A modeling method and system for multi-level power supply equipment and mains power

Abstract

The present application relates to the technical field of visual management of power supply equipment, and provides a modeling method and system for multi-level power supply equipment and mains power, including identifying the load level of each smart meter based on the power consumption and power consumption time in the power consumption information; clustering according to the load level corresponding to each smart meter, and dividing the target area into multiple sub-areas; judging the first power supply relationship between the power supply equipment and the sub-area based on a preset strategy; obtaining the location information of the mains power line and the second power supply relationship with each sub-area based on the power supply network diagram; establishing a connection relationship between the sub-area, mains power and power supply equipment based on the two power supply relationships; superimposing the connection relationship and the location information of the power supply equipment, sub-area and mains power line on the map information of the target area to generate a target model. The system realizes the automatic acquisition of the power supply status of multi-level power supply equipment, and also provides data support for power managers by displaying it on the map information.

Description

Technical Field

[0001] The present application relates to the technical field of visual management of power supply equipment, and in particular to a modeling method and system for multi-level power supply equipment and mains power. Background Art

[0002] The contents of this section merely provide background information related to this application and may not constitute prior art.

[0003] A significant issue in current grid control models and power supply diagram designs is that the power supply relationships of power-guaranteeing equipment are not clearly identified. This makes it difficult to accurately determine the actual power supply area of the power-guaranteeing equipment and its relationship to the entire grid during grid operation management and troubleshooting, thus impacting grid stability and reliability.

[0004] Specifically, existing power grid control models primarily focus on the overall operation and scheduling of the grid. However, the power supply relationships and areas of specific power supply equipment, such as backup power supplies and emergency generators, are often not modeled and identified in detail. Furthermore, this critical information is often omitted from power supply diagrams, making it difficult for operations and maintenance personnel to quickly determine which areas are powered by specific power supply equipment when faced with grid failures or emergencies, hindering effective scheduling and fault recovery.

[0005] In the prior art, Chinese patent publication number CN101951016B discloses an adaptive modeling and control method for automatic backup power supply activation based on wide-area information. The method includes establishing a multi-value mapping from a set of fault-tripped power sources to a set of automatic backup power supply modes, performing logical operations and control for the automatic backup power supply, executing regional fault identification measures, performing pre-decision-making on the backup power supply overload control strategy, and performing online matching and search control strategies. Through adaptive modeling and pre-decision-making, the automatic backup power supply mode and overload shedding control strategy are optimized, ensuring safe and stable system operation after the backup power supply is activated and enabling wide-area load restoration.

[0006] However, the existing technology is limited in that it is primarily applicable to control power supply equipment in known, small-scale scenarios, such as within a single hospital. This approach's limitations become apparent when applied to a city-wide power supply system. Because power supply equipment in a city is typically independently located and numerous, traditional manual statistical methods are not only time-consuming and inefficient in achieving a comprehensive understanding of their power supply status. Given this situation, a multi-level modeling method and system for power supply equipment and utility power are urgently needed. Summary of the Invention

[0007] In order to solve the above technical problems, the purpose of this application is to provide a modeling method and system for multi-level power supply equipment and city power. By analyzing the map information of the target area, the power supply network diagram, the location information of the power supply equipment in the target area, the equipment information of the power supply equipment, and the location information and power consumption information of all smart meters, the relationship and connection between the multi-level power supply equipment and the city power in the target area are automatically obtained. At the same time, by integrating multi-source data and displaying it on the map information, a refined description of the power supply management of the target area is achieved, providing accurate decision support for power managers.

[0008] The purpose of this application is achieved through the following technical solutions:

[0009] In a first aspect, the present invention provides a modeling method for multi-level power supply equipment and mains power, comprising:

[0010] S101, obtaining map information and a power supply network diagram of a target area, obtaining location information and device information of power supply guarantee equipment in the target area, and location information and power consumption information of all smart meters;

[0011] S102, identifying the load level at the location of each smart meter based on the power consumption and power consumption time in the power consumption information;

[0012] S103, clustering according to the load level corresponding to each smart meter, and dividing the target area into multiple sub-areas;

[0013] S104, determining a first power supply relationship between the power supply guarantee equipment and the sub-area based on a preset strategy according to the location information of the sub-area, the location information of the power supply guarantee equipment, the working status of the power supply guarantee equipment, and the power consumption information of all smart meters;

[0014] The preset strategy includes: obtaining the time period in which the power consumption fluctuation of any sub-area exceeds the threshold, checking the number of power supply guarantee equipment that meets the preset conditions, and the preset conditions include that the power supply guarantee equipment is started within the time period, and after the power supply guarantee equipment is started, the power consumption of the sub-area is stabilized or restored; if the number of power supply guarantee equipment that meets the preset conditions is 0, then the sub-area is marked as having no power supply guarantee equipment; if the number of power supply guarantee equipment that meets the preset conditions is 1, then the power supply guarantee equipment is deemed to be supplying power to the sub-area;

[0015] If there are multiple power supply guarantee devices that meet the preset conditions, the number of target sub-areas whose power consumption fluctuations exceed the threshold within the time period is detected; when the detection result is 0, it is determined that multiple power supply guarantee devices are all supplying power to the target sub-area; when the detection result is greater than 1, the distance between each target sub-area and the activated power supply guarantee device is calculated, and it is determined that the target sub-area has a power supply relationship with the power supply guarantee devices whose distance is less than the preset distance;

[0016] S105, obtaining location information of the mains power line and a second power supply relationship with each sub-area based on the power supply network diagram; establishing a connection relationship between the sub-area, the mains power, and the power supply guarantee equipment based on the first power supply relationship and the second power supply relationship;

[0017] S106 , superimposing the connection relationship, the location information of the power supply equipment, the sub-area location information, and the location information of the mains power line onto the map information of the target area to generate a target model.

[0018] Furthermore, the step of identifying the load level at the location of each smart meter specifically includes:

[0019] If the power consumption fluctuation of any smart meter is detected to remain below the threshold, it is identified as a first-level power supply area;

[0020] If it is detected that the power consumption of any smart meter exceeds the preset power consumption, and the power consumption fluctuation exceeds the threshold, it is identified as a secondary power supply area;

[0021] If the smart meter's electricity consumption is detected to be within the preset range and contains peak electricity consumption in both the morning and evening time periods, it will be identified as a Level 3 power supply area.

[0022] Furthermore, the step of dividing the target area into multiple sub-areas specifically includes:

[0023] Each smart meter is divided into several categories according to the load level, and each category represents a load level range;

[0024] Calculate the spatial distance between each smart meter and other smart meters within the load level to which it belongs to form a distance matrix;

[0025] Use K-means clustering algorithm to cluster the distance matrix;

[0026] Based on the clustering results, smart meters that are spatially close and have similar load levels are grouped into a sub-region to ensure that the smart meters in each sub-region are relatively consistent in terms of geographical location and electricity consumption characteristics.

[0027] Output the sub-region division results after clustering.

[0028] Furthermore, the expression of the sub-region division result is:

[0029]

[0030] Among them, C is the division result, that is, the set containing the smart meter index; k is the number of sub-areas; C i is the set of all smart meters in the ith sub-area; x is the location information of the smart meter, which is a 2-dimensional real vector; μi is the centroid of the ith subregion, ||x-μ i || 2 is the centroid μ from smart meter x to sub-area i i The square of the Euclidean distance.

[0031] Furthermore, the steps of checking the number of power supply guarantee equipment that meets the preset conditions specifically include:

[0032] Monitor the working status changes of each power supply equipment in real time and record the startup time;

[0033] Synchronously analyze the electricity consumption data of each sub-area within the corresponding time period and identify the sub-areas whose electricity consumption meets the preset variation range;

[0034] The time series analysis method is applied to compare the consistency between the start-up time of the power supply equipment and the time points of the changes in power consumption in the sub-regions, and the number of power supply equipment whose consistency meets the preset consistency range is counted.

[0035] Furthermore, after generating the target model, the following steps are also included:

[0036] Obtain the device information corresponding to the power supply equipment from the preset database and calculate the maximum output power of each power supply equipment;

[0037] Count the maximum power load of each sub-area within a preset time period;

[0038] Compare the maximum output power of each power supply equipment with the maximum power load of the sub-area it supplies power. If the maximum output power of the power supply equipment is greater than or equal to the maximum power load of the sub-area it supplies power, then it is determined that the power supply capacity of the power supply equipment is sufficient to cover the power demand of the sub-area; if the maximum output power of the power supply equipment is less than the maximum power load of the sub-area it supplies power, then it is determined that the power supply capacity of the power supply equipment is insufficient to cover the power demand of the sub-area, and an early warning message is generated.

[0039] Furthermore, after the target model is generated, the generated target model is also dynamically updated;

[0040] Dynamic updates include:

[0041] Real-time monitoring of changes in the working status of power supply equipment in the target area, changes in the power consumption of smart meters, and the power supply status of the mains power lines;

[0042] Based on the monitoring results, update the location information, working status of the power supply equipment, the power consumption information of the smart meter, and the location information and power supply status of the mains power line;

[0043] Based on the updated information, re-determine the first power supply relationship between the power supply equipment and the sub-area and the second power supply relationship between the mains and the sub-area;

[0044] Based on the re-judgment results, the connection relationship between the sub-area, the mains power supply, and the power supply equipment is updated;

[0045] The updated connection relationship, location information of power supply equipment, sub-area location information, and location information of mains power lines are superimposed on the map information of the target area to generate an updated target model.

[0046] In a second aspect, the present invention provides a modeling system for multi-level power supply equipment and mains power, comprising:

[0047] The data acquisition module is used to obtain map information and power supply network diagrams of the target area, the location information of power supply equipment in the target area, the equipment information of power supply equipment, and the location information and power consumption information of all smart meters;

[0048] A load level determination module is used to identify the load level of each smart meter location based on the power consumption and power consumption time in the power consumption information;

[0049] A sub-area division module is used to cluster the target area into multiple sub-areas according to the load level corresponding to each smart meter;

[0050] A first power supply relationship determination module is configured to determine a first power supply relationship between the power supply guarantee equipment and the sub-area based on a preset strategy according to the location information of the sub-area, the location information of the power supply guarantee equipment, the working status of the power supply guarantee equipment, and the power consumption information of all smart meters;

[0051] The preset strategy includes: obtaining the time period in which the power consumption fluctuation of any sub-area exceeds the threshold, checking the number of power supply guarantee equipment that meets the preset conditions, and the preset conditions include that the power supply guarantee equipment is started within the time period, and after the power supply guarantee equipment is started, the power consumption of the sub-area is stabilized or restored; if the number of power supply guarantee equipment that meets the preset conditions is 0, then the sub-area is marked as having no power supply guarantee equipment; if the number of power supply guarantee equipment that meets the preset conditions is 1, then the power supply guarantee equipment is deemed to be supplying power to the sub-area;

[0052] If there are multiple power supply guarantee devices that meet the preset conditions, the number of target sub-areas whose power consumption fluctuations exceed the threshold within the time period is detected; when the detection result is 0, it is determined that multiple power supply guarantee devices are all supplying power to the target sub-area; when the detection result is greater than 1, the distance between each target sub-area and the activated power supply guarantee device is calculated, and it is determined that the target sub-area has a power supply relationship with the power supply guarantee devices whose distance is less than the preset distance;

[0053] A connection relationship determination module is used to obtain the location information of the mains power line and the second power supply relationship with each sub-area based on the power supply network diagram; and establish the connection relationship between the sub-area, the mains power and the power supply guarantee equipment based on the first power supply relationship and the second power supply relationship;

[0054] The model generation module is used to superimpose the connection relationship, the location information of the power supply equipment, the sub-area location information and the location information of the mains power line on the map information of the target area to generate a target model.

[0055] In a third aspect, the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps corresponding to the method in the first aspect are implemented.

[0056] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps corresponding to the method in the first aspect.

[0057] In summary, the technical solutions of the embodiments of the present application have at least the following advantages and beneficial effects:

[0058] The present invention establishes a comprehensive basic data set by collecting map information, power supply network diagrams, and location and equipment information for smart meters and power supply maintenance equipment within the target area. Next, the load level at each smart meter's location is accurately identified using the smart meter's power consumption and usage time, combined with preset load level determination criteria. Spatial clustering is then performed based on load levels, using the K-means clustering algorithm to divide the target area into multiple sub-areas with similar power consumption characteristics. Based on this, a pre-set strategy is used to determine the primary power supply relationship between the power supply maintenance equipment and the sub-areas, using the sub-area location information, the operating status of the power supply maintenance equipment, and power consumption information. The power supply network diagram is used to obtain the location information of the mains power lines and their secondary power supply relationship with each sub-area. Finally, these connection relationships, the location of the power supply maintenance equipment, the location of the sub-areas, and the location of the mains power lines are superimposed on the map information of the target area to generate a target model. This automatically captures the relationships and connections between multiple levels of power supply maintenance equipment and the mains power within the target area. Furthermore, by integrating multi-source data and displaying it on the map, a detailed description of power supply management in the target area is achieved, providing accurate decision support for power managers. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart of a modeling method for multi-level power supply equipment and mains power provided by the present invention;

[0060] Figure 2 Schematic diagram of the target model in the present invention.

[0061] Figure 3 This is a structural diagram of a multi-level power supply equipment and mains power modeling system provided by the present invention. DETAILED DESCRIPTION

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Generally, the components of the embodiments of the present application described and shown in the drawings herein can be arranged and designed in various different configurations.

[0063] The present application provides a modeling method for multi-level power supply equipment and mains power, including:

[0064] S101, obtaining map information and a power supply network diagram of a target area, obtaining location information and device information of power supply guarantee equipment in the target area, and location information and power consumption information of all smart meters.

[0065] Specifically, the target area's map provides a geographic reference framework; the power grid diagram reveals the layout and connections of utility lines; the location and equipment information for power supply equipment illustrates their distribution and technical specifications; and the location and power consumption information for smart meters details power consumption at each point in the area. Together, this information forms the foundational data set for modeling, providing essential input for subsequent steps.

[0066] S102: Identify the load level at the location of each smart meter based on the power consumption and power consumption time in the power consumption information.

[0067] Among them, this step aims to accurately identify the load level of each smart meter's location. Its core is to determine the power supply level of the area represented by each smart meter by analyzing the smart meter's power consumption information and power consumption time, combined with the preset load level judgment criteria. Specifically, first, the system will continuously monitor the power consumption data of each smart meter, including the absolute value of power consumption and its fluctuations over a certain period of time. These data provide the basis for the preliminary judgment of the load level. Then, the system will interpret and classify this data according to a series of detailed rules and standards. The rules are as follows:

[0068] Public service areas such as hospitals and fire departments, which require 24-hour maintenance, have stable and continuous electricity demand, no obvious lows, and minimal fluctuations in electricity consumption within a 24-hour period. Therefore, when any smart meter's electricity consumption fluctuations consistently remain below a threshold, they are identified as a Level 1 power supply area. Commercial and industrial areas, on the other hand, have concentrated peak electricity consumption periods, high electricity consumption, and large fluctuations in electricity consumption due to varying production schedules. Therefore, when any smart meter's electricity consumption exceeds a preset value, and the fluctuation exceeds a threshold, they are identified as a Level 2 power supply area. Residential areas, on the other hand, have distinct morning and evening peaks in electricity consumption. Therefore, when smart meter electricity consumption is detected to be within a preset range, with peaks in both the morning and evening hours, they are identified as a Level 3 power supply area.

[0069] S103: Clustering is performed according to the load level corresponding to each smart meter, and the target area is divided into multiple sub-areas.

[0070] Specifically, a preliminary classification is performed based on the load level corresponding to each smart meter. This step divides all smart meters in the target area into three categories based on their load level (level 1, level 2, level 3, etc.). Each category represents a specific load level range. This classification provides the basis for subsequent spatial clustering, ensuring that the clustering process primarily considers the similarity of load levels.

[0071] The spatial distance between each smart meter and other smart meters within its load level is then calculated. This step aims to quantify the spatial proximity of smart meters. By calculating the distance between each pair of smart meters, a distance matrix is constructed. This matrix clearly shows the spatial relationships between smart meters and provides the necessary data input for the subsequent clustering algorithm.

[0072] The distance matrix is then clustered using the K-means clustering algorithm. K-means clustering is a commonly used unsupervised learning algorithm that can divide data points into K clusters based on their similarity, even without predefined class labels. In this step, the algorithm automatically groups smart meters into clusters based on their spatial distances. The smart meters within each cluster are relatively close in space and, because they fall within the same load level range, their electricity usage characteristics also share a certain degree of similarity.

[0073] Finally, based on the clustering results, smart meters that are spatially close and have similar load levels are grouped into a sub-region. This step interprets and applies the clustering results, ensuring that the smart meters within each sub-region are not only geographically close but also relatively consistent in their power usage characteristics (i.e., load levels). This sub-regional division facilitates subsequent modeling and analysis of power supply equipment and utility power, enabling the model to more accurately reflect the power demand and power supply characteristics of different areas within the target region.

[0074] Among them, the expression of the sub-region division result is:

[0075]

[0076] Among them, C is the division result, that is, the set containing the smart meter index; k is the number of sub-areas; C i is the set of all smart meters in the ith sub-area; x is the location information of the smart meter, which is a 2-dimensional real vector; μ i is the centroid of the ith subregion, ||x-μ i || 2 is the centroid μ from smart meter x to sub-area i i The square of the Euclidean distance.

[0077] S104 , determining a first power supply relationship between the power supply equipment and the sub-area based on a preset strategy according to the location information of the sub-area, the location information of the power supply equipment, the working status of the power supply equipment, and the power consumption information of all smart meters.

[0078] Specifically, this step ensures a precise understanding of the role and impact of power supply maintenance equipment within the actual power supply network. First, the preset strategy obtains the time periods during which power consumption fluctuations in any sub-region exceed a threshold. This is done to identify sub-regions experiencing power supply instability during specific time periods. These fluctuations may be due to insufficient utility power supply or other external factors.

[0079] Then, check the number of power supply equipment that meets the preset conditions within these time periods. The preset conditions include that the power supply equipment is started within the time period, and after the power supply equipment is started, the power consumption of the sub-area is stabilized or restored. The purpose of this step is to verify whether the power supply equipment has indeed played a stabilizing role in the power supply of the sub-area. If a power supply equipment is started and the power consumption is stabilized or restored in a sub-area during a time period when the power consumption fluctuation exceeds the threshold, it is considered that the power supply equipment has supplied power to the sub-area. Specifically, the following implementation method can be adopted: real-time monitoring of the working status changes of each power supply equipment and recording the startup time; synchronous analysis of the power consumption data of each sub-area in the corresponding time period to identify the sub-area whose power consumption meets the preset change range; application of time series analysis method to compare the degree of consistency between the startup time of the power supply equipment and the time point of the sub-area power consumption change, and statistically counting the number of power supply equipment whose consistency meets the preset consistency range.

[0080] After obtaining the number of power supply equipment that meets specific preset conditions, this data becomes an important basis for analyzing power supply relationships. Specifically, if the number of power supply equipment that meets the conditions is 0, this directly indicates that when the power consumption in the sub-area fluctuates, no power supply equipment is activated. This situation reflects that the sub-area is not equipped with power supply equipment, so the system will mark the sub-area as having no power supply equipment. If the number of power supply equipment that meets the conditions is 1, it means that when the power consumption in the sub-area fluctuates, only one power supply equipment is started. This is sufficient to determine that the single power supply equipment is responsible for providing power guarantee for the sub-area.

[0081] If there are multiple power supply equipment that meet the preset conditions, it means that when power consumption fluctuates in the sub-area, multiple power supply equipment are started at the same time. This situation indicates that multiple power supply equipment may be supplying power to one sub-area, or multiple sub-areas may experience power consumption fluctuations at the same time in the time period, resulting in multiple power supply equipment being started at the same time. Therefore, in this case, this embodiment first detects the number of target sub-areas whose power consumption fluctuations exceed the threshold within the time period; when the detection result is 0, it means that multiple power supply equipment are supplying power to one sub-area, that is, it is determined that multiple power supply equipment are all supplying power to the target sub-area; when the detection result is greater than 1, the distance between each target sub-area and the started power supply equipment is calculated using the feature that most power supply equipment are located near the area, and it is determined that the target sub-area has a power supply relationship with the power supply equipment whose distance is less than the preset distance.

[0082] However, if multiple power supply devices meet the requirements, this means that when power consumption in a sub-area fluctuates, multiple power supply devices are activated simultaneously. This situation can be caused by two factors: first, multiple power supply devices jointly provide power to a sub-area to cope with large fluctuations in power demand; second, multiple different sub-areas experience power consumption fluctuations during the same time period, causing their corresponding power supply devices to be activated. To accurately distinguish between these two situations, this embodiment detects the number of target sub-areas whose power consumption fluctuations exceed a preset threshold within a specific time period. If the detection result is 0, meaning no other sub-areas with power consumption fluctuations are detected, it can be inferred that multiple power supply devices are jointly providing power support to a sub-area. If the detection result is greater than 1, meaning that multiple sub-areas experience power consumption fluctuations simultaneously, further analysis is required, leveraging the characteristic that power supply devices are typically located near their respective power supply areas. The system calculates the actual distance between each target sub-area and an activated power supply device and compares this distance with a preset distance threshold. Only when the distance between a target sub-area and a power supply device is less than the preset distance is it determined that a direct power supply relationship exists between the target sub-area and the power supply device.

[0083] S105: Obtain the location information of the mains power line and the second power supply relationship with each sub-area based on the power supply network map; and establish a connection relationship between the sub-area, the mains power supply, and the power supply guarantee equipment based on the first power supply relationship and the second power supply relationship. The power supply network map includes the geographic direction of the mains power line, its branches and intersections, and their relative positional relationships with each sub-area.

[0084] S106 , superimposing the connection relationship, the location information of the power supply equipment, the sub-area location information, and the location information of the mains power line onto the map information of the target area to generate a target model.

[0085] Specifically, after completing the division of sub-areas, determining the primary power supply relationship between power supply equipment and sub-areas, and determining the secondary power supply relationship between mains power and sub-areas, these key information are integrated into a framework based on map information to facilitate subsequent analysis, management, and decision support. During the integration process, the system marks the location information of each sub-area on the map with a specific graphic or color, such as Figure 2 The part surrounded by the dotted line can intuitively reflect the spatial distribution and scope of the sub-area. Then, the location information of the power supply equipment will be superimposed on the map, and the power supply equipment will be represented by a solid circle symbol, such as Figure 2 a in the figure; the hollow circle symbol represents a smart meter, such as Figure 2The relative position relationship between these icons and sub-area marks directly reflects the physical distance and potential power supply connection between the power supply equipment and the sub-area. At the same time, the location information of the mains power line will also be accurately drawn on the map, such as Figure 2 The c in the figure includes key elements such as the direction, branches, and intersections of the lines. This information is combined with the markings of the sub-areas and power supply equipment to form a complete power supply network diagram. In this network diagram, the mains power line, as the main source of electricity, forms a direct power supply relationship with the sub-areas, which is marked by connecting lines. The power supply equipment, as a supplement to electricity, is clearly marked on the map with arrows. In addition, the system will add corresponding arrow annotations to the map based on the first power supply relationship and the second power supply relationship determined in the previous step to show the power supply status of the multi-level power supply equipment.

[0086] Furthermore, after generating the target model, a power supply capacity assessment and early warning mechanism for power supply equipment was introduced to ensure the stability and reliability of the power supply network. Specifically, it includes:

[0087] The system retrieves the corresponding device information for power supply equipment from a pre-set database and calculates the maximum output power of each device. This database typically contains the technical parameters of each type of power supply equipment, including but not limited to key data such as rated power, maximum output power, and operating efficiency. By retrieving these parameters, the system accurately identifies the performance characteristics of each device, providing precise data support for subsequent analysis. Based on the device information retrieved from the database, the system then uses a power calculation formula to calculate the maximum output power of each device under ideal conditions.

[0088] The maximum power load of each sub-region within a preset time period is calculated; that is, the maximum power load of each sub-region within a specific time period (such as peak hours, extreme weather conditions, etc.) is calculated. This data can be obtained by analyzing the power consumption information of smart meters, combining historical data and prediction models, to ensure the accuracy and reliability of the assessment results.

[0089] The maximum output power of each power supply device is compared with the maximum load of the sub-area it serves. If the maximum output power of the power supply device is greater than or equal to the maximum load of the sub-area it serves, the device's power supply capacity is determined to be sufficient to cover the sub-area's electricity needs. If the maximum output power of the power supply device is less than the maximum load of the sub-area it serves, the device's power supply capacity is determined to be insufficient to cover the sub-area's electricity needs, and an early warning message is generated. This warning message prompts relevant personnel to take timely measures, such as adding power supply devices and optimizing the power supply network layout, to ensure the stability and reliability of the power supply network. The generation of early warning information not only helps prevent potential power supply risks in advance but also provides important evidence for subsequent emergency response and decision support.

[0090] Furthermore, after the target model is generated, the generated target model is dynamically updated to ensure that the model can reflect the actual status of the power supply network in the target area in real time. The dynamic update includes:

[0091] Real-time monitoring of changes in the working status of power supply equipment in the target area, changes in power consumption of smart meters, and power supply status of mains power lines.

[0092] Based on the monitoring results, the location and operating status of power supply equipment, smart meter power consumption information, and the location and power supply status of utility lines are updated. Using data communication and processing technologies, real-time monitoring data is uploaded to the processing system and compared and replaced with the existing data in the model. This ensures that the data in the model is up-to-date and accurate, reflecting the latest status of the power supply network.

[0093] Based on the updated information, the primary power supply relationship between the power supply guarantee equipment and the sub-area, as well as the secondary power supply relationship between the mains and the sub-area, is re-evaluated. Specifically, because the power supply network's status is dynamically changing, the activation of the power supply guarantee equipment and the power supply status of the mains line may affect the determination of the power supply relationship. Therefore, by re-analyzing the updated data, the current power supply relationship in the power supply network can be accurately determined, providing an accurate basis for subsequent decision support.

[0094] Based on the reassessment results, the connectivity relationships between sub-regions, utility power, and power supply equipment are updated. Specifically, connectivity is a core element of the model, reflecting the relationships and interactions between various elements in the power supply network. By updating connectivity, the model's power supply network structure is consistent with reality, supporting more accurate power supply network analysis and decision-making.

[0095] The updated connection relationship, location information of power supply equipment, sub-area location information, and location information of mains power lines are superimposed on the map information of the target area to generate an updated target model.

[0096] Based on the same inventive concept, the present invention provides a modeling system for multi-level power supply equipment and mains power, including:

[0097] The data acquisition module is used to obtain map information and power supply network diagrams of the target area, the location information of power supply equipment in the target area, the equipment information of power supply equipment, and the location information and power consumption information of all smart meters;

[0098] A load level determination module is used to identify the load level of each smart meter location based on the power consumption and power consumption time in the power consumption information;

[0099] A sub-area division module is used to cluster the target area into multiple sub-areas according to the load level corresponding to each smart meter;

[0100] A first power supply relationship determination module is configured to determine a first power supply relationship between the power supply guarantee equipment and the sub-area based on a preset strategy according to the location information of the sub-area, the location information of the power supply guarantee equipment, the working status of the power supply guarantee equipment, and the power consumption information of all smart meters;

[0101] The preset strategy includes: obtaining the time period in which the power consumption fluctuation of any sub-area exceeds the threshold, checking the number of power supply guarantee equipment that meets the preset conditions, and the preset conditions include that the power supply guarantee equipment is started within the time period, and after the power supply guarantee equipment is started, the power consumption of the sub-area is stabilized or restored; if the number of power supply guarantee equipment that meets the preset conditions is 0, then the sub-area is marked as having no power supply guarantee equipment; if the number of power supply guarantee equipment that meets the preset conditions is 1, then the power supply guarantee equipment is deemed to be supplying power to the sub-area;

[0102] If there are multiple power supply guarantee devices that meet the preset conditions, the number of target sub-areas whose power consumption fluctuations exceed the threshold within the time period is detected; when the detection result is 0, it is determined that multiple power supply guarantee devices are all supplying power to the target sub-area; when the detection result is greater than 1, the distance between each target sub-area and the activated power supply guarantee device is calculated, and it is determined that the target sub-area has a power supply relationship with the power supply guarantee devices whose distance is less than the preset distance;

[0103] A connection relationship determination module is used to obtain the location information of the mains power line and the second power supply relationship with each sub-area based on the power supply network diagram; and establish the connection relationship between the sub-area, the mains power and the power supply guarantee equipment based on the first power supply relationship and the second power supply relationship;

[0104] The model generation module is used to superimpose the connection relationship, the location information of the power supply equipment, the sub-area location information and the location information of the mains power line on the map information of the target area to generate a target model.

[0105] Based on the same inventive concept, the present invention provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein a method for modeling multi-level power supply equipment and city power is provided when the processor executes the computer program.

[0106] Based on the same inventive concept, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a modeling method for multi-level power supply equipment and mains power.

[0107] The above are merely preferred embodiments of the present application and are not intended to limit the present application. Those skilled in the art will readily appreciate that various modifications and variations are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A modeling method for multi-level power supply equipment and mains power, characterized in that: include: S101, obtaining map information and a power supply network diagram of a target area, obtaining location information and device information of power supply guarantee equipment in the target area, and location information and power consumption information of all smart meters; S102, identifying the load level at the location of each smart meter based on the power consumption and power consumption time in the power consumption information; S103, clustering according to the load level corresponding to each of the smart meters, and dividing the target area into multiple sub-areas; S104, determining a first power supply relationship between the power supply guarantee equipment and the sub-area based on a preset strategy according to the location information of the sub-area, the location information of the power supply guarantee equipment, the working status of the power supply guarantee equipment, and the power consumption information of all smart meters; The preset strategy includes: obtaining a time period in which the power consumption fluctuation of any sub-area exceeds a threshold, checking the number of power supply guarantee equipment that meets the preset conditions, wherein the preset conditions include that the power supply guarantee equipment is started within the time period, and after the power supply guarantee equipment is started, the power consumption of the sub-area is stabilized or restored; if the number of power supply guarantee equipment that meets the preset conditions is 0, marking the sub-area as having no power supply guarantee equipment; if the number of power supply guarantee equipment that meets the preset conditions is 1, determining that the power supply guarantee equipment is supplying power to the sub-area; If there are multiple power supply guarantee equipment that meet the preset conditions, the number of target sub-areas whose power consumption fluctuations exceed the threshold within the time period is detected; when the detection result is 0, it is determined that multiple power supply guarantee equipment are all supplying power to the target sub-area; when the detection result is greater than 1, the distance between each target sub-area and the activated power supply guarantee equipment is calculated, and it is determined that the target sub-area has a power supply relationship with the power supply guarantee equipment whose distance is less than the preset distance; S105: Obtain location information of the mains power line and a second power supply relationship with each sub-area based on the power supply network diagram; establish a connection relationship between the sub-area, the mains power, and the power supply guarantee equipment based on the first power supply relationship and the second power supply relationship; S106 , superimposing the connection relationship, the location information of the power supply equipment, the sub-area location information, and the location information of the mains power line onto the map information of the target area to generate a target model.

2. A modeling method for multi-level power supply equipment and mains power according to claim 1, characterized in that: The step of identifying the load level at the location of each smart meter specifically includes: If the power consumption fluctuation of any smart meter is detected to remain below the threshold, it is identified as a first-level power supply area; If it is detected that the power consumption of any smart meter exceeds the preset power consumption, and the power consumption fluctuation exceeds the threshold, it is identified as a secondary power supply area; If the smart meter's electricity consumption is detected to be within the preset range and contains peak electricity consumption in both the morning and evening time periods, it will be identified as a Level 3 power supply area.

3. A modeling method for multi-level power supply equipment and mains power according to claim 1, characterized in that: The step of dividing the target area into a plurality of sub-areas specifically includes: Each smart meter is divided into several categories according to the load level, and each category represents a load level range; Calculate the spatial distance between each smart meter and other smart meters within the load level to which it belongs to form a distance matrix; Clustering the distance matrix using a K-means clustering algorithm; Based on the clustering results, smart meters that are spatially close and have similar load levels are grouped into a sub-region to ensure that the smart meters in each sub-region are relatively consistent in terms of geographical location and electricity consumption characteristics. Output the sub-region division results after clustering.

4. A modeling method for multi-level power supply equipment and mains power according to claim 3, characterized in that: The expression of the sub-region division result is: Among them, C is the division result, that is, the set containing the smart meter index; k is the number of sub-areas; C i is the set of all smart meters in the ith sub-area; x is the location information of the smart meter, which is a 2-dimensional real vector; μ i is the centroid of the ith subregion, ||x-μ i || 2 is the centroid μ from smart meter x to sub-area i i The square of the Euclidean distance.

5. The modeling method of multi-level power supply equipment and mains power according to claim 1, characterized in that: The step of checking the number of power supply guarantee equipment that meets the preset conditions specifically includes: Monitor the working status changes of each power supply equipment in real time and record the startup time; Synchronously analyze the electricity consumption data of each sub-area within the corresponding time period and identify the sub-areas whose electricity consumption meets the preset variation range; The time series analysis method is applied to compare the consistency between the start-up time of the power supply equipment and the time points of the changes in power consumption in the sub-regions, and the number of power supply equipment whose consistency meets the preset consistency range is counted.

6. A modeling method for multi-level power supply equipment and mains power according to claim 1, characterized in that: After generating the target model, the method further includes: Obtain the device information corresponding to the power supply equipment from the preset database and calculate the maximum output power of each power supply equipment; Count the maximum power load of each sub-area within a preset time period; Compare the maximum output power of each power supply equipment with the maximum power load of the sub-area it supplies power. If the maximum output power of the power supply equipment is greater than or equal to the maximum power load of the sub-area it supplies power, then it is determined that the power supply capacity of the power supply equipment is sufficient to cover the power demand of the sub-area; if the maximum output power of the power supply equipment is less than the maximum power load of the sub-area it supplies power, then it is determined that the power supply capacity of the power supply equipment is insufficient to cover the power demand of the sub-area, and an early warning message is generated.

7. The modeling method of multi-level power supply equipment and mains power according to claim 1, characterized in that: After the target model is generated, the method further includes dynamically updating the generated target model; The dynamic update includes: Real-time monitoring of changes in the working status of power supply equipment in the target area, changes in the power consumption of smart meters, and the power supply status of the mains lines; Based on the monitoring results, update the location information, working status of the power supply equipment, the power consumption information of the smart meter, and the location information and power supply status of the mains power line; Based on the updated information, re-determine the first power supply relationship between the power supply equipment and the sub-area and the second power supply relationship between the mains and the sub-area; Based on the re-judgment results, the connection relationship between the sub-area, the mains power supply, and the power supply equipment is updated; The updated connection relationship, location information of the power supply equipment, sub-area location information, and location information of the mains power line are superimposed on the map information of the target area to generate an updated target model.

8. A modeling system for multi-level power supply equipment and mains power, characterized by: include: A data acquisition module is used to obtain map information and a power supply network diagram of a target area, and obtain location information and equipment information of power supply guarantee equipment in the target area, as well as location information and power consumption information of all smart meters; a load level determination module, configured to identify the load level at the location of each smart meter based on the power consumption and power consumption time in the power consumption information; a sub-area division module, configured to perform clustering according to the load level corresponding to each of the smart meters, and divide the target area into a plurality of sub-areas; A first power supply relationship determination module is configured to determine a first power supply relationship between the power supply guarantee equipment and the sub-area based on a preset strategy according to the location information of the sub-area, the location information of the power supply guarantee equipment, the working status of the power supply guarantee equipment, and the power consumption information of all smart meters; The preset strategy includes: obtaining a time period in which the power consumption fluctuation of any sub-area exceeds a threshold, checking the number of power supply guarantee equipment that meets the preset conditions, wherein the preset conditions include that the power supply guarantee equipment is started within the time period, and after the power supply guarantee equipment is started, the power consumption of the sub-area is stabilized or restored; if the number of power supply guarantee equipment that meets the preset conditions is 0, marking the sub-area as having no power supply guarantee equipment; if the number of power supply guarantee equipment that meets the preset conditions is 1, determining that the power supply guarantee equipment is supplying power to the sub-area; If there are multiple power supply guarantee equipment that meet the preset conditions, the number of target sub-areas whose power consumption fluctuations exceed the threshold within the time period is detected; when the detection result is 0, it is determined that multiple power supply guarantee equipment are all supplying power to the target sub-area; when the detection result is greater than 1, the distance between each target sub-area and the activated power supply guarantee equipment is calculated, and it is determined that the target sub-area has a power supply relationship with the power supply guarantee equipment whose distance is less than the preset distance; The connection relationship determination module is used to obtain the location information of the mains power line and the connection relationship between each sub-area according to the power supply network diagram. Second power supply relationship; establishing a connection relationship between the sub-area, the mains power and the power supply equipment according to the first power supply relationship and the second power supply relationship; The model generation module is used to superimpose the connection relationship, the location information of the power supply equipment, the sub-area location information and the location information of the mains power line on the map information of the target area to generate a target model.

9. An electronic device, characterized in that: The electronic device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps corresponding to the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps corresponding to the method according to any one of claims 1 to 7 are implemented.

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