Preparation method of fused salt material, fused salt material and fused salt energy storage system

Abstract

The invention relates to the technical field of fused salt energy storage, and particularly provides a preparation method of a fused salt material, the fused salt material and a fused salt energy storage system. The preparation method comprises the following steps: determining the lowest thermal conductivity of a molten salt material in the molten salt energy storage system, substituting the lowest thermal conductivity into a component calculation formula of a nano filling material, and determining the mass fractions of nano silicon dioxide, nano aluminum oxide, nano silicon carbide and nano graphene in the nano filling material, the preparation method comprises the following steps: preparing a nano filling material according to the mass fractions of nano silicon dioxide, nano aluminum oxide, nano silicon carbide and nano graphene in the nano filling material, and then preparing the fused salt material by utilizing the nano filling material and basic fused salt in a preset mass ratio. According to the method, the minimum thermal conductivity is substituted into a nano filler component calculation formula, the mass fraction of the four components can be calculated, and then the fused salt material is prepared, so that the selection design and selection difficulty of the fused salt material in the design and construction process of the fused salt energy storage system are reduced.

Description

Technical Field

[0001] The present application relates to the technical field of molten salt energy storage, and specifically relates to a preparation method of a molten salt material, a molten salt material, and a molten salt energy storage system. Background Art

[0002] A molten salt energy storage system is a system that utilizes the temperature difference during the heating and cooling processes of a molten salt material to achieve heat energy storage and release. Due to the advantages of high energy storage density, long heat storage time, long service life, etc. of the molten salt energy storage system, it has been applied in fields such as solar thermal power generation and power grid peak shaving. For example, during the low valley period of the power grid or when there is an oversupply of new energy power, it can heat the molten salt material with the heat generated by energy sources such as solar thermal energy, geothermal energy, industrial waste heat, low-grade waste heat, and valley electricity to raise its temperature, thereby storing the heat energy. Subsequently, it can also control the molten salt material to cool down to achieve an orderly release of energy. Therefore, for a molten salt energy storage system, the molten salt material is its core component.

[0003] The thermal conductivity of the molten salt material has an important impact on the storage and release of heat energy. During the design and construction process of the molten salt energy storage system, the thermal conductivity is one of the key indicators of the molten salt material in the molten salt energy storage system. However, the structure of the molten salt energy storage system is complex. In addition to including a molten salt storage tank for accommodating the energy storage material, it also includes related pipelines, heat exchangers, steam generators, and power systems, etc. These systems all have an impact on the thermal conductivity of the molten salt material, resulting in great difficulties in the selection and design of the molten salt material during the design and construction process of the molten salt energy storage system. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a preparation method of a molten salt material, a molten salt material, and a molten salt energy storage system, which are used to solve the problem that it is difficult to select a suitable molten salt material during the design and construction process of the existing molten salt energy storage system.

[0005] The first aspect of the embodiments of the present application provides a preparation method of a molten salt material, including: Determine the minimum thermal conductivity of the molten salt material in the molten salt energy storage system; Substitute the minimum thermal conductivity into the calculation formula for the components of the nano-filled material to determine the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in the nano-filled material; where the calculation formula for the components of the nano-filled material is specifically:

[0006] Where: k is the minimum thermal conductivity; Δk is the safety margin; k0 is the thermal conductivity of the base molten salt, where the base molten salt contains sodium nitrate and potassium nitrate; x iis the mass fraction of the i-th component in the nano-filled material, where x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene respectively; x j is the mass fraction of the j-th component in the nano-filled material; a i is the linear influence coefficient of the i-th component in the nano-filled material; b i is the quadratic term influence coefficient of the i-th component in the nano-filled material; c ij is the interaction influence coefficient between the i-th component and the j-th component; Prepare the nano-filled material according to the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material; Prepare the molten salt material by using the nano-filled material and the base molten salt with a preset mass ratio.

[0007] Preferably, the method further includes: Weigh multiple groups of nano-filled material samples and the base molten salt according to the preset mass ratio; among them, the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples are different; After heating each group of base molten salts to the molten state, add the corresponding groups of nano-filled material samples respectively, and stir until uniform to obtain multiple groups of molten salt material samples; Measure the thermal conductivity of each group of molten salt material samples; Taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples as independent variables, and the thermal conductivity of the corresponding molten salt material samples as the dependent variable, determine a i 、b i and c ij .

[0008] Preferably, taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples as independent variables, and the thermal conductivity of the corresponding molten salt material samples as the dependent variable, determine a i 、b i and c ij , specifically including: Construct a functional relationship ; where y pred is the dependent variable; Randomly for a i 、b i and c ijPerform assignment and calculate the corresponding function value y according to the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples pred ; Calculate this y pred The difference from the thermal conductivity of the corresponding molten salt material; According to y pred The partial derivatives with respect to x1, x2, x3, and x4 respectively to generate the Jacobian matrix J; According to the update formula of the L-M regression algorithm Δx=(J T J +λI) -1 J T e, adjust a i , b i and c ij Get the new a i , b i and c ij , and then with the new a i , b i and c ij , and calculate the new function value y according to the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples pred , and continue to calculate this y pred The difference from the thermal conductivity of the corresponding molten salt material to readjust the new a i , b i and c ij , repeat multiple times until the convergence condition is met, and obtain a i , b i and c ij at convergence as the finally calculated a i , b i and c ij , where I is the identity matrix with the same dimension as the matrix J T J; λ is the damping factor and λ>0; e is the residual vector of the L-M regression algorithm.

[0009] Preferably, the preset mass ratio is specifically: 100 parts by mass of the base molten salt and 2.6 to 10.5 parts by mass of the nano-filled material.

[0010] Preferably, the mass ratio of sodium nitrate to potassium nitrate in the base molten salt is 3:7 to 7:3.

[0011] Preferably, preparing the molten salt material using the nano-filled material and the base molten salt with the preset mass ratio specifically includes: Weigh the nano-filled material and the base molten salt according to the preset mass ratio; Place the weighed base molten salt in a high-temperature furnace and heat it to a molten state; Add the weighed nano-filling material to the molten base molten salt and stir until homogeneous to obtain the molten salt material.

[0012] Preferably, the method further includes: pre-measuring the thermal conductivity k0 of the base molten salt.

[0013] Preferably, determining the minimum thermal conductivity of the molten salt material in the molten salt energy storage system specifically includes: Using the energy storage capacity, charge and discharge duration, and operating temperature range of the molten salt energy storage system, estimate the minimum thermal conductivity by establishing a heat conduction model.

[0014] A second aspect of the embodiments of the present application provides a molten salt material, including: a nano-filling material and a base molten salt in a preset mass ratio, where: The base molten salt contains sodium nitrate and potassium nitrate; The components in the nano-filling material include: nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene; Among them, the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filling material conform to the calculation formula for the components of the nano-filling material:

[0015] Where: k is the minimum thermal conductivity of the molten salt material in the molten salt energy storage system; Δk is the safety margin; k0 is the thermal conductivity of the base molten salt; x i is the mass fraction of the i-th component in the nano-filling material, where x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene respectively; x j is the mass fraction of the j-th component in the nano-filling material; a i is the linear influence coefficient of the i-th component in the nano-filling material; b i is the quadratic term influence coefficient of the i-th component in the nano-filling material; c ij is the interaction influence coefficient between the i-th component and the j-th component.

[0016] A third aspect of the embodiments of the present application provides a molten salt energy storage system, and the molten salt energy storage system includes the molten salt material provided by the embodiments of the present application.

[0017] The preparation method of the molten salt material provided by the embodiment of the present application includes determining the lowest thermal conductivity of the molten salt material in the molten salt energy storage system, and then substituting the lowest thermal conductivity into the calculation formula for the components of the nano-filled material to determine the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material. The specific calculation formula for the components of the nano-filled material is as follows:

[0018] , where: k is the lowest thermal conductivity; Δk is the safety margin; k0 is the thermal conductivity of the base molten salt, and the base molten salt contains sodium nitrate and potassium nitrate, x i is the mass fraction of the i-th component in the nano-filled material. Among them, x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene respectively, and x j is the mass fraction of the j-th component in the nano-filled material, a i is the linear influence coefficient of the i-th component in the nano-filled material, b i is the quadratic term influence coefficient of the i-th component in the nano-filled material, c ij is the interaction influence coefficient between the i-th component and the j-th component. Then, according to the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material, the nano-filled material is prepared. Then, using the nano-filled material and the base molten salt with a preset mass ratio, the molten salt material is prepared. By determining the lowest thermal conductivity of the molten salt material in the molten salt energy storage system and then substituting it into the calculation formula for the components of the nano-filled material, the mass fractions of the four components of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene can be calculated, and then the nano-filled material and the molten salt material can be prepared. Therefore, it can reduce the difficulty of selecting and designing the molten salt material in the design and construction process of the molten salt energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments of the present application. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0020] Figure 1 is a specific process schematic diagram of the preparation method of the molten salt material provided by an embodiment of the present application; Figure 2 is a specific process schematic diagram of the method for determining the parameters in the calculation formula for the components of the nano-filled material provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings in the embodiments of the present application. In the description of the present application, terms such as "first" and "second" are only used for descriptive distinction and cannot be understood as indicating or implying relative importance or sequence.

[0022] The embodiments of the present application provide a preparation method of a molten salt material, a molten salt material and a molten salt energy storage system, which can be used to solve the problems in the prior art. As Figure 1 shown in the specific process schematic diagram of the preparation method of the molten salt material in the molten salt energy storage system provided by the embodiments of the present application, the preparation method includes: Step S11: Determine the minimum thermal conductivity of the molten salt material in the molten salt energy storage system.

[0023] In practical applications, during the design and construction of the molten salt energy storage system, the thermal conductivity of the selected molten salt material needs to meet the design requirements, that is, it needs to be greater than or equal to the minimum thermal conductivity. The minimum thermal conductivity refers to the minimum value of the thermal conductivity that can meet the heat transfer requirements of the molten salt energy storage system.

[0024] For a certain molten salt energy storage system in design and construction, the present application can estimate the minimum thermal conductivity by establishing a heat conduction model based on parameters such as the energy storage capacity, charge and discharge duration, and operating temperature range of the molten salt energy storage system. Specifically, the heat conduction model can be established in the following way: by simulating the heat conduction inside the molten salt material, establishing a heat conduction equation according to Fourier's law, and by simulating the convective heat transfer between the molten salt material and the container wall or pipeline, establishing a convective heat transfer equation according to Newton's law of cooling, and using the heat conduction equation and the convective heat transfer equation as the established heat conduction model; then, combining parameters such as the energy storage capacity, charge and discharge duration, and operating temperature range, solving the heat conduction model to estimate the minimum thermal conductivity.

[0025] Among them, the heat conduction equation is specifically Formula 1 shown as follows:

[0026] Formula 1 In this Formula 1, ρ is the density of the molten salt material; c p is the specific heat capacity at constant pressure of the molten salt material; T is the temperature, t is the time; k is the minimum thermal conductivity; x, y, and z are respectively three directions in space.

[0027] The convective heat transfer equation is specifically Formula 2 shown as follows:

[0028] Formula 2 In this Formula 2, q is the convective heat transfer flux density, h is the convective heat transfer coefficient, Tfluid is the temperature of the molten salt material; T wall is the wall temperature in contact with the molten salt material.

[0029] Step S12: Substitute the lowest thermal conductivity into the calculation formula for the nano-filled material components to determine the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material.

[0030] It should be emphasized that the molten salt material to be prepared in this application includes a base molten salt and a nano-filled material. Among them, the mass ratio between the nano-filled material and the base molten salt is a preset mass ratio. Specifically, the preset mass ratio is: 100 parts by mass of the base molten salt and 2.6 to 10.5 parts by mass of the nano-filled material.

[0031] In addition, considering that the existing multi-component nitrate molten salt has relatively poor stability compared with the binary nitrate molten salt, the base molten salt used herein is a binary nitrate molten salt, specifically a binary nitrate molten salt composed of sodium nitrate and potassium nitrate. Among them, the mass ratio of sodium nitrate to potassium nitrate in the base molten salt can be 3:7 to 7:3, such as 3:7, 4:6, 5:5, 6:4, 7:3, or other values between 3:7 and 7:3.

[0032] The nano-filled material includes four different components: nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene. Among them, nano-silica can improve the melting and fluidity of the molten salt and enhance the thermal conductivity of the molten salt material due to its good thermal stability and dispersibility; the main function of nano-silicon carbide is also to improve the thermal conductivity of the molten salt material and increase the specific heat capacity at the same time; nano-alumina can reduce the friction of the molten salt material and thus improve its stability at high temperatures; nano-graphene can also reduce the friction of the molten salt material, improve its fluidity and thermal stability.

[0033] Considering the different functions of these four components, the key of this application is to determine the mass fractions of the four components of the nano-filled material. Specifically, in this step S12, the lowest thermal conductivity obtained in step S11 can be substituted into the calculation formula for the nano-filled material components to determine the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material.

[0034] Among them, the calculation formula for the nano-filled material components is specifically Formula Three as shown below:

[0035] Formula Three Where: k is the lowest thermal conductivity, i.e., the lowest thermal conductivity obtained through the above step S11; Δk is the safety margin, and this safety margin Δk is the redundancy in actual engineering. In actual applications, the specific value of this safety margin Δk can be set as needed; k0 is the thermal conductivity of the base molten salt. Among them, the base molten salt contains sodium nitrate and potassium nitrate. In actual applications, the thermal conductivity k0 of this base molten salt can be measured in advance. For example, potassium nitrate and sodium nitrate with a mass ratio of 6:4 can be configured as the base molten salt, and then a thermal conductivity tester can be used to measure its thermal conductivity; x i is the mass fraction of the i-th component in the nano-fill material, where the value of i ranges from 1 to 4, and x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene respectively. That is to say, when i = 1, it corresponds to nano-silica; when i = 2, it corresponds to nano-alumina; when i = 3, it corresponds to nano-silicon carbide; when i = 4, it corresponds to nano-graphene; x j is the mass fraction of the j-th component in the nano-fill material. Similarly, the value of j can also range from 1 to 4, and i is less than j.

[0036] It should be emphasized that in this formula three, a i is the linear influence coefficient of the i-th component in the nano-fill material; b i is the quadratic term influence coefficient of the i-th component in the nano-fill material; c ij is the interaction influence coefficient between the i-th component and the j-th component.

[0037] In the implementation principle of this application, after adding the four components, the effects on the thermal conductivity of the molten salt material are respectively fitted to obtain the linear influence part, quadratic term influence part, and interaction influence part of each component. For example, for nano-silica, after adding nano-silica to the molten salt material, the effect on the thermal conductivity of the molten salt material can be composed of the linear influence part, quadratic term influence part, and the interaction influence part between nano-silica and other components; similarly, the addition of nano-alumina, nano-silicon carbide, and nano-graphene also has an effect on the thermal conductivity of the molten salt material, which is composed of the linear influence part, quadratic term influence part, and interaction influence part.

[0038] In this application, for the linear influence part of the i-th component, it is specifically a i × x i . In this way, the cumulative value of the linear influence parts of the four components is a1× x2 + a2× x2 + a3× x3 + a4× x4, which is the in the above formula three; for the quadratic term influence part of the i-th component, it is specifically b i × x i2 , the cumulative value of the squared term influence part of the four components is b1×x1 2 + b2×x2 2 + b3×x3 2 + b4×x4 2 , which is the in Formula 3 above; for the interaction influence part of the i-th component, it is specifically c ij ×x i ×x j , so the cumulative value of the interaction influence part of the four components is c 12 ×x1×x2 + c 13 ×x1×x3 + c 14 ×x1×x4 + c 23 ×x2×x3 + c 24 ×x2×x4 + c 34 ×x3×x4, which is the in Formula 3 above; after obtaining , and , adding the safety margin Δk and the thermal conductivity k0 of the base molten salt can achieve the fitting of the thermal conductivity of the molten salt material obtained after adding the nano-filling material. Therefore, the lowest thermal conductivity obtained in step S11 above can be substituted into Formula 3 to calculate the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filling material.

[0039] It should be emphasized that the parameters in Formula 3, that is, the linear influence coefficient a i of the i-th component, the squared term influence coefficient b i of the i-th component, and the interaction influence coefficient c ij between the i-th component and the j-th component can be calculated in advance through the parameter determination method shown in Figure 2 in practical applications.

[0040] Step S121: Weigh multiple groups of nano-filling material samples and base molten salts according to a preset mass ratio.

[0041] Among them, the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filling material samples are different. For example, as shown above, the preset mass ratio can be 100 parts by mass of the base molten salt and 5 parts by mass of the nano-filling material. At this time, multiple groups of 100 parts by mass of the base molten salt and multiple groups of 100 parts by mass of the nano-filling material samples can be weighed, and the mass fractions of the four components in each nano-filling material are different.

[0042] Step S122: After heating each group of base molten salts to the molten state, add the corresponding groups of nano-fill material samples respectively, and stir until uniform to obtain multiple groups of molten salt materials.

[0043] In practical applications, the weighed groups of base molten salts can be placed in a high-temperature furnace and heated to the molten state, and then the corresponding groups of nano-fill material samples are added to each group of molten base molten salts respectively, and then stirred until uniform, so as to obtain multiple groups of molten salt material samples. Of course, the molten salt material samples can also be kept warm for 1 to 2 hours and then cooled naturally.

[0044] Step S123: Measure the thermal conductivity of each group of molten salt material samples.

[0045] After obtaining each group of molten salt material samples through the above-mentioned step S122, in this step S123, the thermal conductivity of each group of molten salt material samples can be further measured. For example, a thermal conductivity tester can be used to measure the thermal conductivity of each group of molten salt material samples.

[0046] Step S124: Taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-fill material samples as independent variables, and the thermal conductivity of the corresponding molten salt material as the dependent variable, determine a i 、b i and c ij .

[0047] Among them, the L-M regression algorithm specifically refers to the Levenberg-Marquardt method, which is an estimation method for the least squares estimation of regression parameters in nonlinear regression.

[0048] In this application, through the above-mentioned steps S121 to S123, the data of the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in multiple groups of nano-fill material samples, as well as the thermal conductivity of the molten salt materials corresponding to each group of nano-fill material samples, can be obtained. Furthermore, taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-fill material samples as independent variables, and the thermal conductivity of the corresponding molten salt material as the dependent variable, and determining a i 、b i and c ij .

[0049] Among them, taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-fill material samples as independent variables, and the thermal conductivity of the corresponding molten salt material as the dependent variable, and determining a i 、b i and c ij, and the specific method can be to construct a functional relationship:

[0050] wherein, in this functional relationship, y pred is the dependent variable, which corresponds to the thermal conductivity of the molten salt material; the other parameters in this functional relationship are the same as those in the above formula three. Additionally, according to the definition of this function, obviously y can be expressed as , and subsequently, it is necessary to determine the specific values of a i , b i , and c ij .

[0051] The values of a i , b i , and c ij can be randomly assigned first, and then, according to the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples, the corresponding function value y pred is calculated; then the difference between this y pred and the thermal conductivity of the corresponding molten salt material is calculated; according to the partial derivatives of y pred with respect to x1, x2, x3, and x4 respectively, the Jacobian matrix J is generated; according to the update formula of the L-M regression algorithm Δx = (J T J + λI) -1 J T e, a i , b i , and c ij are adjusted to obtain new a i , b i , and c ij , and then, with this new a i , b i , and c ij , and according to the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples, a new function value y pred is calculated, and the difference between this y pred and the thermal conductivity of the corresponding molten salt material is continuously calculated to readjust this new a i , b i , and c ij . This is repeated multiple times until the convergence condition is met, and the convergent a i , b i , and c ij are obtained as the finally calculated a i , b i , and c ij， wherein, I is the identity matrix with the same dimension as the matrix J T J; λ is the damping factor, and λ is greater than 0; e is the residual vector of the L-M regression algorithm.

[0052] Step S13: Prepare the nano-filled material according to the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in the nano-filled material.

[0053] After obtaining the mass fractions of the four components of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in the nano-filled material in the above Step S12, the corresponding weights of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene can be weighed according to the mass fractions of the four components, and then uniformly mixed to obtain the nano-filled material.

[0054] Step S14: Prepare a molten salt material using the nano-filled material and the base molten salt with a preset mass ratio.

[0055] The nano-filled material and the base molten salt can be weighed first according to the preset mass ratio. For example, the above-mentioned preset mass ratio is 100 parts by mass of the base molten salt and 2.6 to 10.5 parts by mass of the nano-filled material. Therefore, 100 parts by mass of the base molten salt and 2.6 to 10.5 parts by mass of the nano-filled material can be weighed. Then, the weighed base molten salt is placed in a high-temperature furnace and heated to a molten state, and the weighed nano-filled material is added to the molten base molten salt and stirred until uniform to obtain the molten salt material.

[0056] It should be noted that after preparing the molten salt material by the method provided in the embodiments of the present application, the thermal conductivity of the prepared molten salt material can be further measured. For example, in Example 1 of the present application, it is determined that the minimum thermal conductivity of the molten salt material in the molten salt energy storage system is 0.7 W / (m·K). Substituting this minimum thermal conductivity of 0.7 W / (m·K) into the calculation formula for the components of the nano-filled material, it can be calculated that when the mass fraction of nano-silica is 38% - 48%, the mass fraction of nano-aluminum oxide is 28.6% - 38%, the mass fraction of nano-silicon carbide is 4% - 10%, and the mass fraction of nano-graphene is 4% - 7%, the calculation result of the calculation formula for the components of the nano-filled material can meet the requirement of being greater than or equal to 0.7 W / (m·K). Therefore, the nano-filled material can be prepared according to the mass fractions of the components, and then 100 parts by mass of the base molten salt and 10.5 parts by mass of the nano-filled material are weighed to prepare the molten salt material. Obviously, the molten salt material prepared by this method can meet the requirement that its thermal conductivity is greater than the minimum thermal conductivity, which is convenient for selecting a suitable molten salt material in the design and construction process of the molten salt energy storage system.

[0057] Adopting the method for preparing the molten salt material provided by the embodiment of the present application, it includes determining the lowest thermal conductivity of the molten salt material in the molten salt energy storage system, and then substituting the lowest thermal conductivity into the calculation formula for the nano-filled material components to determine the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material. The specific calculation formula for the nano-filled material components is as follows: , where: k is the lowest thermal conductivity; Δk is the safety margin; k0 is the thermal conductivity of the base molten salt, and the base molten salt contains sodium nitrate and potassium nitrate, x i is the mass fraction of the i-th component in the nano-filled material. Among them, x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene respectively, x j is the mass fraction of the j-th component in the nano-filled material, a i is the linear influence coefficient of the i-th component in the nano-filled material, b i is the quadratic term influence coefficient of the i-th component in the nano-filled material, c ij is the interaction influence coefficient between the i-th component and the j-th component. Then, according to the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material, the nano-filled material is prepared. Then, using the nano-filled material and the base molten salt with a preset mass ratio, the molten salt material is prepared. By determining the lowest thermal conductivity of the molten salt material in the molten salt energy storage system and then substituting it into the calculation formula for the nano-filled material components, the mass fractions of the four components of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene can be calculated, and then the nano-filled material and the molten salt material can be prepared. Therefore, it can reduce the difficulty of selecting and designing the molten salt material during the design and construction process of the molten salt energy storage system.

[0058] Based on the same inventive concept as the method for preparing the molten salt material provided by the embodiment of the present application, the embodiment of the present application can also provide a molten salt material, which is specifically the molten salt material prepared by the preparation method provided by the embodiment of the present application. It includes: a nano-filled material and a base molten salt with a preset mass ratio, where: the base molten salt contains sodium nitrate and potassium nitrate; the components in the nano-filled material include: nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene; the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material conform to the calculation formula for the nano-filled material components shown in the above formula three. Since the preparation of this molten salt material adopts the same inventive concept as the method for preparing the molten salt material provided by the embodiment of the present application, it can also solve the problems in the prior art.

[0059] In addition, the embodiments of the present application may further provide a molten salt energy storage system, which includes the molten salt material provided by the embodiments of the present application. Obviously, this molten salt energy storage system can also solve the problems in the prior art. Of course, this molten salt energy storage system may further include other related components, which are not limited herein.

[0060] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. A preparation method of a molten salt material, characterized in that, Including: Determine the minimum thermal conductivity of the molten salt material in the molten salt energy storage system; Substitute the minimum thermal conductivity into the calculation formula for the nano-filled material components to determine the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material; wherein, the calculation formula for the nano-filled material components is specifically: ； Wherein: k is the lowest thermal conductivity; Δk is the safety margin; k0 is the thermal conductivity of the base molten salt, wherein the base molten salt contains sodium nitrate and potassium nitrate; x i is the mass fraction of the i-th component in the nano-fill material, where x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene, respectively; x j is the mass fraction of the j-th component in the nano-fill material; a i is the linear influence coefficient of the i-th component in the nano-fill material; b i is the quadratic term influence coefficient of the i-th component in the nano-fill material; c ij is the interaction influence coefficient between the i-th component and the j-th component; Prepare the nano-filled material according to the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material; Prepare the molten salt material by using the nano-filled material and the base molten salt with a preset mass ratio.

2. The preparation method according to claim 1, wherein The method further includes: Weigh multiple groups of nano-filled material samples and the base molten salt according to the preset mass ratio; wherein, the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples are different; After heating each group of base molten salts to the molten state, add the corresponding groups of nano-filled material samples respectively and stir until uniform to obtain multiple groups of molten salt material samples; Measure the thermal conductivity of each group of molten salt material samples; Taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples as independent variables and the thermal conductivity of the corresponding molten salt material samples as the dependent variable, a i , b i , and c ij are determined through the L-M regression algorithm.

3. The preparation method according to claim 2, characterized in that, Taking the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples as independent variables, and the thermal conductivity of the corresponding molten salt material samples as the dependent variable, a i , b i , and c ij are determined through the L-M regression algorithm, specifically including: Construct a functional relationship ; where y pred is the dependent variable; Randomly assign values to a i , b i and c ij , and calculate the corresponding function value y according to the mass fractions of nano-silica, nano-aluminum oxide, nano-silicon carbide, and nano-graphene in each group of nano-filled material samples pred ; Calculate the function value y pred The difference from the thermal conductivity of the corresponding molten salt material; According to y pred Derivatives with respect to x1, x2, x3, and x4 are calculated respectively to generate the Jacobian matrix J; According to the update formula of the L-M regression algorithm Δx = (J T J + λI) -1 J T e, adjust a i 、b i and c ij to obtain the new a i 、b i and c ij , and then with the new a i 、b i and c ij , and according to the mass fractions of nano-silica, nano-alumina, nano-silicon carbide and nano-graphene in each group of nano-filled material samples, calculate the new function value y pred , and continue to calculate this y pred and the difference from the thermal conductivity of the corresponding molten salt material to readjust the new a i 、b i and c ij , repeat multiple times until the convergence condition is met, and obtain a i 、b i and c ij at convergence, as the finally calculated a i 、b i and c ij , where I is the identity matrix with the same dimension as the matrix J T J; λ is the damping factor, and λ is greater than 0; e is the residual vector of the L-M regression algorithm.

4. The preparation method according to claim 1, characterized in that, The preset mass ratio is specifically: 100 parts by mass of the base molten salt and 2.6 - 10.5 parts by mass of the nano-filled material.

5. The preparation method according to claim 1, characterized in that, The mass ratio of sodium nitrate to potassium nitrate in the base molten salt is 3:7 - 7:

3.

6. The preparation method according to claim 1, wherein Preparing the molten salt material by using the nano-filled material and the base molten salt with a preset mass ratio specifically includes: Weigh the nano-filled material and the base molten salt according to the preset mass ratio; Place the weighed base molten salt in a high-temperature furnace and heat it to the molten state; Add the weighed nano-filled material to the molten base molten salt and stir until uniform to obtain the molten salt material.

7. The preparation method according to claim 1, characterized in that The method further includes: pre-measuring the thermal conductivity k0 of the base molten salt.

8. The preparation method according to claim 1, characterized in that, Determining the minimum thermal conductivity of the molten salt material in the molten salt energy storage system specifically includes: Using the energy storage capacity, charge-discharge duration, and operating temperature range of the molten salt energy storage system to estimate the minimum thermal conductivity by establishing a heat conduction model.

9. A molten salt material, characterized in that, Including: Nano-filled material and base molten salt with a preset mass ratio, wherein: The base molten salt contains sodium nitrate and potassium nitrate; The components in the nano-filled material include: nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene; Among them, the mass fractions of nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene in the nano-filled material conform to the calculation formula for the nano-filled material components: ； Where: k is the minimum thermal conductivity of the molten salt material in the molten salt energy storage system; Δk is the safety margin; k0 is the thermal conductivity of the base molten salt; x i is the mass fraction of the i-th component in the nano-fill material, where x1, x2, x3, and x4 are nano-silica, nano-alumina, nano-silicon carbide, and nano-graphene, respectively; x j is the mass fraction of the j-th component in the nano-fill material; a i is the linear influence coefficient of the i-th component in the nano-fill material; b i is the quadratic term influence coefficient of the i-th component in the nano-fill material; c ij is the interaction influence coefficient between the i-th component and the j-th component.

10. A molten salt energy storage system, characterized in that, The molten salt energy storage system includes the molten salt material as described in claim 9.

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