Medium voltage direct current power distribution network multi-line design system and method based on three-dimensional model

Abstract

The application discloses a medium-voltage direct-current power distribution network multi-line design system and method based on a three-dimensional model, relates to the technical field of medium-voltage direct-current power distribution network design, and comprises the following steps: in response to a three-dimensional model construction instruction, spatial geographic data and electrical parameter data sets are loaded; the spatial geographic data is grid processed, a three-dimensional space grid matrix with a topological connection relationship is generated, electrical parameters are mapped to corresponding nodes to form an initial three-dimensional power grid model; high-power density target nodes are identified by traversing the nodes, electrical connection and spatial distance attributes of adjacent nodes are extracted, candidate line path cost evaluation values are calculated, and the optimal one is selected as a basic layout scheme; the basic scheme is superimposed and checked with the three-dimensional grid matrix, if there is a conflict, avoidance adjustment is triggered, and if there is no conflict, the scheme is determined as a to-be-optimized scheme. The application can realize the fusion of space and electrical parameters, improve line layout adaptability, avoid space interference problems, and guarantee the rationality and accuracy of line design.

Description

Technical Field

[0001] This invention belongs to the field of medium-voltage DC distribution network design technology, specifically a multi-line design system and method for medium-voltage DC distribution networks based on a three-dimensional model. Background Technology

[0002] Conventional medium-voltage DC distribution network line design often relies on two-dimensional geographic information data. Designers manually integrate electrical parameters with spatial geographic data to carry out line planning, mark the line route with plane coordinates, and complete the preliminary selection of line path based only on a single electrical constraint condition, without constructing a power grid model that integrates three-dimensional spatial architecture and electrical parameters.

[0003] Two-dimensional planar design cannot accurately reproduce the three-dimensional spatial distribution characteristics of medium-voltage DC distribution networks. Spatial geographic data and electrical parameters are disconnected, failing to achieve corresponding mapping at the node level. Line route selection only considers electrical transmission constraints or spatial distance conditions, without completing path quantification evaluation through dual-attribute joint calculation. The adaptability of line layout to actual spatial scenarios is low. After the line planning is completed, it is not overlaid and verified with the three-dimensional spatial scenario. Lines are prone to crossing non-traffic areas and causing spatial interference with existing infrastructure. Adjustment operations after line conflicts lack standardized procedures.

[0004] This invention requires the spatial geographic data of medium-voltage DC distribution network to be processed into a grid to generate a three-dimensional spatial grid matrix with topological connections. The electrical parameter dataset is then mapped to the corresponding node positions of the three-dimensional spatial grid matrix to form an initial three-dimensional power grid model. For high power density target nodes, the electrical connection attributes and spatial distance attributes of adjacent nodes need to be extracted. The path cost evaluation values ​​of multiple candidate power supply lines are calculated, and the line corresponding to the minimum value is selected as the basic line layout scheme. Summary of the Invention

[0005] This invention aims to solve at least one of the technical problems existing in the prior art;

[0006] Therefore, this invention proposes a multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model, including:

[0007] In response to the 3D model building command, load the spatial geographic data and electrical parameter dataset of the medium-voltage DC distribution network;

[0008] The spatial geographic data is processed into a grid to generate a three-dimensional spatial grid matrix with topological connections, and the electrical parameter dataset is mapped to the corresponding node positions of the three-dimensional spatial grid matrix to form an initial three-dimensional power grid model.

[0009] Traverse all nodes in the initial three-dimensional power grid model, identify the target node set that meets the preset high power density condition, and extract the electrical connection attributes and spatial distance attributes of its neighboring nodes for each target node in the target node set.

[0010] The path cost evaluation values ​​of multiple candidate power supply lines originating from the target node are calculated based on the electrical connection attributes and spatial distance attributes, and the candidate power supply line with the smallest path cost evaluation value is selected as the basic line layout scheme.

[0011] The basic route layout scheme is superimposed and verified with the three-dimensional spatial grid matrix to detect whether there are conflicting line segments that cross non-traffic areas or spatially interfere with other infrastructure. If they exist, the route avoidance adjustment process is triggered. If they do not exist, the basic route layout scheme is determined as the route design scheme to be optimized.

[0012] Furthermore, the generation of a three-dimensional spatial mesh matrix with topological connectivity includes:

[0013] Read the coordinates of discrete sampling points in the spatial geographic data, divide the coordinates of the discrete sampling points into spatial units according to preset fixed-size voxel units, and assign a unique spatial index code to each voxel unit;

[0014] Analyze the connectivity between the coordinates of the discrete sampling points. If there is a direct physical connection between the sampling points in two voxel units and there are no obstructions, then establish a bidirectional connection edge between the two voxel units and record the Euclidean distance value of the bidirectional connection edge.

[0015] By summarizing all voxel units that establish bidirectional connections and their connection relationships, an undirected graph structure containing a node list and an edge list is constructed, which is the three-dimensional spatial mesh matrix.

[0016] The rated DC voltage values ​​of the nodes in the electrical parameter dataset are matched and bound to the node list in the undirected graph structure, so that each node list item carries both spatial location information and electrical parameter information.

[0017] The spatial geographic data includes a sequence of terrain elevation points and records of underground pipeline distribution, while the electrical parameter dataset includes the rated DC voltage and expected load current values ​​for each node.

[0018] Furthermore, the identification of the target node set that satisfies the preset high power density condition includes:

[0019] By traversing each node in the initial three-dimensional power grid model, the total power of the load devices associated with the node is obtained, and the ratio of the total power of the load devices to the total power supply capacity of the feeder to which the node belongs is calculated to obtain the node load rate.

[0020] Obtain the node load rate statistics of all nodes in the initial three-dimensional power grid model, calculate the arithmetic mean and standard deviation of the node load rate, and set the sum of the arithmetic mean and the standard deviation as the high power density judgment threshold.

[0021] Nodes with a load rate greater than the high power density determination threshold are marked as high-density nodes, and all high-density nodes are aggregated to form the target node set.

[0022] For each high-density node in the target node set, its historical operating current peak record is further obtained. If the historical operating current peak record exceeds the preset safe current limit, an overload risk identifier is added to the attributes of the high-density node.

[0023] Further, the extraction of the electrical connection attributes and spatial distance attributes of its neighboring nodes includes:

[0024] Centered on the target node, search for all adjacent nodes with direct connecting edges in the three-dimensional spatial grid matrix to construct an adjacent node list;

[0025] For each adjacent node in the adjacent node list, read the conductor cross-sectional area data and conductor material type data recorded in the initial three-dimensional power grid model, and combine the conductor cross-sectional area data and conductor material type data into the electrical connection attribute corresponding to the adjacent node;

[0026] Calculate the shortest path length between the target node and the adjacent node in the three-dimensional spatial grid matrix, and use the shortest path length as the spatial distance attribute corresponding to the adjacent node;

[0027] The electrical connection attribute and spatial distance attribute corresponding to each adjacent node are packaged into an attribute record, and the attribute records are sorted in ascending order of the spatial distance attribute to generate an ordered attribute record sequence.

[0028] Further, the generation of path cost evaluation values ​​for multiple candidate power supply lines originating from the target node includes:

[0029] Each attribute record is extracted sequentially from the ordered attribute record sequence, the conductor cross-sectional area data and conductor material type data in the electrical connection attribute are parsed out, and a preset material impedance lookup table is queried to obtain the unit length resistance value corresponding to the conductor material type data;

[0030] Based on the conductor cross-sectional area data, the resistance value per unit length, and the spatial distance attribute, the estimated line voltage drop and estimated line power loss value of the candidate power supply line are calculated.

[0031] Read the expected load current value associated with the target node, calculate the line end voltage deviation rate by combining it with the estimated line voltage drop value, and calculate the line energy transmission efficiency by combining it with the estimated line loss power value.

[0032] The path cost evaluation value of the candidate power supply line is obtained by multiplying the line end voltage deviation rate, the line energy transmission efficiency, and the spatial distance attribute by preset weight coefficients and summing them. The path cost evaluation value is then associated with and stored with the corresponding candidate power supply line.

[0033] Furthermore, the identified line design schemes to be optimized include:

[0034] Receive the basic line layout scheme, decompose it into several continuous line segment units, and assign the start endpoint coordinates and end endpoint coordinates to each line segment unit;

[0035] Call the geographic information system interface to query the land use type data of the area traversed by the starting and ending coordinates of each line segment unit. The land use type data includes building, road, green space, and water body category identifiers.

[0036] The number of line segment units that pass through building areas in the basic route layout scheme is counted, and the proportion of the number of line segment units to the total number of line segment units is calculated to obtain the building crossing ratio.

[0037] If the building crossing ratio is greater than the preset acceptable crossing threshold, it is determined that there is spatial interference in the basic route layout scheme, and the route avoidance adjustment process is triggered.

[0038] If the building crossing ratio is not greater than the preset acceptable crossing threshold, then further check whether there is any overlap between the line segment unit and the pipeline location in the underground pipeline distribution record. If there is no overlap, then mark the basic line layout scheme as the line design scheme to be optimized.

[0039] Further, triggering the line avoidance adjustment process includes:

[0040] Identify conflicting line segment units in the basic line layout scheme that have spatial interference or overlap, and record the coordinates of the two endpoints of the conflicting line segment units;

[0041] In the three-dimensional spatial grid matrix, taking the midpoint of the conflict line segment unit as a reference, multiple candidate offset paths are generated in a direction perpendicular to the original line direction. The number of candidate offset paths is determined by a preset number of avoidance attempts.

[0042] For each candidate offset path, the sequence of voxel units it passes through is recalculated, and it is checked whether the sequence of voxel units contains obstacle markers or underground pipeline markers.

[0043] Candidate offset paths that do not contain obstacle markers or underground pipeline markers are selected as valid avoidance paths, and the total length increment of each valid avoidance path is calculated.

[0044] The candidate offset path with the smallest total length increment is selected to replace the conflicting line segment unit, generating an adjusted line layout scheme, and then the process returns to perform the overlay verification step.

[0045] Furthermore, it also includes a step of verifying the current carrying capacity of the line design scheme to be optimized:

[0046] Extract the conductor parameters of each power supply line in the line design scheme to be optimized. The conductor parameters include conductor cross-sectional area, conductor material and laying method.

[0047] Based on the conductor parameters, query the preset ambient temperature download flow correction curve to obtain the maximum allowable continuous current carrying capacity value of the conductor parameters at the current ambient temperature;

[0048] The current distribution of the line design to be optimized under full load operation is simulated, and the actual operating current value of each power supply line is calculated.

[0049] The actual operating current value of each power supply line is compared with its corresponding maximum allowable continuous current carrying capacity. If any actual operating current value exceeds its maximum allowable continuous current carrying capacity, the conductor cross-sectional area of ​​the target power supply line is upgraded and adjusted until the actual operating current value of all power supply lines is less than or equal to its corresponding maximum allowable continuous current carrying capacity.

[0050] The steps for upgrading and adjusting the cross-sectional area of ​​the conductor include:

[0051] Locate the target power supply line whose actual operating current value exceeds the maximum allowable continuous current carrying capacity, and obtain the current conductor cross-sectional area specification of the target power supply line;

[0052] In the preset material impedance comparison table, find the conductor cross-sectional area specification of the larger order of conductors that are the same material and laying method as the target power supply line conductor.

[0053] Calculate the estimated line voltage drop after adopting the larger conductor cross-sectional area specification, and determine whether the estimated line voltage drop meets the preset voltage quality requirements;

[0054] If satisfied, the conductor cross-sectional area specification of the target power supply line is updated to the larger conductor cross-sectional area specification, and the line attribute data in the line design scheme to be optimized is updated.

[0055] If the conditions are not met, continue searching for the next larger conductor cross-sectional area specification and repeat the process of judging the estimated line voltage drop value until a conductor cross-sectional area specification that meets the conditions is found or the maximum selectable specification limit is reached.

[0056] Furthermore, it also includes the step of generating the final construction drawing data:

[0057] Receive the optimized route design scheme after the load capacity has been checked and confirmed to be correct, and analyze all the node coordinates and route information in it;

[0058] According to the preset layer classification rules, the node coordinates are assigned to the equipment layout layer, the line routing information is assigned to the cable laying layer, and the underground pipeline distribution record is assigned to the auxiliary reference layer.

[0059] For each line in the cable laying layer, the corresponding line type and line width parameters are automatically matched according to its laying method and conductor cross-sectional area specifications, and the line length and voltage level information are marked.

[0060] The equipment layout layer, the cable laying layer, and the auxiliary reference layer are overlaid and merged to generate a two-dimensional plan construction drawing and a three-dimensional solid diagram containing complete engineering information. The two-dimensional plan construction drawing and the three-dimensional solid diagram are then packaged into a final construction drawing data package.

[0061] Furthermore, the present invention also includes a multi-line design system for medium-voltage DC distribution networks based on a three-dimensional model. The system includes a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of the multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model as described above.

[0062] Compared with the prior art, the beneficial effects of the present invention are:

[0063] The spatial geographic data of the medium-voltage DC distribution network is processed into a grid to generate a three-dimensional spatial grid matrix with topological connections. The electrical parameter dataset is directly mapped to the corresponding node positions of the three-dimensional spatial grid matrix to form an initial three-dimensional power grid model. The three-dimensional spatial grid matrix can completely present the three-dimensional spatial topology of the distribution network. The node-level mapping between electrical parameters and three-dimensional grid nodes allows spatial geographic information and electrical parameters to be presented synchronously in the same model system, eliminating the separation of spatial information and electrical parameters in the two-dimensional design mode. The topological connections inherent in the three-dimensional spatial grid matrix can clearly reflect the spatial and electrical association states between nodes of the distribution network, which fits the actual spatial deployment of the medium-voltage DC distribution network.

[0064] For target nodes that meet the preset high power density conditions, the electrical connection attributes and spatial distance attributes of their adjacent nodes are extracted. The path cost evaluation values ​​of multiple candidate power supply lines are calculated through dual-dimensional attribute calculation. The candidate power supply line with the smallest path cost evaluation value is selected as the basic line layout scheme. The joint calculation of electrical connection attributes and spatial distance attributes can simultaneously take into account the adaptability of line electrical transmission and the rationality of spatial layout. The path cost evaluation value can quantitatively distinguish the merits of candidate lines. The line corresponding to the smallest path cost evaluation value can be directly determined as the basic line with the best adaptability, avoiding the line layout deviation caused by single constraint selection. The superposition and verification of the basic line layout scheme and the three-dimensional spatial grid matrix can directly identify line segments with spatial conflicts. Triggering the line avoidance adjustment process can eliminate the spatial interference problem between the line and non-traffic areas and other infrastructure. Attached Figure Description

[0065] Figure 1 This is a flowchart illustrating the steps of the multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model as described in this invention.

[0066] Figure 2 Flowchart for generating a 3D spatial mesh matrix;

[0067] Figure 3 A flowchart for extracting attributes from adjacent nodes;

[0068] Figure 4 A comparison of electrical performance parameters for different conductor specifications;

[0069] Figure 5 Box-line diagram for line current carrying capacity verification and conductor specification optimization. Detailed Implementation

[0070] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0071] See Figure 1 This invention provides a multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model. The overall implementation process is as follows:

[0072] The system responds to the 3D model construction command by loading the spatial geographic data and electrical parameter dataset of the medium-voltage DC distribution network. The spatial geographic data is gridded to generate a 3D spatial grid matrix with topological connections, and the electrical parameter dataset is mapped to the corresponding node positions in the 3D spatial grid matrix, forming an initial 3D power grid model. All nodes in the initial 3D power grid model are traversed to identify a set of target nodes that meet the preset high power density conditions. For each target node in the target node set, the electrical connection attributes and spatial distance attributes of its neighboring nodes are extracted. Based on the electrical connection attributes and spatial distance attributes, the path cost evaluation values ​​of multiple candidate power supply lines originating from the target nodes are calculated, and the candidate power supply line with the smallest path cost evaluation value is selected as the basic line layout scheme. The basic line layout scheme is overlaid and verified with the 3D spatial grid matrix to detect whether there are conflicting line segments that cross non-travelable areas or spatially interfere with other infrastructure. If such segments exist, a line avoidance adjustment process is triggered; otherwise, the basic line layout scheme is determined as the line design scheme to be optimized.

[0073] In one embodiment of the present invention, when generating a three-dimensional spatial mesh matrix with topological connections, the system reads the coordinates of discrete sampling points from the spatial geographic data, spatially divides the coordinates of the discrete sampling points according to preset fixed-size voxel units, and assigns a unique spatial index code to each voxel unit. The system analyzes the connectivity between the coordinates of the discrete sampling points. If there is a direct physical connection between sampling points in two voxel units and no obstructions, a bidirectional connection edge is established between the two voxel units, and the Euclidean distance value of the bidirectional connection edge is recorded. The system summarizes all voxel units with established bidirectional connection edges and their connection relationships, constructing an undirected graph structure containing a node list and an edge list. This undirected graph structure is the three-dimensional spatial mesh matrix. The system matches and binds the rated DC voltage values ​​of nodes in the electrical parameter dataset with the node list in the undirected graph structure, so that each node list item carries both spatial location information and electrical parameter information. The spatial geographic data includes a sequence of terrain elevation points and underground pipeline distribution records, and the electrical parameter dataset includes the rated DC voltage values ​​and expected load current values ​​of each node.

[0074] In specific implementation, please refer to Figure 2 The system reads the coordinates of discrete sampling points from spatial geographic data. These coordinates originate from a geographic information system's mapping of a target area, such as an urban industrial zone. The spatial geographic data includes a sequence of terrain elevation points and records of underground pipeline distribution. The terrain elevation point sequence provides three-dimensional terrain surface information, while the underground pipeline distribution records indicate the location and type of underground pipelines. The system spatially divides the discrete sampling point coordinates according to preset fixed-size voxel units. The side length of each fixed-size voxel unit is set to 10 meters, dividing the entire area into a regular cubic grid. The system assigns a unique spatial index code to each voxel unit, using a three-dimensional array format, such as the combination of voxel unit indices in the x, y, and z directions. In some embodiments, the system analyzes the connectivity between discrete sampling point coordinates. If there is a direct physical connection between sampling points within two voxel units without any obstructions, a bidirectional connection edge is established between the two voxel units. The system records the Euclidean distance value of the bidirectional connection edge, calculated using the formula:

[0075]

[0076] in: This represents the average coordinates of the sampling points within voxel unit A. Let represent the average coordinates of the sampling points within voxel unit B, and D represent the Euclidean distance between voxel unit A and voxel unit B. The system summarizes all voxel units with bidirectional connections and their connections, constructing an undirected graph structure containing a node list and an edge list. The undirected graph structure is a three-dimensional spatial mesh matrix. Each node in the node list corresponds to a voxel unit, and each edge in the edge list records the connection relationship and Euclidean distance value between voxel units.

[0077] Optionally, the system matches and binds the rated DC voltage values ​​of nodes in the electrical parameter dataset with the node list in the undirected graph structure. The electrical parameter dataset contains the rated DC voltage values ​​and expected load current values ​​of each node. For example, the rated DC voltage value of a node (e.g., 1500 volts) comes from the distribution network planning data. The system ensures that each node list item carries both spatial location information and electrical parameter information. The spatial location information comes from the center coordinates of the voxel cell, and the electrical parameter information includes the node's rated DC voltage value and expected load current value. In the data comparison, the system uses voxel cells of different fixed sizes for spatial partitioning, with the side lengths of the fixed-size voxel cells set to 5 meters, 10 meters, and 20 meters. The system compares the number of nodes and edges in the generated three-dimensional spatial mesh matrix. When the side length of a fixed-size voxel is 5 meters, the 3D spatial mesh matrix contains more nodes and edges, increasing the mesh resolution but also increasing the computational cost. When the side length of a fixed-size voxel is 20 meters, the 3D spatial mesh matrix contains fewer nodes and edges, reducing the computational cost but potentially ignoring detailed connections. When the side length of a fixed-size voxel is 10 meters, the 3D spatial mesh matrix achieves a balance between the number of nodes and edges, making it suitable for most power distribution network design scenarios.

[0078] It is understandable that when the system analyzes the connectivity between discrete sampling point coordinates, the determination of direct physical connections is based on the Euclidean distance between sampling points and obstacle detection. If the Euclidean distance between sampling points within two voxel cells is less than a preset threshold and there are no buildings or underground pipeline markers on the path, then a direct physical connection is determined to exist. After the system establishes bidirectional connection edges, the undirected graph structure is stored in memory in the form of an adjacency list for easy subsequent topology traversal. In specific implementation, when the system binds the electrical parameter dataset, the node list items are expanded into structure data, which includes spatial index encoding, voxel cell center coordinates, node rated DC voltage values, and expected load current values. The terrain elevation point sequence in the spatial geographic data is used to correct the voxel cell elevation, and the underground pipeline distribution record is used to identify obstacles in connectivity analysis, avoiding the establishment of connection edges in non-travelable areas.

[0079] In one embodiment of the present invention, when a target node set that meets the preset high power density condition is identified, the system traverses each node in the initial three-dimensional power grid model, obtains the total power of the load devices associated with the node, and calculates the ratio of the total power of the load devices to the total power supply capacity of the feeder to which the node belongs, thus obtaining the node load rate. The system obtains the node load rate statistics of all nodes in the initial three-dimensional power grid model, calculates the arithmetic mean and standard deviation of the node load rate, and sets the sum of the arithmetic mean and standard deviation as the high power density judgment threshold. The system marks nodes with a node load rate greater than the high power density judgment threshold as high-density nodes, and aggregates all high-density nodes to form a target node set. For each high-density node in the target node set, the system further obtains its historical operating current peak record. If the historical operating current peak record exceeds the preset safe current limit, an overload risk identifier is added to the high-density node attributes.

[0080] In practical implementation, the system traverses each node in the initial 3D power grid model, which integrates spatial location and electrical parameter information. The system obtains the total power of the load devices associated with each node, which is obtained by summing the nameplate power of all electrical devices connected to that node. The system calculates the ratio of the total power of the load devices to the total power supply capacity of the feeder to which the node belongs, thus obtaining the node load factor. In some embodiments, the system obtains node load factor statistics for all nodes in the initial 3D power grid model. The node load factor statistics include a set of node load factor values ​​for all nodes. The system calculates the arithmetic mean and standard deviation of the node load factors and sets the sum of the arithmetic mean and standard deviation as the high power density judgment threshold. The calculation of the high power density judgment threshold follows the formula... , in the formula The arithmetic mean of the node load rate. The standard deviation of node load rate This represents the high power density threshold. The system marks nodes with a load factor greater than the high power density threshold as high-density nodes and aggregates all high-density nodes to form the target node set.

[0081] Optionally, for each high-density node in the target node set, the system further obtains its historical peak operating current records, which are derived from the distribution network monitoring system's operating data over the past year. The system determines whether the historical peak operating current records exceed a preset safe current limit, which is determined based on the conductor cross-sectional area and laying environment. If the historical peak operating current records exceed the preset safe current limit, the system adds an overload risk flag to the high-density node attributes. In specific implementation, the high power density judgment threshold is set using a dynamic calculation method. For example, in a distribution network area containing 50 nodes, the system calculates the arithmetic mean of the load rates of all nodes. The standard deviation is 0.65. If the value is 0.18, then the high power density threshold is set. The threshold value was set to 0.83, and nodes with a load rate greater than 0.83 were marked as high-density nodes. In the data comparison, the system compared the differences between using a dynamic threshold and a fixed threshold to identify high-density nodes. The fixed threshold method uniformly marked nodes with a load rate greater than 0.8 as high-density nodes, while the dynamic threshold method calculated a threshold of 0.83 based on the actual load distribution of the current network. The set of high-density nodes identified by the dynamic threshold better reflects the statistical outlier characteristics of the current network load and avoids the potential inadequacies of the fixed threshold.

[0082] It is understood that the total power supply capacity of the feeder to which a node belongs is a fixed value, derived from the rated capacity of the upstream substation outgoing switches or distribution transformers. When the system traverses the nodes of the initial 3D power grid model, the node load rate calculation is performed simultaneously, and the calculation results are stored together with the node spatial index and electrical parameters. In some embodiments, historical operating current peak records are stored in time-series format, and the system obtains the maximum current value of high-density nodes during specific time periods, such as the summer peak electricity consumption period, by querying the database. The overload risk indicator is a Boolean attribute field added to the attribute structure of high-density nodes to indicate areas requiring special attention in subsequent line design processes. The system aggregates high-density nodes to form a target node set, which serves as the starting point for subsequent multi-line design, ensuring that newly added lines can effectively serve densely loaded areas.

[0083] In one embodiment of the present invention, when extracting the electrical connection attributes and spatial distance attributes of adjacent nodes of the target node, refer to... Figure 3Centered on the target node, a list of all adjacent nodes with direct connections is constructed by searching the 3D spatial grid matrix. For each adjacent node in the list, the conductor cross-sectional area and conductor material type data recorded in the initial 3D power grid model are read and combined to form the electrical connection attribute corresponding to that adjacent node. The shortest path length between the target node and adjacent nodes in the 3D spatial grid matrix is ​​calculated and used as the spatial distance attribute corresponding to the adjacent node. The electrical connection attribute and spatial distance attribute corresponding to each adjacent node are packaged into an attribute record, and the attribute records are sorted in ascending order of spatial distance attribute to generate an ordered attribute record sequence. When generating path cost evaluation values ​​for multiple candidate power supply lines originating from the target node, each attribute record is sequentially extracted from the ordered attribute record sequence, and the conductor cross-sectional area and conductor material type data in the electrical connection attribute are parsed out. A pre-set material impedance lookup table is consulted to obtain the unit length resistance value corresponding to the conductor material type data. Based on conductor cross-sectional area data, resistance per unit length, and spatial distance attributes, the estimated voltage drop and estimated power loss of candidate power supply lines are calculated. The expected load current associated with the target node is read, and the voltage deviation rate at the line end is calculated using the estimated voltage drop. The line energy transmission efficiency is then calculated using the estimated power loss. The voltage deviation rate at the line end, the line energy transmission efficiency, and the spatial distance attribute are multiplied by preset weighting coefficients and summed to obtain the path cost evaluation value of the candidate power supply line. This path cost evaluation value is then associated with and stored with the corresponding candidate power supply line.

[0084] In practical implementation, taking a specific target node A in the target area as an example, the system searches for all adjacent nodes with direct connections to it in the three-dimensional spatial grid matrix, using target node A as the center, and constructs an adjacent node list containing adjacent nodes B, C, and D. For each adjacent node in the adjacent node list, the system reads the conductor cross-sectional area data and conductor material type data recorded in the initial three-dimensional power grid model. For example, the conductor cross-sectional area data is 300 square millimeters, and the conductor material type data is "copper". The system combines the conductor cross-sectional area data and conductor material type data to form the electrical connection attribute corresponding to that adjacent node. The system calculates the shortest path length between target node A and each adjacent node in the three-dimensional spatial grid matrix, and uses the shortest path length as the spatial distance attribute corresponding to the adjacent node. The shortest path length is obtained by accumulating the Euclidean distances between the centers of voxel elements in the three-dimensional spatial grid matrix. The system packages the electrical connection attribute and spatial distance attribute corresponding to each adjacent node into an attribute record, and sorts the attribute records in ascending order of spatial distance attribute to generate an ordered sequence of attribute records. For example, the distance between adjacent node B and adjacent node C is 50 meters, the distance between adjacent node C and adjacent node D is 80 meters, and the distance between adjacent node D and adjacent node D is 65 meters. The sorted sequence is [(attribute of adjacent node B), (attribute of adjacent node D), (attribute of adjacent node C)].

[0085] In some embodiments, the system sequentially extracts each attribute record from an ordered sequence of attribute records, parses the conductor cross-sectional area data and conductor material type data from the electrical connection attributes, and queries a preset material impedance lookup table to obtain the unit length resistance value corresponding to the conductor material type data. Based on the conductor cross-sectional area data, unit length resistance value, and spatial distance attribute, the system calculates the estimated line voltage drop and estimated line loss power value of the candidate power supply line. The system reads the expected load current value associated with target node A, calculates the line end voltage deviation rate in conjunction with the estimated line voltage drop value, and calculates the line energy transmission efficiency in conjunction with the estimated line loss power value. The system obtains the average value of the spatial distance attributes of all lines in the current three-dimensional power grid model as the distance normalization benchmark, divides the spatial distance attribute of the candidate power supply line by this distance normalization benchmark, and obtains the normalized relative distance value. The system multiplies the line end voltage deviation rate, line energy transmission efficiency, and normalized relative distance value by preset weighting coefficients and then sums them to obtain the path cost evaluation value of the candidate power supply line. The calculation formula for the path cost evaluation value is:

[0086]

[0087] in: This represents the path cost evaluation value. This indicates the voltage deviation rate at the end of the line. Indicates the line energy transmission efficiency. This represents the normalized relative distance value. , , The preset weighting coefficients, representing the voltage deviation rate at the end of the line, the energy transmission efficiency of the line, and the normalized relative distance value, are respectively used to associate and store the path cost evaluation value with the corresponding candidate power supply line.

[0088] Optionally, when calculating the estimated line voltage drop and estimated line power loss, the system uses the expected load current, resistance per unit length, conductor cross-sectional area, and spatial distance attributes based on DC circuit principles. The distance normalization benchmark is a dynamically calculated parameter used to eliminate the influence of absolute distance on the evaluation results under different network scales, ensuring the comparability of evaluation values ​​across different scenarios. In the data comparison, the system calculates the path cost evaluation value for candidate lines from target node A to different adjacent nodes. The expected load current of target node A is 200 amperes, the calculated distance normalization benchmark is 200 meters, and the weighting coefficients are set as follows: , , The comparison results are shown below: For the candidate line to adjacent node B, the spatial distance attribute is 50 meters, the calculated voltage deviation rate at the line end is 0.8%, the calculated energy transmission efficiency is 99.2%, and the normalized relative distance value is... Path cost evaluation value The candidate line to adjacent node C has a spatial distance attribute of 80 meters, a calculated line-end voltage deviation rate of 1.5%, a calculated line energy transmission efficiency of 98.5%, and a normalized relative distance value. Path cost evaluation value The candidate line to adjacent node D has a spatial distance attribute of 65 meters, a calculated line-end voltage deviation rate of 1.1%, a calculated line energy transmission efficiency of 98.9%, and a normalized relative distance value. Path cost evaluation value By comparison, the path cost to adjacent node D has the lowest evaluation value.

[0089] It's understandable that generating an ordered sequence of attribute records ensures the system prioritizes evaluating adjacent nodes with closer spatial distances, which aligns with the general principle of route design to minimize path length. The weighting coefficients used when calculating the path cost evaluation value... , , These are preset constants used to balance the importance of voltage quality, energy efficiency, and relative line length in the design. The line-end voltage deviation rate is the absolute percentage of the difference between the line-end voltage and the rated voltage; the line energy transmission efficiency is the ratio of the power at the line-end to the power at the line-starting point, both being dimensionless ratios. The normalized relative distance value is also a dimensionless ratio. The system associates and stores path cost assessment values ​​with candidate power supply lines, forming a mapping table that provides a direct decision-making basis for subsequent selection of basic line layout schemes.

[0090] In one embodiment of the present invention, when a basic route layout scheme is determined as a route design scheme to be optimized, the system receives the basic route layout scheme, decomposes it into several continuous line segment units, and assigns start and end coordinates to each line segment unit. The system calls the geographic information system interface to query the land use type data of the areas traversed by the start and end coordinates of each line segment unit. The land use type data includes building, road, green space, and water body category identifiers. The system counts the number of line segment units that cross building areas in the basic route layout scheme and calculates the proportion of the number of such line segment units to the total number of line segment units to obtain the building crossing ratio. If the building crossing ratio is greater than a preset acceptable crossing threshold, it is determined that the basic route layout scheme has spatial interference, triggering the route avoidance adjustment process. If the building crossing ratio is not greater than the preset acceptable crossing threshold, it further checks whether there is any overlap between the line segment units and the pipeline locations in the underground pipeline distribution record. If there is no overlap, the basic route layout scheme is marked as a route design scheme to be optimized. After the route avoidance adjustment process is triggered, the system identifies conflicting line segment units in the basic route layout scheme that exhibit spatial interference or overlap, and records the coordinates of the two endpoints of these conflicting line segment units. In the 3D spatial mesh matrix, using the midpoint of the conflicting line segment unit as a reference, multiple candidate offset paths are generated in a direction perpendicular to the original route. The number of candidate offset paths is determined by a preset number of avoidance attempts. For each candidate offset path, the sequence of voxel units it traverses is recalculated, and the system checks whether the voxel unit sequence contains obstacle markers or underground pipeline markers. The system selects candidate offset paths that do not contain obstacle markers or underground pipeline markers as valid avoidance paths and calculates the total length increment of each valid avoidance path. The candidate offset path with the smallest total length increment is selected to replace the conflicting line segment unit, generating the adjusted route layout scheme, and then returns to perform the overlay verification step.

[0091] In implementation, the system receives the basic power line layout scheme generated in previous steps. This scheme includes power line paths originating from multiple high-power-density target nodes. The system decomposes the basic power line layout scheme into several continuous line segment units, each representing a straight path. The system assigns start and end coordinates to each line segment unit, derived from the center point coordinates of voxel cells in a 3D spatial grid matrix. The system calls a Geographic Information System (GIS) interface to query land use type data for the areas traversed by the start and end coordinates of each line segment unit. The GIS-returned land use type data includes building, road, green space, and water body category identifiers. The system counts the number of line segment units crossing building areas in the basic power line layout scheme and calculates the proportion of these line segment units to the total number of line segment units, obtaining the building crossing ratio. The system's preset acceptable crossing threshold is 0.05. If the building crossing ratio is greater than 0.05, the basic power line layout scheme is considered to have spatial interference, triggering a line avoidance adjustment process. If the building penetration ratio is not greater than 0.05, the system will further check whether there is any overlap between the line segment unit and the pipeline location in the underground pipeline distribution record. The system will make a judgment by comparing the coordinate range of the line segment unit with the coordinate range of the underground pipeline. If there is no overlap, the basic line layout scheme will be marked as the line design scheme to be optimized.

[0092] In some embodiments, the system identifies conflicting line segments that spatially interfere or overlap in the basic route layout scheme and records the coordinates of the two endpoints of these conflicting line segments. In a three-dimensional spatial grid matrix, using the midpoint of the conflicting line segment as a reference, multiple candidate offset paths are generated in a direction perpendicular to the original route. The number of candidate offset paths is determined by a preset number of avoidance attempts, which is set to 5. The system generates a total of 5 candidate offset paths: 2 to the left, 2 to the right, and 1 vertically upward. For each candidate offset path, the system recalculates the sequence of voxel cells it traverses and checks whether the voxel cell sequence contains obstacle markers or underground pipeline markers. Obstacle markers include buildings and water bodies, while underground pipeline markers are derived from spatial geographic data. The system selects candidate offset paths that do not contain obstacle markers or underground pipeline markers as valid avoidance paths and calculates the total length increment for each valid avoidance path. The total length increment is calculated using the formula:

[0093]

[0094] in: Indicates the increment of total length. Indicates the total length of the candidate offset paths. This indicates the length of the original conflicting line segment unit. The system selects the candidate offset path with the smallest total length increment to replace the conflicting line segment unit, generates the adjusted line layout scheme, and returns to perform the overlay verification step.

[0095] Optionally, in the data comparison, the system compared the impact of different avoidance attempt counts on the results of the route avoidance adjustment process. Table 1 shows the comparison of the number of candidate offset paths generated by the system, the number of effective avoidance paths, and the final selected total length increment when the number of avoidance attempts is set to 3, 5, and 7, respectively, under the same conflict line segment unit scenario. When the number of avoidance attempts is 3, the system generates fewer candidate offset paths, and may not be able to find the optimal avoidance path; when the number of avoidance attempts is 7, the system's computational load increases, but it may find a path with a smaller total length increment. Through comparison, a balance is achieved between computational efficiency and avoidance effect when the number of avoidance attempts is 5. When the system calculates the total length increment, the total length of the candidate offset path is obtained by accumulating the Euclidean distance between each voxel unit it passes through. The route avoidance adjustment process is an iterative process. After each adjustment, the newly generated route layout scheme needs to be re-overlayed and verified until the building crossing ratio meets the requirements and there is no underground pipeline overlap. See Table 1.

[0096] Table 1: Comparison of the effects of different numbers of avoidance attempts

[0097] 3 3 2 15.2 5 5 4 9.8 7 7 5 9.5

[0098] It is understandable that the building crossing ratio is a quantitative indicator for assessing the degree to which a route occupies building space, and the acceptable crossing threshold is set according to engineering specifications and regional planning requirements. Checking for overlap between line segment units and underground pipelines is to prevent construction damage to existing pipelines and ensure project safety. In practice, when generating candidate offset paths, the system uses the midpoint of the conflicting line segment unit as a reference and generates parallel paths at preset offset distance intervals in a plane perpendicular to the original route. The preset offset distance interval is typically set to the width of a standard cable trench or pipe gallery. When the system checks the markers in the voxel unit sequence, the obstacle markers are pre-annotated based on spatial geographic data during the 3D spatial grid matrix construction stage. The route avoidance adjustment process may require multiple adjustment attempts on the same line segment unit; each adjustment generates a new candidate offset path and evaluates it. The system selects the path with the smallest total length increment, adhering to the principle of economic efficiency in route design, striving to avoid obstacles while minimizing the increase in route length.

[0099] See Figure 4In the current-carrying capacity verification and conductor selection stages of medium-voltage DC distribution network line design, the electrical performance parameters of different conductor cross-sectional area specifications exhibit clear quantitative patterns, providing a core basis for line current-carrying capacity verification and conductor cross-sectional area upgrade adjustments. Specifically, this dual-axis composite chart uses conductor cross-sectional area specifications (120mm², 185mm², 240mm², 300mm²) as the horizontal axis, the left vertical axis represents unit resistance (Ω / km), and the right vertical axis represents the maximum allowable current-carrying capacity (A). The bar chart corresponds to the unit resistance index, and the line chart corresponds to the maximum allowable current-carrying capacity index. From the perspective of electrical characteristics, there is a significant negative correlation between unit resistance and conductor cross-sectional area: the unit resistance of 120mm² conductors is the highest (approximately 0.152Ω / km). As the cross-sectional area increases to 185mm², 240mm², and 300mm², the unit resistance decreases to approximately 0.099Ω / km, 0.076Ω / km, and 0.061Ω / km, respectively. This conforms to the physical law of the conductor resistance formula R=ρL / S (where ρ is the conductor resistivity, L is the line length, and S is the cross-sectional area). The larger the cross-sectional area, the smaller the resistance per unit length, and the lower the line voltage drop and line loss. Correspondingly, there is a significant positive correlation between the maximum allowable current carrying capacity and conductor cross-sectional area: the maximum allowable current carrying capacity of 120mm² conductors is the lowest (approximately 320A). As the cross-sectional area increases, the current carrying capacity increases to approximately 410A, 480A, and 545A, respectively. This demonstrates that larger cross-sectional area conductors have a stronger current carrying capacity, meeting the high load power supply requirements of high power density nodes. In the current carrying capacity verification process, graph data serves as the core input: when the actual operating current of a power supply line in the line design scheme to be optimized exceeds the maximum allowable current carrying capacity of the current specification, the system selects conductor specifications with larger cross-sectional areas step by step according to the pattern of this parameter. At the same time, it recalculates the line voltage drop in combination with the unit resistance data to verify whether the voltage quality requirements are met, until the actual operating current of all lines does not exceed the maximum allowable current carrying capacity of the corresponding specification, and finally completes the conductor selection optimization to ensure the safe and economical operation of the medium-voltage DC distribution network.

[0100] In one embodiment of the present invention, the system extracts the conductor parameters of each power supply line in the line design scheme to be optimized. The conductor parameters include conductor cross-sectional area, conductor material, and laying method. The line design scheme to be optimized is a scheme after spatial verification and avoidance adjustment. The system queries a preset ambient temperature current correction curve based on the conductor parameters. The ambient temperature is taken as the local summer high average temperature of 35 degrees Celsius, and obtains the maximum allowable continuous current carrying capacity of the conductor parameters under the current ambient temperature. The system simulates the current distribution of the line design scheme to be optimized under full load operation. Based on the expected load current value of the nodes and the network topology, it calculates the actual operating current value of each power supply line. The system compares the actual operating current value of each power supply line with its corresponding maximum allowable continuous current carrying capacity. If any actual operating current value exceeds its maximum allowable continuous current carrying capacity, the conductor cross-sectional area of ​​the target power supply line is upgraded and adjusted until the actual operating current value of all power supply lines is less than or equal to its corresponding maximum allowable continuous current carrying capacity.

[0101] In some embodiments, when upgrading the conductor cross-sectional area, the system locates the target power supply line whose actual operating current exceeds the maximum allowable continuous current carrying capacity, and obtains the current conductor cross-sectional area specification of the target power supply line. In a preset material impedance lookup table, a larger conductor cross-sectional area specification with the same conductor material and laying method as the target power supply line is found. The estimated line voltage drop after adopting the larger conductor cross-sectional area specification is calculated, and it is determined whether the estimated line voltage drop meets the preset voltage quality requirements. The estimated line voltage drop is calculated using the formula:

[0102]

[0103] in: This indicates the estimated line voltage drop after adopting the new specifications. This indicates the actual operating current value of the target power supply line. Represents the resistivity of a conductor material. Indicates the length of the target power supply line. This indicates the cross-sectional area of ​​the next larger conductor size. If the preset voltage quality requirements are met, the conductor cross-sectional area of ​​the target power supply line is updated to the next larger conductor size, and the line attribute data in the line design scheme to be optimized is updated. If not, the search continues for the next larger conductor cross-sectional area, and the process of estimating the line voltage drop is repeated until a conductor cross-sectional area that meets the conditions is found or the maximum selectable size limit is reached.

[0104] Optionally, in the data comparison, the current-carrying capacity of a specific power supply line in the optimized line design scheme is checked. This line uses copper conductors, is laid in an underground pipe gallery, and has a current conductor cross-sectional area of ​​240 square millimeters. The maximum permissible continuous current-carrying capacity found at 35 degrees Celsius is 490 amperes. System simulation calculations show that the actual operating current under full load is 520 amperes, exceeding the maximum permissible continuous current-carrying capacity. The system then finds a larger conductor cross-sectional area of ​​300 square millimeters in the material impedance comparison table, with a corresponding maximum permissible continuous current-carrying capacity of 580 amperes. The system calculates the estimated line voltage drop using the 300 square millimeter conductor. The calculated result is 4.2 volts, which meets the preset voltage quality requirement that the line voltage drop should not exceed 2% of the rated voltage (i.e., 30 volts). The system updates the conductor cross-sectional area specification of the line to 300 square millimeters and re-performs the simulation calculation. The updated actual operating current value of 520 amps is less than the new maximum allowable continuous current carrying capacity value of 580 amps, and the verification is passed. If the initially searched higher specification does not meet the voltage quality requirements, the system will continue to search for specifications such as 400 square millimeters and perform the same judgment.

[0105] In practice, the system receives the optimized route design scheme after its current carrying capacity has been verified and confirmed to be correct, and analyzes all node coordinates and route information. According to preset layer classification rules, node coordinates are assigned to the equipment layout layer, route information to the cable laying layer, and underground pipeline distribution records to the auxiliary reference layer. For each route in the cable laying layer, the system automatically matches the corresponding line type and line width parameters based on its laying method and conductor cross-sectional area specifications. For example, direct underground burial uses a dashed line type, while pipe gallery laying uses a solid line type, and the line length and voltage level information are marked. The equipment layout layer, cable laying layer, and auxiliary reference layer are overlaid and merged to generate a two-dimensional plan construction drawing and a three-dimensional solid model containing complete engineering information, and then packaged into a final construction drawing data package.

[0106] See Figure 5Box plots were used to compare and analyze the actual operating current of the line with the adjusted allowable current carrying capacity. Specifically, the left box represents the actual operating current distribution of each power supply line in the line design to be optimized. The upper and lower boundaries of the box correspond to the upper quartile (Q3, approximately 530A) and lower quartile (Q1, approximately 380A), respectively. The horizontal line inside the box represents the median current (approximately 465A), the triangular marker represents the mean current (approximately 455A), and the upper and lower whiskers represent the maximum (approximately 575A) and minimum (approximately 330A), respectively, fully presenting the current distribution characteristics and dispersion under full-load operation. The right box represents the allowable current carrying capacity distribution after the conductor specification upgrade. The upper and lower quartiles of the box are approximately 590A and 465A, respectively, the median is approximately 530A, and the mean is approximately 540A. The upper and lower whiskers correspond to the maximum (approximately 710A) and minimum (approximately 420A), intuitively demonstrating the improvement in the line's current carrying capacity after the conductor cross-sectional area upgrade. The comparison results show that the median, mean, upper and lower quartiles, and extreme values ​​of the adjusted allowable current carrying capacity are all significantly higher than the corresponding statistics of the actual operating current. This verifies the effectiveness of the current carrying capacity verification and conductor specification optimization process: by upgrading the conductor cross-sectional area of ​​lines whose actual operating current exceeds the initial allowable current carrying capacity (e.g., upgrading 240mm² copper core cables to 300mm²), the actual operating current of all lines meets the safety constraint of "not exceeding the maximum allowable continuous current carrying capacity," while ensuring that the line voltage drop meets voltage quality requirements. This box plot statistically quantifies the improvement in line current carrying capacity before and after optimization, providing intuitive data support for the safety, economy, and reliability of medium-voltage DC distribution network line design.

[0107] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model, characterized in that, include: In response to the 3D model building command, load the spatial geographic data and electrical parameter dataset of the medium-voltage DC distribution network; The spatial geographic data is processed into a grid to generate a three-dimensional spatial grid matrix with topological connections, and the electrical parameter dataset is mapped to the corresponding node positions of the three-dimensional spatial grid matrix to form an initial three-dimensional power grid model. Traverse all nodes in the initial three-dimensional power grid model, identify the target node set that meets the preset high power density condition, and extract the electrical connection attributes and spatial distance attributes of its neighboring nodes for each target node in the target node set. The path cost evaluation values ​​of multiple candidate power supply lines originating from the target node are calculated based on the electrical connection attributes and spatial distance attributes, and the candidate power supply line with the smallest path cost evaluation value is selected as the basic line layout scheme. The basic route layout scheme is superimposed and verified with the three-dimensional spatial grid matrix to detect whether there are conflicting line segments that cross non-traffic areas or spatially interfere with other infrastructure. If they exist, the route avoidance and adjustment process is triggered. If they do not exist, the basic route layout scheme is determined as the route design scheme to be optimized. The generation of a three-dimensional spatial mesh matrix with topological connectivity includes: Read the coordinates of discrete sampling points in the spatial geographic data, divide the coordinates of the discrete sampling points into spatial units according to preset fixed-size voxel units, and assign a unique spatial index code to each voxel unit; Analyze the connectivity between the coordinates of the discrete sampling points. If there is a direct physical connection between the sampling points in two voxel units and there are no obstructions, then establish a bidirectional connection edge between the two voxel units and record the Euclidean distance value of the bidirectional connection edge. By summarizing all voxel units that establish bidirectional connections and their connection relationships, an undirected graph structure containing a node list and an edge list is constructed, which is the three-dimensional spatial mesh matrix. The rated DC voltage values ​​of the nodes in the electrical parameter dataset are matched and bound to the node list in the undirected graph structure, so that each node list item carries both spatial location information and electrical parameter information. The spatial geographic data includes a sequence of topographic elevation points and a record of underground pipeline distribution; the electrical parameter dataset includes the rated DC voltage value and expected load current value of each node. The extraction of the electrical connection attributes and spatial distance attributes of its adjacent nodes includes: Centered on the target node, search for all adjacent nodes with direct connecting edges in the three-dimensional spatial grid matrix to construct an adjacent node list; For each adjacent node in the adjacent node list, read the conductor cross-sectional area data and conductor material type data recorded in the initial three-dimensional power grid model, and combine the conductor cross-sectional area data and conductor material type data into the electrical connection attribute corresponding to the adjacent node; Calculate the shortest path length between the target node and the adjacent node in the three-dimensional spatial grid matrix, and use the shortest path length as the spatial distance attribute corresponding to the adjacent node; The electrical connection attribute and spatial distance attribute corresponding to each adjacent node are packaged into an attribute record, and the attribute records are sorted in ascending order of the spatial distance attribute to generate an ordered attribute record sequence.

2. The multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model according to claim 1, characterized in that, The identified set of target nodes that meet the preset high power density conditions includes: By traversing each node in the initial three-dimensional power grid model, the total power of the load devices associated with the node is obtained, and the ratio of the total power of the load devices to the total power supply capacity of the feeder to which the node belongs is calculated to obtain the node load rate. Obtain the node load rate statistics of all nodes in the initial three-dimensional power grid model, calculate the arithmetic mean and standard deviation of the node load rate, and set the sum of the arithmetic mean and the standard deviation as the high power density judgment threshold. Nodes with a load rate greater than the high power density determination threshold are marked as high-density nodes, and all high-density nodes are aggregated to form the target node set. For each high-density node in the target node set, its historical operating current peak record is further obtained. If the historical operating current peak record exceeds the preset safe current limit, an overload risk identifier is added to the attributes of the high-density node.

3. The multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model according to claim 2, characterized in that, The generation of path cost evaluation values ​​for multiple candidate power supply lines originating from the target node includes: Each attribute record is extracted sequentially from the ordered attribute record sequence, and the conductor cross-sectional area data and conductor material type data in the electrical connection attribute are parsed out. A preset material impedance lookup table is then queried to obtain the unit length resistance value corresponding to the conductor material type data. Based on the conductor cross-sectional area data, the resistance value per unit length, and the spatial distance attribute, the estimated line voltage drop and estimated line power loss value of the candidate power supply line are calculated. Read the expected load current value associated with the target node, calculate the voltage deviation rate at the end of the line in combination with the estimated line voltage drop value, and calculate the line energy transmission efficiency in combination with the estimated line loss power value. The path cost evaluation value of the candidate power supply line is obtained by multiplying the line end voltage deviation rate, the line energy transmission efficiency, and the spatial distance attribute by preset weight coefficients and summing them. The path cost evaluation value is then associated with and stored with the corresponding candidate power supply line.

4. The multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model according to claim 3, characterized in that, The identified line design schemes to be optimized include: Receive the basic line layout scheme, decompose it into several continuous line segment units, and assign the start endpoint coordinates and end endpoint coordinates to each line segment unit; Call the geographic information system interface to query the land use type data of the area traversed by the starting and ending endpoint coordinates of each line segment unit. The land use type data includes building, road, green space, and water body category identifiers. The number of line segment units that pass through building areas in the basic route layout scheme is counted, and the proportion of the number of line segment units to the total number of line segment units is calculated to obtain the building crossing ratio. If the building crossing ratio is greater than the preset acceptable crossing threshold, it is determined that there is spatial interference in the basic route layout scheme, and the route avoidance adjustment process is triggered. If the building crossing ratio is not greater than the preset acceptable crossing threshold, then further check whether there is any overlap between the line segment unit and the pipeline location in the underground pipeline distribution record. If there is no overlap, then mark the basic line layout scheme as the line design scheme to be optimized.

5. The multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model according to claim 4, characterized in that, Triggering the aforementioned line avoidance adjustment process includes: Identify conflicting line segment units in the basic line layout scheme that have spatial interference or overlap, and record the coordinates of the two endpoints of the conflicting line segment units; In the three-dimensional spatial grid matrix, taking the midpoint of the conflict line segment unit as a reference, multiple candidate offset paths are generated in a direction perpendicular to the original line direction. The number of candidate offset paths is determined by a preset number of avoidance attempts. For each candidate offset path, the sequence of voxel units it passes through is recalculated, and it is checked whether the sequence of voxel units contains obstacle markers or underground pipeline markers. Candidate offset paths that do not contain obstacle markers or underground pipeline markers are selected as valid avoidance paths, and the total length increment of each valid avoidance path is calculated. The candidate offset path with the smallest total length increment is selected to replace the conflicting line segment unit, generating an adjusted line layout scheme, and then the process returns to perform the overlay verification step.

6. The multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model according to claim 5, characterized in that, It also includes the step of verifying the current carrying capacity of the line design scheme to be optimized: Extract the conductor parameters of each power supply line in the line design scheme to be optimized. The conductor parameters include conductor cross-sectional area, conductor material and laying method. Based on the conductor parameters, query the preset ambient temperature download flow correction curve to obtain the maximum allowable continuous current carrying capacity value of the conductor parameters at the current ambient temperature; The current distribution of the line design to be optimized under full load operation is simulated, and the actual operating current value of each power supply line is calculated. The actual operating current value of each power supply line is compared with its corresponding maximum allowable continuous current carrying capacity. If any actual operating current value exceeds its maximum allowable continuous current carrying capacity, the conductor cross-sectional area of ​​the target power supply line is upgraded and adjusted until the actual operating current value of all power supply lines is less than or equal to its corresponding maximum allowable continuous current carrying capacity. The steps for upgrading and adjusting the cross-sectional area of ​​the conductor include: Locate the target power supply line whose actual operating current value exceeds the maximum allowable continuous current carrying capacity, and obtain the current conductor cross-sectional area specification of the target power supply line; In the preset material impedance comparison table, find the conductor cross-sectional area specification of the larger order of conductors that are the same material and laying method as the target power supply line conductor. Calculate the estimated line voltage drop after adopting the larger conductor cross-sectional area specification, and determine whether the estimated line voltage drop meets the preset voltage quality requirements; If satisfied, the conductor cross-sectional area specification of the target power supply line is updated to the larger conductor cross-sectional area specification, and the line attribute data in the line design scheme to be optimized is updated. If the conditions are not met, continue searching for the next larger conductor cross-sectional area specification and repeat the process of judging the estimated line voltage drop value until a conductor cross-sectional area specification that meets the conditions is found or the maximum selectable specification limit is reached.

7. The multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model according to claim 6, characterized in that, It also includes the step of generating the final construction drawing data: Receive the optimized route design scheme after the load capacity has been checked and confirmed to be correct, and analyze all the node coordinates and route information in it; According to the preset layer classification rules, the node coordinates are assigned to the equipment layout layer, the line routing information is assigned to the cable laying layer, and the underground pipeline distribution record is assigned to the auxiliary reference layer. For each line in the cable laying layer, the corresponding line type and line width parameters are automatically matched according to its laying method and conductor cross-sectional area specifications, and the line length and voltage level information are marked. The equipment layout layer, the cable laying layer, and the auxiliary reference layer are overlaid and merged to generate a two-dimensional plan construction drawing and a three-dimensional solid diagram containing complete engineering information. The two-dimensional plan construction drawing and the three-dimensional solid diagram are then packaged into a final construction drawing data package.

8. A multi-line design system for medium-voltage DC distribution networks based on a three-dimensional model, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the multi-line design method for medium-voltage DC distribution networks based on a three-dimensional model as described in any one of claims 1 to 7.

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