An optimization method and system for a solid-state electric heat storage device heat storage body chamber structure

Abstract

The application discloses a kind of solid electric heat storage device heat storage body chamber structure optimization method and system.The optimization method of the present application includes: the parameterization modeling of heat storage body chamber structure, obtain simulation model;Simulation model grid division;The flow field distribution simulation of heat storage body fluid region, the simulated parameters include the air flow rate of inlet air inlet position, the absolute pressure of outlet air outlet position, the difference of flow rate and average flow rate of each heat exchange channel and velocity standard deviation S1, the pressure difference Δp of inlet air and outlet air;Set response surface, select response surface optimization method, set the variation interval of each variable parameter;Simulation optimization: set velocity standard deviation S1 minimum and the pressure difference Δp minimum of inlet air and outlet air as objective function, select genetic optimization method.The heat storage body chamber structure of the present application is optimized, the floor area of heat storage body chamber structure is reduced, the fluid uniformity of each heat exchange channel of heat storage body is improved, so as to improve the heat storage and release performance of heat storage body.

Description

Technical Field

[0001] This invention belongs to the field of solid-state electric thermal energy storage technology, and relates to a method and system for optimizing the structure of the thermal storage chamber of a solid-state electric thermal energy storage device. Background Technology

[0002] Currently, electric thermal energy storage technology has been widely used. Solid-state electric thermal storage devices use off-peak electricity for heating, converting electrical energy into thermal energy for storage, and outputting heat through heat exchange equipment during the heat usage period.

[0003] As the core of a solid-state electric thermal energy storage device, the heat storage body has a large number of heat exchange channels inside. However, the existing heat storage body chamber structure design is unreasonable, with defects such as large footprint and uneven air flow in the heat exchange channels, which leads to poor heat storage and release performance of the heat storage body. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the defects of the prior art and provide a method and system for optimizing the structure of the heat storage chamber of a solid electric heat storage device, so as to optimize the structure of the heat storage chamber, reduce the floor area of ​​the heat storage chamber, improve the fluid uniformity of each heat exchange channel of the heat storage body, and thus improve the heat storage and release performance of the heat storage body.

[0005] Therefore, the present invention adopts the following technical solution: a method for optimizing the structure of the heat storage chamber of a solid electric heat storage device, comprising:

[0006] Step S1: Parametric modeling of the heat storage chamber structure to obtain the simulation model;

[0007] Step S2, simulation model mesh generation: all models are generated using a structured mesh generation method, defining the number of meshes per unit distance and outputting the mesh file;

[0008] Step S3: Simulate the flow field distribution in the heat storage fluid region. The simulation parameters include the air velocity at the air inlet, the absolute pressure at the air outlet, the difference between the velocity and the average velocity in each heat exchange channel and the velocity standard deviation S1, and the pressure difference Δp between the air inlet and the air outlet.

[0009] Step S4: Set the response surface, select the response surface optimization method, and set the variation range for each variable parameter;

[0010] Step S5, Simulation Optimization: Set the minimum speed standard deviation S1 and the minimum pressure difference Δp between the air inlet and outlet as the objective functions. Select the genetic optimization method, obtain the operating points according to the DOE (Design of Experiments) experimental design method, calculate and output the simulation optimization results of each operating point.

[0011] Furthermore, in step S1, the parameters of the heat storage chamber structure include the length InL and width InW of the air inlet, the width InCW of the air inlet chamber and the width OutCW of the air outlet chamber, and the length OutL and width OutW of the air outlet.

[0012] Furthermore, in step S1, the simulation model file is in the format of *.iges, *.x_t, or *.step.

[0013] Furthermore, in step S2, the number of grids includes the number of grids in the length, width, and depth directions of each geometry.

[0014] Furthermore, in step S2, the mesh file is in the format *.msh.

[0015] Furthermore, in step S3, the heat transfer process in the fluid region of the heat storage body is described by the mass conservation and momentum conservation equations of the fluid.

[0016] Furthermore, in step S3, the mass conservation equation is:

[0017]

[0018] In the formula: ρ is the fluid density, kg / m³ 3 t represents time, in seconds; The velocity is m / s; To express differentiation;

[0019] Momentum conservation equation:

[0020]

[0021] In the formula: μ is the dynamic viscosity, in Pa·s; P is the fluid pressure, in Pa; g is the acceleration due to gravity, in m / s². 2 .

[0022] Furthermore, in step S3, the air inlet is located at the velocity boundary inlet, and the turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hin = 2 × InL × InW ÷ (InL + InW), and the turbulence intensity is set to 5%.

[0023] The air outlet is located at the pressure boundary outlet. The turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hout = 2 × OutL × OutW ÷ (OutL + OutW), and the turbulence intensity is set to 5%.

[0024] Furthermore, in step S3, the average flow rate of the heat exchange channel of the heat storage body... The expression is:

[0025]

[0026] Where: M is the total flow rate at the air inlet, in kg / s;

[0027] n is the total number of heat exchange channels;

[0028] The expression for the standard deviation of flow rate σ is:

[0029]

[0030] Where: m i The flow rate of the i-th heat exchange channel is expressed in kg / s.

[0031] The expression for the pressure difference Δp between the air inlet and outlet is:

[0032] Δp=p in -p out

[0033] In the formula, p in p represents the absolute pressure at the air inlet, in Pa. out This represents the absolute pressure at the air outlet, measured in Pa.

[0034] Furthermore, in step S3, the number of heat exchange channels is greater than 20.

[0035] Another technical solution adopted in this invention is: a system for optimizing the structure of the heat storage chamber of a solid-state electric heat storage device, comprising:

[0036] Simulation model acquisition unit: Parametric modeling of the heat storage chamber structure to obtain the simulation model;

[0037] Simulation model mesh generation: All meshes are generated using a structured meshing method, defining the number of meshes per unit distance, and outputting a mesh file;

[0038] Flow field distribution simulation unit: Flow field distribution simulation of the fluid region of the heat storage body. The simulation parameters include the air velocity at the air inlet, the absolute pressure at the air outlet, the difference between the velocity and the average velocity of each heat exchange channel and the velocity standard deviation S1, and the pressure difference Δp between the air inlet and the air outlet.

[0039] Response surface setting unit: Set the response surface, select the response surface optimization method, and set the variation range of each variable parameter;

[0040] Simulation optimization unit: The objective functions are set as minimizing the speed standard deviation S1 and minimizing the pressure difference Δp between the air inlet and outlet. The genetic optimization method is selected, and the operating points are obtained according to the DOE experimental design method. The simulation optimization results of each operating point are calculated and output.

[0041] This invention proposes a modeling method and system for optimizing the structure of a heat storage chamber. By utilizing the workbench platform of ANSYS software, the fluid uniformity of each heat exchange channel of the heat storage body can be improved, and the floor space of the heat storage chamber structure can be reduced, thereby improving the heat storage and release performance of the heat storage body. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of the heat storage chamber structure optimization method of the present invention;

[0044] Figure 2 This is a schematic diagram of the heat storage chamber structure of the present invention;

[0045] Figure 3 This is a graph showing the relationship between the inlet cavity width W1 and the standard deviation of the heat exchange channel velocity in this invention.

[0046] Figure 4 This is a graph showing the relationship between the velocity standard deviation and the air inlet size response surface of the present invention.

[0047] Figure 5 This is a graph showing the relationship between the oral cavity width W2 and the standard deviation of velocity in this invention;

[0048] Figure 6 This is a graph showing the relationship between the speed standard deviation and OutW in this invention.

[0049] Figure 7 This is a graph showing the relationship between the speed standard deviation and OutL in this invention.

[0050] Figure 8 This is a block diagram of the thermal storage chamber structure optimization system of the present invention. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] Example 1

[0053] This embodiment provides a method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device, such as... Figure 1 As shown, the steps are as follows:

[0054] Step S1: Parametric modeling of the heat storage chamber structure to obtain the simulation model;

[0055] Step S2, simulation model mesh generation: all models are generated using a structured mesh generation method, defining the number of meshes per unit distance, and outputting a mesh file in *.msh format;

[0056] Step S3: Simulate the flow field distribution in the heat storage fluid region. The simulation parameters include the air velocity at the air inlet, the absolute pressure at the air outlet, the difference between the velocity and the average velocity in each heat exchange channel and the velocity standard deviation S1, and the pressure difference Δp between the air inlet and the air outlet.

[0057] Step S4: Set the response surface, select the response surface optimization method, and set the variation range for each variable parameter;

[0058] Step S5, Simulation Optimization: Set the minimum speed standard deviation S1 and the minimum pressure difference Δp between the air inlet and outlet as the objective functions. Select the genetic optimization method, obtain the operating points according to the DOE experimental design method, calculate and output the simulation optimization results of each operating point.

[0059] In step S1, the model file format is *.iges, *.x_t, or *.step; the parameters of the heat storage chamber structure include the length InL and width InW of the air inlet, the width InCW of the air inlet chamber and the width OutCW of the air outlet chamber, and the length OutL and width OutW of the air outlet, such as... Figure 2 As shown.

[0060] In step S2, the number of meshes includes the number of meshes in the length, width, and depth directions of each geometry; the mesh file format is *.msh.

[0061] In step S3, the heat transfer process in the fluid region of the heat storage body is described by the mass conservation and momentum conservation equations of the fluid.

[0062] mass conservation equation:

[0063]

[0064] In the formula: ρ is the fluid density, kg / m³ 3 t represents time, in seconds; The velocity is m / s; To express differentiation;

[0065] Momentum conservation equation:

[0066]

[0067] In the formula: μ is the dynamic viscosity, in Pa·s; P is the fluid pressure, in Pa; g is the acceleration due to gravity, in m / s². 2 .

[0068] In step S3, the air inlet is located at the velocity boundary inlet, and the turbulence mode is selected by the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hin = 2 × InL × InW ÷ (InL + InW), and the turbulence intensity is set to 5%.

[0069] The air outlet is located at the pressure boundary outlet. The turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hout = 2 × OutL × OutW ÷ (OutL + OutW), and the turbulence intensity is set to 5%.

[0070] Average flow rate of heat exchange channels in heat storage body The expression is:

[0071]

[0072] Where: M is the total flow rate at the air inlet, in kg / s;

[0073] n is the total number of heat exchange channels;

[0074] The expression for the standard deviation of flow rate σ is:

[0075]

[0076] Where: m i The flow rate of the i-th heat exchange channel is expressed in kg / s.

[0077] The expression for the pressure difference Δp between the air inlet and outlet is:

[0078] Δp=p in -p out

[0079] In the formula, p in p represents the absolute pressure at the air inlet, in Pa. out This represents the absolute pressure at the air outlet, measured in Pa.

[0080] The number of heat exchange channels is greater than 20.

[0081] As the inlet cavity width W1 gradually increases from 450mm to 750mm, the change in the standard deviation of the heat exchange channel velocity is as follows: Figure 3 As shown. The three-dimensional response surface between the air inlet dimensions InL and InW of the air-side inlet cavity and the velocity standard deviation is as follows. Figure 4As shown. Then, it gradually increases with increasing W2, and the optimal width of the exit cavity is significantly smaller than the width of the inlet cavity; this optimal width is 525 mm. Figure 5 As shown in the figure. The standard deviation of the heat exchange channel velocity of the heat storage body varies with the air outlet dimensions OutW and OutL of the air outlet cavity, respectively. Figure 6 and Figure 7 As shown.

[0082] Example 2

[0083] This embodiment is a system for optimizing the structure of the heat storage chamber in a solid-state electric thermal storage device, such as... Figure 8 As shown, it consists of a simulation model acquisition unit, a simulation model mesh generation unit, a flow field distribution simulation unit, a response surface setting unit, and a simulation optimization unit.

[0084] Simulation model acquisition unit: Parametric modeling of the heat storage chamber structure to obtain the simulation model;

[0085] Simulation model mesh generation: All meshes are generated using a structured meshing method, defining the number of meshes per unit distance, and outputting a mesh file;

[0086] Flow field distribution simulation unit: Flow field distribution simulation of the fluid region of the heat storage body. The simulation parameters include the air velocity at the air inlet, the absolute pressure at the air outlet, the difference between the velocity and the average velocity of each heat exchange channel and the velocity standard deviation S1, and the pressure difference Δp between the air inlet and the air outlet.

[0087] Response surface setting unit: Set the response surface, select the response surface optimization method, and set the variation range of each variable parameter;

[0088] Simulation optimization unit: The objective functions are set as minimizing the speed standard deviation S1 and minimizing the pressure difference Δp between the air inlet and outlet. The genetic optimization method is selected, and the operating points are obtained according to the DOE experimental design method. The simulation optimization results of each operating point are calculated and output.

[0089] In the simulation model acquisition unit, the parameters of the heat storage chamber structure include the length InL and width InW of the air inlet, the width InCW of the air inlet chamber and the width OutCW of the air outlet chamber, and the length OutL and width OutW of the air outlet; the simulation model file format is *.iges, *.x_t, or *.step.

[0090] In the simulation model mesh generation unit, the number of meshes includes the number of meshes in the length, width, and depth directions of each geometry, and the mesh file format is *.msh.

[0091] In the aforementioned flow field distribution simulation unit, the heat transfer process in the fluid region of the heat storage body is described by the fluid's mass conservation and momentum conservation equations.

[0092] mass conservation equation:

[0093]

[0094] In the formula: ρ is the fluid density, kg / m³ 3 t represents time, in seconds; The velocity is m / s; To express differentiation;

[0095] Momentum conservation equation:

[0096]

[0097] In the formula: μ is the dynamic viscosity, in Pa·s; P is the fluid pressure, in Pa; g is the acceleration due to gravity, in m / s². 2 .

[0098] The air inlet is located at the velocity boundary inlet. The turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hin = 2 × InL × InW ÷ (InL + InW), and the turbulence intensity is set to 5%.

[0099] The air outlet is located at the pressure boundary outlet. The turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hout = 2 × OutL × OutW ÷ (OutL + OutW), and the turbulence intensity is set to 5%.

[0100] Average flow rate of heat exchange channels in heat storage body The expression is:

[0101]

[0102] Where: M is the total flow rate at the air inlet, in kg / s;

[0103] n is the total number of heat exchange channels;

[0104] The expression for the standard deviation of flow rate σ is:

[0105]

[0106] Where: m i The flow rate of the i-th heat exchange channel is expressed in kg / s.

[0107] The expression for the pressure difference Δp between the air inlet and outlet is:

[0108] Δp=p in -p out

[0109] In the formula, p inp represents the absolute pressure at the air inlet, in Pa. out This represents the absolute pressure at the air outlet, measured in Pa.

[0110] The number of heat exchange channels is greater than 20.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the structure of the heat storage chamber in a solid-state electric thermal energy storage device, characterized in that, include: Step S1: Parametric modeling of the heat storage chamber structure to obtain the simulation model; Step S2, simulation model mesh generation: all models are generated using a structured mesh generation method, defining the number of meshes per unit distance and outputting the mesh file; Step S3: Simulate the flow field distribution in the heat storage fluid region. The simulation parameters include the air velocity at the inlet, the absolute pressure at the outlet, the difference between the velocity and the average velocity in each heat exchange channel, the velocity standard deviation S1, and the pressure difference between the inlet and outlet. p; Step S4: Set the response surface, select the response surface optimization method, and set the variation range for each variable parameter; Step S5, Simulation Optimization: Set the minimum speed standard deviation S1 and the pressure difference between the air inlet and outlet. The objective function is to minimize p. The genetic optimization method is selected, and the operating points are obtained according to the DOE experimental design method. The simulation optimization results of each operating point are calculated and output. In step S1, the parameters of the heat storage chamber structure include the length InL and width InW of the air inlet, the width InCW of the air inlet chamber and the width OutCW of the air outlet chamber, and the length OutL and width OutW of the air outlet. In step S3, the air inlet is located at the velocity boundary inlet, and the turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hin = 2 × InL × InW ÷ (InL + InW); the air outlet is located at the pressure boundary outlet, and the turbulence mode is selected based on the equivalent diameter and turbulence intensity. The equivalent diameter is calculated as hout = 2 × OutL × OutW ÷ (OutL + OutW).

2. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 1, characterized in that, In step S1, the format of the simulation model file is as follows: .iges、 .x_t or .step.

3. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 1, characterized in that, In step S2, the number of grids includes the number of grids in the length, width, and depth directions of each geometry.

4. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 1, characterized in that, In step S2, the mesh file format is as follows: .msh.

5. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 1, characterized in that, In step S3, the heat transfer process in the fluid region of the heat storage body is described by the mass conservation and momentum conservation equations of the fluid.

6. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 5, characterized in that, In step S3, the mass conservation equation is: （1） In the formula: Fluid density, in kg / m³ 3 ; t Time, in seconds; The velocity is expressed in m / s. To express differentiation; Momentum conservation equation: （2） In the formula: Dynamic viscosity, expressed in Pa·s; The pressure is the fluid pressure, measured in Pa; g is the acceleration due to gravity, measured in m / s². 2 .

7. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 1, characterized in that, In step S3, the turbulence intensity is set to 5%.

8. The method for optimizing the structure of the heat storage chamber in a solid-state electric heat storage device according to claim 1, characterized in that, In step S3, the average flow rate of the heat exchange channel of the heat storage body is... The expression is: ， In the formula: The total airflow rate at the air inlet is expressed in kg / s. n This represents the total number of heat exchange channels; Flow standard deviation The expression is: In the formula: For the first i Flow rate of each heat exchange channel, in kg / s; Pressure difference between air inlet and air outlet The expression is: In the formula, This represents the absolute pressure at the air inlet, in Pa. This represents the absolute pressure at the air outlet, measured in Pa.

9. A system for optimizing the structure of the heat storage chamber of a solid-state electric thermal storage device, used to implement the method for optimizing the structure of the heat storage chamber of the solid-state electric thermal storage device according to any one of claims 1-8, characterized in that, include: Simulation model acquisition unit: Parametric modeling of the heat storage chamber structure to obtain the simulation model; Simulation model mesh generation: All meshes are generated using a structured meshing method, defining the number of meshes per unit distance, and outputting a mesh file; Flow field distribution simulation unit: Simulation of the flow field distribution in the heat storage fluid region. Simulation parameters include the air velocity at the inlet, the absolute pressure at the outlet, the difference between the velocity and the average velocity in each heat exchange channel, the velocity standard deviation S1, and the pressure difference between the inlet and outlet. p; Response surface setting unit: Set the response surface, select the response surface optimization method, and set the variation range of each variable parameter; Simulation optimization unit: Sets the minimum speed standard deviation S1 and the pressure difference between the air inlet and outlet. The objective function is to minimize p. The genetic optimization method is selected, and the operating points are obtained according to the DOE experimental design method. The simulation optimization results of each operating point are calculated and output.

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