DC GIL basin-type insulator electrical performance optimization design method based on particle swarm optimization

Abstract

The invention belongs to the technical field of electrical equipment insulation structure design, and particularly relates to a direct current GIL basin-type insulator electrical performance optimization design method based on a particle swarm optimization algorithm, which comprises the following steps: parameterized reconstruction of an insulator surface profile curve is carried out, and an insulator geometric control coefficient is determined for a quantitative optimization process; establishing an electricity-heat-flow multi-field coupling simulation model of charge accumulation of the basin-type insulator, simulating the distortion influence of the charge accumulation process on a space electric field, and outputting key data such as normal and tangential field intensities and surface charge accumulation amount; carrying out insulator geometric control coefficient optimization analysis by adopting a particle swarm algorithm and supporting and updating corresponding control coefficients; therefore, the structure optimization of the basin-type insulator is realized, and the corresponding geometric control coefficient value is obtained. And meanwhile, through multiple iterations and comparison and assessment of each local optimal solution, a result of realizing the minimum objective function is taken as a global optimal solution. According to the method, the along-surface insulation strength and the surface dust adsorption mechanism of the basin-type insulator are comprehensively considered, geometric control coefficient optimization analysis is carried out through basin-type insulator surface profile curve reconstruction in combination with the particle swarm optimization, and therefore the structural parameters of the novel direct-current basin-type insulator can be obtained; a method and a way are provided for preparing the basin-type insulator with interface charge dissipation performance and improved along-surface insulation strength, and the basin-type insulator has good practicability and economical efficiency.

Description

Technical Field

[0001] The invention belongs to the technical field of insulation structure design of power equipment, and in particular relates to an electrical performance optimization design method for a DC GIL pot-type insulator based on a particle swarm algorithm. Background Art

[0002] The DC transmission pipeline is a composite insulation system composed of gas and solid, including high-voltage conductors, aluminum alloy casings, insulators, and insulating gas. Among them, the basin insulator is conical in shape, which can not only support the conductor, but also play the role of isolating the gas chamber, and is the key to the entire insulation system. Its structural design needs to fully consider the electrical properties of different surface contours of the insulator to avoid insulation failure. By optimizing the geometric structure design of the insulator, the distribution of the interface electric field can be effectively adjusted, especially reducing the intensity of the normal electric field and reducing the accumulation of surface charge.

[0003] Current research has proposed a preliminary control benchmark for the surface field strength of DC insulators, but the relevant theoretical analysis does not consider the influence of temperature gradients, and has not yet considered the interaction between surface charge / electric field and metal particles. In addition, for the complex curved surface profile of the basin insulator surface, the existing DC basin insulator optimization design is limited to the optimization of local insulation structure parameters or key node coordinates, and lacks a quantitative optimization method for DC insulators. Based on the above problems, the present invention proposes a DC GIL basin insulator electrical performance optimization design method based on particle swarm algorithm. Summary of the invention

[0004] The purpose of the present invention is to address the problems existing in the prior art of pot-type insulators in DC GILs and propose a DC GIL pot-type insulator electrical performance optimization design method based on a particle swarm algorithm to improve the overall electrical performance of the pot-type insulator. To achieve the above purpose, the present invention adopts the following technical solutions:

[0005] The electrical performance optimization design method of DC GIL pot insulator based on particle swarm algorithm includes the following steps:

[0006] (1) Based on the simplified model of small-taper pot-type insulator, the parametric reconstruction of the insulator surface contour curve is carried out, the insulator geometric control coefficient is determined in the quantitative optimization process, and the geometric model of the pot-type insulator is constructed.

[0007] (2) An electric-thermal-fluid multi-field coupling simulation model for charge accumulation in basin-type insulators is established to simulate the influence of the charge accumulation process on the spatial electric field distortion. Key data such as normal and tangential field strengths and surface charge accumulation are output to support the comparison and optimization of subsequent simulation results.

[0008] (3) Call the particle swarm algorithm to perform optimization analysis of the insulator geometric control coefficients and support the update of the corresponding control coefficients.

[0009] (4) Optimize the structure of the pot insulator and obtain the corresponding geometric control coefficient. At the same time, through multiple iterations and comparisons of the local optimal solutions, the result of achieving the minimum objective function is taken as the global optimal solution.

[0010] In step (1), taking the convex side of the simplified model of a small-taper pot insulator as an example, 35 feature points that can reflect the profile change behavior are selected on the curve. The selected feature points have an ideal fitting effect. In order to reasonably control the number of variables and the amount of calculation in the subsequent optimization algorithm, the fifth-order Bernstein polynomial is selected as a scheme to describe and reconstruct the surface curve profile of the DC insulator.

[0011]

[0012] Among them, β is the Bernstein coefficient; t is the variable of the equation, and its value range is [0,1].

[0013] In step (1), the central part of the small-taper pot insulator is tightly connected to the high-voltage conductor, and the other end extends to the grounded shell, and the contour curve of the insulator is represented by a curve F(t) composed of the fifth-order Bernstein equation.

[0014]

[0015] Where D is the distance from the outer surface of the center conductor to the inner surface of the ground electrode, which is taken as 160 in this paper; A is the axial height of the insulator profile curve, and the larger its value, the larger the insulator taper; β k is the Bernstein coefficient of the insulator surface profile curve.

[0016] In order to ensure a smooth transition of the electric field intensity at the three junctions, the insulator profile curve f(t) is defined to be perpendicular to the center conductor and the ground electrode, that is, the value of f'(t) is zero when t = 0 and t = 1. It can be obtained that β1 = 1, β2 = 5, β5 = β6 = 0, and the insulator profile curve parameter equation can be further expressed as:

[0017]

[0018] In the electric-thermal-fluid multi-field coupling simulation model of charge accumulation in the basin insulator established in step (2), when the heat generated by the central conductor is equal to the heat dissipated, the temperature gradient between the central conductor and the shell no longer changes, which is the stable temperature field of the GIL pipeline. The relevant heat transfer physical process can be described as

[0019]

[0020] Where T is the temperature in the pipeline space; λ is the thermal conductivity of gas and solid materials; Q s is the conduction heat transfer heat flux; Q c is the convective heat transfer heat flux; N u is the Nusselt constant; T C and T G are the temperatures of the outer wall of the central conductor and the inner wall of the grounded shell respectively; e is the equivalent convection heat transfer coefficient between the outer surface of the shell and the air, approximately 3W / (m 2 ·K); Q r is the radiation heat transfer heat flux; S B is the Stefan-Boltzmann constant; A is the equivalent heat transfer area; ω is the surface thermal emissivity.

[0021] In the electric-thermal-fluid multi-field coupling simulation model of charge accumulation of the basin insulator established in step (2), the charge accumulation process is mainly based on three modes: insulator volume current, gas volume current and gas-solid interface surface current.

[0022] In step (1), six parameters A1, ψ 11 , 12 , A2, ψ 21 and ψ 22 Defined as the geometric control coefficient of the pot insulator, the profile curve f1(t) on the convex side of the insulator and the profile curve f2(t) on the concave side can be specifically described as:

[0023]

[0024] The parameters of the convex side profile curve of the insulator in step (2) must generally meet the following requirements:

[0025]

[0026] The parameters of the insulator concave side profile curve in step (2) must generally meet the following requirements:

[0027]

[0028] Since the insulation distance along the surface is closely related to the shape of the insulator, and the insulator structure also has different effects on the distribution of the tangential electric field along the surface, it is difficult to calculate the required insulation length along the surface of the insulator using analytical formulas. In step (2), since there is no clear data on the allowable value of the surface tangential field strength under DC voltage, when designing the shape and size of the pot-type insulator, it is necessary to refer to the original AC design experience to estimate the required insulation distance along the surface of the insulator to narrow the scope of subsequent optimization calculations. The insulation distance H along the surface of the pot-type insulator can be preliminarily estimated by referring to the following empirical formula:

[0029] H=K3K4·(U / E t )

[0030] Among them: the value range of the electric field non-uniformity coefficient K3 is 1.5~2.0, and the value 1.5 is selected at this time; K4 is the safety factor, the value range is 1.4~1.8, and the value 1.4 is selected; U LI E is the lightning impulse withstand voltage. For ±500kV GIL, the lightning impulse withstand voltage design standard is 1550kV. t is the permissible field strength on the insulator surface, and the value selected is 12kV / mm. From this, we can preliminarily obtain the restrictive conditions for designing the insulation distance along the surface of the DC basin insulator:

[0031] H≥H min

[0032] In step (3), the insulator geometric structure optimization problem is transformed into a mathematical optimization problem for optimizing the insulator surface curve profile. 11 and ψ 12 , the convex side axial height A1 is used to describe the convex side profile curve f1(t) of the insulator; the concave side geometric control coefficient ψ 21 and ψ 22 , the concave side height A2 constructs the concave side contour curve f2(t), and the above six parameters constitute the variables to be optimized.

[0033] In step (4), the maximum value of the normal electric field on both sides of the convex and concave and the average value of the normal electric field are used as decision variables to construct the objective function of the DC basin insulator contour curve optimization:

[0034] δ1=E n1max +E n2max

[0035] δ2=E n1mean +E n2mean

[0036] minχ=ωδ1+(1-ω)δ2

[0037] Where: E n1max and E n2max are the maximum values ​​of the normal electric field intensity on the convex side surface and the normal electric field intensity on the concave side surface of the insulator during the transient process; E n1 mean and E n2 mean are the average values ​​of the normal field strength on the convex side and the concave side of the insulator during the transient process; ω is the weight coefficient, and its value range is [0,1]. The larger the ω is, the primary control target is to reduce the maximum value of the normal field strength; the smaller the ω is, the primary target is to reduce the overall size of the normal field strength. In addition, it is also necessary to consider that the insulator inclination angle should be limited to 60°~90°.

[0038] The present invention comprehensively considers the different electrical performance index requirements of different parts of the concave and convex side surfaces of the pot-type insulator, can provide a method and approach for the structural optimization design of the pot-type insulator with complex geometric curve shapes, and effectively reduces the design cycle and cost of the pot-type insulator, comprehensively improves the electrical performance of the pot-type insulator, and has good practicality and economy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Simplified model for small-taper pot insulator.

[0040] Figure 2 This is the optimization design idea of ​​DC GIL pot-type insulator based on particle swarm algorithm in the present invention.

[0041] Figure 3 The figure is a flow chart of the particle swarm algorithm of the present invention. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention is clearly and completely described below.

[0043] The electrical performance optimization design method of DC GIL pot insulator based on particle swarm algorithm is as follows:

[0044] (1) Based on Figure 1 A simplified model of a small-taper pot-type insulator is proposed. 35 feature points that can reflect the contour change behavior are selected on the curve, and the fifth-order Bernstein polynomial is selected as the scheme to describe and reconstruct the surface curve profile of the DC insulator. The parametric reconstruction of the insulator surface contour curve is carried out, and the insulator geometric control coefficient is determined in the quantitative optimization process to realize the construction of the pot-type insulator geometric model.

[0045] (2) An electric-thermal-fluid multi-field coupling simulation model for surface charge accumulation on DC GIL insulators is established to simulate the influence of the charge accumulation process on the spatial electric field distortion, output key data such as normal and tangential field strengths, surface charge accumulation, and obtain the conditions that the parameters of the insulator concave and convex side profile curves must generally meet, to support the comparison and optimization of subsequent simulation results.

[0046] (3) By transforming the insulator geometric structure optimization problem into a mathematical optimization problem for the insulator surface curve profile optimization, the insulator convex side geometric control coefficient ψ 11 and ψ 12 , the convex side axial height A1 is used to describe the convex side profile curve f1(t) of the insulator; the concave side geometric control coefficient ψ 21 and ψ 22, the concave side height A2 constructs the concave side contour curve f2(t), and the above six parameters constitute the variables to be optimized. The particle swarm algorithm is called to carry out the optimization analysis of the insulator geometric control coefficient and support the update of the corresponding control coefficient.

[0047] (4) Optimize the structure of the pot insulator and obtain the corresponding geometric control coefficient. At the same time, the maximum value of the normal electric field on both sides of the convex and concave and the average value of the normal electric field are used as decision variables to construct the objective function for optimizing the contour curve of the DC pot insulator. After multiple iterations and comparisons of the local optimal solutions, the result of achieving the minimum objective function is taken as the global optimal solution.

[0048] The above-described embodiment is only one embodiment of the present invention, and the description has certain specificity and detail, but it cannot be understood as limiting the scope of the invention patent. It should be pointed out that for ordinary technicians in this field, several modifications and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be based on the attached claims.

Claims

1. The electrical performance optimization design method of DC GIL pot-type insulator based on particle swarm algorithm. The specific experimental steps are as follows: (1) Based on the simplified model of small-taper pot-type insulator, the parametric reconstruction of the insulator surface contour curve is carried out, the insulator geometric control coefficient is determined in the quantitative optimization process, and the geometric model of the pot-type insulator is constructed. (2) An electric-thermal-fluid multi-field coupling simulation model for charge accumulation in basin-type insulators is established to simulate the influence of the charge accumulation process on the spatial electric field distortion. Key data such as normal and tangential field strengths and surface charge accumulation are output to support the comparison and optimization of subsequent simulation results. (3) Call the particle swarm algorithm to perform optimization analysis of the insulator geometric control coefficients and support the update of the corresponding control coefficients. (4) Optimize the structure of the pot insulator and obtain the corresponding geometric control coefficient. At the same time, through multiple iterations and comparisons of the local optimal solutions, the result of achieving the minimum objective function is taken as the global optimal solution.

2. The method for optimizing the electrical performance of a DC GIL pot-type insulator based on a particle swarm algorithm according to claim 1 is characterized in that: In step (1), the convex side of the simplified model of a small-taper pot insulator is taken as an example, and 35 feature points that can reflect the profile change behavior are selected on the curve. The selected feature points have an ideal fitting effect. In order to reasonably control the number of variables and the amount of calculation in the subsequent optimization algorithm, the fifth-order Bernstein polynomial is selected as a scheme to describe and reconstruct the surface curve profile of the DC insulator.

3. The method for optimizing the electrical performance of a DC GIL pot-type insulator based on a particle swarm algorithm according to claim 1, characterized in that: In the electric-thermal-fluid multi-field coupling simulation model of charge accumulation in the pot insulator established in step (2), the heat in the pipeline is transferred outward by processes such as heat conduction, heat convection and heat radiation. The heat transfer medium insulating gas and the pot insulator in the cavity show different heat transfer characteristics, and the insulator body will form a temperature gradient that affects the charge transport. When the heat generated by the central conductor is equal to the heat dissipation, the temperature gradient between the central conductor and the shell no longer changes, which is the stable temperature field of the GIL pipeline.

4. The method for optimizing the electrical performance of a DC GIL pot-type insulator based on a particle swarm algorithm according to claim 1, characterized in that: In step (3), the insulator geometric structure optimization problem is transformed into a mathematical optimization problem for optimizing the insulator surface curve profile. 11 and ψ 12 , the convex side axial height A1 is used to describe the convex side profile curve f1(t) of the insulator; the concave side geometric control coefficient ψ 21 and ψ 22 , the concave side height A2 constructs the concave side contour curve f2(t), and the above six parameters constitute the variables to be optimized.

5. The method for optimizing the electrical performance of a DC GIL pot-type insulator based on a particle swarm algorithm according to claim 1, characterized in that: In step (4), the maximum value of the normal electric field on both sides of the convex and concave and the average value of the normal electric field are used as decision variables to construct the objective function of the DC basin insulator contour curve optimization: δ1=E n1max +E n2max δ2=E n1mean +E n2mean minχ=ωδ1+(1-ω)δ2 Where: E n1max and E n2max are the maximum values ​​of the normal electric field intensity on the convex side surface and the normal electric field intensity on the concave side surface of the insulator during the transient process; E n1mean and E n2mean are the average values ​​of the normal field strength on the convex side and the concave side of the insulator during the transient process; ω is the weight coefficient, and its value range is [0,1]. The larger the ω is, the primary control target is to reduce the maximum value of the normal field strength; the smaller the ω is, the primary target is to reduce the overall size of the normal field strength. In addition, it is also necessary to consider that the insulator inclination angle should be limited to 60°~90°.

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