CN-122021199-A - Switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction

CN122021199ACN 122021199 ACN122021199 ACN 122021199ACN-122021199-A

Abstract

The invention belongs to the technical field of simulation analysis, and particularly relates to a switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction, which comprises the steps of establishing a simulation analysis model of a switch cabinet, adding a physical field, and performing physical field coupling and grid subdivision; the method comprises the steps of solving a simulation analysis model, obtaining the temperature and humidity distribution condition inside a switch cabinet, optimizing the simulation analysis model, using loss data to replace electromagnetic heat as heat source input to be imported into a non-isothermal flow field, constructing a physical field snapshot library for training a reduced-order model, processing the physical field snapshot library based on a POD method to construct a reduced-order model, training a Kriging model to reconstruct a temperature and humidity field of the switch cabinet, constructing a condensation margin assessment cloud image, calculating the actual dynamic dew point temperature in the actual operation process of the switch cabinet, generating the actual operation condensation margin cloud image, and completing online real-time assessment. The invention can realize the efficient and accurate reconstruction of the temperature and humidity field in the switch cabinet and the efficient evaluation of the condensation margin of the switch cabinet.

Inventors

XIAN RICHANG
Han Haocheng
ZHAO RUJIE
YU TAO
ZHANG BAOYUE
Luo Daoye
ZHAO YUXIN
GENG KAI
XIAN RIMING

Assignees

山东汇能电气有限公司

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. The switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction is characterized by comprising the following steps of: S1, for a medium-high voltage switch cabinet, establishing a geometric model of the switch cabinet and importing the geometric model into finite element simulation software to obtain a simulation analysis model, and setting material properties of each part; S2, adding physical fields, setting calculation domains and boundary conditions of the physical fields, coupling the physical fields, and meshing the simulation analysis model; s3, adding transient research, carrying out numerical solution on the simulation analysis model, and carrying out post-processing on a solution result to obtain the temperature and humidity distribution condition inside the switch cabinet; S4, measuring the temperature and the humidity of the switch cabinet in actual operation through a temperature rise test, comparing with a simulation solving result, and optimizing a simulation analysis model; S5, calculating electromagnetic loss distribution in the switch cabinet, using the calculated loss data to replace electromagnetic heat as heat source input, and introducing the heat source input into a non-isothermal flow field; S6, aiming at different working conditions, completing full-order simulation calculation under each working condition one by one, extracting corresponding temperature and humidity field distribution data, and constructing a physical field snapshot library for training a reduced-order model; S7, processing a physical field snapshot library based on an intrinsic orthogonal decomposition method, calculating a snapshot mean value, performing singular value decomposition after centering, extracting a mode and a mode coefficient, cutting off based on a preset energy threshold value and a maximum mode number, projecting a high-dimensional physical field to a low-dimensional mode coefficient space, and constructing a reduced-order model; S8, training a Kriging model by taking working condition characteristics as input and modal coefficients as output, reconstructing a temperature and humidity field of the switch cabinet, and carrying out model accuracy assessment by using a leave-one-out method; S9, analyzing the dynamic dew point temperature of each space node point by utilizing a Magnus equation, and performing coupling operation on the dynamic dew point temperature and the reconstructed temperature field to construct a condensation margin evaluation cloud picture; S10, acquiring real-time temperature and humidity and working condition parameters in the actual operation process of the switch cabinet, correcting a Kriging model by actual measurement data, reconstructing a global temperature and humidity field under the current working condition by the correction model, calculating the actual dynamic dew point temperature, generating an actual operation condensation margin cloud picture, and completing online real-time evaluation.
2. The switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction according to claim 1, wherein in the step S1, according to actual structural parameters of the switch cabinet, a geometric model of the original size of the switch cabinet is built by utilizing SolidWorks three-dimensional drawing software, and the geometric model comprises a current carrying bus, a current transformer, a circuit breaker, a switch cabinet shell, an insulator and a solid sealing pole, wherein the solid sealing pole is obtained by taking the insulating shell as a carrier, and encapsulating a vacuum arc extinguishing chamber and a moving/static contact of the circuit breaker into a whole, and a functional compartment of the bottom of the switch cabinet for accommodating the current transformer is a cable chamber; The geometric model is imported into COMSOL finite element simulation software, a current carrying bus is designated as copper material, a current transformer, an insulator and a solid sealing pole are designated as epoxy resin material, a moving contact and a static contact of a circuit breaker are designated as copper-chromium alloy material, a sleeve of a vacuum arc-extinguishing chamber of the circuit breaker is designated as aluminum oxide material, and a shell of a switch cabinet is designated as stainless steel material; in S2, the physical fields added include electric current physical fields, solid and fluid heat transfer physical fields, turbulent physical fields, and moisture transport physical fields in air.
3. The method for evaluating the condensation margin of a switch cabinet based on simulation analysis and reduced order reconstruction according to claim 2, wherein in the step S5, the electromagnetic loss is calculated by adding contact resistance to a contact surface and a bolt fastening surface, simulating local heating caused by the contact resistance, the bolt fastening surface is a contact surface between two conductive components clamped and fixed by bolts, and the contact resistance R is calculated by the following formula: ; wherein, K is a coefficient related to contact materials, m is a coefficient related to the contact form of two contact surfaces, the contact form comprises surface contact, line contact and point contact; The concentrated heat loss due to contact resistance directly follows the joule law: ; wherein P is concentrated heat loss power generated by contact resistance, I is working current flowing through the contact part; The calculation formula of the volumetric heat loss of the conductor body is as follows: ; In the formula, Heat loss power for the volume of the conductor unit; is the bus body resistivity; J is current density; unit volumes in the simulation analysis model; Total electromagnetic loss is P and And (3) summing.
4. The method for evaluating the condensation margin of the switch cabinet based on simulation analysis and reduced order reconstruction according to claim 1, wherein in the step S6, the working condition parameters of each working condition comprise load current, ambient temperature and relative humidity, the simulation calculation is performed by inputting different working condition parameters, the snapshot of the temperature and humidity field under each working condition is extracted, and a physical field snapshot library is constructed.
5. The method for evaluating the condensation margin of a switch cabinet based on simulation analysis and reduced order reconstruction according to claim 1, wherein in the step S7, the method is characterized in that the method is cut off based on a preset energy threshold and a maximum mode number, only the first r dominant modes with high energy occupation are reserved, a high-dimensional physical field is projected to a low-dimensional mode coefficient space, a reduced order model is constructed, and the high-dimensional physical field is three-dimensional space distribution data of a temperature and humidity field in the switch cabinet obtained through full-order simulation.
6. The method for evaluating the condensation margin of the switch cabinet based on simulation analysis and reduced order reconstruction according to claim 1, wherein in the step S8, a Kriging model is constructed, the input characteristics of working conditions are taken as independent variables, the modal coefficient of an intrinsic orthogonal decomposition method is taken as dependent variables, a Gaussian process regression model is trained, the modal coefficient of a new working condition is predicted, and the corresponding temperature and humidity field is obtained through reconstruction, wherein the Gaussian process regression model adopts Matern kernel functions, and the optimized restarting times are set to be 15 times.
7. The switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction according to claim 1 is characterized in that in the step S8, a leave-one-method cross-validation assessment model precision is adopted, namely samples of one working condition are removed each time, a Kriging model is retrained by using the rest samples, the temperature and humidity field distribution of the removed working condition is predicted, the whole-field relative error is calculated, after all working conditions are traversed, an average value of the errors is taken as a model generalization error, and if the model generalization error is smaller than a set error threshold, the Kriging model is considered to meet the precision requirement.
8. The method for evaluating the condensation margin of the switch cabinet based on simulation analysis and reduced order reconstruction according to claim 2 is characterized in that in the step S9, dynamic dew point temperatures of all the space nodes are calculated point by adopting a Magnus equation based on global temperature and humidity high-dimensional grid data in the switch cabinet in a temperature and humidity field of the switch cabinet obtained through reconstruction, the dynamic dew point temperatures and the reconstructed temperature field data of the corresponding space nodes are subjected to coupling calculation to obtain condensation margin values of all the space nodes, the condensation margin values are temperature differences between wall temperatures and dew point temperatures of the corresponding space nodes, a global condensation margin evaluation cloud chart is generated according to the condensation margin values of all the space nodes, and a condensation risk area in the switch cabinet is determined according to a condensation margin distribution result.
9. The method for evaluating the condensation margin of the switch cabinet based on the simulation analysis and the reduced order reconstruction according to claim 8, wherein in the step S10, the condensation risk area is determined based on the condensation critical node, and the reliability rating is performed on the condensation risk area, specifically: Based on an intrinsic orthogonal decomposition method, respectively extracting a temperature field dominant mode and a humidity field dominant mode, and calculating contribution factors of each mode to the condensation margin gradient, wherein the contribution factors are defined as the condensation margin change rate caused by mode coefficient change; According to condensation risk grades of different functional compartments of the switch cabinet, dynamically adjusting weight coefficients of a temperature field mode and a humidity field mode, namely, for a breaker chamber and a bus chamber, increasing the weight of the temperature field mode, and reducing the weight of the humidity field mode; reconstructing a temperature and humidity field of the switch cabinet again based on the weighted cross physical field mode, calculating a dynamic dew point temperature by adopting a magnus equation, and marking a space node as a condensation critical node when the difference between the wall temperature and the dew point temperature of the space node is less than 2 ℃; Carrying out spatial cluster analysis on the condensation critical nodes, identifying the geometric center and the influence range of the condensation risk area, and setting definition rules of the condensation risk area to be that each cluster of the condensation critical nodes obtained by the spatial cluster analysis is defined as an independent condensation risk area if the number of the nodes in the cluster is not less than 5; And outputting the credibility rating of the condensation risk area by using the prediction variance of the Kriging model, and outputting a processing suggestion based on the credibility rating.
10. The switchgear condensation margin assessment method based on simulation analysis and reduced order reconstruction of claim 9, wherein the division criteria of the credibility rating are: high reliability Kriging model prediction standard deviation at condensation critical node And dew margin value The ratio of (2) satisfies If the proportion of the number of condensation critical nodes in the condensation risk area to the total node number in the area exceeds 80%, judging that the condensation risk area is high in reliability, and immediately starting the heating and dehumidifying device; The credibility of the method meets the following conditions Or the proportion of the number of condensation critical nodes in the condensation risk area to the total node number of the area is 50% -80%, the condensation risk area is judged to be medium credibility, and a heating and dehumidifying device is recommended to be started and the condensation risk area is manually verified; low credibility of meeting Or the proportion of the number of condensation critical nodes in the condensation risk area to the total node number of the area is lower than 50%, determining that the reliability is low, suggesting that active dehumidification is not started temporarily, and increasing the monitoring frequency.

Description

Switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction Technical Field The invention belongs to the technical field of simulation analysis, and particularly relates to a switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction. Background In modern power systems, the high-voltage switch cabinet bears the functions of circuit on-off, control and protection core, and the operation stability of the high-voltage switch cabinet is directly related to the safety of the power grid. The accurate acquisition of the temperature and humidity distribution in the cabinet is an important basis for equipment optimization design, defect early warning and running state evaluation. The current industry generally adopts multi-physical field full-order simulation to carry out analysis, so that the internal field quantity distribution under the electromagnetic, thermal and wet coupling effect can be truly restored, and a quantitative basis is provided for the design and operation and maintenance of the switch cabinet. Taking KYN28A series switch cabinets commonly used in engineering as an example, the interior of the switch cabinet comprises multiple components such as a bus, a contact, a mutual inductor, an insulator, a solid sealing pole and the like, the structure is compact, the space is complex, mass grids are required to be divided in simulation modeling, meanwhile, the current field, heat transfer, turbulent flow and water delivery are subjected to multi-physical field intensity coupling iteration, the solution convergence is slow, the calculation resource consumption is high, the single simulation time is long, the quick diagnosis, the online inversion and the real-time evaluation of an engineering site cannot be supported, and an efficient reduced-order calculation method is needed to realize the quick reconstruction of a temperature and humidity field. Disclosure of Invention According to the defects in the prior art, the invention aims to provide the switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction, which can realize efficient and accurate reconstruction of a temperature and humidity field in the switch cabinet and efficient assessment of the switch cabinet condensation margin based on limited boundary monitoring data. In order to achieve the above purpose, the invention provides a switch cabinet condensation margin assessment method based on simulation analysis and reduced order reconstruction, which comprises the following steps: S1, for a medium-high voltage switch cabinet, establishing a geometric model of the switch cabinet and importing the geometric model into finite element simulation software to obtain a simulation analysis model, and setting material properties of each part; S2, adding physical fields, setting calculation domains and boundary conditions of the physical fields, coupling the physical fields, and meshing the simulation analysis model; s3, adding transient research, carrying out numerical solution on the simulation analysis model, and carrying out post-processing on a solution result to obtain the temperature and humidity distribution condition inside the switch cabinet; S4, measuring the temperature and the humidity of the switch cabinet in actual operation through a temperature rise test, comparing with a simulation solving result, and optimizing a simulation analysis model; S5, calculating electromagnetic loss distribution in the switch cabinet, using the calculated loss data to replace electromagnetic heat as heat source input, and introducing the heat source input into a non-isothermal flow field; S6, aiming at different working conditions, completing full-order simulation calculation under each working condition one by one, extracting corresponding temperature and humidity field distribution data, and constructing a physical field snapshot library for training a reduced-order model; S7, processing a physical field snapshot library based on an intrinsic orthogonal decomposition method, calculating a snapshot mean value, performing singular value decomposition after centering, extracting a mode and a mode coefficient, cutting off based on a preset energy threshold value and a maximum mode number, projecting a high-dimensional physical field to a low-dimensional mode coefficient space, and constructing a reduced-order model; S8, training a Kriging model by taking working condition characteristics as input and modal coefficients as output, reconstructing a temperature and humidity field of the switch cabinet, and carrying out model accuracy assessment by using a leave-one-out method; S9, analyzing the dynamic dew point temperature of each space node point by utilizing a Magnus equation, and performing coupling operation on the dynamic dew point temperature and the reconstructed temperature field to construct a c