WO2024088446A1 - Acquisition method for arrangement of graphene pi heating films, and heating and thermal insulation device - Google Patents

Abstract

An acquisition method for an arrangement of graphene PI heating films, and a heating and thermal insulation device. The method comprises: establishing a parametric model of a heating and thermal insulation device for an SF₆ tank circuit breaker tank body; calling the established parametric model to simulate a transient heating process in view of set input variables; analyzing the sensitivities of the input variables to a gas temperature and a flow velocity of SF₆, and screening key input variables from the input variables according to the sensitivity analysis; constructing a test parameter set according to a set experimental design method and the screened key input variables; constructing a response surface model in view of a response surface construction method set by the test parameter set; and performing iterative optimization on the screened key input variables by means of the constructed response surface model and in view of a set optimization algorithm, so as to obtain optimized input variables, and arranging graphene PI heating films by using the optimized input variables.

Description

Arrangement acquisition method of graphene PI heating sheet and heating and heat preservation device

This application claims priority to the Chinese patent application filed with the China Patent Office on October 26, 2022, with application number 202211318376.8, the entire contents of which are incorporated by reference into this application.

Technical Field

The present application relates to the technical field of high-voltage power supply equipment, for example, to a method for arranging and obtaining a graphene polyimide (PI) heating sheet and a heating and heat preservation device.

Background technique

Sulfur hexafluoride (SF ₆ ) tank circuit breakers have been widely used in ultra-high voltage and large-capacity power systems, with advantages such as excellent arc extinguishing performance, reliable operation and long-term maintenance-free. The gas chamber of the SF ₆ tank circuit breaker is exposed to the atmosphere. For most SF ₆ tank circuit breakers currently operating in the power grid, when the ambient temperature is lower than -27.5℃, the SF ₆ gas will liquefy, and the pressure of the SF ₆ tank circuit breaker gas chamber will drop sharply, causing the circuit breaker alarm, and even pressure lock, circuit breaker over-tripping, etc., which seriously affects the stable operation of the power grid.

The current _SF6 tank circuit breaker tank heating and insulation device usually uses traditional nickel-chromium alloy resistors for heating. The structural schematic diagram of the nickel-chromium alloy resistor is shown in Figure 1. The nickel-chromium alloy resistor 1 needs to be coated with a silicone rubber film 2 on both sides, which reduces the thermal efficiency of the nickel-chromium alloy resistor 1; the series characteristics of the nickel-chromium alloy resistor 1 may cause it to be partially melted after a period of use, resulting in the need to replace the entire heating plate, which has a short life and causes waste of materials, and may bring safety hazards and economic losses; the cutting of nickel-chromium alloy needs to be carried out by chemical etching, which is not environmentally friendly, and its cutting design and layout are limited by its series characteristics, which will further cause waste of materials.

Summary of the invention

The present application provides a method for obtaining an arrangement of a graphene PI heating sheet, so that the graphene PI heating sheet can be applied to the heating and heat preservation of a SF ₆ tank circuit breaker tank after reasonable arrangement.

In a first aspect, an embodiment of the present application provides a method for obtaining the arrangement of a graphene PI heating sheet, comprising: establishing a parameterized model of a heating and heat preservation device for a tank body of an _SF6 tank circuit breaker; calling the established parameterized model in combination with set input variables to perform transient heating process simulation; performing sensitivity analysis of the input variables to the gas temperature and flow velocity of _SF6 , and screening out key input variables from the input variables based on the sensitivity analysis; constructing an experimental parameter set according to a set experimental design method and the screened out key input variables; constructing a response surface model in combination with the experimental parameter set and a set response surface construction method; iteratively optimizing the screened out key input variables through the constructed response surface model in combination with a set optimization algorithm to obtain optimized input variables, and using the optimized input variables to arrange the graphene PI heating sheet.

Optionally, the input variables include the length, width and adjacent graphene PI heating sheet. The spacing between the graphene PI heating sheets. Optionally, in the case of the sensitivity analysis, the arrangement center point of the graphene PI heating sheet and the center point of the pole top of the _SF6 tank circuit breaker are used as variable reference points to extract the gas temperature and flow velocity of _SF6 at the arrangement center point and the gas temperature and flow velocity of _SF6 at the center point of the pole top.

Optionally, the sensitivity analysis is performed using the Spearman rank correlation coefficient method.

Optionally, after arranging the graphene PI heating sheet using the optimized input variables, the method further includes: simulating the transient heating process in combination with the parameterized model to verify the arranged graphene PI heating sheet.

Optionally, screening, multi-objective genetic algorithm (MOGA), non-linear Lagrangian quadratic programming (NLPQL), or mixed-integer sequential quadratic programming (MISQP) optimization method is used to iteratively optimize the selected key input variables.

In a second aspect, an embodiment of the present application provides a heating and heat preservation device, comprising a tank insulation shell, a heat preservation layer and a heating layer arranged in sequence from the outside to the inside, wherein the heating layer is composed of a plurality of graphene PI heating sheets connected in parallel, and the plurality of graphene PI heating sheets are arranged using the arrangement and acquisition method of the graphene PI heating sheets described in the first aspect and attached and fixed on the outer surface of the tank body of the _SF6 tank circuit breaker.

Optionally, the insulation layer is made of EPDM (Ethylene Propylene Diene Monomer) foam rubber.

Optionally, the tank insulation shell is composed of at least two shell parts that are detachably connected.

Optionally, the heating and insulation device also includes a temperature sensor, a temperature controller and a contactor; wherein the temperature sensor is installed at the top of the pole, the temperature sensor is connected to the temperature controller, and the contactor is installed in the power supply circuit of the multiple graphene PI heating plates and is connected to the temperature controller.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of the distribution of nickel-chromium alloy resistors of a SF ₆ tank circuit breaker in the related art;

FIG2 is a flow chart of the method of Example 1 of the present application;

FIG3 is a schematic diagram of the workflow of the method of Example 1 of the present application;

FIG4 is a schematic diagram of input variable extraction in Example 1 of the present application;

FIG5 is a schematic diagram of grid division in Example 1 of the present application;

FIG6 is a schematic diagram of constructing a response surface model according to Example 1 of the present application;

FIG7 is a second schematic diagram of constructing a response surface model in Example 1 of the present application;

FIG8 is a schematic diagram of the heating effect before optimization;

FIG9 is a diagram showing the heating effect of the arrangement scheme obtained by the method of Example 1 of the present application;

FIG10 is a schematic diagram of the overall structure of Example 2 of the present application;

Among them, 1. nickel-chromium alloy resistor, 2. silicone rubber membrane, 3. heating layer, 4. insulation layer, 5. tank insulation shell, 51. shell, 6. pole, 7. bracket, 8. control box, 9. temperature controller, 10. contactor, 11. temperature sensor, 12. copper electrode, 13. graphene PI heating sheet.

Detailed ways

The application of graphene PI film heating sheets to the heating of SF ₆ tank circuit breaker tanks can solve the technical defects of heating with nickel-chromium alloy resistor sheets. The present application arranges the graphene PI film heating sheets that are heated in parallel and can be cut arbitrarily and applies them to the heating of SF ₆ tank circuit breaker tanks.

Example 1

This embodiment provides a method for obtaining the arrangement of a graphene PI heating sheet, as shown in FIG. 2-3 , and includes the following steps.

Step S1: establishing a parameterized model of a heating and heat preservation device for a tank of a _SF6 tank circuit breaker.

In this embodiment, a parametric model of a heating and heat preservation device for a tank body of a _SF6 tank circuit breaker is established by coupling Solidworks with Workbench. The modeling is performed by a parametric modeling module of Design Modeler. The modeling method may be a method in the related art, which will not be described here.

Step S2: Perform parameter sensitivity analysis.

In this embodiment, as shown in Figure 4, the widths of three types of graphene PI heating sheets are extracted, which are P1, P2, and P3, respectively, and the spacings between adjacent graphene PI heating sheets are extracted, which are P4, P5, and P6, respectively. After the input variables are extracted, they are stored in the parameter manager.

In this embodiment, a total of 6 parameters, namely, P1, P2, P3, P4, P5, and P6, are selected as input variables in the parameter manager of the Workbench platform. The values of multiple groups of input variables are manually set and stored in the parameter manager. The transient heating process is simulated according to the set initial experimental design method. The gas temperature P7 of _SF6 at the center point of the pole top and the gas temperature P8 of _SF6 at the center point of the arrangement are extracted, and the average gas temperature P9 of the middle section of _SF6 is extracted. The parameter P10 is set to the difference between the gas temperature of _SF6 at the center point of the arrangement and the gas temperature of _SF6 at the center point of the pole top. Expression (2) is as follows.

P10＝P8-P7      (2)

The number of samples required to construct the response surface will increase significantly with the number of input parameters, which will greatly increase the computational cost. Therefore, a sensitivity analysis of the input variables to the gas temperature and flow velocity of SF ₆ is performed, and the input variables are screened based on the sensitivity analysis. In the parameter correlation sensitivity analysis module, the spearman rank correlation coefficient method is used to perform a sensitivity analysis of the input variables to the gas temperature and flow velocity of SF ₆ , and the input variables are sorted by correlation and screened.

In this embodiment, the parameters P1, P2, and P3 (three different specifications of heating plate widths) are not sensitive to the changes of the four output variables P7, P8, P9, and P10, so three parameters P4, P5, and P6 are selected as the parameters after screening. The key input variables.

The method for obtaining the gas temperature and flow velocity of _SF6 under different input variables through transient heating process simulation is:

Step a: Use the Mechanical module to mesh the parameterized model constructed in step 1. The model is meshed using tetrahedral meshing. The mesh type is set to Computational Fluid Dynamics (CFD) mesh. The overall mesh size is 30 mm, and the local mesh size of 7 mm is used for the PI heating plate. The meshing diagram is shown in Figure 5.

Step b: setting boundary conditions of the thermal flow analysis model of the heating and insulation device for the tank of the _SF6 tank circuit breaker;

In this embodiment, the boundary conditions of the heat flow model are set by combining the input variables with the Fluent fluid analysis software on the Workbench platform. The heat source power of the PI heater is determined by formula (1), where the square resistance R _C =120Ω.

Open the energy equation Engel option, select the viscosity realizable k-ε equation, and use the body force weighted pressure equation on the calculation method panel to ensure the natural convection state of _SF6 .

Step c: Setting the thermal flow analysis solver of the heating and insulation device for the tank of the _SF6 tank circuit breaker;

The transient heat flow solution method was selected to monitor the average temperature of the gas inside the tank, the gas temperature of _SF6 at the center of the arrangement, and the gas temperature of _SF6 at the center of the top of the pole. The solution time was set to 1800s, and the model was solved to obtain the gas flow rate and temperature distribution of _SF6 in the circuit breaker tank under different input variables.

Step S3: Design the experimental group and complete the experimental parameter set for building the response model.

Select Central Composite Design or Optimal Space-Filling Design or Box-Behnken Design or Sparse Grid Initialization or Latin Hypercube Sampling Design as the set experimental design method and complete the experimental group design.

In this embodiment, the design exploration module of the Workbench platform is used to perform experimental design. Since the geometric parameters of the PI heating plate are continuous variables, the Central Composite Design design method is selected as the optimized experimental design method. The parameter variation range of the selected input parameters is 30%, and 45 groups of experimental parameters corresponding to the screened input variables are manually set according to the size of the tank and stored in the parameter manager.

Step S4: construct a response surface model (RSM) by combining the experimental parameters corresponding to the 45 groups of screened input variables obtained in step S3 with the response surface algorithm;

Select Genetic Aggregation or Standard Response Surface or Kriging or Non-Parametric Regression or Neural Network or Parse Grid response surface construction method to complete the response surface The model can be constructed by using the method in the relevant technology, and its steps will not be described here.

In this embodiment, according to the experimental parameter set constructed in step S3, the Kriging response surface construction method is selected to complete the construction of the response surface model. Kriging is a multidimensional interpolation technology suitable for highly nonlinear complex engineering optimization problems. The function expression is as shown in formula (3):

Where: The sample prediction value is the estimated value of the basis function coefficient in the model. is the estimated value of the basis function coefficient in the model, f(x) is the polynomial function about x, r ^T (x _x ) is the correlation vector between the sample point and the prediction point, R is the correlation matrix, y is the column vector composed of the response values of the sample point data, F is the unit column vector, and the resulting response surface is shown in Figures 6 and 7. The response surface constructed in Figure 6 is a fitting surface of the size of the graphene PI heating sheet and the average gas temperature P9 of SF ₆ in the middle section, and the response surface constructed in Figure 7 is a fitting surface of the size of the graphene PI heating sheet and the difference P10 between the gas temperature of SF ₆ at the center of the arrangement and the gas temperature of SF ₆ at the center of the pole top. The construction method can be the method in the relevant technology, and the process is not described here.

Step S5: Using the response surface model constructed in step S4, combined with the input variables screened out in step S3, select an optimization algorithm such as Screening or MOGA or NLPQL or MISQP to perform optimal iterative solution of the input variables, obtain optimized input variable parameters, and finally obtain the optimal arrangement scheme of the graphene PI heating sheet.

In the embodiment, the response surface model constructed in step S4 is used, combined with the input variables screened in step S3, and the MOGA optimization algorithm is selected to perform the optimal iterative solution of the input variables, and the optimized input variable parameters are obtained, and finally three groups of optimized graphene PI heating sheet arrangement schemes are obtained, as shown in Table 1. The optimization target expression of the multi-objective optimization in this step is as shown in formula (4), and the constructed objective function requires that the difference P10 between the gas temperature at the center point of the arrangement and the gas temperature at the center point of the pole top is less than 35K, and the gas temperature P7 of _SF6 at the center point of the pole top is greater than 258K, and the maximum value of the average gas temperature P9 of the middle section of _SF6 is sought, but less than 273K.

Table 1

Step S6: After obtaining the optimal arrangement scheme of the graphene PI heating sheet, according to the obtained optimal arrangement scheme, the established parameterized model is called again to perform transient heating process simulation analysis to verify the effect of the arrangement scheme, wherein the effect of the scheme before optimization is shown in FIG8 , and the effect of the method of this embodiment is shown in FIG9 . The scheme before optimization is that two graphene PI heating sheets wrap the tank body, covering the entire outer surface of the tank body.

As shown in Figures 8-9, the arrangement method of the pre-optimization scheme is used to heat the tank body of the _SF6 tank circuit breaker, resulting in uneven temperature distribution of the tank body and poor thermal insulation performance of the tank body. The arrangement method of the graphene PI heating sheet of this embodiment is used to heat the tank body of the _SF6 tank circuit breaker. The heating effect is better, and the maximum temperature difference is reduced from 39K to 15K, so that the overall temperature distribution of the tank body is more uniform, the overall power consumption is smaller, and there is a better thermal insulation effect.

By adopting the method of this embodiment, a response surface model is constructed, and in combination with the screened input variables, the optimal arrangement scheme of the graphene PI heating sheet is obtained through an optimization algorithm, which can achieve a better heating effect while minimizing the use of materials, improve energy and material utilization, and solve the problem of how to arrange the graphene PI heating sheet in the _SF6 tank circuit breaker tank heating and insulation device. At the same time, through sensitivity analysis, input variables with higher sensitivity are selected as input parameters to construct a response surface model, which reduces the amount of calculation, thereby greatly reducing the calculation cost.

Example 2

The present embodiment provides a heating and heat-insulating device, as shown in FIG10 , comprising a heating layer 3, a heat-insulating layer 4 and a tank heat-insulating shell 5 which are sequentially arranged from the inside to the outside, wherein the heating layer 3 is attached and fixed to the tank of the SF ₆ tank circuit breaker, the heat-insulating layer 4 covers the tank of the SF ₆ tank circuit breaker to which the heating layer 3 is attached, and the tank heat-insulating shell 5 is sleeved on the outer periphery of the tank of the SF ₆ tank circuit breaker.

The heating layer 3 is composed of a plurality of graphene PI heating sheets 13, and the copper electrode 12 is connected to the graphene PI heating sheet 13 by a pressing method. The connection method between the graphene PI heating sheet 13 and the copper electrode 12 can be adopted in the relevant technology. The arrangement scheme of the plurality of graphene PI heating sheets 13 is obtained by the method of Example 1, and the plurality of graphene PI heating sheets 13 are arranged in parallel in the circuit, and the power cable thereof passes through the tank insulation shell 5 and is connected to the power supply through the contactor 10 included in the heating and heat preservation device.

The thermal insulation layer 4 is made of EPDM foam rubber.

The tank body heat-insulating outer shell 5 is composed of at least two shell parts 51 that are detachably connected. In this embodiment, the tank body heat-insulating outer shell 5 is composed of at least two shell parts 51 fixed by bolts.

This structural form cleverly solves the structural limitations of gas insulated substation (GIS) such as small spacing between switch devices and insufficient installation space.

The heating and heat preservation device also includes a temperature sensor 11, a temperature controller 9 and a contactor 10. The temperature sensor 11 is installed at the top of the pole 6 of the _SF6 tank circuit breaker, the temperature sensor 11 is connected to the temperature controller 9, and the temperature controller 9 is connected to the control system installed in the control box 8.

The temperature sensor 11 can collect temperature information and transmit it to the temperature controller 9. The contactor 10 is connected, and the start and stop of the graphene PI heating sheet can be controlled through the contactor 10 according to the collected temperature information.

Under the control of the temperature controller 9, automatic disconnection and shutdown are realized on site, and centralized control is realized in component management, which is convenient for user monitoring and operation.

The start contactor 10 can automatically disconnect and shut down the power supply of the tank heating layer 3; the start contactor 10 mainly starts the heater and sends a heater operation indication signal. This device can realize centralized monitoring of tank insulation.

The heating and heat preservation device of this embodiment is used on the SF ₆ tank circuit breaker, and multiple graphene PI heating sheets 13 are attached and fixed on the outer surface of the tank body of the SF ₆ tank circuit breaker, and the tank body heat preservation shell 5 is sleeved on the tank body of the SF ₆ tank circuit breaker; the tank body of the SF ₆ tank circuit breaker is fixed by a bracket 7, and the temperature sensor 11 is installed on the top of the pole 6 of the SF ₆ tank circuit breaker. The SF ₆ tank circuit breaker is installed with a current transformer and a gas-filled sleeve; the junction box of the heating and heat preservation device is connected to the control box 8 of the SF ₆ tank circuit breaker, and the control system in the control box 8 is configured to control the heating temperature of the heating layer 3. The relevant electric control components of the heat preservation and heating device are connected to the control box through cables.

The heating and heat preservation device of this embodiment utilizes graphene PI heating sheets for heating and is arranged according to the best arrangement scheme, which has better heat conduction efficiency and stability, is more energy-saving and environmentally friendly, thereby making the switch equipment more reliable, effectively reducing the potential safety hazards of the equipment, and increasing the economy of equipment operation.

Claims (10)

1. A method for arranging and obtaining a graphene polyimide PI heating sheet, comprising:

   Establish a parametric model of the heating and insulation device for the sulfur hexafluoride _SF6 tank circuit breaker tank;

   Calling the established parameterized model and combining it with the set input variables to simulate the transient heating process;

   Performing a sensitivity analysis of the input variables to the gas temperature and flow velocity of _SF6 , and selecting key input variables from the input variables according to the sensitivity analysis;

   Construct the test parameter set according to the set experimental design method and the selected key input variables;

   Constructing a response surface model by combining the experimental parameter set and the set response surface construction method;

   The constructed response surface model is combined with a set optimization algorithm to iteratively optimize the selected key input variables to obtain optimized input variables, and the optimized input variables are used to arrange the graphene PI heating sheet.
2. The method of claim 1, wherein the input variables include the length and width of the graphene PI heating sheet and the spacing between adjacent graphene PI heating sheets.
3. The method of claim 1, wherein, in the case of performing the sensitivity analysis, the arrangement center point of the graphene PI heater sheet and the pole top center point of the _SF6 tank circuit breaker are used as variable reference points, and the gas temperature and flow velocity of _SF6 at the arrangement center point and the gas temperature and flow velocity of _SF6 at the pole top center point are extracted.
4. The method according to claim 1, wherein the sensitivity analysis is performed using the Spearman rank correlation coefficient method.
5. The method according to claim 1, after arranging the graphene PI heater sheet using the optimized input variables, further comprising:

   The transient heating process is simulated in combination with the parameterized model to verify the arranged graphene PI heating sheet.
6. The method as claimed in claim 1, wherein the selected key input variables are iteratively optimized using screening or multi-objective genetic algorithm MOGA or Lagrangian nonlinear quadratic programming NLPQL or mixed integer sequence quadratic programming MISQP optimization method.
7. A heating and heat-insulating device comprises a heating layer, a heat-insulating layer and a tank heat-insulating shell which are sequentially arranged on a tank body of an _SF6 tank circuit breaker from the inside to the outside, wherein the heating layer is composed of a plurality of graphene polyimide PI heating sheets connected in parallel, and the plurality of graphene PI heating sheets are arranged by the arrangement and acquisition method of the graphene PI heating sheets according to any one of claims 1 to 6 and attached and fixed on the outer surface of the tank body of the _SF6 tank circuit breaker.
8. The device as claimed in claim 7, wherein the insulation layer is made of EPDM foam rubber.
9. The device as claimed in claim 7, wherein the tank insulation shell is composed of at least two shell parts that are detachably connected.
10. The device as claimed in claim 7 further includes a temperature sensor, a temperature controller and a contactor; wherein the temperature sensor is installed at the top of the pole, the temperature sensor is connected to the temperature controller, and the contactor is installed in the power supply circuit of the multiple graphene PI heating plates and is connected to the temperature controller.