Method and system for establishing simulation model of hydrogen production system by alkaline electrolysis of water

Abstract

The application relates to the technical field of hydrogen production by water electrolysis, and particularly provides a method and system for establishing a simulation model of an alkaline water electrolysis hydrogen production system, which comprises the following steps: establishing dynamic mathematical models of an electrolytic tank subsystem and an auxiliary subsystem of the alkaline water electrolysis hydrogen production system; connecting the models of the electrolytic tank subsystem and the auxiliary subsystem according to the input-output relationship of the system, taking the gas-liquid two-phase flow work medium flow as the input, taking the temperature and pressure of the work medium at the outlets of the subsystems as the output, performing simultaneous solution, and obtaining the model of the alkaline water electrolysis hydrogen production system; performing steady-state simulation by using system design parameters, and in the case of passing the consistency verification, building a PID control module, and determining the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system. The application realizes the dynamic simulation of the changes of internal physical parameters and external performance of the electrolytic tank under various working conditions by analyzing the component models of the alkaline water electrolysis hydrogen production system and establishing the dynamic mathematical models of the components.

Description

Technical Field

[0001] This application relates to the field of hydrogen production technology through water electrolysis, and in particular to a method and system for establishing a simulation model of an alkaline water electrolysis hydrogen production system. Background Technology

[0002] Hydrogen energy, as a clean and efficient secondary energy carrier, possesses unique advantages such as high energy density, long storage period, and cross-regional allocation, making it an important pathway to achieve large-scale, long-term energy storage and low-carbon energy transition. Dynamic simulation of a water electrolysis hydrogen production system can simulate key parameters such as hydrogen production efficiency, gas purity, and temperature / pressure distribution under fluctuating power input, providing quantitative basis for system optimization design and safe operation, thereby reducing investment and operational risks.

[0003] However, hydrogen production systems via electrolysis involve strong coupling between disciplines such as electrochemistry, thermodynamics, fluid mechanics, gas diffusion, and automatic control. Their dynamic processes are complex, making simulation modeling challenging. Existing simulation methods and software, such as ASPEN Plus and HYSYS, can achieve steady-state simulations of chemical processes, but they lack adaptability to dynamic conditions such as power fluctuations and struggle to accurately describe transient processes like start-up, shutdown, and load changes. While MATLAB / Simulink is widely used in control system modeling, its description of the complex multiphysics (electro-thermal-fluid-mass transfer) mechanisms within the electrolyzer often relies on simplification assumptions, resulting in limited modeling accuracy. Dedicated fuel cell simulation software, while powerful in microscale multiphysics coupling, consumes significant computational resources, making it difficult to directly apply to long-term dynamic simulations at the system level (including power supply, electrolyzer, separation, and purification). Summary of the Invention

[0004] To address the aforementioned issues, this application provides a method for establishing a simulation model of an alkaline water electrolysis hydrogen production system. By analyzing the models of each component of the alkaline water electrolysis hydrogen production system, a dynamic mathematical model of each component is established, enabling dynamic simulation of the changes in internal physical parameters and external performance of the electrolyzer under various operating conditions.

[0005] To achieve the objectives of this application, the following technical solution is provided: Firstly, this application provides a method for establishing a simulation model of an alkaline water electrolysis hydrogen production system, including: Dynamic mathematical models of the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system are established. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. Based on the electrolyzer subsystem and the auxiliary subsystem, the models of the electrolyzer subsystem and the auxiliary subsystem are connected according to the system input-output relationship. The flow rate of the gas-liquid two-phase working fluid is taken as the input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and the auxiliary subsystem are taken as the output. The models of the alkaline water electrolysis hydrogen production system are obtained by solving the system simultaneously. Steady-state simulation was performed using system design parameters. After verifying the consistency between the simulation results and the design parameters, a PID control module was built to determine the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system.

[0006] A further improvement in this application is that the dynamic mathematical model for establishing the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system includes: constructing a main electrode plate model based on the principles of energy conservation and charge conservation, and establishing the temperature dynamics, electron current, and potential distribution relationship of the main electrode plate; considering the gas-liquid two-phase flow characteristics, and based on the principles of mass conservation, energy conservation, and momentum conservation, establishing the dynamic relationship of flow, heat transfer, and mass transfer between the electrolyte and the generated gas, and constructing the flow channel model; constructing a porous electrode model, coupling the electrochemical reaction, gas-liquid two-phase flow, charge transport, and heat and mass transfer multi-physics field coupling mechanism, and establishing the internal material of the electrode. The correlation between transport, potential distribution, temperature change, and reaction kinetics characterizes the dynamic reaction and multi-field coupled operation characteristics of porous electrodes. A membrane model is constructed based on energy conservation, charge conservation, and transmembrane mass transfer mechanisms, establishing the dynamic relationships of temperature, ion conduction, and component diffusion / permeation within the membrane to describe the membrane's barrier and mass transfer characteristics. The lumped parameter method is used to model the gas-liquid separator, valves, pumps, heat exchangers, reactors, component distributors, and pipelines, resulting in models for the gas-liquid separator, valves, pumps, heat exchangers, reactors, component distributors, and pipelines.

[0007] A further improvement in this application is that the lumped parameter method is used to model the gas-liquid separator, valves, pumps, heat exchangers, reactors, component distributors, and pipelines to obtain the gas-liquid separator model, the valve model, the pump model, the heat exchanger model, the reactor model, the component distributor model, and the pipeline model. This includes: based on the principles of mass conservation, energy conservation, phase equilibrium, and hydrostatic pressure, performing gas-liquid two-phase separation, medium energy storage, and phase dynamic characterization to construct the gas-liquid separator model; and constructing the valve model, wherein, based on the principle of throttling pressure drop and first-order dynamic response of opening, the valve's throttling pressure drop, flow regulation, and dynamic opening and closing characteristics are characterized; the pressure drop is the difference between the valve inlet and outlet pressures. The pump model is constructed based on the principle of isentropic efficiency, energy transfer, and mechanical loss, which characterizes the fluid pressurization, energy conversion, and power consumption characteristics. The heat exchanger model is constructed by performing heat exchange calculations for hot and cold fluids based on the principles of mass conservation, energy conservation, and logarithmic mean temperature difference heat transfer. The reactor model is constructed by characterizing component conversion and reaction heat effects based on the principles of mass and energy balance, and by processing multi-branch flow rates, components, and energy distribution. Finally, the pipeline model is obtained by calculating fluid transport and pressure loss based on the fundamental principles of fluid mechanics, as well as the laws governing flow resistance, pressure drop, and flow state.

[0008] A further improvement of this application is that the auxiliary subsystem further includes a power supply model, which adopts a feature modeling method and includes the AC / DC conversion process and the DC / DC transformation process.

[0009] A further improvement in this application is that the steady-state simulation using system design parameters includes: inputting the test conditions into the alkaline water electrolysis hydrogen production system model; estimating parameters using initial experimental test data in the gPROMS software program; adjusting the undetermined parameters in the model using the least squares method to make the model simulation output best fit the initial experimental test data, thus completing model calibration; verifying the calibrated model using independent data with variable loads; quantitatively comparing the predicted and measured curves; and analyzing the randomness of error indices and residuals; when the model output matches the experimental test data within a preset error range, the consistency verification between the simulation results and the design parameters is passed.

[0010] A further improvement of this application is that, when the calibration result between the model output and the experimental test data exceeds the preset error range, the key mechanism model of the alkaline water electrolysis hydrogen production system model is corrected by adding correction terms and correction factors.

[0011] A further improvement in this application is that the PID control model is specifically as follows: ; ; ; ;

[0012] ; ; In the formula, For operation variables; The variable value when there are no errors during the operation; It is a proportional term; It is an integral term; For the derivative term; This is the deviation value. For controller gain; Set values ​​for the controller; For process variables; For the Laplace operator; The derivative is the time constant. The rate of change of deviation; In the Laplace domain, the transfer function of the ideal PID control algorithm is given by the following equation: ; When assuming the proportional gain applies to scaled controller inputs and outputs, the controller inputs and outputs are scaled before being used in the PID control algorithm: ; ; in, It is the smallest process variable; It is the largest process variable; It is the smallest operand; It is the largest operating variable.

[0013] A further improvement in this application is that the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system includes: hydrogen-side gas-liquid separator level control: controlling the hydrogen-oxygen level difference by adjusting the opening of the regulating valve on the hydrogen outlet side; oxygen-side gas-liquid separator pressure control: controlling the pressure of the oxygen-side gas-liquid separator by adjusting the opening of the regulating valve on the oxygen outlet side; alkali solution temperature control: controlling the alkali solution temperature by adjusting the valve opening of the cooling water branch; water replenishment control: monitoring the liquid level of the hydrogen-side gas-liquid separator to perform step-by-step water replenishment; hydrogen-side condensate-water separator level control: controlling the liquid level fraction on the hydrogen side by adjusting the valve opening of the gas-water separator drain outlet; oxygen-side condensate-water separator level control: controlling the liquid level fraction on the oxygen side by adjusting the valve opening of the gas-water separator drain outlet.

[0014] A further improvement of this application is that the liquid level control of the hydrogen-side gas-liquid separator, the pressure control of the oxygen-side gas-liquid separator, and the temperature control of the alkali solution all adopt PID control; the water replenishment control adopts upper and lower limit single-point control.

[0015] Secondly, this application provides a simulation model establishment system for an alkaline water electrolysis hydrogen production system, used to implement the above-mentioned method for establishing a simulation model for an alkaline water electrolysis hydrogen production system, including: The first step is to establish a dynamic mathematical model for the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. The second module is used to connect the models of the electrolyzer subsystem and the auxiliary subsystem according to the system input-output relationship, based on the electrolyzer subsystem and the auxiliary subsystem. The gas-liquid two-phase flow working fluid flow rate is used as input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and the auxiliary subsystem are used as output. The modules are solved simultaneously to obtain the alkaline water electrolysis hydrogen production system model. The simulation control module is used to perform steady-state simulation using system design parameters, and after verifying the consistency between the simulation results and the design parameters, to build a PID control module to determine the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system.

[0016] Compared with the prior art, the present invention has the following beneficial effects: This application provides a method and system for establishing a simulation model of an alkaline water electrolysis hydrogen production system. The method involves establishing dynamic mathematical models of the electrolyzer subsystem and auxiliary subsystems of the alkaline water electrolysis hydrogen production system. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. The models of the electrolyzer subsystem and auxiliary subsystem are connected according to the system input-output relationship. The flow rate of the gas-liquid two-phase working fluid is used as the input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and auxiliary subsystem are used as the output. A simultaneous solution is obtained to obtain the alkaline water electrolysis hydrogen production system model. Steady-state simulation is performed using system design parameters. After verifying the consistency between the simulation results and the design parameters, a PID control module is built to determine the control strategy of the alkaline water electrolysis hydrogen production system simulation model. Therefore, this embodiment designs a complete process flow for an alkaline water electrolysis hydrogen production system, including an electrolyzer, gas-liquid separation, hydrogen purification, and cooling system. It determines the key design parameters under rated operation, variable load, and start-up / shutdown conditions. Then, by combining equipment characteristic curves and experimental data, it calibrates and verifies the parameters of core component models such as the electrolyzer and heat exchanger, establishes a system steady-state simulation benchmark, and further introduces control logic to achieve optimized construction of the dynamic simulation model. Attached Figure Description

[0017] The accompanying drawings are provided to further understand this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. Figure 1 A schematic flowchart of an optional method for establishing a simulation model of an alkaline water electrolysis hydrogen production system provided in this application embodiment; Figure 2 A simulation model diagram of an alkaline water electrolysis hydrogen production system provided in the embodiments of this application; Figure 3 A flowchart illustrating the calibration process of the simulation model for the alkaline water electrolysis hydrogen production system provided in this application embodiment; Figure 4 The simulation results of the effect of different alkaline solution flow rates on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 5 The simulation results of the impact of different alkaline flow rates on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 6 Simulation results of the effect of different alkaline solution flow rates on the hydrogen concentration in oxygen in the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 7 The simulation results of the effect of different pressures on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 8 The simulation results of the impact of different pressures on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 9 Simulation results of the effect of different pressures on the hydrogen concentration in oxygen in the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 10 The simulation results of the effect of different currents on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 11 The simulation results of the impact of different currents on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 12 The simulation calculation results of the effect of different currents on the hydrogen concentration in oxygen in the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 13 The simulation results of the effect of different start-up temperatures on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 14 The simulation results of the impact of different start-up temperatures on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 15 The simulation results show the effect of different start-up temperatures on the hydrogen concentration in the oxygen of the water electrolysis hydrogen production system provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0019] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature; in the description of this application, unless otherwise stated, "multiple" means two or more.

[0020] The alkaline water electrolysis hydrogen production system uses an alkaline electrolyte solution as the ion conduction medium. Direct current is applied to the electrolyzer, causing water molecules to undergo an electrolytic reaction, decomposing into hydrogen and oxygen. It integrates pure water preparation, electrolyte circulation, electrolysis reaction, gas-liquid separation, gas purification, cooling and temperature control, rectification power supply, and a safety control unit, achieving a stable and continuous hydrogen production process. The specific process flow of the alkaline water electrolysis hydrogen production system is as follows: Under the action of direct current and alkaline electrolyte, water is decomposed into hydrogen and oxygen. Subsequently, the gas-liquid mixture enters the hydrogen-side and oxygen-side gas-liquid separators for preliminary separation. The separated gas is condensed by a cooler and then enters a condensate-gas-water separator for further purification. The hydrogen is output after subsequent purification and compression, while the oxygen is either discharged or utilized. Simultaneously, the separated alkaline solution is driven by a circulation pump, cooled by a cooler, and returned to the electrolyzer for reuse. An automatic water replenishment system maintains the system's water balance, forming a continuous, closed-loop operation. The specific nodes and mechanisms at these nodes are as follows: the electrolyzer decomposes water based on an electrochemical reaction mechanism, and its efficiency is affected by current density, temperature, and alkali concentration; the gas-liquid separator uses the density difference between gas and liquid to achieve gravity sedimentation separation, and maintains the pressure difference balance on both sides through liquid level and pressure control; the cooling system removes the heat of reaction based on the heat transfer mechanism, and the temperature control loop maintains the optimal operating temperature of the alkali solution; the condensate gas-water separator removes residual liquid droplets from the gas through condensation and inertial capture mechanisms, and drains water in a timely manner with the help of liquid level control; the water replenishment system, based on the stoichiometric relationship of water consumed by electrolysis, relies on liquid level feedback to achieve step-by-step water replenishment, jointly ensuring the material and energy balance of the system, and achieving safe, stable, and efficient continuous hydrogen production.

[0021] Dynamic simulation of a water electrolysis hydrogen production system can simulate key parameters such as hydrogen production efficiency, gas purity, and temperature / pressure distribution under fluctuating power input, providing quantitative basis for system optimization design and safe operation, thereby reducing investment and operational risks. However, the water electrolysis hydrogen production system involves strong coupling between disciplines such as electrochemistry, thermodynamics, fluid mechanics, gas diffusion, and automatic control, and its dynamic processes are complex, making simulation modeling highly challenging. Existing simulation methods and software, such as ASPEN Plus and HYSYS, can achieve steady-state simulation of chemical processes, but they lack adaptability to dynamic conditions such as power fluctuations and struggle to accurately describe transient processes like start-up, shutdown, and load changes. While MATLAB / Simulink (Matrix Laboratory and graphical simulation environment) is widely used in control system modeling, its description of the complex multiphysics (electro-thermal-fluid-mass transfer) mechanisms within electrolyzers often relies on simplification assumptions, resulting in limited modeling accuracy. Dedicated fuel cell simulation software (such as COMSOL and COMSOL Multiphysics) excels in microscale multiphysics coupling, but its high computational resource consumption makes it difficult to directly apply to long-term dynamic simulations at the system level (including power supply, electrolyzer, separation, and purification). Therefore, existing tools still face challenges in accurately simulating the long-term impact of electrolyzer operating mechanisms and strategies.

[0022] To address the aforementioned technical problems, the present invention proposes the following technical solutions and corresponding embodiments.

[0023] The following is combined with Figures 1 to 15 The illustrated embodiments describe the technical solution of the present invention: Example 1 An embodiment of this application provides a method for establishing a simulation model of an alkaline water electrolysis hydrogen production system, comprising the following steps S101 to S103: Step S101: Establish dynamic mathematical models of the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system.

[0024] In this embodiment, the alkaline water electrolysis hydrogen production system includes an electrolyzer subsystem and an auxiliary subsystem. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. In this embodiment, because the variables within the system change over time during the reaction process, it is necessary to establish separate dynamic mathematical models for each component of the subsystem to analyze its working principle. This embodiment employs a mechanistic modeling method, considering components such as the main electrode plate, flow channel, porous electrode, and diaphragm within the electrolyzer subsystem. Detailed modeling of the mass transfer, energy transfer, momentum transfer, and electrochemical reaction mechanisms within the electrolyzer is performed. This embodiment particularly considers the two-phase flow and electrochemical kinetics mechanisms within the system, enabling the model to accurately simulate the internal physical parameters and external performance of the electrolyzer under various operating conditions.

[0025] In this embodiment, current and heat are transferred within the main electrode plate (main electrode plate model), involving energy conservation equations and current conservation equations. The energy conservation equation describes the temperature change of the main electrode plate over time (temperature dynamics), while the current conservation equation describes the voltage loss caused by the current flow. As a feasible implementation method, the construction process of the main electrode plate model in this embodiment is as follows: 1) Constructing the energy conservation equations involved in the main electrode plate: The calculation formula for the energy conservation equations is as follows: ; In the formula, The thickness direction of the anode and cathode; Temperature, unit ; Specific heat capacity, unit ; Density, unit ; Electron current density, in units ； Electron conductivity, in units of ; The thermal conductivity of the electrode material; 2) Constructing the current and potential equations related to the main electrode: ; ; In the formula, Electric potential, unit ; For current, unit A .

[0026] In this embodiment, the flow channel model considers a gas-liquid two-phase flow model, the fluid's mass conservation equation, energy conservation equation, and momentum conservation equation, specifically: mass conservation equation: ; In the formula, This represents the one-dimensional spatial axial coordinates (flow direction). The volume fraction of the gas / liquid phase, in units of... ; The density of the gas / liquid phase, in units of ; Gas / liquid phase velocity, unit: ; In gas / liquid phase Mass fraction of components, in units ; In gas / liquid phase Mass transfer source terms of components; Energy conservation equation: ; In the formula, This is the gas / liquid phase mass enthalpy, in units of ; The heat flux density between the gas / liquid phase and the main electrode plate within the flow channel, in units of ; The heat flux density between the gas / liquid phase and the porous electrode plate within the flow channel, in units of ; Momentum conservation equation: ; In the formula, Fluid pressure, unit ; For fluid dynamic viscosity, in units ; is the flow resistance coefficient.

[0027] In this embodiment, the mass conservation equation, energy conservation equation, momentum conservation equation, and electron conservation equation for each substance are considered in the porous electrode. The electrochemical reaction processes of each substance are described using the Nernst equation and the Butler-Volmer equation, and correlated with relevant conservation equations; specifically: Mass conservation equation for gas-liquid two-phase flow: ; In the formula, Components in electrochemical reactions stoichiometric coefficients; Electron productivity of electrochemical reactions, in units of ; The number of electrons participating in the reaction; Faraday constant, unit ; The overall porosity; Energy conservation equation (heat and mass transfer):

[0028] In the formula, Ion current density, in units ; To activate polarization potential, unit ; Ionic conductivity, in units of ; For reference equilibrium potential, unit ; For reference quality score, unit ; These are the stoichiometric coefficients for chemical reactions; Gas constant, unit ; The momentum conservation equation for gas-liquid two-phase flow: ; In the formula, Permeability of porous media; Equations for electron current and potential (charge transport): ; ; Ion current and potential equations (charge transport): ; ; In the formula, Ionic potential, unit: ; Nernst equation: ; In the formula, The half-cell potential of an electrochemical reaction, in units of... ; Gibbs free energy of an electrochemical reaction, in units of ; This represents the number of electrons exchanged in the electrochemical reaction. Apparent mole fraction, in units ; P For pressure, unit ; For reference pressure, unit ; Let be the stoichiometric coefficient of component i in reaction j; Equation for calculating overpotential: ; ; In the formula, The overpotential on the anode side, in units of ; The electron potential on the anode side, in units of ; The ionic potential on the anode side, in units of ; The half-cell potential on the anode side, in units of ; The overpotential on the cathode side, in units ; The half-cell potential on the cathode side, in units of ; The electron potential on the cathode side, in units of ; The ionic potential on the cathode side, in units of ; Butler-Volmer equations:

[0029] In the formula, The current density of the reaction, in units ; This represents the number of electrons exchanged in the electrochemical reaction. The activation energy of the reaction is expressed in units of... ; For reference current density, units ; Gas constant, unit ; Temperature, unit ; Temperature, unit ; Apparent mole fraction, in units ; For reference pressure, unit ; The reaction order is [number]. The transport coefficient for the reduction reaction; The transport coefficient for the oxidation reaction; Faraday constant, unit .

[0030] In the embodiments of this application, the energy conservation equation, electron conservation equation, and ion conservation equation are considered in the membrane, and the transmembrane transport model of each substance is also considered, specifically: Energy conservation equation: ; In the formula, Density of solid, in units ; For liquid density, units ; Specific enthalpy of liquid, unit ; Equations for electron current and potential: ; Equations for ion current and potential: ; Diaphragm diffusion calculation equation: ; In the formula, Let i be the diffusion coefficient of component i, in units of... ; The diffusion coefficient of component i at the reference temperature is given in units of... ; The activation energy is the diffusion coefficient at the reference temperature, expressed in units of... ; Temperature, unit ; Temperature, unit R is the gas constant; Diaphragm permeability calculation equation: ; In the formula, Let i be the permeability coefficient of component i, in units of... ; The permeability coefficient of component i at the reference temperature, in units of ; The activation energy of the permeability coefficient at the reference temperature is expressed in units of... ; In the embodiments of this application, in addition to the electrolytic cell subsystem (main electrode model, flow channel model, porous electrode model, diaphragm model), gas-liquid separator, valve, compressor, alkali pump, heat exchanger, reactor, component distributor, pipeline, etc. are also modeled. The lumped parameter method is mainly used for modeling, without considering the distribution characteristics of their internal physical quantities.

[0031] Specifically, the gas-liquid separator model is as follows: 1) Mass conservation equation: ; In the formula, Characteristic volume, unit ; The volumetric mass of component i (medium energy storage), in units ; For inlet mass flow rate, in units ; The mass flow rate of the outlet liquid, per unit ; The mass flow rate of the outlet gas, per unit ; The mass fraction of inlet component i, in units ; The mass fraction of component i in the liquid phase, in units of ; The mass fraction of component i in the gas phase, in units of ; 2) Energy Conservation Equation ; ; ; ; ; ; In the formula, Energy retention per unit volume of fluid (energy storage in the medium), per unit ; Energy retention per unit volume of wall surface, per unit ; Specific enthalpy of inlet mass, unit ; The heat flow rate of the supplied fluid, per unit ; The heat flow rate transferred from the fluid to the wall, in units ; The heat flux transferred from the wall to the outside, in units ; Specific enthalpy of the outlet liquid, in units ; Specific enthalpy of the outlet gas, in units ; For specific enthalpy, unit ; For pressure, unit For fluid temperature, in units ; For ambient temperature, in units ; Wall temperature, unit ; For fluid volume, in units ; For wall volume, unit ; The heat transfer coefficient between the fluid and the wall, in units of ; The heat transfer coefficient between the wall and the outside environment, in units of ; The heat exchange area of ​​the inner wall surface, per unit ; The heat exchange area of ​​the outer wall surface, per unit ; The density of the wall surface, in units ; For wall heat capacity, unit ; 3) Phase equilibrium equations In this embodiment, phase equilibrium is achieved by equalizing fugacity, where the fugacity coefficient is calculated from the physical property package: ; ; ; In the formula, Let i be the fugacity coefficient of component i in the gas phase; Let i be the fugacity coefficient of component i in the liquid phase; the relative amounts in each phase can be determined through the mass and energy balance of the phases, specifically: ; ; ; In the formula, The mass retention per unit volume of liquid, per unit ; The mass retention of gas per unit volume, per unit ; The total mass of material retained per unit volume, per unit ; Characterizing the dynamic properties of phase distribution: ; ; ; In the formula, This refers to the liquid volume fraction, in units of... ; For liquid density, units ; This refers to the density of a gas, in units of... ; The total mass fraction of component i, in units ; 4) Pressure drop equation In this embodiment, assuming the liquid outlet is located at the bottom of the container, and considering the effect of static pressure drop, the relationship between the input and output pressures and the liquid height inside the tank (fluid static pressure law / static pressure drop characteristics) is given by the following formula: ; In the formula, Liquid interfacial pressure, unit ; Due to export pressure, unit ; The density of the liquid phase, in units of ; For gravitational acceleration, in units ; Liquid level fraction (relative height of container), unit ; For container height, in units .

[0032] In this embodiment, the valve model is modeled using the lumped parameter method. The fluid passing through the valve is considered an adiabatic process with no change in kinetic energy; therefore, the enthalpy of the fluid remains unchanged after passing through the valve. Wherein: 1) Pressure drop calculation equation (throttling pressure drop principle), specifically: ; In the formula, For pressure drop, unit ; For valve inlet, unit ; For valve outlet, unit Here, the pressure drop in the valve depends on the valve type, fluid properties, and flow rate. The pressure drop is defined as the difference between the valve inlet and outlet pressures. Here, the valve generates pressure loss through throttling, and throttling pressure drop is the core physical law of valves. 2) Flow calculation equation, specifically: ; In the formula, For mass flow rate, per unit ; The flow resistance coefficient is expressed in units of... ; This represents the actual valve opening. Since the actual valve opening may vary to meet specific system requirements, if the valve opening / closing is not rate-limited, the valve opening position will have a first-order response characteristic. The valve opening equation is as follows: ; In the formula, Time constant, in units ; Set the valve opening degree.

[0033] In this embodiment, the pump model simulates fluid flow through the pump. The fluid outlet temperature is calculated by considering the fluid compression process, which is defined relative to an ideal compression process. The deviation from the ideal is defined by a specified ideal efficiency; the calculation equations for its isentropic efficiency, outlet enthalpy, mechanical efficiency, etc., are as follows: 1) Isoentropy efficiency: ; ; In the formula, Specific enthalpy of inlet mass, unit ; The specific enthalpy of the outlet mass of an isentropic process, in units of ; For inlet pressure, unit ; Due to export pressure, unit ; Power required for an isentropic process, unit ; For actual fluid supply power, unit ; Efficiency of isentropic process, in % %. For mass density, units ; 2) Export enthalpy In this embodiment, the outlet enthalpy is determined by the actual power and flow rate of the supplied fluid, specifically: ; In the formula, For export quality specific enthalpy, unit ; 3) Mechanical efficiency Due to mechanical losses, the pump's mechanical power demand exceeds the power required to compress the fluid. For a pump operating under steady-state conditions, mechanical losses can be expressed as mechanical efficiency, specifically: ; In the formula, For the pump's mechanical power requirements, unit ; Mechanical efficiency, expressed in percent.

[0034] In this embodiment, the cooler model (heat exchanger model) can be used to reduce the temperature of the material flow. The desired outlet temperature can be directly specified, or the outlet temperature can be calculated based on the specified heat transfer area, thermal conductivity, and cooling fluid temperature in the cooler. Based on the principles of mass conservation, energy conservation, and logarithmic mean temperature difference heat transfer, heat exchange and heat transfer calculations of hot and cold fluids are performed to construct a heat exchanger model. Its mass conservation equation, energy conservation equation, and heat transfer process calculation equations are as follows: 1) Mass conservation equation: ; ; In the formula, Inlet mass flow rate, in units ; Export quality flow rate, in units ; For inlet quality score, in units ; Export quality score, unit ; 2) Energy conservation equation: ; In the formula, Specific enthalpy of inlet mass, unit ; Export quality flow rate, in units ; For export quality specific enthalpy, unit ; For heat exchange power, unit ; 3) Equations for calculating the heat transfer process: This embodiment uses the Log Mean Temperature Difference (LMTD) method for the model's heat exchange process, specifically as follows: ; In the formula, The overall heat transfer coefficient is expressed in units of... ; For heat exchange area, unit ; This is the logarithmic mean temperature difference, in units of ; As a correction factor, in pure parallel / countercurrent arrangements ; The temperature difference when hot and cold flows are in parallel is given by the following formula: ; ; In the formula, The inlet temperature of the hot fluid, in units of ; The inlet temperature of the cold fluid is expressed in units of... ; The outlet temperature of the hot fluid, in units of ; The cold fluid outlet temperature, in units of .

[0035] In this embodiment, based on the laws of mass conservation, energy conservation, and reaction transformation, component transformation and reaction heat effects are characterized to construct a reactor model. This reactor transformation model is used to simulate a reactor with known conversion rates for each reaction, where the conversion rate of each reaction is defined relative to a baseline component. In this model, reactions can be specified as occurring in parallel. The mass conservation equation and energy conservation equation are calculated as follows: 1) Mass conservation equation In a conversion reactor, reactions can be carried out in parallel or in series. For parallel reactions, the conversion rate of each reaction is applied to the reactor inlet composition, specifically: ; In the formula, The rate of formation / consumption of component i in reaction j is expressed in kmol / s. The inlet molar flow rate is expressed in kmol / s. The reference component in reaction j The import mole fraction, in mol / mol; For reaction j relative to the reference component Conversion rate, in % Let be the stoichiometric coefficient of component i in reaction j, in mol / mol. The reference component in reaction j Stoichiometric coefficients, in mol / mol; For each component i, the outlet component flow rate is determined through mass balance, specifically as follows: ; ; In the formula, This is the outlet mass flow rate, in kg / s; The mass fraction of component i in the inlet stream, in kg / kg; The mass fraction of component i in the effluent stream, in kg / kg; Here is the molecular weight of component i, in kg / mol; The import mass flow rate is expressed in kg / s. 2) Energy conservation equation: ; In the formula, Specific enthalpy of imported material, in kJ / kg; Specific enthalpy for export quality, unit: kJ / kg; The energy rate at which the reactor is heated is expressed in kJ / s.

[0036] In this embodiment, the component splitter model can be used to represent a theoretical separation stage. Based on the principle of mass and energy balance, multi-branch flow, component, and energy distribution are performed to construct the component splitter model. Its mass conservation equation and energy conservation equation are calculated as follows: 1) Mass balance equation: ; In the formula, The outflow ratio of component i in flow s; The mass fraction of component i in the inlet stream, in kg / kg; The mass flow rate of the outlet flow S is expressed in kg / s. The mass fraction of component i in the effluent stream S, in kg / kg; 2) Energy balance equation: ; In the formula, Specific enthalpy of imported material, in kJ / kg; Enthalpy of the outlet flow s, in kJ / kg; The import energy rate is expressed in kW.

[0037] In this embodiment, a pipe model describes the flow of fluid through a pipe. In this model, it is assumed that the fluid properties are uniform throughout the pipe, and the relationship between flow rate and pressure drop is determined using a friction factor correlation. The calculation processes for the basic flow coefficient equation, fluid velocity and Reynolds number equation, average pipe pressure equation, pipe pressure drop equation, and fully turbulent drag coefficient equation are as follows: 1) Basic flow coefficient equation: ; In the formula, For pipeline gas mass flow rate, in units ; The flow coefficient of the pipeline, in units of ; and These are the inlet and outlet pressures of the pipeline, in units of... ; 2) Fluid velocity and Reynolds number equations: ; ; In the formula, The cross-sectional area of ​​the pipe, in units of ; Pipe inner diameter, unit ; The average fluid velocity is expressed in units of... ; For fluid mass density, in units ; For fluid dynamic viscosity, in units ; The Reynolds number for pipeline flow; 3) Mean Pipe Pressure Equation: ; In the formula, For average pipeline pressure, unit ; 4) Pipeline pressure drop equation ; ; In the formula, For pipe length, unit ; It is the equivalent flow resistance coefficient; It is the turbulent friction factor; and These are the elevations of the pipeline inlet and outlet, in units of... ; For gravitational acceleration, in units ; 5) Equation for drag coefficient in fully turbulent flow: ; In the formula, For pipe wall roughness, unit ; Pipe inner diameter, unit .

[0038] In this embodiment, the power supply model employs a feature-based modeling method, encompassing the AC / DC conversion process and the DC / DC transformation process, with the following equations: ; ; In the formula, For AC input voltage and current, in units ; The voltage and current of the DC output after AC conversion, in units of ; Voltage and current of the electrolytic cell, in units of ; AC / DC conversion efficiency, unit 1; DC / DC conversion efficiency, in units of 1.

[0039] Step S102: Based on the electrolyzer subsystem and the auxiliary subsystem, connect the models of the electrolyzer subsystem and the auxiliary subsystem according to the system input-output relationship, and take the flow rate of the gas-liquid two-phase working fluid as the input and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and the auxiliary subsystem as the output, and solve them simultaneously to obtain the alkaline water electrolysis hydrogen production system model.

[0040] In the embodiments of this application, reference is made to Figure 2 The integrated modeling of the alkaline water electrolysis hydrogen production system forms a closed loop through the real-time transmission and feedback of key state variables among the sub-models. In this embodiment, after establishing the main electrode plate model, flow channel model, porous electrode model, and diaphragm model of the electrolyzer subsystem, as well as the gas-liquid separator model, valve model, pump model, heat exchanger model, reactor model, component distributor model, and pipeline model of the auxiliary subsystem in gPROMS software, the models are connected according to the input-output relationship. The flow rate of the gas-liquid two-phase working fluid is used as the input of the alkaline water electrolysis hydrogen production system model, and the temperature and pressure of the working fluid at the outlet of each subsystem are used as the model output. By solving the simultaneous equations, the overall model of the alkaline water electrolysis hydrogen production system can be obtained.

[0041] Specifically, the electrochemical model (porous electrode model and main electrode plate model) outputs gas production and heat generation to drive the two-phase flow model (flow channel model and diaphragm model) and the thermal management model (internal electrode / electrode / flow channel coupled heat transfer + heat exchanger model). The gas holdup and flow resistance fed back by the two-phase flow model in turn correct the electrochemical reaction conditions (operating boundaries of the porous electrode model and main electrode plate model). The temperature field updated by the thermal management model synchronously affects both. After the system state changes are transmitted to the separation and control models of the auxiliary subsystem (gas-liquid separator model, valve model, pump model, component distributor model, pipeline model), control commands are triggered and the system boundary conditions are changed, thereby affecting the core unit (electrolyzer subsystem) in reverse. In other words, the electrochemical model generates gas and heat, providing the driving boundary for the two-phase flow and thermal management models; the two-phase flow model outputs gas holdup and flow resistance to inversely correct the electrochemical reaction conditions between the porous electrode and the main plate; the thermal management model's temperature field simultaneously couples and influences the electrochemical and two-phase flow characteristics; after the overall system operating state is transmitted to the separation and various auxiliary control models, the system inlet boundary is changed by adjusting flow rate, pressure, valve position, etc., which in turn acts inversely on all sub-models of the electrolyzer, realizing the bidirectional closed-loop simultaneous solution of multiple models within the electrolyzer and between the electrolyzer subsystem and auxiliary subsystems, ultimately forming a complete dynamic mathematical model of the alkaline water electrolysis hydrogen production system. This tight coupling of "mechanism-driven - state feedback - control intervention" enables the model to simulate the dynamic response of the system with high fidelity, providing a complete digital experimental platform for variable operating condition analysis, controller optimization, and safety boundary definition.

[0042] Step S103: Perform steady-state simulation using system design parameters, and after verifying the consistency between the simulation results and the design parameters, build a PID control module to determine the control strategy of the alkaline water electrolysis hydrogen production system model.

[0043] In the embodiments of this application, reference is made to Figure 3 The test conditions (including operating conditions such as temperature, pressure, and flow rate) and the corresponding system responses (such as product concentration and temperature distribution) are input into the alkaline water electrolysis hydrogen production system model formed in step S102. Using experimental test data, parameter estimation is performed in the program to verify the model's accuracy. Specifically, the program adjusts the undetermined parameters in the model using the least squares method to achieve the best match between the model output and the experimental test data. If the model matches the experimental test data within the set error range, the verification is successful, and the model can be used for prediction, control, or optimization.

[0044] If the calibration results do not meet the requirements, a new experimental design plan will be proposed, and the iterative process model will be optimized to finally achieve the requirements of a high-precision model. The core implementation directions of the optimization iteration include: modifying the key mechanism model by adding correction terms and correction factors to optimize the electrochemical equations to more accurately describe the dynamic overpotential of the startup process; using high-order finite element / volume methods or isogeometric analysis to achieve higher precision with fewer elements, thereby refining the multi-physics coupling; improving the dynamic and control characterization of the system (e.g., adding the dynamic delay and response characteristics of real components such as valves and distributors); and introducing an uncertainty quantification framework to quantify the uncertainty of input parameters such as material properties and boundary conditions, which is transmitted through the coupled system and affects the final results.

[0045] As a feasible implementation method, the simulation experiment verifies the system's startup and steady-state operation under rated load. First, using initial experimental data (dynamic curves of voltage, temperature, liquid level, etc.), the key mechanism parameters in the model (such as electrochemical kinetic parameters, two-phase mass transfer coefficient, heat dissipation coefficient, etc.) are adjusted through optimization algorithms to achieve the best fit between the simulation output and the experimental data, thus completing parameter estimation. Subsequently, another set of independent variable load experimental data is used to verify the calibrated model, quantitatively comparing the predicted and measured curves, and analyzing the randomness of error indices and residuals. Finally, the model is judged to pass the verification: if the dynamic and steady-state errors of all key variables are within the preset accuracy range and the residuals have no systematic deviation, the model is reliable (the consistency verification between the simulation results and design parameters is passed); if the error exceeds the limit or the trend is inaccurate, it indicates that the model has structural defects, and the model needs to be corrected and new targeted experiments designed for re-estimation and verification until a high-precision simulation model is formed.

[0046] In the alkaline electrolysis system model of this embodiment, in addition to the mathematical model of the alkaline electrolyzer and the auxiliary component model, a control model (PID control model) also needs to be built to simulate the relevant control processes in the actual system. Specifically, this model mainly involves six closed-loop control strategies: hydrogen-side gas-liquid separator level control, oxygen-side gas-liquid separator pressure control, alkaline solution temperature control, water replenishment control, and hydrogen / oxygen-side gas-water separator level control. Among them, hydrogen-side gas-liquid separator level control refers to real-time monitoring of the hydrogen-side liquid level by a level sensor, comparing it with the oxygen-side liquid level, and calculating the level difference; the controller adjusts the opening of the hydrogen outlet regulating valve according to the deviation, controlling the hydrogen discharge flow rate, thereby maintaining a dynamic balance between the liquid levels on both sides of hydrogen and oxygen. Oxygen-side gas-liquid separator pressure control refers to detecting the oxygen-side separator pressure by a pressure sensor, and the controller adjusts the opening of the oxygen outlet regulating valve according to the deviation between the set value and the measured value, controlling the oxygen output flow rate, and achieving stable oxygen-side pressure. Alkali solution temperature control refers to the real-time monitoring of alkali solution temperature by a temperature sensor. The controller adjusts the opening of the cooling water branch regulating valve based on the temperature deviation to control the cooling water flow rate, thereby maintaining the alkali solution temperature within the set range. Water replenishment control involves setting multiple liquid level thresholds based on the signal from the hydrogen-side gas-liquid separator level sensor. When the liquid level falls below a certain threshold, the corresponding water replenishment valve is activated for step-by-step water replenishment until the liquid level returns to a safe range. Hydrogen-side condensate-water separator level control involves monitoring the condensate level through a level sensor. The controller adjusts the opening of the drain outlet regulating valve based on the set liquid level to control the discharge of condensate, preventing excessively high liquid levels from affecting gas quality or equipment safety. The principle of oxygen-side condensate-water separator level control is the same as the hydrogen side, referring to the timely discharge and level stability of oxygen-side condensate through independent level detection and valve adjustment.

[0047] In this embodiment, the level control of the hydrogen-side gas-liquid separator, the pressure control of the oxygen-side gas-liquid separator, and the temperature control of the alkali solution all employ PID control, while the water replenishment control uses single-point control at upper and lower limits. Furthermore, in the simulation model of this embodiment, the complexity of the control model can be adjusted according to the model complexity and simulation objectives. In some examples, perfect control methods will be used instead of PID control in the control model.

[0048] In this embodiment, the PID control model equation is as follows: 1) The PID controller implements the practical form of the ideal PID algorithm. The ideal PID control algorithm determines the relationship between the process variable and the operating variable; this relationship is given by the following formula: ; In the formula, For operation variables; The variable value when there are no errors during the operation; It is a proportional term; It is an integral term; For the derivative term; 2) The proportional term, integral term, and derivative term all depend on the error signal; this error signal is defined as: ; In the formula, This is the controller error signal; Set values ​​for the controller; For process variables; 3) Proportional equation: ; In the formula, For controller gain; 4) Equation of the integral term: ; In the formula, The integral time constant; In the Laplace domain, it is given by the following equation: ; In the formula, For the Laplace operator; 5) Equation with derivative terms: ; In the formula, The derivative is the time constant; In the Laplace domain, it is given by the following equation: ; 6) Transfer function of ideal PID control algorithm In the Laplace domain, the transfer function of the ideal PID control algorithm is given by the following equation: ; 7) Scaling ratio When it is assumed that the proportional gain applies to scaled controller inputs (PV) and outputs (MV), the inputs and outputs are first scaled before being used in a PID control algorithm: ; ; in: It is the smallest process variable; It is the largest process variable; It is the smallest operand; It is the largest operating variable.

[0049] The control strategy of the alkaline water electrolysis hydrogen production system model in this embodiment is as follows: (1) Hydrogen-side gas-liquid separator level control: control the hydrogen-oxygen level difference by adjusting the opening of the regulating valve on the hydrogen outlet side; (2) Oxygen-side gas-liquid separator pressure control: control the pressure of the oxygen-side gas-liquid separator by adjusting the opening of the regulating valve on the oxygen outlet side; (3) Alkali temperature control: control the alkali temperature by adjusting the valve opening of the cooling water branch; (4) Water replenishment control: monitor the liquid level height of the hydrogen-side gas-liquid separator to perform step water replenishment; (5) Hydrogen-side condensate-water separator level control: control the liquid level fraction on the hydrogen side by adjusting the valve opening of the gas-water separator drain outlet; (6) Oxygen-side condensate-water separator level control: control the liquid level fraction on the oxygen side by adjusting the valve opening of the gas-water separator drain outlet.

[0050] In this embodiment, after obtaining the alkaline water electrolysis hydrogen production system model and its control strategy, dynamic simulation is performed to analyze the characteristic changes of key indicators of the system at different stages. Specifically, focusing on the instantaneous response characteristics of the system during startup, load reduction, and load variation stages, the study emphasizes the characteristic changes of key system indicators under different startup temperatures, startup speeds, startup strategies, load reduction strategies, and load variation strategies.

[0051] Taking cold-state rapid start-up as an example, simulation studies show that when the system is directly subjected to rated current from ambient temperature, the combined effect of electrochemical overpotential and thermal inertia leads to a significant instantaneous overshoot in the cell voltage. Simultaneously, a clear temperature gradient and hysteresis form within the electrolytic cell, and the rapid increase in gas production causes drastic fluctuations in separator pressure and liquid level, potentially affecting gas purity temporarily. This dynamic process profoundly reveals how current step excitation, through a multi-physics coupling chain involving electrochemistry, two-phase flow, and heat transfer, ultimately manifests as a macroscopic dynamic response at the system level. The core of this research lies in quantifying these transient stresses and fluctuations, thereby providing crucial quantitative evidence for optimizing start-up strategies (such as introducing preheating or current ramping), tuning control parameters to suppress fluctuations, and even improving equipment design to enhance dynamic stability.

[0052] Furthermore, this embodiment can efficiently integrate multidisciplinary models such as electrochemistry, thermofluidics, and control, and has the advantages of high model accuracy, strong full-condition simulation capability, and fast simulation speed, making it suitable for the design and operation optimization of hydrogen production systems.

[0053] The simulation model establishment method for the alkaline water electrolysis hydrogen production system provided in this embodiment involves establishing dynamic mathematical models of the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. The models of the electrolyzer subsystem and auxiliary subsystem are connected according to the system input-output relationship. The flow rate of the gas-liquid two-phase working fluid is used as the input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and auxiliary subsystem are used as the output. A simultaneous solution is obtained to obtain the alkaline water electrolysis hydrogen production system model. Steady-state simulation is performed using system design parameters. After verifying the consistency between the simulation results and the design parameters, a PID control module is built to determine the control strategy of the alkaline water electrolysis hydrogen production system simulation model. Therefore, this embodiment designs a complete process flow for an alkaline water electrolysis hydrogen production system, including an electrolyzer, gas-liquid separation, hydrogen purification, and cooling system. It determines the key design parameters under rated operation, variable load, and start-up / shutdown conditions. Then, by combining equipment characteristic curves and experimental data, it calibrates and verifies the parameters of core component models such as the electrolyzer and heat exchanger, establishes a system steady-state simulation benchmark, and further introduces control logic to achieve optimized construction of the dynamic simulation model.

[0054] Example 2 Based on the above embodiments, this embodiment uses 1000 This method is illustrated using the simulation modeling process of an alkaline water electrolysis hydrogen production system as an example. Specifically, it includes the following steps: (1) Analyze each subsystem of the alkaline water electrolysis hydrogen production system and establish a dynamic mathematical model for each subsystem; (2) Based on the dynamic mathematical models of each subsystem, an overall model of the alkaline water electrolysis hydrogen production system is established; (3) Input the system design parameters, perform steady-state simulation, and verify the consistency between the simulation results and the design parameters; (4) Based on the steady-state model, a PID control module was built to determine the control strategy in the process of hydrogen production by water electrolysis; (5) Perform dynamic simulation to analyze the changes in the characteristics of key indicators of the system at different stages.

[0055] The alkaline water electrolysis hydrogen production system comprises an electrolyzer system and an auxiliary system. The electrolyzer system includes a main electrode plate, flow channels, porous electrodes, and a diaphragm. The auxiliary system includes a gas-liquid separator, valves, pumps, heat exchangers, a reactor, a component distributor, and piping. During the reaction, various variables within the system change over time; therefore, dynamic mathematical models of each subsystem are necessary to analyze their working principles. A mechanistic modeling approach is used, considering components such as the main electrode, flow channels, porous electrodes, and diaphragm within the electrolyzer. Detailed models are provided for the mass transfer, energy transfer, momentum transfer, and electrochemical reaction mechanisms within the electrolyzer, with particular attention to the internal two-phase flow and electrochemical kinetics. The model accurately simulates the changes in internal physical parameters and external performance of the electrolyzer under various operating conditions. For specific component models and the contents of the PID control module, please refer to Example 1 above; they will not be elaborated upon here.

[0056] Figure 4 The simulation results of the effect of different alkaline solution flow rates on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 5 The simulation results of the impact of different alkaline flow rates on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 6 This document presents simulation results illustrating the effect of different alkali flow rates on the hydrogen concentration in the oxygen of a water electrolysis hydrogen production system, as provided in this embodiment. The embodiment uses an operating current of 6850 A, an alkali temperature of 65 °C, and an electrolyzer pressure of 16 bar to analyze the changes in system chamber voltage, DC energy consumption, and hydrogen concentration in the oxygen under different alkali flow rates. (Refer to...) Figures 4 to 6 As the alkaline solution flow rate increases, both the chamber voltage and DC power consumption show a gradual upward trend, but the rate of increase gradually slows down. When the alkaline solution flow rate increases from 30 m³ / h to 80 m³ / h, the chamber voltage increases by 0.033 V, and the DC power consumption increases by 0.08 kW·h / m³, representing an increase of 1.84%. A larger alkaline solution flow rate means enhanced cooling, thereby lowering the average temperature of the electrolyzer, and consequently increasing the electrolyzer's power consumption. Simultaneously, with the increase in alkaline solution flow rate, the hydrogen concentration in oxygen increases significantly. Specifically, the hydrogen concentration in oxygen increases from 0.37% to 0.63%, nearly doubling. In the electrolyzer system, hydrogen and oxygen dissolve in the alkaline solution. When the alkaline solution flows back from the gas-liquid separator on the hydrogen / oxygen side, it carries a certain amount of dissolved hydrogen and oxygen. After the returned alkaline solution merges with other incoming alkaline solutions, it is released again through the electrolyzer back into the gas-liquid separator. As the flow rate of the alkaline solution increases, the total amount of hydrogen and oxygen refluxed and released per unit time also increases, leading to a significant increase in the hydrogen concentration in the oxygen.

[0057] In this embodiment, the operating current is set to 6850A, the alkaline solution temperature to 65℃, and the alkaline solution flow rate to 60m³ / h. The changes in system chamber voltage, DC energy consumption, and hydrogen concentration in oxygen are analyzed under different pressure conditions of the electrolyzer. Figure 7 The simulation results of the effect of different pressures on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 8 The simulation results of the impact of different pressures on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 9 The simulation results show the effect of different pressures on the hydrogen concentration in the oxygen of the water electrolysis hydrogen production system provided in the embodiments of this application. (Refer to...) Figures 7 to 9 As the electrolyzer pressure increased, both the cell voltage and DC energy consumption showed a significant downward trend. When the operating pressure increased from 10 bar to 16 bar, the cell voltage decreased by 0.02 V, and the DC energy consumption decreased by 0.05 kW·h / m³, a decrease of 1.12%. This indicates that, within a certain range, increasing the electrolyzer pressure helps improve electrolysis efficiency and slightly reduce energy consumption. Simultaneously, with the increase in electrolyzer pressure, the hydrogen concentration in oxygen increased from 0.34% to 0.51%. This change can be attributed to the effect of operating pressure on gas solubility. When the system operating pressure increases, the solubility of hydrogen and oxygen in the alkali solution also increases, leading to more hydrogen and oxygen being carried by the alkali solution and released into the gas-liquid separator. With the increase in gas dissolution, the hydrogen concentration in oxygen also rises, thereby promoting the further release of these gases during the electrolysis process.

[0058] In this embodiment, the alkaline solution temperature is set to a constant 65°C, the alkaline solution flow rate is set to a constant 60 m³ / h, and the electrolytic cell pressure is set to 16 bar. The changes in system cell voltage, DC energy consumption, and hydrogen concentration in oxygen are analyzed under different operating current conditions. Figure 10 The simulation results of the effect of different currents on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 11 The simulation results of the impact of different currents on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 12 The simulation results show the effect of different currents on the hydrogen concentration in the oxygen of the water electrolysis hydrogen production system provided in the embodiments of this application. (Refer to...) Figures 10 to 12As the operating current increases, the cell voltage gradually rises, and the DC power consumption also increases, leading to a decrease in system efficiency. When the current gradually increases from 30% to 100%, the cell voltage increases by 0.23V, and the DC power consumption increases by 0.56 kW·h / m³, a relative increase of 12.70%. This trend shows an approximately linear growth relationship. This phenomenon can be attributed to the corresponding increase in activation polarization and ohmic polarization during the electrolysis process as the current density increases. At high current densities, the system needs to overcome greater electrochemical resistance, resulting in a significant increase in the required electrical energy consumption. Simultaneously, as the operating current increases, the hydrogen concentration in the oxygen decreases by 1.08%, and at current densities above 0.15 A / cm², the hydrogen concentration in the oxygen can be controlled below 1%.

[0059] This embodiment sets the operating current to a constant 6850A, the alkali solution flow rate to a constant 60m³ / h, and the electrolyzer pressure to 16bar. It analyzes the changes in system chamber voltage, DC energy consumption, and hydrogen concentration in oxygen under different alkali solution temperatures. Figure 13 The simulation results of the effect of different start-up temperatures on the cell voltage of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 14 The simulation results of the impact of different start-up temperatures on the DC energy consumption of the water electrolysis hydrogen production system provided in the embodiments of this application; Figure 15 Simulation results showing the effect of different start-up temperatures on the hydrogen concentration in the oxygen-to-hydrogen production system provided in this application's embodiments. (Refer to...) Figures 13 to 15 As the temperature of the alkaline solution increased, both the cell voltage and DC energy consumption of the electrolyzer showed a significant decreasing trend. When the alkaline solution temperature increased from 30℃ to 80℃, the cell voltage decreased by 0.14 V, and the DC energy consumption decreased by 0.33 kW·h / m³, a decrease of 7.05%. The main reason for this phenomenon is that the increase in temperature effectively promotes the water electrolysis reaction, thereby reducing the energy consumption required in the reaction process and reducing the energy barrier of the reaction. With the increase in alkaline solution temperature, the reaction rate increases, and the electrolysis efficiency is improved. As the alkaline solution temperature rises, the hydrogen concentration in oxygen decreases slightly, from 0.56% to 0.49%, but the decrease is relatively small. This is because the temperature increase leads to a decrease in the solubility of gases in the alkaline solution, thereby reducing the amount of gas released in the gas-liquid separator.

[0060] Example 3 Based on the above embodiments, this embodiment provides a simulation model establishment system for an alkaline water electrolysis hydrogen production system, used to implement the above-described method for establishing a simulation model for an alkaline water electrolysis hydrogen production system, including: The first step is to establish a dynamic mathematical model for the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. The second module is used to connect the models of the electrolyzer subsystem and the auxiliary subsystem according to the system input-output relationship, based on the electrolyzer subsystem and the auxiliary subsystem. The gas-liquid two-phase flow working fluid flow rate is used as input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and the auxiliary subsystem are used as output. The modules are solved simultaneously to obtain the alkaline water electrolysis hydrogen production system model. The simulation control module is used to perform steady-state simulation using system design parameters, and after verifying the consistency between the simulation results and the design parameters, to build a PID control module to determine the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system.

[0061] This application also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the method in any of the embodiments of this application. Specifically, a system or apparatus equipped with a storage medium may be provided, on which software program code implementing the functions of any of the above embodiments is stored, and the computer (or CPU (Central Processing Unit) or MPU (Microprocessor Unit) of the system or apparatus may read and execute the program code stored in the storage medium.

[0062] In particular, according to embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication component, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), it performs the functions defined in the system of this application.

[0063] It should be noted that the computer-readable storage medium shown in this invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination thereof. For example, a computer-readable storage medium can be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM) or flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. The transmitted data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable storage medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable storage medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF (Radio Frequency), etc., or any suitable combination thereof.

[0064] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0065] The units described in the embodiments of the present invention can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0066] It should be noted that although several modules or units of the device for performing actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of the present invention, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0067] In the several embodiments provided in this application, it should be understood that the disclosed systems, modules, and methods can be implemented in other ways. For example, the module embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, or indirect coupling or communication connection between modules or units, and may be electrical, mechanical, or other forms.

[0068] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit it. This application is not limited to the exact structures described above and illustrated in the accompanying drawings, and it should not be considered that the specific implementation of this application is limited to these descriptions. For those skilled in the art, various changes and modifications made without departing from the concept of this application should be considered to fall within the protection scope of this application.

Claims

1. A method for establishing a simulation model of an alkaline water electrolysis hydrogen production system, characterized in that, include: Dynamic mathematical models of the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system are established. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. Based on the electrolyzer subsystem and the auxiliary subsystem, the models of the electrolyzer subsystem and the auxiliary subsystem are connected according to the system input-output relationship. The flow rate of the gas-liquid two-phase working fluid is taken as the input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and the auxiliary subsystem are taken as the output. The models of the alkaline water electrolysis hydrogen production system are obtained by solving the system simultaneously. Steady-state simulation was performed using system design parameters. After verifying the consistency between the simulation results and the design parameters, a PID control module was built to determine the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system.

2. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 1, characterized in that, The dynamic mathematical model for establishing the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system includes: A model of the main plate is constructed based on the principles of energy conservation and charge conservation, and the relationship between the temperature dynamics, electronic current and potential distribution of the main plate is established. Considering the characteristics of gas-liquid two-phase flow, and based on the principles of conservation of mass, energy, and momentum, the dynamic relationships of flow, heat transfer, and mass transfer between the electrolyte and the generated gas are established, and the flow channel model is constructed. A porous electrode model was constructed, coupling electrochemical reactions, gas-liquid two-phase flow, charge transport and heat and mass transfer multi-physics field coupling mechanisms. The correlation between material transport, potential distribution, temperature change and reaction kinetics inside the electrode was established, and the dynamic reaction and multi-field coupled operation characteristics of the porous electrode were characterized. A membrane model is constructed based on energy conservation, charge conservation and transmembrane mass transfer mechanism. The dynamic relationship between temperature, ion conduction and component diffusion and permeation within the membrane is established to describe the membrane barrier and mass transfer characteristics. The lumped parameter method is used to model the gas-liquid separator, valves, pumps, heat exchangers, reactors, component distributors, and pipelines, resulting in the gas-liquid separator model, valve model, pump model, heat exchanger model, reactor model, component distributor model, and pipeline model.

3. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 2, characterized in that, The method of using lumped parameter modeling to model the gas-liquid separator, valves, pumps, heat exchangers, reactors, component distributors, and pipelines yields models for the gas-liquid separator, valves, pumps, heat exchangers, reactors, component distributors, and pipelines, including: Based on the principles of mass conservation, energy conservation, phase equilibrium, and hydrostatic pressure, gas-liquid two-phase separation, medium energy storage, and phase dynamic characterization are carried out to construct the gas-liquid separator model. Based on the principle of throttling pressure drop and first-order dynamic response of valve opening, the valve's throttling pressure drop, flow regulation, and dynamic opening and closing characteristics are characterized to construct the valve model; wherein, the pressure drop is the difference between the valve inlet and outlet pressures; The pump model is constructed, wherein the fluid pressurization, energy conversion and power consumption characteristics are characterized based on the principles of isentropic efficiency, energy transfer and mechanical loss. Based on the principles of mass conservation, energy conservation, and logarithmic mean temperature difference heat transfer, calculations are performed on the heat exchange and heat transfer of hot and cold fluids to construct the heat exchanger model. Based on the laws of mass conservation, energy conservation, and reaction transformation, the component transformation and reaction heat effects are characterized, and the reactor model is constructed. Based on the principle of mass and energy balance, multi-branch flow, component and energy distribution are processed to construct the component splitter model; Based on the fundamental principles of fluid mechanics, and the laws governing flow resistance, pressure drop, and flow state, fluid transport and pressure loss are calculated to obtain the pipeline model.

4. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 3, characterized in that, The auxiliary subsystem also includes a power supply model, which employs a feature-based modeling method and includes the AC / DC conversion process and the DC / DC transformation process.

5. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 1, characterized in that, The steady-state simulation using system design parameters includes: The test conditions are input into the alkaline water electrolysis hydrogen production system model. The parameters are estimated in the gPROMS software program using the initial experimental test data. The undetermined parameters in the model are adjusted by the least squares method to make the model simulation output best fit the initial experimental test data, thus completing the model calibration. The calibrated model is validated using independent data of variable load, the predicted and measured curves are quantitatively compared, and the randomness of error indicators and residuals is analyzed. When the model output matches the experimental test data within the preset error range, the consistency verification between the simulation results and the design parameters is passed.

6. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 5, characterized in that, Also includes: If the calibration result between the model output and the experimental test data exceeds the preset error range, the key mechanism model of the alkaline water electrolysis hydrogen production system model is corrected by adding correction terms and correction factors.

7. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 4, characterized in that, The PID control model is specifically as follows: ； ； ； ； ； ； In the formula, For operation variables; The variable value when there are no errors during the operation; It is a proportional term; It is an integral term; For the derivative term; This is the deviation value. For controller gain; Set values ​​for the controller; For process variables; For the Laplace operator; The derivative is the time constant. The rate of change of deviation; In the Laplace domain, the transfer function of the ideal PID control algorithm is given by the following equation: ； When assuming the proportional gain applies to scaled controller inputs and outputs, the controller inputs and outputs are scaled before being used in the PID control algorithm: ； ； in, It is the smallest process variable; It is the largest process variable; It is the smallest operand; It is the largest operating variable.

8. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 7, characterized in that, The control strategy of the simulation model of the alkaline water electrolysis hydrogen production system includes: Hydrogen-side gas-liquid separator level control: The hydrogen-oxygen level difference is controlled by adjusting the opening of the regulating valve on the hydrogen outlet side; Oxygen-side gas-liquid separator pressure control: The pressure of the oxygen-side gas-liquid separator is controlled by adjusting the opening of the regulating valve on the oxygen outlet side; Alkali solution temperature control: The alkali solution temperature is controlled by adjusting the valve opening of the cooling water branch. Water replenishment control: Monitor the liquid level of the hydrogen-side gas-liquid separator to perform step-by-step water replenishment; Hydrogen-side condensate-water separator level control: The liquid level fraction on the hydrogen side is controlled by adjusting the valve opening at the drain outlet of the gas-water separator; Oxygen-side condensate-water separator level control: The oxygen-side liquid level fraction is controlled by adjusting the valve opening at the drain outlet of the gas-water separator.

9. The method for establishing a simulation model of an alkaline water electrolysis hydrogen production system according to claim 8, characterized in that, The level control of the hydrogen-side gas-liquid separator, the pressure control of the oxygen-side gas-liquid separator, and the temperature control of the alkali solution all adopt PID control; the water replenishment control adopts upper and lower limit single-point control.

10. A simulation model establishment system for an alkaline water electrolysis hydrogen production system, used to implement the simulation model establishment method for an alkaline water electrolysis hydrogen production system according to any one of claims 1 to 9, characterized in that, include: The first step is to establish a dynamic mathematical model for the electrolyzer subsystem and auxiliary subsystem of the alkaline water electrolysis hydrogen production system. The electrolyzer subsystem includes a main electrode plate model, a flow channel model, a porous electrode model, and a diaphragm model. The auxiliary subsystem includes a gas-liquid separator model, a valve model, a pump model, a heat exchanger model, a reactor model, a component distributor model, and a pipeline model. The second module is used to connect the models of the electrolyzer subsystem and the auxiliary subsystem according to the system input-output relationship, based on the electrolyzer subsystem and the auxiliary subsystem. The gas-liquid two-phase flow working fluid flow rate is used as input, and the temperature and pressure of the working fluid at the outlet of the electrolyzer subsystem and the auxiliary subsystem are used as output. The modules are solved simultaneously to obtain the alkaline water electrolysis hydrogen production system model. The simulation control module is used to perform steady-state simulation using system design parameters, and after verifying the consistency between the simulation results and the design parameters, to build a PID control module to determine the control strategy of the simulation model of the alkaline water electrolysis hydrogen production system.

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