BIM-based substation cable laying path automatic optimization method and system

Abstract

This application discloses a BIM-based automatic optimization method and system for substation cable laying paths. The method includes: acquiring a building information model; extracting equipment spatial information, equipment operation information, building structural spatial information, and target cable information; constructing the equipment thermal radiation potential energy field and power frequency magnetic leakage potential energy field; determining the cable type and, based on the cable type, determining the magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient; constructing a virtual cable model; constructing an energy coupling function based on the equipment thermal radiation potential energy field, power frequency magnetic leakage potential energy field, magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient; determining the optimal laying path using the energy coupling function; generating a cable spatial constraint potential energy distribution based on the optimal laying path; and determining all optimal laying paths based on the cable spatial constraint potential energy distribution. This application can effectively improve the accuracy of substation cable laying path optimization.

Description

Technical Field

[0001] This application relates to the field of substation cable laying technology, and in particular to a BIM-based automatic optimization method and system for substation cable laying paths. Background Technology

[0002] In the context of increasingly complex power systems, substations, as critical hub nodes, are essential for efficient and reliable operation. With the rapid development of smart grid technology, substations are expanding in scale and increasing equipment density, making cable laying within substations particularly complex and critical. Rational planning and optimization of cable laying routes not only affect the initial construction cost of substations but also directly impact subsequent operation and maintenance efficiency, system reliability, and safe operation.

[0003] Currently, in the field of substation cable route planning, existing technologies are typically based on BIM technology, treating cable optimization as a typical geometric route planning problem. This is achieved using existing algorithms, such as Dijkstra's algorithm or A... Algorithms simulate the geometry of cables in three-dimensional space and use these algorithms to find the shortest or optimal path that avoids static obstacles. However, existing technologies often overlook the engineering nature of substation cable laying in batches and sequences. Cables laid first become new dynamic obstacles, continuously reconstructing, compressing, and fragmenting the available laying topology space for subsequent cables. Substation cable laying typically involves hundreds to thousands of cables in a single project, densely arranged in multiple layers of supports. Existing technologies use a discrete mode of independent optimization for each cable. As the number of cables and layers increases, cable paths may become intertwined and tangled. This not only affects the stable operation of substation equipment and reduces the accuracy of cable laying path optimization, but also can lead to electrical safety accidents, posing a significant threat to the safety of substation equipment and personnel.

[0004] There is currently no good solution to the above problems. Summary of the Invention

[0005] This application provides a BIM-based automatic optimization method and system for substation cable laying paths, which improves the accuracy of substation cable laying path optimization.

[0006] To achieve the above objectives, the embodiments of this application adopt the following technical solutions: Firstly, a BIM-based automatic optimization method for substation cable laying paths is provided, which includes: Obtain the building information model of the target substation; Based on building information modeling, extract equipment spatial information and equipment operation information of primary high-voltage equipment, building structural spatial information and target cable information to be laid; By combining equipment spatial information and equipment operation information, the thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation are constructed. Based on the information of the target cable to be laid, the cable type of the target cable to be laid is determined, and the magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient and bending stiffness coefficient are determined according to the cable type using a preset cable parameter database. A virtual model of the target cable is constructed by combining the bending stiffness coefficient and the information of the target cable to be laid; An energy coupling function for the target cable path to be laid is constructed based on the equipment's thermal radiation potential energy field, power frequency magnetic leakage potential energy field, magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient. By combining the energy coupling function to perform energy iterative calculations on the virtual cable model, the optimal laying path of the target cable to be laid is determined. The building information model is updated based on the optimal laying path, and the corresponding cable spatial constraint potential energy distribution is generated based on the optimal laying path. Based on the spatially constrained potential energy distribution of the cables, a path optimization step is performed on the remaining cables to be laid until the optimal laying path is determined for all cables.

[0007] In another possible implementation of the first aspect, the method of constructing the equipment thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation by combining equipment spatial information and equipment operation information includes: Extract the spatial coordinates of the primary high-voltage equipment from the equipment spatial information; Extract the equipment operating current, load rate, heat dissipation coefficient, magnetic field strength, and magnetic leakage coefficient of the primary high-voltage equipment from the equipment operation information; The surface thermal power value of the primary high-voltage equipment is calculated using the equipment operating current, load rate, and equipment heat dissipation coefficient. A thermal radiation attenuation model is constructed by combining the spatial coordinates of the primary high-voltage equipment and the surface thermal power value. The thermal radiation potential energy field of the equipment in the target substation was determined using a thermal radiation attenuation model. The magnetic leakage potential energy value of the target substation is constructed based on the spatial location coordinates, the magnetic field strength of the equipment, and the magnetic leakage coefficient of the equipment. The power frequency magnetic leakage potential energy field of the target substation is determined by the magnetic leakage potential energy value.

[0008] In another possible implementation of the first aspect, the method for determining the equipment thermal radiation potential energy field of the target substation using a thermal radiation attenuation model includes: The building information model of the target substation is discretized to obtain multiple spatial grid nodes; Calculate the spatial distance between each spatial grid node and the primary high-voltage equipment, and calculate the thermal radiation potential energy value corresponding to each spatial grid node through the spatial distance and thermal radiation attenuation model; The thermal radiation potential energy values ​​of each primary high-voltage device within each spatial grid node are superimposed to obtain the comprehensive thermal radiation potential energy value corresponding to each spatial grid node. The thermal radiation potential energy field of the target substation is constructed based on the comprehensive thermal radiation potential energy value of each spatial grid node.

[0009] In another possible implementation of the first aspect, the method of constructing a virtual cable model of the target cable by combining the bending stiffness coefficient and the target cable information includes: Obtain the cable's outer diameter and minimum bending radius by analyzing the information of the target cable to be laid; The cable bending response index is calculated by combining the cable outer diameter, minimum bending radius, and bending stiffness coefficient. The cable bending response index is used to represent the bending sensitivity of the cable during the spatial path change process. The bending potential energy coefficient of the cable is calculated based on the bending stiffness coefficient and the bending response index of the cable. The bending response weight is determined by dividing the target cable to be laid into sections based on the cable bending potential energy coefficient. A bending limit function is constructed based on the bending response weight, the cable bending potential energy coefficient, and the minimum bending radius. The bending limit function is used to indicate that when the cable bending degree approaches the limit threshold, the bending energy change rate is increased to limit excessive bending. A virtual model of the target cable to be laid is constructed based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function.

[0010] In another possible implementation of the first aspect, the method of constructing a virtual cable model of the target cable to be laid based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function includes: The target cable to be laid is discretized to obtain the cable node sequence; Calculate the curvature formed by adjacent cable nodes in a cable node sequence; The cable bending energy is calculated based on the bending curvature and bending potential energy coefficient. The bending energy distribution of the cable section is obtained by weighting the bending energy corresponding to each cable node using bending response weights. The bending curvature is adjusted by using a bending limit function and bending energy distribution to limit the cable bending to no more than the minimum bending radius; Based on the adjusted spatial location of the cable nodes, the connection relationship between the cable nodes is established to obtain the virtual cable model of the target cable to be laid.

[0011] In another possible implementation of the first aspect, the method of constructing the energy coupling function of the target cable path based on the equipment thermal radiation potential energy field, the power frequency magnetic leakage potential energy field, the magnetic field repulsion response coefficient, the thermal radiation repulsion response coefficient, and the bending stiffness coefficient includes: The cable nodes and the path arc length of the cable nodes are obtained through a virtual cable model. The cable nodes are mapped to the equipment's thermal radiation potential energy field and power frequency magnetic leakage potential energy field respectively to obtain the thermal radiation potential energy value and magnetic leakage potential energy value corresponding to each cable node. The environmental response potential energy of each cable node is calculated by adjusting the magnetic leakage potential energy value and the thermal radiation potential energy value based on the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient. The total environmental response potential energy of the target cable path is obtained by summing the environmental response potential energy of each cable node. Calculate the path curvature corresponding to each cable node, and calculate the bending strain potential energy of each cable node through the bending stiffness coefficient, path curvature and path arc length; The total elastic strain potential energy of the target cable path is obtained by summing the bending strain potential energy of each cable node. The total potential energy of elastic strain and the total potential energy of environmental response are normalized. An energy coupling function is constructed using the normalized total potential energy of elastic strain and the total potential energy of environmental response.

[0012] In another possible implementation of the first aspect, the method of calculating the environmental response potential energy of each cable node by adjusting the magnetic leakage potential energy value and the thermal radiation potential energy value based on the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient includes: The magnetic leakage potential energy of each cable node is obtained by adjusting the magnetic leakage potential energy value of each cable node through the magnetic repulsion response coefficient. The thermal radiation response potential energy is obtained by adjusting the thermal radiation potential energy value of each cable node through the thermal radiation repulsion response coefficient. The environmental coupling modulation factor is determined based on the intensity relationship between the nodal magnetic field response potential energy and the nodal thermal radiation response potential energy. The environmental response potential energy of each cable node is obtained by using the potential energy proportional coupling formula and the environmental coupling modulation factor to jointly calculate the node magnetic field response potential energy and the node thermal radiation response potential energy.

[0013] In another possible implementation of the first aspect, the method of combining the energy coupling function to perform energy iterative calculations on the cable virtual model to determine the optimal laying path of the target cable includes: An initial path node sequence is generated using a virtual model of the target cable to be laid. Substitute the node data corresponding to each path node in each initial path node sequence into the energy coupling function to obtain the comprehensive energy value corresponding to each path node; Calculate the corresponding spatial energy gradient based on the comprehensive energy value of each path node; The virtual force of each path node is constructed by the spatial energy gradient, and the spatial position of the path node is iteratively updated according to the virtual force. After iteratively updating the spatial positions of the path nodes, the comprehensive energy corresponding to the path nodes is recalculated, and the updated initial path node sequence is smoothed. When the change in comprehensive energy obtained from two consecutive iterations is less than the preset convergence threshold, the path corresponding to the current cable node sequence is determined as the optimal laying path for the target cable to be laid.

[0014] Secondly, this application provides a machine-readable storage medium storing instructions that cause a machine to execute the above-described BIM-based automatic optimization method for substation cable laying paths.

[0015] Thirdly, this application provides an electronic device, comprising: The memory is configured to store instructions; and The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the aforementioned BIM-based automatic optimization method for substation cable laying paths.

[0016] Through the above technical solutions, a digital representation of all elements of a substation can be achieved by acquiring a Building Information Model (BIM), providing an intuitive three-dimensional spatial display. Extracting information from primary high-voltage equipment and building structure provides realistic constraints for path optimization, ensuring that cable laying paths are conducted without interfering with equipment operation or damaging the building structure. By constructing the equipment's thermal radiation potential energy field and power frequency magnetic leakage potential energy field, high-temperature areas can be automatically avoided during path planning, reducing the risk of cable aging and failure, and high magnetic field areas can be avoided during laying, reducing electromagnetic interference and cable damage. The cable type is determined by the information of the cable to be laid, and based on this, the magnetic field repulsion response coefficient, thermal radiation repulsion coefficient, and bending stiffness coefficient are determined. Appropriate parameters can be selected according to different cable types, ensuring that the virtual cable model accurately reflects its physical characteristics, such as flexibility, heat resistance, and antimagnetic properties. Constructing an energy coupling function for the cable path automatically generates reasonable, low-risk laying paths, avoiding local optima and non-physical path problems that are easily generated by traditional geometric search methods. Combining the energy coupling function with energy iterative calculations on the virtual cable model determines the optimal laying path, reducing manual intervention and improving planning efficiency and accuracy. Furthermore, the energy iteration process naturally considers bending constraints, thermal radiation, and magnetic field repulsion to achieve global optimization. The building information model is updated based on the optimal laying path, and a cable spatial constraint potential energy distribution is generated. This path information can be fed back into the BIM, providing constraints for subsequent cable planning, avoiding path conflicts, and improving construction safety and controllability. Based on the cable spatial constraint potential energy distribution, path optimization is performed on the remaining cables until the optimal path is determined for all cables to be laid. This enables overall coordinated optimization of multiple cables, ensuring that all cables are rationally laid out within a limited space, avoiding conflicts and interference between different cables, improving the overall safety and reliability of the system, increasing construction efficiency and design repeatability, and reducing later maintenance costs.

[0017] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0018] Figure 1 A flowchart illustrating an automatic optimization method for substation cable laying paths based on BIM, provided for an embodiment of this application; Figure 2 This is a schematic diagram of a process for constructing a device thermal radiation potential energy field and a power frequency magnetic leakage potential energy field, provided for an embodiment of this application. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0020] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0021] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0022] Figure 1 This illustration schematically shows a flowchart of an automatic optimization method for substation cable laying paths based on BIM, according to an embodiment of this application. Figure 1 As shown in the figure, this application provides a BIM-based automatic optimization method for substation cable laying paths, which may include the following steps.

[0023] S110. Obtain the building information model of the target substation; S120. Extract equipment spatial information and equipment operation information of primary high-voltage equipment, building structure spatial information and target cable information based on building information model; S130. Construct the thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation by combining equipment spatial information and equipment operation information. S140. Determine the cable type of the target cable based on the information of the target cable to be laid, and determine the magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient and bending stiffness coefficient according to the cable type using a preset cable parameter database. S150. Construct a virtual cable model of the target cable by combining the bending stiffness coefficient and the target cable information. S160. Construct the energy coupling function of the target cable path based on the equipment's thermal radiation potential energy field, power frequency magnetic leakage potential energy field, magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient. S170. Combine the energy coupling function to perform energy iteration calculation on the virtual cable model to determine the optimal laying path of the target cable to be laid. S180. Update the building information model according to the optimal laying path, and generate the corresponding cable spatial constraint potential energy distribution based on the optimal laying path. S190. Based on the spatial constraint potential energy distribution of the cable, perform a path optimization step on the remaining cables to be laid until the optimal laying path is determined for all cables to be laid.

[0024] In this embodiment of the invention, the building information model (BIM) of the target substation is first acquired. The BIM not only includes the spatial layout, geometric information such as walls, floors, beams, columns, and pipes of the substation's building structure, but also the location, dimensions, operating status, and other relevant attribute information of the primary high-voltage equipment. By acquiring the BIM of the target substation, the system can accurately obtain the possible cable laying space, confined spaces, and potential obstacle locations, providing accurate digital foundation data for subsequent cable route optimization. Simultaneously, the BIM model enables the acquisition of equipment space occupancy information and operating status information, ensuring the safety of cable laying route planning.

[0025] Secondly, based on the acquired building information model, further extraction of equipment spatial information and operational information of the primary high-voltage equipment, building structural spatial information, and information on the target cable to be laid is performed. Equipment spatial information includes the equipment's three-dimensional coordinates, dimensions, and occupied space; equipment operational information includes operating status data such as surface temperature, electromagnetic field strength, and power rating; building structural spatial information includes the spatial location and dimensions of beams, columns, walls, floors, and pipes; and information on the target cable to be laid includes cable type, cross-sectional area, flexibility, maximum allowable bending radius, and laying length. By extracting this information, it is possible to ensure that cable route planning, while meeting spatial constraints, achieves protection for equipment safety, construction feasibility, and accuracy in route optimization, thereby improving the automation level and safety reliability of substation cable laying.

[0026] By combining equipment spatial information and equipment operation information, the thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation are constructed. Specifically, the spatial coordinates of the primary high-voltage equipment are extracted from the equipment spatial information. Since the primary high-voltage equipment generates heat and power frequency magnetic fields, there are high-temperature zones and strong magnetic field zones in the surrounding space. If cables are laid in these areas, it may lead to insulation aging, cable damage, or electromagnetic interference. Therefore, based on determining the spatial location of the equipment, the operating current, load rate, heat dissipation coefficient, magnetic field strength, and magnetic leakage coefficient of the primary high-voltage equipment are further extracted from the equipment operation information. Among them, the operating current and load rate are used to characterize the operating load of the equipment and determine the amount of heat generated by the equipment and the magnetic field strength; the heat dissipation coefficient is used to reflect the ability of the equipment to dissipate heat to the surrounding environment, thereby determining the temperature distribution characteristics of the space around the equipment; the magnetic field strength and magnetic leakage coefficient are used to characterize the power frequency magnetic field generated by the equipment during operation and its attenuation characteristics in space. The surface thermal power value of the primary high-voltage equipment is calculated using the equipment operating current, load rate, and heat dissipation coefficient extracted from the equipment operation information. Among them, the equipment operating current and load rate are used to characterize the load level of the equipment under actual operating conditions. The higher the load, the greater the internal power loss of the equipment, thus generating more heat. The equipment heat dissipation coefficient is used to reflect the equipment's ability to transfer and dissipate heat to the surrounding environment. Based on the above parameters, the heat generation of the primary high-voltage equipment under operating conditions is calculated through a preset thermal power calculation model to obtain the corresponding equipment surface thermal power value, which is used to characterize the intensity of heat released by the equipment to the surrounding space per unit time. Based on obtaining the spatial coordinates of the primary high-voltage equipment and its surface thermal power value, a thermal radiation attenuation model is constructed in combination with the equipment's positional distribution in the three-dimensional space of the substation. Specifically, the spatial coordinates of each primary high-voltage equipment are used as the heat source center point, the equipment surface thermal power value is used as the heat source intensity parameter, and a thermal radiation attenuation function is established according to the propagation and attenuation law of thermal radiation in space, thereby describing the attenuation distribution characteristics of the heat generated by the equipment at different spatial locations. By performing thermal radiation calculations on each spatial location point in the three-dimensional space of the target substation, the corresponding thermal radiation potential energy value is obtained, and a device thermal radiation potential energy field covering the spatial range of the target substation is constructed accordingly to characterize the spatial temperature influence distribution formed during equipment operation. Furthermore, the magnetic leakage potential energy value of the target substation is constructed based on the spatial coordinates of the primary high-voltage equipment, the equipment magnetic field strength, and the equipment magnetic leakage coefficient. The equipment magnetic field strength characterizes the power frequency magnetic field strength generated during equipment operation, and the equipment magnetic leakage coefficient describes the diffusion and attenuation characteristics of the magnetic field in space. By combining the spatial location of the equipment to establish a magnetic field attenuation model, the magnetic leakage potential energy value corresponding to each location point in the three-dimensional space of the substation is calculated.After obtaining the magnetic leakage potential energy values ​​at each spatial location, the power frequency magnetic leakage potential energy field of the target substation can be further constructed to characterize the spatial distribution of the magnetic field generated by the equipment operation.

[0027] The cable type of the target cable to be laid is determined based on the target cable information, which includes parameters such as cable specifications, voltage rating, application type, and structural characteristics. Since different cable types differ in heat resistance, electromagnetic environment adaptability, and mechanical flexibility, after determining the cable type, the corresponding physical characteristic parameters are obtained by accessing a pre-set cable parameter database. Based on the cable type, the magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient can be determined from the cable parameter database. The magnetic field repulsion response coefficient characterizes the cable's sensitivity to electromagnetic environments, enabling the cable to generate a corresponding repulsion effect in strong magnetic field areas during path optimization. The thermal radiation repulsion response coefficient characterizes the cable's tolerance to high-temperature environments, allowing the cable to avoid high-temperature areas during path planning. The bending stiffness coefficient reflects the cable's ability to resist bending deformation during laying. The pre-set cable parameter database collects basic technical data on different cable types, including cable structure, conductor materials, and insulation materials. Cables are categorized according to their applications, including high-voltage power cables, medium-voltage power cables, control cables, and communication cables. Subsequently, based on the structural parameters and operational characteristics of each cable type, their response characteristics under electromagnetic, thermal, and mechanical bending conditions are parameterized and organized. Key physical characteristic parameters reflecting the interaction between the cable and its external environment are extracted and standardized into a set of parameters. These key physical characteristic parameters include at least the magnetic field repulsion response coefficient, the thermal radiation repulsion response coefficient, and the bending stiffness coefficient. Finally, each cable type is mapped to its corresponding physical characteristic parameters and stored according to a unified data structure, thus constructing a pre-defined cable parameter database.

[0028] By combining the bending stiffness coefficient and structural parameters of the target cable to be laid, a virtual model of the cable's bending behavior during spatial path changes is constructed. The cable's outer diameter and minimum bending radius are obtained from the target cable information, which can be derived from substation design data, equipment parameters in a BIM model, or a pre-set cable parameter database. The cable outer diameter characterizes the overall structural dimensions of the cable, while the minimum bending radius characterizes the minimum allowable bending limit during actual engineering installation. The bending characteristics of the cable are comprehensively calculated by combining the cable outer diameter, minimum bending radius, and bending stiffness coefficient to obtain the cable bending response index. This index represents the cable's sensitivity to bending deformation when its spatial path changes. A larger cable outer diameter or higher bending stiffness coefficient results in a higher bending response index, while a smaller minimum bending radius results in a lower index, thus comprehensively reflecting the ease with which the cable undergoes bending deformation during path adjustments. Subsequently, the bending potential energy coefficient of the cable is calculated based on the bending stiffness coefficient and the cable bending response index. The bending potential energy coefficient represents the degree of change in bending energy generated when the cable path undergoes bending changes. The larger the bending potential energy coefficient, the more significant the energy change during the bending process. In subsequent path optimization calculations, the system will tend to select paths with smaller bending degrees. Furthermore, the target cable to be laid is divided into segments based on the cable bending potential energy coefficient. The cable path is discretized at each path node, forming multiple path segments. The corresponding bending response weight is determined by combining the spatial variation of each path segment. Segments with more significant bending changes have higher bending response weights, while segments with less bending changes have lower bending response weights, thus achieving differentiated expression of the bending behavior of the cable at different locations. After determining the bending response weights, a bending constraint function is constructed in conjunction with the minimum bending radius. This function describes the energy change trend as the cable bending degree gradually approaches the minimum bending radius threshold. When the cable bending degree is small, the bending energy change is relatively gradual. However, when the bending degree approaches the minimum bending radius threshold, the bending constraint function significantly increases the rate of change of bending energy, thus constraining excessive bending behavior during path optimization. Finally, the bending stiffness coefficient, bending potential energy coefficient, bending response weights, and the bending constraint function are all introduced into the cable path energy calculation model to construct a virtual cable model of the target cable to be laid. In this virtual model, the cable is abstracted as a virtual flexible structure composed of multiple path nodes, which are connected by bending energy constraints. During subsequent path optimization calculations, when the position of a path node changes, the corresponding bending energy change is calculated using the bending constraint function, and the path node positions are iteratively adjusted based on the energy minimization principle to obtain a cable laying path that satisfies the cable bending constraint conditions.

[0029] Based on the equipment's thermal radiation potential energy field and power frequency magnetic leakage potential energy field, and combined with the magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient, an energy coupling function for the target cable path to be laid is constructed. Multiple cable nodes and their corresponding path arc lengths are obtained from the virtual cable model. The cable nodes are the path control points after discretization of the cable path, representing the actual laying form of the cable in space. Subsequently, each cable node is mapped to the pre-constructed equipment thermal radiation potential energy field and power frequency magnetic leakage potential energy field, obtaining the thermal radiation potential energy value and magnetic leakage potential energy value of each cable node at its corresponding spatial location. The thermal radiation potential energy value represents the degree of thermal influence of the thermal radiation generated during equipment operation on the cable node location, while the magnetic leakage potential energy value represents the degree of electromagnetic influence of the equipment's power frequency magnetic leakage on the cable node location. After obtaining the aforementioned potential energy values, the magnetic leakage potential energy and thermal radiation potential energy values ​​are weighted and adjusted according to the magnetic field repulsion response coefficient and the thermal radiation repulsion response coefficient to calculate the environmental response potential energy corresponding to each cable node. The environmental response potential energies of all cable nodes are then accumulated to obtain the total environmental response potential energy corresponding to the target cable laying path. Further, the spatial path morphology corresponding to each cable node on the cable path is analyzed, the path curvature at each cable node is calculated, and the bending strain potential energy of each cable node is calculated by combining the bending stiffness coefficient, path curvature, and corresponding path arc length. The bending strain potential energies of all cable nodes are then accumulated to obtain the total elastic strain potential energy corresponding to the target cable laying path. Since the total environmental response potential energy and the total elastic strain potential energy differ in dimensions and numerical range, they are normalized to ensure they are on a unified dimensional scale. Finally, the normalized total elastic strain potential energy and the total environmental response potential energy are coupled and combined to construct the energy coupling function for the target cable laying path.

[0030] Energy iterative calculations are performed on the cable virtual model using an energy coupling function to determine the optimal laying path for the target cable. After constructing the cable virtual model and the energy coupling function, energy iterative calculations are performed on the cable virtual model using the energy coupling function to determine the optimal laying path for the target cable. An initial path node sequence for the target cable is generated based on the cable virtual model. This path node sequence consists of multiple cable nodes connected sequentially according to the path arc length, forming the initial cable path structure. Subsequently, the initial path node sequence is substituted into the energy coupling function for calculation. By comprehensively calculating the environmental response potential energy of the path nodes in the equipment's thermal radiation potential energy field and the power frequency magnetic leakage potential energy field, as well as the elastic strain potential energy generated by the cable path bending, the total energy value corresponding to the current cable path is obtained. Furthermore, the spatial positions of the cable path nodes are adjusted according to the total path energy value. By iteratively updating the spatial coordinates of each cable node, the cable nodes gradually move in the direction of decreasing energy, thereby changing the spatial morphology of the cable path. After each path node adjustment, the updated path node sequence is recalculated using the energy coupling function to obtain the updated total path energy value. This value is then compared with the total path energy from the previous iteration. If the total path energy decreases, the current path node position is retained; otherwise, further adjustments are made to the path nodes. This process of adjusting path nodes and calculating energy is repeated continuously, causing the cable path to gradually converge towards the minimum energy state under the combined influence of environmental response potential energy and elastic strain potential energy. When the change in total path energy is less than a preset convergence threshold or the preset maximum number of iterations is reached, the iterative calculation stops, and the corresponding cable path is taken as the optimal laying path for the target cable.

[0031] The Building Information Model (BIM) is updated based on the optimal cable laying path, and a corresponding cable spatial constraint potential energy distribution is generated based on this path. Specifically, after determining the optimal laying path for the current cable, this path information is updated in the BIM, and a cable spatial constraint potential energy distribution is generated based on the laid cable path. The laid cable path is discretized into several spatial nodes, each node forming a local constraint potential energy region in three-dimensional space. This region represents the node's occupancy and repulsion effect on the surrounding area. The potential energy center of the local constraint potential energy region can be determined based on the actual location of the node in space, and the potential energy intensity is set according to the spatial distance between the node and the surrounding laid cables and environmental structures. The closer the node is to obstacles or other cables, the higher its potential energy value, reflecting the strength of the spatial constraint. Secondly, the range of the local potential energy is adjusted based on the bending radius of the cable segment where the node is located, ensuring sufficient space for cable laying in the bending area. Finally, the local potential energy region is trimmed considering pipe channels, supports, and other spatial constraints to prevent the potential energy from extending to areas where laying is not possible. By accumulating the local potential energy of all nodes, a spatial constraint potential energy distribution covering the entire area of ​​laid cables can be formed, reflecting the repulsive effect of the laid cables as dynamic obstacles on the path of the remaining cables to be laid. In the subsequent cable planning process, the path of the cables to be laid is also discretized into several nodes, and each node is mapped to the aforementioned spatial constraint potential energy distribution to obtain the constraint potential energy value of the corresponding node. During the path iterative optimization process, each node to be laid adjusts its position based on the combined influence of spatial constraint potential energy, equipment thermal radiation potential energy, and power frequency magnetic leakage potential energy. Spatial constraint potential energy reflects the relative distance and potential conflict between the node and the laid cables; thermal radiation potential energy represents the influence of the thermal environment generated during equipment operation on the node's position; and power frequency magnetic leakage potential energy represents the influence of the equipment's electromagnetic environment on the node. Taking all these factors into account, each node gradually moves along the comprehensive environmental potential energy gradient, moving away from high-potential-energy areas and tending towards the minimum energy state, thereby ensuring that the path of the cables to be laid avoids crossing with the laid cables while optimizing the thermal and magnetic environment response.

[0032] Based on the spatial constraint potential energy distribution of the cables, a path optimization step is performed on the remaining cables to be laid until the optimal laying path is determined for all cables. After obtaining the spatial constraint potential energy distribution of the cables, each cable to be laid is discretized into several path nodes, each node corresponding to a position in three-dimensional space, used to characterize the actual laying form of the cable. Subsequently, each node is mapped to the generated spatial constraint potential energy distribution of the cables to obtain the constraint potential energy value of the node in space, thereby reflecting the degree of spatial conflict between it and the laid cables or environmental obstacles; at the same time, the nodes are mapped to the thermal radiation potential energy field and the power frequency magnetic leakage potential energy field of the equipment to obtain the environmental response potential energy corresponding to the nodes, and the constraint potential energy and environmental response potential energy are weighted and combined according to preset weights to form a comprehensive environmental potential energy. After obtaining the comprehensive environmental potential energy, the initial path of the cables to be laid is generated according to the cable start and end points and the node sequence. The initial path can be formed by straight line or curve interpolation. Subsequently, the path nodes are iteratively optimized. Each node moves along the direction of the comprehensive environmental potential energy gradient, moving away from high potential energy areas to avoid already laid cables, equipment obstructions, and thermally and magnetically sensitive areas, while ensuring that the cable bending radius and channel constraints meet construction requirements. After each node adjustment, the comprehensive environmental potential energy of the node and path is recalculated, and the change in total path potential energy is evaluated. If the total path potential energy decreases, the current node position is retained; otherwise, adjustments continue until the change in total path potential energy is below a preset threshold or the maximum number of iterations is reached. After each cable path optimization is completed, the path information is updated to the BIM, and a new cable spatial constraint potential energy distribution is generated to provide dynamic constraints for the next cable to be laid. By repeating the above steps, path optimization is performed for all remaining cables to be laid until the optimal laying path for all cables is determined. During this process, the optimization of each cable path fully considers the dynamic spatial constraints of already laid cables to ensure that the path avoids conflicts, while also incorporating environmental factors such as thermal radiation and power frequency magnetic leakage to achieve environmental response optimization of the path.

[0033] By acquiring Building Information Modeling (BIM), a fully digital representation and intuitive 3D display of all elements of a substation can be achieved. Information on primary high-voltage equipment and building structures can be extracted, providing realistic constraints for cable laying path optimization and ensuring that the path does not interfere with equipment operation or damage the building structure. Constructing potential energy fields for equipment thermal radiation and power frequency magnetic leakage allows for automatic avoidance of high-temperature and high-magnetic-field areas during path planning, reducing the risks of cable aging, failures, electromagnetic interference, and damage. Combining the information of the cable to be laid to determine the cable type, and then setting magnetic field repulsion, thermal radiation repulsion, and bending stiffness coefficients, ensures that the virtual cable model accurately reflects its flexibility, heat resistance, and antimagnetic properties. By constructing a cable path energy coupling function, a reasonable low-risk path can be automatically generated, avoiding local optima and non-physical path problems that are prone to occur in traditional geometric search methods. Combined with energy iterative calculations, the optimal path is determined, reducing manual intervention and improving planning efficiency and accuracy. Simultaneously, bending constraints, thermal radiation, and magnetic field repulsion are naturally taken into account, achieving global optimization. The optimal path is updated to BIM and a cable spatial constraint potential energy distribution is generated to provide constraints for subsequent cable planning and avoid path conflicts. Based on this distribution, the remaining cables are successively optimized to achieve overall coordinated deployment of multiple cables, avoid mutual interference, improve system safety, reliability and construction efficiency, and reduce later maintenance costs.

[0034] Figure 2 This illustration schematically depicts a process for constructing a thermal radiation potential energy field and a power frequency magnetic leakage potential energy field according to an embodiment of this application. Figure 2 As shown, in one embodiment, the thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation are constructed by combining equipment spatial information and equipment operation information, including: S210. Extract the spatial location coordinates of the primary high-voltage equipment from the equipment spatial information; S220. Extract the equipment operating current, load rate, heat dissipation coefficient, magnetic field strength, and magnetic leakage coefficient of the primary high-voltage equipment from the equipment operation information. S230. The surface thermal power value of the primary high-voltage equipment is calculated using the equipment operating current, load rate and equipment heat dissipation coefficient. S240. A thermal radiation attenuation model is constructed by combining the spatial coordinates of the primary high-voltage equipment and the surface thermal power value. S250. Determine the equipment thermal radiation potential energy field of the target substation using a thermal radiation attenuation model. S260. Construct the magnetic leakage potential energy value of the target substation based on the spatial location coordinates, equipment magnetic field strength, and equipment magnetic leakage coefficient. S270. Determine the power frequency magnetic leakage potential energy field of the target substation by using the magnetic leakage potential energy value.

[0035] The spatial coordinates of primary high-voltage equipment are extracted from the equipment spatial information. The building information model (BIM) or 3D model of the equipment in the target substation is obtained, and the equipment objects of each primary high-voltage device are identified within the model. These primary high-voltage devices include circuit breakers, disconnectors, instrument transformers, transformers, and busbar equipment. Subsequently, by parsing the geometric information or component attribute information corresponding to the equipment objects, the position data of each primary high-voltage device in the 3D spatial coordinate system is extracted. Alternatively, the coordinates of the positioning points, installation reference points, or geometric centers of the equipment components can be read based on the unified spatial coordinate system used by the BIM, and this coordinate information can be used as the spatial coordinates of the corresponding primary high-voltage equipment.

[0036] The system extracts the operating current, load rate, heat dissipation coefficient, magnetic field strength, and magnetic leakage coefficient of the primary high-voltage equipment from the equipment operation information. It acquires the equipment operation information of each primary high-voltage device in the target substation, which can be sourced from the substation monitoring system, SCADA system, equipment operation monitoring system, or equipment operation record database. Subsequently, the equipment operation information is analyzed to extract key operating parameters reflecting the electrical operating status of the equipment, including the operating current and load rate. The operating current represents the actual current value passing through the equipment under the current operating condition, and the load rate represents the ratio between the current load level and the rated capacity of the equipment. Furthermore, to describe the thermal radiation impact generated during equipment operation, the corresponding equipment heat dissipation coefficient is obtained from the equipment technical parameters or preset equipment parameter database. The heat dissipation coefficient characterizes the equipment's ability to release heat to the surrounding space during operation. Simultaneously, to reflect the electromagnetic impact generated during equipment operation, the equipment magnetic field strength and magnetic leakage coefficient are extracted from the equipment operation information or equipment electromagnetic characteristic parameter database. The magnetic field strength characterizes the magnetic field strength level in the space surrounding the equipment, and the magnetic leakage coefficient characterizes the degree of leakage of the equipment's magnetic field to the external space. Furthermore, the extracted equipment operating current, load rate, heat dissipation coefficient, magnetic field strength, and magnetic leakage coefficient are processed in a unified data format.

[0037] The surface thermal power value of the primary high-voltage equipment is calculated using the equipment's operating current, load rate, and heat dissipation coefficient. This involves obtaining the operating current and load rate information of each primary high-voltage device in the target substation. The operating current characterizes the actual current passing through the equipment under its current operating condition, and the load rate represents the ratio between the current load level and the rated capacity. Subsequently, the heat dissipation coefficient of each device is obtained. This coefficient reflects the device's ability to release heat to the surrounding environment per unit time. Then, the operating current, load rate, and heat dissipation coefficient are used to calculate the surface thermal power value of the equipment under actual operating conditions. This surface thermal power value represents the total amount of heat released by the equipment to the external space per unit time. The thermal power value can be obtained using the formula shown below:

[0038] Where I is the equipment operating current, L is the equipment load factor, k is the equipment heat dissipation coefficient, and Q is the equipment heat dissipation coefficient. i Let be the surface thermal power value of the i-th device. Calculating the surface thermal power value of a device can reflect the impact of its operating status and heat dissipation capacity on the actual heat output.

[0039] Next, a thermal radiation attenuation model is constructed by combining the spatial coordinates and surface thermal power values ​​of the primary high-voltage equipment. Specifically, the model is built in three-dimensional space with the center of the equipment as the heat source. This model maps the heat output capacity of the primary high-voltage equipment to the thermal environment influence at each point in space, thereby determining the impact on the cable to be laid. The specific expression of the thermal radiation attenuation model is shown below:

[0040] Among them, U T (x,y,z) represents the total radiative heat flux density at any point in space; d i Q represents the distance from the point to the i-th device; i Let be the surface thermal power value of the i-th device; ε represents a very small positive number to prevent d i When the value is 0, the denominator is 0 to avoid numerical calculation divergence; N is the total number of devices; V iVi represents the shading factor from device i to point (x,y,z), reflecting the impact of the degree of shading on the cable node. A smaller Vi indicates more severe shading at that point, and a greater impact on the feasibility of path planning; a larger Vi indicates less obstruction. Vi is determined by constructing a 3D spatial model of the device and its surrounding environment; secondly, emitting a virtual ray from device i to point (x,y,z), determining whether there are obstructions along the ray path, their thickness, and projected area, and determining the shading attenuation ratio accordingly; finally, combining the shading attenuation ratio with spatial geometric relationships and the device's radiation characteristics to obtain the shading factor Vi from device i to point (x,y,z).

[0041] Subsequently, based on the thermal radiation attenuation model, the thermal power of each primary high-voltage device is propagated along space. The potential energy value of each spatial point in the target substation affected by the thermal radiation from each device is calculated according to the distance attenuation law, where the device's thermal radiation potential energy value decreases with increasing spatial distance. In the calculation process, for each spatial point, its distance from each primary high-voltage device is used as input, substituted into the thermal radiation attenuation model to calculate its heat contribution value. The contributions of all devices are then summed to obtain the comprehensive thermal potential energy value of each spatial point. By distributing the comprehensive thermal potential energy values ​​of all points in the target substation, a three-dimensional device thermal radiation potential energy field of the target substation is formed.

[0042] Based on spatial coordinates, equipment magnetic field strength, and equipment magnetic leakage coefficient, a magnetic leakage attenuation model is established to describe the attenuation of the equipment's magnetic field as it propagates through space. The attenuation model can employ an inverse square attenuation function or an exponential attenuation function to reflect the characteristic that magnetic potential energy weakens with increasing spatial distance. The specific expression for the magnetic leakage attenuation model is shown below:

[0043] Among them, U M (x,y,z)) represents the magnetic leakage potential energy at any point in space; d i This represents the distance from the point to the i-th device; ε represents a very small positive number to prevent d from being... i When the denominator is 0, the value is equal to 0, thus avoiding divergence in numerical calculations; k i The magnetic leakage coefficient of the equipment is represented by N; N is the total number of equipment.

[0044] The power frequency magnetic leakage potential energy field of the target substation is determined by measuring the magnetic leakage potential energy value. This involves acquiring the magnetic leakage potential energy value at each point in the target substation space, which represents the degree to which a point is affected by the magnetic field leakage of various devices. Subsequently, the magnetic leakage potential energy values ​​are mapped and distributed in the three-dimensional space of the target substation. The substation space can be divided into a discrete grid or a set of sampling points according to actual engineering requirements to ensure a continuous and smooth distribution of the magnetic leakage potential energy in space. During the processing, for each spatial point, the magnetic leakage potential energy values ​​from multiple devices are accumulated to obtain the comprehensive magnetic leakage potential energy value for that point. By distributing the comprehensive magnetic leakage potential energy values ​​of all spatial points in the target substation, the power frequency magnetic leakage potential energy field of the target substation is formed. This field quantifies the magnetic environment intensity at each point in the target substation space.

[0045] By constructing the thermal radiation potential energy field and the power frequency magnetic leakage potential energy field of the substation, the spatial distribution of thermal radiation diffusion and magnetic field leakage of primary high-voltage equipment was quantitatively characterized, providing a precise basis for substation electromagnetic environment safety assessment, equipment health status monitoring, and delineation of personnel safety protection areas.

[0046] In one embodiment, determining the equipment thermal radiation potential energy field of the target substation using a thermal radiation attenuation model includes: S310. Discretize the building information model of the target substation to obtain multiple spatial grid nodes; S320. Calculate the spatial distance between each spatial grid node and the primary high-voltage equipment, and calculate the thermal radiation potential energy value corresponding to each spatial grid node through the spatial distance and thermal radiation attenuation model. S330. The thermal radiation potential energy values ​​of each primary high-voltage device within each spatial grid node are superimposed to obtain the comprehensive thermal radiation potential energy value corresponding to each spatial grid node. S340. Construct the equipment thermal radiation potential energy field of the target substation based on the comprehensive thermal radiation potential energy value of each spatial grid node.

[0047] The building information model (BIM) of the target substation is discretized to obtain multiple spatial grid nodes. The 3D BIM of the target substation includes information such as the building structure, spatial layout of primary high-voltage equipment, and auxiliary pipelines and their arrangement. Based on a preset spatial range and grid resolution, the substation space is divided into regular spatial units along the x, y, and z directions, each with a uniform side length or size. Within each spatial unit, its center point is determined as a representative node, used for subsequent calculations and modeling. By processing all spatial units of the entire substation space, a set of multiple discretized grid nodes covering the target substation space is obtained. The preset spatial range and grid resolution can be set according to the actual conditions of the substation project, i.e., based on the accuracy requirements of the substation project, such as adding appropriate safety distances to industry safety standards to form the preset spatial range. The grid resolution can use finer grids in areas with cable bending requirements or high-risk areas, such as near primary high-voltage equipment, while using coarser grids in low-risk areas with gentle potential energy changes, thereby optimizing computational efficiency while ensuring computational accuracy.

[0048] The spatial distance between each spatial grid node and the primary high-voltage equipment is calculated, and the corresponding thermal radiation potential energy value of each spatial grid node is calculated using the spatial distance and thermal radiation attenuation model. For each spatial grid node, the Euclidean distance between it and each primary high-voltage equipment is calculated to quantify the spatial interval between the spatial node and the equipment's heat source. Next, the calculated spatial distance is substituted into the aforementioned thermal radiation attenuation model, and the thermal radiation potential energy contribution value of each node to the equipment is calculated based on the equipment's surface thermal power value. Further, for each spatial grid node, the thermal radiation potential energy contributions from multiple equipment are summed to obtain the node's comprehensive thermal radiation potential energy value. By distributing the comprehensive thermal radiation potential energy values ​​of all spatial grid nodes in the target substation, a three-dimensional thermal radiation potential energy field of the target substation is formed. This thermal radiation potential energy field can quantify the thermal environment intensity at each point in the substation space.

[0049] The thermal radiation potential energy values ​​of each primary high-voltage device within each spatial grid node are superimposed to obtain the comprehensive thermal radiation potential energy value corresponding to each spatial grid node. That is, for each spatial grid node, the thermal radiation potential energy values ​​received by each primary high-voltage device are calculated, and the thermal radiation potential energy values ​​of multiple devices received by the node are summed to obtain the comprehensive thermal radiation potential energy value of that node. By performing the above calculations on all spatial grid nodes of the target substation, a three-dimensional comprehensive thermal radiation potential energy field covering the entire substation space is formed. The comprehensive thermal radiation potential energy field can quantify the thermal environment intensity at each point in the substation space.

[0050] The thermal radiation potential energy field of the target substation is constructed based on the comprehensive thermal radiation potential energy value of each spatial grid node. The comprehensive thermal radiation potential energy value of each node is mapped to its three-dimensional spatial coordinates, and a continuous three-dimensional potential energy distribution is formed through spatial interpolation, achieving a quantitative representation of the entire substation's spatial thermal environment. By organizing and processing the comprehensive thermal radiation potential energy values ​​of all spatial grid nodes, a thermal radiation potential energy field covering the target substation space is generated, where high potential energy regions represent areas with higher thermal environments, and low potential energy regions represent areas with lower thermal environments. The equipment thermal radiation potential energy field provides complete and quantifiable thermal environment constraint data for subsequent cable path optimization based on energy coupling functions.

[0051] By discretizing the building information model of the substation into a grid and combining it with the thermal radiation attenuation model to calculate the spatial distance between each grid node and the primary high-voltage equipment and the corresponding thermal radiation potential energy value, the thermal radiation distribution in the three-dimensional space of the substation can be clearly defined. This allows for a direct presentation of the spatial gradient changes of the temperature field and hot spot clustering areas, providing a visual decision-making basis for optimizing equipment heat dissipation layout, early warning of thermal faults, and identification of high-temperature risk areas for operation and maintenance personnel.

[0052] In one embodiment, a virtual cable model of the target cable to be laid is constructed by combining the bending stiffness coefficient and the target cable information, including: S410. Obtain the outer diameter and minimum bending radius of the cable by using the information of the target cable to be laid; S420. The cable bending response index is calculated by combining the cable outer diameter, minimum bending radius and bending stiffness coefficient. The cable bending response index is used to represent the bending sensitivity of the cable during the spatial path change process. S430. Calculate the cable bending potential energy coefficient based on the bending stiffness coefficient and the cable bending response index. S440. The bending response weight is determined by dividing the target cable to be laid into sections based on the cable bending potential energy coefficient. S450. Construct a bending limit function based on the bending response weight, the cable bending potential energy coefficient, and the minimum bending radius. The bending limit function is used to indicate that when the cable bending degree approaches the limit threshold, the bending energy change rate is increased to limit excessive bending. S460. A virtual model of the target cable to be laid is constructed based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function.

[0053] By obtaining the outer diameter and minimum bending radius of the target cable, the system can determine the type and relevant specifications of the target cable. Subsequently, the minimum bending radius is determined according to cable standards or specifications. This minimum bending radius limits the degree of bending of the cable during changes in its spatial path, preventing damage to the cable insulation.

[0054] The cable bending response index is calculated by combining the cable's outer diameter, minimum bending radius, and bending stiffness coefficient. The cable bending response index represents the cable's sensitivity to bending during changes in its spatial path. The bending stiffness coefficient describes the cable's resistance to bending. Subsequently, the cable's geometric bending sensitivity is calculated based on the ratio of its outer diameter to its minimum bending radius. This geometric sensitivity is then weighted by the bending stiffness coefficient to obtain the cable bending response index. The bending response index quantifies the cable's sensitivity to bending during changes in its spatial path; a larger index value indicates a more sensitive cable, while a smaller index value indicates a less sensitive cable.

[0055] The cable bending potential energy coefficient is calculated by weighting or multiplying the bending stiffness coefficient and the bending response index. This coefficient quantifies the potential energy generated during cable bending. The bending potential energy coefficient reflects the risk of cable bending during spatial path changes; a higher value indicates a greater likelihood of strain or stress in the bending region, thus making the cable more likely to be avoided during path optimization.

[0056] The target cable to be laid is divided into sections using the cable bending potential energy coefficient to determine the bending response weight of each section. Specifically, the cable is divided into N consecutive sections based on its total length. The bending potential energy coefficient of each node within each section is calculated. All bending potential energy coefficients are accumulated and added together to obtain the overall bending potential energy value of that section. The bending potential energy values ​​of each section are then normalized or weighted to calculate the bending response weight of each section. A larger bending response weight indicates a higher bending sensitivity of the section, and the path optimization algorithm will prioritize avoiding high-weight sections during cable laying; a smaller weight indicates a lower bending sensitivity of the section, which can be laid preferentially.

[0057] A bending constraint function is constructed based on the bending response weight, the cable bending potential energy coefficient, and the minimum bending radius to limit excessive bending of the target cable to be laid. The bending response weight, bending potential energy coefficient, and the current bending radius of the cable are combined to construct the bending constraint function by setting a functional relationship. This can be done using a quadratic function approach. Specifically, the bending response weight w of the cable is... b Bending potential energy coefficient k bBy combining the current bending radius R of the cable with a defined functional relationship, a bending constraint function is constructed to dynamically constrain the minimum bending radius of the cable. The bending constraint function can be expressed in the form of a quadratic potential energy function, i.e.:

[0058] Where f(R) represents the bending constraint function; R min The minimum bending radius of the cable is preset; w b For bending response weights; k b R is the bending potential energy coefficient; R is the current real-time bending radius of the cable. When the cable bending radius is greater than R... min When the function value is small, the cable is in a safe bending state; when the cable bending radius is close to or lower than R... min When the function value increases rapidly, it generates a large virtual potential energy during the path optimization process, which drives the cable node to automatically adjust its position to avoid excessive bending.

[0059] A virtual cable model is constructed based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function. This involves discretizing the target cable into a series of spatial nodes, characterizing its bending resistance using the bending stiffness coefficient, calculating the bending potential energy of each node using the bending potential energy coefficient and bending response weight, and constraining the current bending radius of each node using the bending constraint function, thus creating a bending penalty for each node in the virtual model. Furthermore, based on the gradient of the bending potential energy, the virtual force acting on each node is calculated, and the spatial position of the node is iteratively updated according to this virtual force, gradually bringing the cable virtual model towards a low-potential-energy stable state and preventing nodes from exceeding the minimum bending radius. During the iteration process, the bending stiffness coefficient, bending potential energy coefficient, and bending response weight can be flexibly adjusted according to the cable type and actual laying environment to achieve adaptation to different cables and refined constraints. The final cable virtual model not only accurately reflects the bending state of the cable in complex spatial environments but can also be used to guide the optimization of actual laying paths, thereby ensuring safe cable laying.

[0060] By constructing the cable bending response index and bending potential energy coefficient, and introducing a bending constraint function to achieve segmented weighting and excessive bending constraints, the bending state of the cable can be accurately assessed, and the energy change rate can be adjusted when approaching the critical threshold to prevent excessive bending, thereby ensuring the safety, reliability and optimality of cable laying.

[0061] In one embodiment, a virtual cable model of the target cable to be laid is constructed based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function, including: S510. Discretize the target cable to be laid to obtain the cable node sequence; S520. Calculate the bending curvature formed by adjacent cable nodes in a cable node sequence; S530. The cable bending energy is calculated based on the bending curvature and bending potential energy coefficient. S540. The bending energy distribution of the cable section is obtained by weighting the bending energy corresponding to each cable node through bending response weight. S550: The bending curvature is adjusted using the bending limit function and bending energy distribution to limit the cable bending to no more than the minimum bending radius; S560. Based on the adjusted spatial location of the cable nodes, establish the connection relationship between the cable nodes to obtain the virtual cable model of the target cable to be laid.

[0062] First, the target cable is discretized, transforming the continuous cable into a series of discrete nodes with spatial coordinate information, thus forming a cable node sequence. Specifically, based on the coordinates of the cable's start and end points, the initial laying path of the cable is determined, and an appropriate node spacing or total number of nodes is selected according to the required modeling accuracy or cable length. Then, nodes are generated uniformly along the initial path at the selected spacing. Each node corresponds to the cable's position coordinates and additional attributes in three-dimensional space, such as bending radius, bending potential energy, and virtual stress. By arranging the generated nodes sequentially according to the cable laying order, a complete cable node sequence is obtained.

[0063] Secondly, the curvature formed by adjacent nodes in the cable node sequence is calculated. For the discretized cable node sequence {P1, P2, ..., Pn}, the curvature is calculated for every three consecutive nodes P... i−1 ,P i ,P i+1 As a computational unit, it calculates the vectors between nodes. and The included angle θ i To further determine the bending radius at the node, it can be calculated using the bending radius formula, which involves adding v1 and v2 and then applying the formula at 2sinθ. i After obtaining the bending radius, the reciprocal of the bending radius is used to obtain the local curvature.

[0064] The local curvature of each node is calculated using the method described above for the discretized cable node sequence. Based on virtual cable mechanics, the bending energy is correlated with the square of the curvature, as shown in the following expression:

[0065] Where Ui represents the local bending energy; k i Indicates local curvature; k bThis represents the bending potential energy coefficient. Bending energy increases with increasing curvature, reflecting the degree of bending penalty of the cable at that node. The overall bending energy of the cable is obtained by summing the bending energies of all nodes.

[0066] The bending energy of each node in the cable node sequence is weighted to obtain the bending energy distribution of the cable segment. Specifically, a bending response weight is assigned to each node based on its location in the cable segment, environmental constraints, or cable type, and the node's bending energy is multiplied by the corresponding weight to obtain the weighted bending energy. By accumulating or averaging the weighted node bending energies across all cable segments, the bending energy distribution of the cable segment is obtained, reflecting the bending strength and risk level of each segment. This segment bending energy distribution can be used to guide iterative optimization of nodes, adjusting the location of high-energy segments, and combining multiple factors such as bending constraint functions, magnetic field potential energy, and thermal radiation potential energy for comprehensive path optimization.

[0067] The bending curvature is adjusted using a bending constraint function and bending energy distribution to limit cable bending to within a minimum bending radius. Specifically, the bending constraint function increases its value when the node bending radius is below the minimum allowable radius, generating virtual penalty potential energy that drives the node to adjust its position. The bending energy distribution is the node energy weighted by the bending response. Substituting the node bending radius into the bending constraint function, when R... i <R min When the bending constraint function generates a large penalty value, the virtual force at the corresponding node increases, driving the node to adjust. In other words, the constraint function generates a large virtual potential energy to constrain excessive bending of the node. Subsequently, the virtual force at the node is calculated based on the bending energy gradient and the bending constraint function gradient, and the spatial position of the node is iteratively adjusted along the direction of reducing local curvature until the bending radius of all nodes meets the minimum bending radius requirement or the iteration converges.

[0068] After completing the curvature constraints and spatial position adjustments of the cable nodes, the connection relationships between the cable nodes are established based on the adjusted spatial positions, thereby constructing a virtual cable model of the target cable to be laid. The sequence of cable nodes, after bending constraint function constraints and bending energy distribution optimization, is represented as {P1′, P2′, ..., Pn′}, where each cable node contains corresponding three-dimensional spatial coordinate information to characterize the actual position of the cable in space. Subsequently, the connection relationships between adjacent nodes are established sequentially according to the cable laying direction, so that nodes Pi′ and Pi+1′ form spatial connection segments. By sequentially connecting each adjacent node, a set of cable path segments is formed, and further combined to form a continuous path structure of the cable in three-dimensional space, thus obtaining the virtual cable model of the target cable to be laid. The virtual cable model can realistically reflect the laying form and bending state of the cable in the spatial environment.

[0069] By discretizing the nodes of the cable, calculating the bending curvature and bending energy of adjacent nodes, and combining the bending response weight to realize the weighted characterization of the energy distribution of the section, and using the bending constraint function to dynamically adjust the curvature to ensure that it does not exceed the minimum bending radius constraint, the flexible deformation behavior and bending stress distribution of the cable in the actual laying process can be realistically simulated, providing a solid foundation for the optimal design of cable path.

[0070] In one embodiment, an energy coupling function for the target cable path is constructed based on the device's thermal radiation potential energy field, power frequency magnetic leakage potential energy field, magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient, including: S610. Obtain the cable nodes and the path arc length of the cable nodes for the target cable to be laid through the cable virtual model. S620. Map the cable nodes to the equipment thermal radiation potential energy field and the power frequency magnetic leakage potential energy field respectively to obtain the thermal radiation potential energy value and magnetic leakage potential energy value corresponding to each cable node. S630. Adjust the magnetic leakage potential energy value and thermal radiation potential energy value according to the magnetic repulsion response coefficient and thermal radiation repulsion response coefficient, and calculate the environmental response potential energy of each cable node. S640. The total environmental response potential energy of the target cable path is obtained by summing the environmental response potential energy of each cable node. S650. Calculate the path curvature corresponding to each cable node, and calculate the bending strain potential energy of each cable node through the bending stiffness coefficient, path curvature and path arc length. S660. The bending strain potential energy of each cable node is accumulated to obtain the total elastic strain potential energy of the target cable path to be laid. S670. Normalize the total potential energy of elastic strain and the total potential energy of environmental response. S680. Construct an energy coupling function using the normalized total potential energy of elastic strain and the total potential energy of environmental response.

[0071] A sequence of cable nodes arranged according to the cable laying order is extracted from the virtual cable model. Each cable node contains corresponding three-dimensional spatial coordinates to represent the specific position of the cable in space. Subsequently, the path length between each node is calculated based on the spatial distance between adjacent cable nodes. Taking the starting node of the cable as the arc length starting point, the path lengths between adjacent nodes are accumulated sequentially to obtain the cumulative path length of each cable node relative to the starting point of the cable, i.e., the path arc length of the cable node.

[0072] Cable nodes are mapped to the equipment's thermal radiation potential energy field and power frequency magnetic leakage potential energy field, respectively, to obtain the corresponding thermal radiation potential energy value and magnetic leakage potential energy value for each cable node. A sequence of cable nodes arranged according to the cable path is extracted from the virtual cable model, and the three-dimensional spatial coordinate information of each cable node is obtained to characterize the specific position of the cable in space. Subsequently, based on the spatial position and operating parameters of the substation's primary high-voltage equipment, the equipment's thermal radiation potential energy field and power frequency magnetic leakage potential energy field are constructed. The equipment's thermal radiation potential energy field describes the spatial distribution of thermal radiation generated during equipment operation, while the power frequency magnetic leakage potential energy field describes the spatial distribution of the power frequency magnetic field generated during equipment operation. Then, the spatial coordinates of each cable node are substituted into the aforementioned potential energy field model to calculate or query the energy value of the node at its corresponding spatial position, thereby obtaining the corresponding thermal radiation potential energy value and magnetic leakage potential energy value for each cable node.

[0073] The magnetic leakage potential energy and thermal radiation potential energy values ​​are adjusted based on the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient to calculate the environmental response potential energy of each cable node. After obtaining the magnetic leakage potential energy and thermal radiation potential energy values ​​corresponding to each cable node, the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient are introduced. The magnetic repulsion response coefficient is used to characterize the sensitivity of the target cable to the power frequency magnetic field environment, and the thermal radiation repulsion response coefficient is used to characterize the sensitivity of the target cable to the thermal radiation environment of the equipment. Subsequently, the magnetic leakage potential energy value and the magnetic repulsion response coefficient corresponding to each cable node are weighted and calculated, and the thermal radiation potential energy value and the thermal radiation repulsion response coefficient corresponding to each cable node are weighted and calculated. The two calculation results are then combined to obtain the environmental response potential energy value corresponding to each cable node.

[0074] After obtaining the environmental response potential energy corresponding to each cable node, the environmental response potential energy of each cable node is accumulated and calculated to obtain the total environmental response potential energy of the target cable path. Specifically, the sequence of cable nodes arranged sequentially along the cable path is obtained based on the cable virtual model, and the environmental response potential energy value corresponding to each cable node is extracted; then, the environmental response potential energy values ​​of each cable node are accumulated one by one according to the cable path direction, and the environmental response potential energy corresponding to all cable nodes is summed to obtain the total environmental response potential energy of the target cable path.

[0075] The path curvature corresponding to each cable node can be calculated using the three-point discretization method. The specific method for calculating curvature has been discussed in the above scheme and will not be repeated here. After obtaining the path curvature, the cable nodes arranged sequentially along the cable path and their corresponding path arc lengths are obtained from the cable virtual model. The path curvature of each cable node is then calculated to represent the degree of local bending of the node on the path. Subsequently, based on the cable's bending stiffness coefficient, the node path curvature and the corresponding path arc length are combined, and the bending strain potential energy of each cable node is calculated according to the bending energy calculation formula. This can be achieved using the beam bending formula in existing technology, where the bending strain potential energy of each node is jointly determined by the cable bending stiffness coefficient, the node path curvature, and the node arc length. By performing the above calculations on all nodes along the cable path, the bending strain potential energy distribution corresponding to each node is obtained, reflecting the bending state and local strain energy of the cable path in space.

[0076] After obtaining the bending strain potential energy corresponding to each cable node, the bending strain potential energy of all nodes along the cable path is accumulated to calculate the total elastic strain potential energy of the target cable path. The bending strain potential energy values ​​of each cable node arranged sequentially along the cable path are obtained from the cable virtual model. Then, the bending strain potential energy values ​​of each node are accumulated one by one according to the cable path direction. The bending strain potential energy of all nodes along the cable path is summed to obtain the total elastic strain potential energy of the entire cable path. This method allows for the overall quantification of the local bending energy of each node along the cable path, reflecting the total bending energy storage of the cable path.

[0077] Subsequently, the total potential energy of elastic strain and the total potential energy of environmental response are normalized. First, the maximum and minimum values ​​of the total potential energy of elastic strain and environmental response of the cable path are obtained. Then, the total potential energy values ​​are numerically mapped using a normalization calculation method, so that the normalized total potential energy of elastic strain and environmental response both fall within a uniform numerical range. This method allows the bending characteristics of the cable path and environmental factors to be represented on a unified quantitative scale, providing fundamental data for constructing the energy coupling function of the cable path.

[0078] The normalized total potential energy of elastic strain and the total potential energy of environmental response are used to construct the energy coupling function of the cable path. Specifically, the normalized total potential energy of elastic strain is denoted as E. bend The normalized total potential energy of the environmental response is denoted as E. envThe total potential energy of the environmental response characterizes the combined effects of external environmental factors such as equipment thermal radiation, power frequency magnetic leakage, and spatial obstacle avoidance constraints on the cable path in space. The total potential energy of elastic strain characterizes the internal elastic energy stored in the cable due to bending deformation under the current path configuration. Based on this, an energy coupling function for the cable path is constructed by weighting and coupling the two types of normalized energy. Specifically, the elastic energy weighting coefficient α and the environmental energy weighting coefficient β can be set, and the following energy coupling function can be constructed:

[0079] Where Et represents the comprehensive energy value of the cable path under the current spatial state; α represents the influence weight of cable bending deformation on path optimization, used to adjust the importance of cable bending constraints; β represents the influence weight of external environmental factors on path optimization, used to adjust the influence of factors such as equipment thermal radiation, magnetic field repulsion, and spatial structural constraints on cable path selection. In practical applications, the weight coefficients can be set according to the characteristics of the substation cable laying environment. For example, in densely equipped areas, the environmental energy weight coefficient can be appropriately increased to enhance the cable's ability to avoid equipment thermal radiation areas and magnetic field leakage areas; while in areas with many path bends, the elastic energy weight coefficient can be appropriately increased to ensure that the cable path meets the minimum bending radius constraint, thereby avoiding excessive cable bending. Specific weight coefficients can be selected through laboratory calibration to select representative substation equipment layout environments and cable laying scenarios. By constructing multiple sets of typical cable path samples, the actual operating states of different paths under the influence of equipment thermal radiation, power frequency magnetic field, and cable bending constraints are collected and analyzed. Multiple sets of combined tests are performed on the elastic energy weight coefficient and the environmental energy weight coefficient, and each set of weight coefficients is substituted into the energy coupling function for path optimization calculation to obtain the corresponding cable path results. Subsequently, the calculation results were compared and analyzed to comprehensively evaluate the performance of the obtained path in terms of bending rationality, equipment avoidance effect and overall path stability. The weight coefficient combination that can simultaneously meet the minimum bending radius constraint of the cable and effectively avoid high heat radiation area and high magnetic field area was selected as the final calibration parameter.

[0080] By constructing a multi-physics coupled energy function model, the electromagnetic safety protection requirements and the physical bending constraints of the cable can be simultaneously weighed when searching for the optimal path. This generates the optimal cable route that meets both electromagnetic compatibility standards and engineering laying process requirements, significantly improving the safety and rationality of cable laying in complex industrial environments.

[0081] In one embodiment, the environmental response potential energy of each cable node is calculated by adjusting the magnetic leakage potential energy value and the thermal radiation potential energy value based on the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient, including: S710. The magnetic leakage potential energy of each cable node is obtained by adjusting the magnetic leakage potential energy value through the magnetic repulsion response coefficient. S720. The thermal radiation response potential energy is obtained by adjusting the thermal radiation potential energy value of each cable node through the thermal radiation repulsion response coefficient. S730. Determine the environmental coupling modulation factor based on the intensity relationship between the nodal magnetic field response potential energy and the nodal thermal radiation response potential energy. S740. By using the potential energy proportional coupling formula and the environmental coupling modulation factor, the environmental response potential energy of each cable node is calculated in a coordinated manner to obtain the potential energy of the node magnetic field response and the potential energy of the node thermal radiation response.

[0082] After obtaining the magnetic leakage potential energy values ​​corresponding to each cable node along the cable path, the magnetic leakage potential energy values ​​are adjusted by introducing a magnetic field repulsion response coefficient to obtain the node magnetic field response potential energy corresponding to each cable node. Based on the pre-constructed power frequency magnetic leakage potential energy field, the magnetic leakage potential energy value corresponding to the spatial location of each cable node in the cable virtual model is obtained. The magnetic leakage potential energy value is used to characterize the strength of the influence of the power frequency magnetic field of the surrounding primary high-voltage equipment on the node location. Subsequently, according to the cable type of the target cable to be laid, the magnetic field repulsion response coefficient corresponding to the cable type is obtained from the preset cable parameter database. The magnetic field repulsion response coefficient is used to represent the repulsion sensitivity of the cable in the magnetic field environment. On this basis, the magnetic field repulsion response coefficient and the magnetic leakage potential energy value corresponding to each cable node are weighted and adjusted. That is, the magnetic leakage potential energy value of each cable node is weighted and calculated with the magnetic field repulsion response coefficient. By multiplying the magnetic leakage potential energy value and the magnetic field repulsion response coefficient, the original magnetic leakage potential energy value is amplified or scaled to obtain the magnetic field response potential energy value of the corresponding cable node.

[0083] Similarly, after obtaining the thermal radiation potential energy values ​​corresponding to each cable node along the cable path, a thermal radiation repulsion response coefficient, used to characterize the cable's sensitivity to the thermal environment, is introduced to weight and adjust the original thermal radiation potential energy, allowing the cable to adjust according to its heat resistance differences during path optimization. Based on the pre-constructed equipment thermal radiation potential energy field, the thermal radiation potential energy value corresponding to each cable node in the cable virtual model at its spatial location is obtained. The thermal radiation potential energy value is used to characterize the strength of the influence of heat dissipation from surrounding primary high-voltage equipment at that node location; the higher the equipment's thermal power or the closer the node is to the heat source equipment, the higher the corresponding thermal radiation potential energy value. Subsequently, according to the cable type of the target cable to be laid, the corresponding thermal radiation repulsion response coefficient is determined. The thermal radiation repulsion response coefficient is used to represent the cable's sensitivity to high-temperature environments and its ability to avoid thermal radiation areas. The thermal radiation repulsion response coefficient is then weighted and adjusted with the thermal radiation potential energy values ​​corresponding to each cable node. The thermal radiation potential energy value of each cable node is multiplied by the thermal radiation repulsion response coefficient. The original thermal radiation potential energy value is then amplified or scaled to obtain the thermal radiation response potential energy of the corresponding cable node. A larger thermal radiation repulsion response coefficient indicates that the target cable to be laid is more sensitive to high-temperature environments. The multiplication operation amplifies the node's thermal radiation potential energy value, thereby enhancing the repulsive effect of high-temperature areas on the cable path during subsequent path optimization calculations. Conversely, a smaller thermal radiation repulsion response coefficient indicates that this type of cable is less sensitive to thermal radiation environments, and the influence of thermal radiation potential energy on the overall energy calculation is relatively weakened.

[0084] The environmental coupling modulation factor is determined based on the strength relationship between the node magnetic field response potential energy and the node thermal radiation response potential energy. Specifically, the node magnetic field response potential energy and the node thermal radiation response potential energy corresponding to each cable node are determined through a virtual cable model. The node magnetic field response potential energy characterizes the intensity of the influence of the surrounding equipment's power frequency magnetic field on the node location, while the node thermal radiation response potential energy characterizes the intensity of the influence of the surrounding equipment's thermal radiation environment on the node location. Subsequently, to reflect the coupling relationship between the two environmental factors, a potential energy proportional coupling mechanism is used to construct the environmental coupling modulation factor. For the i-th cable node, the node magnetic field response potential energy is denoted as U. m,i Let the potential energy of the nodal thermal radiation response be denoted as U. t,i The environmental coupling modulation factor is calculated based on the following relationship:

[0085] Where, γ i This represents the environmental coupling modulation factor corresponding to the i-th cable node; This is the coupling strength coefficient, used to adjust the degree of coupling between two environmental factors; This is a very small positive number used to prevent the denominator from reaching zero. The coupling strength coefficient can be set based on laboratory data calibration statistics. A representative substation equipment layout scenario can be selected, and multiple sets of typical cable path samples can be constructed. The environmental potential energy distribution of each path under the combined effects of magnetic field and thermal radiation environments can be collected. These values ​​are then substituted into the environmental coupling modulation factor calculation formula for path optimization. Subsequently, the cable path results obtained under different coefficients are compared and analyzed to comprehensively evaluate the path's ability to avoid high magnetic field areas, high temperature areas, and overall path stability. The coefficient value that simultaneously meets the cable safety laying requirements and has the most reasonable path energy distribution is selected as the final coupling strength coefficient.

[0086] The potential energy ratio coupling formula is used to jointly calculate the magnetic field response potential energy and thermal radiation response potential energy of a node to obtain the environmental response potential energy corresponding to each cable node. Specifically, for the i-th cable node in the virtual cable model, the node's magnetic field response potential energy and thermal radiation response potential energy are determined, and the corresponding environmental coupling modulation factor is obtained. The environmental coupling modulation factor reflects the degree of coupling enhancement between the magnetic field environment and the thermal radiation environment. The environmental coupling modulation factor is then jointly calculated with the node's magnetic field response potential energy and thermal radiation response potential energy using the potential energy ratio coupling formula. This adjustment and fusion of the combined effects of the two environmental potential energies yields the environmental response potential energy corresponding to that cable node.

[0087] By introducing a dual-field collaborative modulation mechanism, the shortcomings of traditional environmental potential energy calculation, which involves independent accounting of the effects of multiple physical fields such as electromagnetic and thermal radiation and cannot reflect their collaborative constraint effects, are effectively solved. This significantly improves the fit between the environmental response potential energy calculation results and the actual cable laying and operation scenarios, and can more realistically and comprehensively reflect the environmental constraint intensity and operational risks of each cable node.

[0088] In one embodiment, energy iterative calculations are performed on the virtual cable model using an energy coupling function to determine the optimal laying path for the target cable, including: S810. Generate an initial path node sequence using the virtual cable model of the target cable to be laid; S820. Substitute the node data corresponding to each path node in each initial path node sequence into the energy coupling function to obtain the comprehensive energy value corresponding to each path node. S830. Calculate the corresponding spatial energy gradient based on the comprehensive energy value of each path node; S840. Construct virtual forces for each path node using spatial energy gradients, and iteratively update the spatial positions of the path nodes based on the virtual forces. S850. After iteratively updating the spatial positions of the path nodes, recalculate the comprehensive energy corresponding to the path nodes and perform path smoothing on the updated initial path node sequence. S860. When the change in comprehensive energy obtained from two consecutive iterations is less than the preset convergence threshold, the path corresponding to the current cable node sequence is determined as the optimal laying path for the target cable to be laid.

[0089] An initial path node sequence is generated using a virtual cable model of the target cable to be laid. The starting and ending connection positions of the target cable are determined based on equipment space information extracted from the Building Information Model (BIM), and these positions are used as the start and end nodes of the cable path. Subsequently, an initial spatial path is constructed between the start and end nodes based on their spatial relationship. This initial spatial path can be constructed using a straight-line connection, along the cable tray direction, or along a preset channel direction to obtain an initial cable path that satisfies basic connectivity. After obtaining the initial spatial path, it is discretized according to a preset node spacing, dividing the entire path into multiple consecutive path nodes, which are numbered in spatial order from the start to the end node, thus forming the initial path node sequence. Each path node contains corresponding spatial coordinate information and the connection relationships between adjacent nodes. The preset number of nodes can be determined based on the total length of the target cable to be laid. For example, first set the proportion of nodes corresponding to each unit length (e.g., 5 to 10 nodes per 10 meters), then calculate the number of nodes to be generated based on the total length of the cable, and distribute them evenly between the starting node and the ending node to form an initial path node sequence.

[0090] After generating the initial path node sequence, the spatial and environmental information corresponding to each path node is extracted, and this node data is substituted into a pre-constructed energy coupling function for calculation. This yields the comprehensive energy value of each path node at its current spatial location, used to characterize the rationality of the node's position within the overall cable path. Specifically, each path node is sequentially read from the initial path node sequence, and the node data corresponding to each path node is obtained. Node data typically includes the node's three-dimensional spatial coordinates, magnetic field response potential energy, thermal radiation response potential energy, and bending response parameters. The magnetic field response potential energy and thermal radiation response potential energy characterize the degree to which the node's location is affected by the surrounding equipment's magnetic field and thermal radiation environment, while the bending response parameters reflect the cable's bending state at that node. After acquiring the node data, the magnetic field response potential energy and thermal radiation response potential energy are fused using the aforementioned environmental response potential energy calculation method to obtain the corresponding environmental response potential energy for that node. Simultaneously, the elastic strain potential energy generated by the cable at that node is calculated based on the spatial relationship between the node and its adjacent nodes, used to characterize the internal energy generated by the cable's bending deformation. Based on this, the node's environmental response potential energy and the node's elastic strain potential energy are substituted into a pre-constructed energy coupling function for comprehensive calculation, thereby obtaining the comprehensive energy value corresponding to the path node.

[0091] Next, by analyzing the spatial variation of the comprehensive energy between adjacent nodes, the direction and rate of energy change in space are calculated, thus obtaining the spatial energy gradient at each path node. The spatial energy gradient reflects the direction of the most significant energy change along the cable path at the current spatial location and provides a directional basis for adjusting the path node positions using virtual forces. The comprehensive energy value and corresponding three-dimensional spatial coordinate information of each path node are obtained sequentially according to the initial path node sequence. Then, taking the current path node as the central node, its adjacent preceding and following nodes are selected as reference nodes. By comparing the changes in comprehensive energy values ​​between adjacent nodes and the corresponding spatial position differences, the rate of change of comprehensive energy in the spatial coordinate direction is calculated. For example, the energy change per unit distance can be calculated based on the energy difference between adjacent nodes and the spatial distance between nodes, thus obtaining the energy change trend of that node in space. Further combining the spatial coordinate information of the node, the energy change is decomposed into spatial coordinate axes, thus obtaining the spatial energy gradient vector corresponding to that node. The direction of the spatial energy gradient vector indicates the direction of the fastest increase in comprehensive energy, while its magnitude indicates the intensity of the energy change.

[0092] Virtual forces are constructed for each path node using spatial energy gradients, and the spatial positions of the path nodes are iteratively updated under the drive of these virtual forces. For each path node in the cable virtual model, the direction and magnitude of the virtual force are determined based on the spatial energy gradient corresponding to that node. The direction of the virtual force is set to be opposite to the direction of the spatial energy gradient, so that the path node moves in the direction of decreasing overall energy under the action of the virtual force. Simultaneously, the spatial energy gradient is proportionally converted according to a preset virtual force adjustment coefficient to obtain the virtual force for the corresponding path node. That is, in the actual calculation process, the spatial energy gradient vector is multiplied by the virtual force adjustment coefficient, and the direction of the virtual force is set to the opposite direction of the spatial energy gradient to obtain the virtual force vector corresponding to that path node. After obtaining the virtual force, the spatial coordinates of the path node are updated based on the virtual force. The spatial position of the path node is adjusted by superimposing a displacement in the same direction as the virtual force on the original node spatial position. After completing one node position update, the overall energy value and spatial energy gradient corresponding to the updated path node are recalculated, and the corresponding virtual force is constructed again to continue iteratively updating the spatial position of the path node. Through multiple iterative adjustments, each path node gradually moves towards a spatial location with lower overall energy until the preset iteration termination condition is met, thus obtaining a cable path configuration with a more reasonable overall energy distribution. The preset virtual force adjustment coefficient can be set based on the spatial spacing between path nodes. When the spacing between path nodes is small and the number of nodes is large, node movement is more sensitive during path optimization. In this case, the virtual force adjustment coefficient can be appropriately reduced to avoid excessive displacement of nodes during iteration, which could lead to path oscillations. When the spacing between path nodes is large, the virtual force adjustment coefficient can be appropriately increased, and the specific value can be set according to accuracy requirements. To ensure the stability and convergence of the iterative update, the virtual force adjustment coefficient can be set to a range of 0.01 to 0.5 (for example only). For instance, in actual implementation, a virtual force adjustment coefficient of 0.1 (for example only) can be selected and adjusted proportionally to the step size of each iteration to achieve smooth iterative updates of path nodes.

[0093] After updating the spatial positions of the path nodes, the updated path node sequence is reread, and the new spatial coordinate information of each path node is obtained. Then, based on the updated node spatial positions, the environmental response potential energy and elastic strain potential energy corresponding to each node are recalculated, and the recalculated potential energy data is substituted into the energy coupling function to obtain the updated comprehensive energy value for each path node. By recalculating the comprehensive energy, the changes in energy distribution of the current path can be determined, providing new energy basis for subsequent path optimization. Subsequently, path smoothing processing is performed on the updated path node sequence. Specifically, intermediate nodes in the path node sequence can be selected sequentially, and the position of the current node can be smoothly adjusted by combining the spatial coordinate information of the adjacent nodes before and after it. For example, the spatial position of the current node can be fine-tuned by using a weighted average of the coordinates of adjacent nodes or local curve fitting, making the connection relationship between path nodes smoother and more continuous, thereby reducing abrupt bends in the path. Simultaneously, during the path smoothing process, the minimum bending radius constraint of the cable can be used to constrain and correct the node position to avoid excessive bending that does not meet the cable laying requirements.

[0094] During the path optimization iteration process, by comparing the changes in the overall energy of the path obtained from two adjacent iterations, when the change in overall energy is very small, it indicates that the path optimization has stabilized. At this point, the current path can be considered close to the stable state with the lowest energy, thus determining the path formed by the current path node sequence as the final optimal cable laying path. After each update of the spatial position of the path nodes and completion of the overall energy calculation, the overall overall energy corresponding to the current path node sequence is statistically calculated. For example, the overall overall energy value of the current path is obtained by accumulating or averaging the overall energy values ​​of all path nodes, and this energy value is recorded as the path energy of the current iteration. Subsequently, after completing the next round of path node position updates and energy calculations, a new overall overall energy value of the path is obtained and compared with the overall overall energy value of the path corresponding to the previous iteration to calculate the change in overall energy between the two iterations. Then, it is compared with a pre-set convergence threshold. When the change in overall energy exceeds the preset convergence threshold, it indicates that there is still significant room for adjustment in path optimization. It is necessary to continue calculating the virtual force based on the spatial energy gradient and further iteratively update the path node positions. When the change in overall energy is less than or equal to the preset convergence threshold, it indicates that the overall energy of the path has basically stabilized, and the path morphology is converging. At this point, the path iteration calculation is stopped, and the cable path corresponding to the current path node sequence is determined as the optimal laying path for the target cable. The preset convergence threshold can be determined through simulation testing or experimental calibration. A comparative analysis of the number of iterations, path stability, and final path energy value during the path optimization process is conducted to select a threshold that ensures stable convergence of the path optimization results while maintaining high computational efficiency. For practical implementation, the preset convergence threshold can be set in the range of 0.001 to 0.01 (for example only). For instance, 0.005 (for example only) can be used as the threshold for path iteration convergence judgment to ensure that the path node iteration update achieves a balance between optimization effect and computational efficiency.

[0095] By performing energy iteration calculations on the virtual cable model using the energy coupling function, the optimal laying path of the target cable can be determined. This effectively solves the pain points of traditional cable path planning methods, such as being prone to getting stuck in local optima, insufficient convergence stability, and weak multi-objective collaborative optimization capabilities. It also achieves multi-dimensional collaborative optimization of cable structure safety, environmental adaptability, and construction and maintenance feasibility, significantly improving the computational efficiency and solution accuracy of cable laying path planning.

[0096] This application also provides a machine-readable storage medium storing instructions that cause a machine to execute the above-described BIM-based automatic optimization method for substation cable laying paths.

[0097] This application also provides an electronic device, including: The memory is configured to store instructions; and The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the aforementioned BIM-based automatic optimization method for substation cable laying paths.

[0098] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0099] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0102] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0103] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0104] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0105] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0106] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A BIM-based automatic optimization method for substation cable laying paths, characterized in that, include: Obtain the building information model of the target substation; Based on building information modeling, extract equipment spatial information and equipment operation information of primary high-voltage equipment, building structural spatial information and target cable information to be laid; By combining equipment spatial information and equipment operation information, the thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation are constructed. Based on the information of the target cable to be laid, the cable type of the target cable to be laid is determined, and the magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient and bending stiffness coefficient are determined according to the cable type using a preset cable parameter database. A virtual model of the target cable is constructed by combining the bending stiffness coefficient and the information of the target cable to be laid; An energy coupling function for the target cable path to be laid is constructed based on the equipment's thermal radiation potential energy field, power frequency magnetic leakage potential energy field, magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient. By combining the energy coupling function to perform energy iterative calculations on the virtual cable model, the optimal laying path of the target cable to be laid is determined. The building information model is updated based on the optimal laying path, and the corresponding cable spatial constraint potential energy distribution is generated based on the optimal laying path. Based on the spatially constrained potential energy distribution of the cables, a path optimization step is performed on the remaining cables to be laid until the optimal laying path is determined for all cables.

2. The method according to claim 1, characterized in that, The construction of the equipment thermal radiation potential energy field and power frequency magnetic leakage potential energy field of the target substation by combining equipment spatial information and equipment operation information includes: Extract the spatial coordinates of the primary high-voltage equipment from the equipment spatial information; Extract the equipment operating current, load rate, heat dissipation coefficient, magnetic field strength, and magnetic leakage coefficient of the primary high-voltage equipment from the equipment operation information; The surface thermal power value of the primary high-voltage equipment is calculated using the equipment operating current, load rate, and equipment heat dissipation coefficient. A thermal radiation attenuation model is constructed by combining the spatial coordinates of the primary high-voltage equipment and the surface thermal power value. The thermal radiation potential energy field of the equipment in the target substation was determined using a thermal radiation attenuation model. The magnetic leakage potential energy value of the target substation is constructed based on the spatial location coordinates, the magnetic field strength of the equipment, and the magnetic leakage coefficient of the equipment. The power frequency magnetic leakage potential energy field of the target substation is determined by the magnetic leakage potential energy value.

3. The method according to claim 2, characterized in that, The determination of the equipment thermal radiation potential energy field of the target substation using the thermal radiation attenuation model includes: The building information model of the target substation is discretized to obtain multiple spatial grid nodes; Calculate the spatial distance between each spatial grid node and the primary high-voltage equipment, and calculate the thermal radiation potential energy value corresponding to each spatial grid node through the spatial distance and thermal radiation attenuation model; The thermal radiation potential energy values ​​of each primary high-voltage device within each spatial grid node are superimposed to obtain the comprehensive thermal radiation potential energy value corresponding to each spatial grid node. The thermal radiation potential energy field of the target substation is constructed based on the comprehensive thermal radiation potential energy value of each spatial grid node.

4. The method according to claim 1, characterized in that, The construction of a virtual cable model of the target cable to be laid, combining the bending stiffness coefficient and the target cable information, includes: Obtain the cable's outer diameter and minimum bending radius by analyzing the information of the target cable to be laid; The cable bending response index is calculated by combining the cable outer diameter, minimum bending radius, and bending stiffness coefficient. The cable bending response index is used to represent the bending sensitivity of the cable during the spatial path change process. The bending potential energy coefficient of the cable is calculated based on the bending stiffness coefficient and the bending response index of the cable. The bending response weight is determined by dividing the target cable to be laid into sections based on the cable bending potential energy coefficient. A bending limit function is constructed based on the bending response weight, the cable bending potential energy coefficient, and the minimum bending radius. The bending limit function is used to indicate that when the cable bending degree approaches the limit threshold, the bending energy change rate is increased to limit excessive bending. A virtual model of the cable to be laid is constructed based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function.

5. The method according to claim 4, characterized in that, The virtual cable model for constructing the target cable to be laid, based on the bending stiffness coefficient, bending potential energy coefficient, bending response weight, and bending constraint function, includes: The target cable to be laid is discretized to obtain the cable node sequence; Calculate the curvature formed by adjacent cable nodes in a cable node sequence; The cable bending energy is calculated based on the bending curvature and bending potential energy coefficient. The bending energy distribution of the cable section is obtained by weighting the bending energy corresponding to each cable node using bending response weights. The bending curvature is adjusted by using a bending limit function and bending energy distribution to limit the cable bending to no more than the minimum bending radius; Based on the adjusted spatial location of the cable nodes, the connection relationship between the cable nodes is established to obtain the virtual cable model of the target cable to be laid.

6. The method according to claim 1, characterized in that, The energy coupling function for constructing the target cable path based on the equipment's thermal radiation potential energy field, power frequency magnetic leakage potential energy field, magnetic field repulsion response coefficient, thermal radiation repulsion response coefficient, and bending stiffness coefficient includes: The cable nodes and the path arc length of the cable nodes are obtained through a virtual cable model. The cable nodes are mapped to the equipment's thermal radiation potential energy field and power frequency magnetic leakage potential energy field respectively to obtain the thermal radiation potential energy value and magnetic leakage potential energy value corresponding to each cable node. The environmental response potential energy of each cable node is calculated by adjusting the magnetic leakage potential energy value and the thermal radiation potential energy value based on the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient. The total environmental response potential energy of the target cable path is obtained by summing the environmental response potential energy of each cable node. Calculate the path curvature corresponding to each cable node, and calculate the bending strain potential energy of each cable node through the bending stiffness coefficient, path curvature and path arc length; The total elastic strain potential energy of the target cable path is obtained by summing the bending strain potential energy of each cable node. The total potential energy of elastic strain and the total potential energy of environmental response are normalized. An energy coupling function is constructed using the normalized total potential energy of elastic strain and the total potential energy of environmental response.

7. The method according to claim 6, characterized in that, The calculation of the environmental response potential energy of each cable node, based on the magnetic repulsion response coefficient and the thermal radiation repulsion response coefficient, adjusts the magnetic leakage potential energy value and the thermal radiation potential energy value, including: The magnetic leakage potential energy of each cable node is obtained by adjusting the magnetic leakage potential energy value of each cable node through the magnetic repulsion response coefficient. The thermal radiation response potential energy is obtained by adjusting the thermal radiation potential energy value of each cable node through the thermal radiation repulsion response coefficient. The environmental coupling modulation factor is determined based on the intensity relationship between the nodal magnetic field response potential energy and the nodal thermal radiation response potential energy. The environmental response potential energy of each cable node is obtained by using the potential energy proportional coupling formula and the environmental coupling modulation factor to jointly calculate the node magnetic field response potential energy and the node thermal radiation response potential energy.

8. The method according to claim 1, characterized in that, The step of performing energy iteration calculations on the virtual cable model using the energy coupling function to determine the optimal laying path for the target cable includes: An initial path node sequence is generated using a virtual model of the target cable to be laid. Substitute the node data corresponding to each path node in each initial path node sequence into the energy coupling function to obtain the comprehensive energy value corresponding to each path node; Calculate the corresponding spatial energy gradient based on the comprehensive energy value of each path node; The virtual force of each path node is constructed by the spatial energy gradient, and the spatial position of the path node is iteratively updated according to the virtual force. After iteratively updating the spatial positions of the path nodes, the comprehensive energy corresponding to the path nodes is recalculated, and the updated initial path node sequence is smoothed. When the change in comprehensive energy obtained from two consecutive iterations is less than the preset convergence threshold, the path corresponding to the current cable node sequence is determined as the optimal laying path for the target cable to be laid.

9. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to execute the BIM-based automatic optimization method for substation cable laying paths according to any one of claims 1 to 8.

10. An electronic device, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the BIM-based automatic optimization method for substation cable laying paths according to any one of claims 1 to 8.

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