Method, system and equipment for optimizing and regulating operating parameters of hydrogen production system and medium

Abstract

The invention provides a method, a system and equipment for optimizing and regulating operating parameters of a hydrogen production system and a medium. The method comprises the following steps: acquiring current, operating pressure, temperature and alkali liquor flow of the hydrogen production system under various different working conditions; based on the current, the operation pressure and the temperature under various working conditions, the electrolysis efficiency of the hydrogen production system under the corresponding working conditions is determined; based on the operation pressure and the alkali liquor flow under various working conditions, determining the hydrogen content in oxygen of the hydrogen production system under the corresponding working conditions; and aiming at the temperature and the corresponding current under each working condition, maximizing the electrolytic efficiency as an optimization target, and carrying out constraint optimization on the operating pressure and the alkali liquor flow under the constraint condition that the hydrogen content in oxygen is smaller than or equal to a preset safety threshold value, so as to obtain the target operating pressure and the target alkali liquor flow under the corresponding current and temperature conditions. According to the method, the electrolysis efficiency can be maximized under the condition of ensuring that the hydrogen content in oxygen meets the safety threshold value.

Description

Technical Field

[0001] This invention relates to the field of electrolytic hydrogen production technology, and in particular to a method, system, equipment, and medium for optimizing and controlling the operating parameters of a hydrogen production system. Background Technology

[0002] With the increasing global demand for clean energy, hydrogen energy, as a highly promising clean energy source, boasts advantages such as high energy density, zero pollution, and abundant resources. It also possesses dual energy and material attributes, offering advantages over other energy storage methods in terms of storage duration and inter-regional transfer. Its production technology has become a research hotspot. Alkaline water electrolysis hydrogen production technology, with its high maturity and relatively low cost, occupies an important position in the field of large-scale hydrogen production.

[0003] However, alkaline water electrolysis hydrogen production systems face a trade-off between safety and operational efficiency. On the one hand, the system's efficiency is constrained by various factors, including maximum allowable current, maximum allowable voltage, highest and lowest operating pressure, highest and lowest operating temperature, and alkaline solution flow rate. On the other hand, the hydrogen-in-oxygen (HTO) content is a critical safety indicator; exceeding 2% can trigger an explosion risk, seriously threatening equipment and personnel safety. Existing research largely focuses on reducing the HTO content by adjusting operating pressure or alkaline solution circulation, but these methods involve complex solutions and are difficult to directly guide on-site operators. Therefore, there is a need for a method, system, equipment, and medium for optimizing and controlling the operating parameters of a hydrogen production system. Summary of the Invention

[0004] This invention provides a method, system, equipment, and medium for optimizing and controlling the operating parameters of a hydrogen production system, in order to solve the technical problem of achieving the highest electrolysis efficiency in an alkaline water electrolysis hydrogen production system while ensuring the safety of the hydrogen content in oxygen.

[0005] This invention provides a method for optimizing the operating parameters of a hydrogen production system. The method includes: acquiring the current, operating pressure, temperature, and alkali flow rate of the hydrogen production system under various operating conditions; determining the electrolysis efficiency of the hydrogen production system under the corresponding operating conditions based on the current, operating pressure, and temperature under various operating conditions; determining the hydrogen content in oxygen under the corresponding operating conditions based on the operating pressure and alkali flow rate under various operating conditions; and for each operating condition and its corresponding current: maximizing the electrolysis efficiency as the optimization objective, and using the hydrogen content in oxygen being less than or equal to a preset safety threshold as a constraint, optimizing the operating pressure and alkali flow rate to obtain the target operating pressure and target alkali flow rate under the corresponding current and temperature conditions.

[0006] In one embodiment of the present invention, for each operating condition, the step of determining the electrolysis efficiency of the hydrogen production system under the corresponding operating condition based on the current, operating pressure, temperature, and alkaline flow rate under that operating condition includes: calculating the cell voltage of each electrolysis cell in the hydrogen production system based on the current, operating pressure, and temperature under that operating condition; calculating the system input power of the hydrogen production system based on the current under that operating condition, the cell voltage of each electrolysis cell, and the number of electrolysis cells in the hydrogen production system obtained in advance; calculating the hydrogen output chemical energy per unit time based on the current under that operating condition and a preset Faraday constant; and calculating the ratio of the hydrogen output chemical energy to the system input power to obtain the electrolysis efficiency of the hydrogen production system under the corresponding operating condition.

[0007] In one embodiment of the present invention, for each operating condition, the step of determining the hydrogen content in oxygen of the hydrogen production system under the corresponding operating condition based on the operating pressure and alkaline flow rate under that operating condition includes: determining the diffusion flux, convection flux, and mixing flux of hydrogen in the electrolyte of the hydrogen production system based on the operating pressure under that operating condition; summing the diffusion flux, convection flux, and mixing flux to obtain the total hydrogen flux, and thereby obtaining the hydrogen content in oxygen of the hydrogen production system under the corresponding operating condition.

[0008] In one embodiment of the present invention, when performing constraint optimization, the constraint optimization includes a first optimization subtask, a second optimization subtask, and a third optimization subtask based on different constraint conditions. Among the constraint conditions of the first optimization subtask, the second optimization subtask, and the third optimization subtask, the corresponding hydrogen content in oxygen is less than or equal to a preset first safety threshold, an unlimited content, and a second safety threshold, respectively, wherein the first safety threshold is less than the second safety threshold.

[0009] In one embodiment of the present invention, the step of optimizing the electrolysis efficiency as the optimization objective and constraining the hydrogen content in oxygen to be less than or equal to a preset safety threshold, and optimizing the operating pressure and alkaline flow rate to obtain the target operating pressure and target alkaline flow rate under the corresponding current and temperature conditions, includes: performing the following processing for each preset optimization cycle; performing the following processing for each optimization sub-task: taking the local operating pressure and corresponding local alkaline flow rate of the previous optimization cycle as the candidate operating pressure and corresponding candidate alkaline flow rate of the current optimization cycle; wherein, in the first optimization cycle, a preset number of candidate operating pressures and corresponding candidate alkaline flow rates are randomly generated; based on the temperature and current under the operating condition, and each candidate operating pressure and corresponding candidate alkaline flow rate, the corresponding electrolysis efficiency and hydrogen content in oxygen are determined. The optimization process involves maximizing electrolysis efficiency as the objective, with a hydrogen content in oxygen less than or equal to a preset safety threshold as a constraint. Candidate operating pressures and alkaline flow rates are optimized and updated a preset number of times to obtain the initial local optimum solution set for this sub-task. This initial local optimum solution set includes a preset number of candidate operating pressures with the highest electrolysis efficiency during the optimization process, along with their corresponding candidate alkaline flow rates. The initial local optimum solution sets of each optimization sub-task are then transferred between each other to obtain the final local optimum solution set for each sub-task in the optimization cycle. After all sub-tasks have been transferred, the process proceeds to the next optimization cycle until the preset maximum number of optimization iterations is reached. Finally, the sub-task with the highest electrolysis efficiency is selected from the local optimum solution set of the first optimization sub-task as the target operating pressure and target alkaline flow rate.

[0010] In one embodiment of the present invention, the step of fusing the various local alkaline flow rates to obtain the final target alkaline flow rate includes: migrating the initial local optimal solution sets corresponding to the second and third optimization sub-tasks to the initial local optimal solution set of the first optimization sub-task, forming the final local optimal solution set of the first optimization sub-task; migrating the initial local optimal solution sets corresponding to the first and second optimization sub-tasks to the initial local optimal solution set of the third optimization sub-task, forming the final local optimal solution set of the third optimization sub-task; and migrating the local alkaline flow rates corresponding to the first and third optimization sub-tasks to the initial local optimal solution set of the second optimization sub-task, forming the final local optimal solution set of the second optimization sub-task.

[0011] In one embodiment of the present invention, a method for regulating a hydrogen production system is also provided. The method includes: acquiring the current, temperature, operating pressure, and alkaline flow rate at the current sampling moment, and determining the target operating pressure and target alkaline flow rate under the current and temperature conditions; wherein the target operating pressure and target alkaline flow rate are obtained by constrained optimization using any of the above-mentioned hydrogen production system operating parameter optimization methods; calculating the difference between the operating pressure and the target operating pressure, and the difference between the alkaline flow rate and the target alkaline flow rate, and regulating the operating pressure and alkaline flow rate of the hydrogen production system accordingly.

[0012] This invention also provides an operating parameter optimization system for a hydrogen production system. The system includes: a parameter acquisition module for acquiring the current, operating pressure, temperature, and alkali flow rate of the hydrogen production system under various operating conditions; an electrolysis efficiency calculation module for determining the electrolysis efficiency of the hydrogen production system under corresponding operating conditions based on the current, operating pressure, and temperature under various operating conditions; an oxygen hydrogen content calculation module for determining the oxygen hydrogen content of the hydrogen production system under corresponding operating conditions based on the operating pressure and alkali flow rate under various operating conditions; and an optimization module for optimizing the operating pressure and alkali flow rate under each operating condition, with the temperature and corresponding current as the optimization objective, and with the oxygen hydrogen content being less than or equal to a preset safety threshold as a constraint, to obtain the target operating pressure and target alkali flow rate under the corresponding current and temperature conditions.

[0013] The present invention also provides an electronic device, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device enables the implementation of any of the above-described methods for optimizing the operating parameters of a hydrogen production system or for regulating the hydrogen production system.

[0014] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a computer processor, causes the computer to perform any of the above-described methods for optimizing the operating parameters of a hydrogen production system or for regulating the hydrogen production system.

[0015] The beneficial effects of this invention are as follows: This invention proposes a method, system, equipment, and medium for optimizing and controlling the operating parameters of a hydrogen production system. Based on operating pressure, current, and temperature, the electrolysis efficiency can be determined using the electrochemical principles of alkaline water electrolysis. Based on operating pressure and alkaline solution flow rate, the hydrogen content in oxygen can be determined according to the physical laws of gas diffusion and convection transport in the alkaline electrolyte. With maximizing electrolysis efficiency as the optimization objective and ensuring that the hydrogen content in oxygen does not exceed a safe threshold as a constraint, the operating pressure and alkaline solution flow rate are optimized under different temperatures and currents, thereby obtaining the target operating pressure and target alkaline solution flow rate for each operating condition. This invention, by establishing a joint constraint optimization mechanism for electrolysis efficiency and hydrogen content in oxygen, can maximize electrolysis efficiency while ensuring that the hydrogen content in oxygen meets the safe threshold, thus addressing both the safety and high efficiency issues of the alkaline water electrolysis hydrogen production system. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0017] In the attached diagram: Figure 1 A flowchart illustrating a method for optimizing the operating parameters of a hydrogen production system according to an embodiment of the present invention; Figure 2 A schematic flowchart of a method for controlling a hydrogen production system according to an embodiment of the present invention; Figure 3 A graph showing the variation trend of alkaline solution flow rate and operating pressure under the condition that the hydrogen content in oxygen is less than or equal to 2% and the electrolysis efficiency is the highest, provided as an embodiment of the present invention; Figure 4 For each current in Figure 3 Schematic diagram of electrolysis efficiency and hydrogen content in oxygen under the conditions of medium alkali solution flow rate and operating pressure; Figure 5 To maintain Figure 3 A schematic diagram showing the electrolysis efficiency and hydrogen content in oxygen exceeding safety limits at a specified current while maintaining constant alkaline flow rate and operating pressure. Figure 6 This is a structural block diagram of an operating parameter optimization system for a hydrogen production system provided in one embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of an electronic device provided in one embodiment of the present invention. Detailed Implementation

[0018] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0019] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0020] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0021] This invention provides a method for optimizing the operating parameters of a hydrogen production system, aiming to mitigate the safety risks caused by excessive hydrogen content in oxygen within alkaline water electrolysis hydrogen production systems, as well as addressing the shortcomings of existing electrolysis efficiency control methods and the limited range of operating parameter control options. This invention comprehensively considers reversible electrolysis voltage, activation overpotential, ohmic overpotential, and oxygen production rate, and establishes an electrolysis efficiency model accordingly, providing strong assurance for the safe operation of the hydrogen production system. Furthermore, it considers hydrogen diffusion flux, hydrogen convection flux, hydrogen mixing flux, and hydrogen production rate, and establishes an oxygen-hydrogen model based on these factors, enabling a comprehensive and detailed description of the electrolysis efficiency behavior of the hydrogen production system during operation. This allows for quantitative calculation of electrolysis efficiency and oxygen-hydrogen content under different current, operating pressure, temperature, and alkaline solution flow rate conditions. Based on this, this invention uses maximizing electrolysis efficiency as the optimization objective and an oxygen-hydrogen content less than or equal to a preset safety threshold as a constraint. Through multi-task constraint optimization, it obtains the target operating pressure and corresponding target alkaline solution flow rate combinations under different operating conditions, and constructs the optimal operating parameter curve accordingly. During the operation of the hydrogen production system, parameters such as operating pressure and alkaline flow rate can be adjusted based on this optimal operating parameter curve. This maximizes the electrolysis efficiency of the hydrogen production system while ensuring the hydrogen content in oxygen remains within a safe range, thus enabling stable and efficient operation. Therefore, this invention can accurately simulate the electrolysis process mechanism, significantly improving the safety and electrolysis efficiency of the hydrogen production system. It effectively addresses the problems of existing technologies, such as single control methods and a lack of synergistic optimization between electrolysis efficiency and operational safety, thereby providing crucial assurance for the safe and efficient operation of alkaline water electrolysis hydrogen production systems.

[0022] like Figure 1 As shown, the method for optimizing the operating parameters of a hydrogen production system includes the following steps S100 to S400: S100: Obtain the current, operating pressure, temperature, and alkaline flow rate of the hydrogen production system under various operating conditions.

[0023] A hydrogen production system refers to a device system used for alkaline water electrolysis to produce hydrogen. It includes an electrolyzer, a circulating alkali circuit, a gas-liquid separation device, a heating and cooling module, and an operating pressure regulation module. The hydrogen production system can achieve stable operation of the electrolysis reaction under different operating parameters and monitor the operating status of the electrolysis reaction. In this invention, multiple different operating conditions can be preset according to operational requirements. Each operating condition corresponds to a different operating state of the hydrogen production system, representing the operating characteristics of the hydrogen production system under different current, operating pressure, temperature, and alkali flow rate conditions. Here, current refers to the operating current of the electrolyzer, used to characterize the electrolysis intensity. Operating pressure includes anode operating pressure and cathode operating pressure, used to characterize the degree of restriction on gas generation and transmission inside the electrolyzer, and can be obtained by pressure sensors installed in the anode and cathode chambers. Temperature refers to the temperature of the electrolyte, which can be monitored by a temperature sensor. Alkali flow rate refers to the flow rate of alkali entering the electrolyzer, which can be measured by a flow meter.

[0024] S200: Based on the current, operating pressure, and temperature under various operating conditions, and according to the electrochemical principle of alkaline water electrolysis reaction, the electrolysis efficiency of the hydrogen production system under corresponding operating conditions is determined.

[0025] By inputting the operating pressure, current, temperature, and alkali flow rate under different operating conditions into the electrolysis efficiency model, the corresponding electrolysis efficiency under each condition can be calculated based on the electrochemical principles of alkaline water electrolysis. By comparing and analyzing the electrolysis efficiencies under different combinations of operating pressure and alkali flow rate, it can be determined that the optimal combination of operating pressure and alkali flow rate for achieving the highest electrolysis efficiency under specific temperature and current conditions is available for the hydrogen production system. The electrolysis efficiency model is constructed based on the electrochemical principles of alkaline water electrolysis.

[0026] In an optional embodiment of the present invention, for each working condition: step S200 includes steps S210 to S240: S210. Based on the current, operating pressure, and temperature under this operating condition, calculate the cell voltage of each electrolysis cell in the hydrogen production system.

[0027] Specifically, since the operating pressure includes the anode operating pressure and the cathode operating pressure of the electrolytic cell, the total pressure of the electrolytic cell can be calculated by adding the two together. Based on the temperature of the electrolytic cell and the total pressure of the electrolytic cell, the reversible electrolysis voltage can be calculated using formula (1): (1) in, The reversible electrolysis voltage is used to characterize the theoretical minimum voltage required to sustain the reaction at a given pressure and temperature. The reversible electrolysis voltage under preset standard conditions. The gas constant ( =8.314 J / (mol) K)), The temperature under this operating condition. The preset Faraday constant ( =96485), This refers to the total pressure of the electrolytic cell. The preset partial pressure of water vapor, The preset water activity.

[0028] The activation overpotential can be calculated according to formula (2): (2) in, To activate the overpotential, The amount of charge transferred when 1 mol of hydrogen gas is generated ( ), and These represent the charge transfer coefficients of the anode and cathode, respectively, and can be calculated using empirical formulas related to temperature. For the pre-obtained current density, and These represent the exchange current densities at the anode and cathode of the electrolytic cell, respectively. The bubble coverage rate on the electrode surface is obtained in advance.

[0029] The ohmic overpotential can be calculated according to formula (3): (3) in, This is an ohmic overpotential. For cathode resistance, For anode resistance, The preset electrolyte resistance, The preset diaphragm resistance, The preset bubble resistance, This represents the current under this operating condition.

[0030] The reversible electrolysis voltage obtained from the above formulas (1) to (3) Activation overpotential Ohmic overpotential Summing these values ​​yields the cell voltages of each electrolytic cell in the electrolytic cell. As shown in formula (4): (4) S220. Based on the current under this operating condition, the cell voltage of each electrolysis cell, and the number of electrolysis cells in the hydrogen production system obtained in advance, calculate the system input power of the hydrogen production system.

[0031] Because the electrolyzer of the hydrogen production system is composed of It consists of several electrolytic cells connected in series, with each cell having a voltage of [voltage value missing]. Then the total voltage of the entire electrolytic cell is Based on the total voltage and the current under this operating condition The system input power of the hydrogen production system can be calculated. As shown in formula (5): (5) S230. Based on the current under this operating condition and the preset Faraday constant, calculate the chemical energy output of hydrogen per unit time.

[0032] The chemical energy output of hydrogen per unit time is used to characterize the chemical energy corresponding to the hydrogen production system producing hydrogen per second under this operating condition. The hydrogen production rate per unit time can be calculated according to formula (6) based on the current of the electrolyzer under this operating condition, as well as the preset Faraday constant and the number of electrolysis cells in the electrolyzer: (6) in, The hydrogen production rate per unit time. This represents the rate of oxygen production per unit time. The number of electrolysis chambers, This refers to the current under this operating condition. The Faraday constant is a preset value. The Faraday efficiency reflects the effective proportion of electrons converted into hydrogen gas in an actual reaction, and can be obtained by formula (7): (7) in, For electrode area, and The preset empirical coefficient can be obtained through experimental data calibration. After obtaining the hydrogen generation rate per unit time, the hydrogen output chemical energy per unit time can be obtained accordingly, as shown in formula (8): (8) in, Hydrogen output chemical energy per unit time is used to characterize the energy output level of hydrogen production system under this operating condition and is a key indicator for measuring electrolysis efficiency. The preset lower heating value of hydrogen is typically 242. kJ / mol.

[0033] S240. Calculate the ratio of hydrogen output chemical energy to system input power to obtain the electrolysis efficiency of the hydrogen production system under the corresponding operating conditions.

[0034] Electrolysis efficiency is used to characterize the ability of a hydrogen production system to convert electrical energy into the chemical energy of hydrogen under this operating condition, and to measure the output chemical energy of hydrogen per unit time obtained by the above formula (8). and the system input power obtained by formula (5) The ratio was calculated to obtain the electrolysis efficiency under this operating condition. As shown in formula (9): (9) S300: Based on the operating pressure and alkaline flow rate under various operating conditions, and according to the physical laws of gas diffusion and convection transport in alkaline electrolyte, determine the hydrogen content in oxygen of the hydrogen production system under the corresponding operating conditions.

[0035] In the alkaline water electrolysis hydrogen production process, the generated hydrogen and oxygen initially exist in a dissolved state in the electrolyte. As the electrolysis reaction proceeds and the operating environment of the hydrogen production system changes, bubbles gradually form on the electrode surface and move between each other through the diaphragm. When oxygen mixes with hydrogen, the hydrogen purity decreases. Conversely, when hydrogen mixes with oxygen, the minimum safe load of the hydrogen production system is limited, and in severe cases, it may even lead to safety risks such as explosions. Therefore, the hydrogen content in oxygen is a critical indicator for the safe operation of the hydrogen production system. In this invention, different operating pressures and alkaline solution flow rates are input into the oxygen-hydrogen model to obtain the corresponding oxygen-hydrogen concentration, enabling a quantitative assessment of the safety risks of the hydrogen production system under different operating conditions.

[0036] In an optional embodiment of the present invention, for each working condition: step S300 includes steps S310 and S320: S310. Based on the operating pressure under this condition, calculate the diffusion flux, convection flux, and mixing flux of hydrogen in the electrolyte of the hydrogen production system.

[0037] The solubility of hydrogen in alkaline solution can be determined using formula (10) based on the Sechenov relation. : (10) in, This is a preset Sechenov constant, the value of which depends on the type of electrolyte and gas, for example... , The molar concentration of the pre-detected alkali solution (KOH) The solubility of hydrogen in pure water can be determined based on a preset water density. Operating pressure under this condition Preset hydrogen Henry coefficient And it is calculated using formula (11): (11) The solubility of hydrogen in alkaline solution was obtained. Then, based on the preset structural parameters of the diaphragm, since the diaphragm is filled with alkaline solution, the effective diffusion coefficient of hydrogen permeation through the diaphragm can be obtained by formula (12): (12) in, This represents the effective diffusion coefficient of hydrogen permeation through the membrane under this operating condition. This is the preset diffusion coefficient of hydrogen in alkaline solution. The preset membrane porosity, This is the preset tortuosity.

[0038] Based on the above calculations, according to Fick's diffusion law, the hydrogen diffusion flux under this operating condition is obtained, as shown in formula (13): (13) in, This is the hydrogen diffusion flux under this operating condition, used to characterize the rate at which hydrogen permeates the membrane under the influence of the concentration gradient. The preset diaphragm thickness, For the dissolved gas concentration gradient, The effective diffusion coefficient of hydrogen permeation through the membrane is obtained from formula (12). The solubility of hydrogen in alkaline solution is obtained by formula (11).

[0039] Considering the pressure difference between the anode and cathode, hydrogen gas will migrate under the drive of the pressure difference, resulting in a convection flow, as shown in formula (14): (14) in, This represents the hydrogen convection flow rate under this operating condition. The preset membrane permeability is closely related to the membrane parameters and can be obtained by pre-calibrating based on the membrane pore size, porosity, and tortuosity. The pre-obtained alkali concentration, The solubility of hydrogen in alkaline solution is obtained from formula (11). This refers to the difference between the anode pressure and the cathode pressure in the electrolyzer of a hydrogen production system. The membrane thickness is preset. Furthermore, the hydrogen mixing flux can be calculated according to formula (15) to characterize the amount of hydrogen solute transported with the alkaline solution flow: (15) in, This represents the hydrogen mixing flux under this operating condition. The flow rate of the alkali solution under this operating condition can be obtained through a flow sensor.

[0040] S320. Summing the diffusion flux, convection flux, and mixing flux yields the total hydrogen flux, and based on this, the hydrogen content in oxygen of the hydrogen production system under the corresponding operating conditions is obtained.

[0041] After obtaining the diffusion flux, convection flux, and mixing flux, they can be summed according to their contributions. Based on the structural parameters of the electrolyzer and the gas yield parameters, the hydrogen content in oxygen under this operating condition can be obtained, as shown in formula (16): (16) in, The hydrogen content in oxygen under the current operating conditions. The oxygen generation rate calculated using formula (6) is... This is the flux of hydrogen gas from the cathode side to the anode side of the electrolyzer per unit time, i.e., the hydrogen exchange flux. The hydrogen diffusion flux under this operating condition is calculated using formula (13). The hydrogen convection flow rate under this operating condition is calculated using formula (14). The hydrogen mixing flux under this operating condition is calculated using formula (15). This is the preset number of electrolysis chambers.

[0042] S400: For each operating condition and its corresponding current, the goal is to maximize electrolysis efficiency. With the hydrogen content in oxygen being less than or equal to a preset safety threshold as a constraint, the operating pressure and alkali flow rate are optimized to obtain the target operating pressure and target alkali flow rate under the corresponding current and temperature conditions.

[0043] In an optional embodiment of the present invention, constraint optimization includes a first optimization subtask, a second optimization subtask, and a third optimization subtask based on different constraint conditions. The constraints of the first, second, and third optimization subtasks correspond to oxygen hydrogen content that is less than or equal to a preset first safety threshold, an unlimited content, and a second safety threshold, respectively, where the first safety threshold is less than the second safety threshold. Specifically, the purpose of constraint optimization is to achieve the optimal electrolysis efficiency while ensuring the safe operation of the hydrogen production system. To achieve this objective, the present invention performs multi-task collaborative processing based on different constraint conditions, decomposing the original multi-objective optimization problem into three parallel subtasks, denoted as the first optimization subtask, the second optimization subtask, and the third optimization subtask. The first optimization subtask corresponds to oxygen hydrogen content that is less than or equal to a preset first safety threshold (e.g., 2%) to ensure the safe and efficient operation of the hydrogen production system. The second optimization subtask corresponds to oxygen hydrogen content that is infinitely large, therefore the oxygen hydrogen content is not limited, and it is used to obtain the solution with the highest electrolysis efficiency. The third optimization subtask corresponds to an oxygen hydrogen content that is less than or equal to a preset second safety threshold (e.g., 2.5%), and is used to obtain a solution that balances safety and high electrolysis efficiency.

[0044] In an optional embodiment of the present invention, step S400 includes the following process: For each preset optimization cycle, execute steps S410 to S440: For each optimization subtask, execute steps S410 to S430: S410. The local operating pressures and corresponding local alkaline flow rates of the previous optimization cycle are used as candidate operating pressures and corresponding candidate alkaline flow rates of the current optimization cycle; wherein, a preset number of candidate operating pressures and corresponding candidate alkaline flow rates are randomly generated in the first optimization cycle.

[0045] In the first optimization cycle, based on the preset operating pressure range and the preset alkali flow rate range, a preset number (e.g., N) of candidate operating pressures are randomly generated from the operating pressure range. Based on these candidate operating pressures and empirical or physical correlations, corresponding candidate alkali flow rates are generated from the alkali flow rate range, forming N candidate parameter pairs. , ),in, For the i-th candidate operating pressure, To and The corresponding i-th candidate alkali flow rate. In subsequent optimization cycles, the local operating pressure and corresponding local alkali flow rate of the previous optimization cycle are used as the candidate operating pressure and corresponding candidate alkali flow rate of the current optimization cycle.

[0046] S420. Based on the temperature and current under this operating condition, as well as the candidate operating pressure and the corresponding candidate alkali flow rate, determine the corresponding electrolysis efficiency and hydrogen content in oxygen.

[0047] Based on the temperature and current under this operating condition, for the N candidate parameter pairs obtained above ( , Using the above formulas (9) and (16), we can obtain the corresponding electrolysis efficiency and hydrogen content in oxygen for each candidate parameter under the current operating conditions of temperature and current.

[0048] S430. With maximizing electrolysis efficiency as the optimization objective and the hydrogen content in oxygen being less than or equal to a preset safety threshold as a constraint, the candidate operating pressure and candidate alkaline flow rate are optimized and updated a preset number of times to obtain the initial local optimal solution set of this optimization sub-task; wherein, the initial local optimal solution set includes a preset number of candidate operating pressures with the highest electrolysis efficiency during the optimization process and the corresponding candidate alkaline flow rates.

[0049] In this invention, each optimization cycle includes multiple iterations. By progressively searching, the parameter combination with the highest electrolysis efficiency that satisfies the constraints is gradually obtained. Specifically, for each optimization cycle, in the first iteration, the local optimal solution set of the previous optimization cycle is used as the input of the current optimization cycle. Constraint optimization is performed according to the constraints of the current optimization sub-task to obtain multiple sets of operating parameter combinations. Each set of operating parameter combinations includes an optimized candidate operating pressure and a corresponding candidate alkali flow rate, which serve as the first round of candidate solutions for that optimization cycle. In the remaining iterations, the candidate solution set obtained in the previous iteration is used as the input to obtain the candidate solution set under the current operating conditions of temperature and current. Specifically, in each constraint optimization, the electrolysis efficiency and hydrogen content in oxygen corresponding to each set of candidate solutions are obtained according to the aforementioned formulas (9) and (16). With maximizing the electrolysis efficiency as the objective function and the hydrogen content in oxygen being less than or equal to the preset safety threshold of the optimization sub-task as the condition, the input candidate operating pressure and the corresponding candidate alkali flow rate are subjected to fitness evaluation and optimization update to obtain a new set of candidate solutions.

[0050] S440. The initial local optimal solution sets between each optimization subtask are transferred to each other to obtain the final local optimal solution set of each optimization subtask in the optimization cycle. After all optimization subtasks have been transferred, the next optimization cycle is started until the preset maximum number of optimizations is reached. The highest electrolysis efficiency is selected from the local optimal solution set of the first optimization subtask as the target operating pressure and target alkali flow rate.

[0051] To achieve coordinated convergence among the three different types of optimization subtasks, cross-task migration is performed after each optimization subtask has independently iterated a preset number of times in each optimization cycle. Specifically, solutions satisfying the constraints of the first optimization subtask are migrated from the initial local optimum solution sets of the second and third optimization subtasks to the solution set of the first optimization subtask, obtaining the final local optimum solution set of the first optimization subtask. Similarly, corresponding migration operations are performed on the second and third optimization subtasks to obtain the final local optimum solution of each optimization subtask. After all optimization subtasks have been migrated, if the maximum number of optimization iterations has not been reached, the process continues to the next optimization cycle. When the maximum number of optimization iterations is reached, the parameter combination with the highest electrolysis efficiency and satisfying its constraints is selected from the final local optimum solution set of the first optimization subtask as the target operating pressure and target alkali flow rate for subsequent operation and control of the hydrogen production system.

[0052] In an optional embodiment of the present invention, the step of fusing the various local alkaline flow rates to obtain the final target alkaline flow rate includes: migrating the initial local optimal solution sets corresponding to the second and third optimization sub-tasks to the initial local optimal solution set of the first optimization sub-task, forming the final local optimal solution set of the first optimization sub-task; migrating the initial local optimal solution sets corresponding to the first and second optimization sub-tasks to the initial local optimal solution set of the third optimization sub-task, forming the final local optimal solution set of the third optimization sub-task; and migrating the local alkaline flow rates corresponding to the first and third optimization sub-tasks to the initial local optimal solution set of the second optimization sub-task, forming the final local optimal solution set of the second optimization sub-task.

[0053] Specifically, from the initial local optimal solution sets corresponding to the second and third optimization sub-tasks, candidate solutions with high electrolysis efficiency (such as electrolysis efficiency higher than a preset efficiency threshold, or electrolysis efficiency ranking in the top N) and hydrogen content in oxygen less than or equal to the first safety threshold are selected and added to the original initial local optimal solution set of the first optimization sub-task to form the final local optimal solution set of the optimization sub-task.

[0054] Therefore, the multi-task collaborative optimization method adopted in this invention optimizes complex multi-objective constrained problems by solving problems in separate tasks and transferring effective solutions across tasks. Its core idea can be summarized as "breaking down a complex optimization problem into multiple parallel optimization sub-tasks, solving each sub-task independently, and then exchanging and fusing useful information to finally obtain the optimal solution that satisfies the original problem." For the optimization objective of maximizing electrolysis efficiency while ensuring that the hydrogen content in oxygen does not exceed a safety threshold (e.g., 2%), the original problem is first decomposed into three parallel optimization sub-tasks. The first optimization sub-task is a constrained optimization task, following the original problem's constraint that the hydrogen content in oxygen does not exceed the first safety threshold (e.g., 2%), and seeking a combination of operating pressure and alkali flow rate that ensures both the safety of the hydrogen production system and high electrolysis efficiency. The second optimization sub-task is an unconstrained optimization task, disregarding safety constraints and only pursuing the maximization of electrolysis efficiency. The third optimization sub-task is a relaxed constraint optimization task, appropriately relaxing the hydrogen content in oxygen to the second safety threshold (e.g., 2.5%) to find a solution with high electrolysis efficiency close to the safety boundary.

[0055] During optimization, each subtask is solved independently using the same optimization algorithm (such as NSGA-II), undergoing up to 100 iterations of independent optimization to obtain a local optimum solution set for the corresponding subtask. Then, a migration phase is initiated, where effective solutions from each subtask are interacted with and merged to obtain the final local optimum solution set for each subtask. For example, the first subtask introduces a safer solution with higher electrolysis efficiency from the second and third subtasks; the second subtask introduces a more efficient solution close to the safety threshold from the first and third subtasks; and the third subtask introduces a solution with high electrolysis efficiency and near-unconstrained conditions from the first and second subtasks, thus balancing safety and electrolysis efficiency. For instance, if the first subtask has a solution with 1.8% hydrogen content and 80% electrolysis efficiency, the second subtask will merge this solution and continue searching for a solution. This migration phase continues until a preset maximum number of iterations (e.g., 1000) is reached. As the iterations proceed, the local optimal solution sets of each optimization subtask gradually converge. Specifically, the solution of the first optimization subtask tends to be both safe and have high electrolysis efficiency; the solution of the second optimization subtask tends to have high electrolysis efficiency and is close to the safety boundary; and the solution of the third optimization subtask tends to balance safety and high electrolysis efficiency. Finally, the operating pressure and alkali flow rate combination with the highest electrolysis efficiency and meeting the constraints is selected from the first optimization subtask as the final global optimal solution to achieve the safe and efficient operation of the hydrogen production system.

[0056] like Figure 2 As shown, the present invention also provides a method for regulating a hydrogen production system, the method comprising the following steps: S500: Obtain the current, temperature, operating pressure, and alkaline flow rate at the current sampling moment, and determine the target operating pressure and target alkaline flow rate under the current and temperature conditions; wherein, the target operating pressure and target alkaline flow rate are obtained by constrained optimization through any of the above-mentioned hydrogen production system operating parameter optimization methods. S600 calculates the difference between the operating pressure and the target operating pressure, as well as the difference between the alkali flow rate and the target alkali flow rate, and adjusts the operating pressure and alkali flow rate of the hydrogen system accordingly.

[0057] Specifically, using the aforementioned electrolysis efficiency model and oxygen-to-hydrogen model, or data analysis methods such as multiple linear regression and machine learning algorithms, the target operating pressure and target alkali flow rate under given current and temperature conditions can be calculated. These are compared with the actual obtained operating pressure and alkali flow rate. When the operating pressure or alkali flow rate deviates from the corresponding target value, a control command can be triggered. By adjusting the pressure regulating valve or the alkali circulation pump, the operating pressure or alkali flow rate is regulated to ensure the hydrogen production system achieves optimal electrolysis efficiency and meets operational safety requirements. For example, by adjusting the pressure regulating valve, the operating pressure is reduced at a rate of 0.05 MPa / min, while simultaneously adjusting the alkali flow rate according to model predictions to maintain the hydrogen production system operating within a safe and efficient range. If an abnormal alkali flow rate is found to be causing low electrolysis efficiency in the hydrogen production system, the system can adjust the speed of the alkali pump to change the alkali flow rate. For instance, if it is determined that the alkali flow rate is too high, the alkali pump speed is automatically reduced, decreasing the alkali flow rate at a rate of 0.5 L / min, while simultaneously monitoring the system status to ensure the adjusted hydrogen production system returns to a safe range.

[0058] The following is a specific example of the present invention: Taking a 10kW alkaline hydrogen production system as an example, the rated current of the alkaline electrolyzer in this system is 200A, the upper limit of the pressure is 1.6MPa and the lower limit is 0.6MPa, and the upper limit of the alkaline solution flow rate is 0.42m³ / h. 3 The lower limit for / h is 0.21 m 3 / h, with an upper temperature limit of 95℃ and a lower limit of 0℃. The specific steps are as follows: I. Construct electrolysis efficiency model and oxygen-hydrogen model, and use MATLAB platform to implement model coding (covering electrolysis efficiency and oxygen-hydrogen models) to obtain the mapping relationship between current, pressure, temperature and alkaline flow rate and electrolysis efficiency and oxygen-hydrogen.

[0059] II. Based on the design specifications and safe operation requirements of the hydrogen production system, the following parameter constraints are set: current 40~200A; temperature 0~95℃; operating pressure 0.6~1.6MPa; alkali solution flow rate 0.21~0.42m³ / h. 3 / h.

[0060] III. With the dual objectives of maximizing electrolysis efficiency and minimizing hydrogen concentration in oxygen, an optimization model was constructed using the aforementioned optimization method and implemented on the MATLAB platform. The input variables of the optimization model are current (40~200A), temperature (0~95℃), operating pressure (0.6~1.6MPa), and alkali solution flow rate (0.21~0.42m³ / h). 3 The output variables are electrolysis efficiency and hydrogen content in oxygen, respectively, with constraints including upper and lower limits of the input variables and hydrogen content in oxygen less than or equal to 2%. Ultimately, the optimal operating pressure and alkali flow rate parameters under specific operating conditions can be obtained, and the optimal operating curve can be plotted using multiple sets of parameters.

[0061] Specifically, such as Figure 3 As shown, this graph illustrates the trends in alkaline solution flow rate and operating pressure under different currents in an alkaline water electrolysis hydrogen production system, where the hydrogen content in oxygen is less than or equal to 2% and the electrolysis efficiency is highest. The graph shows that when the current is between 40-200A, and the hydrogen content in oxygen is maintained at less than or equal to 2%, the alkaline solution flow rate initially increases and then stabilizes with increasing current, while the operating pressure increases rapidly and then stabilizes with increasing current. Furthermore, as... Figure 4 As shown, it illustrates the various currents at... Figure 3 A schematic diagram showing the electrolysis efficiency and hydrogen content in oxygen under different alkaline solution flow rates and operating pressures reveals that electrolysis efficiency increases with increasing current, while the hydrogen content in oxygen decreases in the opposite direction. Figure 5 As shown, it demonstrates the ability to maintain Figure 3 A schematic diagram showing the electrolysis efficiency and hydrogen content in oxygen exceeding safety limits at a specified current while maintaining constant alkali flow rate and operating pressure. It can be seen that at 150A, the hydrogen content in oxygen exceeds the safety limit of 2%, and at 70A, it exceeds the explosion limit. The optimal operating curve using the example of this invention maximizes electrolysis efficiency while ensuring safety.

[0062] Fourth, based on the optimal combination of pressure and alkali flow rate corresponding to each current, the optimal electrolysis efficiency can be achieved by inputting the data into the controller of the hydrogen production system. Alternatively, the parameters can be manually adjusted by the operator according to the optimal operating curve.

[0063] like Figure 6As shown, the operating parameter optimization system for the hydrogen production system includes: a parameter acquisition module 610, an electrolysis efficiency calculation module 620, an oxygen hydrogen content calculation module 630, and an optimization module 640. The parameter acquisition module 610 acquires the current, operating pressure, temperature, and alkali flow rate of the hydrogen production system under various operating conditions. The electrolysis efficiency calculation module 620 determines the electrolysis efficiency of the hydrogen production system under corresponding operating conditions based on the current, operating pressure, and temperature. The oxygen hydrogen content calculation module 630 determines the oxygen hydrogen content of the hydrogen production system under corresponding operating conditions based on the operating pressure and alkali flow rate. The optimization module 640 optimizes the operating pressure and alkali flow rate for each operating condition, taking the temperature and corresponding current as the optimization objective, and using the oxygen hydrogen content being less than or equal to a preset safety threshold as a constraint, to obtain the target operating pressure and target alkali flow rate under the corresponding current and temperature conditions.

[0064] Specific limitations regarding the optimization system for the operating parameters of the hydrogen production system can be found in the limitations on the optimization method for the operating parameters of the hydrogen production system described above, and will not be repeated here. Each module in the aforementioned optimization system for the operating parameters of the hydrogen production system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in the processor of a computer device in hardware format or independent of it, or stored in the memory of a computer device in software format, so that the processor can call the corresponding operations of each module.

[0065] It should be noted that, in order to highlight the innovative aspects of this invention, this embodiment does not include modules that are not closely related to solving the technical problems proposed by this invention, but this does not mean that there are no other modules in this embodiment.

[0066] like Figure 7 As shown, the electronic device 7 may include a memory 11, a processor 72 and a bus, and may also include a computer program stored in the memory 11 and that can run on the processor 72, such as an operating parameter optimization program for the hydrogen production system or a control program for the hydrogen production system.

[0067] The memory 11 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of the electronic device 7, such as the portable hard drive of the electronic device 7. In other embodiments, the memory 11 can also be an external storage device of the electronic device 7, such as a plug-in portable hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 7. Furthermore, the memory 11 can include both internal and external storage units of the electronic device 7. The memory 11 can be used not only to store application software and various types of data installed on the electronic device 7, such as code for optimizing the operating parameters of the hydrogen production system or controlling the hydrogen production system, but also to temporarily store data that has been output or will be output.

[0068] In some embodiments, the processor 72 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 72 is the control unit of the electronic device 7, connecting various components of the entire electronic device 7 via various interfaces and lines. It executes programs or modules stored in the memory 11 (such as operating parameter optimization programs or control programs for hydrogen production systems) and calls data stored in the memory 11 to perform various functions and process data in the electronic device 7.

[0069] The processor 72 executes the operating system of the electronic device 7 and various installed application programs. The processor 72 executes the application programs to implement the steps in the above-mentioned hydrogen production system operating parameter optimization or hydrogen production system control method.

[0070] For example, a computer program may be divided into one or more modules, one or more of which are stored in memory 11 and executed by processor 72 to complete this application. One or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in electronic device 7. For example, the computer program may be divided into a parameter acquisition module 610, an electrolysis efficiency calculation module 620, an oxygen hydrogen content calculation module 630, and an optimization module 640.

[0071] The integrated unit implemented as a software functional module described above can be stored in a computer-readable storage medium, which can be non-volatile or volatile. The software functional module, stored in the storage medium, includes several instructions to cause a computer device (which may be a personal computer, computer equipment, or network device, etc.) or processor to execute some functions of the hydrogen production system operating parameter optimization or hydrogen production system control methods of the various embodiments of this application.

[0072] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A method for optimizing the operating parameters of a hydrogen production system, characterized in that, The method comprises: acquiring the current, operating pressure, temperature and alkali flow of the hydrogen production system under a plurality of different working conditions; determining the electrolysis efficiency of the hydrogen production system under the corresponding working condition based on the current, operating pressure and temperature under various working conditions; determining the hydrogen content in oxygen of the hydrogen production system under the corresponding working condition based on the operating pressure and alkali flow under various working conditions; for the temperature and its corresponding current under each working condition: maximizing the electrolysis efficiency as the optimization target, taking the hydrogen content in oxygen less than or equal to the preset safety threshold as the constraint condition, and performing constraint optimization on the operating pressure and alkali flow to obtain the target operating pressure and target alkali flow under the corresponding current and temperature conditions.

2. The method of claim 1, wherein, For each working condition: the step of determining the electrolysis efficiency of the hydrogen production system under the corresponding working condition based on the current, operating pressure, temperature and alkali flow under the working condition comprises: calculating the cell voltage of each electrolysis cell in the hydrogen production system based on the current, operating pressure and temperature under the working condition; calculating the system input power of the hydrogen production system based on the current, cell voltage of each electrolysis cell under the working condition, and the number of electrolysis cells in the hydrogen production system obtained in advance; calculating the hydrogen output chemical energy per unit time based on the current and the preset Faraday constant under the working condition; calculating the ratio of the hydrogen output chemical energy to the system input power to obtain the electrolysis efficiency of the hydrogen production system under the corresponding working condition.

3. The method of claim 1, wherein For each working condition: the step of determining the hydrogen content in oxygen of the hydrogen production system under the corresponding working condition based on the operating pressure and alkali flow under the working condition comprises: determining the diffusion flux, convection flux and mixing flux of hydrogen in the electrolyte of the hydrogen production system based on the operating pressure under the working condition; summing the diffusion flux, convection flux and mixing flux to obtain the total hydrogen flux, and accordingly obtaining the hydrogen content in oxygen of the hydrogen production system under the corresponding working condition.

4. The method of claim 1, wherein, When performing constraint optimization, the constraint optimization comprises a first optimization subtask, a second optimization subtask and a third optimization subtask based on different constraint conditions, and the constraint conditions of the first optimization subtask, the second optimization subtask and the third optimization subtask are that the corresponding hydrogen content in oxygen is less than or equal to a preset first safety threshold, not limited to the content and a second safety threshold, respectively, wherein the first safety threshold is less than the second safety threshold.

5. The method of claim 4, wherein, The step of maximizing the electrolysis efficiency as the optimization target, taking the hydrogen content in oxygen less than or equal to the preset safety threshold as the constraint condition, and performing constraint optimization on the operating pressure and alkali flow to obtain the target operating pressure and target alkali flow under the corresponding current and temperature conditions comprises: for each preset optimization period, the following processing is performed: for each optimization subtask, the following processing is performed: the local operating pressure and the corresponding local alkali flow of the previous optimization period are taken as the candidate operating pressure and the corresponding candidate alkali flow of the current optimization period; wherein a preset number of candidate operating pressures and the corresponding candidate alkali flows are randomly generated in the first optimization period; determine the corresponding electrolysis efficiency and the hydrogen content in oxygen based on the temperature and the current under the working condition, and the candidate operating pressure and the corresponding candidate caustic flow rate; maximize the electrolysis efficiency as an optimization target, and perform preset number of optimization updates on the candidate operating pressure and the candidate caustic flow rate under the constraint condition that the hydrogen content in oxygen is less than or equal to a preset safety threshold, to obtain an initial local optimal solution set of the optimization subtask; wherein the initial local optimal solution set includes a preset number of candidate operating pressures with the highest electrolysis efficiency in the optimization process and the candidate caustic flow rates corresponding to the candidate operating pressures; migrate the initial local optimal solution sets between the optimization subtasks to obtain the final local optimal solution set of each optimization subtask in the optimization period, and after all the optimization subtasks are migrated, enter the processing of the next optimization period until a preset maximum optimization number is reached, and select the highest electrolysis efficiency from the local optimal solution set of the first optimization subtask as the target operating pressure and the target caustic flow rate.

6. The method of claim 4, wherein, The step of fusing the local caustic flow rates to obtain the final target caustic flow rate includes: migrate the initial local optimal solution sets corresponding to the second optimization subtask and the third optimization subtask to the initial local optimal solution set of the first optimization subtask to form the final local optimal solution set of the first optimization subtask; migrate the initial local optimal solution sets corresponding to the first optimization subtask and the second optimization subtask to the initial local optimal solution set of the third optimization subtask to form the final local optimal solution set of the third optimization subtask; migrate the local caustic flow rates corresponding to the first optimization subtask and the third optimization subtask to the initial local optimal solution set of the second optimization subtask to form the final local optimal solution set of the second optimization subtask.

7. A method for regulating a hydrogen production system, characterized in that, The control method includes: obtain the current, temperature, operating pressure and caustic flow rate at the current sampling time, and determine the target operating pressure and target caustic flow rate under the current and temperature conditions; wherein the target operating pressure and the target caustic flow rate are obtained by constraint optimization through the operating parameter optimization method of the hydrogen production system according to any one of claims 1-6; calculate the difference between the operating pressure and the target operating pressure, and the difference between the caustic flow rate and the target caustic flow rate, and accordingly control the operating pressure and the caustic flow rate of the hydrogen production system.

8. A system for optimizing operating parameters of a hydrogen production system, characterized in that, The system includes: a parameter acquisition module for acquiring the current, operating pressure, temperature and caustic flow rate of the hydrogen production system under multiple different working conditions; an electrolysis efficiency calculation module for determining the electrolysis efficiency of the hydrogen production system under the corresponding working condition based on the current, operating pressure and temperature under various working conditions; an oxygen hydrogen content calculation module for determining the hydrogen content in oxygen of the hydrogen production system under the corresponding working condition based on the operating pressure and caustic flow rate under various working conditions; An optimization module is configured to maximize electrolysis efficiency as an optimization objective, with hydrogen content in oxygen being less than or equal to a preset safety threshold as a constraint condition, and to perform constraint optimization on the operating pressure and the alkali flow to obtain a target operating pressure and a target alkali flow under a corresponding current and temperature condition.

9. An electronic device, comprising: The electronic device includes: one or more processors; a storage device for storing one or more programs, which, when executed by the one or more processors, cause the electronic device to implement the operating parameter optimization method of the hydrogen production system of any one of claims 1 to 6 or the regulation method of the hydrogen production system of claim 7.

10. A computer-readable storage medium, characterized in that, a computer program stored thereon, which, when executed by a processor of a computer, causes the computer to perform the operating parameter optimization method of the hydrogen production system of any one of claims 1 to 6 or the regulation method of the hydrogen production system of claim 7.

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