Operation optimization method and device of electrolytic hydrogen storage device, medium and computing equipment

Abstract

The invention provides an operation optimization method and device of an electrolytic hydrogen storage device, a medium and computing equipment, and relates to the technical field of hydrogen energy. The method comprises the following steps: constructing a multi-physical field simulation model of the electrolytic hydrogen storage device; acquiring a sampling matrix containing operation parameters based on the multi-physics field simulation model; determining an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix; wherein the initial adjustment scheme comprises initial adjustment data corresponding to each operation parameter; determining an optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; and optimizing operation parameters in the multi-physics field simulation model based on the optimal adjustment scheme to obtain optimized performance indexes of the electrolytic hydrogen storage device. The running efficiency of the multi-physical field simulation model running based on the optimized performance indexes of the electrolytic hydrogen storage device can be improved, and then the electrolytic hydrogen storage device running based on the optimized performance indexes of the electrolytic hydrogen storage device can achieve the optimal performance.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of hydrogen energy technology. More specifically, embodiments of the present invention relate to an operation optimization method, device, medium and computing equipment for an electrolytic hydrogen storage device. Background Art

[0002] This section is intended to provide a background or context to embodiments of the invention that are recited in the claims. No description herein is admitted to be prior art by inclusion in this section.

[0003] Large-scale deployment of renewable energy is a key strategy to address greenhouse gas emissions and energy crises. However, the instability and intermittent nature of these energy sources pose significant challenges to the stable operation of the power system. In this context, hydrogen energy, with its excellent clean properties and high energy density, is gradually becoming a strong candidate for smoothing fluctuations in energy supply and demand.

[0004] As an important part of the hydrogen energy industry chain, water electrolysis hydrogen production technology. Traditional electrolytic hydrogen storage devices mostly use alkaline electrolytic cells and operate at room temperature and pressure. Their electrolysis efficiency is relatively low, and it is impossible to adjust the operating parameters in the electrolytic hydrogen storage device in a targeted manner, which makes it difficult for the electrolytic hydrogen storage device to achieve optimal performance. Summary of the invention

[0005] In this context, embodiments of the present invention are intended to provide a method, device, medium, and computing equipment for optimizing the operation of an electrolytic hydrogen storage device.

[0006] In a first aspect of an embodiment of the present invention, there is provided a method for optimizing the operation of an electrolytic hydrogen storage device, comprising:

[0007] Construct a multi-physics simulation model of an electrolytic hydrogen storage device;

[0008] Acquire a sampling matrix containing operating parameters based on the multi-physics field simulation model; wherein the operating parameters at least include current, inlet gas flow rate, inlet pressure, and inlet gas temperature in the multi-physics field simulation model;

[0009] Based on the sampling matrix, determining an initial adjustment scheme of the multi-physics field simulation model; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter;

[0010] Based on the sampling matrix and the initial adjustment scheme, determining an optimal adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter;

[0011] Based on the optimal adjustment scheme, the operating parameters in the multi-physical field simulation model are optimized to obtain the optimized performance indicators of the electrolytic hydrogen storage device.

[0012] In one embodiment of this implementation, determining an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix includes:

[0013] randomly determining initial operating parameters from the sampling matrix;

[0014] Based on the initial operating parameters and preset standardized operating parameters, determining a plurality of candidate initial adjustment schemes;

[0015] Calculating the device efficiency value of each candidate initial adjustment scheme;

[0016] The candidate initial adjustment scheme with the largest device efficiency value is determined as the initial adjustment scheme of the multi-physics field simulation model.

[0017] In an example of this implementation manner, determining the optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme includes:

[0018] Acquire candidate operating parameters corresponding to the initial operating parameters from the sampling matrix; wherein the positions of the candidate operating parameters in the sampling matrix are adjacent to the positions of the initial operating parameters in the sampling matrix;

[0019] Determine candidate adjustment schemes corresponding to each candidate operating parameter;

[0020] Based on the initial adjustment scheme, calculate the scheme parameters of each candidate adjustment scheme;

[0021] Calculate the global sensitivity data of each candidate adjustment scheme;

[0022] Based on the scheme parameters of each candidate adjustment scheme and the global sensitivity data, each candidate adjustment scheme is updated to obtain an updated candidate adjustment scheme;

[0023] Calculate and obtain the device efficiency value of each updated candidate adjustment scheme;

[0024] From the initial adjustment scheme and the updated candidate adjustment schemes, the initial adjustment scheme or the updated candidate adjustment scheme corresponding to the maximum device efficiency value is determined as the optimal adjustment scheme.

[0025] In an example of this implementation, the scheme parameters include at least a distance value, a gravity value, and a speed value. The scheme parameters of each candidate adjustment scheme are calculated based on the initial adjustment scheme, including:

[0026] Calculate the distance between each candidate adjustment solution and the initial adjustment solution;

[0027] Based on the distance value and the first random number, calculate the attraction value between each candidate adjustment solution and the initial adjustment solution;

[0028] Based on the distance value, the speed value of each candidate adjustment solution is calculated.

[0029] In one embodiment of this implementation, the calculation formula for the global sensitivity data of the candidate adjustment scheme is:

[0030]

[0031] Δ=L / 2(LW)

[0032] Wherein, γ is the global sensitivity data, r represents the sampling number of the kth influencing factor, μ represents the basic effect average value of the operating parameter obtained by sampling; f(x) represents the device efficiency value, X W , X2, ...X k represents the candidate adjustment data corresponding to each operating parameter included in the candidate adjustment scheme, and L represents the number of equal parts of the value range of each candidate adjustment data.

[0033] In an example of this implementation manner, updating each candidate adjustment scheme based on the scheme parameters of each candidate adjustment scheme and the global sensitivity data to obtain an updated candidate adjustment scheme includes:

[0034] Randomly generate a current random number and randomly select a first random candidate adjustment scheme and a second random candidate adjustment scheme from the candidate adjustment schemes;

[0035] If the first random number is greater than the current random number, then based on the first random candidate adjustment scheme, the second random candidate adjustment scheme and the initial adjustment scheme, each candidate adjustment scheme is updated to obtain a first candidate adjustment scheme;

[0036] If the first random number is less than or equal to the current random number, the candidate adjustment schemes are sorted in descending order according to the global sensitivity data to obtain an update sequence of the candidate adjustment schemes, and based on the initial adjustment scheme, the gravity value, and the speed value, the candidate adjustment schemes in the update sequence are updated in sequence to obtain a second candidate adjustment scheme;

[0037] The first candidate adjustment scheme / the second candidate adjustment scheme and the unupdated candidate adjustment scheme are calculated based on a target algorithm to obtain an updated candidate adjustment scheme.

[0038] In one embodiment of this implementation, the first candidate adjustment scheme / the second candidate adjustment scheme and the unupdated candidate adjustment scheme are calculated based on the target algorithm, and the formula for obtaining the updated candidate adjustment scheme is expressed as follows:

[0039]

[0040] in, represents the updated candidate adjustment scheme, represents the first candidate adjustment scheme / the second candidate adjustment scheme, Indicates the candidate adjustment scheme that has not been updated.

[0041] In a second aspect of an embodiment of the present invention, there is provided an operation optimization device for an electrolytic hydrogen storage device, comprising:

[0042] A construction unit, used to construct a multi-physics simulation model of an electrolytic hydrogen storage device;

[0043] An acquisition unit, configured to acquire a sampling matrix containing operating parameters based on the multi-physics field simulation model; wherein the operating parameters at least include current, inlet gas flow rate, inlet pressure, and inlet gas temperature in the multi-physics field simulation model;

[0044] A first determining unit is used to determine an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter;

[0045] A second determining unit, configured to determine an optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter;

[0046] An optimization unit is used to optimize the operating parameters in the multi-physics field simulation model based on the optimal adjustment scheme to obtain the performance indicators of the optimized electrolytic hydrogen storage device.

[0047] In a third aspect of an embodiment of the present invention, a computing device is provided, comprising: at least one processor, a memory, and an input-output unit; wherein the memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute any one of the methods described in the first aspect.

[0048] In a fourth aspect of the embodiments of the present invention, a computer-readable storage medium is provided, which includes instructions, and when the instructions are executed on a computer, the computer executes the method described in any one of the first aspects.

[0049] According to the operation optimization method, device, medium and computing equipment of the electrolytic hydrogen storage device according to the embodiment of the present invention, the electrolytic hydrogen storage device can be simulated to obtain a multi-physical field simulation model, and the operating parameters that can affect the operating efficiency of the multi-physical field simulation model can be obtained based on the obtained multi-physical field simulation model to obtain a sampling matrix containing the operating parameters, and an initial adjustment scheme for the multi-physical field simulation model can be first determined based on the sampling matrix, and then the optimal adjustment scheme can be determined by calculating the sampling matrix and the initial adjustment scheme. Based on the optimal adjustment scheme, the operating parameters in the multi-physical field simulation model can be optimized to obtain the performance indicators of the optimized electrolytic hydrogen storage device, thereby improving the operating efficiency of the multi-physical field simulation model that operates based on the performance indicators of the optimized electrolytic hydrogen storage device, and further enabling the electrolytic hydrogen storage device that operates based on the performance indicators of the optimized electrolytic hydrogen storage device to achieve optimal performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, in which:

[0051] Figure 1 A schematic flow chart of an operation optimization method of an electrolytic hydrogen storage device provided in one embodiment of the present invention;

[0052] Figure 2 for Figure 1 A detailed flow chart of step S104;

[0053] Figure 3 A schematic diagram of the structure of an operation optimization device for an electrolytic hydrogen storage device provided in one embodiment of the present invention;

[0054] Figure 4 A schematic structural diagram of an electrolytic hydrogen storage device provided in one embodiment of the present invention;

[0055] Figure 5 A schematic diagram of the structure of a medium according to an embodiment of the present invention is schematically shown;

[0056] Figure 6 A schematic diagram of the structure of a computing device according to an embodiment of the present invention is schematically shown.

[0057] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts. DETAILED DESCRIPTION

[0058] The principles and spirit of the present invention will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are provided only to enable those skilled in the art to better understand and implement the present invention, and are not intended to limit the scope of the present invention in any way. On the contrary, these embodiments are provided to make the present disclosure more thorough and complete, and to fully convey the scope of the present disclosure to those skilled in the art.

[0059] Those skilled in the art will appreciate that the embodiments of the present invention may be implemented as a system, device, apparatus, method or computer program product. Therefore, the present disclosure may be specifically implemented in the following forms, namely: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.

[0060] According to an embodiment of the present invention, an operation optimization method, device, medium and computing equipment of an electrolytic hydrogen storage device are proposed.

[0061] It should be noted that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction and does not have any limiting meaning.

[0062] The principle and spirit of the present invention are explained in detail below with reference to several representative embodiments of the present invention.

[0063] Exemplary Methods

[0064] Reference below Figure 1 , Figure 1 A schematic diagram of a flow chart of an operation optimization method of an electrolytic hydrogen storage device provided in an embodiment of the present invention. It should be noted that the embodiments of the present invention can be applied to any applicable scenario.

[0065] Figure 1 The process of the operation optimization method of the electrolytic hydrogen storage device provided by one embodiment of the present invention includes:

[0066] Step S101, constructing a multi-physical field simulation model of an electrolytic hydrogen storage device.

[0067] In the embodiment of the present invention, the multi-physics field simulation model can be constructed by using the finite element method and can be completed using COMSOL multi-physics field simulation software.

[0068] In an embodiment of the present invention, the electrolytic hydrogen storage device includes a high-temperature proton exchange membrane electrolytic cell and a metal solid-state hydrogen storage unit, and the multi-physics field simulation model includes an electrochemical reaction module, a chemical reaction module, a mass transfer module, a momentum transfer module, a heat transfer module of the high-temperature proton exchange membrane electrolytic cell, and a heat transfer module of the metal solid-state hydrogen storage unit.

[0069] Among them, the electrochemical module is responsible for calculating the reaction rate of electrolyzing water to produce hydrogen in the electrolytic hydrogen storage device, the chemical module is responsible for calculating the adsorption / desorption rate of the metal solid hydrogen storage unit in the electrolytic hydrogen storage device, the mass transfer module is responsible for calculating the material transfer of the gas in the electrolytic hydrogen storage device, the heat transfer module of the high-temperature proton exchange membrane electrolyzer is responsible for calculating the temperature of the high-temperature proton exchange membrane fuel cell, and the heat transfer module of the metal solid hydrogen storage unit is responsible for calculating the temperature of the metal solid hydrogen storage unit.

[0070] In the embodiment of the present invention, the electrochemical reaction module can be constructed using the Butler–Volme equation, which is expressed as:

[0071]

[0072] Where i represents the working current density, α is the transfer coefficient, i0 is the exchange current density, n is the number of transferred electrons in the electrolysis reaction, η act is the activation overpotential, F is the Faraday constant, T is the temperature, and R is the gas constant, also known as the Universal Gas Constant, which is 8.314 J / (mol·K).

[0073] In the embodiment of the present invention, the chemical reaction module can be calculated using COMSOL commercial software and can be expressed as:

[0074]

[0075] Where C represents the kinetic constant, E represents the activation energy, p represents the equilibrium pressure, and T represents the temperature. is the saturation density of the solid material, ρ s It is the density of the solid material when all metal hydrides are converted into alloys and hydrogen. eqa It represents the equilibrium pressure, specifically the equilibrium pressure between metal hydride and hydrogen. In the solid-state hydrogen storage process, the pressure when hydrogen reaches equilibrium with the hydrogen storage material at a certain temperature and pressure. It indicates the actual pressure of hydrogen, that is, the current pressure of hydrogen in the system. The difference between this pressure and the equilibrium pressure determines whether the reaction proceeds in the direction of absorbing hydrogen or releasing hydrogen. s It indicates the hydrogen storage capacity of solid materials, that is, the saturation of hydrogen stored in metal hydrides. This value is closely related to the saturation density of the hydrogen storage material and the current state of the hydride.

[0076] The mass transfer module is represented as:

[0077]

[0078] Among them, Ni Defined as the mass transfer, y i is the mole fraction of the operating parameter i, B0 is the permeability coefficient, μ represents the gas viscosity, represents the effective diffusion coefficient of the operating parameter i, p represents the pressure, and T represents the temperature.

[0079] The momentum transfer module is expressed as:

[0080]

[0081] Wherein, ρ represents the density of the porous medium in the electrolytic cell, and u represents the flow rate.

[0082] The heat transfer module is represented as:

[0083]

[0084] Among them, C p represents the heat capacity of the fluid, λ eff represents effective thermal conductivity, Q represents reaction heat source (reaction heat source can be heat in electrochemical reaction), and T represents temperature.

[0085] In the embodiment of the present invention, the heat transfer module can be expressed as:

[0086]

[0087] Among them, (ρC p ) e represents the effective heat capacity, k e represents thermal conductivity, C p，g is the isobaric heat capacity of gas, ρ g represents the gas density, C p，s is the heat capacity of metal, ρ s represents the metal density, v represents the hydrogen flux, m represents the hydrogen mass reaction rate, and ΔH is the enthalpy change.

[0088] Step S102: acquiring a sampling matrix including operating parameters based on the multi-physics field simulation model.

[0089] In an embodiment of the present invention, the operating parameters include at least the current, inlet gas flow rate, inlet pressure and inlet gas temperature in the multi-physics field simulation model.

[0090] In the embodiment of the present invention, the Latin Hypercube Sampling (LHS) method can be used to construct a sampling matrix to ensure that the sampling points of key operating parameters such as current, inlet gas flow rate, inlet pressure, and inlet gas temperature fully cover the entire parameter space, thereby obtaining a sampling matrix. Through this strategy, the parameter space can be efficiently explored, providing a solid data foundation for the operation optimization of the electrolytic hydrogen storage device.

[0091] Step S103: determining an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix.

[0092] In an embodiment of the present invention, the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter. When the multi-physics field simulation model is initially constructed, the initial adjustment data of each operating parameter needs to be set in advance. Therefore, the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter.

[0093] As an optional implementation, the method of determining the initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix in step S103 may include:

[0094] randomly determining initial operating parameters from the sampling matrix;

[0095] Based on the initial operating parameters and preset standardized operating parameters, determining a plurality of candidate initial adjustment schemes;

[0096] Calculating the device efficiency value of each candidate initial adjustment scheme;

[0097] The candidate initial adjustment scheme with the largest device efficiency value is determined as the initial adjustment scheme of the multi-physics field simulation model.

[0098] In the embodiment of the present invention, there may be multiple standardized operating parameters corresponding to each operating parameter, and the value of the standardized operating parameter corresponding to each operating parameter has a preset value range, and the preset standardized operating parameters are all within the preset value range.

[0099] Step S104, determining an optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter.

[0100] Please also read Figure 2 , Figure 2 It is a detailed flow chart of step S104;

[0101] Step S201: Acquire candidate operating parameters corresponding to the initial operating parameters from the sampling matrix.

[0102] In the embodiment of the present invention, the position of the candidate operating parameter in the sampling matrix is ​​adjacent to the position of the initial operating parameter in the sampling matrix.

[0103] Step S202: determine candidate adjustment schemes corresponding to the candidate operating parameters.

[0104] Step S203: Based on the initial adjustment scheme, calculate the scheme parameters of each candidate adjustment scheme.

[0105] In the embodiment of the present invention, the scheme parameters at least include a distance value, a gravity value and a speed value.

[0106] As an optional implementation, the method of calculating the scheme parameters of each candidate adjustment scheme based on the initial adjustment scheme in step S203 may include:

[0107] Calculate the distance between each candidate adjustment solution and the initial adjustment solution;

[0108] Based on the distance value and the first random number, calculate the attraction value between each candidate adjustment solution and the initial adjustment solution;

[0109] Based on the distance value, the speed value of each candidate adjustment solution is calculated.

[0110] In the embodiment of the present invention, the distance value may be the Euclidean distance, and the distance value R i The calculation formula of (t) can be:

[0111]

[0112] Among them, X S (t) represents the initial adjustment plan, X i (t) represents the candidate adjustment scheme.

[0113] In the embodiment of the present invention, the gravitational value The calculation formula can be:

[0114]

[0115] Among them, M s With m i Represents X S (t) and X i The mass of (t), and Represents M s With m i The normalized value of ε represents a very small positive number, e iis the planet orbit eccentricity (a value between 0 and 1), r1 is the first random number between 0 and 1 used to provide more variation to the gravity value during the optimization process, YesR i The normalized value of (t) based on the square of the distance emphasizes the candidate adjustment solutions with larger distances, which are used to further optimize the solutions far away from the optimal solution.

[0116] Among them, the mass M s With m i Defined by:

[0117]

[0118] in:

[0119]

[0120] Among them, μ(t) is a function that decreases exponentially with time (t) to control the search accuracy, which is expressed as follows:

[0121]

[0122] Among them, α is a constant, μ0 is the initial value, t and T max is the current and maximum number of iterations for manipulating parameters in a multiphysics simulation model.

[0123] In the embodiment of the present invention, the speed value V i The calculation formula of (t) can be:

[0124]

[0125] Among them, r3 and r4 represent random numbers between 0 and 1. and represents a random vector between 0 and 1, as well as represents the candidate adjustment scheme, R i-norm (t) represents R i The direct normalized value of (t) reflects the distance between the candidate adjustment scheme at the current moment and the optimal solution, which is defined as follows:

[0126]

[0127] In addition, the intermediate variable and U2 is expressed as follows:

[0128]

[0129] Among them, a i(t) represents the semi-major axis of the elliptical orbit of object i at time t.

[0130] Step S204: calculate and obtain the global sensitivity data of each candidate adjustment scheme.

[0131] In the embodiment of the present invention, the calculation formula of the global sensitivity data of the candidate adjustment scheme is:

[0132]

[0133] Δ=L / 2(L-1)

[0134] Wherein, γ is the global sensitivity data, r represents the sampling number of the kth influencing factor, μ represents the basic effect average value of the operating parameters obtained by sampling; f(x) represents the device efficiency value, X1, X2, ···X k represents the candidate adjustment data corresponding to each operating parameter included in the candidate adjustment scheme, and L represents the number of equal parts of the value range of each candidate adjustment data.

[0135] Step S205 , updating each candidate adjustment scheme based on the scheme parameters of each candidate adjustment scheme and the global sensitivity data to obtain an updated candidate adjustment scheme.

[0136] As an optional implementation, step S205 updates each candidate adjustment scheme based on the scheme parameters of each candidate adjustment scheme and the global sensitivity data, and the method of obtaining the updated candidate adjustment scheme may include:

[0137] Randomly generate a current random number and randomly select a first random candidate adjustment scheme and a second random candidate adjustment scheme from the candidate adjustment schemes;

[0138] If the first random number is greater than the current random number, then based on the first random candidate adjustment scheme, the second random candidate adjustment scheme and the initial adjustment scheme, each candidate adjustment scheme is updated to obtain a first candidate adjustment scheme;

[0139] If the first random number is less than or equal to the current random number, the candidate adjustment schemes are sorted in descending order according to the global sensitivity data to obtain an update sequence of the candidate adjustment schemes, and based on the initial adjustment scheme, the gravity value, and the speed value, the candidate adjustment schemes in the update sequence are updated in sequence to obtain a second candidate adjustment scheme;

[0140] The first candidate adjustment scheme / the second candidate adjustment scheme and the unupdated candidate adjustment scheme are calculated based on a target algorithm to obtain an updated candidate adjustment scheme.

[0141] In the embodiment of the present invention, based on the first random candidate adjustment scheme, the second random candidate adjustment scheme and the initial adjustment scheme, each candidate adjustment scheme is updated to obtain a first candidate adjustment scheme The formula can be:

[0142]

[0143] Where h is the adaptation factor, defined as follows:

[0144]

[0145] Where r is the current random number randomly generated based on a normal distribution, and η is a linear decreasing factor from 1 to -2.

[0146] In the embodiment of the present invention, based on the initial adjustment scheme, the gravity value and the speed value, the candidate adjustment schemes in the update sequence are updated in sequence to obtain a second candidate adjustment scheme. The formula can be:

[0147]

[0148] In the embodiment of the present invention, the first candidate adjustment scheme / the second candidate adjustment scheme and the unupdated candidate adjustment scheme are calculated based on the target algorithm, and the formula for obtaining the updated candidate adjustment scheme is expressed as follows:

[0149]

[0150] in, represents the updated candidate adjustment scheme, represents the first candidate adjustment scheme / the second candidate adjustment scheme, Indicates the candidate adjustment scheme that has not been updated.

[0151] Step S206, calculating and obtaining the device efficiency value of each updated candidate adjustment scheme.

[0152] Step S207 : From the initial adjustment scheme and the updated candidate adjustment schemes, determine the initial adjustment scheme or the updated candidate adjustment scheme corresponding to the maximum device efficiency value as the optimal adjustment scheme.

[0153] like Figure 2 As shown, the global sensitivity data of the parameters near the electrolytic hydrogen storage operating parameters are calculated each time, and the parameters with high global sensitivity data are adjusted first when adjusting the optimal parameters, and the fitness is set to the optimal efficiency of the electrolytic hydrogen storage device.

[0154] These specific improvements are intended to optimize the algorithm's search strategy to more effectively explore the parameter space and accurately locate the optimal solution. Through these improvements, the present invention can more quickly adjust the operating parameters of the electrolytic hydrogen storage device, thereby achieving higher operating efficiency.

[0155] Step S105, optimizing the operating parameters in the multi-physics field simulation model based on the optimal adjustment scheme to obtain the optimized performance indicators of the electrolytic hydrogen storage device.

[0156] After step S105, the current number of iterations of the operating parameters in the multi-physics field simulation model can be judged. If the current number of iterations reaches the preset maximum number of iterations, the iteration of the operating parameters in the multi-physics field simulation model can be ended; if the current number of iterations does not reach the preset maximum number of iterations, the optimal adjustment plan can be used as the initial adjustment plan, and steps S104 to S105 can be continued.

[0157] In addition, the previous device efficiency value of the previous optimal adjustment scheme can be obtained, and the difference between the device efficiency value of the current optimal adjustment scheme and the previous device efficiency value can be calculated. If the difference is less than the preset threshold, the iteration of the operating parameters in the multi-physical field simulation model can be ended; if the difference is greater than or equal to the preset threshold, the optimal adjustment scheme can be used as the initial adjustment scheme, and steps S104 to S105 can be continued.

[0158] The present invention can simulate an electrolytic hydrogen storage device to obtain a multi-physical field simulation model, and can obtain operating parameters that can affect the operating efficiency of the multi-physical field simulation model based on the obtained multi-physical field simulation model, and obtain a sampling matrix containing the operating parameters, and can first determine an initial adjustment scheme for the multi-physical field simulation model based on the sampling matrix, and then determine the optimal adjustment scheme by calculating the sampling matrix and the initial adjustment scheme. Based on the optimal adjustment scheme, the operating parameters in the multi-physical field simulation model can be optimized to obtain the performance indicators of the optimized electrolytic hydrogen storage device, thereby improving the operating efficiency of the multi-physical field simulation model that operates based on the performance indicators of the optimized electrolytic hydrogen storage device, and further enabling the electrolytic hydrogen storage device that operates based on the performance indicators of the optimized electrolytic hydrogen storage device to achieve optimal performance.

[0159] Exemplary Devices

[0160] After introducing the method of the exemplary embodiment of the present invention, next, refer to Figure 3 An operation optimization device for an electrolytic hydrogen storage device according to an exemplary embodiment of the present invention is described, and the device comprises:

[0161] A construction unit 301 is used to construct a multi-physics field simulation model of an electrolytic hydrogen storage device;

[0162] An acquisition unit 302 is used to acquire a sampling matrix containing operating parameters based on the multi-physics field simulation model; wherein the operating parameters at least include current, inlet gas flow rate, inlet pressure and inlet gas temperature in the multi-physics field simulation model;

[0163] A first determining unit 303 is used to determine an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter;

[0164] A second determining unit 304 is configured to determine an optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter;

[0165] The optimization unit 305 is used to optimize the operating parameters in the multi-physics field simulation model based on the optimal adjustment scheme to obtain the performance indicators of the optimized electrolytic hydrogen storage device.

[0166] The present invention can simulate an electrolytic hydrogen storage device to obtain a multi-physical field simulation model, and can obtain operating parameters that can affect the operating efficiency of the multi-physical field simulation model based on the obtained multi-physical field simulation model, and obtain a sampling matrix containing the operating parameters, and can first determine an initial adjustment scheme for the multi-physical field simulation model based on the sampling matrix, and then determine the optimal adjustment scheme by calculating the sampling matrix and the initial adjustment scheme. Based on the optimal adjustment scheme, the operating parameters in the multi-physical field simulation model can be optimized to obtain the performance indicators of the optimized electrolytic hydrogen storage device, thereby improving the operating efficiency of the multi-physical field simulation model that operates based on the performance indicators of the optimized electrolytic hydrogen storage device, and further enabling the electrolytic hydrogen storage device that operates based on the performance indicators of the optimized electrolytic hydrogen storage device to achieve optimal performance.

[0167] In addition, reference Figure 4 An electrolytic hydrogen storage device according to an exemplary embodiment of the present invention is described, and the electrolytic hydrogen storage device includes a high-temperature proton exchange membrane electrolysis cell, a metal solid hydrogen storage unit, an evaporator, a first heater, a second heater, a first circulation pump, a second circulation pump, a separation device, and an emptying device, wherein:

[0168] The high temperature proton exchange membrane electrolyzer comprises an anode, a cathode and an electrolyte, and the high temperature proton exchange membrane electrolyzer is used to electrolyze water vapor to obtain hydrogen;

[0169] The evaporator is used to evaporate the input water into water vapor and input the water vapor to the first heater;

[0170] The first heater is used to heat the water vapor input by the first circulation pump and the evaporator, and input the heated water vapor to the anode;

[0171] The anode is used to input the oxygen obtained after the electrolysis of water vapor and the un-electrolyzed water vapor into the separation device;

[0172] The separation device is used to separate the oxygen from the un-electrolyzed water vapor, and input the oxygen to the emptying device, and input the un-electrolyzed water vapor to the first circulation pump;

[0173] The exhaust device is used to discharge the oxygen;

[0174] The second heater is used to heat the hydrogen input by the second circulation pump and input the heated hydrogen into the cathode;

[0175] The cathode is used to input hydrogen after the electrolysis process is completed into the second circulation pump;

[0176] The second circulation pump is used to input a part of the hydrogen into the second heater, and another part of the hydrogen into the metal solid-state hydrogen storage unit;

[0177] The metal solid-state hydrogen storage unit is used to store the received hydrogen.

[0178] In the embodiment of the present invention, both the cathode and anode of the high-temperature proton exchange membrane electrolyzer adopt an exhaust gas circulation structure design, and water vapor with a temperature range of 120°C to 200°C is introduced into the anode side, while hydrogen generated during the electrolysis process is introduced into the cathode side as a carrier gas. This structural design is intended to efficiently recover the heat energy in the incompletely reacted reactants and exhaust gas, thereby significantly improving the energy efficiency of the electrolytic hydrogen storage device.

[0179] The metal solid-state hydrogen storage unit adopts LaNi5 alloy and metal solid-state hydrogen storage technology, which can achieve high-density hydrogen storage in a limited space. This design not only optimizes the volume efficiency of the electrolytic hydrogen storage device, but also improves the overall hydrogen storage capacity. Through these innovative designs, the electrolytic hydrogen storage device of the present invention shows significant technical advantages in improving energy efficiency and hydrogen storage density.

[0180] Exemplary Media

[0181] After introducing the method and apparatus of the exemplary embodiment of the present invention, next, reference is made to Figure 5For a description of a computer-readable storage medium according to an exemplary embodiment of the present invention, please refer to Figure 5 , the computer-readable storage medium shown is a CD 50, on which a computer program (i.e., a program product) is stored. When the computer program is executed by the processor, it will implement the steps described in the above method implementation, for example, constructing a multi-physics field simulation model of an electrolytic hydrogen storage device; obtaining a sampling matrix containing operating parameters based on the multi-physics field simulation model; wherein the operating parameters at least include the current, inlet gas flow rate, inlet pressure, and inlet gas temperature in the multi-physics field simulation model; determining an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter; determining an optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter; optimizing the operating parameters in the multi-physics field simulation model based on the optimal adjustment scheme to obtain the optimized performance indicators of the electrolytic hydrogen storage device; the specific implementation method of each step will not be repeated here.

[0182] It should be noted that examples of the computer-readable storage medium may also include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other optical or magnetic storage media, which are not listed here one by one.

[0183] Exemplary Computing Devices

[0184] After introducing the method, apparatus and medium of the exemplary embodiments of the present invention, next, reference is made to Figure 6 A computing device for optimizing the operation of an electrolytic hydrogen storage device according to an exemplary embodiment of the present invention.

[0185] Figure 6 A block diagram of an exemplary computing device 60, which may be a computer system or a server, is shown that is suitable for use in implementing embodiments of the present invention. Figure 6 The computing device 60 shown is only an example and should not bring any limitation to the functionality and scope of use of the embodiments of the present invention.

[0186] like Figure 6 As shown, the components of the computing device 60 may include, but are not limited to: one or more processors or processing units 601, a system memory 602, and a bus 603 connecting different system components (including the system memory 602 and the processing unit 601).

[0187] The computing device 60 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computing device 60, including volatile and non-volatile media, removable and non-removable media.

[0188] The system memory 602 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 6021 and / or cache memory 6022. The computing device 60 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the ROM 6023 may be used to read and write non-removable, non-volatile magnetic media ( Figure 6 is not shown in the Figure 6 As shown in FIG. 6 , a disk drive for reading and writing a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing a removable non-volatile optical disk (e.g., a CD-ROM, a DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 603 via one or more data medium interfaces. System memory 602 may include at least one program product having a set (e.g., at least one) of program modules that are configured to perform the functions of various embodiments of the present invention.

[0189] A program / utility 6025 having a set (at least one) of program modules 6024 may be stored, for example, in system memory 602, and such program modules 6024 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment. Program modules 6024 generally perform the functions and / or methods of the embodiments described herein.

[0190] The computing device 60 may also communicate with one or more external devices 604 (e.g., a keyboard, a pointing device, a display, etc.). Such communication may be performed via an input / output (I / O) interface 605. Furthermore, the computing device 60 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 606. Figure 6 As shown, the network adapter 606 communicates with other modules (such as the processing unit 601, etc.) of the computing device 60 via the bus 603. It should be understood that although Figure 6 Not shown, other hardware and / or software modules may be used in conjunction with computing device 60 .

[0191] The processing unit 601 executes various functional applications and data processing by running the program stored in the system memory 602, for example, constructing a multi-physics simulation model of an electrolytic hydrogen storage device; obtaining a sampling matrix containing operating parameters based on the multi-physics simulation model; wherein the operating parameters at least include the current, inlet gas flow rate, inlet pressure and inlet gas temperature in the multi-physics simulation model; determining the initial adjustment scheme of the multi-physics simulation model based on the sampling matrix; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter; determining the optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter; optimizing the operating parameters in the multi-physics simulation model based on the optimal adjustment scheme to obtain the optimized performance indicators of the electrolytic hydrogen storage device. The specific implementation methods of each step will not be repeated here. It should be noted that although several units / modules or sub-units / sub-modules of the operation optimization device of the electrolytic hydrogen storage device are mentioned in the above detailed description, this division is only exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0192] In the description of the present invention, it should be noted that the terms “first”, “second” and “third” are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0193] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0194] In the several embodiments provided by the present invention, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0195] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0196] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0197] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0198] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

[0199] In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that the operations must be performed in this specific order, or that all the operations shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

Claims

1. An operation optimization method for an electrolytic hydrogen storage device, characterized in that: include: Construct a multi-physics simulation model of an electrolytic hydrogen storage device; Acquire a sampling matrix containing operating parameters based on the multi-physics field simulation model; wherein the operating parameters at least include current, inlet gas flow rate, inlet pressure, and inlet gas temperature in the multi-physics field simulation model; Based on the sampling matrix, determining an initial adjustment scheme of the multi-physics field simulation model; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter; Based on the sampling matrix and the initial adjustment scheme, determining an optimal adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter; Based on the optimal adjustment scheme, the operating parameters in the multi-physical field simulation model are optimized to obtain the optimized performance indicators of the electrolytic hydrogen storage device.

2. The operation optimization method of the electrolytic hydrogen storage device according to claim 1, characterized in that: The step of determining an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix includes: randomly determining initial operating parameters from the sampling matrix; Based on the initial operating parameters and preset standardized operating parameters, determining a plurality of candidate initial adjustment schemes; Calculating the device efficiency value of each candidate initial adjustment scheme; The candidate initial adjustment scheme with the largest device efficiency value is determined as the initial adjustment scheme of the multi-physics field simulation model.

3. The operation optimization method of the electrolytic hydrogen storage device according to claim 2, characterized in that: The determining of the optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme includes: Acquire candidate operating parameters corresponding to the initial operating parameters from the sampling matrix; wherein the positions of the candidate operating parameters in the sampling matrix are adjacent to the positions of the initial operating parameters in the sampling matrix; Determine candidate adjustment schemes corresponding to each candidate operating parameter; Based on the initial adjustment scheme, calculate the scheme parameters of each candidate adjustment scheme; Calculate the global sensitivity data of each candidate adjustment scheme; Based on the scheme parameters of each candidate adjustment scheme and the global sensitivity data, each candidate adjustment scheme is updated to obtain an updated candidate adjustment scheme; Calculate and obtain the device efficiency value of each updated candidate adjustment scheme; From the initial adjustment scheme and the updated candidate adjustment schemes, the initial adjustment scheme or the updated candidate adjustment scheme corresponding to the maximum device efficiency value is determined as the optimal adjustment scheme.

4. The operation optimization method of the electrolytic hydrogen storage device according to claim 3, characterized in that: The scheme parameters include at least a distance value, a gravity value, and a speed value. The scheme parameters of each candidate adjustment scheme are calculated based on the initial adjustment scheme, including: Calculate the distance between each candidate adjustment solution and the initial adjustment solution; Based on the distance value and the first random number, calculate the attraction value between each candidate adjustment solution and the initial adjustment solution; Based on the distance value, the speed value of each candidate adjustment solution is calculated.

5. The operation optimization method of the electrolytic hydrogen storage device according to claim 3 or 4, characterized in that: The calculation formula of the global sensitivity data of the candidate adjustment scheme is: Δ=L / 2(L-1) Wherein, γ is the global sensitivity data, r represents the sampling number of the kth influencing factor, μ represents the basic effect average value of the sampling operating parameters; f(x) represents the device efficiency value, X1, X2, ...X k represents the candidate adjustment data corresponding to each operating parameter included in the candidate adjustment scheme, and L represents the number of equal parts of the value range of each candidate adjustment data.

6. The operation optimization method of the electrolytic hydrogen storage device according to claim 4, characterized in that: The updating of each candidate adjustment scheme based on the scheme parameters of each candidate adjustment scheme and the global sensitivity data to obtain an updated candidate adjustment scheme includes: Randomly generate a current random number and randomly select a first random candidate adjustment scheme and a second random candidate adjustment scheme from the candidate adjustment schemes; If the first random number is greater than the current random number, then based on the first random candidate adjustment scheme, the second random candidate adjustment scheme and the initial adjustment scheme, each candidate adjustment scheme is updated to obtain a first candidate adjustment scheme; If the first random number is less than or equal to the current random number, the candidate adjustment schemes are sorted in descending order according to the global sensitivity data to obtain an update sequence of the candidate adjustment schemes, and based on the initial adjustment scheme, the gravity value, and the speed value, the candidate adjustment schemes in the update sequence are updated in sequence to obtain a second candidate adjustment scheme; The first candidate adjustment scheme / the second candidate adjustment scheme and the unupdated candidate adjustment scheme are calculated based on a target algorithm to obtain an updated candidate adjustment scheme.

7. The operation optimization method of the electrolytic hydrogen storage device according to claim 6, characterized in that: The first candidate adjustment scheme / the second candidate adjustment scheme and the unupdated candidate adjustment scheme are calculated based on the target algorithm to obtain the updated candidate adjustment scheme as follows: in, represents the updated candidate adjustment scheme, represents the first candidate adjustment scheme / the second candidate adjustment scheme, Indicates the candidate adjustment scheme that has not been updated.

8. An operation optimization device for an electrolytic hydrogen storage device, characterized in that: include: A construction unit, used to construct a multi-physics simulation model of an electrolytic hydrogen storage device; An acquisition unit, configured to acquire a sampling matrix containing operating parameters based on the multi-physics field simulation model; wherein the operating parameters at least include current, inlet gas flow rate, inlet pressure, and inlet gas temperature in the multi-physics field simulation model; A first determining unit is used to determine an initial adjustment scheme of the multi-physics field simulation model based on the sampling matrix; wherein the initial adjustment scheme includes initial adjustment data corresponding to each operating parameter; A second determining unit, configured to determine an optimal adjustment scheme based on the sampling matrix and the initial adjustment scheme; wherein the optimal adjustment scheme includes adjustment data corresponding to each operating parameter; An optimization unit is used to optimize the operating parameters in the multi-physics field simulation model based on the optimal adjustment scheme to obtain the performance indicators of the optimized electrolytic hydrogen storage device.

9. A computing device, characterized in that The computing device comprises: at least one processor, memory, and input-output unit; The memory is used to store a computer program, and the processor is used to call the computer program stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, enable the computer to execute the method according to any one of claims 1 to 7.

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