CN113122867B - Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system - Google Patents

Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system Download PDF

Info

Publication number
CN113122867B
CN113122867B CN202110415969.5A CN202110415969A CN113122867B CN 113122867 B CN113122867 B CN 113122867B CN 202110415969 A CN202110415969 A CN 202110415969A CN 113122867 B CN113122867 B CN 113122867B
Authority
CN
China
Prior art keywords
cell
temperature
hydrogen production
module
water
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202110415969.5A
Other languages
Chinese (zh)
Other versions
CN113122867A (en
Inventor
李洋洋
杨福源
欧阳明高
古俊杰
赵英朋
党健
江亚阳
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Tsinghua University
Original Assignee
Tsinghua University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tsinghua University filed Critical Tsinghua University
Priority to CN202110415969.5A priority Critical patent/CN113122867B/en
Publication of CN113122867A publication Critical patent/CN113122867A/en
Application granted granted Critical
Publication of CN113122867B publication Critical patent/CN113122867B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • C—CHEMISTRY; METALLURGY
    • C25—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES; APPARATUS THEREFOR
    • C25B—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES FOR THE PRODUCTION OF COMPOUNDS OR NON-METALS; APPARATUS THEREFOR
    • C25B1/00—Electrolytic production of inorganic compounds or non-metals
    • C25B1/01—Products
    • C25B1/02—Hydrogen or oxygen
    • C25B1/04—Hydrogen or oxygen by electrolysis of water
    • C—CHEMISTRY; METALLURGY
    • C25—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES; APPARATUS THEREFOR
    • C25B—ELECTROLYTIC OR ELECTROPHORETIC PROCESSES FOR THE PRODUCTION OF COMPOUNDS OR NON-METALS; APPARATUS THEREFOR
    • C25B15/00—Operating or servicing cells
    • C25B15/02—Process control or regulation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/30—Hydrogen technology
    • Y02E60/36—Hydrogen production from non-carbon containing sources, e.g. by water electrolysis

Landscapes

  • Chemical & Material Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Electrochemistry (AREA)
  • Materials Engineering (AREA)
  • Metallurgy (AREA)
  • Organic Chemistry (AREA)
  • Inorganic Chemistry (AREA)
  • Automation & Control Theory (AREA)
  • Electrolytic Production Of Non-Metals, Compounds, Apparatuses Therefor (AREA)

Abstract

The invention provides an optimization method and a hydrogen production system for an alkaline water electrolysis hydrogen production device transient process, wherein the optimization method for the alkaline water electrolysis hydrogen production device transient process comprises the following steps: and inputting the test parameters of the transient process of the hydrogen production equipment into the target digital twin model, and optimizing the transient process of the hydrogen production equipment to obtain optimized control parameters, wherein the optimized control parameters are used for guiding the input parameters in the hydrogen production process. By implementing the method, the starting process, particularly the normal-temperature starting process time can be shortened, and the energy consumption of equipment is reduced, so that the actual hydrogen yield is improved.

Description

Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system
Technical Field
The invention relates to the technical field of hydrogen production, in particular to an optimization method of an alkaline water electrolysis hydrogen production device in a transient process and a hydrogen production system.
Background
The hydrogen energy is used as secondary energy, has multiple advantages of various sources, zero emission at terminals, wide application and the like, and has important significance in the aspects of ensuring national energy safety, promoting energy industry upgrading and the like. With the technology becoming mature and the cost greatly reduced, the strategic opportunity of rapid development of hydrogen energy is being met. In the mature water electrolysis hydrogen production technology, the alkaline water electrolysis hydrogen production technology is relatively mature, the process is relatively simple, the cost is relatively low, but the bottleneck is that the working current density is relatively low (lower than 0.5A/cm2), the efficiency of an electrolytic cell (60-75%) is still to be improved, the load operation range is only 40% -110%, the multi-equipment coordination control strategy is complex and large in size under a large-scale state, the time required from the normal temperature to the temperature corresponding to the rated power (example 95 ℃) is long, and the hydrogen production quantity is 500Nm3The time required for starting the alkali liquor equipment to 95 ℃ at normal temperature is close to 3-4 hours, so that a great deal of electric energy and hydrogen are consumed.
However, in the related art, in order to reduce the loss, a model of the mechanism of hydrogen production by alkaline water is generally constructed, and then a parameter sensitivity analysis is performed on the model, without considering the problem of large amount of loss of electric energy and hydrogen of the hydrogen production equipment in the transient change process due to the influence of the process involving transient change, such as long-time shutdown and startup, short-time shutdown and startup, or change from one steady state to another steady state, on the hydrogen production process, and therefore, there is a need to provide an optimization method of the transient process of the hydrogen production equipment by alkaline water electrolysis to solve the problem.
Disclosure of Invention
In view of this, the embodiment of the invention provides an optimization method for the transient process of an alkaline water electrolysis hydrogen production device and a hydrogen production system, so as to solve the defect that the hydrogen production device consumes a large amount of electric energy and hydrogen in the transient change process in the prior art.
According to a first aspect, the embodiment of the invention provides a method for optimizing transient process of an alkaline water electrolysis hydrogen production device, which comprises the following steps: and inputting the test parameters of the transient process of the hydrogen production equipment into the target digital twin model, and optimizing the transient process of the hydrogen production equipment to obtain optimized control parameters, wherein the optimized control parameters are used for guiding the input parameters in the hydrogen production process.
Optionally, the constructing of the target digital twin model includes: inputting test parameters in the starting process of the hydrogen production equipment into a pre-established digital twinning model to obtain a digital twinning result; and calibrating the pre-built digital twin model according to the actual measurement result of the hydrogen production equipment and the digital twin result to obtain a target digital twin model.
Optionally, the calibrating the pre-built digital twin model according to the actual measurement result of the hydrogen production equipment and the digital twin result includes: and when the relative deviation between the voltage variation condition along with the current amount and/or the temperature variation condition along with time in the actual measurement result and the voltage variation condition along with the current amount and/or the temperature variation condition along with time in the digital twin result is smaller than a preset threshold, completing the calibration of the pre-established digital twin model.
According to a second aspect, embodiments of the present invention provide a hydrogen production digital twinning system, comprising: the electrochemical module is used for simulating a hydrogen production process according to a hydrogen production mechanism; the temperature module is connected with the electrochemical module and the mass transfer module and used for simulating the solution temperature in the hydrogen production process and sending the solution temperature to the electrochemical module and the mass transfer module; the electrolyte concentration module is connected with the electrochemical module and used for simulating the electrolyte concentration change in the hydrogen production process and sending the simulated electrolyte concentration to the electrochemical module; and the mass transfer module is connected with the electrochemical module and used for calculating the hydrogen and oxygen partial pressure and the water vapor partial pressure according to the solution temperature and sending the hydrogen and oxygen partial pressure and the water vapor partial pressure to the electrochemical module.
Optionally, the electrochemical module comprises: the reversible voltage determining module is used for determining reversible voltage according to the concentration of the electrolyte, the temperature of the solution and the partial pressure of hydrogen and oxygen; the activation polarization voltage determination module is used for determining activation polarization voltage according to the solution temperature and the current; the ohmic polarization voltage determining module is used for determining ohmic polarization voltage according to internal resistance in the electrolysis process; and the concentration polarization voltage determination module is used for determining the concentration polarization voltage according to the solution temperature and the electrolyte concentration.
Optionally, the temperature module comprises: a solution temperature determination module for determining the cell temperature according to the following formula:
Figure BDA0003025285170000031
wherein, TcellIs the temperature of the cell, Cth_cellIs a constant of temperature change, sigma Q is the total heat of the electrolytic cell to overcome the loss, and sigma Q is Qgene-Qloss-Qout±Qcool；
Figure BDA0003025285170000032
Is heat generated by the electrolytic cell, Qgene＝i×A×(Ecell-Ethe_cell) (ii) a Ecell monomer electrolytic Voltage, Eth_cellIs the thermal neutral voltage, A is the active area, i is the current;
Figure BDA0003025285170000033
in order to exchange heat with the environment,
Figure BDA0003025285170000034
Tcell-1the temperature of the electrolytic bath obtained by the last calculation is calculated; t isenviIs ambient temperature, Rth_cellIs the temperature change constant of thermal interaction with the environment;
Figure BDA0003025285170000035
the heat quantity for the alkali liquor and the water to be carried out,
Figure BDA0003025285170000036
the flow rate of the water and the alkali liquor is adopted,
Figure BDA0003025285170000037
is the constant pressure specific heat of water and alkali liquor;
Figure BDA0003025285170000038
the pure water is used for bringing in heat,
Figure BDA0003025285170000039
is the constant pressure specific heat of pure water, ninIs the water inlet flow.
Optionally, the mass transfer module comprises: a pressure calculation module for determining the oxygen partial pressure according to the following formula:
Figure BDA00030252851700000310
wherein the content of the first and second substances,
Figure BDA00030252851700000311
is the partial pressure of the oxygen at the anode,
Figure BDA00030252851700000312
is the partial pressure of the water vapor,
Figure BDA00030252851700000313
is the molar mass fraction of water in the anode,
Figure BDA0003025285170000041
εanis the porosity of the anode, τanFor the tortuosity of the anode, R is the ideal gas constant (8.314), T is the temperature at which the reaction proceeds, i is the current density, lan-cLength of anode electrode to flow field, panIs the anode pressure, F is the Faraday constant,
Figure BDA0003025285170000042
is the anode effective molar diffusion coefficient.
According to a third aspect, the embodiment of the invention provides an apparatus for optimizing transient process of an alkaline water electrolysis hydrogen production device, which comprises: and the optimization control parameter determining module is used for inputting the test parameters of the transient process of the hydrogen production equipment into the target digital twin model, optimizing the transient process of the hydrogen production equipment to obtain the optimization control parameters, and the optimization control parameters are used for guiding the input parameters in the hydrogen production process.
According to a fourth aspect, embodiments of the present invention provide an electronic device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for optimizing a transient process of an alkaline water electrolysis hydrogen production plant according to the first aspect or any embodiment of the first aspect.
According to a fifth aspect, embodiments of the present invention provide a storage medium having stored thereon computer instructions which, when executed by a processor, implement the steps of the method for optimizing a transient process of an alkaline water electrolysis hydrogen production plant according to the first aspect or any of the embodiments of the first aspect.
The technical scheme of the invention has the following advantages:
according to the method/device for optimizing the transient process of the alkaline water electrolysis hydrogen production equipment, provided by the embodiment of the invention, the starting process of the hydrogen production equipment is optimized through the target digital twin model to obtain the optimized control parameters, and the control parameters in the actual starting process of the hydrogen production equipment are adjusted according to the optimized control parameters, so that the effects of shortening the starting process time in the starting process, reducing the energy consumption of the equipment and improving the actual hydrogen production are achieved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a diagram of a specific example of the optimization method of the transient process of the alkaline water electrolysis hydrogen production equipment in the embodiment of the invention;
FIG. 2 is a diagram of one embodiment of a digital twin system for producing hydrogen in an embodiment of the present invention;
FIG. 3 is a diagram of an embodiment of the present invention for optimizing the transient process of an alkaline water electrolysis hydrogen production plant;
FIG. 4 is a diagram of a specific example of the optimization method of the transient process of the alkaline water electrolysis hydrogen production equipment in the embodiment of the invention;
FIG. 5 is a diagram of an embodiment of the present invention for optimizing the transient process of an alkaline water electrolysis hydrogen production plant;
FIG. 6 is a diagram of an embodiment of the present invention for optimizing the transient process of an alkaline water electrolysis hydrogen production plant;
FIG. 7 is a diagram of an embodiment of the present invention for optimizing the transient process of an alkaline water electrolysis hydrogen production plant;
FIG. 8 is a diagram of an embodiment of the present invention for optimizing the transient process of an alkaline water electrolysis hydrogen production plant;
FIG. 9 is a diagram of an embodiment of the present invention for optimizing the transient process of an alkaline water electrolysis hydrogen production plant;
FIG. 10 is a diagram of one embodiment of a digital twin system for producing hydrogen in an embodiment of the present invention;
fig. 11 is a schematic block diagram of a specific example of an electronic device in the embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two elements may be directly connected or indirectly connected through an intermediate medium, or may be communicated with each other inside the two elements, or may be wirelessly connected or wired connected. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
In addition, the technical features involved in the different embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
The embodiment provides an optimization method of a transient process of an alkaline water electrolysis hydrogen production device, as shown in fig. 1, comprising the following steps:
s101, inputting test parameters of the transient process of the hydrogen production equipment into a target digital twin model;
for example, transient processes may include long term shutdown start-up processes, short term shutdown start-up processes, or processes that change from one steady state to another. The test parameters of the transient process of the hydrogen production equipment characterize the initial parameters when the hydrogen production process transmits changes. The transient process is not limited in this embodiment, and can be determined by those skilled in the art as needed.
The present embodiment is described by taking a long shutdown start-up process as an example. In the long-time shutdown and startup process, the test parameters of the startup process of the hydrogen production equipment represent initial parameters during hydrogen production, and may include initial temperature, electrolyte concentration, system pressure and the like during startup of the hydrogen production equipment. The target digital twinning model is a model developed based on software, is constructed according to key component structure parameters and performance parameters of actual hydrogen production equipment, is virtual digital repeated engraving of the actual hydrogen production equipment, can basically accord with actual measurement results of the hydrogen production equipment by calculating a final twinning result through the target digital twinning model, and is determined according to different actual conditions of the hydrogen production equipment by a specific construction mode of the target digital twinning model and the structure parameters and the performance parameters of the target digital twinning model.
The framework of the target digital twin model in this embodiment can be as shown in fig. 2, and includes an electrochemical module 201, a temperature module 202, an electrolyte concentration module 203, and a mass transfer module 204. The electrochemical module 201 simulates a hydrogen production process according to various input parameters (including initial temperature, structural parameters of hydrogen production equipment, solution temperature, electrolyte concentration, current of controlled current, hydrogen and oxygen partial pressure and water vapor partial pressure) and a hydrogen production mechanism, and outputs efficiency, a hydrogen production rate, a faraday efficiency, an output voltage, an oxygen concentration in hydrogen and a hydrogen concentration in oxygen; the temperature module 202 is respectively connected with the electrochemical module 201 and the mass transfer module 204, and is used for simulating the solution temperature at the next moment in the hydrogen production process according to the inlet enthalpy of the electrolyte, the control current, the solution temperature at the previous moment and the like, and sending the solution temperature to the electrochemical module 201 and the mass transfer module 204; the electrolyte concentration module 203 is connected with the electrochemical module 201 and used for simulating the electrolyte concentration change in the hydrogen production process according to the hydrogen and oxygen level, the electrolyte circulation period, the pump rotating speed and flow and the deionized water flow and sending the simulated electrolyte concentration to the electrochemical module 201; and the mass transfer module 204 is connected with the electrochemical module 201 and is used for calculating the hydrogen and oxygen partial pressure and the water vapor partial pressure according to the solution temperature and the structural parameters of the hydrogen production equipment and sending the hydrogen and oxygen partial pressure and the water vapor partial pressure to the electrochemical module 201.
S102, optimizing the transient process of the hydrogen production equipment to obtain optimized control parameters, wherein the optimized control parameters are used for guiding input parameters in the hydrogen production process.
Illustratively, the starting process of the hydrogen production equipment is optimized, and the optimized control parameters can be obtained by inputting the test parameters into a target digital twin model, and the target digital twin model optimizes the starting process of the hydrogen production equipment by adopting a dynamic programming algorithm based on the temperature and the rated voltage, and the obtained optimized control parameters can be the optimized control current and the optimized system pressure required by the hydrogen production equipment at different moments.
As shown in fig. 3, the optimized control parameter is current, the curve corresponding to the dot is the change curve of the optimized current parameter with time, and the curve corresponding to the square point is the change curve of the current parameter actually measured in the testing process with time; as shown in fig. 4, the optimized control parameter is the system pressure, the curve corresponding to the dot is the change curve of the optimized system pressure with time, and the curve corresponding to the square is the change curve of the system pressure actually measured with time during the test.
After obtaining the optimized control parameters, engineers can adjust the input parameters of the hydrogen production equipment according to the optimized control parameters, and the specific way can be to analyze the optimized control parameters based on two aspects of safety (the solubility of hydrogen in oxygen is not more than 2%) and rated voltage limit (provided by manufacturers, the rated voltage of 500Nm3/h alkali liquor equipment is 440V). And adjusting the parameters in the actual hydrogen production process according to the analysis result and the optimized control parameters, namely adjusting the parameters in the actual hydrogen production process under the condition of ensuring safety.
In the method for optimizing the transient process of the alkaline water electrolysis hydrogen production equipment provided by the embodiment, as shown in fig. 5, the curve corresponding to the circular dots is a curve of the temperature changing with time when hydrogen production is performed according to the optimized control parameters, and the curve corresponding to the square dots is a curve of the temperature changing with time when hydrogen production is not performed according to the optimized control parameters, so that the total time of the hydrogen production equipment in the starting process not according to the optimized control parameters is 41 minutes longer than the starting process optimized by the model. As shown in fig. 6, the curve corresponding to the circular dots is a curve of the system voltage changing with time when hydrogen production is performed according to the optimized control parameters, and the curve corresponding to the square dots is a curve of the system voltage changing with time when hydrogen production is not performed according to the optimized control parameters. Therefore, the implementation method can shorten the starting process time, particularly the normal-temperature starting process time, reduce the energy consumption of equipment and further improve the actual hydrogen production.
As an optional implementation manner of this embodiment, the constructing of the target digital twin model includes:
firstly, test parameters in the starting process of the hydrogen production equipment are input into a pre-established digital twinning model to obtain a digital twinning result.
Illustratively, the test parameters characterize initial parameters during startup of the hydrogen plant when the digital twin model is trained, and may include initial temperature at startup of the hydrogen plant, electrolyte concentration, system pressure, and so forth. The present embodiment does not limit the types of the test parameters, and those skilled in the art can determine the types as needed. The digital twin result may be voltage versus current magnitude in a steady state or temperature/voltage versus time in a transient state.
And secondly, calibrating the pre-built digital twin model according to the actual measurement result and the digital twin result of the hydrogen production equipment to obtain the target digital twin model.
Illustratively, the actual measurements of the hydrogen plant are those obtained by various sensors in the hydrogen plant with the same inputs as the digital twin model. The actual measurement may be voltage versus current magnitude in steady state or temperature/voltage versus time in transient state. According to the actual measurement result and the digital twinning result of the hydrogen production equipment, the pre-built digital twinning model is calibrated, and the internal parameters of the digital twinning model can be continuously adjusted to obtain the target digital twinning model until the relative deviation between the actual measurement result and the digital twinning result is within a preset range, wherein the preset range can be 5%.
As shown in fig. 7, the curve corresponding to the dots is the curve of the voltage varying with the amount of current in the calibrated digital twin result; the curve corresponding to the square point is a curve of voltage changing with the current amount in the actual measurement result under the condition of the same input. As shown in fig. 8, the curve corresponding to the dots is the curve of the temperature change with time in the calibrated digital twin result; the curve corresponding to the square point is a curve of the temperature in the actual measurement result changing with time under the condition of the same input. As shown in fig. 9, the curve corresponding to the dots is the curve of the voltage variation with time in the calibrated digital twin result; the curve corresponding to the square point is a curve of voltage variation with time in the actual measurement result under the condition of the same input. And when the digital twin result is basically identical with the actually measured result, taking the current digital twin model as the target digital twin model.
The present embodiment provides a hydrogen production digital twin system, as shown in fig. 2, including:
the electrochemical module 201 is used for simulating a hydrogen production process according to a hydrogen production mechanism;
the temperature module 202 is connected with the electrochemical module and the mass transfer module, and is used for simulating the solution temperature in the hydrogen production process and sending the solution temperature to the electrochemical module and the mass transfer module;
the electrolyte concentration module 203 is connected with the electrochemical module and used for simulating the change of the electrolyte concentration in the hydrogen production process and sending the simulated electrolyte concentration to the electrochemical module;
and the mass transfer module 204 is connected with the electrochemical module and is used for calculating the hydrogen and oxygen partial pressure and the water vapor partial pressure according to the solution temperature and sending the hydrogen and oxygen partial pressure and the water vapor partial pressure to the electrochemical module.
According to the hydrogen production digital twin system provided by the embodiment, the hydrogen production equipment, the hydrogen production principle and the hydrogen production process are digitally re-engraved, so that the accuracy of a hydrogen production system model is improved, and the starting process of the hydrogen production equipment can be optimized through the hydrogen production digital twin system, so that the effects of shortening the starting process time of the starting process, reducing the energy consumption of the equipment and improving the actual hydrogen production are achieved. Of course, other simulation work can also be carried out based on the digital twin system, such as: and (3) disclosing influence mechanisms among control, performance and operation parameters, parameter sensitivity analysis, concept design and the like.
As an alternative implementation manner of this embodiment, the electrochemical module 201, as shown in fig. 10, includes:
the reversible voltage determining module is used for determining reversible voltage according to the concentration of the electrolyte, the temperature of the solution and the partial pressure of hydrogen and oxygen;
the activation polarization voltage determination module is used for determining activation polarization voltage according to the solution temperature and the current;
the ohmic polarization voltage determining module is used for determining ohmic polarization voltage according to internal resistance in the electrolysis process;
and the concentration polarization voltage determination module is used for determining the concentration polarization voltage according to the solution temperature and the electrolyte concentration.
Illustratively, in the electrolysis process, the electrolysis voltage for producing hydrogen from alkali liquor at a given current density consists of four parts, namely reversible voltage, activation polarization voltage, ohmic polarization voltage and concentration polarization voltage.
Ecell＝Erev+ηact+ηohn+ηcon；
Wherein E iscellDenotes the cell electrolysis voltage, ErevRepresenting reversible voltage, ηactRepresenting the activation polarization voltage, ηohmRepresenting ohmic polarization voltage, ηconRepresenting the concentration polarization voltage.
Therefore, a reversible voltage determination module is included in the electrochemical module 201 for determining a reversible voltage according to the electrolyte concentration, the solution temperature, and the hydrogen and oxygen partial pressures.
Reversible voltage refers to the minimum voltage required for an electrolytic reaction to occur at a given temperature and pressure. In particular, under standard conditions (25 ℃, 1 atmosphere), the reversible voltage is 1.229V. It is related to the gibbs free energy of the reaction, which can be derived from the thermodynamic relationship as follows.
ΔG＝ΔH-TΔS；
Figure BDA0003025285170000111
Wherein Δ G is Gibbs free energy change of reaction, Δ H is enthalpy change of reaction, Δ S is entropy change of reaction, T is temperature at which reaction proceeds, ErevUnder the standard conditions of reactants and products, reversible voltage at a given temperature is given, F is a Faraday constant, and n is the number of electrons transferred by the reaction. The enthalpy and entropy changes of the reaction are both functions of temperature, and therefore the reversible voltage is also a function of temperature.
From the nernst equation, the relationship between the reversible voltage and the reactant product concentration at a certain temperature can be obtained.
Figure BDA0003025285170000121
Wherein E isrev(T) isUnder the standard condition of reactants and products, given reversible voltage at reaction temperature, R is an ideal gas constant (8.314),
Figure BDA0003025285170000122
is the partial pressure of the hydrogen gas,
Figure BDA0003025285170000123
is the partial pressure of oxygen, P0The pressure was set at normal atmospheric pressure, 101.325kPa,
Figure BDA0003025285170000124
is the activity of water.
The above calculation method needs to calculate the entropy change of the reaction at a given temperature, which is not easily obtained in reality, and therefore, the relationship between the reversible voltage and the temperature and pressure can also be obtained using the following empirical formula.
Figure BDA0003025285170000125
Figure BDA0003025285170000126
Wherein, aw(KOH)Activity of water in KOH solution, mKOHThe concentration of KOH solution (mol/kg).
And the activation polarization voltage determination module is used for determining the activation polarization voltage according to the solution temperature and the current.
Transition state theory suggests that the chemical reaction needs to be achieved by an activated complex, and therefore, to generate a certain current density, the voltage needs to be higher than the reversible voltage. This portion above the reversible voltage is called the activation overpotential. The magnitude of the activation overpotential can be described by the following equation.
Figure BDA0003025285170000127
Wherein R is an ideal gasNumber (8.314), T is the temperature at which the reaction proceeds, α is the transmission coefficient, F is the Faraday constant, i is the current density, i is0To exchange current density.
And the ohmic polarization voltage determining module is used for determining ohmic polarization voltage according to the internal resistance in the electrolysis process.
In an actual electrolysis process, internal resistance exists in the electrodes, electrolyte and separator. The magnitude of ohmic polarization is linear with the magnitude of the current.
Rohm＝Re+Re1+Rs
ηohm＝(Re+Rel+Rs)Icell
Wherein eta isohmOhmic polarization voltage, Re is electrode resistance, RelIs an electrolyte resistance, RsIs a diaphragm resistance, IcellIs the single-sheet current of the electrolytic cell.
The internal resistance of the anode can be expressed by the following equation:
Figure BDA0003025285170000131
wherein R ise，anIs an anode resistance, AeThe area of the anode electrode is the area of the anode electrode,
Figure BDA0003025285170000132
is the anode effective resistivity, deltaanIs the anode electrode thickness.
The anode effective resistivity and electrode porosity have the following relationship:
Figure BDA0003025285170000133
wherein the content of the first and second substances,
Figure BDA0003025285170000134
is the resistivity, ε, of the anode material in the standard stateanPorosity of the anode electrode.
Considering that the electrode resistance is temperature dependent and the resistivity increases with increasing temperature.
Figure BDA0003025285170000141
Wherein, κanThe coefficient of resistivity of the anode electrode, T, as a function of temperaturerefIs the reference temperature.
Similarly, an expression for the cathode resistance, electrode resistance R, can be obtainedeThe expression of (a) is as follows:
Figure BDA0003025285170000142
wherein, κcatIs the coefficient of the resistivity of the cathode electrode changing with temperature,
Figure BDA0003025285170000143
is the resistivity of the cathode material in the standard state.
The effect of bubbles needs to be taken into account for the resistance generated by the electrolyte. On the anode side, the resistance generated by electrolysis can be expressed by the following equation.
Figure BDA0003025285170000144
Wherein the content of the first and second substances,
Figure BDA0003025285170000145
is an electrolyte resistance of the anode cell,
Figure BDA0003025285170000146
the electrolyte resistance of the anode without bubble area,
Figure BDA0003025285170000147
is the electrolyte resistance of the anode bubble region, rhoelIs the electrolyte resistivity,. lan-sDistance of anode electrode to separator, betaanIs the width of the anode bubble region，
Figure BDA0003025285170000148
Is the electrolyte resistivity in the bubble region.
The electrolyte resistivity in the bubble region is related to the electrolyte resistivity in the bubble-free region, where the bubble rate in the bubble region is equal to the bubble coverage on the electrode.
Figure BDA0003025285170000149
Wherein the content of the first and second substances,
Figure BDA00030252851700001410
is the electrolyte resistivity, rho, of the bubble regionelThe electrolyte resistivity is the bubble-free zone of the electrolyte,
Figure BDA00030252851700001411
is the bubble volume fraction in the anode region.
Consider that there is a relationship between electrolyte resistivity and temperature as follows:
Figure BDA0003025285170000151
where ρ isel，refIs the reference resistivity, κ, of the electrolyte at the reference temperatureelIs the temperature coefficient of the electrolyte resistivity.
Similarly, an expression of the cathode side cell electrolyte resistance can be obtained, and therefore the expression of the electrolyte resistance is as follows:
Figure BDA0003025285170000152
wherein, betaanLength of electrolyte in anode bubble region, betacatIs the length of the electrolyte in the cathode bubble region,
Figure BDA0003025285170000153
is the volume fraction of the bubbles in the anode bubble area,
Figure BDA0003025285170000154
is the volume fraction of bubbles in the cathode bubble region,/an-sDistance of anode electrode to separator, Icat-sThe distance from the cathode electrode to the separator.
For a separator, its electrical resistance is related to porosity, wetting coefficient and tortuosity.
Figure BDA0003025285170000155
Wherein, tausIs the tortuosity of the diaphragm, deltasIs the thickness of the diaphragm, omegasIs the degree of membrane wettability, εsIs the porosity of the membrane, AsIs the area of the membrane.
And the concentration polarization voltage determination module is used for determining the concentration polarization voltage according to the solution temperature and the electrolyte concentration.
Concentration polarization is produced due to the differences in the concentrations and bulk concentrations of the reactants and products at the reaction interface, and the expression for concentration polarization can be given by:
Figure BDA0003025285170000161
wherein the content of the first and second substances,
Figure BDA0003025285170000162
is the oxygen concentration on the surface of the anode under the standard state (the outlet pressure is the standard atmospheric pressure, the temperature is 25 ℃),
Figure BDA0003025285170000163
is the concentration of oxygen on the surface of the anode electrode,
Figure BDA0003025285170000164
is the oxygen concentration at the cathode surface in the standard state,
Figure BDA0003025285170000165
is the concentration of hydrogen on the surface of the cathode electrode.
Figure BDA0003025285170000166
Figure BDA0003025285170000167
Wherein the content of the first and second substances,
Figure BDA0003025285170000168
is the concentration of oxygen on the surface of the anode,
Figure BDA0003025285170000169
is the concentration of hydrogen gas, P, on the cathode surfaceanThe anode pressure is shown as the pressure at the anode,
Figure BDA00030252851700001610
for anodic oxygen mole fraction, R represents the ideal gas constant, T represents the temperature at which the reaction proceeds, and δanIs the thickness of the anode electrode, and is,
Figure BDA00030252851700001611
is the molar gas production rate of the oxygen,
Figure BDA00030252851700001612
effective molar diffusion coefficient, P, from the electrode to the bulk of the electrolyte for the anodecatIs the pressure of the cathode, and is,
Figure BDA00030252851700001613
is the cathode hydrogen molar mass fraction, deltacatIs the thickness of the cathode electrode and is,
Figure BDA00030252851700001614
is the molar gas production rate of the hydrogen gas,
Figure BDA00030252851700001615
is the effective molar diffusion coefficient of the cathode from the electrode to the bulk of the electrolyte.
As an alternative implementation of this embodiment, the temperature module 202 simulates the solution temperature during hydrogen production including:
Figure BDA00030252851700001616
wherein, TcellIs the temperature of the cell, Cth-cellIs a constant of temperature change, sigma Q is the total heat of the electrolytic cell to overcome the loss, and sigma Q is Qgene-Qloss-Qout±Qcool；
Figure BDA0003025285170000171
Is heat generated by the electrolytic cell, Qgene＝i×A×(Ecell-Ethe_cell) (ii) a Ecell monomer electrolytic Voltage, Eth_cellIs the thermal neutral voltage, A is the active area, i is the current;
Figure BDA0003025285170000172
in order to exchange heat with the environment,
Figure BDA0003025285170000173
Tcell-1the temperature of the electrolytic bath obtained by the last calculation is calculated; t isenviIs ambient temperature, Rth_cellIs the temperature change constant of thermal interaction with the environment;
Figure BDA0003025285170000174
the heat quantity for the alkali liquor and the water to be carried out,
Figure BDA0003025285170000175
the flow rate of the water and the alkali liquor is adopted,
Figure BDA0003025285170000176
is the constant pressure specific heat of water and alkali liquor;
Figure BDA0003025285170000177
the pure water is used for bringing in heat,
Figure BDA0003025285170000178
is the constant pressure specific heat of pure water, ninIs the water inlet flow.
The electrolyte concentration module 203 is used for simulating the change of the electrolyte concentration in the hydrogen production process, and the process comprises the following steps:
Figure BDA0003025285170000179
wherein m isKOHConcentration of KOH solution, mKOH-1For the last calculated concentration of KOH solution,
Figure BDA00030252851700001710
in order to realize the flow rate of the inlet water,
Figure BDA00030252851700001711
is H2Density of O.
As an optional implementation manner of this embodiment, the mass transfer module 204 includes: for calculating the partial pressure of oxygen at the anode electrode and the partial pressure of hydrogen at the cathode electrode.
The partial pressure of the anode oxygen may be represented by the following formula:
Figure BDA00030252851700001712
wherein the content of the first and second substances,
Figure BDA00030252851700001713
is the partial pressure of the oxygen at the anode,
Figure BDA00030252851700001714
is the partial pressure of the water vapor,
Figure BDA00030252851700001715
is the molar mass fraction of water in the anode.
According to the one-dimensional Stefan-Maxwell formula, the change of the anode water vapor mole fraction in the direction perpendicular to the flow channel can be expressed as:
Figure BDA0003025285170000181
wherein epsilonanPorosity of the anode electrode, /)an-cLength from anode electrode to flow field, PanIs the anode pressure.
Integrating the above equation along the direction perpendicular to the flow channel can yield:
Figure BDA0003025285170000182
the mole fraction of anodic oxygen can be calculated using the following formula:
Figure BDA0003025285170000183
the mole fraction of cathodic hydrogen can be calculated in the same way.
The effective molar diffusion coefficient can be obtained by the following formula:
Figure BDA0003025285170000184
Figure BDA0003025285170000185
wherein, tauanIs the tortuosity of the anode, epsilonanIs the porosity of the anode, τcatIs the tortuosity of the cathode,. epsiloncatIn order to be a porosity factor, the pore size of the porous material,
Figure BDA0003025285170000186
is a binary molar diffusion coefficient of a hydrogen-water system,
Figure BDA0003025285170000187
is a binary molar diffusion coefficient of an oxygen-water system,
Figure BDA0003025285170000188
is the effective Knudsen diffusion coefficient.
The binary molecular molar diffusion coefficient can be calculated by the following formula:
Figure BDA0003025285170000191
Figure BDA0003025285170000192
wherein the content of the first and second substances,
Figure BDA0003025285170000193
is the molar mass of the oxygen gas,
Figure BDA0003025285170000194
is the molar mass of the hydrogen gas,
Figure BDA0003025285170000195
is the average intermolecular distance of hydrogen and water in a hydrogen-water binary system,
Figure BDA0003025285170000196
is the average intermolecular distance between oxygen and water in an oxygen-water binary system, PanPressure at the anode, PcatPressure of the cathode, gammaDIs a dimensionless number.
The dimensionless number can be calculated by the following formula:
Figure BDA0003025285170000197
wherein, for oxygen-water systems, hydrogen-water systems, τ can be expressed as:
Figure BDA0003025285170000198
Figure BDA0003025285170000199
wherein the content of the first and second substances,
Figure BDA00030252851700001910
is Lennard-Jones energy, and for oxygen, hydrogen, water is 106.7, 59.7, 809.1K, respectively.
Wherein the effective Knudsen diffusion coefficient can be calculated using the following equation:
Figure BDA00030252851700001911
wherein the content of the first and second substances,
Figure BDA0003025285170000201
is the molar mass of water and r is the average pore diameter of the electrode.
The embodiment provides an optimizing device for the transient process of an alkaline water electrolysis hydrogen production device, which comprises:
and the optimization control parameter determining module is used for inputting the test parameters of the transient process of the hydrogen production equipment into the target digital twin model, optimizing the transient process of the hydrogen production equipment to obtain the optimization control parameters, and the optimization control parameters are used for guiding the input parameters in the hydrogen production process. For details, refer to the corresponding parts of the above embodiments, and are not described herein again.
Optionally, the optimization control parameter determination module includes:
the digital twinning result determining module is used for inputting the test parameters in the starting process of the hydrogen production equipment into a pre-established digital twinning model to obtain a digital twinning result; for details, refer to the corresponding parts of the above embodiments, and are not described herein again.
And the calibration module is used for calibrating the pre-built digital twin model according to the actual measurement result of the hydrogen production equipment and the digital twin result to obtain a target digital twin model. For details, refer to the corresponding parts of the above embodiments, and are not described herein again.
Optionally, the calibration module includes:
and the calibration submodule is used for completing calibration of the pre-established digital twin model when the relative deviation between the voltage variation condition along with the current amount and/or the temperature variation condition along with time in the actual measurement result and the voltage variation condition along with the current amount and/or the temperature variation condition along with time in the digital twin result is smaller than a preset threshold value. For details, refer to the corresponding parts of the above embodiments, and are not described herein again.
The embodiment of the present application also provides an electronic device, as shown in fig. 10, a processor 310 and a memory 320, where the processor 310 and the memory 320 may be connected by a bus or other means.
Processor 310 may be a Central Processing Unit (CPU). The Processor 310 may also be other general purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, or any combination thereof.
The memory 320 is a non-transitory computer readable storage medium, and can be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the method for optimizing the transient process of the alkaline water electrolysis hydrogen production plant according to the embodiment of the present invention. The processor executes various functional applications and data processing of the processor by executing non-transitory software programs, instructions, and modules stored in the memory.
The memory 320 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created by the processor, and the like. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 320 may optionally include memory located remotely from the processor, which may be connected to the processor via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The one or more modules are stored in the memory 320 and, when executed by the processor 310, perform the method for optimizing the transient process of the alkaline water electrolysis hydrogen production plant of the above-described embodiments.
The specific details of the electronic device may be understood by referring to the relevant description and effects corresponding to the embodiments, which are not described herein again.
The present embodiments also provide a computer storage medium having stored thereon computer-executable instructions that can perform the method for optimizing transient processes in an alkaline water electrolysis hydrogen plant of any of the above-described method embodiments. The storage medium may be a magnetic Disk, an optical Disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a Flash Memory (Flash Memory), a Hard Disk (Hard Disk Drive, abbreviated as HDD), a Solid State Drive (SSD), or the like; the storage medium may also comprise a combination of memories of the kind described above.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications therefrom are within the scope of the invention.

Claims (9)

1. The method for optimizing the transient process of the alkaline water electrolysis hydrogen production equipment is characterized by comprising the following steps of:
inputting test parameters of the transient process of the hydrogen production equipment into a target digital twin model;
optimizing the transient process of the hydrogen production equipment to obtain optimized control parameters, wherein the optimized control parameters are used for guiding input parameters in the hydrogen production process;
wherein the target digital twin model comprises: the device comprises an electrochemical module, a temperature module, an electrolyte concentration module and a mass transfer module; the temperature module includes: a solution temperature determination module for determining the cell temperature according to the following formula:
Figure FDA0003356718460000011
wherein, TcellIs the temperature of the cell, Cth_cellIs a constant of temperature change, sigma Q is the total heat of the electrolytic cell to overcome the loss, and sigma Q is Qgene-Qloss-Qout±Qcool；QgeneIs heat generated by the electrolytic cell, Qgene＝i×A×(Ecell-Ethe_cell)；EcellElectrolytic potential of monomer, Eth_cellIs the thermal neutral voltage, A is the active area, i is the current;
Figure FDA0003356718460000012
in order to exchange heat with the environment,
Figure FDA0003356718460000013
Tcell-1the temperature of the electrolytic bath obtained by the last calculation is calculated; t isenviIs ambient temperature, Rthe_cellIs the temperature change constant of thermal interaction with the environment;
Figure FDA0003356718460000014
the heat quantity for the alkali liquor and the water to be carried out,
Figure FDA0003356718460000015
Figure FDA0003356718460000016
the flow rate of the water and the alkali liquor is adopted,
Figure FDA0003356718460000017
is the constant pressure specific heat of water and alkali liquor;
Figure FDA0003356718460000018
the pure water is used for bringing in heat,
Figure FDA0003356718460000019
Figure FDA00033567184600000110
is the constant pressure specific heat of pure water, ninIs the water inlet flow.
2. The method of claim 1, wherein the constructing of the target digital twin model comprises:
inputting test parameters in the starting process of the hydrogen production equipment into a pre-established digital twinning model to obtain a digital twinning result;
and calibrating the pre-built digital twin model according to the actual measurement result of the hydrogen production equipment and the digital twin result to obtain a target digital twin model.
3. The method according to claim 2, wherein the calibrating the pre-built digital twin model according to the actual measurement result of the hydrogen production equipment and the digital twin result comprises:
and when the relative deviation between the voltage variation condition along with the current amount and/or the temperature variation condition along with time in the actual measurement result and the voltage variation condition along with the current amount and/or the temperature variation condition along with time in the digital twin result is smaller than a preset threshold, completing the calibration of the pre-established digital twin model.
4. A hydrogen production digital twinning system, comprising:
the electrochemical module is used for simulating a hydrogen production process according to a hydrogen production mechanism;
the temperature module is connected with the electrochemical module and the mass transfer module and used for simulating the solution temperature in the hydrogen production process and sending the solution temperature to the electrochemical module and the mass transfer module;
the electrolyte concentration module is connected with the electrochemical module and used for simulating the electrolyte concentration change in the hydrogen production process and sending the simulated electrolyte concentration to the electrochemical module;
the mass transfer module is connected with the electrochemical module and used for calculating the hydrogen and oxygen partial pressure and the water vapor partial pressure according to the solution temperature and sending the hydrogen and oxygen partial pressure and the water vapor partial pressure to the electrochemical module;
wherein the temperature module comprises: a solution temperature determination module for determining the cell temperature according to the following formula:
Figure FDA0003356718460000031
wherein, TcellIs the temperature of the cell, Cth_cellIs a constant of temperature change, sigma Q is the total heat of the electrolytic cell to overcome the loss, and sigma Q is Qgene-Qloss-Qout±Qcool；QgeneIs heat generated by the electrolytic cell, Qgene＝i×A×(Ecell-Ethe_cell)；EcellElectrolytic potential of monomer, Eth_cellIs the thermal neutral voltage, A is the active area, i is the current;
Figure FDA0003356718460000032
in order to exchange heat with the environment,
Figure FDA0003356718460000033
Tcell-1the temperature of the electrolytic bath obtained by the last calculation is calculated; t isenviIs ambient temperature, Rthe_cellIs the temperature change constant of thermal interaction with the environment;
Figure FDA0003356718460000034
the heat quantity for the alkali liquor and the water to be carried out,
Figure FDA0003356718460000035
Figure FDA0003356718460000036
the flow rate of the water and the alkali liquor is adopted,
Figure FDA0003356718460000037
is the constant pressure specific heat of water and alkali liquor;
Figure FDA0003356718460000038
the pure water is used for bringing in heat,
Figure FDA0003356718460000039
Figure FDA00033567184600000310
is the constant pressure specific heat of pure water, ninIs the water inlet flow.
5. The hydrogen producing digital twinning system of claim 4, wherein the electrochemical module comprises:
the reversible voltage determining module is used for determining reversible voltage according to the concentration of the electrolyte, the temperature of the solution and the partial pressure of hydrogen and oxygen;
the activation polarization voltage determination module is used for determining activation polarization voltage according to the solution temperature and the current;
the ohmic polarization voltage determining module is used for determining ohmic polarization voltage according to internal resistance in the electrolysis process;
and the concentration polarization voltage determination module is used for determining the concentration polarization voltage according to the solution temperature and the electrolyte concentration.
6. The hydrogen producing digital twin system as set forth in claim 4 wherein the mass transfer module comprises: a pressure calculation module for determining the oxygen partial pressure according to the following formula:
Figure FDA0003356718460000041
wherein the content of the first and second substances,
Figure FDA0003356718460000042
is the partial pressure of the oxygen at the anode,
Figure FDA0003356718460000043
is the partial pressure of the water vapor,
Figure FDA0003356718460000044
is the molar mass fraction of water in the anode,
Figure FDA0003356718460000045
εanis the porosity of the anode, τanFor the tortuosity of the anode, R is the ideal gas constant (8.314), T is the temperature at which the reaction proceeds, i is the current density, lan-cLength of anode electrode to flow field, panIs the anode pressure, F is the Faraday constant,
Figure FDA0003356718460000046
is the anode effective molar diffusion coefficient.
7. An optimization device for the transient process of an alkaline water electrolysis hydrogen production device is characterized by comprising:
the control parameter input module is used for inputting the test parameters of the transient process of the hydrogen production equipment into the target digital twin model;
the optimizing module is used for optimizing the transient process of the hydrogen production equipment to obtain optimized control parameters, and the optimized control parameters are used for guiding input parameters in the hydrogen production process;
wherein the target digital twin model comprises: the device comprises an electrochemical module, a temperature module, an electrolyte concentration module and a mass transfer module;
the temperature module includes: a solution temperature determination module for determining the cell temperature according to the following formula:
Figure FDA0003356718460000047
wherein, TcellIs the temperature of the cell, Cth_cellIs a constant of temperature change, sigma Q is the total heat of the electrolytic cell to overcome the loss, and sigma Q is Qgene-Qloss-Qout±Qcool；QgeneIs heat generated by the electrolytic cell, Qgene＝i×A×(Ecell-Ethe_cell)；EcellElectrolytic potential of monomer, Eth_cellIs the thermal neutral voltage, A is the active area, i is the current;
Figure FDA0003356718460000051
in order to exchange heat with the environment,
Figure FDA0003356718460000052
Tcell-1the temperature of the electrolytic bath obtained by the last calculation is calculated; t isenviIs ambient temperature, Rthe_cellIs the temperature change constant of thermal interaction with the environment;
Figure FDA0003356718460000053
the heat quantity for the alkali liquor and the water to be carried out,
Figure FDA0003356718460000054
Figure FDA0003356718460000055
the flow rate of the water and the alkali liquor is adopted,
Figure FDA0003356718460000056
is the constant pressure specific heat of water and alkali liquor;
Figure FDA0003356718460000057
the pure water is used for bringing in heat,
Figure FDA0003356718460000058
Figure FDA0003356718460000059
is the constant pressure specific heat of pure water, ninIs the water inlet flow.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method for optimizing a transient process in an alkaline water electrolysis hydrogen plant according to any one of claims 1 to 3.
9. A storage medium having stored thereon computer instructions, wherein the instructions when executed by a processor, perform the steps of the method for optimizing a transient state of an alkaline water electrolysis hydrogen plant according to any of claims 1 to 3.
CN202110415969.5A 2021-04-16 2021-04-16 Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system Active CN113122867B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110415969.5A CN113122867B (en) 2021-04-16 2021-04-16 Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110415969.5A CN113122867B (en) 2021-04-16 2021-04-16 Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system

Publications (2)

Publication Number Publication Date
CN113122867A CN113122867A (en) 2021-07-16
CN113122867B true CN113122867B (en) 2022-04-08

Family

ID=76777372

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110415969.5A Active CN113122867B (en) 2021-04-16 2021-04-16 Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system

Country Status (1)

Country Link
CN (1) CN113122867B (en)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113793649B (en) * 2021-09-13 2024-02-27 同济大学 Method for constructing digital twin model of operation characteristics of alkaline electrolytic tank
CN114481215B (en) * 2022-01-10 2022-08-19 清华大学 Electrolytic hydrogen production device and control method thereof
CN114855185A (en) * 2022-04-28 2022-08-05 同济大学 Active liquid level adjusting system and method for alkali tank of large electrolytic cell
CN114921811A (en) * 2022-04-28 2022-08-19 同济大学 Alkali liquor concentration control system and method for alkaline electrolysis system
CN116516412B (en) * 2023-06-30 2023-10-27 中石油深圳新能源研究院有限公司 Alkaline water hydrogen production control system and alkaline water hydrogen production control method
CN117075498A (en) * 2023-10-16 2023-11-17 三峡科技有限责任公司 Water electrolysis hydrogen production energy consumption monitoring and bionic optimizing system
CN117252032B (en) * 2023-11-10 2024-02-13 三峡科技有限责任公司 Method, device and equipment for constructing digital twin body of alkaline water electrolysis hydrogen production system

Also Published As

Publication number Publication date
CN113122867A (en) 2021-07-16

Similar Documents

Publication Publication Date Title
CN113122867B (en) Method for optimizing transient process of alkaline water electrolysis hydrogen production equipment and hydrogen production system
Xia et al. The application of orthogonal test method in the parameters optimization of PEMFC under steady working condition
García-Valverde et al. Simple PEM water electrolyser model and experimental validation
Schalenbach et al. Pressurized PEM water electrolysis: Efficiency and gas crossover
Colbertaldo et al. Zero-dimensional dynamic modeling of PEM electrolyzers
Milewski et al. Modeling an alkaline electrolysis cell through reduced-order and loss-estimate approaches
Lamy et al. Kinetics analysis of the electrocatalytic oxidation of methanol inside a DMFC working as a PEM electrolysis cell (PEMEC) to generate clean hydrogen
Zhao et al. Dynamic behaviour and control strategy of high temperature proton exchange membrane electrolyzer cells (HT-PEMECs) for hydrogen production
Dedigama et al. An experimentally validated steady state polymer electrolyte membrane water electrolyser model
KR100811982B1 (en) Fuel cell system and control method of it
Headley et al. Development and experimental validation of a physics-based PEM fuel cell model for cathode humidity control design
CN115207417A (en) Large-area fuel cell current density distribution calculation method
Atifi et al. Effect of internal current, fuel crossover, and membrane thickness on a PEMFC performance
Casalegno et al. DMFC anode polarization: Experimental analysis and model validation
Unnikrishnan et al. Mechanistic modeling of electrochemical charge transfer in HT-PEM fuel cells
Espinoza-Andaluz et al. Empirical correlations for the performance of a PEFC considering relative humidity of fuel and oxidant gases
Thomassen et al. Evaluation of concepts for hydrogen–chlorine fuel cells
Han et al. Modeling of interfacial resistance effects on the performance and efficiency for electrolyzer energy storage
JP4584184B2 (en) Fuel cell fuel supply control method
CN102195052A (en) Adaptive method for conversion of external power request to current setpoint to a fuel cell system based on stack performance
CN113540536B (en) Method and device for humidifying galvanic pile and electronic equipment
CN114171760A (en) Fuel cell testing method combined with simulation model
US10957928B2 (en) Method for measuring and controlling methanol concentration in a methanol fuel cell
KR101105364B1 (en) Sensor and method for sensing fuel concentration, method and system apparatus for fuel recirculation of fuel cell using the same, fuel cell usage apparatus using the same
CN110993035B (en) Two-dimensional steady-state model establishment method for proton exchange membrane electrolytic cell characteristic analysis

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant