Optimization design method of dc high voltage power transmission line based on electric field mirror theory

Abstract

The application belongs to the technical field of high-voltage power transmission and electromagnetic field coupling analysis, and specifically discloses a DC high-voltage power transmission line optimization design method based on an electric field mirror theory. According to the application, a unit length capacitance matrix is solved according to an electromagnetic field analytical model; an objective function of the transmission line design is constructed; the iteration solution of the to-be-optimized variables in the parameterized geometric model is carried out according to the objective function and an objective intelligent optimization algorithm, and the transmission line optimization design is carried out according to the optimal structure parameters and the corresponding unit length distribution parameters. Through the above mode, for the coupling relationship among the internal multi-conductor, shielding layer and ground reference boundary in the multi-stage DC high-voltage power system, the electromagnetic field analytical model is introduced to solve the unit length capacitance matrix, the optimal structure parameters are iteratively solved by using the objective intelligent optimization algorithm, and the design is carried out in combination with the unit length distribution parameters, so that the transmission line optimization design for the insulation reliability and transient security can be realized.

Description

Technical Field

[0001] This application belongs to the field of high-voltage power transmission and electromagnetic field coupling analysis technology, and more specifically, relates to an optimization design method for DC high-voltage power transmission lines based on electric field image theory. Background Technology

[0002] Multi-stage DC high-voltage power supplies are widely used in neutral beam injection systems of fusion devices, high-voltage test platforms, and other scenarios requiring megavolt-level DC output. These systems typically consist of multiple high-voltage output stages connected in series to form a total high-voltage output, which is then transmitted to the high-voltage load via transmission lines. During this process, significant electromagnetic coupling exists between conductors within the transmission line, between conductors and the shielding layer, and between the shielding layer and ground, resulting in non-negligible distributed capacitance, distributed inductance, distributed resistance, and distributed conductance.

[0003] Currently, transmission line design typically starts with rated voltage, insulation distance, or empirical structural dimensions for initial determination, followed by minor adjustments through electromagnetic simulations. However, in practical applications, this approach has the following shortcomings: First, it determines the structure solely from the perspective of static insulation distance, failing to simultaneously consider multi-conductor coupling, electric field distribution, and distributed parameter energy. Second, it lacks a unified optimization design framework, making it difficult to achieve a balance between insulation safety, coupling suppression, and structural compactness. Third, there is a lack of a unified mapping relationship between transmission line parameter design and subsequent high-voltage system simulation analysis. Therefore, this approach cannot achieve optimized transmission line design that addresses both insulation reliability and transient safety. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this application aims to provide a DC high-voltage power supply transmission line optimization design method based on electric field mirror theory. This method addresses the problems of existing technologies failing to simultaneously consider multi-conductor coupling, electric field distribution and distributed parameter energy, the difficulty in achieving a balance between insulation safety, coupling suppression and structural compactness, and the lack of a unified mapping relationship between transmission line parameter design and subsequent high-voltage system simulation analysis, which prevents the implementation of transmission line optimization design oriented towards insulation reliability and transient safety.

[0005] To achieve the above objectives, in a first aspect, this application provides a DC high-voltage power supply transmission line optimization design method based on electric field image theory, comprising: The parameterized geometric model of the transmission line is converted into an analytical electromagnetic field model, and the unit-length capacitance matrix is ​​solved based on the analytical electromagnetic field model. Calculate the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface based on the unit length capacitance matrix. The objective function for the transmission line design is constructed based on the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface. The parameters to be optimized in the parameterized geometric model are iteratively solved according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints. The transmission line is then optimized based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters.

[0006] In one embodiment, the step of converting the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and solving for the unit-length capacitance matrix based on the analytical electromagnetic field model, includes: Obtain information about the internal conductors of the transmission line to be designed and the radius of the cylindrical shielding layer to be arranged; Conductor spacing constraints are constructed based on the internal conductor information and minimum spacing margin, and net spacing constraints are constructed based on the internal conductor information, the radius, and the minimum net spacing between the internal conductor and the cylindrical shielding layer. A parameterized geometric model of the transmission line is constructed based on the conductor spacing constraint and the net spacing constraint, and the parameterized geometric model of the transmission line is converted into an analytical electromagnetic field model of the transmission line cross section. The self-potential coefficient and mutual potential coefficient are determined based on the electromagnetic field analytical model and the material parameter model. Construct a potential coefficient matrix based on the self-potential coefficient and the mutual potential coefficient, and solve for the unit length capacitance matrix based on the potential coefficient.

[0007] In one embodiment, the step of calculating the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface based on the unit length capacitance matrix includes: Obtain the transmission line length and the voltage vector of the internal conductor relative to the cylindrical shielding layer, respectively. The total energy stored in the distributed capacitance of the transmission line is calculated based on the transmission line length, the voltage vector, and the unit length capacitance matrix. The normal electric field distribution at different angular positions on the surface of each internal conductor is determined based on the voltage vector and the unit length capacitance matrix. The normal electric field distributions at different angular positions on the surface of each internal conductor are sorted according to a preset sorting rule, and the maximum value in the sorting result is taken as the maximum electric field intensity on the conductor surface.

[0008] In one embodiment, the step of determining the normal electric field distribution at different angular positions on the surfaces of each internal conductor based on the voltage vector and the unit-length capacitance matrix includes: Calculate the linear charge density per unit length of each conductor based on the voltage vector and the unit length capacitance matrix; Calculate the center coordinates based on the central polar diameter and central polar angle of the internal conductor; Calculate the coordinates of the surface point corresponding to the surface parameter angle based on the coordinates of the center of the circle and the radius of the inner conductor, and calculate the electric field vector at the coordinates of the surface point. The outward normal unit vector is determined based on the surface parameter angle; The normal electric field distribution at different angular positions on the surface of each internal conductor is determined based on the electric field vector, the outward normal unit vector, and the linear charge density per unit length of each conductor.

[0009] In one embodiment, the step of iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints, and then performing transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters, includes: The target constraint conditions are determined based on the conductor spacing constraint, net spacing constraint, and maximum electric field strength constraint. The optimal structural parameters that satisfy the objective constraints are obtained by iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm. Determine the unit length distribution parameters corresponding to the optimal structural parameters, and perform transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters.

[0010] In one embodiment, the step of iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints includes: The variables to be optimized in the parametric geometric model are determined based on the internal conductor information, the radius of the arranged cylindrical shielding layer, and the central polar coordinates. Construct a multi-objective optimization model based on the objective function and / or a preset set of optional objectives; Based on the multi-objective optimization model, the variables to be optimized are iteratively solved using the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints.

[0011] Secondly, this application provides a DC high-voltage power transmission line optimization design device based on electric field image theory, comprising: The solver module is used to convert the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and to solve for the unit-length capacitance matrix based on the analytical electromagnetic field model. The calculation module is used to calculate the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface based on the unit length capacitance matrix. The construction module is used to construct the objective function for the transmission line design based on the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface; The optimization design module is used to iteratively solve the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints, and to perform transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters.

[0012] Thirdly, this application provides an electronic device, comprising: at least one memory for storing a program; and at least one processor for executing the program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to execute the method described in the first aspect or any possible implementation thereof.

[0013] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0014] Fifthly, this application provides a computer program product that, when run on a processor, causes the processor to perform the method described in the first aspect or any possible implementation thereof.

[0015] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0016] Overall, the technical solutions conceived in this application have the following beneficial effects compared with the prior art: (1) This application addresses multi-stage DC high-voltage power supply systems consisting of at least two high-voltage output stages connected in series. It transforms the coupling relationships between conductors, between conductors and shielding layers, and between shielding layers and ground into quantifiable distributed parameters, rather than relying solely on empirical insulation distances. This approach simultaneously considers the three types of coupling relationships: between conductors, between conductors and shielding layers, and between shielding layers and ground, thereby improving the accuracy of solving the distributed parameters of the transmission line. After constructing the parameterized geometric model of the transmission line, the parameterized geometric model is converted into an analytical electromagnetic field model of the transmission line cross-section. The unit-length capacitance matrix is ​​then solved based on the analytical electromagnetic field model. Furthermore, the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface are calculated separately. The variables to be optimized in the parameterized geometric model are iteratively solved, and then the design is carried out in conjunction with the unit-length distributed parameters. This enables the optimized design of the transmission line that addresses both insulation reliability and transient safety.

[0017] (2) This application will also construct a multi-objective optimization model containing one or more objectives from the set of distributed capacitance total energy storage target, conductor surface maximum electric field strength target and / or preset optional objectives, to complete the multi-objective trade-off, and use particle swarm optimization algorithm, genetic algorithm, non-dominated sorting genetic algorithm (NSGA-II) or differential evolution algorithm to iteratively solve the above problems, and obtain the optimal structural parameters or Pareto optimal structural parameters that meet the objective constraints. This solves the limitations of the existing technology that only relies on empirical dimensions or only considers a single coupling relationship for transmission line design, as well as the problems of insufficient engineering pertinence and weak practical significance in the parameter design process. It ensures that multi-stage DC high voltage power transmission lines achieve lower energy storage risk, better field strength distribution and higher system reliability under the premise of meeting insulation safety requirements. Compared with manual trial calculation and limited number of simulation corrections, it can effectively improve the efficiency of transmission line optimization design.

[0018] In summary, this application converts the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and solves for the unit-length capacitance matrix based on the analytical electromagnetic field model. It then calculates the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface based on the unit-length capacitance matrix. Finally, it constructs the objective function for the transmission line design based on the total energy stored in the distributed capacitance and the maximum electric field strength on the conductor surface. The objective function and an intelligent optimization algorithm are used to iteratively solve for the variables to be optimized in the parameterized geometric model to obtain the optimal structural parameters that satisfy the objective constraints. The transmission line is then optimized based on these optimal structural parameters and the corresponding unit-length distributed parameters. Through this method, for the coupling relationship between internal multiple conductors, shielding layers, and ground reference boundaries in a multi-stage DC high-voltage power supply system, an analytical electromagnetic field model is introduced to solve for the unit-length capacitance matrix. Further calculations of the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface are then performed. An intelligent optimization algorithm is used to iteratively solve for the optimal structural parameters, and the design is then combined with the unit-length distributed parameters. This enables optimized transmission line design that addresses both insulation reliability and transient safety. Attached Figure Description

[0019] Figure 1 This is one of the flowcharts illustrating the DC high-voltage power supply transmission line optimization design method based on electric field image theory provided in this application embodiment; Figure 2 This is a schematic diagram of the system topology provided in the embodiments of this application; Figure 3 This is a schematic diagram of the cross-section of the transmission line provided in an embodiment of this application; Figure 4 This is the second flowchart illustrating the DC high-voltage power supply transmission line optimization design method based on electric field image theory provided in this application embodiment; Figure 5 This is a schematic diagram of the module structure of the DC high voltage power supply transmission line optimization design device based on electric field image theory provided in the embodiments of this application; Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0021] In this article, the term "and / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. The symbol " / " in this article indicates that the related objects are in an "or" relationship; for example, A / B means A or B.

[0022] The terms "first" and "second," etc., used in the specification and claims herein are used to distinguish different objects, not to describe a specific order of objects. For example, "first response message" and "second response message," etc., are used to distinguish different response messages, not to describe a specific order of response messages.

[0023] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0024] Based on this, embodiments of this application provide an optimized design method for DC high-voltage power supply transmission lines based on electric field image theory, referring to... Figure 1 , Figure 1 This is one of the flowcharts illustrating the DC high-voltage power supply transmission line optimization design method based on electric field image theory provided in this application embodiment. In this embodiment, the DC high-voltage power supply transmission line optimization design method based on electric field image theory includes steps S10 to S40: Step S10: Convert the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and solve for the unit length capacitance matrix based on the analytical electromagnetic field model.

[0025] It should be noted that this embodiment is applicable to multi-stage DC high-voltage power supply systems consisting of at least two high-voltage output stages connected in series. (Refer to...) Figure 2 , Figure 2This is a schematic diagram of the system topology, specifically consisting of: an n-stage DC high-voltage power supply, transmission lines, and a high-voltage load. The relationship between these three is as follows: each high-voltage output stage is connected to the high-voltage load via the transmission lines. The interface between the n-stage DC high-voltage power supply and the transmission lines can be the source end, and the interface between the transmission lines and the high-voltage load can be the load end. The n-stage DC high-voltage power supply can be output in series, and the outer shielding layer can be a cylindrical metal sheath. (Reference) Figure 3 , Figure 3 This is a schematic diagram of the cross-section of the transmission line, which specifically includes multiple inner conductors, namely inner conductor 1 to inner conductor n. Insulating media are provided between the inner conductors and between the inner conductors and the outer shielding layer to avoid contact.

[0026] To transform the coupling relationships between conductors, between conductors and the shield, and between the shield and ground into quantifiable distributed parameters, rather than relying solely on empirical insulation distances, this method simultaneously considers all three types of coupling relationships—between conductors, between conductors and the shield, and between the shield and ground—improving the accuracy of solving for the distributed parameters of the transmission line. Furthermore, compared to the finite element method, it significantly increases the speed of solving the capacitance matrix per unit length. After constructing a parameterized geometric model of the transmission line, this model is converted into an analytical electromagnetic field model of the transmission line's cross-section, and the capacitance matrix per unit length is then solved based on this analytical electromagnetic field model.

[0027] Further, step S10 includes: obtaining information about the internal conductors of the transmission line to be designed and the radius of the arranged cylindrical shielding layer; constructing conductor spacing constraints based on the internal conductor information and the minimum spacing margin, and constructing net spacing constraints based on the internal conductor information, the radius, and the minimum net spacing between the internal conductors and the cylindrical shielding layer; constructing a parameterized geometric model of the transmission line based on the conductor spacing constraints and the net spacing constraints, and converting the parameterized geometric model of the transmission line into an analytical electromagnetic field model of the transmission line cross-section; determining the self-potential coefficient and the mutual potential coefficient based on the analytical electromagnetic field model and the material parameter model; constructing a potential coefficient matrix based on the self-potential coefficient and the mutual potential coefficient, and solving for the unit length capacitance matrix based on the potential coefficient.

[0028] It should be understood that by uniformly parameterizing the internal conductor radius, conductor position, shielding radius, distance to ground, transmission line length, and material parameters to construct a parameterized geometric model of the transmission line, the transmission line structure is transformed from empirical selection into a set of calculable, constrainable, and optimizable design variables. Furthermore, the parameterized geometric model of the transmission line needs to satisfy conductor spacing constraints and net spacing constraints. The purpose of setting conductor spacing constraints is to ensure that internal conductors do not overlap, and the purpose of setting net spacing constraints is to ensure that the internal conductors maintain a minimum net distance from the cylindrical shielding layer. Specifically:

[0029]

[0030] .

[0031] in, Indicates spacing, a i Indicates the first i The radius of the conductor inside the root, a j Indicates the first j The radius of the conductor inside the root, Indicates the minimum margin. Indicates the first i The central polarity of the conductor inside the root, Indicates the first j The central polarity of the conductor inside the root, This indicates the minimum clear distance between the internal conductor and the cylindrical shielding layer. b This indicates the radius of the cylindrical shielding layer. and They represent the first i Root internal conductor and the first j The central polar angle of the conductor inside the root.

[0032] It should be noted that, in addition to constructing the parameterized geometric model of the transmission line, this embodiment will also construct a material parameter model. This material parameter model includes at least the dielectric constant of the dielectric. For the cross-section of a cylindrical shielded multi-conductor transmission line, an analytical electromagnetic field model is used to determine the self-potential coefficient and the mutual potential coefficient, specifically:

[0033] .

[0034] in, P ii Represents the self-potential coefficient. P ij Represents the mutual potential coefficient. Indicates the dielectric constant of the internal medium. and They represent the first i Root internal conductor and the first j The central polar angle of the conductor inside the root.

[0035] It should be understood that, when determining the self-potential coefficients separately P ii and mutual potential coefficient P ij Next, the potential coefficient matrix is ​​constructed as follows: .

[0036] It should be noted that in constructing the potential coefficient matrix... P Then, the unit-length capacitance matrix can be solved. This is a key technical detail in solving the transmission line capacitance matrix, which directly reflects the electrostatic coupling between multiple internal conductors and between the internal conductors and the cylindrical shielding layer. Specifically: C=P -1 .

[0037] in, C Represents a unit-length capacitance matrix. P This represents the potential coefficient matrix.

[0038] Step S20: Calculate the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface based on the unit length capacitance matrix.

[0039] Understandably, to address the energy release risks associated with abnormal transients such as arcing and short circuits in multi-stage DC high-voltage systems, the total energy storage of the transmission line distributed capacitance is used as a core evaluation indicator. This differs from design methods that only perform static insulation dimension checks. In this case, the total energy storage of the transmission line distributed capacitance needs to be calculated separately based on the capacitance matrix per unit length. Furthermore, to identify local electric field hotspots and weak insulation locations, and to ensure that the optimization results simultaneously meet both overall energy storage and local field strength safety requirements, the maximum electric field strength on the conductor surface also needs to be calculated based on the capacitance matrix per unit length. Using the total energy storage of the transmission line distributed capacitance and the maximum electric field strength on the conductor surface as core design indicators effectively improves the consistency between insulation design and transient safety design.

[0040] Step S30: Construct the objective function for the transmission line design based on the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface.

[0041] It should be understood that the objective function refers to the function used to solve for the optimal structural parameters that satisfy the objective constraints. This objective function may include at least the total energy storage of the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface. It considers multiple core indicators to achieve unified optimization of insulation reliability and transient safety. Compared with methods that only consider a single indicator, the design results are more comprehensive and reliable. In addition, this embodiment will also construct objective constraints, which include at least the non-overlapping constraint between conductors, the minimum net distance constraint between conductors and the shielding layer, and the maximum electric field strength constraint. The total energy storage of the distributed capacitance, the maximum electric field strength on the surface, the non-overlapping of conductors, the net distance to the shielding layer, and the maximum electric field strength constraint are uniformly constructed into an optimization problem to realize the system design of multi-stage DC high-voltage power transmission lines.

[0042] Step S40: Iteratively solve the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints, and perform transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters.

[0043] Understandably, after determining the objective function, introducing an intelligent optimization algorithm to iteratively solve the variables to be optimized in the parameterized geometric model can effectively improve the efficiency of transmission line optimization design compared to manual trial calculations and finite-number simulation corrections. This leads to the optimal design scheme under multiple objective trade-offs. The intelligent optimization algorithm can be at least one of particle swarm optimization, genetic algorithm, NSGA-II, or differential evolution algorithm. The final iterative solution can be the optimal structural parameters that satisfy the objective constraints or the Pareto optimal structural parameters. At this point, combining the unit length distribution parameters corresponding to the optimal structural parameters for transmission line optimization design directly serves subsequent electromagnetic transient simulation, insulation verification, and engineering implementation, forming a closed loop of "structural design—parameter calculation—performance verification." This solves the problem of the lack of a unified mapping relationship between transmission line parameter design and subsequent high-voltage system simulation analysis in existing technologies.

[0044] Further, step S40 includes: determining the target constraint conditions based on the conductor spacing constraint, net spacing constraint, and maximum field strength constraint; iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the target intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the target constraint conditions; determining the unit length distribution parameters corresponding to the optimal structural parameters, and performing transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters.

[0045] It should be understood that the target constraints include at least conductor spacing constraints, net spacing constraints, and maximum electric field strength constraints. During the iterative solution of the variables to be optimized in the parametric geometric model, these target constraints must also be considered, ensuring that the final optimal structural parameters satisfy the target constraints and yielding the preferred design scheme under a multi-objective trade-off. After solving for the optimal structural parameters that satisfy the target constraints, further transmission line optimization design is needed, taking into account the unit length distribution parameters, to facilitate subsequent simulation verification and engineering implementation.

[0046] Furthermore, the step of iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints includes: determining the variables to be optimized in the parameterized geometric model based on the internal conductor information, the radius of the arranged cylindrical shielding layer, and the central polar coordinates; constructing a multi-objective optimization model based on the objective function and / or a preset set of optional objectives; and iteratively solving the variables to be optimized according to the objective intelligent optimization algorithm based on the multi-objective optimization model to obtain the optimal structural parameters that satisfy the objective constraints.

[0047] It should be noted that the variable to be optimized in the parametric geometric model refers to the relevant variable used in the iterative solution. This variable to be optimized can be represented as: ,in, a 1 to a n represents the radius of each internal conductor. to These represent the center polarities of each internal conductor. to These represent the center polar angles of each internal conductor. b This represents the radius of the cylindrical shielding layer. To obtain the optimal design scheme under multiple objective trade-offs, this embodiment, when constructing the multi-objective optimization model, can select one or more objectives from a preset set of optional objectives, in addition to the total energy storage objective of the distributed capacitance and the maximum electric field intensity objective on the conductor surface. This preset set of optional objectives includes, but is not limited to, volume objectives, weight objectives, coupling degree objectives, and manufacturing cost objectives. The constructed multi-objective optimization model can then be expressed as:

[0048]

[0049] .

[0050] in, This represents the total energy storage target of the distributed capacitance. This represents the target maximum electric field strength on the conductor surface. to This represents the target in the preset set of optional targets. L Indicates the length of the transmission line. V This represents the voltage vector of the internal conductor relative to the cylindrical shielding layer. C Represents a unit-length capacitance matrix. This represents the field strength at the most dangerous surface of the system.

[0051] Understandably, after constructing a multi-objective optimization model, particle swarm optimization, genetic algorithm, NSGA-II, or differential evolution algorithm are used to iteratively solve the above problems to obtain the optimal structural parameters or Pareto optimal structural parameters that satisfy the objective constraints. This solves the limitations of existing technologies that design transmission lines based solely on empirical dimensions or considering only a single coupling relationship, as well as the problems of insufficient engineering relevance and weak practical significance in the parameter design process. It ensures that multi-stage DC high-voltage power transmission lines achieve lower energy storage risks, better field strength distribution, and higher system reliability while meeting insulation safety requirements.

[0052] This embodiment converts the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and solves for the unit-length capacitance matrix based on the analytical electromagnetic field model. The total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface are calculated based on the unit-length capacitance matrix. An objective function for the transmission line design is constructed based on the total energy stored in the distributed capacitance and the maximum electric field strength on the conductor surface. The variables to be optimized in the parameterized geometric model are iteratively solved using the objective function and an intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints. The transmission line is then optimized based on the optimal structural parameters and the corresponding unit-length distributed parameters. Through this method, for the coupling relationship between internal multiple conductors, shielding layers, and ground reference boundaries in a multi-stage DC high-voltage power supply system, an analytical electromagnetic field model is introduced to solve for the unit-length capacitance matrix. The total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface are further calculated. An intelligent optimization algorithm is used to iteratively solve for the optimal structural parameters, and the design is performed in conjunction with the unit-length distributed parameters. This enables optimized transmission line design that addresses both insulation reliability and transient safety.

[0053] In one specific embodiment, this application provides steps for calculating the total stored energy of the transmission line's distributed capacitance and the maximum electric field strength on the conductor surface, respectively. Please refer to... Figure 4 , Figure 4 This is the second flowchart illustrating the DC high-voltage power supply transmission line optimization design method based on electric field image theory provided in this application embodiment. Step S20 includes steps S201 to S204: Step S201: Obtain the transmission line length and the voltage vector of the internal conductor relative to the cylindrical shielding layer, respectively.

[0054] Step S202: Calculate the total energy storage of the distributed capacitance of the transmission line based on the transmission line length, the voltage vector, and the unit length capacitance matrix.

[0055] It is understandable that the total energy stored in the distributed capacitance of a transmission line can reflect the electrostatic energy stored in the transmission line under high voltage steady-state conditions, and can serve as an important indicator for transient safety design. After obtaining the transmission line length and the voltage vector of the internal conductor relative to the cylindrical shield, the total energy stored in the distributed capacitance of the transmission line can be calculated by combining the capacitance matrix per unit length. Specifically: .

[0056] in, W This represents the total energy stored in the distributed capacitance of the transmission line. L Indicates the length of the transmission line. V This represents the voltage vector of the internal conductor relative to the cylindrical shielding layer. C This represents a unit-length capacitance matrix.

[0057] Step S203: Determine the normal electric field distribution at different angular positions on the surface of each internal conductor based on the voltage vector and the unit length capacitance matrix.

[0058] Further, step S203 includes: calculating the linear charge density per unit length of each conductor based on the voltage vector and the capacitance matrix per unit length; calculating the center coordinates based on the center radius and center angle of the inner conductor; calculating the surface point coordinates corresponding to the surface parameter angle based on the center coordinates and the radius of the inner conductor, and calculating the electric field vector at the surface point coordinates; determining the outward normal unit vector based on the surface parameter angle; and determining the normal electric field distribution at different angular positions on the surface of each inner conductor based on the electric field vector, the outward normal unit vector, and the linear charge density per unit length of each conductor.

[0059] Understandably, after obtaining the voltage vector of the inner conductor relative to the cylindrical shielding layer, the linear charge density per unit length of each conductor can be calculated by combining it with the unit length capacitance matrix, specifically: .

[0060] in, This represents the linear charge density per unit length of each conductor. V This represents the voltage vector of the internal conductor relative to the cylindrical shielding layer. C This represents a unit-length capacitance matrix.

[0061] It should also be emphasized that, for the inner conductor, the coordinates of its center are assumed to be ( x i , y i At this point, the coordinates of the center can be calculated based on the central polar radius and the central polar angle, specifically: .

[0062] in, Indicates the firsti The central polarity of the conductor inside the root, Indicates the first i The central polar angle of the conductor inside the root.

[0063] It should be understood that after determining the coordinates of the center of the internal conductor, the coordinates of the surface points corresponding to its surface parameter angles can be further calculated. Specifically: .

[0064] in,( x i , y i () represents the coordinates of the center of the inner conductor. Indicates the surface parameter angle. a i Indicates the first i The radius of the conductor inside the root.

[0065] It should be noted that after calculating the electric field vector at the surface point coordinates, it is also necessary to determine the outward normal unit vector based on the surface parameter angle. Specifically: .

[0066] in, This represents the surface parameter angle.

[0067] It is understandable that the electric field vector at the coordinates of the surface point of the internal conductor can be obtained by superimposing the conductor's own term, the real charge term of other conductors, and the image charge term of the shielding layer. At this time, the normal electric field distribution at different angular positions on the surface of each internal conductor can be determined based on the electric field vector, the external normal unit vector, and the linear charge density per unit length of each conductor.

[0068] Step S204: Sort the normal electric field distribution at different angular positions on the surface of each internal conductor according to a preset sorting rule, and take the maximum value in the sorting result as the maximum electric field intensity on the conductor surface.

[0069] Understandably, after obtaining the normal electric field distribution at different angular positions on the surface of each internal conductor, it can be sorted according to a preset sorting rule, and the maximum value in the sorting result can be taken as the maximum electric field intensity on the conductor surface, specifically: .

[0070] in, Indicates the maximum electric field strength on the conductor surface. This represents the normal electric field distribution at different angular positions on the surface of each internal conductor.

[0071] This embodiment obtains the transmission line length and the voltage vector of the internal conductors relative to the cylindrical shielding layer. It calculates the total energy storage of the distributed capacitance of the transmission line based on the transmission line length, the voltage vector, and the unit-length capacitance matrix. It determines the normal electric field distribution at different angular positions on the surface of each internal conductor based on the voltage vector and the unit-length capacitance matrix. The normal electric field distributions at different angular positions on the surface of each internal conductor are sorted according to a preset sorting rule, and the maximum value in the sorting result is taken as the maximum electric field strength on the conductor surface. Through this method, after obtaining the voltage vector of the internal conductors relative to the cylindrical shielding layer, the total energy storage of the distributed capacitance of the transmission line is calculated by combining the unit-length capacitance matrix and the transmission line length. After determining the normal electric field distribution at different angular positions on the surface of each internal conductor, the maximum electric field strength on the conductor surface is determined by sorting. This effectively improves the accuracy of calculating the total energy storage of the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface, thereby identifying local electric field hotspots and weak insulation locations, ensuring that the optimization results simultaneously meet the overall energy storage and local field strength safety requirements.

[0072] The following describes the DC high-voltage power supply transmission line optimization design device based on electric field image theory provided in this application. The DC high-voltage power supply transmission line optimization design device described below corresponds to the DC high-voltage power supply transmission line optimization design method based on electric field image theory described above. Please refer to... Figure 5 , Figure 5 This is a schematic diagram of the module structure of the DC high-voltage power supply transmission line optimization design device based on electric field image theory provided in this application embodiment, including: The solver module T10 is used to convert the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and to solve for the unit-length capacitance matrix based on the analytical electromagnetic field model.

[0073] The calculation module T20 is used to calculate the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface based on the unit length capacitance matrix.

[0074] Module T30 is used to construct the objective function for the transmission line design based on the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface.

[0075] The optimization design module T40 is used to iteratively solve the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints, and to perform transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters.

[0076] This embodiment converts the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and solves for the unit-length capacitance matrix based on the analytical electromagnetic field model. The total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface are calculated based on the unit-length capacitance matrix. An objective function for the transmission line design is constructed based on the total energy stored in the distributed capacitance and the maximum electric field strength on the conductor surface. The variables to be optimized in the parameterized geometric model are iteratively solved using the objective function and an intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints. The transmission line is then optimized based on the optimal structural parameters and the corresponding unit-length distributed parameters. Through this method, for the coupling relationship between internal multiple conductors, shielding layers, and ground reference boundaries in a multi-stage DC high-voltage power supply system, an analytical electromagnetic field model is introduced to solve for the unit-length capacitance matrix. The total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface are further calculated. An intelligent optimization algorithm is used to iteratively solve for the optimal structural parameters, and the design is performed in conjunction with the unit-length distributed parameters. This enables optimized transmission line design that addresses both insulation reliability and transient safety.

[0077] It is understood that the detailed functional implementation of each of the above modules can be found in the description of the aforementioned method embodiments, and will not be repeated here.

[0078] It should be understood that the above-described device is used to execute the methods in the above embodiments. The implementation principle and technical effect of the corresponding program modules in the device are similar to those described in the above methods. The working process of the device can be referred to the corresponding process in the above methods, and will not be repeated here.

[0079] Based on the methods in the above embodiments, this application provides an electronic device, please refer to... Figure 6 , Figure 6 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application.

[0080] It should be noted that the system may include: a processor 10, a communications interface 20, a memory 30, and a communication bus 40. The processor 10, communications interface 20, and memory 30 communicate with each other via the communication bus 40. The processor 10 can invoke logical instructions stored in the memory 30 to execute the methods described in the above embodiments.

[0081] Furthermore, the logical instructions in the aforementioned memory 30 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0082] Based on the methods in the above embodiments, this application provides a computer-readable storage medium storing a computer program that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0083] Based on the methods in the above embodiments, this application provides a computer program product that, when run on a processor, causes the processor to execute the methods in the above embodiments.

[0084] It is understood that the processor in the embodiments of this application can be a central processing unit, or other general-purpose processors, digital signal processors, application-specific integrated circuits, field-programmable gate arrays, or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. A general-purpose processor can be a microprocessor or any conventional processor.

[0085] The method steps in this application embodiment can be implemented in hardware or by a processor executing software instructions. The software instructions can consist of corresponding software modules, which can be stored in random access memory, flash memory, read-only memory, programmable read-only memory, erasable programmable read-only memory, electrically erasable programmable read-only memory, registers, hard disks, portable hard disks, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor, enabling the processor to read information from and write information to the storage medium. Of course, the storage medium can also be a component of the processor.

[0086] It is understood that the various numerical designations used in the embodiments of this application are merely for descriptive convenience and are not intended to limit the scope of the embodiments of this application. Those skilled in the art will readily understand that the above descriptions are merely preferred embodiments of this application and are not intended to limit this application. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for optimizing the design of DC high-voltage power supply transmission lines based on electric field image theory, characterized in that, include: The parameterized geometric model of the transmission line is converted into an analytical electromagnetic field model, and the unit-length capacitance matrix is ​​solved based on the analytical electromagnetic field model. Calculate the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface based on the unit length capacitance matrix. The objective function for the transmission line design is constructed based on the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface. The parameters to be optimized in the parameterized geometric model are iteratively solved according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints. The transmission line is then optimized based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters.

2. The DC high-voltage power supply transmission line optimization design method as described in claim 1, characterized in that, The step of converting the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and solving for the unit-length capacitance matrix based on the analytical electromagnetic field model, includes: Obtain information about the internal conductors of the transmission line to be designed and the radius of the cylindrical shielding layer to be arranged; Conductor spacing constraints are constructed based on the internal conductor information and minimum spacing margin, and net spacing constraints are constructed based on the internal conductor information, the radius, and the minimum net spacing between the internal conductor and the cylindrical shielding layer. A parameterized geometric model of the transmission line is constructed based on the conductor spacing constraint and the net spacing constraint, and the parameterized geometric model of the transmission line is converted into an analytical electromagnetic field model of the transmission line cross section. The self-potential coefficient and mutual potential coefficient are determined based on the electromagnetic field analytical model and the material parameter model. Construct a potential coefficient matrix based on the self-potential coefficient and the mutual potential coefficient, and solve for the unit length capacitance matrix based on the potential coefficient.

3. The DC high-voltage power supply transmission line optimization design method as described in claim 1, characterized in that, The steps of calculating the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface based on the unit length capacitance matrix include: Obtain the transmission line length and the voltage vector of the internal conductor relative to the cylindrical shielding layer, respectively. The total energy stored in the distributed capacitance of the transmission line is calculated based on the transmission line length, the voltage vector, and the unit length capacitance matrix. The normal electric field distribution at different angular positions on the surface of each internal conductor is determined based on the voltage vector and the unit length capacitance matrix. The normal electric field distributions at different angular positions on the surface of each internal conductor are sorted according to a preset sorting rule, and the maximum value in the sorting result is taken as the maximum electric field intensity on the conductor surface.

4. The DC high-voltage power supply transmission line optimization design method as described in claim 3, characterized in that, The step of determining the normal electric field distribution at different angular positions on the surface of each internal conductor based on the voltage vector and the unit-length capacitance matrix includes: Calculate the linear charge density per unit length of each conductor based on the voltage vector and the unit length capacitance matrix; Calculate the center coordinates based on the central polar diameter and central polar angle of the internal conductor; Calculate the coordinates of the surface point corresponding to the surface parameter angle based on the coordinates of the center of the circle and the radius of the inner conductor, and calculate the electric field vector at the coordinates of the surface point. The outward normal unit vector is determined based on the surface parameter angle; The normal electric field distribution at different angular positions on the surface of each internal conductor is determined based on the electric field vector, the outward normal unit vector, and the linear charge density per unit length of each conductor.

5. The DC high-voltage power supply transmission line optimization design method as described in any one of claims 1 to 4, characterized in that, The step of iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints, and then performing transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters, includes: The target constraint conditions are determined based on the conductor spacing constraint, net spacing constraint, and maximum electric field strength constraint. The optimal structural parameters that satisfy the objective constraints are obtained by iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm. Determine the unit length distribution parameters corresponding to the optimal structural parameters, and perform transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters.

6. The DC high-voltage power supply transmission line optimization design method as described in claim 5, characterized in that, The step of iteratively solving the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints includes: The variables to be optimized in the parametric geometric model are determined based on the internal conductor information, the radius of the arranged cylindrical shielding layer, and the central polar coordinates. Construct a multi-objective optimization model based on the objective function and / or a preset set of optional objectives; Based on the multi-objective optimization model, the variables to be optimized are iteratively solved using the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints.

7. A device for optimizing the design of DC high-voltage power transmission lines based on electric field image theory, characterized in that, include: The solver module is used to convert the parameterized geometric model of the transmission line into an analytical electromagnetic field model, and to solve for the unit-length capacitance matrix based on the analytical electromagnetic field model. The calculation module is used to calculate the total energy stored in the distributed capacitance of the transmission line and the maximum electric field intensity on the conductor surface based on the unit length capacitance matrix. The construction module is used to construct the objective function for the transmission line design based on the total energy stored in the distributed capacitance of the transmission line and the maximum electric field strength on the conductor surface; The optimization design module is used to iteratively solve the variables to be optimized in the parameterized geometric model according to the objective function and the objective intelligent optimization algorithm to obtain the optimal structural parameters that satisfy the objective constraints, and to perform transmission line optimization design based on the optimal structural parameters and the unit length distribution parameters corresponding to the optimal structural parameters.

8. An electronic device, characterized in that, include: At least one memory for storing computer programs; At least one processor is configured to execute a program stored in the memory, wherein when the program stored in the memory is executed, the processor is configured to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is run on the processor, it causes the processor to perform the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, When the computer program product is run on a processor, the processor causes the processor to perform the method as described in any one of claims 1-6.

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