time. When the preset dynamic triggering conditions are met, steps 21 to 23 are automatically repeated based on the latest meteorological conditions to correct the drift of the interception positions or recalculate them. Based on the differences between the old and new positions, dynamic instructions containing equipment ID, new deployment coordinates, optimal transfer path and operational parameter corrections are generated to direct mobile equipment to quickly transfer positions or correct firing parameters in real time, ensuring that the defense positions are always in spatiotemporal synchronization with the severe convective threat.

[0031] Furthermore, in step 21, all targets are uniformly divided into the smallest protection units. For node-type targets, the protection unit is the node itself; for linear targets, they are discretized into several continuous line segment units (such as spans).

[0032] Furthermore, in step 21, for the first region... i Minimum protection unit U i Define the comprehensive risk coefficient. R total ( U i )for:

[0033] in, R i The basic risk coefficient is determined by the static value of the asset itself and dynamic weather threats; C cluster ( U i ) is the neighborhood risk enhancement coefficient, which represents the risk gain caused by the presence of other heterogeneous high-value targets in the surrounding area.

[0034] Furthermore, in step 21, the basic risk coefficient... R i In this context, each variable is associated with data from the power grid or meteorological operational systems, specifically:

[0035] in, K v and K L These are dimensional weighting coefficients used to adjust the strategy for setting power grid protection objectives, and are typically required to... K v + K L =1; V ( U i The voltage level weighting coefficient is normalized and is generally used for ultra-high voltage equipment. V ( U i =1.0, Ultra-high voltage equipment V ( U i =0.7, high-voltage substation V ( U i )=0.4, other devices V ( U i =0.2; L ( U i The load importance coefficient is assigned based on the nature of the power supply area and normalized. It is generally set for equipment of first-level important users (power supply protection areas, important civil facilities, important enterprises, etc.). L ( U i )=1.0, Level 2 Important User Equipment L ( U i )=0.6, other user equipment L ( U i =0.3; P impact ( t , U i The probability of a lightning strike is derived from a weather radar echo extrapolation algorithm. Based on the prediction of the future location of the thunderstorm, it calculates the overlap between the thunderstorm coverage area and the target coordinates of the power grid. If the prediction indicates complete coverage, then... P impact ( t , U i If the edge is swept, the calculation is based on the proportion of the target area of ​​the power grid covered by thunderstorms, taking 0 < 1. P impact ( t , U i )<1; Tarrival The estimated arrival time, s, is provided by the power grid lightning warning system; Δ t buf As a buffer constant, to prevent T arrival When the value approaches 0, the divergence of the value causes other high-value targets to be overlooked.

[0036] Furthermore, in step 21, the clustering coupling coefficient C cluster ( U i ), used to characterize the target U i The sum of risks posed by all non-homogeneous targets within the neighborhood is used to increase the risk gain of clustered risks for parallel transmission channels, hub substation areas, or multiple high-value targets, while simultaneously introducing a homogeneous indicator function δ( S i , S j Remove the smallest protective unit belonging to the whole, specifically:

[0037] Among them, Ω i For neighborhood set, with U i Centered on the thunderstorm, all other protective units are within a radius equal to the maximum impact area of ​​the pre-defined thunderstorm cell. U j The set; δ( S i , S j () is a homogeneous indicator function used to eliminate spurious clusters caused by assets belonging to the same power grid (such as adjacent spans of the same transmission line). S i , S j Corresponding minimum protection unit U i , U j The ID of the power grid asset to which it belongs, if S i = S j If they are homologous, then they are marked as δ( S i , S j If )=0; S i ≠ S j If it is a heterogeneous source, then it is marked as δ( S i , Sj )=1; α This is the coupling strength factor, used to quantify the strength of risk transmission between adjacent targets. Its value ranges from [0,1]. When adjacent targets belong to the same transmission channel (e.g., double circuit on the same tower or shared corridor), a higher value is used. α =1 indicates that both are highly susceptible to simultaneous disasters and the consequences are severe; when adjacent targets are only geographically close but have weak electrical connections (such as lines belonging to different power supply zones), take the lower value. d ( U i , U j ) as the target i With the goal j The physical distance, in meters.

[0038] Furthermore, in step 22, to ensure that the catalyst has sufficient time and distance to complete the cloud physics suppression process before the strongly convective monomers reach the grid target, for high-value targets... U i Based on this, and taking into account the movement of the thunderstorm, the optimal catalyst dissemination center coordinates are calculated upwind of the direction from which the thunderstorm originates. P opt ( U i ):

[0039] in, P ( U i ( ) represents the coordinates of the power grid target; k This is the directional correction coefficient, used to spatially compensate and correct the catalyst drift vector and operational safety margin based on the real-time upper-level wind field. V storm The velocity of the thunderstorm is expressed in m / s, and the data is derived from a weather radar echo extrapolation algorithm, determined by tracking the centroid movement of strong echo cells in the thunderstorm; Δ t The time constant required for the catalyst to diffuse from the release point to the target cloud and complete the suppression of thunderstorms is the advance time for artificial intervention reaction. It is usually set according to the physicochemical properties of silver iodide (AgI) catalyst.

[0040] Furthermore, in step 22, based on the ballistic performance of the mobile equipment, P opt ( U i Using as the center, construct the corresponding protection target. U i Set of potential work sites for the deployment of mobile manual intervention equipment in a ring-shaped area Ring ( U i ):

[0041] in, R min 、R max The minimum and maximum effective operating radii for mobile manual intervention equipment for meteorological disasters; P final_n ( U i This refers to the final set of deployment sites for mobile manual intervention equipment for meteorological disasters. P Represents a set element.

[0042] Furthermore, in step 22, precise point selection based on road network and environmental constraints... Ring ( U i Within the scope of the data, GIS geographic information is overlaid, and coordinates that meet the following conditions are automatically selected as potential final work points: not less than 30 meters from the nearest public road; not less than 100 meters from densely populated areas or important facilities; and less than 10 km from the protected power grid facilities.

[0043] Furthermore, in step 22, if the number of potential final work points selected is greater than 1, then a wind direction priority strategy is adopted to select the final work point. P final ( U i That is, among all candidate points, select the one that corresponds to the strong convection movement vector. The point with the shortest distance in the opposite direction is selected to ensure that the equipment is positioned at the forefront of the thunderstorm cell on the windward side, thereby achieving the maximum interception depth.

[0044] Furthermore, in step 22, if the target is a linear target, then based on the above steps, the baseline operation point and deployment position should be clearly defined, and the specific logic is as follows: (1) Selection of benchmark work points: First, identify the target unit with the highest comprehensive risk coefficient in the linear target. U ( n The final work point corresponding to ) P final ( U n () is used as the initial baseline work point.

[0045] (2) Calculation of wind direction angle: Based on the location of the benchmark work point, the wind direction vector is calculated. and U ( n ) Gear spacing direction vector The included angle θ n .

[0046] (3) Lateral interception mode: if 30°≤ θ n ≤150°, at this angle, thunderstorms mainly approach from the side of the power line. Maintain the above... P final ( U n Using this point as the reference point and as the anchor point, calculate its position relative to the protected target unit. U i The spatial offset is used to identify the start and end spans of the linear target within the thunderstorm warning impact area, i.e., the first and last units with a risk coefficient greater than the threshold. The physical coordinates of these start and end spans are then translated in the same direction along the aforementioned offset vector to obtain the starting and ending boundary points of the strip-shaped operation area. Connecting the starting and ending boundary points constructs a strip-shaped operation area parallel to the threatened line. Operational equipment is deployed within this strip-shaped area to form a parallel interception defense line.

[0047] (4) Head-on defense mode: If θ n <30° or θ n When the angle exceeds 150°, the thunderstorm moves along the line. At this point, the baseline work point should be adjusted, selecting the point where the line first intersects the line at the forefront of the thunderstorm's path, i.e., the first intersection of the thunderstorm warning zone boundary and the line. Work forces should be concentrated upwind of this initial intersection point.

[0048] Furthermore, in step 23, the identified key sections are aggregated into deployment clusters, where the distance between any two theoretical positions is less than the effective protection diameter of a single piece of equipment, and the required number of mobile operational equipment is calculated. N devices To ensure the continuity of protective coverage, specifically:

[0049] in, L criti To determine the effective interception envelope length of the defense cluster, the diameter of its circumscribed circle is used for point-like target clusters, and the projection length of its line-like target clusters in the direction of the thunderstorm is used for the line-like target clusters. D eq The effective protection radius of a single mobile work equipment; further, in step 23, for each deployment cluster, the system meets the following requirements. N devices To meet the needs, the system combines the real-time location, driving capacity, and terrain conditions of each mobile device to optimize the shortest arrival time, and performs route planning and dynamic scheduling.

[0050] Furthermore, in step 24, the conditions that trigger the repeated execution of the above steps (21 to 23) for dynamic adjustment of the defense line include, but are not limited to, any of the following situations: Periodic trigger: The preset time interval is reached, for example, every 5 minutes; Deviation trigger: The deviation between the real-time monitoring location of the thunderstorm cell center and the previously predicted location by the severe convection early warning system exceeds a preset threshold. Risk change trigger: any high-value target U i Comprehensive risk coefficient R total ( U i A risk level shift occurs, for example, from medium risk to high risk.

[0051] Furthermore, in step 24, the generated defense adjustment command includes the following information: Redeployment target: Specify the equipment ID that needs to be moved; Target position: New optimal interception coordinates ; Spatiotemporal constraints: including optimized transfer paths and required arrival times to ensure that equipment is in place before the thunderstorm reaches the optimal operating point; Operational correction: Adjust the elevation and azimuth parameters based on the latest thunderstorm height and wind speed.

[0052] This invention addresses the technical pain points of traditional power grid meteorological disaster prevention, such as passive disaster bearing, mismatch between artificial weather modification operations and power grid protection needs, and insufficient timeliness of operation scheduling, by constructing a method and system for deploying artificial weather modification equipment defense lines for power grids in the event of severe convective weather disasters. It achieves multi-dimensional technological breakthroughs and enhances application value. Specific invention effects are as follows: In terms of defense mechanisms, traditional power grid disaster prevention relies on static physical protection such as lightning rods and lightning conductors, which can only mitigate post-disaster losses and cannot intervene in severe convective weather at its source. This invention, based on the linkage analysis of severe convective weather early warning data and power grid operation data, can perform pre-emptive interception operations before severe convective systems form or move into critical areas using mobile, artificial intervention equipment for meteorological disasters, such as vehicle-mounted rockets and drones. This reduces or suppresses the threat of severe convective weather to the power grid from the source of the disaster, moving the defense point forward, reversing the passive situation of power grid meteorological disaster defense, and significantly reducing the probability of line tripping, equipment damage, and other faults.

[0053] In terms of precise protection, existing weather modification operations target large-scale fixed areas, which is incompatible with the diverse, highly discrete, and strongly topologically related protection targets of power grid substations (points), transmission lines (lines), and load centers (areas). This invention innovatively constructs a differentiated spatial mapping model, generating point-like defense positions for nodal targets such as substations and linear parallel defense positions for linear targets such as transmission lines. Simultaneously, it discretizes linear targets into minimum protection units at the span level and, combined with a comprehensive risk coefficient, sorts high-value targets. This allows for precise identification of key protection targets, avoiding ineffective dispersion of protection resources and enabling precise allocation of protection resources to core, high-risk power grid assets.

[0054] In terms of response timeliness, traditional weather modification operations rely on fixed operation points, and scheduling is based on broad administrative regions and forecast conclusions, lacking rapid response capabilities at the minute to hour level. This invention, through a dynamic identification of protection gaps and a collaborative scheduling mechanism for mobile equipment, can coordinate the position, status, and mobility of artificial intervention equipment such as vehicle-mounted rockets and drones to quickly fill the protection blind spots of fixed equipment. At the same time, it sets multiple defense line adjustment trigger conditions, such as periodicity, deviation triggering, and risk level transition, and can update the interception array coordinates and adjust equipment operation parameters according to the real-time movement trajectory and intensity changes of severe convective weather cells. This enables minute-level operation command generation and equipment redeployment, fully adapting to the rapid generation, dissipation, and movement characteristics of severe convective weather, ensuring the timeliness and effectiveness of operations.

[0055] In terms of system resilience, this invention introduces a clustering coupling coefficient, which can significantly improve the risk weight of high-value target clustering areas such as parallel transmission channels and hub substation areas, enabling key protection of critical topologically related areas of the power grid and avoiding cascading failures caused by local disasters. At the same time, the risk coefficient calculation of the protected targets is associated with the voltage level and load importance, which can prioritize the protection of core assets such as ultra-high voltage equipment and power supply equipment for first-level important users, effectively reducing the risk of large-scale power outages in the power grid, ensuring reliable power supply in key scenarios such as power protection areas, important civil facilities, and key enterprises, and comprehensively improving the disaster resistance resilience and operational reliability of the power grid system.

[0056] Example 3: According to the present invention, a power grid severe convective disaster artificial intervention equipment defense line deployment system is provided, used to execute the above-mentioned defense line deployment method, such as... Figure 4 As shown, the system mainly includes the following core modules: The high-value target dynamic identification and risk assessment module is equipped with a data interface to access real-time weather warnings and power grid operation data. It has a built-in risk quantification calculation unit to identify power grid facilities currently on the risk path and calculate the real-time comprehensive risk coefficient based on the asset value and clustering coupling degree of the facilities, generating a protection target list sorted by priority. The differentiated active interception position calculation module is equipped with a spatial topology mapping algorithm, which is used to calculate point defense positions or linear parallel interception positions according to the geometric topology attributes (point or line) of the targets in the protection list, and output the optimal interception coordinates in combination with terrain and equipment range constraints. The protection gap analysis and resource coordination scheduling module is used to compare the theoretically optimal interception position with the coverage of existing fixed equipment in the area to identify protection gaps, and to coordinate the dynamic task assignment and path planning of available mobile equipment in the area with the goal of minimizing response time. The closed-loop dynamic command and control and correction module is used to track the evolution of weather conditions in real time. It has a built-in trigger monitoring unit. When the preset time, location deviation or risk change trigger conditions are met, the module is driven to run again and a dynamic adjustment command is generated and sent to the mobile equipment terminal.

[0057] Furthermore, the specific execution logic of the high-value target dynamic identification and risk assessment module is as follows: divide the power grid target into the smallest protection unit, and calculate the basic risk coefficient based on voltage level weight, load importance coefficient, thunderstorm coverage probability and expected arrival time; further calculate the clustering coupling coefficient based on the facility density and electrical connection relationship around the target, and superimpose the two to obtain the final comprehensive risk coefficient.

[0058] Furthermore, the specific execution logic of the differentiated active interception array position calculation module is as follows: for nodal targets such as substations, a point-like area with the highest coverage probability is constructed along the opposite direction of the thunderstorm's direction of travel, with the substation as the focus; for linear targets such as power transmission channels, high-risk key sections are identified, and parallel strip-shaped work areas are generated; and the optimal interception distance, including lead time, is calculated based on the thunderstorm's movement speed and the human intervention response time.

[0059] Furthermore, the specific execution logic of the closed-loop dynamic command and control and correction module is as follows: continuously compare the deviation between the real-time thunderstorm trajectory and the predicted trajectory. When the deviation exceeds the threshold, generate a redeployment command containing the new deployment coordinates and the optimal transfer path; or generate a shooting parameter adjustment command containing the elevation and azimuth corrections based on the latest thunderstorm height data to ensure that the defense action and the meteorological disaster are synchronized in time and space.

[0060] Example 4: This embodiment aims to illustrate the specific implementation process of the present invention's method and system for deploying artificial intervention equipment for severe convective weather disasters in power grids in complex scenarios involving substations and parallel transmission channels, as follows: 1. The system receives severe thunderstorm and convective weather warnings issued by meteorological departments, and determines the target area by fusing severe convection identification data from radar, power grid PMS, and GIS data through a data perception layer. In this example, the obtained speed of the thunderstorm cell movement... Vstorm Approximately 8 m / s, moving from due west to due east (azimuth 270°), estimated arrival time T arrival It takes 120 minutes.

[0061] 2. In this example, based on the power grid topology information, the target identification module identifies three high-value targets located along the thunderstorm path: Target A is a 1000kV UHV substation; Target B is a 500kV DC transmission line; and Target C is a 220kV AC transmission line. Targets B and C run parallel to each other along the same corridor, oriented northeast-southwest, with an average distance of approximately 0.5km. The system further divides Target A into nodal-type minimum protection units. U A Discretize targets B and C into several segment units of different spacing levels. U B ( i )and U C ( i ).

[0062] 3. Based on step 21 above, the risk assessment module calculates the comprehensive risk coefficient for each objective. Dimension weights are then set. K v =0.5, K L =0.5. Buffer constant Δ t buf =60s. Since the thunderstorm has completely covered all targets, therefore... P impact =1.0, and the remaining parameters are determined as follows:

[0063] in, U A Substations are isolated targets with a high coupling coefficient. C cluster_A =0. R total ( U A =0.067. U B and U C Since they share a corridor, they are considered to have a coupling relationship, and the coupling strength factor is used. α =0.8, physical distance d=0.5km. ≈0.106, therefore we can obtain R total ( U B )≈0.063. Calculate similarly. Rtotal ( U C The final output list of protection targets is sorted as follows: (The value is approximately 0.039). U A > U B > U C The system determines that A needs to be protected with priority, while B and C need to be protected with cluster defense.

[0064] 4. Based on step 22 above, for node-type targets U A ,by U A Based on the benchmark, combining thunderstorm speed and reaction lead Δ t =15min, calculate the optimal catalyst seeding center P A Based on GIS, multiple candidate points within the ring-shaped area were selected. Following a priority strategy based on the direction of the incoming wind, the coordinates of a point approximately 10km west of the substation (upwind of the thunderstorm), with a clear view and proximity to a road, were chosen as the final work point. P final ( U A ).

[0065] 6. Based on step 22 above, for linear targets U B and U C The steps are as follows: (1) Reference point selection: Identify the highest risk span in line B. U B ( n ), calculate its corresponding optimal work point P final ( U B () as the initial reference point; (2) Pattern determination: Calculate the angle between the thunderstorm wind direction and the line direction. θ n ≈45°. Since 30°≤45°≤150°, the system is determined to enter lateral interception mode.

[0066] (3) Defense line construction: with P final ( U B () is the anchor point, and its relative position is calculated. U B(n) is the spatial offset vector. The starting and ending spans of the threatened line are identified, and their coordinates are translated along this vector to form a strip-shaped work area located on the northwest side of the line and parallel to the line's direction.

[0067] 7. Based on step 23 above, the scheduling and command module performs protection gap analysis and resource scheduling.

[0068] The system identified the parallel segments of targets B and C as critical sections requiring clustered defense. Through projection calculations, the effective interception length of this critical segment in the direction of the approaching thunderstorm was determined. L critical It is approximately 8km.

[0069] Based on the effective protection radius of a single piece of equipment R =4km, calculated the number of mobile equipment required for this cluster N devices =2 units. Adding the 1 unit required for target A, a total of 3 units need to be deployed in the area.

[0070] The system coordinates the available vehicle-mounted rocket equipment (Dev-01, 02, 03) within the region, and with the goal of minimizing the response time, assigns Dev-01 to target position A, and assigns Dev-02 and Dev-03 to linear positions at targets B and C, and generates scheduling instructions that include the travel paths.

[0071] 8. Following step 24 above, the dynamic control module tracks real-time weather conditions. After deployment, the system detects that the center of the thunderstorm cell deviates southward by more than 1 km from the predicted path (meeting the deviation trigger condition). The system automatically re-runs the array position calculation logic to generate new interception coordinates. It also issues dynamic adjustment commands to Dev-01, 02, and 03, including new position coordinates and firing elevation corrections, to ensure that the defense line is always aligned with the core of the thunderstorm threat.

[0072] Example 5: Based on the same inventive concept, this invention also provides a power grid severe convective disaster artificial intervention equipment defense line deployment system, such as... Figure 5 As shown, it includes: The identification module is used to identify power grid protection targets currently on risk paths based on the acquired severe convection early warning data and power grid operation data, calculate the comprehensive risk coefficient of each target, and generate a list of protection targets; The settlement module is used to calculate the array positions by calling a differentiated spatial mapping model based on the geometric topology attributes of each target in the protection target list, and to generate theoretical interception array positions. The overall planning module is used to perform neighborhood analysis and fusion optimization on the theoretical interception positions to identify protection gaps, and to coordinate the status information of available mobile manual intervention equipment in the area for task assignment and path planning.

[0073] Preferably, the identification module is specifically used for: Based on the thunderstorm prediction trajectory in the acquired severe convection early warning data and the geographical coordinates of power grid facilities in the power grid operation data, the spatial positional relationship between each power grid facility and the thunderstorm prediction trajectory is calculated. Based on the spatial location relationship, power grid facilities located within the influence range of the thunderstorm prediction trajectory are identified as power grid protection targets on the risk path; The node-type target in the power grid protection target is determined as the smallest protection unit; The linear targets in the power grid protection targets are discretized to generate several continuous line segment units, which are then determined as the smallest protection unit. The basic risk coefficient is determined based on the voltage level, load weight, lightning strike probability and estimated arrival time of each minimum protection unit, and the neighborhood risk enhancement coefficient is determined based on the spatial topological relationship between each minimum protection unit. The comprehensive risk coefficient of each minimum protection unit is determined by the basic risk coefficient of each minimum protection unit and the risk enhancement coefficient of the neighborhood, and a list of protection targets is generated in descending order of the comprehensive risk coefficient. The nodal targets include substations and / or converter station nodes, and the linear targets include transmission lines.

[0074] Preferably, the comprehensive risk coefficient in the identification module is obtained by the following formula:

[0075] in, For the i-th smallest protection unit The overall risk coefficient, Basic risk coefficient, This represents the risk enhancement coefficient in the neighborhood. The basic risk coefficient in the identification module is obtained by the following formula:

[0076] in, For voltage level weighting parameters, For load weighting parameters, For voltage level weighting coefficients, This is the load importance coefficient. This represents the probability of being struck by lightning. Δ is the estimated arrival time. t bufIt is the buffer constant; The neighborhood risk enhancement coefficient in the identification module is obtained by the following formula:

[0077] in, For neighborhood set, For same-source indicator functions, As the smallest protection unit The ID of the power grid asset to which it belongs. As the smallest protection unit The ID of the power grid asset to which it belongs. Let be the coupling strength factor between target i and target j. Let be the physical distance between target i and target j.

[0078] Preferably, the solution module is specifically used for: Identify the geometric topology attributes of each target in the protection target list, the geometric topology attributes including node type attributes and line type attributes; For targets with nodal attributes, the point defense array solution model is invoked to construct point interception arrays for nodal power grid protection targets; For targets with linear attributes, the linear defense array solution model is invoked to construct lateral strip-shaped interception arrays and / or head-on blocking interception arrays for linear power grid protection targets; The point-shaped interception positions, the lateral strip-shaped interception positions, and / or the head-on blocking interception positions are determined as theoretical interception positions. Initial operational parameters are calculated based on the coordinates of each theoretical interception position and the thunderstorm height and wind field data in the severe convection warning data. The initial operational parameters include the firing elevation angle and the firing azimuth angle.

[0079] Preferably, the point-like interception array positions for constructing nodal power grid protection targets in the solution module include: Based on the obtained coordinates of the nodal power grid protection target, the speed and direction of the thunderstorm movement, and the time required for the catalyst to diffuse into the target cloud and complete the suppression reaction, the advance amount of the artificial intervention response time is determined. The optimal catalyst dissemination center coordinates are determined based on the aforementioned advance time of the artificial intervention reaction. Using the optimal catalyst dispersal center coordinates as the center and the minimum and maximum effective operating radii of the mobile manual intervention equipment as boundaries, a set of potential operational points for the deployment of mobile manual intervention equipment for nodal power grid protection targets is constructed, resulting in point-like interception array positions.

[0080] Preferably, the optimal catalyst seeding center coordinates in the solution module are obtained by the following calculation formula:

[0081] in, Protection targets for nodal power grids The optimal catalyst dissemination center coordinates This is the direction correction factor. This refers to the speed at which thunderstorms move. This is the lead time for human intervention response; The set of potential work sites for the deployment of mobile manual intervention equipment in the solution module is obtained through the following calculation formula:

[0082] in, Protection targets for nodal power grids The set of potential operational sites for the deployment of mobile human intervention equipment. This serves as the final deployment point for mobile manual intervention equipment for meteorological disasters. The minimum effective operating radius for mobile manual intervention equipment for meteorological disasters. This represents the maximum effective operating radius of mobile manual intervention equipment for meteorological disasters.

[0083] Preferably, the calculation module constructs lateral strip-shaped interception positions and / or head-on blocking interception positions for linear power grid protection targets, including: Identify the highest-risk minimum protection unit with the highest comprehensive risk coefficient among the linear power grid protection targets, and obtain the final operation point corresponding to the high-risk minimum protection unit as the initial benchmark operation point; Based on the initial benchmark work point location, calculate the angle between the thunderstorm moving wind direction vector and the span direction vector of the high-risk minimum protection unit; If the included angle is within a preset first angle range, then a parallel lateral strip-shaped interception array is constructed upwind of the high-risk minimum protection unit. If the included angle is within the preset second angle range, a head-on blocking interception position is constructed at the entry point of the linear power grid protection target on the side facing the thunderstorm. The preset first angle range is 30° ≤ included angle ≤ 150°, and the preset second angle range is included angle < 30° or included angle > 150°.

[0084] Preferably, the overall planning module is specifically used for: A spatial neighborhood search is performed on each theoretical interception position, and adjacent positions with overlapping coverage areas are merged into a shared defense cluster. The coordinates of the center position of the shared defense cluster are then recalculated. Based on the comparison between the coordinates of the central array position and the coverage area of ​​the fixed manual intervention equipment in the region, the protective gap areas that cannot be covered by the fixed manual intervention equipment are identified. The required number of mobile manual intervention devices is calculated based on the effective interception length of the protected gap area projected in the direction of the thunderstorm and the effective protection radius of a single fixed manual intervention device. With the optimization objectives of minimizing response time and maximizing overall protection success rate, and while meeting the requirements for the number of mobile manual intervention equipment, the status information of available mobile manual intervention equipment in the area is coordinated to assign tasks to the mobile manual intervention equipment. Based on the real-time location, driving capability, and / or terrain conditions in the status information, the optimal transfer path is generated for the assigned mobile manual intervention equipment to reach the corresponding target position from its current location.

[0085] Preferably, the system further includes a correction module, used for: The evolution of the severe convective system is obtained based on the preset dynamic adjustment conditions of the defense line, and the preset dynamic adjustment trigger conditions of the defense line are monitored. When the triggering conditions are met, the system re-executes the process based on the latest strong convection warning data and power grid operation data, identifies the power grid protection targets currently on the risk path, calculates the comprehensive risk coefficient of each target, generates a list of protection targets sorted by risk priority, and obtains the corrected target position coordinates and corrected operation parameters. The target coordinates are compared with the theoretical interception array coordinates to determine the coordinate correction amount; The difference between the corrected operation parameters and the initial operation parameters is calculated to determine the amount of operation parameter correction; Based on the position coordinate correction and the operational parameter correction, a dynamic adjustment command is generated and sent to the corresponding mobile manual intervention equipment to perform position transfer or firing parameter correction.

[0086] Example 6 like Figure 6 As shown, the present invention also provides an electronic device, which may be a computer device, a microcontroller device, a smart mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, processor, and transceiver component are connected via a bus; the memory can be used to store executable programs, and an exemplary executable program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, which can be accessed and / or modified when instructions are executed.

[0087] The processor may be a Central Processing Unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and it is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to realize the corresponding method flow or corresponding function, so as to realize the steps of the method for deploying artificial intervention equipment defense line for strong convective disasters in power grids in the above embodiments.

[0088] Example 7 Based on the same inventive concept, this invention also provides a readable storage medium, specifically an electronic device readable storage medium (Memory). This readable storage medium is a memory device within an electronic device used to store programs and data. It is understood that the storage medium here can include both built-in storage media within the electronic device and extended storage media supported by the electronic device. The storage medium provides storage space, which stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more executable programs (including program code). It should be noted that the storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device. Loading and executing one or more instructions stored in the storage medium by the processor can implement the steps of the above-described method for deploying artificial intervention equipment for severe convective weather disasters in a power grid.

[0089] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for deploying artificial intervention equipment defense lines for severe convective weather disasters in power grids, characterized in that, include: Based on the acquired severe convection early warning data and power grid operation data, identify the power grid protection targets currently on the risk path, calculate the comprehensive risk coefficient of each target, and generate a list of protection targets; Based on the geometric topology attributes of each target in the protection target list, a differentiated spatial mapping model is invoked to calculate the array positions and generate theoretical interception array positions. The theoretical interception positions are analyzed and fused to identify protection gaps, and the status information of available mobile manual intervention equipment in the area is used to assign tasks and plan paths.

2. The method according to claim 1, characterized in that, Based on the acquired severe convective weather warning data and power grid operation data, the system identifies power grid protection targets currently on risk paths, calculates the comprehensive risk coefficient of each target, and generates a list of protection targets, including: Based on the thunderstorm prediction trajectory in the acquired severe convection early warning data and the geographical coordinates of power grid facilities in the power grid operation data, the spatial positional relationship between each power grid facility and the thunderstorm prediction trajectory is calculated. Based on the spatial location relationship, power grid facilities located within the influence range of the thunderstorm prediction trajectory are identified as power grid protection targets on the risk path; The node-type target in the power grid protection target is determined as the smallest protection unit; The linear targets in the power grid protection targets are discretized to generate several continuous line segment units, which are then determined as the smallest protection unit. The basic risk coefficient is determined based on the voltage level, load weight, lightning strike probability and estimated arrival time of each minimum protection unit, and the neighborhood risk enhancement coefficient is determined based on the spatial topological relationship between each minimum protection unit. The comprehensive risk coefficient of each minimum protection unit is determined by the basic risk coefficient of each minimum protection unit and the risk enhancement coefficient of the neighborhood, and a list of protection targets is generated in descending order of the comprehensive risk coefficient. The nodal targets include substations and / or converter station nodes, and the linear targets include transmission lines.

3. The method according to claim 2, characterized in that, The comprehensive risk coefficient is obtained through the following formula: in, For the i-th smallest protection unit The overall risk coefficient, Basic risk coefficient, This represents the risk enhancement coefficient in the neighborhood. The basic risk coefficient is obtained through the following formula: in, For voltage level weighting parameters, For load weighting parameters, For voltage level weighting coefficients, This is the load importance coefficient. This represents the probability of being struck by lightning. Δ is the estimated arrival time. t buf It is the buffer constant; The neighborhood risk enhancement coefficient is obtained by the following formula: in, For neighborhood set, For same-source indicator functions, As the smallest protection unit The ID of the power grid asset to which it belongs. As the smallest protection unit The ID of the power grid asset to which it belongs. Let be the coupling strength factor between target i and target j. Let be the physical distance between target i and target j.

4. The method according to claim 1, characterized in that, The step of calculating the theoretical interception array positions by calling a differentiated spatial mapping model based on the geometric topology attributes of each target in the protection target list includes: Identify the geometric topology attributes of each target in the protection target list, the geometric topology attributes including node type attributes and line type attributes; For targets with nodal attributes, the point defense array solution model is invoked to construct point interception arrays for nodal power grid protection targets; For targets with linear attributes, the linear defense array solution model is invoked to construct lateral strip-shaped interception arrays and / or head-on blocking interception arrays for linear power grid protection targets; The point-shaped interception positions, the lateral strip-shaped interception positions, and / or the head-on blocking interception positions are determined as theoretical interception positions. Initial operational parameters are calculated based on the coordinates of each theoretical interception position and the thunderstorm height and wind field data in the severe convection warning data. The initial operational parameters include the firing elevation angle and the firing azimuth angle.

5. The method according to claim 4, characterized in that, The point-like interception array positions for constructing node-type power grid protection targets include: Based on the obtained coordinates of the nodal power grid protection target, the speed and direction of the thunderstorm movement, and the time required for the catalyst to diffuse into the target cloud and complete the suppression reaction, the advance amount of the artificial intervention response time is determined. The optimal catalyst dissemination center coordinates are determined based on the aforementioned advance time of the artificial intervention reaction. Using the optimal catalyst dispersal center coordinates as the center and the minimum and maximum effective operating radii of the mobile manual intervention equipment as boundaries, a set of potential operational points for the deployment of mobile manual intervention equipment for nodal power grid protection targets is constructed, resulting in point-like interception array positions.

6. The method according to claim 5, characterized in that, The optimal catalyst dissemination center coordinates are obtained through the following calculation formula: in, Protection targets for nodal power grids The optimal catalyst dissemination center coordinates This is the direction correction factor. This refers to the speed at which thunderstorms move. This is the lead time for human intervention response; The set of potential work sites for the deployment of mobile manual intervention equipment is obtained through the following calculation formula: in, Protection targets for nodal power grids The set of potential operational sites for the deployment of mobile human intervention equipment. This serves as the final deployment point for mobile manual intervention equipment for meteorological disasters. The minimum effective operating radius for mobile manual intervention equipment for meteorological disasters. This represents the maximum effective operating radius of mobile manual intervention equipment for meteorological disasters.

7. The method according to claim 4, characterized in that, The lateral strip-shaped interception array positions and / or head-on blocking interception array positions for constructing linear power grid protection targets include: Identify the highest-risk minimum protection unit with the highest comprehensive risk coefficient among the linear power grid protection targets, and obtain the final operation point corresponding to the high-risk minimum protection unit as the initial benchmark operation point; Based on the initial benchmark work point location, calculate the angle between the thunderstorm moving wind direction vector and the span direction vector of the high-risk minimum protection unit; If the included angle is within a preset first angle range, then a parallel lateral strip-shaped interception array is constructed upwind of the high-risk minimum protection unit. If the included angle is within the preset second angle range, a head-on blocking interception position is constructed at the entry point of the linear power grid protection target on the side facing the thunderstorm. The preset first angle range is 30° ≤ included angle ≤ 150°, and the preset second angle range is included angle < 30° or included angle > 150°.

8. The method according to claim 1, characterized in that, The process of performing neighborhood analysis and fusion optimization on the theoretical interception positions to identify protection gaps, and coordinating the status information of available mobile manual intervention equipment within the area for task assignment and path planning, includes: A spatial neighborhood search is performed on each theoretical interception position, and adjacent positions with overlapping coverage areas are merged into a shared defense cluster. The coordinates of the center position of the shared defense cluster are then recalculated. Based on the comparison between the coordinates of the central array position and the coverage area of ​​the fixed manual intervention equipment in the region, the protective gap areas that cannot be covered by the fixed manual intervention equipment are identified. The required number of mobile manual intervention devices is calculated based on the effective interception length of the protected gap area projected in the direction of the thunderstorm and the effective protection radius of a single fixed manual intervention device. With the optimization objectives of minimizing response time and maximizing overall protection success rate, and while meeting the requirements for the number of mobile manual intervention equipment, the status information of available mobile manual intervention equipment in the area is coordinated to assign tasks to the mobile manual intervention equipment. Based on the real-time location, driving capability, and / or terrain conditions in the status information, the optimal transfer path is generated for the assigned mobile manual intervention equipment to reach the corresponding target position from its current location.

9. The method according to claim 4, characterized in that, After assigning tasks and planning paths based on the status information of available mobile manual intervention equipment within the overall planning area, the following is also included: The evolution of the severe convective system is obtained based on the preset dynamic adjustment conditions of the defense line, and the preset dynamic adjustment trigger conditions of the defense line are monitored. When the triggering conditions are met, the system re-executes the process based on the latest strong convection warning data and power grid operation data, identifies the power grid protection targets currently on the risk path, calculates the comprehensive risk coefficient of each target, generates a list of protection targets sorted by risk priority, and obtains the corrected target position coordinates and corrected operation parameters. The target coordinates are compared with the theoretical interception array coordinates to determine the coordinate correction amount; The difference between the corrected operation parameters and the initial operation parameters is calculated to determine the amount of operation parameter correction; Based on the position coordinate correction and the operational parameter correction, a dynamic adjustment command is generated and sent to the corresponding mobile manual intervention equipment to perform position transfer or firing parameter correction.

10. A system for deploying equipment for artificial intervention in power grid severe convective disasters, characterized in that, include: The identification module is used to identify power grid protection targets currently on risk paths based on the acquired severe convection early warning data and power grid operation data, calculate the comprehensive risk coefficient of each target, and generate a list of protection targets; The settlement module is used to calculate the array positions by calling a differentiated spatial mapping model based on the geometric topology attributes of each target in the protection target list, and to generate theoretical interception array positions. The overall planning module is used to perform neighborhood analysis and fusion optimization on the theoretical interception positions to identify protection gaps, and to coordinate the status information of available mobile manual intervention equipment in the area for task assignment and path planning.

11. The system according to claim 10, characterized in that, The identification module is specifically used for: Based on the thunderstorm prediction trajectory in the acquired severe convection early warning data and the geographical coordinates of power grid facilities in the power grid operation data, the spatial positional relationship between each power grid facility and the thunderstorm prediction trajectory is calculated. Based on the spatial location relationship, power grid facilities located within the influence range of the thunderstorm prediction trajectory are identified as power grid protection targets on the risk path; The node-type target in the power grid protection target is determined as the smallest protection unit; The linear targets in the power grid protection targets are discretized to generate several continuous line segment units, which are then determined as the smallest protection unit. The basic risk coefficient is determined based on the voltage level, load weight, lightning strike probability and estimated arrival time of each minimum protection unit, and the neighborhood risk enhancement coefficient is determined based on the spatial topological relationship between each minimum protection unit. The comprehensive risk coefficient of each minimum protection unit is determined by the basic risk coefficient of each minimum protection unit and the risk enhancement coefficient of the neighborhood, and a list of protection targets is generated in descending order of the comprehensive risk coefficient. The nodal targets include substations and / or converter station nodes, and the linear targets include transmission lines.

12. The system according to claim 11, characterized in that, The comprehensive risk coefficient in the identification module is obtained by the following formula: in, For the i-th smallest protection unit The overall risk coefficient, Basic risk coefficient, This represents the risk enhancement coefficient in the neighborhood. The basic risk coefficient in the identification module is obtained by the following formula: in, For voltage level weighting parameters, For load weighting parameters, For voltage level weighting coefficients, This is the load importance coefficient. This represents the probability of being struck by lightning. Δ is the estimated arrival time. t buf It is the buffer constant; The neighborhood risk enhancement coefficient in the identification module is obtained by the following formula: in, For neighborhood set, For same-source indicator functions, As the smallest protection unit The ID of the power grid asset to which it belongs. As the smallest protection unit The ID of the power grid asset to which it belongs. Let be the coupling strength factor between target i and target j. Let be the physical distance between target i and target j.

13. The system according to claim 10, characterized in that, The solution module is specifically used for: Identify the geometric topology attributes of each target in the protection target list, the geometric topology attributes including node type attributes and line type attributes; For targets with nodal attributes, the point defense array solution model is invoked to construct point interception arrays for nodal power grid protection targets; For targets with linear attributes, the linear defense array solution model is invoked to construct lateral strip-shaped interception arrays and / or head-on blocking interception arrays for linear power grid protection targets; The point-shaped interception positions, the lateral strip-shaped interception positions, and / or the head-on blocking interception positions are determined as theoretical interception positions. Initial operational parameters are calculated based on the coordinates of each theoretical interception position and the thunderstorm height and wind field data in the severe convection warning data. The initial operational parameters include the firing elevation angle and the firing azimuth angle.

14. The system according to claim 13, characterized in that, The solution module constructs point-like interception array positions for nodal power grid protection targets, including: Based on the obtained coordinates of the nodal power grid protection target, the speed and direction of the thunderstorm movement, and the time required for the catalyst to diffuse into the target cloud and complete the suppression reaction, the advance amount of the artificial intervention response time is determined. The optimal catalyst dissemination center coordinates are determined based on the aforementioned advance time of the artificial intervention reaction. Using the optimal catalyst dispersal center coordinates as the center and the minimum and maximum effective operating radii of the mobile manual intervention equipment as boundaries, a set of potential operational points for the deployment of mobile manual intervention equipment for nodal power grid protection targets is constructed, resulting in point-like interception array positions.

15. The system according to claim 14, characterized in that, The optimal catalyst dissemination center coordinates in the solution module are obtained through the following calculation formula: in, Protection targets for nodal power grids The optimal catalyst dissemination center coordinates This is the direction correction factor. This refers to the speed at which thunderstorms move. This is the lead time for human intervention response; The set of potential work sites for the deployment of mobile manual intervention equipment in the solution module is obtained through the following calculation formula: in, Protection targets for nodal power grids The set of potential operational sites for the deployment of mobile human intervention equipment. This serves as the final deployment point for mobile manual intervention equipment for meteorological disasters. The minimum effective operating radius for mobile manual intervention equipment for meteorological disasters. This represents the maximum effective operating radius of mobile manual intervention equipment for meteorological disasters.

16. The system according to claim 13, characterized in that, The solution module constructs lateral strip-shaped interception array positions and / or head-on blocking interception array positions for linear power grid protection targets, including: Identify the highest-risk minimum protection unit with the highest comprehensive risk coefficient among the linear power grid protection targets, and obtain the final operation point corresponding to the high-risk minimum protection unit as the initial benchmark operation point; Based on the initial benchmark work point location, calculate the angle between the thunderstorm moving wind direction vector and the span direction vector of the high-risk minimum protection unit; If the included angle is within a preset first angle range, then a parallel lateral strip-shaped interception array is constructed upwind of the high-risk minimum protection unit. If the included angle is within the preset second angle range, a head-on blocking interception position is constructed at the entry point of the linear power grid protection target on the side facing the thunderstorm. The preset first angle range is 30° ≤ included angle ≤ 150°, and the preset second angle range is included angle < 30° or included angle > 150°.

17. The system according to claim 10, characterized in that, The overall planning module is specifically used for: A spatial neighborhood search is performed on each theoretical interception position, and adjacent positions with overlapping coverage areas are merged into a shared defense cluster. The coordinates of the center position of the shared defense cluster are then recalculated. Based on the comparison between the coordinates of the central array position and the coverage area of ​​the fixed manual intervention equipment in the region, the protective gap areas that cannot be covered by the fixed manual intervention equipment are identified. The required number of mobile manual intervention devices is calculated based on the effective interception length of the protected gap area projected in the direction of the thunderstorm and the effective protection radius of a single fixed manual intervention device. With the optimization objectives of minimizing response time and maximizing overall protection success rate, and while meeting the requirements for the number of mobile manual intervention equipment, the status information of available mobile manual intervention equipment in the area is coordinated to assign tasks to the mobile manual intervention equipment. Based on the real-time location, driving capability, and / or terrain conditions in the status information, the optimal transfer path is generated for the assigned mobile manual intervention equipment to reach the corresponding target position from its current location.

18. The system according to claim 13, characterized in that, The system also includes a correction module, used for: The evolution of the severe convective system is obtained based on the preset dynamic adjustment conditions of the defense line, and the preset dynamic adjustment trigger conditions of the defense line are monitored. When the triggering conditions are met, the system re-executes the process based on the latest strong convection warning data and power grid operation data, identifies the power grid protection targets currently on the risk path, calculates the comprehensive risk coefficient of each target, generates a list of protection targets sorted by risk priority, and obtains the corrected target position coordinates and corrected operation parameters. The target coordinates are compared with the theoretical interception array coordinates to determine the coordinate correction amount; The difference between the corrected operation parameters and the initial operation parameters is calculated to determine the amount of operation parameter correction; Based on the position coordinate correction and the operational parameter correction, a dynamic adjustment command is generated and sent to the corresponding mobile manual intervention equipment to perform position transfer or firing parameter correction.

19. An electronic device, characterized in that, include: At least one processor and memory; The memory and processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, the method for deploying artificial intervention equipment defense lines for severe convective disasters in power grids as described in any one of claims 1 to 9 is implemented.

20. A readable storage medium, characterized in that, It contains an execution program, which, when executed, implements the method for deploying artificial intervention equipment defense lines for severe convective disasters in power grids as described in any one of claims 1 to 9.

Images