A power grid resilience power supply guarantee method and system for extreme working conditions

Abstract

The application discloses a kind of power grid toughness power supply guarantee method and system for extreme working condition, it is related to power grid safe operation technical field, the method includes: the power grid architecture diagram of target area is constructed;Mobile energy storage preventive planning is carried out, and the target mobile energy storage layout is obtained;The target area is monitored to the power grid, and real-time power grid information is obtained;Real-time toughness power supply decision is formed by calling the target mobile energy storage layout;According to the real-time toughness power supply decision, the target area is powered to guarantee.The application solves the technical problems that the prior art is insufficient in the extreme working condition, energy storage scheduling lags behind, operation and maintenance monitoring is single, and it is difficult to guarantee continuous and stable power supply, achieves the technical effect that the power grid is quickly responded and toughness power supply under extreme working condition, improves the power supply continuity and toughness guarantee capability of power grid under extreme scene.

Description

Technical Field

[0001] This invention relates to the field of power grid safe operation technology, and specifically to a method and system for ensuring resilient power supply under extreme operating conditions. Background Technology

[0002] With the increasing frequency of extreme weather and natural disasters, the external disturbances faced by the power grid have intensified significantly. Traditional power grid dispatching models rely heavily on post-event emergency response, lacking forward-looking and visual assessment of load status and preventative deployment of mobile energy storage. At the same time, existing operation and maintenance systems often use single monitoring methods, resulting in data silos, insufficient perception dimensions, and weak fusion analysis capabilities. This leads to delayed power grid response and slow power restoration under extreme conditions, making it difficult to form an efficient and reliable resilient power supply guarantee and failing to meet the actual needs of continuous and stable power supply in complex scenarios.

[0003] Existing technologies suffer from insufficient power grid prediction under extreme operating conditions, lagging energy storage dispatch, and limited operation and maintenance monitoring, making it difficult to guarantee continuous and stable power supply. Summary of the Invention

[0004] This application provides a grid resilience power supply guarantee method and system for extreme operating conditions, which is used to address the technical problems of insufficient grid prediction, lagging energy storage dispatch, and single operation and maintenance monitoring under extreme operating conditions in existing technologies, making it difficult to guarantee continuous and stable power supply.

[0005] In view of the above problems, this application provides a method and system for ensuring resilient power supply under extreme operating conditions.

[0006] The first aspect of this application provides a method for ensuring resilient power supply under extreme operating conditions, the method comprising: A power grid architecture diagram of the target area is constructed, and load status prediction rendering is performed on the power grid architecture diagram in combination with multi-source load time series to obtain a target visibility diagram. The target visibility diagram is coordinated with the target transportation network of the target area to carry out preventive planning of mobile energy storage, resulting in a target mobile energy storage layout. A three-layer three-dimensional operation and maintenance system is introduced to monitor the power grid of the target area to obtain real-time power grid information. When the real-time power grid operating conditions obtained by analyzing the real-time power grid information meet the predetermined extreme operating conditions, the target mobile energy storage layout is retrieved to form a real-time resilient power supply decision. Power supply is guaranteed for the target area based on the real-time resilient power supply decision.

[0007] A second aspect of this application provides a grid resilience power supply assurance system for extreme operating conditions, the system comprising: The target visibility acquisition module is used to construct a power grid architecture diagram of the target area and perform load state prediction rendering on the power grid architecture diagram in combination with multi-source load time series to obtain the target visibility diagram; the energy storage layout acquisition module is used to coordinate the target visibility diagram with the target transportation network of the target area to carry out preventive planning of mobile energy storage to obtain the target mobile energy storage layout; the real-time power grid information acquisition module is used to introduce a three-layer three-dimensional operation and maintenance system to monitor the power grid of the target area and obtain real-time power grid information; the power supply decision generation module is used to retrieve the target mobile energy storage layout to form a real-time resilient power supply decision when the real-time power grid operating conditions obtained by analyzing the real-time power grid information meet the predetermined extreme operating conditions; the power supply guarantee module is used to guarantee the power supply of the target area according to the real-time resilient power supply decision.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages: A power grid architecture diagram of the target area is constructed to obtain a target visual diagram; preventative planning of mobile energy storage is carried out to obtain a target mobile energy storage layout; a three-layer three-dimensional operation and maintenance system is introduced to monitor the power grid in the target area to obtain real-time power grid information; when the real-time power grid operating conditions obtained from the analysis of the real-time power grid information meet the predetermined extreme operating conditions, the target mobile energy storage layout is retrieved to form a real-time resilient power supply decision; and power supply is guaranteed for the target area based on the real-time resilient power supply decision. This achieves the technical effect of realizing rapid power grid response and resilient power supply under extreme operating conditions, and improves the power grid's power supply continuity and resilience guarantee capabilities in extreme scenarios. Attached Figure Description

[0009] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0010] Figure 1 A schematic flowchart of a power grid resilience power supply assurance method for extreme operating conditions provided in this application embodiment; Figure 2 This is a schematic diagram of a power grid resilience power supply guarantee system for extreme operating conditions, provided as an embodiment of this application.

[0011] Explanation of reference numerals in the attached diagram: Target visibility acquisition module 10, Energy storage layout acquisition module 20, Real-time power grid information acquisition module 30, Power supply decision generation module 40, Power supply guarantee module 50. Detailed Implementation

[0012] This application provides a grid resilience power supply guarantee method and system for extreme operating conditions, which addresses the technical problems of insufficient grid prediction, lagging energy storage dispatch, and single operation and maintenance monitoring under extreme operating conditions, making it difficult to guarantee continuous and stable power supply.

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0014] Example 1, as Figure 1 As shown, this application provides a method for ensuring resilient power supply under extreme operating conditions, the method comprising: Step S100: Construct a power grid architecture diagram of the target area, and combine the multi-source load time series to perform load state prediction rendering on the power grid architecture diagram to obtain a target view.

[0015] Specifically, a power grid architecture map of the target area is constructed, and the power grid architecture map is rasterized to obtain a power grid raster map composed of several continuous grids. In the pre-acquired multi-source load time series data, the first load time series corresponding to the first grid in the power grid raster map is matched, and the first load time series is fitted and analyzed to obtain the first load spline. Based on the first load spline, the first predicted load corresponding to the first grid is calculated. According to the one-to-one mapping relationship between the first grid and the first predicted load, the load status of each grid is visualized and rendered on the power grid raster map, and finally a target visual view that intuitively reflects the predicted distribution of power grid load in the target area is formed.

[0016] Step S200: The target visual diagram coordinates with the target transportation network of the target area to carry out preventive planning of mobile energy storage, thereby obtaining the target mobile energy storage layout.

[0017] Specifically, based on the obtained target visual map, a target predicted load contour map of the target area is generated. The first contour line and the second contour line in the contour map are extracted sequentially, and the first grid set corresponding to the first contour line and the second grid set corresponding to the second contour line are determined respectively. Combined with the target traffic network pre-constructed in the target area, mobile energy storage preventive planning is carried out on the first grid set and the second grid set respectively. The first grid set is filtered by a predetermined step size to obtain the first representative grid set. With a predetermined scheduling duration as the planning constraint, the deployment area corresponding to each representative grid is calculated in combination with the target traffic network. It is determined whether the deployment areas of different representative grids overlap. If they overlap, mobile energy storage is deployed in the overlapping area. If they do not overlap, the deployment node is determined with the shortest scheduling duration as the objective, and the first mobile energy storage layout is obtained. The second grid set is planned in the same way to obtain the second mobile energy storage layout. The second mobile energy storage layout is used to supplement and improve the first mobile energy storage layout through preventive planning, and finally a target mobile energy storage layout covering the load hotspots of the target area and adapting to traffic scheduling conditions is formed.

[0018] Step S300: Introduce a three-layer three-dimensional operation and maintenance system to monitor the power grid in the target area and obtain real-time power grid information.

[0019] Specifically, a three-layer integrated operation and maintenance system consisting of a physical layer, a sensing layer, and an application layer is introduced to conduct real-time monitoring of the power grid in the target area. The physical layer uses fiber optic composite overhead ground wire cables as the hardware carrier to provide stable link support for sensing and transmission. The sensing layer integrates various sensing devices such as distributed fiber optic sensors, video surveillance, and drones to collect multi-dimensional data on power grid operation status, environmental parameters, and equipment operating conditions. The application layer fuses and analyzes the collected multi-source data to predict power grid operation trends and ultimately outputs real-time power grid information that comprehensively reflects the real-time operation status of the power grid.

[0020] Step S400: When the real-time power grid operating conditions obtained by analyzing the real-time power grid information meet the predetermined extreme operating conditions, the target mobile energy storage layout is retrieved to form a real-time resilient power supply decision.

[0021] Specifically, the system collects and integrates real-time grid information from the three-layer three-dimensional operation and maintenance system to determine operating conditions and assess risks. When the real-time grid operating conditions are determined to reach or exceed the preset limit operating condition threshold, the system immediately retrieves the target mobile energy storage layout data that has been pre-planned for preventive purposes. It then performs real-time matching and scheduling calculations based on the current grid fault location, load gap, traffic accessibility, and power supply restoration priority to quickly generate real-time resilient power supply decisions for rapid response, precise support, and stable recovery under extreme operating conditions.

[0022] Step S500: Provide power supply assurance for the target area based on the real-time resilience power supply decision.

[0023] Specifically, based on the real-time resilient power supply decisions, power supply regulation operations such as mobile energy storage scheduling, load transfer, and power support are performed on the target area. At the same time, relying on the dual-ring network hot standby communication guarantee mechanism, when real-time communication data such as real-time optical power attenuation rate or real-time bit error rate reach the predetermined constraints, the channel switching mechanism is triggered, and the communication link is automatically switched from the primary communication channel to the backup communication channel. Communication security can be ensured by accessing the quantum key distributor through reserved optical fiber, ensuring the reliable issuance and execution of real-time resilient power supply decisions. In this way, a continuous, stable, and secure power supply is provided to the target area under extreme operating conditions, realizing the grid resilient power supply guarantee.

[0024] In one possible implementation, step S500 further includes: Step S510: Construct a dual-ring network hot standby, wherein the dual-ring network hot standby includes a primary communication channel and a backup communication channel.

[0025] Step S520: When the real-time communication data of the target area reaches the predetermined constraint, the switching mechanism is triggered.

[0026] Step S530: Based on the switching mechanism, switch the communication channel from the primary communication channel to the backup communication channel.

[0027] Step S540: Communicate and transmit the real-time resilient power supply decision through the backup communication channel.

[0028] Specifically, to ensure the reliability and continuity of power grid dispatch communication under extreme operating conditions, a dual-ring hot standby communication architecture is pre-constructed for the target area. This dual-ring hot standby consists of two independent and physically isolated communication links, defined as the primary communication channel and the backup communication channel, respectively. The primary communication channel is used for the transmission of real-time resilient power supply decisions and power grid operation data under normal conditions, while the backup communication channel is in a hot standby standby state and can be put into use immediately when the primary channel fails. The dual-ring hot standby is also equipped with reserved optical fibers, which can support the access of quantum key distributors, further improving the security and anti-interference capability of communication transmission.

[0029] By deploying optical power monitoring modules and bit error rate detection modules on communication nodes, the real-time optical power attenuation rate and real-time bit error rate of the main communication channel in the target area are continuously collected as real-time communication data. The edge computing unit compares the collected data with the preset communication degradation threshold in real time. When the real-time communication data meets or exceeds the predetermined constraints, a high-level trigger signal is immediately output and the communication control unit is linked to automatically activate the channel switching mechanism of the dual-ring network hot standby.

[0030] After the switching mechanism is triggered, the communication control unit performs a seamless switching operation without interruption according to the preset switching logic. It instantly disconnects the data transmission link of the primary communication channel and simultaneously activates the backup communication channel in hot standby mode. It quickly completes signal routing reconstruction and channel status switching to ensure that the real-time resilient power supply decision commands and power grid operation data are not lost or interrupted during the switching process, and maintains the continuity and stability of the communication link.

[0031] After the communication channel switch is completed, the real-time resilient power supply decision information generated by the system is encoded, encapsulated and securely transmitted using the backup communication channel that is in operation. Key data such as dispatch instructions, mobile energy storage configuration and load control parameters are sent stably and reliably to the grid execution terminal and mobile energy storage devices, ensuring that grid dispatch instructions are delivered accurately under extreme conditions and providing real-time and reliable communication support for power supply guarantee actions.

[0032] In one possible implementation, step S500 further includes: The real-time communication data refers to the real-time optical power attenuation rate or the real-time bit error rate.

[0033] Specifically, the real-time communication data refers to core indicators used to quantify and determine the transmission quality and link status of the power grid communication channel, including real-time optical power attenuation rate and real-time bit error rate. Real-time optical power attenuation rate refers to the ratio of the actual output power of the optical signal to the nominal transmission power during transmission through the primary communication channel, reflecting physical conditions such as fiber optic link loss, breakage, and interference. Real-time bit error rate refers to the proportion of erroneous bits transmitted per unit time to the total number of transmitted bits, characterizing the accuracy and reliability of data transmission. These two parameters together serve as the direct basis for determining whether to trigger the channel switching mechanism.

[0034] In one possible implementation, step S500 further includes: The dual-ring network hot standby has reserved optical fibers, which are used to access the quantum key distributor.

[0035] Specifically, the dual-ring network hot standby, in addition to the primary and backup communication channels, is equipped with reserved optical fibers. These reserved optical fibers are pre-laid, independently available optical fiber resources in the dual-ring network architecture. They do not participate in regular scheduling data transmission and are specifically used to access the quantum key distributor. The quantum key distributor uses the reserved optical fibers to achieve secure distribution and synchronization of quantum keys. It can encrypt and transmit core scheduling commands such as real-time resilient power supply decisions, effectively resisting communication interference and tampering risks under extreme operating conditions, and further improving the confidentiality and anti-attack capability of power grid scheduling communication.

[0036] In one possible implementation, step S100 further includes: Step S110: Rasterize the power grid architecture diagram to obtain a power grid raster diagram.

[0037] Step S120: Match the first load time sequence corresponding to the first grid in the power grid grid diagram in the multi-source load time sequence.

[0038] Step S130: Fit and analyze the first load time series to obtain the first load spline, and obtain the first predicted load based on the first load spline.

[0039] Step S140: Form the target view based on the mapping relationship between the first grid and the first predicted load.

[0040] Specifically, according to the preset spatial scale and regional division rules, the completed target area power grid architecture map is rasterized, and the continuous power grid coverage area is evenly divided into several regular raster units of the same size and with clear location, so that each raster corresponds to a specific geographical range and electrical node in the power grid, thereby forming a power grid raster map that is convenient for load calculation, status rendering and planning analysis.

[0041] By employing spatiotemporal index matching and geospatial association, a unique geographic coordinate and distribution topology index are first established for the first grid cell in the power grid grid map. Then, a spatiotemporal alignment algorithm is used to perform timestamp calibration and spatial attribution matching on the multi-source load time series data, accurately binding load monitoring data with the first grid cell in the same time dimension and within the same power supply coverage area, and automatically extracting and generating the first load time series corresponding to the first grid cell.

[0042] A cubic spline interpolation algorithm is used to fit and analyze the first load time series. Using discrete historical load data in the first load time series as interpolation nodes, a piecewise smooth and continuously differentiable cubic polynomial function is constructed. By solving the continuity equations of the first and second derivatives at the nodes, a globally smooth load change curve, i.e., the first load spline, is obtained. Extrapolation calculation is performed based on this first load spline. By substituting the independent variables of the future target time, the load prediction value at the corresponding time is obtained directly through the spline function, i.e., the first predicted load, thus achieving high-precision and smoothed power grid load time series prediction.

[0043] Establish a one-to-one spatial-numerical mapping relationship between the first grid and the first predicted load. Set different color gradients, fill styles or brightness levels according to the magnitude of the predicted load value. Perform point-by-point load status visualization rendering on the first grid and all grids in the entire area on the power grid grid map. Transform the abstract predicted load value into an intuitive, recognizable and locatable spatial visualization effect. Finally, form a target visualization map that can present the overall distribution of the predicted power grid load in the target area.

[0044] In one possible implementation, step S200 further includes: Step S210: Based on the target visibility map, form a target predicted load contour map of the target area.

[0045] Step S220: Obtain the first contour line of the target predicted load contour map.

[0046] Step S230: Combine the target transportation network to perform preventive planning of mobile energy storage for the first grid set corresponding to the first contour line, and obtain the first mobile energy storage layout.

[0047] Step S240: Obtain the second contour line of the target predicted load contour map.

[0048] Step S250: Combine the target transportation network to perform preventive planning of mobile energy storage for the second grid set corresponding to the second contour line, and obtain the second mobile energy storage layout.

[0049] Step S260: The first mobile energy storage layout is supplemented with the second mobile energy storage layout through preventative planning to obtain the target mobile energy storage layout.

[0050] Specifically, an improved Marching Squares contour extraction algorithm is used to process the target view. The first predicted load of each grid cell in the power grid grid map is used as the grid node value. All grid cells are traversed and the position of the contour line crossing edge is determined according to the relationship between the node load value and the preset contour threshold. The precise coordinates of the contour line are calculated by linear interpolation. Then, the contour line segments of adjacent grid cells are tracked, connected and smoothed to finally generate a target predicted load contour map that can continuously and accurately reflect the spatial distribution characteristics of the predicted load in the target area.

[0051] Based on the pre-set load classification threshold, the contour lines that correspond to the highest load level, are spatially continuous and closed, and can delineate the core heavy load range within the target area are selected and extracted from the target predicted load contour map. These contour lines are the first contour lines in the target predicted load contour map.

[0052] Based on the geographical area enclosed by the first contour line, all grid cells within this area are determined to constitute the first grid set. The load density, weak power supply points, and emergency response requirements of this grid set are used as the planning basis. Combined with traffic constraints such as road connectivity, travel distance, and access time of the target transportation network, the deployment locations, standby numbers, and dispatch routes of mobile energy storage vehicles are comprehensively optimized and configured to complete the preventive planning of mobile energy storage for high-load core areas, and finally form the first mobile energy storage layout.

[0053] In the target predicted load contour map, based on the preset load classification standard, continuous closed contour lines that are lower than the load level corresponding to the first contour line and can cover the second highest load area or important protection area are selected, and the second contour line is extracted through spatial matching and threshold determination.

[0054] Based on the second grid set delineated by the second contour lines, the first predicted load value, power supply node coordinates, and reliability weights of each grid are extracted. With the clustering objective of "maximizing load coverage and minimizing the number of points," the K-means algorithm iteratively calculates the cluster centers, dividing the second grid set into several load-aggregating sub-regions. The core coverage coordinates of each sub-region are output as the candidate deployment point set for mobile energy storage. Next, the road network topology data of the target transportation network, including road grade, traffic speed, and node connectivity, is imported. Starting from the candidate deployment point set and ending at each grid sub-region, Dijkstra's algorithm is used to traverse the road network weight map. The process involves calculating the shortest travel time from each candidate point to all grids within its corresponding sub-region, filtering out effective deployment points whose travel times meet preset emergency response thresholds, such as those reachable within 30 minutes. Finally, a multi-objective integer programming model is constructed, with constraints including "energy storage capacity matching load gap, lowest scheduling cost, and redundancy coverage meeting standards." Inputs include load demand, traffic accessibility data, and mobile energy storage device parameters, such as rated capacity and charging / discharging efficiency, for effective deployment points. The model is solved using the branch-and-bound method to determine the number of mobile energy storage configurations, capacity specifications, and cross-regional scheduling linkages for each effective deployment point, ultimately forming the second mobile energy storage layout.

[0055] The second mobile energy storage layout is used as a supplementary solution to the first mobile energy storage layout. It supplements the second-highest load area, the edge area with weak power supply, and the blind spot of transportation access that are not covered by the first mobile energy storage layout. Through site merging, capacity redundancy verification and scheduling path coordination, the guarantee gap between the high load area and the second-highest load area is eliminated, forming a complete planning result with full coverage, clear hierarchy and coordinated scheduling, and finally obtaining the target mobile energy storage layout.

[0056] In one possible implementation, step S230 further includes: Step S231: Select grids in the first grid set with a predetermined step size to obtain a first representative grid set.

[0057] Step S232: Using the predetermined scheduling duration as a planning constraint, and combining it with the target traffic network, obtain the first deployment area corresponding to the first representative grid in the first representative grid set.

[0058] Step S233: Determine the second deployment area corresponding to the second representative grid in the first representative grid set.

[0059] Step S234: Determine whether the first deployment area and the second deployment area overlap.

[0060] Step S235: If it exists, deploy mobile energy storage at the overlapping area to form the first mobile energy storage layout.

[0061] Specifically, according to the preset spatial sampling step size, the first grid set covered by the first contour line is systematically selected and representatively screened. Based on the load density, spatial location and geographical importance of the grid, redundant and duplicate grid units are eliminated, and the set of grid units that can fully reflect the core load characteristics and spatial distribution patterns of the area is retained. Finally, the first representative grid set is obtained, which provides a concise and effective spatial benchmark for subsequent deployment area division and layout planning.

[0062] With the predetermined scheduling duration as a constraint, and combining the design speed and actual travel time of each road segment in the target transportation network, a weighted topology map of the road network centered on the first representative grid is constructed. All reachable road nodes are traversed through breadth-first search (BFS), the travel time is accumulated segment by segment, and all nodes and road segments whose total travel time does not exceed the preset scheduling duration are selected. The geographical space covered by these nodes is closed and delineated to form the mobile energy storage dispatchable service range corresponding to the first representative grid, i.e., the first deployment area.

[0063] Using the same calculation method as the first representative grid, with a predetermined scheduling duration as a constraint, and combining the road segment travel time, driving speed and topological connectivity of the target transportation network, the isochronous reachability range is calculated with the second representative grid as the center. All road network nodes and geographical areas reachable within the specified time are traversed to form the mobile energy storage coverage service range corresponding to the grid, which is the second deployment area.

[0064] The first deployment area and the second deployment area are converted into regularized spatial polygon data. The geometric boundaries and coverage of the two polygons are compared point by point using a spatial intersection determination algorithm. The intersection area of ​​the two polygons is calculated. Based on whether there is a spatial range with overlapping coordinates, it is determined whether the first deployment area and the second deployment area overlap.

[0065] If it is determined that the first deployment area and the second deployment area have spatial overlap, then the overlapping area is identified as a key point for priority deployment of mobile energy storage. Mobile energy storage devices are configured in a coordinated manner within this area so that they can simultaneously cover the load areas where the two representative grids are located, thereby achieving resource intensive and efficient scheduling, and finally completing the planning and forming the first mobile energy storage layout.

[0066] In one possible implementation, step S234 further includes: If it does not exist, mobile energy storage is deployed on the first representative grid to obtain the first layout, and mobile energy storage is deployed on the second representative grid to obtain the second layout.

[0067] The first layout and the second layout together form the first mobile energy storage layout.

[0068] The first layout is obtained by deploying mobile energy storage on the first representative grid, including: Obtain any node in the first deployment region.

[0069] The arbitrary scheduling time from any node to the first representative grid is obtained by combining the target transportation network.

[0070] The target node is obtained with the goal of minimizing the arbitrary scheduling time, and the target node is used as the first layout.

[0071] Specifically, if it is determined that there is no spatial overlap between the first deployment area and the second deployment area, then mobile energy storage site planning will be carried out independently for the first representative grid and the second representative grid respectively: the node with the optimal scheduling time in the first deployment area will be selected to complete the mobile energy storage deployment, forming the first layout; the node with the optimal scheduling time in the second deployment area will be selected to complete the mobile energy storage deployment, forming the second layout.

[0072] The first and second layouts, which were independently planned, are spatially merged and coordinated, retaining their respective mobile energy storage deployment sites, scheduling ranges, and configuration schemes. By combining them, a complete planning result is formed that covers the entire first representative grid set, has no overlap or conflict, and is highly efficient in scheduling. This is the first mobile energy storage layout.

[0073] In the process of deploying mobile energy storage for the first representative grid to determine the first layout, any node that can be used to park and dispatch mobile energy storage devices is selected from the geographical and road network range covered by the first deployment area as an initial candidate node. This node is selected from a legal and feasible location within the first deployment area and is used for subsequent scheduling time calculation and optimal deployment location selection.

[0074] A weighted directed graph of road segments is constructed based on the target transportation network. The road segment weight is obtained by dividing the road length between nodes by the travel speed. Dijkstra's algorithm is used to search for the shortest path from any node to the first representative grid. The travel time of all road segments on the path is accumulated to obtain the scheduling time from the node to the first representative grid.

[0075] After traversing all candidate nodes in the first deployment area and calculating their respective scheduling durations, with the goal of minimizing scheduling duration, the node with the shortest scheduling time is selected from all nodes as the optimal target node, and this node is directly determined as the deployment location for mobile energy storage, thus forming the first layout.

[0076] In one possible implementation, step S300 further includes: The three-layer three-dimensional operation and maintenance system includes a physical layer, a sensing layer, and an application layer. The physical layer uses optical fiber composite overhead ground wire cable as the carrier, the sensing layer integrates distributed optical fiber sensing, video surveillance, and drones, and the application layer is used to perform fusion analysis on the real-time power grid information to obtain predicted operating status.

[0077] Specifically, the three-layer three-dimensional operation and maintenance system consists of a physical layer, a sensing layer, and an application layer, forming an integrated three-dimensional protection architecture. The physical layer uses OPGW (Optical Fiber Composite Overhead Ground Wire) cable as the carrier. This cable serves dual functions of grounding and lightning protection for transmission lines and fiber optic communication transmission, providing a stable and reliable physical transmission channel for sensor signals and monitoring data. The sensing layer integrates distributed fiber optic sensing, video surveillance, and drone inspection equipment. Distributed fiber optic sensing relies on the OPGW cable to achieve continuous distributed monitoring of parameters such as temperature, vibration, strain, and sag along the entire transmission line. Video surveillance is used for all-weather visual image acquisition of towers, line corridors, and external hazards. Drones are equipped with visible light and infrared imaging... The module enables mobile inspection and defect identification in complex sections and high-altitude locations. These three components work together to form a multi-dimensional, fully covered real-time power grid information sensing network. The application layer adopts a three-level progressive algorithm structure of data fusion, feature extraction, and time series prediction. First, it uses weighted DS evidence theory to perform spatiotemporal fusion and noise reduction on multi-source heterogeneous real-time power grid information. Then, it uses CNN convolutional neural network to extract key features of line operation. Finally, it inputs the time series features into LSTM long short-term memory network for trend reasoning and state judgment. Through deep fusion analysis of multi-source sensing data, it outputs the predicted operating status of the power grid, realizing intelligent prediction and decision support for transmission line operation risks, fault probabilities, and future operating conditions.

[0078] Example 2 is based on the same inventive concept as the grid resilience power supply assurance method for extreme operating conditions described in the previous examples, such as... Figure 2 As shown, this application provides a grid resilience power supply guarantee system for extreme operating conditions. The system and method embodiments in this application are based on the same inventive concept. The system includes: The target visibility acquisition module 10 is used to construct a power grid architecture diagram of the target area and perform load state prediction rendering on the power grid architecture diagram in combination with multi-source load time series to obtain the target visibility diagram.

[0079] The energy storage layout acquisition module 20 is used to conduct preventive planning of mobile energy storage in coordination with the target transportation network of the target area to obtain the target mobile energy storage layout.

[0080] The real-time power grid information acquisition module 30 is used to introduce a three-layer three-dimensional operation and maintenance system to monitor the power grid in the target area and obtain real-time power grid information.

[0081] The power supply decision generation module 40 is used to retrieve the target mobile energy storage layout to form a real-time resilient power supply decision when the real-time power grid operating conditions obtained by analyzing the real-time power grid information meet the predetermined extreme operating conditions.

[0082] The power supply guarantee module 50 is used to guarantee the power supply to the target area based on the real-time resilience power supply decision.

[0083] Furthermore, the system is also used to implement the following functions: A dual-ring network hot standby is constructed, wherein the dual-ring network hot standby includes a primary communication channel and a backup communication channel; when the real-time communication data of the target area reaches a predetermined constraint, a switching mechanism is triggered; based on the switching mechanism, the communication channel is switched from the primary communication channel to the backup communication channel; the real-time resilient power supply decision is communicated and transmitted through the backup communication channel.

[0084] Furthermore, the system is also used to implement the following functions: The real-time communication data refers to the real-time optical power attenuation rate or the real-time bit error rate.

[0085] Furthermore, the system is also used to implement the following functions: The dual-ring network hot standby has reserved optical fibers, which are used to access the quantum key distributor.

[0086] Furthermore, the system is also used to implement the following functions: The power grid architecture diagram is rasterized to obtain a power grid raster diagram; the first load time series corresponding to the first grid in the power grid raster diagram is matched in the multi-source load time series; the first load time series is fitted and analyzed to obtain a first load spline, and a first predicted load is obtained based on the first load spline; the target visual diagram is formed based on the mapping relationship between the first grid and the first predicted load.

[0087] Furthermore, the system is also used to implement the following functions: Based on the target visual map, a target predicted load contour map of the target area is generated; a first contour line of the target predicted load contour map is obtained; mobile energy storage preventive planning is performed on the first grid set corresponding to the first contour line in conjunction with the target transportation network to obtain a first mobile energy storage layout; a second contour line of the target predicted load contour map is obtained; mobile energy storage preventive planning is performed on the second grid set corresponding to the second contour line in conjunction with the target transportation network to obtain a second mobile energy storage layout; the first mobile energy storage layout is supplemented with preventive planning using the second mobile energy storage layout to obtain the target mobile energy storage layout.

[0088] Furthermore, the system is also used to implement the following functions: The first grid set is selected by a predetermined step size to obtain a first representative grid set; the first deployment area corresponding to the first representative grid in the first representative grid set is obtained by combining the predetermined scheduling time as a planning constraint with the target transportation network; the second deployment area corresponding to the second representative grid in the first representative grid set is determined; it is determined whether the first deployment area and the second deployment area overlap; if they do, mobile energy storage is deployed at the overlapping area to form the first mobile energy storage layout.

[0089] Furthermore, the system is also used to implement the following functions: If it does not exist, mobile energy storage is deployed on the first representative grid to obtain a first layout, and mobile energy storage is deployed on the second representative grid to obtain a second layout; the first layout and the second layout form the first mobile energy storage layout; wherein, deploying mobile energy storage on the first representative grid to obtain the first layout includes: obtaining any node in the first deployment area; obtaining any scheduling time from the arbitrary node to the first representative grid in combination with the target transportation network; obtaining a target node with the shortest arbitrary scheduling time as the target, and using the target node as the first layout.

[0090] Furthermore, the system is also used to implement the following functions: The three-layer three-dimensional operation and maintenance system includes a physical layer, a sensing layer, and an application layer. The physical layer uses optical fiber composite overhead ground wire cable as the carrier, the sensing layer integrates distributed optical fiber sensing, video surveillance, and drones, and the application layer is used to perform fusion analysis on the real-time power grid information to obtain predicted operating status.

[0091] It should be noted that the order of the embodiments described above is for descriptive purposes only and does not represent the superiority or inferiority of the embodiments. Specific embodiments of this specification have been described above. Furthermore, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0092] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0093] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for ensuring resilient power supply under extreme operating conditions, characterized in that, include: Construct a power grid architecture diagram for the target area, and combine it with multi-source load time series to perform load state prediction rendering on the power grid architecture diagram to obtain a target view; The target visual diagram coordinates with the target transportation network of the target area to carry out preventive planning of mobile energy storage, thereby obtaining the target mobile energy storage layout; A three-tiered, integrated operation and maintenance system is introduced to monitor the power grid in the target area and obtain real-time power grid information. When the real-time power grid operating conditions obtained by analyzing the real-time power grid information meet the predetermined extreme operating conditions, the target mobile energy storage layout is retrieved to form a real-time resilient power supply decision. Power supply is guaranteed for the target area based on the real-time resilience power supply decision.

2. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 1, characterized in that, Based on the real-time resilient power supply decision, power supply assurance is provided to the target area, which previously included: Construct a dual-ring network hot standby, wherein the dual-ring network hot standby includes a primary communication channel and a backup communication channel; When the real-time communication data of the target area reaches a predetermined constraint, a switching mechanism is triggered; Based on the switching mechanism, the communication channel is switched from the primary communication channel to the backup communication channel; The real-time resilient power supply decision is communicated and transmitted through the backup communication channel.

3. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 2, characterized in that, The real-time communication data refers to the real-time optical power attenuation rate or the real-time bit error rate.

4. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 2, characterized in that, The dual-ring network hot standby has reserved optical fibers, which are used to access the quantum key distributor.

5. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 1, characterized in that, Construct a power grid architecture diagram for the target area, and combine it with multi-source load time series to perform load state prediction rendering on the power grid architecture diagram to obtain a target view, including: The power grid architecture diagram is rasterized to obtain a power grid raster diagram; Match the first load time sequence corresponding to the first grid in the power grid grid diagram in the multi-source load time sequence; The first load spline is obtained by fitting and analyzing the first load time series, and the first predicted load is obtained based on the first load spline; The target visualization is formed based on the mapping relationship between the first grid and the first predicted load.

6. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 5, characterized in that, The target visual diagram coordinates with the target transportation network of the target area to conduct preventative planning of mobile energy storage, resulting in a target mobile energy storage layout, including: Based on the target visibility map, a target predicted load contour map of the target area is generated; Obtain the first contour line of the target predicted load contour map; By combining the target transportation network, preventive planning for mobile energy storage is carried out on the first grid set corresponding to the first contour line, resulting in the first mobile energy storage layout. Obtain the second contour line of the target predicted load contour map; By combining the target transportation network, preventive planning for mobile energy storage is carried out on the second grid set corresponding to the second contour line, resulting in the second mobile energy storage layout. The first mobile energy storage layout is supplemented by the second mobile energy storage layout through preventative planning to obtain the target mobile energy storage layout.

7. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 6, characterized in that, Preventive planning for mobile energy storage is performed on the first grid set corresponding to the first contour line in conjunction with the target transportation network to obtain the first mobile energy storage layout, including: The first grid set is selected by a predetermined step size to obtain the first representative grid set; Using the predetermined scheduling duration as a planning constraint, and combining it with the target transportation network, the first deployment area corresponding to the first representative grid in the first representative grid set is obtained; Determine the second deployment area corresponding to the second representative grid in the first representative grid set; Determine whether the first deployment area and the second deployment area overlap; If they exist, mobile energy storage is deployed at the overlapping areas to form the first mobile energy storage layout.

8. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 7, characterized in that, Determine whether the first deployment area and the second deployment area overlap, then include: If it does not exist, mobile energy storage is deployed on the first representative grid to obtain the first layout, and mobile energy storage is deployed on the second representative grid to obtain the second layout; The first layout and the second layout together form the first mobile energy storage layout; The first layout is obtained by deploying mobile energy storage on the first representative grid, including: Obtain any node in the first deployment region; The arbitrary scheduling time from any node to the first representative grid is obtained by combining the target transportation network; The target node is obtained with the goal of minimizing the arbitrary scheduling time, and the target node is used as the first layout.

9. The grid resilience power supply guarantee method for extreme operating conditions as described in claim 1, characterized in that, The three-layer three-dimensional operation and maintenance system includes a physical layer, a sensing layer, and an application layer. The physical layer uses optical fiber composite overhead ground wire cable as the carrier, the sensing layer integrates distributed optical fiber sensing, video surveillance, and drones, and the application layer is used to perform fusion analysis on the real-time power grid information to obtain predicted operating status.

10. A power grid resilience power supply guarantee system for extreme operating conditions, characterized in that, The system is used to implement the grid resilience power supply guarantee method for extreme operating conditions as described in any one of claims 1-9, and the system comprises: The target visibility acquisition module is used to construct a power grid architecture diagram of the target area, and combine multi-source load time series to perform load state prediction rendering on the power grid architecture diagram to obtain the target visibility diagram; The energy storage layout acquisition module is used to perform preventive planning of mobile energy storage in coordination with the target transportation network of the target area to obtain the target mobile energy storage layout. The real-time power grid information acquisition module is used to introduce a three-layer three-dimensional operation and maintenance system to monitor the power grid in the target area and obtain real-time power grid information. The power supply decision generation module is used to retrieve the target mobile energy storage layout to form a real-time resilient power supply decision when the real-time power grid operating conditions obtained by analyzing the real-time power grid information meet the predetermined extreme operating conditions. The power supply guarantee module is used to guarantee the power supply to the target area based on the real-time resilience power supply decision.

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