Power transmission line corona discharge risk assessment method based on bird nest polarization characteristics

Abstract

The invention discloses a power transmission line corona discharge risk assessment method based on bird nest polarization characteristics, and relates to the field of power transmission line safe operation. The method specifically comprises the following steps: establishing a bird nest polarization characteristic mathematical model, considering bird nest material and shape characteristics, and calculating an electric field enhancement coefficient; introducing critical polarization intensity as a criterion of corona discharge; establishing a kinetic equation of polarization intensity changing along with time, and revealing dynamic characteristics of the polarization process; and defining a corona discharge probability function to realize quantitative evaluation of the discharge probability. According to the method, a complete physical model from bird nest polarization to corona discharge is established, key links such as electric field enhancement, polarization dynamics, critical polarization intensity and discharge probability are covered, a systematic theoretical framework is provided for corona discharge caused by bird nests, and the method has remarkable practical value for guiding design, operation and maintenance of power transmission lines and is worthy of popularization and application. And an important contribution is made for ensuring safe and stable operation of a power system.

Description

Technical Field

[0001] The invention relates to the field of safe operation of power transmission lines, and in particular to a method for assessing the risk of corona discharge of power transmission lines based on the polarization characteristics of bird nests. Background Art

[0002] Bird nests are a common problem in the operation of power transmission lines. Birds build nests on transmission towers, especially in the middle of the tower. Bird nests are made of materials such as hay and branches, which may absorb moisture in a humid environment and enhance conductivity. Conductive materials such as iron wire used by birds will also increase the conductivity of bird nests. These factors make bird nests prone to polarization in high-voltage electric fields, which may cause corona discharge, leading to insulator aging, equipment damage and line tripping, threatening the safe operation of transmission lines.

[0003] Traditional bird prevention measures such as bird spikes have limited effectiveness, and birds can often bypass protection. Existing monitoring technologies such as cameras can only provide rough estimates, increasing the complexity and cost of operation and maintenance. These methods make it difficult to assess the danger of bird nests from an electrical perspective. Existing technologies mainly include experimental measurements and numerical simulations. Experimental measurements measure discharge characteristics by building a test platform, but this is time-consuming and labor-intensive and difficult to cover all operating conditions. Numerical simulations use the finite element method to calculate the electric field distribution, but they usually ignore the influence of the polarization characteristics of the bird nest, making it difficult to accurately assess the discharge risk.

[0004] Traditional numerical simulation methods are mostly static simulations, ignoring the dynamic characteristics of polarization and corona discharge, and cannot accurately reflect the time-varying characteristics of polarization intensity and predict the dynamic behavior of corona discharge. This limitation makes it difficult to reflect the dynamic evolution characteristics of the polarization process, and also ignores the significant enhancement of the local electric field caused by polarization. Summary of the invention

[0005] The purpose of this invention is to propose a transmission line corona discharge risk assessment method based on the polarization characteristics of bird nests, which is used to assess the risk of corona discharge caused by foreign objects near transmission lines. The model considers the influence of the material properties and geometric shape of the bird nest on the polarization process and electric field distribution, introduces the electric field enhancement coefficient and critical polarization intensity as key parameters, establishes the time-varying dynamic equation of polarization intensity, defines the corona discharge probability function, and realizes the quantitative description and risk assessment of the whole process from polarization to corona discharge.

[0006] To achieve the above object, the present invention proposes a method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests, and the steps are as follows:

[0007] S1. Establish a mathematical model of the polarization characteristics of the bird's nest, consider the material and shape characteristics of the bird's nest, and calculate the electric field enhancement coefficient β;

[0008] S2. Introducing critical polarization intensity P c As the criterion for corona discharge, Pc The calculation formula of

[0009] S3. Establish the dynamic equation of the change of polarization intensity P with time to reveal the dynamic characteristics of the polarization process;

[0010] S4. Define the corona discharge probability function P corona (t), achieving quantitative evaluation of discharge probability.

[0011] Preferably, in S1, the electric field enhancement coefficient β is introduced into the mathematical model of the polarization characteristics of the bird's nest to characterize the disturbance effect of the bird's nest on the local electric field, and its expression is:

[0012] β=f(ε r ,σ,L / r,RH);

[0013] Among them, ε r is the relative dielectric constant of the bird's nest, σ is the electrical conductivity, L and r are the characteristic length and radius of the bird's nest respectively, RH is the relative humidity, and function f is the polarization intensity function.

[0014] Preferably, situations where bird nests are likely to cause power transmission line failures include:

[0015] S11. Polarization characteristics of wet bird nests: using a hybrid model to describe the equivalent dielectric constant ε eff , the formula is as follows:

[0016]

[0017] Among them, ε m is the dielectric constant of the dry bird nest material, ε w is the dielectric constant of water, g is the volume fraction of water;

[0018] S12. Polarization characteristics of bird nests containing conductive materials: A polarization model is used, and the model formula is as follows:

[0019]

[0020] Where, σ is the equivalent conductivity, ε * (ω) is the complex dielectric constant, ε ∞ is the high frequency limiting dielectric constant, ε s is the static dielectric constant, i is the imaginary unit, ω is the angular frequency, τ MWS is the Maxwell-Wagner-Sillars polarization characteristic time, α is the distribution parameter (0<α<1), ε0 is the vacuum dielectric constant;

[0021] S13. Polarization characteristics of bird nest materials that are easy to disperse: anisotropic dielectric model is used, and the model formula is as follows:

[0022]

[0023] in, is the anisotropic complex permittivity tensor, is the high frequency limiting dielectric constant tensor, is the static dielectric constant tensor, τ ij is the relaxation time tensor.

[0024] Preferably, considering the influence of the porosity of the bird nest material on the dielectric properties, an effective dielectric constant model is introduced:

[0025] ε eff =ε m (1-φ)+ε a φ;

[0026] Where φ is the porosity, ε m is the dielectric constant of the bird nest material, ε a is the dielectric constant of air;

[0027] Considering the influence of temperature on the polarization characteristics of bird nest materials, the Arrhenius equation is introduced:

[0028]

[0029] Among them, E a is the activation energy, k B is the Boltzmann constant, T is the absolute temperature, τ0 is the pre-exponential factor, and τ(T) is the characteristic relaxation time at temperature T.

[0030] Preferably, in S2, the critical polarization intensity P c The calculation formula is:

[0031] P c =ε0(ε r -1)E c / β;

[0032] Where ε0 is the dielectric constant of vacuum, ε r is the relative dielectric constant of the bird's nest, E c is the corona starting field strength.

[0033] Preferably, the corona initial field strength E c The calculation of is based on the modified Peek formula:

[0034]

[0035] Among them, E0 is the corona starting field strength under standard conditions, δ is the relative density of air, m is the surface condition coefficient of the conductor, K is a constant related to the geometric shape of the conductor, and r eqis the equivalent radius of the wire.

[0036] Preferably, in S3, the kinetic equation of the change of the polarization intensity P with time is:

[0037]

[0038] Where, τ is the polarization relaxation time, χ e is the electric susceptibility, and E is the external electric field strength.

[0039] Preferably, for complex situations, the fourth-order Runge-Kutta method is used for numerical solution, and the calculation is as follows:

[0040] k1=hf(t n ,P n )

[0041]

[0042] k4=hf(t n +h,P n +k3)

[0043]

[0044] f(t,P)=ε0χ e E / τ-P / τ;

[0045] Where k1, k2, k3, k4 are the four slope estimates in the Runge-Kutta method, h is the time step, and t n is the current time point, P n is the polarization intensity value at the current time point, P n+1 is the polarization intensity value at the next time point, and f(t,P) is a function that describes the change of polarization intensity over time.

[0046] Preferably, considering the influence of the vibration of the bird's nest under the action of wind on the polarization process, the dynamic equation is expressed as follows:

[0047]

[0048] Among them, A is the vibration amplitude and ω is the vibration frequency, which can be estimated by wind speed and bird nest characteristics.

[0049] Preferably, in S4, the corona discharge probability function P corona (t) is defined as:

[0050]

[0051] Where P(t) is the polarization intensity at time t, P cis the critical polarization intensity, n is the power index reflecting the discharge characteristics;

[0052] Considering the non-uniformity and moisture effects of bird nest materials, a correction factor is introduced:

[0053]

[0054] E c′ is the corrected corona onset field strength, ε r,eff is the equivalent relative dielectric constant after considering the effect of moisture, f RH is the humidity correction factor, expressed as follows:

[0055] ε r,eff =ε r (1+α RH RH)

[0056] f RH =1-β RH (RH-RH0);

[0057] Where RH is the relative humidity, RH0 is the reference humidity (usually 50%), α RH and β RH is an experimentally determined coefficient.

[0058] Therefore, the present invention proposes a transmission line corona discharge risk assessment method based on the bird's nest polarization characteristics, and its beneficial effects are as follows:

[0059] (1) The present invention establishes a complete physical model from bird nest polarization to corona discharge, covering key links such as electric field enhancement, polarization dynamics, critical polarization intensity and discharge probability, and provides a systematic theoretical framework for corona discharge induced by bird nests.

[0060] (2) The present invention comprehensively improves the research level of corona discharge induced by bird nests by establishing a complete physical model, improving calculation accuracy, introducing dynamic analysis, improving the universality of judgment criteria and realizing quantitative risk assessment.

[0061] (3) The technical features and advantages of the present invention have significant practical value in guiding the design, operation and maintenance of transmission lines, and have made important contributions to ensuring the safe and stable operation of power systems.

[0062] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 The present invention is a flow chart of the risk assessment of corona discharge of power transmission lines based on the polarization characteristics of bird nests. DETAILED DESCRIPTION

[0064] In order to make the technical solutions, advantages and purposes of the present invention clearer, the technical solutions of the embodiments of the present invention are clearly and completely described below. The described embodiments are part of the embodiments of the present invention, rather than all the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work belong to the protection scope of this application.

[0065] Unless otherwise defined, technical or scientific terms used in the present invention shall have the common meanings understood by one having ordinary skills in the field to which the present invention belongs.

[0066] like Figure 1 As shown, the present invention proposes a method for corona discharge risk assessment of transmission lines based on the polarization characteristics of bird nests. Bird nests are common foreign objects near transmission lines, and their polarization characteristics and corona discharge risk assessment are of great significance for ensuring the safe operation of transmission lines. The following will describe in detail the calculation method of bird nest related parameters, the determination of parameter values, the mutual influence between parameters, and the implementation of numerical algorithms.

[0067] Step 101: Establish a mathematical model of the polarization characteristics of the bird's nest. Considering the complexity and diversity of bird's nest materials, the Maxwell-Garnett hybrid model is used to calculate the equivalent dielectric constant of the bird's nest. Equivalent dielectric constant ε e The calculation formula of ff is:

[0068]

[0069] Among them, ε m is the dielectric constant of the matrix material (such as hay, branches, etc.), ε i is the dielectric constant of the inclusion (such as air, water), and g is the volume fraction of the inclusion.

[0070] To take into account the porosity of the material, we introduce the effective dielectric constant model:

[0071] ε eff =ε m (1-φ)+ε a φ

[0072] Where φ is the porosity, ε a is the dielectric constant of air.

[0073] Through these models, we can theoretically describe the equivalent dielectric properties of bird nests, thus providing a basis for subsequent electric field enhancement analysis.

[0074] Step 102: Determine parameter values. In practical applications, parameter values ​​need to be determined in combination with measured data and empirical values, for example:

[0075] Dielectric constant of hay: ε grass ≈1.5-3.0

[0076] Dielectric constant of the tree: ε branch ≈2.0-4.0

[0077] Dielectric constant of feather: ε feather ≈1.8-2.5

[0078] Dielectric constant of water (20℃): ε water ≈80.0

[0079] Dielectric constant of air: ε air ≈1.0

[0080] Geometric parameters such as the diameter of the bird's nest and the equivalent radius of the surface roughness need to be obtained through field measurement or estimation, and environmental parameters such as temperature and relative humidity also need to be set according to actual conditions.

[0081] Step 103: Calculate the electric field enhancement coefficient:

[0082] Assuming that the bird's nest is approximately spherical, the calculation formula of the electric field enhancement coefficient β is:

[0083]

[0084] Where D is the diameter of the bird's nest and r is the equivalent radius of the surface roughness.

[0085] To improve the accuracy, the shape factor k is introduced s and surface roughness factor k r To make corrections:

[0086] β corrected =β·k s

[0087]

[0088] Among them, h is the characteristic height of surface roughness, R is the equivalent radius of the bird's nest, k r is the roughness coefficient, usually between 0.1 and 0.5.

[0089] These corrections take into account the deviation of the actual shape of the bird's nest from the ideal sphere, as well as the effects of local electric field enhancement caused by surface roughness.

[0090] Step 104: Consider the interaction between parameters:

[0091] The effect of moisture content on the equivalent dielectric constant can be described by the following formula:

[0092] ε eff (w) = εdry +w(ε water -ε dry )

[0093] Wherein, w is the moisture content.

[0094] The effect of temperature on the dielectric constant can be described by the Arrhenius equation:

[0095]

[0096] Among them, E a is the activation energy, k B is the Boltzmann constant, T is the absolute temperature, T ref is the reference temperature. The effect of humidity on the corona initiation field strength is considered through the humidity correction factor:

[0097] k h =1-0.0045(RH-50%)

[0098] E c′ =E c ·k h

[0099] Where RH is relative humidity, E c′ is the corrected corona starting field strength.

[0100] These interactions make the model closer to reality.

[0101] Step 105: Establish the polarization intensity dynamics equation:

[0102] In order to describe the polarization process of the bird's nest in the electric field, the dynamic equation of the change of polarization intensity with time is established:

[0103]

[0104] Where, τ is the polarization relaxation time, χ e is the electric susceptibility, and E is the external electric field strength.

[0105] In order to more accurately describe the nonlinear effect, nonlinear terms are introduced into the equation:

[0106]

[0107] Among them, α is the nonlinear coefficient.

[0108] Considering the frequency dependence, the complex dielectric constant is introduced:

[0109]

[0110] Among them, ε ∞ is the high frequency limiting dielectric constant, εs is the static dielectric constant, ω is the angular frequency, and α is the distribution parameter.

[0111] These equations and parameters help describe the dynamics of the polarization process in bird nests.

[0112] Step 106: Implement the numerical algorithm:

[0113] In actual calculations, the finite difference method is used to discretize the control equation. Taking the Poisson equation as an example, the discretization form is:

[0114]

[0115] For solving the discretized equation, the Gauss-Seidel iteration method is used:

[0116]

[0117] For time-dependent problems, such as the kinetic equations of polarization intensity, the fourth-order Runge-Kutta method is used for numerical solution:

[0118] k1=hf(t n ,P n )

[0119]

[0120] k4=hf(t n +h,P n +k3)

[0121]

[0122] Where h is the time step and f(t,P) is the right side of the dynamic equation. These numerical methods can ensure the accuracy and stability of the calculation.

[0123] Step 107: Ensure numerical stability. When performing numerical calculations, pay special attention to the stability of the calculations. For example, when using the fourth-order Runge-Kutta method, the time step must meet certain conditions to ensure numerical stability:

[0124] Δt≤2τ

[0125] In actual calculations, the recommended time step is:

[0126] Δt=0.1τ

[0127] The iterative convergence condition is:

[0128]

[0129] Where ε is the relative error threshold, and its typical value is 10-6 . These strategies ensure the stability and convergence of the numerical calculations.

[0130] Step 108: Verify and optimize the model. After the model is established, verify the accuracy and applicability of the model through field measurements and laboratory tests. Compare the model prediction results with the actual observation data, and calibrate and optimize the model parameters based on the comparison results. In this process, you can consider using machine learning algorithms (such as neural networks or support vector machines) to optimize model parameters and improve the accuracy and generalization ability of risk assessment. Define the loss function for optimization:

[0131]

[0132] Among them, y i is the actual observed value, is the model prediction value, and N is the number of samples.

[0133] Step 109: Establish a risk early warning system:

[0134] Based on the established model and evaluation method, a transmission line corona discharge risk warning system is developed. The system can monitor the operating status and environmental parameters of the transmission line in real time, and combine with meteorological forecast data to predict the corona discharge risk in the future. Define the risk index RI:

[0135]

[0136] Among them, w1, w2, w3 are weight coefficients, P c is the critical polarization intensity, E c′ is the corrected corona onset field strength, RH c is the critical relative humidity. When the risk index exceeds the preset threshold, the system automatically sends out an early warning signal to remind the operation and maintenance personnel to take corresponding protective measures.

[0137] Step 110: Develop a protection strategy. Based on the risk assessment results, develop a targeted protection strategy. For high-risk areas, measures such as strengthening insulation, installing bird-proofing facilities, or increasing the frequency of inspections can be taken. At the same time, the design and layout of the transmission line can be optimized based on the model prediction results to reduce the possibility of bird nests. When optimizing the design of transmission lines, consider the safety distance d affected by bird nests. safe :

[0138] d safe =k s β final ·D

[0139] Among them, k sis the safety factor, usually 1.2-1.5. In addition, new bird-repelling technologies can be developed or existing bird-proofing facilities can be improved to reduce the impact of bird nests on transmission lines from the source.

[0140] Therefore, the transmission line corona discharge risk assessment method based on the bird's nest polarization characteristics proposed in the present invention has significant practical value for guiding the design, operation and maintenance of transmission lines, and makes an important contribution to ensuring the safe and stable operation of the power system.

[0141] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests, characterized in that: The following steps are involved: S1. Establish a mathematical model of the polarization characteristics of the bird's nest, consider the material and shape characteristics of the bird's nest, and calculate the electric field enhancement coefficient β; S2. Introducing critical polarization intensity P c As the criterion for corona discharge, P c The calculation formula of S3. Establish the dynamic equation of the change of polarization intensity P with time to reveal the dynamic characteristics of the polarization process; S4. Define the corona discharge probability function P corona (t), achieving quantitative evaluation of discharge probability.

2. A method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 1, characterized in that: In S1, the electric field enhancement coefficient β is introduced into the mathematical model of the polarization characteristics of the bird's nest to characterize the disturbance effect of the bird's nest on the local electric field, and its expression is: β=f(ε r ,σ,L / r,RH); Among them, ε r is the relative dielectric constant of the bird's nest, σ is the electrical conductivity, L and r are the characteristic length and radius of the bird's nest respectively, RH is the relative humidity, and function f is the polarization intensity function.

3. A method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 2, characterized in that: Situations where bird nests are likely to cause transmission line failures include: S11. Polarization characteristics of wet bird nests: using a hybrid model to describe the equivalent dielectric constant ε eff , the formula is as follows: Among them, ε m is the dielectric constant of the dry bird nest material, ε w is the dielectric constant of water, g is the volume fraction of water; S12. Polarization characteristics of bird nests containing conductive materials: The polarization model is used, and the formula is as follows: Among them, σ is the equivalent conductivity, ε * (ω) is the complex dielectric constant, ε ∞ is the high frequency limiting dielectric constant, ε s is the static dielectric constant, i is the imaginary unit, ω is the angular frequency, τ MWS is the polarization characteristic time, α is the distribution parameter, ε0 is the vacuum dielectric constant; S13. Polarization characteristics of bird nest materials that are easy to disperse: anisotropic dielectric model is used, and the formula is as follows: in, is the anisotropic complex permittivity tensor, is the high frequency limiting dielectric constant tensor, is the static dielectric constant tensor, τ ij is the relaxation time tensor.

4. A method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 3, characterized in that: Considering the influence of the porosity of the bird's nest material on the dielectric properties, the effective dielectric constant model is introduced: e eff =e m (1-φ)+ε a f; Where φ is the porosity, ε m is the dielectric constant of the bird nest material, ε a is the dielectric constant of air; Considering the influence of temperature on the polarization characteristics of bird nest materials, the Arrhenius equation is introduced: Among them, E a is the activation energy, k B is the Boltzmann constant, T is the absolute temperature, τ0 is the pre-exponential factor, and τ(T) is the characteristic relaxation time at temperature T.

5. The method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 1, characterized in that: S2, the critical polarization intensity P c The calculation formula is: P c =ε0(ε r -1)E c / b; Where ε0 is the dielectric constant of vacuum, ε r is the relative dielectric constant of the bird's nest, E c is the corona starting field strength.

6. A method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 5, characterized in that: The corona initial field strength E c The calculation of is based on the modified Peek formula: Among them, E0 is the corona starting field strength under standard conditions, δ is the relative density of air, m is the surface condition coefficient of the conductor, K is a constant related to the geometric shape of the conductor, and r eq is the equivalent radius of the conductor.

7. The method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 1, characterized in that: In S3, the kinetic equation of the change of the polarization intensity P with time is: Where, τ is the polarization relaxation time, χ e is the electric susceptibility, and E is the external electric field strength.

8. A method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 7, characterized in that: For complex situations, the fourth-order Runge-Kutta method is used for numerical solution, and the calculation is as follows: k1=hf(t n ,P n ) k4=hf(t n +h,P n +k3) f(t,P)=ε0χ e E / t-P / t; Where k1, k2, k3, k4 are the four slope estimates in the Runge-Kutta method, h is the time step, and t n is the current time point, P n is the polarization intensity value at the current time point, P n+1 is the polarization intensity value at the next time point, and f(t,P) is a function that describes the change of polarization intensity over time.

9. The method for risk assessment of corona discharge of power transmission lines based on bird nest polarization characteristics according to claim 7, characterized in that: Considering the influence of the vibration of the bird's nest under the action of wind on the polarization process, the dynamic equation is expressed as follows: Among them, A is the vibration amplitude and ω is the vibration frequency, which can be estimated by wind speed and bird nest characteristics.

10. The method for assessing the risk of corona discharge in power transmission lines based on the polarization characteristics of bird nests according to claim 1, characterized in that: In S4, the corona discharge probability function P corona (t) is defined as: Where P(t) is the polarization intensity at time t, P c is the critical polarization intensity, n is the power index reflecting the discharge characteristics; Considering the non-uniformity and moisture effects of bird nest materials, a correction factor is introduced: E c′ is the corrected corona onset field strength, ε r,eff is the equivalent relative dielectric constant after considering the effect of moisture, f RH is the humidity correction factor, which is expressed as follows: e r,eff =e r (1+a RH ·RH) f RH =1-β RH (RH-RH0); Where RH is the relative humidity, RH0 is the reference humidity, and α RH and β RH is an experimentally determined coefficient.

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