A gas insulated switchgear contact temperature rise prediction method considering multiple influencing factors

Abstract

The application discloses a kind of gas insulation fully enclosed switchgear (GIS) contact temperature rise prediction method considering multiple influence factors, belong to electric power equipment state monitoring technical field.This method is first by building the electromagnetic field-flow field-temperature field multi-physical field coupling model of GIS under operating condition and carries out experimental verification;Based on model simulation, the mapping data of contact temperature rise and shell temperature rise are extracted, and the load current, contact resistance, wind speed, solar radiation intensity and SF6 gas pressure are analyzed and selected as the main influence parameters;Through temperature measurement point space matching optimization, the shell measurement point with the highest thermal coupling strength of three-phase contact is selected as input, and the contact temperature rise prediction empirical formula based on radiation-wind speed coupling saturation model is established.The application fully considers the nonlinear influence of multidimensional environmental factors, significantly improves the inversion accuracy of contact temperature rise through space matching mechanism, effectively controls the prediction error within 2℃, has the advantages of non-invasive, simple calculation, clear physical meaning, etc., can effectively support the safety evaluation and overheating fault warning of GIS equipment.

Description

Technical Field

[0001] This invention relates to a method for predicting the temperature rise of contacts in a gas-insulated switchgear (GIS) that takes into account multiple influencing factors, and belongs to the field of power equipment condition monitoring and fault early warning technology. Background Technology

[0002] Gas-insulated switchgear (GIS) has been widely used in modern power systems due to its advantages such as compact structure, small footprint, high operational reliability, and minimal susceptibility to external environmental influences. However, the conductors inside a GIS are constantly subjected to high current flow, and the entire device uses a fully enclosed metal shell structure, resulting in a compact internal space, good sealing, and relatively limited heat dissipation. During long-term operation, if heat generated by localized Joule losses accumulates and cannot be dissipated in time, it can easily lead to excessive temperature rise inside the device, accelerating the aging of insulation materials and potentially causing poor contact. In severe cases, it can even lead to short circuits and power outages, resulting in significant economic losses. Therefore, monitoring the internal temperature distribution of the GIS and accurately predicting contact temperature rise is crucial for ensuring the safe and stable operation of the equipment.

[0003] Currently, online monitoring methods for GIS overheating faults mainly include loop resistance testing, infrared thermography, and internally embedded sensors (such as fiber Bragg grating temperature measurement). While loop resistance testing can reflect the contact state of the contacts, it usually requires a power outage, making it difficult to meet real-time online monitoring needs. Infrared thermography has advantages such as being non-contact and easy to operate, but due to the fully enclosed metal casing structure of GIS, its monitoring target is mostly the equipment casing, making it difficult to directly obtain the true temperature of the internal contacts. Internally embedded temperature measurement technologies such as fiber Bragg gratings have advantages in resisting electromagnetic interference, but their deployment within GIS is limited by extremely strict insulation requirements, limited installation space, and long-term reliability issues. Overall, existing direct physical monitoring methods still have significant limitations in continuously, accurately, and non-destructively obtaining the temperature of internal contacts.

[0004] Numerous studies and engineering practices have demonstrated a thermodynamic correlation between the temperature of the GIS outer shell and the temperature of its internal contacts. By monitoring the temperature rise of the outer shell and combining it with appropriate algorithms, the temperature of the internal contacts can be indirectly estimated. This non-invasive method has great potential for implementation in engineering sites. Currently, there have been some explorations in related fields regarding the estimation of contact temperature based on the outer shell temperature, but existing research still has significant shortcomings: First, in actual operation, the temperature field distribution of GIS is affected by multiple factors such as load current, contact state, wind speed, solar radiation intensity, and SF6 gas pressure. However, most existing methods only consider a single factor or a few ideal environmental conditions, failing to deeply explore the thermal response characteristics under the coupling effect of multiple factors. This results in the temperature rise relationship between the outer shell and the contacts not being fixed under complex operating conditions. Second, most existing empirical formulas or algorithms ignore the matching problem between the selection of the outer shell temperature measurement point location and the spatial thermal coupling strength of the target contact, limiting further improvement in prediction accuracy. Furthermore, there is a lack of a comprehensive method for accurately predicting the temperature rise of GIS contacts that integrates multi-dimensional operating parameters and environmental factors for correlation modeling and can adapt to complex operating conditions. Summary of the Invention

[0005] The purpose of this invention is to propose a method for predicting the temperature rise of contacts in gas-insulated, fully enclosed switchgear (GIS) considering multiple influencing factors. This invention aims to overcome the limitations of existing monitoring methods that cannot directly measure the temperature of hot spots inside GIS. By exploring the influence of multi-dimensional operating parameters and environmental factors on the temperature field, it establishes an indirect prediction model for contact temperature rise that combines physical mechanism support with ease of engineering application.

[0006] The technical solution of this invention is:

[0007] A method for predicting the contact temperature rise of gas-insulated fully enclosed switchgear (GIS) considering multiple influencing factors, characterized in that the contact temperature rise is estimated based on the relationship between the housing temperature rise and environmental parameters, and the estimation method includes the following steps:

[0008] Step 1: Build a multiphysics coupling model of electromagnetic field, flow field and temperature field of GIS under operating conditions;

[0009] Step 2: Verify the above multiphysics coupling model by comparing experimental measurements with simulation calculations;

[0010] Step 3: Based on the simulation results, extract the corresponding relationship data between the temperature rise of the GIS contact and the temperature rise of the shell. Under different operating conditions, change the load current, contact resistance, wind speed, solar radiation intensity, SF6 gas pressure parameters and ambient temperature to obtain the variation characteristics between the temperature rise of the contact and the temperature rise of the shell under the influence of multiple factors, and screen out the main influencing parameters used to build the prediction model.

[0011] Step 4: Based on the multi-condition data obtained in Step 3, the temperature rise of each phase contact is correlated with the temperature rise of the shell at the corresponding spatial location and the main influencing parameters. An empirical formula for the temperature rise of the contact is established based on the radiation-wind speed coupled saturation model through data fitting. The actual measured shell temperature rise and environmental parameters are substituted into the formula to realize the calculation and prediction of the temperature rise of the GIS contact.

[0012] Step 1 includes the following specific steps:

[0013] Step 1-1: Analyze the loss generation and heat transfer process of gas-insulated fully enclosed switchgear (GIS) under actual operation, and establish multi-physics field control equations including conductor Joule heating, shell eddy current loss heating, internal SF6 gas natural convection, and surface thermal radiation.

[0014] Steps 1-2: Based on the structural dimensions and material parameters of the GIS, and combined with the characteristics of the internal SF6 gas and the external air medium, a multi-physics coupled finite element model including solid heat conduction, natural gas convection and surface radiation heat transfer is established. The relevant simulation data are shown in Tables 1, 2 and 3.

[0015] Table 1

[0016] parameter numerical values 252 550 Voltage level / kV 126 3.15 5.00 Rated current / kA 2.00 376 590 Outer diameter of the outer casing / mm 580 368 575 Inner diameter of the outer casing / mm 572 90 160 Guide rod outer diameter / mm 70 60 135 Guide rod inner diameter / mm 50 160 240 Shielding cover outer diameter / mm 120 140 220 Inner diameter of shielding cover / mm 100 0.4 0.5 <![CDATA[SF6 gas pressure / MPa]]> 0.4 2000 2000 Disconnect switch length / mm 2000 252 550

[0017] To characterize the contact resistance at the contact point between the contact and the guide rod, an equivalent simulation is performed by introducing a conductor with varying resistivity in the contact area. The contact length is 0.3 m, and the thickness of the resistivity variation region is 0.01 m.

[0018] Table 2

[0019] part Electrical conductivity (S / m) relative permeability Relative permittivity shell <![CDATA[2×10 7 ]]> 1 1 Shielding cover <![CDATA[2.63×10 7 ]]> 1 1 Guide rod <![CDATA[2.63×10 7 ]]> 1 1 Contact point <![CDATA[2.63×10 7 / (65750πR+0.01)]]> 1 1 <![CDATA[SF6 gas]]> <![CDATA[1×10 -5 ]]> 1 1.12

[0020] In the table, R represents the change in resistance at the contact point between the guide rod and the contactor.

[0021] Table 3

[0022] Structural components <![CDATA[Density (kg / m 3 )]]> <![CDATA[Thermal conductivity (10 -2 W / (m·K))]]> Specific heat capacity (J / (kg·K)) shell 2680 156 942 Shielding cover 2719 177 780 Guide rod 2719 177 780

[0023] The ambient temperature of the external air zone of the GIS equipment is set to 25℃, and the ambient pressure is set to 0.1 MPa. Since the physical properties of SF6 gas and air are functions of temperature and air pressure, the COMSOL software material library is selected.

[0024] Steps 1-3: To balance computational accuracy and solution efficiency, a free tetrahedral mesh controlled by the physical field is used for multiphysics solutions. The GIS equipment body uses a finer free tetrahedral mesh, while the external air domain uses a conventional tetrahedral mesh. Considering that the inner and outer surfaces of the GIS are important boundaries for natural convection and radiation heat transfer, a boundary layer mesh is specially set up and appropriately densified in this adjacent area for numerical solution, and the calculation results converge.

[0025] Step 2 includes the following specific steps:

[0026] Step 2-1: Obtain typical GIS temperature rise measurement data under different voltage levels and operating conditions; select typical GIS online temperature measurement experimental data recognized in the field as a benchmark, the data covering multiple voltage levels and operating conditions:

[0027] 126 kV three-phase common-enclosure GIS: Measured contact temperature (51.12℃) and enclosure temperature (32.60℃) were obtained under the following conditions: power frequency current 2 kA, SF6 gas pressure 0.4 MPa, and ambient temperature 26.30℃.

[0028] 252 kV GIS: Measured data of contact temperature rise (33.97℃) and shell temperature rise (13.14℃) were obtained under the conditions of power frequency current 3 kA, ambient temperature 21.00℃, SF6 gas pressure 0.3 MPa, and contact resistance 25 μΩ.

[0029] 550 kV single-phase box-type GIS: The measured contact temperature rise data (78.90℃) was obtained under the conditions of test current 6.9 kA, SF6 gas pressure 0.5 MPa, and ambient temperature 20.00℃.

[0030] Step 2-2: Establish the corresponding simulation verification model and perform quantitative error analysis; Based on the physical structure and operating parameters of the above voltage level experiments, establish the corresponding multi-physics coupling simulation verification model and extract the simulated temperature rise values ​​at the same monitoring points:

[0031] The comparison results show that the simulated contact temperature of 126 kV GIS differs from the measured data by 1.40℃; the simulated temperature rise of 252 kV GIS differs from the measured data by 0.53℃; and the simulated temperature rise of 550 kV GIS differs from the measured data by 1.58℃.

[0032] By comparing the simulation results under multiple voltage levels with typical experimental data, it was verified that the calculation errors under each working condition meet the engineering accuracy requirements, thus proving the accuracy and universality of the proposed multi-physics coupling modeling approach of electromagnetic field-fluid field-temperature field.

[0033] Step 3 includes the following specific steps:

[0034] Step 3-1: In order to facilitate the study of the influence characteristics of multiple complex factors on the internal thermal state of GIS, the mapping relationship between the temperature rise of the three-phase contacts and the temperature rise of the shell at the corresponding spatial location is taken as the basic analysis object.

[0035] Step 3-2: Assuming that external wind speed, solar radiation intensity and SF6 pressure and other environmental and operating parameters remain constant, set the load current and contact resistance to vary within a preset range, and obtain the contact temperature rise and shell temperature rise curves under different electrical parameters; it is found that the load current and contact resistance significantly increase the temperature rise of both the contact and shell, which are the core internal factors causing the temperature rise change and have a significant impact on the temperature rise correlation.

[0036] Step 3-3: Assuming that the internal load current and contact resistance remain constant, and setting the wind speed and solar radiation intensity to fluctuate within the range of meteorological changes, the temperature rise curves of the contact and the outer shell under different external environmental conditions are obtained. It is found that increasing wind speed significantly suppresses temperature rise by enhancing external convection heat transfer (and has nonlinear saturation cooling characteristics), while increasing solar radiation intensity causes the temperature rise to rise in an approximately linear manner. The two have a significant impact on the correlation of temperature rise.

[0037] Steps 3-4: Assuming the above electrical parameters and wind and solar meteorological parameters remain unchanged, set the ambient temperature to vary between -10℃ and 30℃, and obtain the contact temperature rise and shell temperature rise curves under different ambient temperatures; it is found that the change in ambient temperature mainly raises the absolute temperature level of the equipment's interior and shell, but has a very small impact on the contact temperature rise and shell temperature rise values ​​themselves and the corresponding relationship between the two, which can be ignored in the process of building the prediction model.

[0038] Steps 3-5: Assuming the above electrical and meteorological parameters remain unchanged, set the internal SF6 pressure to vary between 0.3 and 0.6 MPa, and obtain the contact temperature rise and shell temperature rise curves under different pressures; it is found that increasing the SF6 pressure can effectively enhance internal convection heat dissipation and thus reduce the contact temperature rise (with saturation characteristics), but has almost no effect on the shell temperature rise.

[0039] Steps 3-6: Based on the above simulation and data pattern analysis, the environmental temperature factor with a small impact is eliminated, and the shell temperature rise, load current, contact resistance velocity, solar radiation intensity and SF6 gas pressure are finally selected as the main influencing parameters for constructing the empirical formula for predicting the temperature rise of GIS contacts.

[0040] Step 4 includes the following specific steps:

[0041] Step 4-1: Sample data organization and preprocessing;

[0042] The data obtained in step 3 through multiphysics simulation, including the temperature rise of three-phase contacts, the temperature rise of multiple points on the shell, and various operating parameters (load current, wind speed, solar radiation intensity, SF6 pressure), are summarized to construct a sample dataset for formula fitting, and outlier detection and data cleaning are performed.

[0043] Step 4-2: Optimize the spatial matching of the outer casing temperature rise monitoring points;

[0044] Based on the sensitivity differences in the thermal response of the internal contacts to the temperature rise of the outer shell at different orientations, the selection of monitoring points was optimized. Through comparative analysis, the outer shell temperature rise data with the strongest thermal coupling and the closest spatial distance to the A, B, and C phase contacts were selected as the feature input quantities for the corresponding phase contact temperature rise prediction formula, so as to restore the direct path of heat transfer from the internal hot spot to the outer shell to the greatest extent.

[0045] Step 4-3 establishes the radiation-wind speed coupled saturated model function relationship between the contact temperature rise, the matching shell temperature rise, and multiple environmental parameters. The general expression is shown in equation (1):

[0046] (1)

[0047] In the formula, T c —Contact temperature rise, a0—constant term, a1—load current square coefficient, I—load current, a2—casing temperature rise coefficient, T m —Outer shell temperature rise, a3—Wind speed saturation coefficient, k3—Wind speed saturation rate, v—Wind speed, a4—Solar radiation coefficient, S—Solar radiation intensity, a5—Pressure saturation coefficient, k5—Pressure saturation rate, p—Pressure, C—Product coefficient, b w0 —Basic wind speed amplitude, non-negative; b w1 —The amplification factor of radiation on wind speed amplitude, a non-negative value.

[0048] Using the aforementioned sample dataset, nonlinear regression analysis was used to determine the specific model coefficients for the three contacts A, B, and C, thereby improving the goodness of fit R of each phase formula. 2 All reached above 0.98. Taking a 126 kV three-phase common-enclosure GIS as an example, the simulation data was fitted to obtain the three-phase contact temperature rise prediction model, as shown in equations (2), (3) and (4):

[0049] (2)

[0050] (3)

[0051] (4)

[0052] Step 4-4: Verify the validity of the formula and assess the error;

[0053] 164 sets of typical working condition data, independent of the fitted dataset, were selected as validation samples. These samples were used to replace equations (2), (3), and (4) to obtain the calculated contact temperature rise values, and the difference between these values ​​and the validation data was calculated. The results show that, under the optimized spatial thermal matching conditions of the monitoring points, the predicted contact temperature rise values ​​of each phase are highly consistent with the reference values. The maximum absolute error of the prediction is controlled within 1.9℃ across the entire working condition range (the maximum error for phase B is 1.495℃, and for phase C it is 1.710℃), which verifies the reliability of this empirical formula.

[0054] Steps 4-5: Achieve real-time online prediction of internal contact temperature rise in GIS;

[0055] By substituting the real-time monitored temperature rise data of a specific phase of the outer shell and environmental parameters (load, wind speed, sunshine, air pressure) into the corresponding empirical formula for the phase determined in step 4-3, rapid inversion and online monitoring of hotspot temperatures within the GIS can be achieved.

[0056] This invention takes into account the influence of multiple environmental factors and the coupling effect of multiple physical fields during the research process, resulting in more realistic temperature rise data. This fills the gap in current GIS contact temperature rise prediction, which does not fully consider the coupling effect of complex environmental factors. Through empirical formulas for spatial matching, the contact temperature rise can be predicted with high accuracy using only the shell temperature rise and external environmental parameters. Compared with traditional contact temperature measurement or complex intelligent algorithms, this method is simpler, more convenient, non-invasive, and has clear physical meaning, making it significant in practical engineering applications. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of a 126 kV three-phase common-enclosure GIS structure and a schematic diagram of its physical model.

[0058] Figure 2 This is a schematic diagram of the grid division in a GIS model.

[0059] Figure 3 This is a GIS temperature field distribution map under rated operating conditions.

[0060] Figure 4 This is a curve showing the temperature rise of the contacts and housing when the load current changes.

[0061] Figure 5 This is a curve showing the temperature rise of the contact and housing when the contact resistance changes.

[0062] Figure 6 This is a curve showing the temperature rise of the contact and outer casing when the wind speed changes.

[0063] Figure 7 The curves show the temperature rise of the contacts and casing when the SF6 gas pressure changes.

[0064] Figure 8 This is a curve showing the temperature rise of the contact and outer casing as the solar radiation intensity changes.

[0065] Figure 9 This is a curve showing the temperature rise of the contacts and casing when the ambient temperature changes.

[0066] Figure 10 This is the location for monitoring the temperature rise of the outer casing.

[0067] Figure 11 Error curve of three-phase contact temperature rise calculation when using a unified monitoring point temperature rise.

[0068] Figure 12 Error curve of three-phase contact temperature rise calculation when using spatially matched monitoring point temperature rise.

[0069] Figure 13 Research Roadmap for GIS Contact Temperature Rise Prediction Method Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0071] The purpose of this invention is to propose a method for predicting the temperature rise of contacts in gas-insulated fully enclosed switchgear (GIS) that takes into account multiple influencing factors.

[0072] The technical solution of this invention is:

[0073] A method for predicting the temperature rise of GIS contacts considering multiple influencing factors, wherein the contact temperature rise is estimated based on the relationship between the shell temperature rise and environmental parameters, and the estimation method includes the following steps:

[0074] Step 1: Build a multiphysics coupling model of electromagnetic field, fluid field and temperature field of GIS under operating conditions;

[0075] Step 2: Verify the above multiphysics coupling model by comparing experimental measurements with simulation calculations;

[0076] Step 3: Based on the simulation results, extract the corresponding relationship data between the temperature rise of the GIS contact and the temperature rise of the shell. Under different operating conditions, change the load current, contact resistance, wind speed, solar radiation intensity and SF6 gas pressure parameters to obtain the variation characteristics between the temperature rise of the contact and the temperature rise of the shell under the influence of multiple factors, and screen out the main influencing parameters used to build the prediction model.

[0077] Step 4: Based on the multi-condition data obtained in Step 3, the temperature rise of each phase contact is correlated with the temperature rise of the shell at the corresponding spatial location and the main influencing parameters. An empirical formula for the temperature rise of the contact is established based on the radiation-wind speed coupled saturation model through data fitting. The actual measured shell temperature rise and environmental parameters are substituted into the formula to realize the calculation and prediction of the temperature rise of the GIS contact.

[0078] Step 1 includes the following specific steps:

[0079] Step 1-1: Analyze the loss generation and heat transfer process of GIS during actual operation, and establish multi-physics field control equations including conductor Joule heating, shell eddy current loss heating, internal SF6 gas natural convection, and surface thermal radiation, as follows:

[0080] The internal magnetic field of the GIS is mainly generated by a 50 Hz power frequency current, distributed in a ring around the conductor rod, and the magnetic field strength is directly proportional to the current magnitude. The GIS shell material is aluminum alloy, which exhibits eddy current phenomena. The heat loss problem of the GIS equipment falls into the category of low-frequency eddy current losses, and the heat source mainly consists of two aspects: first, the Joule heat generated when the current flows through the conductor; and second, the eddy current losses generated by the metal shell under electromagnetic induction. To ensure accurate calculation of the heat loss, this paper makes the following assumptions:

[0081] (1) For low-frequency cases, the influence of displacement current is ignored;

[0082] (2) Ignore the effect of leakage current between the conductor rod and the outer shell and shield on the heat generation, and only consider the current flowing along the conductor axis.

[0083] Based on the above assumptions, the governing equations for current density are established, as shown in equations (1) to (4). Equations (1) and (2) describe the current density distribution in the outer shell and shield, equation (3) describes the current density distribution inside the conductor, and equation (4) is the expression for the total current density.

[0084] (1)

[0085] (2)

[0086] (3)

[0087] (4)

[0088] In the formula, µ1 is the magnetic permeability of the material, σ is the electrical conductivity of the material, ω is the angular frequency of the current, φ is the scalar potential, and J is the electric potential. z —Total current density, A —Magnetic vector potential, J e —Source current density.

[0089] When the effective value of the total current I is applied to the conductor end face as a boundary condition, its relationship with the total current density inside the conductor is as follows:

[0090] (5)

[0091] The conductor, shell, and power loss in the eddy current field are:

[0092] (6)

[0093] In the formula, S C —Cross-sectional area of ​​the conductor end face, V —Volume domain containing the conductor and the outer shell.

[0094] The calculation of the temperature field in GIS requires simultaneous consideration of multiple heat sources and multi-medium heat transfer processes. The heat sources mainly include Joule heating of the conductor, eddy current loss heat of the outer shell, and solar radiation heat. The heat transfer methods mainly include heat conduction through the metal structure, radiative heat transfer between the conductor and the outer shell, natural convection of SF6 gas within the cavity, and forced convection of external air. To improve computational efficiency and ensure the accuracy of the results, this paper makes the following assumptions for the calculation of the fluid field and temperature field:

[0095] (1) Solar radiation conditions are simulated by applying a boundary heat source to the surface of the shell;

[0096] (2) Use the gas velocity vector at the inlet boundary as the wind speed boundary condition;

[0097] (3) The Reynolds numbers calculated from the relevant parameters of this model for air and SF6 flow are both relatively small, therefore laminar flow models are used in the fluid domain.

[0098] (4) The physical properties of solid materials are treated as constants during the calculation process.

[0099] (5) To ensure the accuracy of the thermal model solution, the natural convection heat transfer of the fluid satisfies the Boussinesq approximation. In computational fluid dynamics (CFD) analysis, except for the specific heat of SF6 gas and air, other thermophysical properties are considered to be temperature-dependent. The change in density with temperature and pressure is expressed using the ideal gas law:

[0100] (7)

[0101] The dynamic viscosity and thermal conductivity of a gas are almost unaffected by gas pressure; their changes with temperature are determined by Sutherland's law:

[0102] (8)

[0103] (9)

[0104] In the formula, P corresponds to the gas pressure, M corresponds to the molar mass of the gas, R is the ideal gas constant, T corresponds to the gas temperature, µ0 and k0 are the dynamic viscosity and thermal conductivity of SF6 gas and air at 0℃, S1 and S2 are the Sutherland temperatures corresponding to the calculation of the dynamic viscosity and thermal conductivity of the gas, and T0 is the reference temperature.

[0105] Based on the above simplification, the following governing equations are obtained:

[0106] (10)

[0107] (11)

[0108] (12)

[0109] In the formula, ρ represents density, and c represents density. p —Specific heat capacity, u—Velocity vector, k—Thermal conductivity, Q h —Volume heat source of each component of GIS, p—gas pressure, I1—identity matrix, µ—gas dynamic viscosity, S—source term, — This is the symbol for tensor product.

[0110] Considering the influence of various external factors, the research model in this paper uses multiple boundary conditions:

[0111] (1) Temperature boundary conditions.

[0112] (13)

[0113] In the formula, T0 is the ambient temperature.

[0114] (2) Radiation boundary conditions

[0115] Equations (2-14) and (2-15) are the surface-to-surface radiation boundary conditions inside the GIS, and equations (2-16) and (2-17) are the boundary conditions between the outer shell of the GIS and solar radiation.

[0116] (14)

[0117] (15)

[0118] (16)

[0119] (17)

[0120] In the formula, σ is the Stefan-Boltzmann constant, and q is the... r—Total heat flux flowing into the surface through radiation, J —Total heat flux flowing out through radiation, G —Direct heat flux across the surface, G ext —Heat flux to the surface of the outer shell directly from the sun, F ext (x0, y0) — Incident vector of solar radiation source, q o.s —External radiation source heat flux, ε1, ε2 —Emissivity of the inner and outer surfaces of the GIS.

[0121] (3) Equations (2-18) and (2-19) are the boundary conditions for wind speed inlet and outlet:

[0122] (18)

[0123] (19)

[0124] In the formula, v0 is the airflow velocity at the inlet, n is the normal direction, and p0 is the static pressure at the outlet.

[0125] Steps 1-2: Based on the structural dimensions and material parameters of the GIS, and considering the characteristics of the internal SF6 gas and external air medium, a model was built using finite element simulation software. The relevant 126 kV GIS simulation data are shown in Tables 1, 2, and 3.

[0126] Table 1

[0127] parameter numerical values 252 550 Voltage level / kV 126 3.15 5.00 Rated current / kA 2.00 376 590 Outer diameter of the casing / mm 580 368 575 Inner diameter of the outer casing / mm 572 90 160 Guide rod outer diameter / mm 70 60 135 Guide rod inner diameter / mm 50 160 240 Shielding cover outer diameter / mm 120 140 220 Inner diameter of shielding cover / mm 100 0.4 0.5 <![CDATA[SF6 Gas Pressure / MPa]]> 0.4 2000 2000 Disconnect switch length / mm 2000 252 550

[0128] To characterize the contact resistance at the contact point between the contact and the guide rod, an equivalent simulation is performed by introducing a conductor with varying resistivity in the contact area. The contact length is 0.3 m, and the thickness of the resistivity variation region is 0.01 m.

[0129] Table 2

[0130] part Electrical conductivity (S / m) relative permeability Relative permittivity shell <![CDATA[2×10 7 ]]> 1 1 Shielding cover <![CDATA[2.63×10 7 ]]> 1 1 Guide rod <![CDATA[2.63×10 7 ]]> 1 1 Contact point <![CDATA[2.63×10 7 / (65750πR+0.01)]]> 1 1 <![CDATA[SF6 gas]]> <![CDATA[1×10 -5 ]]> 1 1.12

[0131] In the table, R represents the change in resistance at the contact point between the guide rod and the contactor.

[0132] Table 3

[0133] Structural components <![CDATA[Density (kg / m 3 )]]> <![CDATA[Thermal conductivity (10 -2 W / (m·K))]]> Specific heat capacity (J / (kg·K)) shell 2680 156 942 Shielding cover 2719 177 780 Guide rod 2719 177 780

[0134] The ambient temperature of the external air zone of the GIS equipment is set to 25℃, and the ambient pressure is set to 0.1 MPa. Since the physical properties of SF6 gas and air are functions of temperature and air pressure, the COMSOL software material library is selected.

[0135] Steps 1-3: To balance computational accuracy and solution efficiency, a free tetrahedral mesh controlled by the physical field is used for subdivision in the multiphysics solution. Among them, the GIS equipment body adopts a finer free tetrahedral mesh specification, and a boundary layer mesh is set in the adjacent area of ​​the inner and outer surfaces of the GIS and appropriately densified, and the calculation results converge.

[0136] Step 2 includes the following specific steps:

[0137] Step 2-1: Obtain typical GIS online temperature measurement experimental data recognized in this field, including measured shell and contact temperature data at multiple voltage levels such as 126 kV, 252 kV and 550 kV;

[0138] Step 2-2: Establish the corresponding GIS simulation model based on the experimental parameters, and set the corresponding load current, SF6 gas pressure and ambient temperature conditions. By comparing the measured results with the simulation results, it can be seen that the maximum error at each voltage level is within 1.6℃ (e.g., the error is 1.40℃ for 126 kV, 0.53℃ for 252 kV, and 1.58℃ for 550 kV). The simulation and the measured results are highly consistent, which verifies the correctness of the multiphysics model and its universality across voltage levels.

[0139] Step 3 includes the following specific steps:

[0140] Step 3-1: To study the influence characteristics of multiple complex factors on the internal thermal state of GIS, the mapping relationship between the temperature rise of the three-phase contacts and the temperature rise of the shell at the corresponding spatial location is taken as the basic analysis object.

[0141] Step 3-2: Keeping other parameters constant, set the contact resistance increment range to 0~100 μΩ (step 20 μΩ) and the load current range to 0.5~2 kA (step 0.5 kA); it was found that the load current and contact resistance significantly increased the temperature rise of the contacts and the shell, which is the core internal factor causing the temperature rise change.

[0142] Step 3-3: Keeping other parameters constant, set the wind speed variation range to 0~15 m / s and the solar radiation intensity variation range to 0~1000 W / m² (step size 100 W / m²); it was found that increasing wind speed can significantly suppress temperature rise and exhibit nonlinear saturation characteristics, while increasing solar radiation causes the temperature rise to increase approximately linearly.

[0143] Steps 3-4: Keep other parameters constant and set the ambient temperature variation range to -10℃ to 30℃ (step size 10℃); the ambient temperature only increases the absolute temperature, which has a very small impact on the temperature rise value itself and the corresponding relationship, and can be ignored in the prediction.

[0144] Steps 3-5: Keeping other parameters constant, set the internal SF6 gas pressure variation range to 0.3~0.6 MPa (step 0.05 MPa); it is found that the increase in gas pressure can effectively enhance convective heat dissipation and reduce the temperature rise of the contacts, but has almost no effect on the temperature rise of the outer casing.

[0145] Step 4 includes the following specific steps:

[0146] Step 4-1: Organize and preprocess the multi-condition data obtained in Step 3;

[0147] Step 4-2: For three-phase common-enclosure GIS, select the temperature rise data of the shell measuring points (defined as points a, b, and c) that have the strongest thermal coupling with the contacts of phases A, B, and C and are closest in space as the input of the corresponding phase prediction formula;

[0148] Step 4-3: Fit the processed data to establish the radiation-wind speed coupled saturation model function relationship:

[0149] (20)

[0150] (twenty one)

[0151] (twenty two)

[0152] Step 4-4: Calculate the error using 164 sets of validation data independent of the fitted dataset.

[0153] A temperature field simulation model based on the aforementioned GIS was constructed to obtain the variation patterns of contact temperature rise and shell temperature rise under the influence of multiple factors. Specifically, this was achieved through the following steps:

[0154] In the modeling, a 126 kV three-phase co-enclosure GIS was used as an example. Considering the actual situation, the following simplifications were made: the contact area was assumed to have uniform heating and was considered an equivalent volumetric heat source; the influence of the upper operating mechanism box of the disconnecting switch on heat dissipation was ignored; the cross-section of the basin-type insulator was set as an adiabatic boundary; and a 0.01 m thick resistivity variation layer was introduced in the contact area between the contact and the conductor rod to simulate the change in contact resistance, such as... Figure 1 As shown in the figure. The following section verifies the rationality of the above simplification through simulation and actual measurement comparisons at multiple voltage levels.

[0155] To balance computational efficiency with accurate characterization of near-wall fluid and temperature field gradients, a free tetrahedral mesh was used overall, with a dedicated boundary layer mesh set in the natural convection and radiation heat transfer regions adjacent to the inner and outer surfaces, ultimately generating 152,189 domain elements. Figure 2 This is a schematic diagram of the specific grid division results.

[0156] To investigate the influence of contact resistance and load current, temperature rise curves under different internal heating conditions were obtained using a model, such as... Figure 4 and Figure 5 As shown in the figure. The results indicate that when the contact resistance or load current increases, the heat generated at the contacts rises sharply, while the temperature rise of the casing, although it responds, is relatively delayed and the increase is small.

[0157] To investigate the influence of external meteorological conditions, temperature rise curves under different wind speeds and solar radiation intensities were obtained using a model, such as... Figure 6 and Figure 8 As shown in the figure, the results indicate that when the wind speed increases from 0 to 5 m / s, the temperature rise decreases significantly, but the cooling effect gradually approaches saturation after the wind speed exceeds 5 m / s; while the increase in solar radiation intensity causes a linear increase in internal and external temperature rise by approximately the same magnitude. This demonstrates the physical basis of the radiation-wind speed coupled saturation model proposed in this invention.

[0158] To investigate the influence of the insulating medium on the ambient reference temperature, temperature rise curves were obtained using a model under different SF6 gas pressures and ambient temperatures, such as... Figure 7 and Figure 9 As shown in the figure. The results demonstrate that ambient temperature only changes the absolute temperature of the system without altering the temperature rise mapping relationship, and can be eliminated from the predictor variables; while changes in air pressure cause changes in the contact temperature rise but have almost no effect on the shell temperature rise, making them the key variables that must be included.

[0159] With the support of the above data, data under multiple operating conditions (load current 1~2 kA, wind speed 0~15 m / s, solar radiation 0~1000 W / m², air pressure 0.3~0.6 MPa, etc.) were extracted and regression analysis was performed on equation (1). To address the problem of interphase heat conduction interference, this invention optimized the spatial matching of monitoring points, such as... Figure 10 As shown. The temperature rise at points a, b, and c is used as the input to the three-phase formulas for phases A, B, and C, respectively. The coefficients of determination (R²) of the fitted formulas for each phase are... 2 All reached 0.98 or higher.

[0160] The effectiveness of the above formula was verified by substituting 164 sets of data, independent of the dataset, into the formula. The prediction results and error distribution are as follows: Figure 11 and Figure 12 As shown, compared to the case of fitting the temperature rise using a unified monitoring point, the prediction error of the three-phase contact temperature rise is greatly reduced after spatial matching optimization. Specifically, the maximum absolute prediction errors for phases B and C are significantly reduced from 2.755℃ and 2.816℃ with a unified monitoring point to 1.495℃ and 1.710℃, respectively. The predicted contact temperature rise values ​​have extremely small errors and excellent performance, providing strong support for the feasibility of the prediction method proposed in this patent.

[0161] This invention comprehensively considers the coupling effects of multiple physical fields, such as electromagnetic loss, gas convection, heat conduction, and radiation, and fully covers the fluctuation range of multi-dimensional operating parameters, including load, air pressure, wind, and solar power, resulting in data that is more realistic. Through a spatially thermally matched radiation-wind speed coupled saturation model, the contact temperature rise can be inverted using only easily measurable variables such as the shell temperature rise and external environmental parameters. Compared with traditional power outage measurements or invasive temperature measurements, this method is simpler, more convenient, non-invasive, and has clear physical meaning, making it significant for engineering applications in actual GIS operation status monitoring and overheat fault early warning.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit the scope of protection of the present invention. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the essence and scope of the technical solutions of the present invention.

Claims

1. A method for predicting the temperature rise of contacts in a gas-insulated switchgear (GIS) considering multiple influencing factors, characterized in that, The contact temperature rise is estimated based on the relationship between the housing temperature rise and environmental parameters. The method includes the following steps: Step 1: Build a multiphysics coupling model of electromagnetic field, fluid field and temperature field of GIS under operating conditions; Step 2: Verify the above multiphysics coupling model by comparing experimental measurements with simulation calculations; Step 3: Based on the simulation results, extract the corresponding relationship data between the temperature rise of the GIS contact and the temperature rise of the shell. Under different operating conditions, change the load current, contact resistance, wind speed, solar radiation intensity and SF6 gas pressure parameters to obtain the variation characteristics between the temperature rise of the contact and the temperature rise of the shell under the action of multiple factors, and screen out the main influencing parameters used to build the prediction model. Step 4: Based on the multi-condition data obtained in Step 3, the temperature rise of each phase contact is correlated with the temperature rise of the shell at the corresponding spatial location and the main influencing parameters. An empirical formula for the temperature rise of the contact is established based on the radiation-wind speed coupled saturation model through data fitting. The actual measured shell temperature rise and environmental parameters are substituted into the formula to realize the calculation and prediction of the temperature rise of the GIS contact.

2. The method for predicting the temperature rise of GIS contacts considering multiple influencing factors according to claim 1, characterized in that: Step 1 includes the following specific steps: Step 1-1: Analyze the heat transfer mechanism between conductors, contacts and shell during GIS operation, and establish a steady-state heat balance equation that includes Joule heating of conductors, eddy current loss heating of shell and solar radiation heat source terms. Steps 1-2: Based on the structural dimensions and material parameters of the GIS, and combined with the characteristics of the internal SF6 gas and the external air medium, establish a multi-physics coupled finite element model that includes solid heat conduction, natural gas convection and surface radiation heat transfer. Steps 1-3: Perform geometric modeling and mesh generation on the model, set boundary conditions for ambient temperature, wind speed, solar radiation and gas pressure, and perform numerical solutions to obtain the GIS three-dimensional temperature field distribution and temperature rise data of each component.

3. The method for predicting the temperature rise of GIS contacts considering multiple influencing factors according to claim 1, characterized in that: Step 2 includes the following specific steps: Step 2-1: Acquire GIS temperature measurement data under actual operating or experimental platform conditions, measure the temperature change of the shell and contacts over time using temperature sensors, and record the corresponding environmental operating parameters; Step 2-2: Establish the corresponding finite element simulation model based on the experimental working condition parameters, and calculate and obtain the simulation results of the GIS temperature field; Steps 2-3: Compare the simulation results of the contact temperature rise and the shell temperature rise with the measured data to verify the effectiveness and accuracy of the multiphysics coupling model.

4. The method for predicting the temperature rise of GIS contacts considering multiple influencing factors according to claim 1, characterized in that: Step 3 includes the following specific steps: Step 3-1: Under the condition of keeping the wind speed, solar radiation intensity and SF6 pressure constant, change the load current and contact resistance parameters, obtain the change curves of contact temperature rise and shell temperature rise under different electrical parameters, and extract the positive enhancement characteristics of load current and contact resistance on temperature field distribution. Step 3-2: Under the condition of keeping the load current and contact resistance constant, change the wind speed, solar radiation intensity and SF6 pressure parameters, and extract the nonlinear forced convection cooling characteristics of wind speed, the linear warming characteristics of solar radiation and the saturation promotion characteristics of air pressure increase on internal convection heat dissipation. Step 3-3: Based on the combined effects of multiple factors, determine the outer shell temperature rise, load current, wind speed, solar radiation intensity, and SF6 gas pressure as the main input parameters for the contact temperature rise prediction model.

5. The method for predicting the temperature rise of GIS contacts considering multiple influencing factors according to claim 1, characterized in that: Step 4 includes the following specific steps: Step 4-1: Extract the multi-condition data obtained from the simulation in Step 3, construct a sample dataset containing the temperature rise of each phase contact, the temperature rise of multiple points in the shell, and the main influencing parameters, and perform abnormal data removal preprocessing. Step 4-2: Perform spatial matching optimization of temperature measurement points. Select the temperature rise data of the shell measurement point that is closest to the contacts of phases A, B, and C and has the strongest thermal coupling as the input parameters of the independent prediction formula for each phase, so as to reduce the interference of heat conduction between multiple phases. Step 4-3: Establish the radiation-wind speed coupled saturation model function relationship between the contact temperature rise, the matching shell temperature rise, and multiple environmental parameters. The general expression is shown in equation (1): （1） In the formula, T c —Contact temperature rise, a0—constant term, a1—load current square coefficient, I—load current, a2—casing temperature rise coefficient, T m —Outer shell temperature rise, a3—Wind speed saturation coefficient, k3—Wind speed saturation rate, v—Wind speed, a4—Solar radiation coefficient, S—Solar radiation intensity, a5—Pressure saturation coefficient, k5—Pressure saturation rate, p—Pressure, C—Product coefficient, b w0 —Basic wind speed amplitude, non-negative; b w1 —The amplification factor of radiation on wind speed amplitude, a non-negative value.

6. Step 4-4: Taking a 126 kV three-phase common-enclosure GIS as an example, the simulation data is fitted to obtain the three-phase contact temperature rise prediction model, as shown in equations (2), (3) and (4): （2） （3） （4） Steps 4-5: Use the variable working condition simulation verification dataset and the measured experimental data to verify the effectiveness of the calculation error of the prediction formula; Steps 4-6: Configure the verified prediction formula in the monitoring system of the actual GIS equipment. By obtaining the shell temperature rise and corresponding environmental parameters during equipment operation and substituting them into the prediction formula, the online calculation and prediction of the temperature rise of the GIS contact can be realized.

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