Design method and system of basin-type insulator particle trapper and medium

Abstract

The invention discloses a design method and system of a basin-type insulator particle catcher and a medium, relates to the technical field of high-voltage equipment manufacturing, and aims to improve the insulation reliability of a direct-current GIL power transmission system and guarantee safe and stable operation of a power transmission line in a special environment. Metal particles generated in the production, transportation, assembly and operation processes of the GIL may damage the insulation performance of equipment and cause discharge accidents. Through collaborative optimization of geometric structures of the basin-type insulator and the particle catcher, electric field distribution is changed, the influence of metal particles on the insulation performance is reduced, the probability of partial discharge and surface flashover is reduced, and the safety and reliability of equipment operation are guaranteed.

Description

Technical Field

[0001] This invention relates to the field of high-voltage equipment manufacturing technology, and in particular to a design method, system and medium for a basin-type insulator particle trap. Background Technology

[0002] Gas-insulated transmission lines (GILs) are widely used in complex power transmission scenarios due to their large power transmission capacity, strong environmental adaptability, and high stability. During the production, transportation, assembly, and operation of GILs, metal particles are inevitably generated due to friction and vibration. These metal particles move freely within the GIL cavity or adhere to the insulator surface, potentially causing discharge accidents, damaging the insulation performance of the equipment, and jeopardizing the stable and safe operation of the power system. In a DC electric field, charged metal particles, once activated, can penetrate the high-voltage conductor and move back and forth between the high-voltage conductor and the grounded casing. Some particles are attracted to the insulator surface, shortening the creepage distance and easily causing network faults.

[0003] Existing methods for suppressing metal particles mainly include particle traps, coating the surface of insulators / high-voltage conductors, and pre-embedded electrodes. However, these methods still have some side effects or limitations. For example, electric field distortion occurs near particle traps, and particles may still escape after being trapped; when coating the surface of insulators / high-voltage conductors, the coating layer may be damaged or peel off, without affecting the final charge of the metal particles; pre-embedded electrodes can repel dangerous metal particles near insulators, but cannot effectively suppress particle movement. Summary of the Invention

[0004] To overcome the aforementioned shortcomings of the prior art, this invention provides a design method, system, and medium for a basin-type insulator particle trap. The aim is to collaboratively optimize the geometry of the basin-type insulator and the particle trap using artificial intelligence algorithms. Specifically, with the goal of obtaining an electric field distribution that is conducive to driving away and collecting metal particles, and under the premise of satisfying constraints such as the electric field strength and mechanical stress of the basin-type insulator, the shape of the basin-type insulator and the particle trap with particle driving effect is obtained by using a genetic algorithm.

[0005] The technical solution adopted by this invention to solve its technical problem is: a design method for a DC GIL basin-type insulator particle trap, comprising the following steps:

[0006] Step 1: Establish a simulation design model for a DC GIL basin insulator and set relevant parameters;

[0007] Step 2: Calculate the electric field distribution of the simulation design model and analyze its metal particle repelling performance;

[0008] Step 3: Optimize the geometric structure of the basin insulator based on the simulation design model, analyze the influence of different curvatures of the basin insulator on the electric field distribution and the driving effect of metal particles, and obtain the optimal structure of the basin insulator with the best driving effect.

[0009] Step 4: Based on the optimal structure of the basin-type insulator, optimize the geometry of the grounding shell and install a sunken particle trap on the grounding shell.

[0010] By optimizing the geometry of the basin-type insulator, the electric field distribution is actively altered, thereby influencing the force and trajectory of metal particles at the source, making them easier to guide to the target area and improving the initiative and efficiency of control. Simulation design models and electric field distribution calculations provide electric field analysis basis for structural optimization and particle trap placement, enabling more accurate evaluation of the metal particle repelling effect. This allows for the selection of superior structural combinations, improving the reliability and relevance of the design, and ensuring its scientific rigor and accuracy. Optimizing the grounding shell and trap placement based on the optimal basin-type insulator structure allows the design parameters of the particle trap to be adapted to the optimized electric field environment of the basin-type insulator, creating functional complementarity and enhancement, and improving the synergistic optimization effect.

[0011] As a further improvement of the present invention: in step one, the simulation design model includes a high-voltage conductor, a basin insulator, and a grounding shell.

[0012] By simultaneously incorporating the high-voltage conductor, basin insulator, and grounding shell into the simulation design model, the inter-electrode structure inside the GIL can be realistically reproduced. This ensures that the electric field calculation accurately reflects the coupling relationship between the high-voltage conductor, basin insulator, and grounding shell, which is the basis for analyzing the electric field on the insulator surface and the forces acting on particles. Secondly, since the simulation design model includes both the basin insulator and the grounding shell, the optimization of the basin insulator geometry in step three and the design of the grounding shell structure and particle trap in step four can be iterated and evaluated within the same simulation design model. This ensures that the electric field disturbances caused by changes in the insulator shape can be reflected in the electric field distribution near the shell in real time.

[0013] As a further improvement of the present invention: In step one, both the high-voltage conductor and the grounding shell are made of aluminum material, the high-voltage conductor and the grounding shell are arranged coaxially, the high-voltage conductor is connected to ±800kV DC voltage, the radius of the high-voltage conductor is 150mm, the inner diameter of the grounding shell is 650mm, and the thickness of the grounding shell is 10mm.

[0014] As a further improvement of the present invention: the basin-type insulator is made of epoxy resin-alumina composite material with a relative permittivity of 5 and a conductivity of 3×10⁻⁶. -15 S / m.

[0015] As a further improvement of the present invention: In step three, the metal particles are aluminum particles with a diameter of 0.2 mm. After colliding with the high-voltage conductor or grounded shell, the metal particles become charged. The metal particles are subjected to gravity, electric field force, electric field gradient force and gas resistance in the GIL cavity.

[0016] As a further improvement of the present invention: in step three, the optimization method for the geometric structure of the basin insulator is a genetic algorithm.

[0017] As a further improvement of the present invention: the parameters of the genetic algorithm are set as follows: population size N=10, gene mutation probability mut=0.2, gene crossover probability acr=0.2, and number of iterations iter=5; during the optimization process, the basin insulator satisfies the following constraints:

[0018] Surface charge density at rated voltage ≤25μC / m²;

[0019] Surface electric field strength at 1346kV DC voltage ≤6kV / mm;

[0020] Under lightning impulse voltage, the surface electric field strength is ≤12kV / mm, and the conductor surface electric field strength is ≤24kV / mm;

[0021] Mechanical stress ≤35MPa under 2.7MPa water pressure.

[0022] As a further improvement of the present invention, step three further includes: adding a metal particle motion model to the simulation design model, setting the release position and number of metal particles, calculating the motion trajectory of the metal particles within 1 second, and evaluating the optimization effect by calculating the metal particle repellency rate. By establishing a metal particle motion model and calculating its motion trajectory within 1 second, the actual influence process of the optimized basin insulator geometry on the metal particles can be intuitively and dynamically simulated.

[0023] As a further improvement of the present invention, the setting of the metal particle release location and quantity specifically includes: releasing one metal particle every 25 mm at a distance of 40 mm to 200 mm from the basin insulator near the concave-convex grounding shell and the high-voltage conductor, with all particles released simultaneously. By releasing one metal particle every 25 mm at a distance of 40 mm to 200 mm from the basin insulator near the concave-convex grounding shell and the high-voltage conductor, these two locations are precisely the core areas where metal particles are easily attracted, activated, and endanger the basin insulator by the electric field. By placing these points, the ability of the optimized basin insulator geometry to suppress the most dangerous metal particles can be directly tested. By adopting an equally spaced, dense release strategy, a spatial detection array from near to far is formed, which can not only evaluate the electric field control effect near the surface of the basin insulator but also detect the dynamic process of metal particles being attracted or driven away at greater distances. This comprehensively reflects the spatial influence range and gradient effect of the optimized basin insulator geometry on the movement of metal particles, avoiding the one-sidedness of the evaluation caused by a single release point.

[0024] As a further improvement of the present invention: in step four, the axial length of the sinking particulate trap is 660mm, the inclination angle at both ends is 60°, the sinking particulate trap is made of aluminum material, and the potential is 0.

[0025] This invention also provides a design system for a DC GIL basin-type insulator particulate trap, comprising:

[0026] The simulation design model building module is used to build a simulation design model of a DC GIL basin insulator and set relevant parameters;

[0027] The analysis module is used to calculate the electric field distribution of the simulation design model and analyze its metal particle repelling performance.

[0028] The acquisition module is used to optimize the geometric structure of the basin insulator based on the simulation design model, analyze the influence of different curvatures of the basin insulator on the electric field distribution and the driving effect of metal particles, and obtain the optimal structure of the basin insulator with the best driving effect.

[0029] The optimization module optimizes the geometry of the grounding shell based on the optimal structure of the basin-type insulator and installs a sunken particle trap on the grounding shell.

[0030] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the design method of a DC GIL basin insulator particle trap as described above.

[0031] Compared with the prior art, the beneficial effects of the present invention are:

[0032] This invention utilizes artificial intelligence algorithms to collaboratively optimize the geometry of the basin-type insulator and the particle trap, altering the electric field distribution near the insulator. This allows metal particles to move away from the insulator more quickly during their initial movement, preventing them from adhering to the insulator surface. This effectively reduces the impact of metal particles on the insulation performance of the DC basin-type insulator, demonstrating a significant metal particle suppression effect. This invention effectively reduces the impact of metal particles on the insulation performance of DC GIL basin-type insulators, lowers the probability of partial discharge and surface flashover, and ensures the safety and reliability of equipment operation. Attached Figure Description

[0033] Figure 1 This is a diagram illustrating the effect of driving away metal particles from the initial ±800kV GIL basin insulator.

[0034] Figure 2 This is a flowchart of a genetic algorithm;

[0035] Figure 3 The image shows the effect of the optimized ±800kV GIL basin insulator in driving away metal particles.

[0036] Figure 4 The diagram shows the effect of repelling metal particles in the ±800kV GIL basin insulator after co-optimization.

[0037] Figure 5 The graphs show the efficiency of metal particle removal before and after optimization.

[0038] Figure 6 A flowchart illustrating a design method for a DC GIL basin-type insulator particle trap according to a first embodiment;

[0039] Figure 7 This is a flowchart of a design system for a DC GIL basin-type insulator particle trap, as shown in the second embodiment. Detailed Implementation

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the present invention will be briefly introduced below in conjunction with the accompanying drawings and descriptions of the embodiments or the prior art. Obviously, the following description of the structure of the accompanying drawings is only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. It should be noted that the description of these embodiments is for the purpose of helping to understand the present invention, but does not constitute a limitation of the present invention.

[0041] It should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0042] It should be understood that although the terms first, second, etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are only used to distinguish one unit from another. For example, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit, without departing from the scope of the exemplary embodiments of the invention.

[0043] It should be understood that the term "and / or" that may appear in this document is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" that may appear in this document describes another relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " that may appear in this document generally indicates that the related objects before and after it are in an "or" relationship.

[0044] It should be understood that specific details are provided in the following description to facilitate a complete understanding of the exemplary embodiments. However, those skilled in the art will understand that the exemplary embodiments can be implemented without these specific details. For example, the system may be shown in block diagrams to avoid obscuring the example with unnecessary details. In other instances, well-known processes, structures, and techniques may be shown without unnecessary details to avoid obscuring the exemplary embodiments.

[0045] Please see Figure 6 The first embodiment of the present invention provides a design method for a DC GIL basin-type insulator particle trap, comprising the following steps:

[0046] Step 1: Establish a simulation design model for a DC GIL basin insulator and set relevant parameters;

[0047] Step 2: Calculate the electric field distribution of the simulation design model and analyze its metal particle repelling performance;

[0048] Step 3: Optimize the geometric structure of the basin insulator based on the simulation design model, analyze the influence of different curvatures of the basin insulator on the electric field distribution and the driving effect of metal particles, and obtain the optimal structure of the basin insulator with the best driving effect.

[0049] Step 4: Based on the optimal structure of the basin-type insulator, optimize the geometry of the grounding shell and install a sunken particle trap on the grounding shell.

[0050] By optimizing the geometry of the basin insulator (especially its curvature), the electric field distribution can be actively altered, thereby influencing the force and trajectory of metal particles at the source, making them easier to guide to the target area and improving the initiative and efficiency of control.

[0051] By using simulation design models and electric field distribution calculations, electric field analysis is provided as a basis for structural optimization (such as curvature selection) and particle trap placement. This allows for a more accurate evaluation of the metal particle repelling effect, thereby selecting structural combinations with better performance, improving the reliability and relevance of the design, and ensuring the scientific nature and accuracy of the design.

[0052] By optimizing the grounding shell and setting up the trap based on the optimal structure of the basin insulator, the design parameters of the particle trap (such as position and shape) can be adapted to the optimized electric field environment of the basin insulator, so that the two complement and enhance each other in function, and improve the synergistic optimization effect.

[0053] In some implementations, in step one, the simulation design model includes a high-voltage conductor, a basin insulator, and a grounding shell.

[0054] By simultaneously incorporating the high-voltage conductor, basin insulator, and grounding shell into the simulation design model, the inter-electrode structure inside the GIL can be realistically reproduced. This ensures that the electric field calculation accurately reflects the coupling relationship between the high-voltage conductor, basin insulator, and grounding shell, which is the basis for analyzing the electric field on the insulator surface and the forces acting on particles. Secondly, since the simulation design model includes both the basin insulator and the grounding shell, the optimization of the basin insulator geometry in step three and the design of the grounding shell structure and particle trap in step four can be iterated and evaluated within the same simulation design model. This ensures that the electric field disturbances caused by changes in the insulator shape can be reflected in the electric field distribution near the shell in real time.

[0055] In some embodiments, in step one, both the high-voltage conductor and the grounding shell are made of aluminum, the high-voltage conductor and the grounding shell are arranged coaxially, the high-voltage conductor is connected to ±800kV DC voltage, the radius of the high-voltage conductor is 150mm, the inner diameter of the grounding shell is 650mm, and the thickness of the grounding shell is 10mm.

[0056] By using aluminum for both the high-voltage conductor and the grounding shell, the authenticity of material properties such as conductivity and density in the simulation design model is ensured. At the same time, the two are arranged coaxially, establishing the most typical and regularly distributed GIL basic configuration, which enables subsequent electric field analysis and optimization to be carried out under standard and comparable structural conditions.

[0057] Secondly, by directly providing a ±800kV DC voltage, the ultra-high voltage DC application scenario targeted by the simulation design model is clearly defined. Specific dimensions such as a high-voltage conductor radius of 150mm, a grounding shell inner diameter of 650mm, and a thickness of 10mm are provided. This not only fully defines the geometric boundaries of the simulation design model, but also ensures that the electric field distribution calculation and subsequent structural optimization (such as curvature and trap size) closely match the scale and constraints of the actual product, significantly enhancing the practical value and guiding significance of this design method.

[0058] In some embodiments, in step one, the GIL is filled with SF6 gas, which has a relative permittivity of 1 and a conductivity of 10⁻⁶. -18 S / m.

[0059] By filling the GIL with SF6 gas, which has excellent insulation properties, the use of SF6 gas and its extremely low conductivity ensures the authenticity of the conductivity characteristics of the insulating medium in the simulation design model.

[0060] In some embodiments, in step one, the basin-type insulator is made of epoxy resin-alumina composite material with a relative permittivity of 5 and a conductivity of 3×10⁻⁶. -15 S / m.

[0061] The use of epoxy resin-alumina composite material in basin-type insulators is demonstrated, and its key electromagnetic parameters (relative permittivity 5, conductivity 3×10⁻⁶) are given. -15 The S / m ratio facilitates subsequent calculations of electric field distribution, simulation of charge accumulation, and evaluation of insulation performance, significantly improving the accuracy and reliability of the simulation design model.

[0062] Secondly, the dielectric properties of the basin insulator directly affect the electric field distribution on its surface and surroundings, thus determining the electric and gradient forces experienced by the metal particles. Determining its relative permittivity and extremely low conductivity is a prerequisite for accurately simulating the surface charge behavior of the basin insulator, calculating the spatial electric field force, and further analyzing the particle trajectory. This ensures that the analysis of particle repellency in step two and the optimization of the basin insulator's geometry in step three are based on quantitative analysis conforming to actual physical laws, guaranteeing the scientific validity and effectiveness of the design method.

[0063] In some embodiments, in step three, the metal particles are aluminum particles with a diameter of 0.2 mm. The metal particles become charged after colliding with the high-voltage conductor or grounded shell. The metal particles are subjected to gravity, electric field force, electric field gradient force and gas resistance in the GIL cavity.

[0064] In some implementations, the optimization method for the geometry of the basin-type insulator in step three is a genetic algorithm.

[0065] In some implementations, the parameters of the genetic algorithm are set as follows: population size N=10, gene mutation probability mut=0.2, gene crossover probability acr=0.2, and number of iterations iter=5; during the optimization process, the basin insulator satisfies the following constraints:

[0066] Surface charge density at rated voltage ≤25μC / m²;

[0067] Surface electric field strength at 1346kV DC voltage ≤6kV / mm;

[0068] Under lightning impulse voltage, the surface electric field strength is ≤12kV / mm, and the conductor surface electric field strength is ≤24kV / mm;

[0069] Mechanical stress ≤35MPa under 2.7MPa water pressure.

[0070] In some implementations, step three further includes: adding a metal particle motion model to the simulation design model, setting the release position and number of metal particles, calculating the motion trajectory of the metal particles within 1 second, and evaluating the optimization effect by calculating the metal particle drive-off rate.

[0071] By establishing a motion model of metal particles and calculating their trajectory within 1 second, the actual impact of the optimized basin insulator geometry on the metal particles can be intuitively and dynamically simulated.

[0072] In some embodiments, the setting of the release location and quantity of metal particles specifically includes: releasing one metal particle every 25 mm from a distance of 40 mm to 200 mm from the basin insulator near the concave-convex grounding shell of the basin insulator and the high-voltage conductor, with all particles released simultaneously.

[0073] By releasing one metal particle every 25 mm at distances ranging from 40 mm to 200 mm from the concave-convex grounding shell of the basin insulator and near the high-voltage conductor, these two locations are the core areas where metal particles are easily attracted, agitated, and endanger the basin insulator under the influence of the electric field. By placing these points, the ability of the optimized basin insulator geometry to suppress the most dangerous metal particles can be directly tested. By employing a densely spaced, equally spaced release strategy, a spatial detection array is formed from near to far. This not only assesses the electric field control effect near the surface of the basin insulator but also detects the dynamic process of metal particles being attracted or driven away at greater distances. This comprehensively reflects the spatial influence range and gradient effect of the optimized basin insulator geometry on the movement of metal particles, avoiding the biased evaluation caused by a single release point.

[0074] In some embodiments, in step four, the axial length of the sinking particulate trap is 660 mm, the inclination angle at both ends is 60°, the sinking particulate trap is made of aluminum, and the potential is 0.

[0075] Please see Figure 7 The second embodiment of the present invention also provides a design system for a DC GIL basin-type insulator particle trap, comprising:

[0076] The simulation design model building module is used to build a simulation design model of a DC GIL basin insulator and set relevant parameters;

[0077] The analysis module is used to calculate the electric field distribution of the simulation design model and analyze its metal particle repelling performance.

[0078] The acquisition module is used to optimize the geometric structure of the basin insulator based on the simulation design model, analyze the influence of different curvatures of the basin insulator on the electric field distribution and the driving effect of metal particles, and obtain the optimal structure of the basin insulator with the best driving effect.

[0079] The optimization module optimizes the geometry of the grounding shell based on the optimal structure of the basin-type insulator and installs a sunken particle trap on the grounding shell.

[0080] A third embodiment of the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the design method of a DC GIL basin insulator particle trap.

[0081] The fourth embodiment of the present invention also provides a design method for a DC GIL basin-type insulator particulate trap, comprising the following steps:

[0082] Step 1: Build a simulation design model of ±800 kV DC GIL basin insulator, and establish a preliminary schematic structure of GIL, high voltage conductor, basin insulator, and grounding shell. The geometric structure of the basin insulator is determined by the values ​​of the corresponding parameters.

[0083] Step 2: Calculate the electric field distribution within the GIL under a DC voltage of 816kV based on the simulation design model obtained in Step 1, and analyze its metal particle repelling performance.

[0084] Step 3: The charged metal particles in the GIL cavity are subjected to gravity, electric force, electric field gradient force, and gas drag, as expressed in the following expressions:

[0085]

[0086]

[0087]

[0088]

[0089] In the formula, F q Let F be the electric force, G be gravity, and F be the electric force. grad For the electric field gradient force, F v air resistance; g is the acceleration due to gravity, m / s² 2 q represents the electric charge of the metal particle, in C; ρ g Δv is the density of SF6 insulating gas, in kg / m³; Re is the Reynolds number; Δv is the relative velocity between the metal particles and the insulating gas medium, in m / s.

[0090] When a metal particle collides with a high-voltage conductor or grounded casing, its charge changes, and the charge can be calculated using the following formulas:

[0091]

[0092]

[0093] In the formula, q hv Let q be the charge carried by the metal particle during the collision with the high-voltage conductor. gnd Let ε0 and εgrounded be the charges carried by the metal particles during the collision with the grounded casing. r The relative permittivity of vacuum and the material are respectively, r is the radius of the metal particle, and E is the relative permittivity of the material. n Let be the normal electric field strength at the collision location of the metal particles.

[0094] Based on the above force analysis and charge change, a particle tracking module was added to the simulation model. A 0.1mm radius metal particle was released every 25mm at distances ranging from 40mm to 200mm from the insulator, near the concave-convex grounding shell of the basin-type insulator and near the high-voltage conductor. The movement of the metal particles is as follows: Figure 1 As shown.

[0095] Step 4: Write the genetic algorithm code, setting the population size N=10, gene mutation probability mut=0.2, gene crossover probability acr=0.2, and iteration count iter=5. The algorithm flow is as follows: Figure 2 As shown. During the optimization process, the insulator needs to meet the following constraint: the surface charge density of the insulator under rated voltage does not exceed 25 μC / m. 2 Under 1346kV DC voltage, the electric field strength on the surface of the insulator shall not exceed 6kV / mm; under lightning impulse voltage, the electric field strength on the surface of the insulator shall not exceed 12kV / mm, and the electric field strength on the surface of the conductor shall not exceed 24kV / mm; under 2.7MPa water pressure, the mechanical stress shall not exceed 35MPa.

[0096] Step 5: Based on the basin-type insulator geometry with the best metal particle repelling effect obtained in Step 4, simulation is performed to calculate the electric field distribution near the insulator and the metal particle repelling effect. The results are as follows: Figure 3 As shown in the figure. Based on the simulation results of metal particle motion, it can be seen that the optimized insulator, due to its basin-shaped characteristics, still has the potential to attract grounding initiation particles on its convex side. Therefore, a metal particle trap is designed at the grounding shell on the convex side of the basin-shaped insulator. The metal particle trap is formed by modifying the structure of the GIL grounding shell, with a length of 660mm and an inclination angle of 60° at both ends. Releasing metal particles into the co-optimized GIL results in the following metal particle repelling effect: Figure 4 As shown in the figure. The repelling effect of this device on metal particles can be represented by the metal particle repelling efficiency. The metal particle repelling efficiency diagrams of the device before and after optimization are shown in the figure. Figure 5 As shown.

[0097] This invention uses artificial intelligence algorithms to collaboratively optimize the geometry of basin insulators and particle traps. Specifically, it aims to obtain an electric field distribution that is conducive to driving away and collecting metal particles. Under the premise of satisfying constraints such as electric field strength and mechanical stress of basin insulators, the shape of basin insulators and particle traps with particle driving effect is obtained by using genetic algorithms.

[0098] The main functions of this invention are:

[0099] This invention can prevent metal particles in the DC GIL cavity from adsorbing onto the surface of the basin insulator after activation, effectively reducing the impact of metal particles on the insulation performance of the DC basin insulator, reducing the probability of partial discharge and surface flashover in the insulation equipment, and ensuring the safety and reliability of equipment operation.

[0100] The functions described herein can be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions can be stored as one or more instructions or codes on or transmitted via a computer-readable medium. Other examples and embodiments are within the scope and spirit of this invention and the appended claims. For example, due to the nature of software, the functions described above can be implemented using software executed by a processor, hardware, firmware, hardwired, or any combination thereof. Furthermore, the functional units can be integrated into a single processing unit, or each unit can exist physically separately, or two or more units can be integrated into a single unit.

[0101] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For instance, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0102] The units described as separate components may or may not be physically separate. Similarly, the components of the control device may or may not be physical units; they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0103] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or 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, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory, random access memory, portable hard drives, magnetic disks, or optical disks.

[0104] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the scope of the claims and specification of the present invention.

Claims

1. A design method for a DC GIL basin-type insulator particle trap, characterized in that: Includes the following steps: Step 1: Establish a simulation design model for a DC GIL basin insulator and set relevant parameters; Step 2: Calculate the electric field distribution of the simulation design model and analyze its metal particle repelling performance; Step 3: Optimize the geometric structure of the basin insulator based on the simulation design model, analyze the influence of different curvatures of the basin insulator on the electric field distribution and the driving effect of metal particles, and obtain the optimal structure of the basin insulator with the best driving effect. Step 4: Based on the optimal structure of the basin-type insulator, optimize the geometry of the grounding shell and install a sunken particle trap on the grounding shell.

2. The design method of a DC GIL basin-type insulator particle trap according to claim 1, characterized in that: In step one, the simulation design model includes a high-voltage conductor, a basin-type insulator, and a grounding shell; both the high-voltage conductor and the grounding shell are made of aluminum and are arranged coaxially.

3. The design method of a DC GIL basin-type insulator particle trap according to claim 2, characterized in that: In step one, the basin-type insulator is made of epoxy resin-alumina composite material.

4. The design method of a DC GIL basin-type insulator particle trap according to claim 1, characterized in that: In step three, the metal particles are aluminum particles.

5. The design method of a DC GIL basin-type insulator particle trap according to claim 1, characterized in that: In step three, the optimization method for the geometry of the basin-type insulator is a genetic algorithm.

6. The design method of a DC GIL basin-type insulator particle trap according to claim 1, characterized in that: Step three also includes: adding a metal particle motion model to the simulation design model, setting the release position and number of metal particles, calculating the motion trajectory of metal particles within 1 second, and evaluating the optimization effect by calculating the metal particle drive-off rate.

7. The design method of a DC GIL basin-type insulator particle trap according to claim 6, characterized in that: The setting of the release location and quantity of metal particles specifically includes: releasing one metal particle every 25 mm from a distance of 40 mm to 200 mm from the concave-convex grounding shell of the basin insulator and near the high-voltage conductor, with all particles released simultaneously.

8. The design method of a DC GIL basin-type insulator particle trap according to claim 1, characterized in that: In step four, the sinking particle trap is made of aluminum.

9. A design system for a DC GIL basin-type insulator particle trap, characterized in that: include: The simulation design model building module is used to build a simulation design model of a DC GIL basin insulator and set relevant parameters; The analysis module is used to calculate the electric field distribution of the simulation design model and analyze its metal particle repelling performance. The acquisition module is used to optimize the geometric structure of the basin insulator based on the simulation design model, analyze the influence of different curvatures of the basin insulator on the electric field distribution and the driving effect of metal particles, and obtain the optimal structure of the basin insulator with the best driving effect. The optimization module optimizes the geometry of the grounding shell based on the optimal structure of the basin-type insulator and installs a sunken particle trap on the grounding shell.

10. A computer-readable storage medium, characterized in that: It stores a computer program that, when executed by a processor, implements a design method for a DC GIL basin insulator particle trap as described in any one of claims 1-8.

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