Simulation optimization method and device for long-time liquid storage tank of all-vanadium redox flow battery

Abstract

The invention discloses a simulation optimization method and device for a long-time liquid storage tank of an all-vanadium redox flow battery, and the method comprises the steps: constructing a simulation model of the long-time liquid storage tank of the all-vanadium redox flow battery, and enabling an initial parameter set of the simulation model to comprise the number of simulation baffle plates, and the initial size and initial position corresponding to each simulation baffle plate; carrying out an initial fluid circulation simulation test on the simulation model based on the initial parameter set and a fluid mechanics simulation tool, after one-time electrolyte circulation simulation is completed, obtaining the proportion of the volume of the dead zone to the volume of the simulated electrolyte as an initial proportion, and calculating the volume of the electrolyte according to the initial parameter set, the initial proportion and the fluid mechanics simulation tool. And executing the simulation baffle plate parameter set optimization operation, and obtaining the optimal simulation baffle plate parameter set in the simulation model, so that optimal design parameters can be provided for the design of the baffle plate in the long-time liquid storage tank of the all-vanadium redox flow battery, the performance of the long-time liquid storage tank is optimized, the dead zone phenomenon of electrolyte in the long-time liquid storage tank is reduced, and the service life of the electrolyte in the long-time liquid storage tank is prolonged. And the energy conversion efficiency of the all-vanadium redox flow battery system is improved.

Description

Technical Field

[0001] This text relates to the field of new energy batteries, and particularly to a simulation optimization method and device for a long-duration liquid storage tank of a vanadium redox flow battery. Background Art

[0002] Currently, the mainstream electrolyte storage tanks of vanadium redox flow batteries are mainly divided into two types: horizontal and vertical. Among them, most of the vertical storage tanks are cylindrical in shape and are processed by a winding process. They are mainly used in factory-style energy storage power stations. However, limited by the conditions of manufacturing, transportation, and site space, it is difficult for them to meet the requirements of long-duration energy storage and are mostly suitable for projects with a relatively short discharge duration. The horizontal storage tank is mainly made by a process of welding sheet metals. Its shape is mostly rectangular and is placed in a container, mostly used in outdoor projects. When the length of the storage tank is short, the orderly flow effect of the electrolyte can still meet the use requirements. However, for long-duration projects, the capacity of the storage tank needs to be increased. Limited by the space of the container, the length needs to be increased. At this time, there will be many "dead zones" in the flow of the electrolyte in the tank, resulting in a significant reduction in the efficiency of the system. Usually, baffle plates are added in the storage tank to change the flow of the electrolyte. However, how to set the baffle plates to achieve the best performance of the vanadium redox flow battery system has become an urgent problem to be solved. Summary of the Invention

[0003] The embodiments of the present application provide a simulation optimization method and device for a long-duration liquid storage tank of a vanadium redox flow battery, which can provide optimal design parameters for the design of the internal baffle plates of the long-duration liquid storage tank of the vanadium redox flow battery, optimize the performance of the long-duration liquid storage tank, reduce the dead zone phenomenon of the electrolyte in the long-duration liquid storage tank, and improve the energy conversion efficiency of the vanadium redox flow battery system.

[0004] On the one hand, the embodiments of the present application provide a simulation optimization method for a long-duration liquid storage tank of a vanadium redox flow battery, including: Construct a simulation model of the long-duration liquid storage tank of the vanadium redox flow battery, where the simulation model includes a simulation housing, as well as simulated electrolyte and a plurality of simulated baffle plates inside the simulation housing. The initial parameter set P 0 of the simulation model includes the number N of the simulated baffle plates, the initial size and initial position corresponding to each simulated baffle plate; Based on the initial parameter set and a fluid dynamics simulation tool, perform an initial fluid circulation simulation test on the simulation model. After completing one cycle simulation of the electrolyte, obtain the proportion of the dead zone volume to the volume of the simulated electrolyte as the initial proportion V 0 ; According to the initial parameter set P 0 , the initial proportion V 0Together with the hydrodynamic simulation tool, perform an optimization operation on the set of baffling plate parameters through simulation to obtain the optimal set of simulated baffling plate parameters in the simulation model, where the optimal set of simulated baffling plate parameters is used to achieve the optimized design of the baffling plate in the long-duration liquid storage tank of the all-vanadium redox flow battery.

[0005] On the other hand, an embodiment of the present application further provides a simulation optimization device for a long-duration liquid storage tank of an all-vanadium redox flow battery, including a memory and a processor; The memory is used to store the simulation optimization program for the long-duration liquid storage tank of the all-vanadium redox flow battery; The processor is configured to read the simulation optimization program for the long-duration liquid storage tank of the all-vanadium redox flow battery and perform the simulation optimization method for the long-duration liquid storage tank of the vanadium redox flow battery as described in the above embodiment.

[0006] Compared with the related art, a simulation optimization method and device for a long-duration liquid storage tank of an all-vanadium redox flow battery according to an embodiment of the present application can provide optimal design parameters for the design of the internal baffling plate of the long-duration liquid storage tank of the all-vanadium redox flow battery, including the number of baffling plates, the dimensions and positions of each baffling plate, reduce the cost and time required for designing the long-duration liquid storage tank, optimize the performance of the long-duration liquid storage tank, reduce the dead zone phenomenon of the electrolyte in the long-duration liquid storage tank, and improve the energy conversion efficiency of the all-vanadium redox flow battery system.

[0007] Other features and advantages of the present application will be described in the following specification, and some of them will become obvious from the specification, or be understood by implementing the present application. Other advantages of the present application can be realized and obtained through the solutions described in the specification and the accompanying drawings. Description of the Drawings

[0008] The drawings are used to provide an understanding of the technical solutions of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the technical solutions of the present application and do not constitute a limitation to the technical solutions of the present application.

[0009] Figure 1 It is a flowchart of a simulation optimization method for a long-duration liquid storage tank of an all-vanadium redox flow battery according to an embodiment of the present application; Figure 2 It is a schematic diagram of a simulation model of a specific example of the present application; Figure 3 It is a schematic diagram of a simulation optimization device for a long-duration liquid storage tank of an all-vanadium redox flow battery according to an embodiment of the present application. Detailed Embodiments

[0010] This application describes multiple embodiments, but the description is exemplary rather than restrictive, and it will be apparent to those of ordinary skill in the art that there can be more embodiments and implementation solutions within the scope of the embodiments described in this application. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically restricted, any feature or element of any embodiment can be used in combination with any other feature or element in any other embodiment, or can replace any other feature or element in any other embodiment.

[0011] This application includes and contemplates combinations with features and elements known to those of ordinary skill in the art. The embodiments, features, and elements disclosed in this application can also be combined with any conventional features or elements to form a unique inventive solution. Any feature or element of any embodiment can also be combined with features or elements from other inventive solutions to form another unique inventive solution. Therefore, it should be understood that any feature shown and / or discussed in this application can be implemented alone or in any suitable combination. Therefore, the embodiments are not subject to other limitations except those made in accordance with the appended claims and their equivalents. In addition, various modifications and changes can be made within the scope of the appended claims.

[0012] In addition, when describing representative embodiments, the specification may have presented the method and / or process as a specific sequence of steps. However, to the extent that the method or process does not depend on the specific order of the steps described herein, the method or process should not be limited to the specific order of steps described. As will be understood by those of ordinary skill in the art, other step orders are possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation on the claims. In addition, the claims directed to the method and / or process should not be limited to performing their steps in the order written, and those skilled in the art can easily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0013] With the rapid development of new clean energy in recent years, energy storage technology has developed rapidly in the industry. Relying on its good stability and safety, the all-vanadium redox flow battery has been widely used in the energy storage industry and has become the mainstream technical solution in the energy storage field. The all-vanadium redox flow battery is based on the redox reaction generated by the flow of the electrolyte, enabling the vanadium ions to continuously change their valence states, thereby achieving the purpose of charging and discharging. Since the liquid storage tank is not only the main container for storing the electrolyte, but also the orderly flow of the electrolyte in the liquid storage tank is directly related to the overall efficiency of the all-vanadium redox flow system, the design of the liquid storage tank is crucial.

[0014] An embodiment of the present application provides a simulation optimization method for a long-term storage tank of a vanadium redox flow battery, including steps S100 - S300, as Figure 1 shown: S100: Construct a simulation model of a long-term storage tank of a vanadium redox flow battery, where the simulation model includes a simulation shell, and simulated electrolyte and a plurality of simulated baffle plates inside the simulation shell. The initial parameter set P 0 of the simulation model includes the number N of the simulated baffle plates, the initial size and initial position corresponding to each simulated baffle plate; S200: Based on the initial parameter set and a fluid dynamics simulation tool, perform an initial fluid circulation simulation test on the simulation model. After completing one simulation of electrolyte circulation, obtain the proportion of the dead volume to the volume of the simulated electrolyte as the initial proportion V 0 ; S300: According to the initial parameter set P 0 , the initial proportion V 0 and the fluid dynamics simulation tool, perform an optimization operation for the parameter set of the simulated baffle plates to obtain the optimal parameter set of the simulated baffle plates in the simulation model, where the optimal parameter set of the simulated baffle plates is used to realize the optimized design of the baffle plates in the long-term storage tank of the vanadium redox flow battery.

[0015] In this embodiment, the simulation shell is a simulation model of the tank body of the long-term storage tank of the vanadium redox flow battery, which can simulate the shape and size of the long-term storage tank. Simulated electrolyte and a plurality of simulated baffle plates are arranged inside it. The plurality of simulated baffle plates divide the interior of the simulation shell into different regions, and at the same time, a certain space is reserved at the top and bottom inside the simulation shell to ensure overall connection inside the simulation shell; the simulation shell can include size parameters and position parameters, which can be used as boundary conditions and calculation domains for the optimization operation of the parameter set of the simulated baffle plates in step S300, and the simulation shell provides limiting conditions for the parameters of each simulated baffle plate. For example, the size parameters and position parameters of the simulated baffle plate need to ensure that it is completely located inside the simulation shell and cannot divide the simulation shell into multiple unconnected regions.

[0016] In this embodiment, the initial parameter set P 0 and the initial proportion V 0 provide starting parameters for the optimization operation of the parameter set of the simulated baffle plates in step S300. This optimization process can use an adjoint solver as an optimization tool to adjust the parameters of the simulated baffle plates to obtain the optimal parameter set of the simulated baffle plates; when performing step S100, the volume of the simulated electrolyte needs to be set, and in addition, the parameters of the simulated electrolyte can also be set, including vanadium ion concentration, electrolyte flow rate, electrolyte temperature, etc., and parameters such as the pressure inside the simulation shell can also be set.

[0017] In this embodiment, the hydrodynamic simulation tool can simulate the circulation process of the electrolyte in the long-term storage tank of the all-vanadium redox flow battery. After completing one cycle, the dead volume in this cycle can be obtained, and the ratio of the dead volume to the simulated electrolyte volume can be obtained by dividing the dead volume by the simulated electrolyte volume.

[0018] The simulation optimization method for the long-term storage tank of the all-vanadium redox flow battery in this embodiment can provide optimal design parameters for the design of the baffle inside the long-term storage tank of the all-vanadium redox flow battery, including the number of baffles, the size and position of each baffle, reducing the cost and time required for designing the long-term storage tank, optimizing the performance of the long-term storage tank, reducing the dead zone phenomenon of the electrolyte in the long-term storage tank, and improving the energy conversion efficiency of the all-vanadium redox flow battery system.

[0019] In an exemplary embodiment, step S300 may include: repeatedly performing the following optimization iteration operations, where the i-th optimization iteration operation may include steps S310-S330: S310: Adjust the simulated baffle parameter set P i-1 , and obtain the simulated baffle parameter set P i used in the i-th optimization iteration, where when i≥2, P i-1 is the simulated baffle parameter set used in the (i-1)-th optimization iteration; when i = 1, P i-1 is the initial parameter set P 0 ; S320: Based on P i and the hydrodynamic simulation tool, perform the i-th fluid circulation simulation test. After completing one cycle of electrolyte circulation simulation, obtain the ratio V i of the dead volume to the simulated electrolyte volume; S330: Compare V i with the target value V* of the dead volume ratio. If V i ≤ V*, then use P i as the optimal simulated baffle parameter set P*; if V i > V*, then perform the (i + 1)-th optimization iteration operation, where V*﹤V 0 .

[0020] In this embodiment, the optimization operation of the simulated baffle parameter set in step S300 can be a cyclic optimization process, using the initial parameter set P 0 in step S100 as the starting parameter of the optimization operation. When performing the first optimization iteration, adjust the parameters of the simulated baffle based on the initial parameter set P 0 , and obtain the simulated baffle parameter set P 1; In each adjacent pair of optimization iterations, the adjustment of the simulated baffle parameters in the latter iteration is based on the simulated baffle parameters in the previous iteration.

[0021] In this embodiment, after adjusting the simulated baffle parameter set each time, a fluid circulation simulation test is carried out. After completing one electrolyte circulation simulation, the proportion V of the dead volume corresponding to this optimization iteration in the simulated electrolyte volume is obtained. i , until V i ≤ V*, the simulated baffle parameter set at this time is used as the optimal simulated baffle parameter set.

[0022] In an exemplary embodiment, "adjusting the simulated baffle parameter set P i-1 " in step S310 may include at least one of the following operations: changing the number of the simulated baffles, changing the size of at least one of the simulated baffles, and changing the position of at least one of the simulated baffles.

[0023] In this embodiment, when executing step S310, the number of simulated baffles can be increased or decreased, or the size of one or more simulated baffles can be changed, including adjusting the size of the simulated baffle, such as increasing or decreasing the length, width or thickness of the simulated baffle, or the position of the simulated baffle can be adjusted, including moving the simulated baffle along the length direction of the simulation model.

[0024] In an exemplary embodiment, "if V i > V*, then perform the (i + 1)-th optimization iteration operation" in step S330 may include step S331 or S332: S331: If V* < V i < V i-1 , when performing the (i + 1)-th optimization iteration operation, adjust the simulated baffle parameter set P i according to the same adjustment trend as in the i-th optimization iteration to obtain the simulated baffle parameter set P i+1 for the (i + 1)-th optimization iteration; S332: If V i > V i-1 , when performing the (i + 1)-th optimization iteration operation, adjust the simulated baffle parameter set P i according to the opposite adjustment trend to that in the i-th optimization iteration to obtain the simulated baffle parameter set P i+1 for the (i + 1)-th optimization iteration; In this embodiment, V i-1 is the proportion of the dead volume obtained during the (i - 1)-th optimization iteration operation in the simulated electrolyte volume.

[0025] In this embodiment, in every three adjacent optimization iterations, if the dead zone volume ratio obtained in the second iteration optimization is less than the dead zone volume ratio obtained in the first iteration optimization, it indicates that when adjusting the simulated baffle parameter set in the second iteration optimization, the trend of adjustment makes the dead zone volume ratio approach the dead zone volume ratio target value V*. Then, when performing the third iteration optimization, the simulated baffle parameter set is adjusted according to the same trend as in the second iteration optimization, so that the dead zone volume ratio obtained in the third iteration optimization further approaches V*.

[0026] In this embodiment, in every three adjacent optimization iterations, if the dead zone volume ratio obtained in the second iteration optimization is greater than the dead zone volume ratio obtained in the first iteration optimization, it indicates that when adjusting the simulated baffle parameter set in the second iteration optimization, the trend of adjustment makes the dead zone volume ratio move away from the dead zone volume ratio target value V*. Then, when performing the third iteration optimization, the simulated baffle parameter set is adjusted according to the trend opposite to that in the second iteration optimization, so that the dead zone volume ratio obtained in the third iteration optimization further approaches V*.

[0027] In this embodiment, by executing step S331 or S332, the process of optimization iteration can be accelerated, reaching the volume ratio target value V* as soon as possible and obtaining the optimal simulated baffle parameter set P* as soon as possible.

[0028] In an exemplary embodiment, step S100 may include steps S110 - S130: S110: Obtain the internal space dimensions of the container, and obtain the dimensions of the simulation housing according to the internal space dimensions, wherein the all - vanadium redox flow battery long - term liquid storage tank is located inside the container; S120: Obtain the material properties of the all - vanadium redox flow battery long - term liquid storage tank, the electrolyte volume inside the tank, and the safety space inside the tank, and construct an initial simulation model including the simulated electrolyte in combination with the dimensions of the simulation housing, wherein the volume of the simulated electrolyte is equal to the electrolyte volume; S130: On the premise of ensuring the internal connection of the initial simulation model, randomly add N simulated baffles inside the initial simulation model to generate the simulation model, wherein the plane where each simulated baffle is located is perpendicular to the length direction of the initial simulation model.

[0029] In this embodiment, the long-term liquid storage tank and the stack (or single cell) of the all-vanadium redox flow battery can be placed in a container together. When designing the simulation model, the size of the long-term liquid storage tank can be designed according to the internal space size of the container, so as to obtain the size of the simulation shell. Since a safety space is required in the long-term liquid storage tank except for the electrolyte, according to the actual design requirements of the long-term liquid storage tank of the all-vanadium redox flow battery, a certain proportion of the internal safety space of the tank is reserved, and the volume of the simulated electrolyte and the safety space are set according to the internal space volume of the simulation shell. The simulation model can be a cuboid, and any number of simulated baffle plates are randomly set inside the simulation shell. At least one side of each simulated baffle plate is not connected to the inner wall of the simulation model to ensure the internal connection of the simulation model and support the circulation of the simulated electrolyte inside the simulation model.

[0030] In an exemplary embodiment, when performing "randomly adding N of the simulated baffle plates" in step S130, the initial size and the initial position of each of the simulated baffle plates are randomly set.

[0031] In an exemplary embodiment, after step S130, step S140 may further be included: S140: For the N simulated baffle plates, obtain the initial size and the initial position of each of the simulated baffle plates; In this embodiment, each of the initial sizes includes the length, width, and thickness of the simulated baffle plate; each of the initial positions is the distance from the plane where the simulated baffle plate is located to the inner walls on both sides in the length direction of the simulation model.

[0032] In this embodiment, for each simulated baffle plate, its initial size and initial position can be randomly set; when performing step S300, the number of simulated baffle plates can be increased or decreased, and the positions and sizes of the respective simulated baffle plates can be adjusted. For example, the thickness of a certain simulated baffle plate is increased from 1 cm to 2 cm, and the position of a certain simulated baffle plate is adjusted from 1 m away from the left boundary in the length direction of the simulation model to 2 m.

[0033] In an exemplary embodiment, the computational fluid dynamics simulation tool is Fluent software.

[0034] In an exemplary embodiment, the dead zone volume at least includes the volume of the region where the velocity component of the simulated electrolyte in the length direction of the simulation model is 0.

[0035] In this embodiment, the dead zone volume may further include the dead zone at the bottom of the tank, the dead zone near the inlet and outlet of the long-term liquid storage tank, the dead zone blocked by internal components of the long-term liquid storage tank, etc.

[0036] To illustrate the simulation optimization method for the long-duration liquid storage tank of a vanadium redox flow battery in the embodiments of the present application, a specific example is used to describe in detail below, including steps S1 - S6, where step S6 includes loop steps S61 - S63: S1: Obtain the internal space dimensions of the container, and obtain the dimensions of the simulation housing according to the internal space dimensions; S2: Obtain the material properties of the long-duration liquid storage tank of the vanadium redox flow battery, the volume of the electrolyte in the tank, and the safety space in the tank. Combine the dimensions of the simulation housing to construct an initial simulation model including the simulated electrolyte; S3: While ensuring the internal connection of the initial simulation model, randomly add N simulated baffle plates inside the initial simulation model to generate the simulation model. As shown in, the plane of the simulated baffle plate is perpendicular to the length direction of the simulation model; Figure 2 Shown, the plane of the simulated baffle plate is perpendicular to the length direction of the simulation model; S4: For the N simulated baffle plates, obtain the initial dimensions and initial positions of each simulated baffle plate. Take the number of simulated baffle plates N, the initial dimensions and initial positions of each simulated baffle plate as the initial parameter set P 0 ; S5: Based on the initial parameter set P 0 And the Fluent software, conduct an initial fluid circulation simulation test on the simulation model. After completing one electrolyte circulation simulation, obtain the proportion of the dead zone volume to the volume of the simulated electrolyte as the initial proportion V 0 ; S6: According to the initial parameter set P 0 , the initial proportion V 0 And the Fluent software, perform an optimization operation for the simulated baffle plate parameter set to obtain the optimal simulated baffle plate parameter set in the simulation model, including loop steps S61 - S63: S61: Adjust the simulated baffle plate parameter set P i-1 , obtain the simulated baffle plate parameter set P used in the i-th optimization iteration i ; S62: Based on P i And the fluid dynamics simulation tool, conduct the i-th fluid circulation simulation test. After completing one electrolyte circulation simulation, obtain the proportion of the dead zone volume to the volume of the simulated electrolyte as V i ; S63: Compare V i With the dead zone volume proportion target value V*. If V i ≤V*, then take P i As the optimal simulated baffle plate parameter set P*; if V i >V*, then perform the (i + 1)-th optimization iteration operation, where V*﹤V 0 .

[0037] An embodiment of the present application also provides a simulation optimization device for a long-term storage tank of a vanadium redox flow battery, including a memory and a processor. As Figure 3 shown, it includes: The memory is used to store the simulation optimization program for the long-term storage tank of the vanadium redox flow battery; The processor is configured to read the simulation optimization program for the long-term storage tank of the vanadium redox flow battery and perform the simulation optimization method for the long-term storage tank of the vanadium redox flow battery as described in the above embodiments.

[0038] Those of ordinary skill in the art can understand that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, and their appropriate combinations. In the hardware implementation, the division of functional modules / units mentioned above does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or one function or step may be executed by several physical components in cooperation. Some or all components may be implemented as software executed by a processor, such as a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include a computer storage medium (or a non-transitory medium) and a communication medium (or a transitory medium). As is well known to those of ordinary skill in the art, the term "computer storage medium" includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cassette, tape, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, as is well known to those of ordinary skill in the art, a communication medium typically contains computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and may include any information delivery medium.

Claims

1. A simulation optimization method for a long-term liquid storage tank of an all-vanadium liquid flow battery, characterized in that: include: Constructing a simulation model of a long-term liquid storage tank of an all-vanadium liquid flow battery, wherein the simulation model includes a simulation shell, a simulated electrolyte and a plurality of simulated baffles inside the simulation shell, and an initial parameter set P0 of the simulation model includes the number N of the simulated baffles, and the initial size and initial position corresponding to each of the simulated baffles; Based on the initial parameter set and the fluid mechanics simulation tool, an initial fluid circulation simulation test is performed on the simulation model, and after completing one electrolyte circulation simulation, a ratio of the dead zone volume to the simulated electrolyte volume is obtained as an initial ratio V0; According to the initial parameter set P0, the initial ratio V0 and the fluid mechanics simulation tool, a simulation baffle parameter set optimization operation is performed to obtain the best simulation baffle parameter set in the simulation model, wherein the best simulation baffle parameter set is used to achieve the optimal design of the baffles in the long-term liquid storage tank of the all-vanadium liquid flow battery.

2. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 1, characterized in that: The performing of the simulation baffle parameter set optimization operation according to the initial parameter set P0, the initial ratio V0 and the fluid mechanics simulation tool to obtain the best simulation baffle parameter set in the simulation model includes: The following optimization iteration operations are performed cyclically, wherein the i-th optimization iteration operation includes the following steps: Adjust the simulated baffle parameter set P i-1 , obtain the simulated baffle parameter set P used in the i-th optimization iteration i , where i≥2, P i-1 is the simulation baffle parameter set used in the i-1th optimization iteration; when i=1, P i-1 is the initial parameter set P0; Based on P i The fluid mechanics simulation tool is used to perform the i-th fluid circulation simulation test. After completing one electrolyte circulation simulation, the ratio of the dead zone volume to the simulated electrolyte volume V is obtained. i ; Contrast V i and the dead zone volume ratio target value V*, if V i ≤V*, then P i As the best simulation baffle parameter set P*; if V i >V*, then the i+1th optimization iteration operation is performed, where V*﹤V0.

3. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 2, characterized in that: The adjustment simulation baffle parameter set P i-1 , including at least one of the following operations: changing the number of the simulated baffles, changing the size of at least one of the simulated baffles, and changing the position of at least one of the simulated baffles.

4. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 2, characterized in that: If V i >V*, then the i+1th optimization iteration operation is performed, including: If V*<V i <V i-1 When performing the i+1th optimization iteration, the simulated baffle parameter set P is adjusted according to the same adjustment trend as that of the i-th optimization iteration. i , and obtain the simulated baffle parameter set P used in the i+1th optimization iteration i+1 ; If V i >V i-1 When performing the i+1th optimization iteration, the simulated baffle parameter set P is adjusted according to the opposite adjustment trend of the i-th optimization iteration. i , and obtain the simulated baffle parameter set P used in the i+1th optimization iteration i+1 ; Among them, V i-1 It is the ratio of the dead zone volume obtained during the i-1th optimization iteration operation to the volume of the simulated electrolyte.

5. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 1, characterized in that: The simulation model of constructing a long-term liquid storage tank of an all-vanadium liquid flow battery comprises: Acquire the inner space size of the container, and obtain the size of the simulated shell according to the inner space size, wherein the long-term liquid storage tank of the all-vanadium liquid flow battery is located in the container; Obtaining the material properties of the long-term liquid storage tank of the all-vanadium liquid flow battery, the volume of the electrolyte in the tank, and the safety space in the tank, and building an initial simulation model including the simulated electrolyte in combination with the size of the simulation shell, wherein the volume of the simulated electrolyte is equal to the volume of the electrolyte; Under the condition that the internal connectivity of the initial simulation model is ensured, N simulated baffles are randomly added inside the initial simulation model to generate the simulation model, wherein the plane where each simulated baffle is located is perpendicular to the length direction of the initial simulation model.

6. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 5, characterized in that: The initial size and the initial position of each simulated baffle are randomly set.

7. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 5, characterized in that: After generating the simulation model, the method further includes: For the N simulated baffles, obtaining the initial size and the initial position of each simulated baffle; Among them, each of the initial dimensions includes the length, width and thickness of the simulated baffle; each of the initial positions is the distance from the plane where the simulated baffle is located to the inner walls on both sides in the length direction of the simulation model.

8. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 1, characterized in that: The fluid mechanics simulation tool is Fluent software.

9. The simulation optimization method for the long-term liquid storage tank of the all-vanadium liquid flow battery according to claim 1, characterized in that: The dead volume at least includes the volume of a region where the velocity component of the simulated electrolyte in the length direction of the simulation model is 0.

10. A simulation optimization device for a long-term liquid storage tank of an all-vanadium liquid flow battery, comprising a memory and a processor, characterized in that: The memory is used to store the simulation optimization program of the long-term liquid storage tank of the all-vanadium liquid flow battery; The processor is used to read the simulation optimization program of the long-term liquid storage tank of the all-vanadium liquid flow battery, and perform the simulation optimization method of the long-term liquid storage tank of the vanadium liquid flow battery as described in any one of claims 1-9.

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