A distribution network reliability evaluation method

Abstract

The present invention discloses a method for evaluating the reliability of a distribution network. The present invention relates to the technical field of distribution networks. The first-level reliability parameters of the distribution network are determined based on the power levels of multiple power load nodes, the power losses of multiple power load nodes, and the power supply of multiple power load nodes, thereby ensuring the accuracy of the first-level reliability parameters of the distribution network. The corresponding power equipment is determined based on the positioning traversal of multiple power load nodes, and the second-level reliability parameters of the distribution network are determined based on the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss. Therefore, the surrounding environmental parameters of the distribution network are determined based on the environmental detection of the locations of multiple power load nodes, and the reliability level of the distribution network is comprehensively evaluated based on the surrounding environmental parameters of the distribution network, the first-level reliability parameters, and the second-level reliability parameters, thereby improving the accuracy of the reliability level of the distribution network.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution networks, and in particular to a distribution network reliability evaluation method. Background Art

[0002] With the development of science and technology, distribution networks are gradually applied to people's lives. As part of power supply facilities, distribution networks need to be used for a long time, and the reliability of distribution networks needs to be evaluated accordingly. In the existing technology, the distribution network is detected and the reliability of the distribution network is evaluated based on the power loss of the distribution network. The reliability evaluation of the distribution network is performed under a single dimension, which cannot guarantee the comprehensive evaluation of the reliability level of the power grid and affects the accuracy of the reliability level of the distribution network. Summary of the Invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art, and the present invention provides a method for evaluating the reliability of a distribution network.

[0004] An embodiment of the present invention provides a distribution network reliability evaluation method, comprising: determining a distribution network based on multiple distribution areas and line routing paths; determining multiple power load nodes based on the relative positions of the distribution network, multiple distribution areas, and the power supply of the multiple distribution areas; determining the power levels of the multiple power load nodes based on the locations of the multiple power load nodes, the distribution priorities of the multiple distribution areas, and the current time; determining the first-level reliability parameters of the distribution network based on the power levels of the multiple power load nodes, the power losses of the multiple power load nodes, and the power supply of the multiple power load nodes; determining the corresponding power equipment based on the positioning traversal of the multiple power load nodes, and determining the second-level reliability parameters of the distribution network based on the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss; determining the surrounding environmental parameters of the distribution network based on environmental detection of the locations of the multiple power load nodes, and comprehensively evaluating the reliability level of the distribution network based on the surrounding environmental parameters of the distribution network, the first-level reliability parameters, and the second-level reliability parameters.

[0005] In an embodiment of the present invention, through the method in the embodiment of the present invention, a distribution network is determined according to multiple distribution areas and line routing paths; multiple power load nodes are determined according to the relative positions of the distribution network and multiple distribution areas and the power supply of multiple distribution areas; the power levels of multiple power load nodes are determined based on the locations of multiple power load nodes, the distribution priorities of multiple distribution areas and the current time; the first-level reliability parameters of the distribution network are determined according to the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supply of multiple power load nodes, which is compatible with the overall consideration of the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supply of multiple power load nodes, ensures the accuracy of the first-level reliability parameters of the distribution network, and realizes the preliminary control of the distribution network at the power level.

[0006] Furthermore, the corresponding power equipment is determined based on the positioning traversal of multiple power load nodes, and the second-level reliability parameters of the distribution network are determined based on the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss, thereby realizing the overall control of the distribution network at the power equipment level and ensuring the accuracy of the second-level reliability parameters of the distribution network.

[0007] Therefore, the peripheral environmental parameters of the distribution network are determined based on the environmental detection of the locations of multiple power load nodes, and the reliability level of the distribution network is comprehensively evaluated based on the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network. This is compatible with the overall consideration of the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, and realizes multi-dimensional control of the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, ensuring the comprehensive evaluation of the reliability level of the power grid and improving the accuracy of the reliability level of the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 Schematic diagram of an application scenario of a distribution network reliability evaluation method in an embodiment.

[0009] Figure 2 4 is a flow chart of a distribution network reliability evaluation method in an embodiment of the present invention.

[0010] Figure 3 Schematic diagram of the structure of the distribution network reliability evaluation system in an embodiment of the present invention.

[0011] Figure 4 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0012] The technical solutions in the embodiments of the present invention will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present invention.

[0013] Example 1: The distribution network reliability evaluation method provided by this application can be applied to Figure 1 In the application environment shown, the computer 102 communicates with the server 104 via a network. The terminal 102 can be, but is not limited to, various personal computers, servers, and power distribution networks, and the server 104 can be implemented as an independent server or a server cluster consisting of multiple servers.

[0014] Example 2: Please refer to Figures 1 to 4 A distribution network reliability evaluation method is applied to a distribution network reliability evaluation scenario. The distribution network reliability evaluation method includes:

[0015] Step S11: determining a distribution network based on multiple distribution areas and line routing paths;

[0016] Step S12: determining a plurality of power load nodes according to the relative positions of the power distribution network and the plurality of power distribution areas and the power supply of the plurality of power distribution areas;

[0017] Step S13: determining the power levels of the plurality of power load nodes based on the locations of the plurality of power load nodes, the power distribution priorities of the plurality of power distribution areas, and the current time;

[0018] Step S14: determining a first-level reliability parameter of the distribution network according to the power levels of the plurality of power load nodes, the power losses of the plurality of power load nodes, and the power supplies of the plurality of power load nodes;

[0019] Step S15: determining corresponding power equipment according to the location traversal of multiple power load nodes, and determining the second-level reliability parameter of the distribution network according to the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss;

[0020] Step S16: determining the peripheral environmental parameters of the distribution network based on the environmental detection of the locations of multiple power load nodes, and comprehensively evaluating the reliability level of the distribution network based on the peripheral environmental parameters of the distribution network, the first-level reliability parameters, and the second-level reliability parameters.

[0021] In step S11, a distribution network is determined based on multiple distribution areas and line routing paths;

[0022] In the specific implementation process of the present invention, the specific steps are:

[0023] S111: Collect power supply distribution map;

[0024] S112: Determine multiple power distribution areas based on the detection of the power supply distribution map;

[0025] S113: Locating locations of multiple power distribution areas;

[0026] S114: Determine a line routing path based on the locations of the multiple power distribution areas and the line distribution map;

[0027] S115: Detect multiple power distribution areas and line routing paths, and determine a power distribution network based on the multiple power distribution areas and line routing paths.

[0028] In an embodiment of the present application, a power supply distribution map is collected; and multiple power distribution areas are determined based on the detection of the power supply distribution map, so as to introduce multiple power distribution areas and perform subsequent management and control of the multiple power distribution areas.

[0029] Specifically, power distribution Figure 1 It is generally stored in the power company database, and the power company database is traversed to collect the power supply distribution map and further control the power supply distribution map.

[0030] At the same time, a power supply distribution map is introduced and the power supply distribution map is detected, so that multiple distribution areas are determined based on the detection of the power supply distribution map. At this time, the power supply distribution map is divided and multiple distribution areas are output to facilitate more refined distribution network planning and management.

[0031] The principles for division include load density, geographical conditions, and administrative divisions. Distribution areas are divided based on load density. High-load-density areas may require more power facilities and higher power reliability, taking into account the impact of terrain, landforms, rivers, roads, and other geographical conditions on the distribution network layout. For example, mountainous areas may require more line corridors, while urban areas may require the laying of underground cables. In some cases, the division of distribution areas may also require consideration of administrative boundaries to coordinate with local government planning and policies.

[0032] Specifically, after obtaining the power supply distribution map for the new district, the division of distribution zones was initiated. First, the new district was divided into three main distribution zones based on load density: a high-load density zone (primarily commercial and industrial areas), a medium-load density zone (primarily residential areas), and a low-load density zone (primarily agricultural land and undeveloped areas). Then, the boundaries of the distribution zones were fine-tuned to account for geographical factors. For example, the width of the line corridors in mountainous areas was increased to ensure the reliability and safety of power facilities. Finally, communication was conducted with the urban planning department to ensure that the division of distribution zones was consistent with local administrative divisions and policies.

[0033] Furthermore, the locations of multiple distribution areas are located; the line routing paths are determined based on the locations of multiple distribution areas and the line distribution map, which is compatible with the overall consideration of the locations of multiple distribution areas and the line distribution map, realizes the multi-dimensional control of the locations of multiple distribution areas and the line distribution map, and ensures the accuracy of the line routing paths.

[0034] Specifically, multiple power distribution areas are introduced, and position control is performed on the multiple power distribution areas, so as to locate the locations of the multiple power distribution areas and derive the locations of the multiple power distribution areas.

[0035] At this time, the line routing path is determined based on the locations of multiple distribution areas and line distribution maps. The locations of multiple distribution areas and line distribution maps are introduced, and the locations of multiple distribution areas and line distribution maps are interacted to ensure the accuracy of the line routing path and ensure the stability and reliability of the power supply.

[0036] Specifically, after determining the specific locations of the three distribution areas, the line routing was planned. First, using the GIS system, a preliminary plan of the paths connecting the various distribution areas was made on the map. Taking into account the topography and urban planning of the new district, a combination of overhead lines and underground cables was chosen. Then, a field survey was conducted to verify the feasibility and safety of the line. During the survey, it was discovered that a certain section of the line path needed to pass through a wetland, posing a safety hazard. Therefore, the path was optimized and adjusted to bypass the wetland area, and a safer and more reliable path was selected. Ultimately, the optimal path for the power line was determined as the line routing path.

[0037] Therefore, multiple distribution areas and line routing paths are detected, and the distribution network is determined based on the multiple distribution areas and line routing paths, thereby achieving further control of the multiple distribution areas and line routing paths and ensuring the combination of the multiple distribution areas and line routing paths, so as to ensure the accuracy of the distribution network.

[0038] At this time, the detection of multiple distribution areas and the detection of line routing paths were introduced, and comprehensive management and control of multiple distribution areas and line routing paths were carried out to ensure the interaction of multiple distribution areas and line routing paths. The detection results were determined based on the interaction of multiple distribution areas and line routing paths. Combined with the detection results of distribution areas and line paths, a comprehensive analysis was carried out to determine the optimal distribution network. The distribution network simulation software was used to simulate the distribution network to verify its operating performance and reliability.

[0039] Specifically, after completing the detection of the distribution area and line path, the work of determining the distribution network began. Based on the detection results, the following distribution network structure and equipment configuration were determined:

[0040] Distribution network structure: A hierarchical and partitioned distribution network structure is adopted, which manages high-voltage, medium-voltage and low-voltage networks separately, improving the reliability and flexibility of the distribution network.

[0041] Equipment Configuration: The number and location of substations, switchyards, and distribution transformers are rationally arranged based on load density and geographical conditions. Equipment redundancy and backup are also considered to improve the reliability of the distribution network.

[0042] Line specifications: The conductor model and cross-sectional area are determined based on the line's load current and voltage loss. The mechanical strength and weather resistance of the line are also considered to ensure safe operation.

[0043] In step S12, a plurality of power load nodes are determined according to the relative positions of the power distribution network and the plurality of power distribution areas and the power supply of the plurality of power distribution areas;

[0044] In the specific implementation process of the present invention, the specific steps are:

[0045] S121: Performing positioning detection on multiple power distribution areas;

[0046] S122: Determine relative positions of the plurality of power distribution areas based on positioning detection of the plurality of power distribution areas;

[0047] S123: Determine the power supply amount of the plurality of power distribution areas based on the power detection of the plurality of power distribution areas;

[0048] S124: Associating the distribution network, relative locations of multiple distribution areas, and power supply amounts of the multiple distribution areas;

[0049] S125: performing multiple interactions on the distribution network, relative positions of multiple distribution areas, and power supply amounts of the multiple distribution areas;

[0050] S126: Determine multiple power load nodes based on the distribution network, the relative positions of the multiple distribution areas, and the multiple interactions of the power supply amounts of the multiple distribution areas, where the multiple power load nodes are present at different positions of the distribution network.

[0051] In an embodiment of the present application, positioning detection is performed on multiple distribution areas; based on the positioning detection of multiple distribution areas, the relative positions of multiple distribution areas are determined, thereby realizing positioning detection of multiple distribution areas, ensuring the accuracy of the relative positions of multiple distribution areas, and performing subsequent management and control of multiple distribution areas.

[0052] Among them, positioning detection is carried out on multiple distribution areas, and the geographical location information of each distribution area, including longitude, latitude, altitude, etc., is accurately obtained during the positioning detection, thereby realizing positioning detection of multiple distribution areas. The relative positions of multiple distribution areas are determined based on the comparison of the geographical location information of each distribution area, thereby ensuring the accuracy of the relative positions of multiple distribution areas, and determining the relative positions between each distribution area, providing a basis for subsequent distribution network planning, load distribution, etc.

[0053] At this time, select a suitable geographic coordinate system (such as WGS84), unify the positioning data of all distribution areas into this coordinate system, use the principles of spatial geometry to calculate the distance and direction between each distribution area, and use GIS software or other visualization tools to display the location relationship of the distribution areas in the form of a map.

[0054] Specifically, there are three distribution areas A, B, and C, which need to be located and detected to determine their relative positions. A GPS device is used to conduct an on-site survey of distribution area A, and its latitude and longitude coordinates are obtained as (116.404, 39.915). Remote sensing technology is used to obtain a high-resolution image of distribution area B. Its location is analyzed using GIS software, and the coordinates are obtained as (116.420, 39.900). The existing power supply distribution map is integrated to find the location of distribution area C, and the coordinates are obtained as (116.380, 39.925). The WGS84 coordinate system is selected and all coordinates are unified into this coordinate system. The distance from distribution area A to B is calculated to be approximately 2.5 kilometers in the northeast direction; the distance from A to C is approximately 2.3 kilometers in the southwest direction. A map is drawn using GIS software, and distribution areas A, B, and C are represented by different colors or icons, and their relative positions are marked on the map.

[0055] At the same time, the power supply of multiple distribution areas is determined based on the power detection of multiple distribution areas, which realizes the power detection of multiple distribution areas and ensures the accuracy of the power supply of multiple distribution areas.

[0056] At this time, power consumption is detected in multiple distribution areas. At the same time, power meters are installed at the entrance of each distribution area or on key power facilities. The power meters are used to monitor power data in real time, thereby collecting power data from each distribution area and calculating the power supply of each distribution area based on the collected power data.

[0057] To calculate the power supply, the collected electricity data is cleaned, denoised, and formatted to ensure data quality and availability. Based on the working principles and parameters of the electricity meter, the electricity value of each distribution area is calculated and converted into power supply, usually in kilowatt-hours (kWh) or megawatt-hours (MWh).

[0058] Specifically, high-precision electricity meters were installed at the entrances of distribution areas A, B, and C, and a data acquisition system was established. This system collects electricity data in real time and uploads it to the central control room. The data acquisition system automatically reads electricity data from the meters every hour. To ensure data accuracy, manual recording and data comparison are performed weekly. After preprocessing the collected electricity data, the electricity values ​​for distribution areas A, B, and C are calculated based on the operating principles and parameters of the electricity meters. These values ​​are converted into power supply quantities, resulting in a power supply of 100MWh / day for distribution area A, 150MWh / day for distribution area B, and 80MWh / day for distribution area C.

[0059] Furthermore, the distribution network, the relative positions of the multiple distribution areas, and the power supply amounts of the multiple distribution areas are associated; multiple interactions are performed on the distribution network, the relative positions of the multiple distribution areas, and the power supply amounts of the multiple distribution areas, and the distribution network, the relative positions of the multiple distribution areas, and the power supply amounts of the multiple distribution areas are introduced, and comprehensive interactions are performed on the distribution network, the relative positions of the multiple distribution areas, and the power supply amounts of the multiple distribution areas.

[0060] Specifically, the distribution network, the relative positions of multiple distribution areas, and the power supply of multiple distribution areas are introduced, and the distribution network, the relative positions of multiple distribution areas, and the power supply of multiple distribution areas are associated to facilitate multiple interactions of the distribution network, the relative positions of multiple distribution areas, and the power supply of multiple distribution areas.

[0061] Regarding the multiple interactions between the distribution network, the relative positions of multiple distribution areas, and the power supply to multiple distribution areas, the distribution network is an electric power network system composed of various distribution equipment (such as overhead lines, cables, distribution transformers, etc.). Its structure is usually radial and used to distribute electricity directly to end users. The relative positions of each distribution area in the distribution network are usually presented through a geographic information system (GIS) or power network diagram. The relative position relationship between distribution areas determines the direction and path of power flow, which in turn affects the stability and efficiency of the distribution network. The interaction between the distribution network and the relative positions of distribution areas is mainly reflected in power flow and load distribution. The location of the distribution area determines the method and location of its connection to the distribution network, which in turn affects the path of power flow and the balance of load distribution.

[0062] Power supply refers to the total amount of electricity provided to users in each distribution area. Data from electricity meters is fundamental to distribution network planning and operation, reflecting the power demand and supply situation in each distribution area. The interaction between the distribution network and power supply is primarily reflected in load management and power dispatch. The distribution network requires real-time dispatch and adjustment based on the power supply in each distribution area to ensure balance and stability. Furthermore, changes in power supply also impact the structure and operation of the distribution network. For example, if power demand in a distribution area increases, the capacity of the transmission lines and transformers in that area may need to be increased to accommodate the increased load.

[0063] Specifically, take a city's distribution network as an example. The city consists of three distribution areas: A, B, and C. Distribution area A is located in the city center and has a high load density; distribution area B is located in the suburbs and has a relatively low load density; and distribution area C is located on the city's edge and is primarily used by industrial loads.

[0064] Regarding the interaction between the distribution network and the relative locations of distribution areas: The distribution network adopts different structures and operating modes based on the location and load characteristics of each distribution area. For example, in the city center area A, due to the high and variable load density, a ring network power supply method is used to improve power supply reliability and flexibility; while in the suburban area B and the peripheral area C, a radial power supply method is used to reduce costs.

[0065] Regarding the interaction between the distribution network and power supply: Power supply in each distribution area is monitored and recorded in real time using electricity meters. Based on this monitoring data, the distribution network conducts real-time load management and power dispatch. For example, during peak load periods, transformer tap adjustments and capacitor bank switching are used to reduce line losses and improve voltage quality. During power shortages, power is supplemented by drawing on power from other distribution areas or activating backup power sources to ensure power supply reliability.

[0066] Regarding the interaction between multiple distribution areas: In this city, a robust mechanism for power mutualization and load balancing has been established among the distribution areas. For example, during peak load periods in Area A, power can be supplemented by electricity from Areas B or C. During periods of low industrial load in Area C, excess power can be transferred to other areas for utilization. These interactions are facilitated through interconnection lines and the power trading market, and require robust information communication and coordination mechanisms between distribution areas to ensure the overall stability and efficiency of the distribution network.

[0067] At the same time, multiple power load nodes are determined based on the multiple interactions of the distribution network, the relative positions of multiple distribution areas, and the power supply of multiple distribution areas. Multiple power load nodes are presented at different positions of the distribution network, realizing the multiple interactions of the relative positions of the distribution network, multiple distribution areas, and the power supply of multiple distribution areas, and ensuring the accuracy of multiple power load nodes.

[0068] At this time, multiple interactions of the distribution network, the relative positions of multiple distribution areas, and the power supply amounts of multiple distribution areas are introduced, and multiple power load nodes are gradually determined in the process of multiple interactions.

[0069] Power load nodes are the terminal nodes directly connected to loads in the power grid. PQ nodes primarily represent load points in the grid. The configuration and status of PQ nodes have a significant impact on the stability of the distribution network. By analyzing the power balance and voltage stability of these nodes, the stable operation of the entire power grid can be assessed.

[0070] Specifically, obtain information such as the topology, line parameters, transformer capacity, etc. of the distribution network, understand the operating status of the distribution network, including historical load data, voltage level, current distribution, etc., so as to determine the geographical location, boundary range, load density, etc. of each distribution area, and collect historical power supply data of each distribution area.

[0071] At the same time, based on the geographic location and boundaries of each distribution area, the distribution area of ​​load nodes is preliminarily divided. Within each area, the potential load node locations are further subdivided based on the load density and power supply distribution. The path and direction of power flow in the distribution network are analyzed to ensure that the setting of load nodes can reasonably guide power flow and avoid setting too many load nodes along the power flow path to reduce line losses and improve power utilization efficiency. Furthermore, load forecasting is carried out using historical load data and load change trends. Based on the load forecast results, the location and number of load nodes are adjusted. When determining load nodes, physical constraints such as line capacity and transformer capacity need to be considered. It is necessary to ensure that the setting of load nodes does not exceed these physical constraints to ensure the stable operation of the distribution network.

[0072] In step S13, power levels of the plurality of power load nodes are determined based on the locations of the plurality of power load nodes, the power distribution priorities of the plurality of power distribution areas, and the current time;

[0073] In the specific implementation process of the present invention, the specific steps are:

[0074] S131: Determine the locations of the plurality of power load nodes based on the position detection of the plurality of power load nodes;

[0075] S132: In the distribution network, obtain relative positions of multiple distribution areas;

[0076] S133: Determine power distribution priorities for the multiple power distribution areas based on relative positions of the multiple power distribution areas, power supply types corresponding to the multiple power distribution areas, and power supply ratios of the multiple power distribution areas relative to the power distribution network;

[0077] S134: Associating the locations of multiple power load nodes, the power distribution priorities of multiple power distribution areas, and the current time;

[0078] S135: Input the locations of multiple power load nodes, the power distribution priorities of multiple distribution areas, and the current time into the corresponding power level learning model, and determine the power levels of the multiple power load nodes based on the power level learning model.

[0079] In an embodiment of the present application, the locations of multiple power load nodes are determined based on the location detection of multiple power load nodes, thereby realizing the location detection of multiple power load nodes and ensuring the accuracy of the locations of multiple power load nodes.

[0080] Specifically, multiple power load nodes are introduced and their locations are detected. The exact locations of the load nodes are determined using a location detection algorithm. Optionally, an RSSI-based location detection algorithm is employed. This algorithm calculates the node's location by measuring the signal strength received by different sensors. Specifically, the algorithm calculates the precise coordinates of the load nodes based on the signal strength transmitted by the smart meter and the known sensor locations.

[0081] After determining the location of the load node, position verification and correction are required. At this point, the calculated load node location is compared with the known locations of substations or important load points, using these reference points. If significant deviations are found, algorithm parameters can be adjusted or data can be recollected to improve location accuracy. The determined load node location data needs to be stored in a database and effectively managed.

[0082] Alternatively, load data can be collected in real time and sent to the power grid company's data center. Upon receiving this data, the data center first preprocesses it to remove outliers and invalid data. Then, an RSSI-based location detection algorithm is applied to calculate the load node's location. During this calculation, the known locations of base stations or reference points are used as a calibration basis to ensure accurate positioning. Finally, the calculated location data is stored in a database and effectively managed.

[0083] Furthermore, in the distribution network, the relative positions of multiple distribution areas are obtained; the distribution priorities of the multiple distribution areas are determined according to the relative positions of the multiple distribution areas, the power supply types corresponding to the multiple distribution areas, and the power supply ratios of the multiple distribution areas relative to the distribution network. The relative positions of the multiple distribution areas, the power supply types corresponding to the multiple distribution areas, and the power supply ratios of the multiple distribution areas relative to the distribution network are introduced, and the relative positions of the multiple distribution areas, the power supply types corresponding to the multiple distribution areas, and the power supply ratios of the multiple distribution areas relative to the distribution network are comprehensively considered, thereby ensuring the accuracy of the distribution priorities of the multiple distribution areas and fully considering the distribution priorities of the multiple distribution areas.

[0084] Specifically, the relative positions of multiple distribution areas, the power supply types corresponding to the multiple distribution areas, and the power supply ratios of the multiple distribution areas relative to the distribution network are introduced. At this time, the relative positions of the multiple distribution areas refer to the geographical location relationships of the distribution areas in the distribution network, the power supply types corresponding to the multiple distribution areas refer to the types of power provided by the distribution areas, which mainly include AC power supply and DC power supply; the power supply ratios of the multiple distribution areas relative to the distribution network refer to the power supply shares of the distribution areas in the distribution network.

[0085] At this time, relevant data of each distribution area is collected, including geographical location information, power supply type, historical power supply, etc., and the data is preprocessed to ensure the accuracy and consistency of the data. The relative position, power supply type and power supply ratio of each distribution area are evaluated and quantified according to the evaluation results. A scoring system or weight distribution method can be used to assign reasonable weights to each factor, and score according to actual conditions. The quantified scores of each factor are weighted and summed to obtain a comprehensive score for each distribution area. The distribution areas are sorted according to the comprehensive score. Distribution areas with higher scores have higher priorities. At the same time, when determining the distribution priority, the overall stability and reliability of the power grid should be fully considered to avoid being too biased towards a certain area and causing power grid imbalance.

[0086] Alternatively, assume there are three power distribution areas, A, B, and C. Area A is located in the city center, powered by AC, and has a high power share. Area B is located in an industrial area, powered by DC, and has a moderate power share. Area C is located in the suburbs, powered by AC, but has a low power share. Based on this information, you can determine power distribution priorities by following these steps:

[0087] Evaluate and quantify the relative locations, power supply types, and power supply ratios of areas A, B, and C. Calculate a comprehensive score based on the quantified results and a weighted distribution method. Rank areas A, B, and C based on the comprehensive score. Assume area A has the highest score, area B has the second highest, and area C has the lowest. Determine the power distribution priority based on the ranking results, with area A having the highest priority, area B having the second highest, and area C having the lowest.

[0088] Therefore, the locations of multiple power load nodes, the distribution priorities of multiple distribution areas, and the current time are associated; the locations of multiple power load nodes, the distribution priorities of multiple distribution areas, and the current time are input into the corresponding power level learning model, and the power levels of multiple power load nodes are determined based on the power level learning model, thereby ensuring the accuracy of the power levels of multiple power load nodes.

[0089] Specifically, the locations of multiple power load nodes, the distribution priorities of multiple distribution areas, and the current time are introduced. At this time, the locations of multiple power load nodes, the distribution priorities of multiple distribution areas, and the current time are collected. This information is the basis for determining the power level of the power load nodes. The collected locations of multiple power load nodes, the distribution priorities of multiple distribution areas, and the current time are integrated to form a database or data set containing all necessary information.

[0090] At the same time, select a pre-trained power level learning model. This model should be built based on extensive historical data and machine learning algorithms, and be able to accurately predict the power level of power load nodes based on the input information. This integrated information is fed into the power level learning model as input. This typically involves formatting the data into a format acceptable to the model and ensuring its accuracy and completeness. The power level learning model then calculates the power level for each power load node based on the input information. Once the power level learning model completes its calculations, it outputs the power level for each power load node. These levels are typically categorized based on factors such as load importance, stability, and demand.

[0091] Specifically, assume there is a city distribution network with three distribution areas (A, B, and C) and ten power load nodes (L1 to L10). The following is an example of how to apply the above steps to determine the power levels of these load nodes:

[0092] Collect the locations of the ten load nodes L1 to L10 (e.g., longitude and latitude coordinates), the power distribution priorities of zones A, B, and C (e.g., zone A is the highest priority, zone B is medium priority, and zone C is the lowest priority), and the current time (e.g., February 3, 2025, 10:57:39). This information is integrated into a table or database for subsequent processing.

[0093] A power level learning model was introduced, which predicts the power level of load nodes based on location, distribution priority, and time information. This integrated information is fed into the model to ensure data accuracy and completeness. For example, location information can be converted into a format the model can understand (such as longitude and latitude coordinates), and distribution priority and time information can be appropriately represented.

[0094] The power level learning model calculates the power levels of ten load nodes, L1 through L10, based on the input information. For example, suppose the model predicts that L1 is located in Area A, close to a critical load center, and is therefore classified as a Level 1 load; while L10 is located in Area C, far from the critical load center, and is therefore classified as a Level 3 load. Other load nodes are classified into different levels based on their location, distribution priority, and time information.

[0095] In step S14, a first-level reliability parameter of the power distribution network is determined based on the power levels of the plurality of power load nodes, the power losses of the plurality of power load nodes, and the power supplies of the plurality of power load nodes;

[0096] In the specific implementation process of the present invention, the specific steps are:

[0097] S141: Real-time monitoring of multiple power load nodes;

[0098] S142: Determine a power data set of a plurality of power load nodes based on real-time monitoring of the plurality of power load nodes;

[0099] S143: determining power consumption amounts of the plurality of power load nodes and power supply amounts of the plurality of power load nodes based on the power data sets of the plurality of power load nodes;

[0100] S144: Associating the power levels of multiple power load nodes, the power losses of multiple power load nodes, and the power supplies of multiple power load nodes, and determining the first-level reliability parameters of the distribution network based on the multiple interactions of the power levels of multiple power load nodes, the power losses of multiple power load nodes, and the power supplies of multiple power load nodes.

[0101] At this time, multiple power load nodes are monitored in real time; the power data sets of multiple power load nodes are determined based on the real-time monitoring of multiple power load nodes, and the power data sets of multiple power load nodes are introduced to facilitate subsequent management and control of the power data sets of multiple power load nodes.

[0102] At this time, multiple power load nodes are introduced and real-time monitoring of multiple power load nodes is performed, thereby realizing real-time monitoring of multiple power load nodes, so as to collect multiple power data of each power load node during the monitoring process, thereby forming a power data set of multiple power load nodes from the multiple power data.

[0103] Optionally, the real-time monitoring data from each power load node is integrated into a unified data set and verified to ensure its accuracy and completeness. This may include checking the rationality of the data (e.g., whether current and voltage are within normal ranges) and consistency (e.g., whether data measured by different devices are consistent). Data is then categorized and labeled based on its nature and application requirements. For example, data can be categorized into real-time data, historical data, and abnormal data; or it can be labeled based on the type of power load node (e.g., residential power consumption, industrial power consumption, etc.).

[0104] Furthermore, based on the power data sets of multiple power load nodes, the power losses of multiple power load nodes and the power supplies of multiple power load nodes are determined, and the analysis of the power data sets of multiple power load nodes is realized, thereby introducing the power losses of multiple power load nodes and the power supplies of multiple power load nodes, and ensuring the accuracy of the power losses of multiple power load nodes and the power supplies of multiple power load nodes.

[0105] At this point, power data sets from multiple power load nodes are introduced and data extraction is performed on these data sets. Data relevant to power loss calculations, such as current, voltage, and power factor, are extracted from these data sets. This data should be high-quality data that has been verified and integrated.

[0106] Specifically, the extracted data is input into the loss calculation model and calculated to output the calculation results, which are verified to ensure that they are within a reasonable range, so as to determine the calculation results as the power loss amount of multiple power load nodes.

[0107] Furthermore, the power supply of multiple load nodes is determined based on the power data set of multiple load nodes. Data related to power supply, such as active power and reactive power, is filtered from the power data set. Based on the filtered data, the power supply of each load node is calculated, ensuring that the calculated supply is synchronized with actual power consumption time to accurately assess the power demand and supply situation of the load nodes. Optionally, the calculated losses and supply can be used to optimize and dispatch the distribution network. For example, line layout and resistance values ​​can be adjusted based on the magnitude of losses; power supply strategies and demand response measures can be adjusted based on changes in supply.

[0108] Therefore, the power levels of multiple power load nodes, the power losses of multiple power load nodes, and the power supplies of multiple power load nodes are associated, and the first-level reliability parameters of the distribution network are determined based on the multiple interactions of the power levels of multiple power load nodes, the power losses of multiple power load nodes, and the power supplies of multiple power load nodes. This realizes the multiple interactions of the power levels of multiple power load nodes, the power losses of multiple power load nodes, and the power supplies of multiple power load nodes, and ensures the accuracy of the first-level reliability parameters of the distribution network.

[0109] At this time, the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supplies of multiple power load nodes are introduced, and multiple interactions are performed on the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supplies of multiple power load nodes.

[0110] In view of the multiple interactions of the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supplies of multiple power load nodes, the interactions of the power levels of multiple power load nodes and the power supplies of multiple power load nodes, the interactions of the power losses of multiple power load nodes and the power supplies of multiple power load nodes, and the interactions of the power levels of multiple power load nodes and the power losses of multiple power load nodes are introduced.

[0111] Regarding the interaction between the power levels of multiple power load nodes and their power supply, the power levels of multiple power load nodes reflect their power demand and capacity, while the power supply of multiple power load nodes refers to the total amount of power provided by the distribution network to the load nodes. The power levels and power supply interact with each other. On the one hand, load nodes with higher power levels may require more power supply to meet their power needs; on the other hand, the distribution network's generation and transmission capacity are also adjusted and optimized based on the power levels of the load nodes.

[0112] Regarding the interaction between power loss and power supply at multiple load nodes, power loss at multiple load nodes refers to the energy loss caused by factors such as resistance and inductance during power transmission and distribution. This power loss at multiple load nodes has a direct impact on the power supply at these load nodes. On the one hand, power loss reduces the amount of power actually reaching the load nodes. On the other hand, to reduce power loss, the distribution network may need to increase generation and transmission capacity to compensate for the loss. Distribution networks implement a range of measures to reduce power loss, such as optimizing the transmission network structure, improving the quality of transmission equipment, and adopting energy-saving technologies. Furthermore, distribution networks rationally allocate power resources based on the power demand and power supply of load nodes to reduce unnecessary losses.

[0113] Regarding the interaction between the power levels and power losses of multiple power load nodes, load nodes of different power levels also have different power consumption characteristics and power consumption time, which will also have an impact on power loss. In the planning and operation of the distribution network, it is necessary to comprehensively consider the interaction between power levels, power loss, and power supply. This can be achieved through measures such as optimizing the grid structure, improving equipment efficiency, and strengthening power management.

[0114] Alternatively, assume that a distribution network contains multiple power load nodes of different power levels. Among them, power load nodes with high power levels (such as large factories and hospitals) require a large amount of power supply to meet their electricity needs; while power load nodes with low power levels (such as residential areas and small businesses) have relatively small electricity demands.

[0115] During power transmission, factors such as resistance and inductance generate a certain amount of power loss. High-power load nodes, due to their large power consumption and high current density, may experience even greater power losses. To reduce these losses, distribution networks can implement measures such as optimizing the transmission network structure and improving the quality of transmission equipment.

[0116] At the same time, to ensure the power demand of high-power load nodes and reduce unnecessary losses, the distribution network also needs to rationally allocate power resources based on the power consumption characteristics and time of the load nodes. For example, during peak power consumption periods, the power demand of high-power load nodes can be prioritized; while during low power consumption periods, their power supply can be appropriately reduced to reduce losses.

[0117] For the first-level reliability parameters of the distribution network, optionally, a machine learning or deep learning algorithm is used to construct a training model that can process multi-variable inputs (power level, power loss, power supply) and outputs (first reliability parameters). At this time, the collected power level, power loss and power supply data are input into the training model, and the model is trained so that it can learn the complex relationship between these factors and their impact on the reliability parameters. The trained model is used to calculate the first-level reliability parameters of the distribution network based on the input power level, power loss and power supply data. These parameters may include the power supply reliability index (ASAI), the average power outage time for users (SAIDI) and the average number of power outages for users (SAIFI).

[0118] In step S15, the corresponding power equipment is determined based on the positioning traversal of multiple power load nodes, and the second-level reliability parameter of the distribution network is determined based on the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss;

[0119] In the specific implementation process of the present invention, the specific steps are:

[0120] S151: Positioning and traversing a plurality of power load nodes, and determining corresponding power equipment based on the positioning and traversing of the plurality of power load nodes;

[0121] S152: determining a set of past usage data of the electric power equipment based on the tracing back of the electric power equipment;

[0122] S153: Determine the power usage efficiency of the power equipment based on the past usage data set of the power equipment;

[0123] S154: collecting the service life of the power equipment;

[0124] S155: Correlating the power usage efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss;

[0125] S156: Determine the second level reliability parameter of the power distribution network based on multiple calculations of the power usage efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss amount.

[0126] At this time, multiple power load nodes are positioned and traversed, and corresponding power equipment is determined based on the positioning and traversal of the multiple power load nodes, thereby achieving the positioning and traversal of the multiple power load nodes and ensuring the accuracy of the power equipment.

[0127] Specifically, multiple power load nodes are introduced to realize the positioning traversal of multiple power load nodes. Optionally, a handheld GPS device is used to locate each load node one by one and record the location information. At the same time, according to the location information of the load node, the power network diagram is consulted to determine the power equipment connected to each node, and the basic information of the power equipment is recorded, such as transformer model, capacity, manufacturer, etc.

[0128] Furthermore, the previous usage data set of the power equipment is determined based on the tracing of the power equipment, and the power usage efficiency of the power equipment is determined based on the previous usage data set of the power equipment. The previous usage data set of the power equipment is fully taken into consideration, and the power usage efficiency of the power equipment is determined by calculating the previous usage data set of the power equipment, thereby ensuring the accuracy of the power usage efficiency of the power equipment.

[0129] Specifically, the electric power equipment is introduced and traced. At the same time, the equipment database is collected, and the previous usage data set of the electric power equipment is matched according to the equipment database and the basic information of the electric power equipment.

[0130] Power utilization efficiency usually refers to the power conversion efficiency or the ratio of output power to input power of power equipment under specific load conditions. At this time, the power utilization efficiency of power equipment under different load conditions is calculated based on the previous usage data set of the power equipment (such as load curve, operating time, etc.).

[0131] Alternatively, for example, consider a transformer with a rated capacity of 1000 kVA. The power company's monitoring system retrieved its load curve and operating hours over the past year. Based on this data, the transformer's power efficiency under different load conditions was calculated. The transformer's efficiency reached a peak of 98% at 75% of the rated load, but decreased at low or high loads.

[0132] At the same time, the service life of the power equipment is collected; the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss are correlated; and the second-level reliability parameters of the distribution network are determined based on multiple calculations of the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss. This realizes multiple calculations of the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss, thereby ensuring the accuracy of the second-level reliability parameters of the distribution network.

[0133] At this time, the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss are introduced, and management and control are carried out at the power equipment level. The second-level reliability parameters of the distribution network are determined based on multiple calculations of the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss.

[0134] Specifically, the service life of the power equipment is obtained by subtracting the installation date of the power equipment from the service life of the power equipment. At the same time, the power loss of the power equipment is obtained through on-site tests or historical data calculations. A correlation model between power utilization efficiency, service life and power loss is established. The established correlation model is verified to ensure its accuracy and reliability. The model parameters are adjusted according to the verification results to improve the prediction accuracy.

[0135] Suppose data has been collected for a transformer: its power efficiency is 96%, its service life is 13.75 years, and its power loss is 2%. Using data analysis software, a correlation model is constructed, revealing a positive correlation between service life and power loss and a negative correlation with power efficiency. Verification of the correlation model reveals that the predicted results match actual conditions, thus confirming the reliability of the model.

[0136] At this time, the power efficiency, service life and power loss data in the association model are combined with the structure and operation data of the distribution network to perform multiple operations. Optionally, it is assumed that the second-level reliability parameter of the distribution network is the system average outage duration (SAIDI). Using the multiple operation method, combined with the power efficiency (96%), service life (13.75 years) and power loss (2%) of the transformer, as well as the structure and operation data of the distribution network, the SAIDI is calculated to be 2.5 hours / year. Analysis of the calculation results shows that this value is higher than the industry average, indicating that the reliability of the distribution network needs to be improved.

[0137] In step S16, the peripheral environmental parameters of the distribution network are determined based on the environmental detection of the locations of the plurality of power load nodes, and the reliability level of the distribution network is comprehensively evaluated based on the peripheral environmental parameters of the distribution network, the first-level reliability parameters, and the second-level reliability parameters;

[0138] In the specific implementation process of the present invention, the specific steps are:

[0139] S161: Obtaining locations of multiple power load nodes;

[0140] S162: triggering corresponding environmental detection according to the locations of the plurality of power load nodes;

[0141] S163: determining a plurality of environmental data of the distribution network based on environmental detection of locations of the plurality of power load nodes, and determining surrounding environmental parameters of the distribution network according to the plurality of environmental data of the distribution network;

[0142] S164: Associated distribution network surrounding environmental parameters, first-level reliability parameters, and second-level reliability parameters;

[0143] S165: performing multiple interactions on the surrounding environmental parameters, the first-level reliability parameters, and the second-level reliability parameters of the distribution network;

[0144] S166: In the multiple interactions of the surrounding environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, multiple interaction combinations are formed based on the surrounding environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, and the reliability characteristics of each power load node are determined according to the identification of the multiple interaction combinations. The reliability level of the distribution network is determined according to the reliability characteristics of each power load node and the corresponding evaluation learning model.

[0145] At this time, the locations of multiple power load nodes are obtained; corresponding environmental detection is triggered according to the locations of the multiple power load nodes;

[0146] The locations of multiple power load nodes are introduced to manage and control the locations of multiple power load nodes. According to the locations of the power load nodes, the environmental factors that need to be detected are determined. These factors may include temperature, humidity, wind speed, air quality, soil resistivity, etc., depending on the characteristics of the power load nodes and the operating environment.

[0147] At the same time, corresponding environmental detection equipment is deployed near the power load nodes or in the surrounding environment. These devices can be sensors, monitoring stations, etc., which are used to monitor changes in environmental factors in real time, collect real-time environmental data from the detection equipment, pre-process and analyze these data, and extract key information that affects the operation of the power load nodes.

[0148] Furthermore, based on the environmental detection of the locations of multiple power load nodes, multiple environmental data of the distribution network are determined, and the peripheral environmental parameters of the distribution network are determined based on the multiple environmental data of the distribution network, thereby realizing the environmental detection of the locations of multiple power load nodes, ensuring the accuracy of the multiple environmental data of the distribution network, and further ensuring the accuracy of the peripheral environmental parameters of the distribution network.

[0149] Environmental detection of the locations of multiple power load nodes is introduced to control the environmental detection of the locations of multiple power load nodes. At this time, environmental data is monitored and recorded in real time and transmitted to the data center via wired or wireless means. The collected data is preprocessed, including data cleaning, outlier detection and processing, data format conversion, etc., to provide a high-quality data basis for subsequent analysis. The preprocessed environmental data is integrated according to time, space and other dimensions to form an environmental data set of the distribution network. Key environmental parameters such as average temperature, average humidity, maximum wind speed, air quality index, etc. are extracted from the integrated environmental data set. These parameters can reflect the overall characteristics and changing trends of the environment around the distribution network.

[0150] Furthermore, the extracted environmental parameters are analyzed and evaluated to determine the extent of their impact on the operation of the distribution network. Historical data and professional knowledge are used to establish a correlation model between environmental parameters and the operating status of the distribution network. Based on the analysis results, the extracted environmental parameters are optimized and adjusted to ensure that they can accurately reflect the actual situation of the environment around the distribution network. The determined environmental parameters are applied to various stages of distribution network planning, design, operation and maintenance, and the environmental parameters are used to guide the optimization layout, equipment selection, fault prediction and emergency response of the distribution network.

[0151] At this time, the surrounding environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network are associated; multiple interactions are performed on the surrounding environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, realizing multiple interactions of the surrounding environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, and comprehensively considering the surrounding environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network.

[0152] The peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network are introduced. The peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network correspond to three different levels: the external environment, power and circuit equipment of the distribution network, respectively, realizing multi-level management and control of the external environment, power and circuit equipment of the distribution network.

[0153] Therefore, in the multiple interactions of the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, multiple interaction combinations are formed based on the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network. The reliability characteristics of each power load node are determined according to the identification of multiple interaction combinations, and the reliability level of the distribution network is determined according to the reliability characteristics of each power load node and the corresponding evaluation learning model.

[0154] At this point, the distribution network's surrounding environmental parameters (such as temperature, humidity, and wind speed) affect the failure rate and performance of equipment (first-level reliability parameters). Furthermore, the failure rate and performance of equipment (first-level reliability parameters) affect the power supply reliability and stability of the entire system (second-level reliability parameters). Combining these parameters creates various interactive combinations, such as "high temperature + high humidity + aging equipment" and "low temperature + dryness + new equipment."

[0155] After identifying various interaction combinations, we need to analyze their impact on each power load node. This includes analyzing equipment failure rates, repair times, and load fluctuations under different interaction combinations. Through these analyses, we can determine the reliability characteristics of each power load node, such as failure rate and power supply reliability.

[0156] Furthermore, an evaluation learning model is established, which can evaluate the reliability level of the entire distribution network according to the reliability characteristics of each power load node. By inputting the reliability characteristics of each power load node into the evaluation learning model, the reliability level of the entire distribution network can be obtained.

[0157] To evaluate the learning model, a multivariate dataset covering environmental parameters surrounding the distribution network (such as temperature, humidity, and wind speed), first-level reliability parameters, and second-level reliability parameters must be collected. This data should come from an actual distribution network and include a sufficient sample size to ensure the model's generalization capabilities. After data collection, it is necessary to perform data cleaning to remove invalid, redundant, and abnormal data.

[0158] The most valuable features for distribution network reliability assessment are selected from the original dataset. This can be achieved through methods such as correlation analysis and mutual information analysis to screen out the features with the highest correlation with the target variable (such as system power supply reliability). The original features are then further extracted and transformed to generate new, more expressive features. For example, feature dimensionality reduction can be performed through methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), or new features can be generated through methods such as feature cross-pollination and feature aggregation. These features can then be further optimized, such as through feature scaling and smoothing, to improve the predictive performance of the evaluation learning model.

[0159] Alternatively, assume that there is a distribution network that includes multiple power load nodes and various devices. The following data is monitored in real time:

[0160] Surrounding environmental parameters: Current temperature is 35°C, humidity is 80%, and wind speed is 5 m / s.

[0161] Equipment status parameters: The failure rate of device A is 0.01 / year, the failure rate of device B is 0.02 / year, and the failure rate of device C is 0.03 / year. Based on the current environmental parameters and equipment status parameters, various interactive combinations can be formed, such as "high temperature and high humidity + normal device A + aging device B + new device C"; "high temperature and high humidity + aging device A + normal device B + new device C"; and so on.

[0162] Through real-time monitoring and analysis, we identified the current interaction combination of "high temperature and high humidity + normal device A + aging device B + new device C." Under this interaction combination, the aging of device B may increase its failure rate, thereby affecting the power supply reliability of its downstream power load nodes.

[0163] By analyzing the failure rate of device B and downstream load fluctuations, the reliability characteristics of the affected power load nodes were determined. The reliability characteristics of each power load node were input into the evaluation learning model. After calculation and analysis, the reliability level of the entire distribution network was determined to be "medium."

[0164] In an embodiment of the present invention, through the method in the embodiment of the present invention, a distribution network is determined according to multiple distribution areas and line routing paths; multiple power load nodes are determined according to the relative positions of the distribution network and multiple distribution areas and the power supply of multiple distribution areas; the power levels of multiple power load nodes are determined based on the locations of multiple power load nodes, the distribution priorities of multiple distribution areas and the current time; the first-level reliability parameters of the distribution network are determined according to the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supply of multiple power load nodes, which is compatible with the overall consideration of the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supply of multiple power load nodes, ensures the accuracy of the first-level reliability parameters of the distribution network, and realizes the preliminary control of the distribution network at the power level.

[0165] Furthermore, the corresponding power equipment is determined based on the positioning traversal of multiple power load nodes, and the second-level reliability parameters of the distribution network are determined based on the power utilization efficiency of the power equipment, the service life of the power equipment and the corresponding power loss, thereby realizing the overall control of the distribution network at the power equipment level and ensuring the accuracy of the second-level reliability parameters of the distribution network.

[0166] Therefore, the peripheral environmental parameters of the distribution network are determined based on the environmental detection of the locations of multiple power load nodes, and the reliability level of the distribution network is comprehensively evaluated based on the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network. This is compatible with the overall consideration of the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, and realizes multi-dimensional control of the peripheral environmental parameters, first-level reliability parameters and second-level reliability parameters of the distribution network, ensuring the comprehensive evaluation of the reliability level of the power grid and improving the accuracy of the reliability level of the distribution network.

[0167] Example 3: Please refer to Figure 3 , Figure 3 Schematic diagram of the structure of the distribution network reliability evaluation system in an embodiment of the present invention.

[0168] like Figure 3 As shown, a distribution network reliability evaluation system, the distribution network reliability evaluation system includes:

[0169] A power distribution module 21 is configured to determine a power distribution network based on multiple power distribution areas and line routing paths;

[0170] The power load node module 22 is configured to determine a plurality of power load nodes according to the relative positions of the power distribution network and the plurality of power distribution areas and the power supply of the plurality of power distribution areas;

[0171] A power level module 23 is configured to determine the power levels of the plurality of power load nodes based on the locations of the plurality of power load nodes, the power distribution priorities of the plurality of power distribution areas, and the current time;

[0172] a first-level reliability parameter module 24 for determining a first-level reliability parameter of the distribution network according to power levels of the plurality of power load nodes, power losses of the plurality of power load nodes, and power supplies of the plurality of power load nodes;

[0173] The second-level reliability parameter module 25 is used to determine the corresponding power equipment based on the positioning traversal of multiple power load nodes, and determine the second-level reliability parameters of the distribution network based on the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss;

[0174] The reliability level module 26 is used to determine the peripheral environmental parameters of the distribution network based on the environmental detection of the locations of multiple power load nodes, and comprehensively evaluate the reliability level of the distribution network based on the peripheral environmental parameters of the distribution network, the first-level reliability parameters and the second-level reliability parameters.

[0175] Example 4: In this embodiment, an electronic device is provided. Its internal structure diagram can be as follows Figure 4As shown. The electronic device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database, which is used to store user behavior data and user portraits. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with other electronic devices that have deployed application software. When the computer program is executed by the processor, a low-altitude patrol method of a drone is implemented. The display screen of the electronic device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the housing of the electronic device, or an external keyboard, touchpad or mouse.

[0176] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A distribution network reliability evaluation method, characterized in that: include: Determine the distribution network based on multiple distribution areas and line routing; determining a plurality of power load nodes based on a distribution network, relative locations of the plurality of distribution areas, and power supply amounts of the plurality of distribution areas; determining power levels of the plurality of power load nodes based on locations of the plurality of power load nodes, power distribution priorities of the plurality of power distribution areas, and a current time; determining a first-level reliability parameter of the distribution network based on power levels of the plurality of power load nodes, power losses of the plurality of power load nodes, and power supplies of the plurality of power load nodes; Determine the corresponding power equipment based on the positioning traversal of multiple power load nodes, and determine the second-level reliability parameters of the distribution network based on the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss; The peripheral environmental parameters of the distribution network are determined based on environmental detection of the locations of multiple power load nodes, and the reliability level of the distribution network is comprehensively evaluated based on the peripheral environmental parameters, first-level reliability parameters, and second-level reliability parameters of the distribution network: the peripheral environmental parameters, first-level reliability parameters, and second-level reliability parameters of the distribution network are associated; multiple interactions are performed on the peripheral environmental parameters, first-level reliability parameters, and second-level reliability parameters of the distribution network, and the peripheral environmental parameters, first-level reliability parameters, and second-level reliability parameters of the distribution network are comprehensively considered; multiple interaction combinations are formed based on the peripheral environmental parameters, first-level reliability parameters, and second-level reliability parameters of the distribution network, and the reliability characteristics of each power load node are determined based on the identification of the multiple interaction combinations. The reliability level of the distribution network is determined based on the reliability characteristics of each power load node and the corresponding evaluation learning model.

2. The distribution network reliability evaluation method according to claim 1, characterized in that: Determining the distribution network according to the multiple distribution areas and line routing paths includes: Collect power supply distribution map; Determining a plurality of power distribution areas based on detection of a power distribution map; Locate the locations of multiple power distribution areas; Determine the line routing based on the locations of multiple distribution areas and line distribution maps; A plurality of power distribution areas and line routing paths are detected, and a power distribution network is determined based on the plurality of power distribution areas and line routing paths.

3. The distribution network reliability evaluation method according to claim 2, characterized in that: The determining of the plurality of power load nodes according to the relative positions of the power distribution network and the plurality of power distribution areas and the power supply of the plurality of power distribution areas comprises: Conduct location detection for multiple power distribution areas; Determining relative positions of the plurality of power distribution areas based on location detection of the plurality of power distribution areas; determining the power supply amount of the plurality of power distribution areas based on the power quantity detection of the plurality of power distribution areas; the relative locations of the associated distribution network, multiple distribution areas, and the amount of power available to the multiple distribution areas; Multiple interactions on the distribution network, the relative locations of multiple distribution areas, and the amount of power available to multiple distribution areas; Based on the multiple interactions among the relative positions of the distribution network, multiple distribution areas, and the power supply of multiple distribution areas, multiple power load nodes are determined, and multiple power load nodes appear at different locations on the distribution network; the interaction between the relative positions of the distribution network and distribution areas is reflected in power flow and load distribution; the interaction between the distribution network and power supply is reflected in load management and power dispatch; based on the geographical location and boundary range of each distribution area, the distribution area of ​​the power load nodes is preliminarily divided. Within each distribution area, the potential power load node locations are further subdivided according to the distribution of load density and power supply.

4. The distribution network reliability evaluation method according to claim 3, characterized in that: The determining of the power levels of the plurality of power load nodes based on the locations of the plurality of power load nodes, the power distribution priorities of the plurality of power distribution areas, and the current time includes: Determining the locations of the plurality of power load nodes based on the position detection of the plurality of power load nodes; In the distribution network, obtain the relative positions of multiple distribution areas; Determining the power distribution priorities of the multiple power distribution areas according to the relative positions of the multiple power distribution areas, the power supply types corresponding to the multiple power distribution areas, and the power supply ratios of the multiple power distribution areas relative to the power distribution network; Associating the locations of multiple power load nodes, the power distribution priorities of multiple distribution areas, and the current time; The locations of multiple power load nodes, the power distribution priorities of multiple distribution areas, and the current time are input into the corresponding power level learning model, and the power levels of the multiple power load nodes are determined based on the power level learning model.

5. The distribution network reliability evaluation method according to any one of claims 1 to 4, characterized in that: The determining of the first-level reliability parameter of the power distribution network according to the power levels of the plurality of power load nodes, the power loss amounts of the plurality of power load nodes, and the power supply amounts of the plurality of power load nodes includes: Real-time monitoring of multiple power load nodes; Determining a power data set of a plurality of power load nodes based on real-time monitoring of the plurality of power load nodes; determining power consumption amounts of the plurality of power load nodes and power supply amounts of the plurality of power load nodes based on a set of power data of the plurality of power load nodes; The power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supplies of multiple power load nodes are associated, and the first-level reliability parameters of the distribution network are determined based on the multiple interactions of the power levels of multiple power load nodes, the power losses of multiple power load nodes and the power supplies of multiple power load nodes: the collected power level, power loss and power supply data are input into the training model, and the model is trained so that it can learn the complex relationship between these elements and their impact on the reliability parameters; the trained model is used to calculate the first-level reliability parameters of the distribution network according to the input power level, power loss and power supply data.

6. The distribution network reliability evaluation method according to claim 5, characterized in that: The method of determining corresponding power equipment according to the positioning traversal of multiple power load nodes, and determining the second-level reliability parameter of the distribution network according to the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss, includes: Positioning and traversing a plurality of power load nodes, and determining corresponding power equipment based on the positioning and traversing of the plurality of power load nodes; Determining a collection of past usage data of the electric power equipment based on tracing back the electric power equipment; The power usage efficiency of the electrical equipment is determined based on a set of past usage data of the electrical equipment.

7. The distribution network reliability evaluation method according to claim 6, characterized in that: The method further includes determining corresponding power equipment according to the positioning traversal of multiple power load nodes, and determining the second-level reliability parameter of the distribution network according to the power utilization efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss. Collect the service life of the power equipment; Correlate the power usage efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss; The second level reliability parameter of the power distribution network is determined based on multiple calculations of the power usage efficiency of the power equipment, the service life of the power equipment, and the corresponding power loss amount.

8. The distribution network reliability evaluation method according to claim 7, characterized in that: The method of determining the peripheral environmental parameters of the distribution network based on the environmental detection of the locations of the plurality of power load nodes, and comprehensively evaluating the reliability level of the distribution network based on the peripheral environmental parameters of the distribution network, the first-level reliability parameters, and the second-level reliability parameters includes: Obtaining the locations of multiple power load nodes; Trigger corresponding environmental detection according to the location of multiple power load nodes; A plurality of environmental data of the power distribution network is determined based on environmental detection of locations of a plurality of power load nodes, and a peripheral environmental parameter of the power distribution network is determined according to the plurality of environmental data of the power distribution network.

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