Electrolytic device simulator, simulation method, and electrolytic device

Abstract

To provide an electrolytic device simulator capable of determining a state close to a real operation of an electrolytic cell or an electrolytic cell stack.SOLUTION: A simulator 100 according to an embodiment of the present invention is an electrolytic device simulator that simulates the performance of a first cell stack comprising one or a plurality of electrolytic cells each comprising a cathode carrying out a reductive reaction and an anode carrying out an oxidation reaction by calculation, and comprises a calculation unit 120 performing calculation using a first group of variables representing at least one of the flooding and salt precipitation in the first electrolytic cell stack, in a calculation method implemented in the simulator 100.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] An embodiment of the present invention relates to a simulator for an electrolysis device, a simulation method, and an electrolysis device. [Background technology]

[0002] In recent years, there have been concerns about the depletion of fossil fuels such as oil and coal, and expectations are growing for renewable energy that can be used sustainably. Examples of renewable energy include solar power generation, hydroelectric power generation, wind power generation, and geothermal power generation. These are power sources with fluctuating output (variable power sources) because the amount of power generated depends on the weather and natural conditions, and they have the problem of difficulty in providing a stable supply of electricity. For this reason, attempts have been made to store the electricity generated by renewable energy in storage batteries to stabilize the power. However, when storing electricity, there are problems such as the cost of storage batteries and the occurrence of losses during storage.

[0003] In response to these issues, technologies that convert electrical energy into chemical substances (chemical energy) are attracting attention, such as producing hydrogen from water by performing water electrolysis using electricity generated from renewable energy, producing carbon compounds such as carbon monoxide, formic acid, methanol, methane, acetic acid, ethanol, ethane, and ethylene by electrochemically reducing carbon dioxide, or producing ammonia by electrochemically reducing nitrogen. Storing these chemical substances in cylinders or tanks has the advantage of reducing energy storage costs and reducing storage losses compared to storing electricity (electrical energy) in storage batteries.

[0004] The electrolysis of water (H2O), carbon dioxide (CO2), nitrogen (N2), etc., as described above, is often carried out in an electrolysis cell or an electrolysis cell stack in which a plurality of such cells are stacked. In the electrolysis cell stack, phenomena such as flooding and salt deposition occur, which causes a problem of performance degradation. For example, in a CO2 electrolysis cell in which an electrolyte is supplied to the anode and carbon dioxide is supplied to the cathode, the electrolyte may move from the anode side to the cathode side. The electrolyte that moves to the cathode side prevents carbon dioxide from reaching the reaction field on the catalyst surface of the cathode, causing a performance degradation of the electrolysis cell. Therefore, there is a demand for a technology that can predict the performance of a cell stack taking into account such phenomena of flooding and salt deposition, and a technology that can control the cell stack so as to suppress flooding and salt deposition. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] JP 2021-046574 A [Patent Document 2] JP 2020-045515 A [Non-patent literature]

[0006] [Non-Patent Document 1] R.Guan and A.Bazylak, Electrochimica Acta, 447, 42103 (2023) [Non-Patent Document 2] DGWheeler et al., Energy & Environmental Science, 13, 5126-5134 (2020) Summary of the Invention [Problem to be solved by the invention]

[0007] The problem to be solved by the present invention is to provide an electrolysis device simulator and a simulation method that make it possible to determine a state close to the actual operation of an electrolysis cell or an electrolysis cell stack, and an electrolysis device equipped with such a simulator. [Means for solving the problem]

[0008] The simulator of the embodiment is a simulator of an electrolytic device that simulates through calculation the performance of a first cell stack that has one or more electrolytic cells each having a cathode that performs a reduction reaction and an anode that performs an oxidation reaction, and in a calculation method implemented in the simulator, the simulator includes a calculation unit that performs calculations using a first group of variables that represent at least one of flooding and salt precipitation in the first electrolytic cell stack. [Brief description of the drawings]

[0009] [Figure 1] FIG. 2 illustrates a first example of a simulator according to an embodiment. [Diagram 2] FIG. 1 is a diagram illustrating an example of an electrolysis device whose performance is simulated by calculation using a simulator according to an embodiment. [Diagram 3] FIG. 13 is a diagram illustrating a second example of the simulator according to the embodiment. [Figure 4] FIG. 13 is a diagram illustrating a third example of a simulator according to an embodiment. [Diagram 5] FIG. 13 is a diagram illustrating a fourth example of the simulator according to the embodiment. [Figure 6] FIG. 13 is a diagram illustrating a fifth example of the simulator according to the embodiment. [Figure 7] 4 is a diagram showing a schematic diagram of a change in light intensity over time in a cathode flow channel as one of a first variable group of the simulator of the embodiment. FIG. [Figure 8] FIG. 13 is a diagram showing an example of an analysis result of X-ray imaging of a cross section of an electrolysis cell as one of the first variable group of the simulator of the embodiment. [Figure 9]FIG. 13 is a diagram showing an example of an analysis result of X-ray imaging of a cross section of a cathode while changing the current density applied to an electrolysis cell as one of the first variable group of the simulator of the embodiment. [Figure 10] FIG. 1 is a diagram illustrating an example of an electrolysis device according to an embodiment. [Figure 11] FIG. 13 is a diagram showing another example of the electrolysis device according to the embodiment. [Figure 12] FIG. 2 is a conceptual diagram of a simulator according to an embodiment. [Figure 13] FIG. 2 is a first flowchart of a control method for an electrolysis device according to an embodiment. [Figure 14] FIG. 2 is a second flowchart of the control method for the electrolysis device according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0010] Hereinafter, an electrolysis device simulator, a simulation method, and an electrolysis device including such a simulator according to an embodiment will be described with reference to the drawings. In the following embodiments, substantially the same components are denoted by the same reference numerals, and some of the descriptions thereof may be omitted. The drawings are schematic, and the relationship between thickness and planar dimensions, the thickness ratio of each part, etc. may differ from the actual ones.

[0011] The electrolysis device to be simulated by the simulator of the embodiment includes a first cell stack having one or more electrolysis cells each including a cathode for performing a reduction reaction and an anode for performing an oxidation reaction. The size of the first cell stack to be simulated and the number of stacked electrolysis cells are not important. Usually, the electrode area is several cm. 2 From several thousand cm 2 The number of layers often ranges from 1 (single cell) to several hundred.

[0012] Fig. 1 is a diagram showing a first example of a simulator 100 according to an embodiment. As shown in Fig. 1, the simulator 100 according to an embodiment is a computer that implements a simulation model (calculation method). The model includes an input unit 110, a calculation unit 120, and an output unit 130. Variables (first input variables) that reflect the operating state of the first cell stack, such as temperature, pressure, and current density, and parameters that are independent of the operating state, such as the thickness of a member, porosity, and coefficients that represent the characteristics of the catalyst material, are input to the input unit 110. Calculations are performed based on these inputs.

[0013] The calculation may be, in particular, an analytical equation, a numerical solution, or machine learning. It may also be a multiphysics model that couples material balance, energy balance, chemical reaction rate, overvoltage calculation, etc. These calculations may involve convergence calculations. The output obtained as a result of the calculation represents the performance of the first cell stack. For example, the output may be, but is not limited to, a current-voltage characteristic, a product selectivity, a Faraday efficiency, etc.

[0014] The simulator 100 of the embodiment is characterized by using a first variable group representing at least one of flooding and salt precipitation in the first electrolysis cell stack. The first variable group consists of one or more variables. The variables of the first variable group may be inputs to the calculation, may be indirectly calculated from other variables in the calculation, or may be both. In addition to the first input variables reflecting the operating state of the first electrolysis cell stack and parameters independent of the operating state, second input variables consisting of all or part of the variables constituting the first variable group are input to the input unit 110 of the simulator 100 shown in FIG. 1.

[0015] The variables of the first group of variables can be selected from the composition, mass, volume, density, and temporal and spatial changes of the solution or solid in a specific region inside the first electrolytic cell stack, for example, in the anode flow path, the anode, the diaphragm, the cathode, and the cathode flow path, or non-dimensionalized versions of each of the above quantities. Furthermore, in a stack having a plurality of electrolytic cells, statistics (e.g., average, standard deviation, etc.) of the above quantities in each cell in the stack can also be used as variables of the first group of variables. Examples of temporal and spatial changes include the accumulation and loss of the solution or solid in a region inside the cell of interest, and the fluxes entering and leaving each of the above regions. Examples of non-dimensionalized quantities include the ratio of the liquid to the volume of the cathode flow path, and the inflow flux of the solution at a certain position in the cathode normalized by the value at the start of electrolysis.

[0016] FIG 2 shows a carbon dioxide (CO2) electrolysis cell stack 10 as an example of an electrolysis device whose performance is simulated by calculation using the simulator 100 of the embodiment. The electrolysis cell stack 10 shown in FIG 2 includes an electrolysis cell 20. Although FIG 2 shows only one electrolysis cell (single cell) 20, the single cells 20 can be stacked up to several hundred to be used as the electrolysis cell stack 10. Here, the electrolysis cell stack 10 refers to a single electrolysis cell 10 and a stack in which the required number of such cells are stacked. The electrolysis cell 20 includes a cathode section 30, an anode section 40, and a separator (diaphragm) 50.

[0017] The cathode section 30 includes a reduction electrode (cathode) 31 having a metal catalyst layer, a cathode flow path 32, and a cathode current collector 33. The cathode flow path 32 is a gas flow path that supplies CO2 gas as a gas to be reduced to the cathode 31. The cathode 31 is disposed so as to be in contact with CO2 flowing through the cathode flow path 32. The anode section 40 includes an anode (oxidation electrode) 41, an anode flow path 42, and an anode current collector 43. The anode flow path 42 is an electrolyte flow path that supplies an electrolyte to the anode 41 as an anode solution. The electrolyte contains water (H2O) or hydroxide ions (OH) as an oxidizable gas. -The anode 41 is disposed so as to be in contact with the anode solution flowing through the anode flow channel 42.

[0018] The electrolysis cell stack 10 includes a gas supply unit 60 that supplies CO2 to the electrolysis cell 20, and an anode solution supply unit (supply system) 70 that supplies an anode solution to the electrolysis cell 20. The gas supply unit 60 includes a CO2 storage unit 61 such as a CO2 gas cylinder and a CO2 adjustment unit 62 that adjusts the flow rate of the CO2 gas, and supplies CO2 gas from the CO2 storage unit 61 to the cathode flow path 32 through a gas pipe 63. Ions are supplied to the cathode 31 of the electrolysis cell 20 shown in FIG. 2 through the separator 50, and CO2 gas is supplied from the cathode flow path 32. The CO2 reduction product is mainly discharged from the cathode flow path 32. The anode solution supply unit 70 includes an anode solution tank 71 and a pump 72, and supplies an anode solution from the anode solution tank 71 to the anode flow path 42 through the pump 72 and the electrolyte pipe 73. The anode solution circulates through the anode flow path 42 and the electrolyte pipe 73.

[0019] The electrolysis cell 20 is generally sandwiched between a pair of support plates (not shown) and further fastened with bolts or the like. The cathode current collector 33 and the anode current collector 43 are connected to a power source 80. The power source 80 is not limited to a normal commercial power source or a battery, but may be a power source that converts renewable energy into electric energy and supplies it. Examples of such power sources include a power source that converts kinetic energy or potential energy such as wind power, hydraulic power, geothermal power, and tidal power into electric energy, a power source such as a solar cell having a photoelectric conversion element that converts light energy into electric energy, a power source such as a fuel cell or a storage battery that converts chemical energy into electric energy, and a power source such as a device that converts vibration energy such as sound into electric energy.

[0020] The cathode 31 is an electrode (reduction electrode) that generates carbon compounds such as carbon monoxide (CO), methane (CH4), ethane (C2H6), ethylene (C2H4), methanol (CH3OH), ethanol (C2H5OH), and ethylene glycol (C2H6O2) by causing a reduction reaction of carbon dioxide (CO2) as a gas to be reduced. In the cathode 31, a side reaction that generates hydrogen (H2) by a reduction reaction of water (H2O) may occur simultaneously with the reduction reaction of carbon dioxide (CO2). In such a cathode section 30, CO2 gas is introduced from the gas supply section 60 through a gas inlet of the cathode flow path 32. Furthermore, reaction product gases including CO, H2, and the like are discharged through a gas outlet, and the discharged gas is sent to a valuables production section (not shown) or recovered in a product recovery section.

[0021] The cathode 31 has a structure capable of transferring gas or liquid between the separator 50 and the cathode flow path 32, such as a porous structure made of a mesh material, a punching material, a porous body, or a sintered metal fiber body. The cathode 31 includes a porous substrate containing, for example, carbon fiber, and a cathode catalyst layer provided on the porous substrate. A porous layer denser than the porous substrate may be provided between the porous substrate and the cathode catalyst layer. The porous substrate is provided on the cathode flow path 32 side, and the cathode catalyst layer is provided on the separator 50 side. The cathode catalyst layer may be embedded in the porous substrate. The cathode catalyst layer of the cathode 31 preferably has catalyst nanoparticles, catalyst nanostructures, or the like. The cathode catalyst layer is preferably made of a catalyst material (cathode catalyst material) capable of reducing CO2 to generate carbon compounds and reducing the overvoltage of such a reaction.

[0022] The anode 41 causes an oxidation reaction of water (HO) in the anode solution to produce oxygen (O) and hydrogen ions (H + ) or hydroxide ions (OH -) to generate oxygen and water (oxidation electrode). In the anode section 40, an anode solution is introduced and discharged by a pump 72 through a solution inlet and a solution outlet of the anode flow path 42. The anode solution flows through the anode flow path 42 so as to come into contact with the anode 41. When an aqueous electrolyte solution is used as the anode solution, the anode 41 oxidizes water (HO) to generate oxygen and hydrogen ions, or generates hydroxide ions (OH - ) to produce water and oxygen, and is preferably composed mainly of a catalyst material (anode catalyst material) capable of reducing the overvoltage of such a reaction.

[0023] The anode 41 is provided with a structure that allows the anode solution and ions to move between the separator 50 and the anode flow path 42, such as a porous substrate (porous substrate) made of a mesh material, a punched material, a porous sintered body, or the like. The anode solution can be an aqueous solution containing any electrolyte. Such an electrolyte can be, for example, phosphate ions (PO4 2- ), borate ion (BO3 3- ), sodium ion (Na + ), potassium ion (K + ), calcium ion (Ca 2+ ), lithium ion (Li + ), Cesium ion (Cs + ), magnesium ion (Mg 2+ ), chloride ion (Cl - ), hydrogen carbonate ion (HCO3 - ), carbonate ion (CO3 2- The separator 50 is made of a material that allows ions to move between the anode 41 and the cathode 31 and that can separate the anode section 40 and the cathode section 30.

[0024] In the electrolysis cell stack 10 as described above, the electrolyte may move from the anode 41 side to the cathode 31 side. The electrolyte that moves to the cathode 31 side prevents carbon dioxide from reaching the reaction field on the catalyst surface of the cathode 31, causing a decrease in performance of the electrolysis cell. Therefore, it is necessary to predict the performance of the electrolysis cell stack 10 while taking into consideration such flooding and salt precipitation phenomena, and to suppress flooding and salt precipitation. Therefore, in the simulator 100 of the embodiment, the performance is simulated by calculation using variables representing at least one of flooding and salt precipitation as a first variable group, so that the performance of the electrolysis cell stack 10 can be simulated under conditions close to actual use conditions.

[0025] The variables of the first group of variables can be selected from the composition, mass, volume, density, and temporal and spatial changes of the solution or solid in a specific region inside the electrolytic cell stack 10, for example, the anode flow channel 42, the anode 41, the separator 50, the cathode 31, and the cathode flow channel 32, or non-dimensionalized versions of each of the above quantities. Furthermore, in a cell stack having a plurality of electrolytic cells 20, statistics (e.g., average, standard deviation, etc.) of the above quantities in each cell in the stack can also be used as variables of the first group of variables. Examples of temporal and spatial changes include the accumulation and loss of the solution or solid in a region inside the electrolytic cell of interest, and the flux entering and leaving each of the above regions. Examples of non-dimensionalized quantities include the ratio of the liquid to the volume of the cathode flow channel 32, and the inflow flux of the solution at a certain position in the cathode 31 normalized by the value at the start of electrolysis.

[0026] 3 is a diagram showing a second example of the simulator 100 of the embodiment. In the simulator 100 of the embodiment, the variables constituting the first variable group may be defined as functions of other variables or parameters. For example, the volume of the solution in the cathode flow channel can be defined as a function of the operating temperature, the dew point of the gas supplied to the electrolysis cell, the wettability of the flow channel material, etc.

[0027] Fig. 4 is a diagram showing a third example of the simulator 100 of the embodiment. In the simulator 100 of the embodiment, other variables and model parameters may be updated based on the variables constituting the first variable group. For example, the porosity and exchange current density of the cathode, the local temperature of the reaction field, and the like can be updated based on the volume of the solution in the cathode. Fig. 4 shows a case where other variables and model parameters are updated from the first variable group that is an input to the calculation (second input variable), but other variables and model parameters may be updated from the first variable group that is calculated within the model.

[0028] 5 is a diagram showing a fourth example of the simulator 100 according to the embodiment. In the simulator 100 according to the embodiment, the values ​​of the first variable group calculated from the variables and parameters may be further used to update other variables and parameters. In this case, the variables and parameters updated based on the values ​​of the first variable group may or may not be those used to determine the values ​​of the first variable group.

[0029] FIG. 6 is a diagram showing a fifth example of the simulator 100 of the embodiment. The first group of variables is the composition, mass, volume, density, or temporal and / or spatial changes of the solution or solid inside the electrolytic cell. All or part of these values ​​can be determined from an analysis of the first electrolytic cell stack or a second electrolytic cell stack having properties equivalent to those of the first electrolytic cell stack. The variables of the first group of variables handled by the simulator 100 shown in FIG. 6 or a calculation method of the variables is specified based on the results of an analysis of the first electrolytic cell stack 10 or the second electrolytic cell stack by the analysis device 210.

[0030] The analysis device 210 is configured to analyze the electrolytic cell stack 10 using at least one of electromagnetic waves, particle beams, sound waves, electromagnetic fields, current, and voltage, and quantitative information on the solution or solid is obtained by analyzing the results. In this case, signals other than electromagnetic waves, particle beams, sound waves, electromagnetic fields, current, and voltage may be used. Specific analysis methods include imaging of the inside of the electrolytic cell using X-rays, visible light, neutron beams, ultrasound, nuclear magnetic resonance, etc., and electrochemical impedance measurement using alternating current and voltage. Multiple analysis methods may be combined.

[0031] When it is difficult to directly apply the analytical method to the first electrolysis cell stack, a second electrolysis cell stack having the same characteristics can be prepared, and the analysis results can be used to construct a simulator for the first electrolysis cell stack. For example, if the surface of the first electrolysis cell stack is made of metal, it is difficult to analyze the inside of the cell using visible light. Therefore, a second electrolysis cell stack can be prepared by replacing the metal members on the surface with a transparent material, and the analysis results can be used to simulate the first electrolysis cell stack. Similarly, if the first electrolysis cell stack is made of a material that strongly absorbs X-rays, it is difficult to image the inside of the cell using transmitted X-rays. In such a case, the second electrolysis cell stack can be prepared by reducing the thickness of the member made of a material that strongly absorbs X-rays or by changing it to a material that absorbs X-rays less. It is also possible to prepare a second electrolysis cell stack that is easy to handle by reducing the number of layers of the first electrolysis cell stack or by reducing the electrode area.

[0032] The variables of the first variable group may be inputs for the calculation, or may be indirectly calculated from other variables in the model. Therefore, there are two possible ways to use the analysis results of the first or second electrolytic cell stack. One is to obtain and use the value of the variable itself that represents the degree of at least one of flooding and salt deposition. The other is to obtain and use the relationship between the device conditions, such as operating conditions and material characteristics, and the value of the first variable group. The former can be applied to a case where the first electrolytic cell stack is directly analyzed during operation to determine the value of the first variable group, and a calculation is performed based on the determined value to predict the future performance of the first electrolytic cell stack. For example, observation using visible light or ultrasound, and electrochemical impedance measurement using alternating current and / or voltage do not require large-scale equipment, so that it is possible to install analytical equipment next to the electrolytic cell stack and directly analyze the electrolytic cell stack during operation.

[0033] The latter method can be used even when the first electrolysis cell stack is not directly analyzed during operation. The first or second electrolysis cell stack is analyzed under various conditions in advance, and the changes in the values ​​of the first variable group depending on the conditions are understood, and the relationship is incorporated into the model. This makes it possible to predict performance taking into account flooding and / or salt precipitation by estimating the state of flooding and / or salt precipitation only from operating conditions such as temperature, pressure, and current density that have been conventionally measured, without performing special analysis during operation when performance is to be predicted. For example, analysis using X-rays or neutrons and measurement using nuclear magnetic resonance require large-scale and advanced equipment. Usually, the site where the electrolysis device is used is in an environment where such special analysis equipment is not available. Therefore, when these analyses are used, the first or second electrolysis cell stack is analyzed in advance using specialized equipment or facilities, and the results are incorporated into the model, so that the simulation of the embodiment can be used at the site where the electrolysis device is used. The above-mentioned two types of utilization methods can also be used in combination. In other words, both the variables obtained from real-time analysis and the variables calculated in the model may be used.

[0034] For imaging experiments that measure transmitted X-ray light, an analysis based on the Beer-Lambert law is useful, which can be written as A=-log 10 (I out / I in )=ECL …(1) In equation (1), A is the absorbance, I in and I out is the light intensity of the incident light and the transmitted light, E is the molar absorptivity, C is the molar concentration of the medium, and L is the length of the medium. This allows the quantification of the substance in the measurement range. For example, the cathode flow channel of a carbon dioxide electrolysis cell is filled with carbon dioxide gas at the start of electrolysis, and X-ray imaging can be used to quantify the amount of liquid flowing into it.

[0035] In an experiment in which X-rays were irradiated from the cross-sectional direction of the electrolysis cell to a specific position in the cathode flow channel and the transmitted light intensity was observed, the transmitted light intensity before the start of electrolysis (time t = 0) was I0, and the transmitted light intensity at a certain time t1 during electrolysis was I t1 At time t = 0, only gas exists in the flow path, but at t = t1, liquid has moved into the flow path and absorbs X-rays. If we assume that there is no precipitation of solid salt and that the absorption of X-rays by gas and changes in liquid concentration can be ignored, the difference in absorbance at the two times depends only on the amount of liquid in the flow path, and the following equation (2) is established. -log 10 (I t1 / I0)=E liq C liq L liq,t1 …(2) In formula (2), E liq and C liq is the molar absorptivity and molar concentration of the liquid, and L liq,t1 is the length of the liquid in the depth direction at the observation position of the cross section of the flow channel at time t1. From this, I0 and I t1 From L liq,t1 can be obtained and used as the constituent variables of the first variable group. liq,t1By integrating (or performing an approximate product-sum calculation) over the cross section of the flow path, the volume of the liquid occupying the flow path space can be obtained, and this can also be used as a constituent variable of the first variable group.

[0036] In addition to comparing the time t1 before the start of electrolysis and the time during electrolysis, it is also possible to compare two times t1 and t2 during electrolysis. In that case, the transmitted light intensity I t1 and I t2 From this, the change in liquid volume between the two times can be calculated using the following formula (3). -log 10 (I t1 / I t2 )=E liq C liq (L liq,t2 -L liq,t1 ) …(32) It is also possible to obtain the rate of change in the liquid volume by dividing the change in the liquid volume by time. These may be used as constituent variables of the first variable group. Figure 7 shows a schematic diagram of the time change in light intensity in the cathode flow channel.

[0037] FIG. 8 shows an example of an analysis result of X-ray imaging of a cross section of an electrolytic cell including a cathode, a diaphragm, and an anode. FIG. 8 shows the liquid volume at each position calculated based on the measurement result of the transmitted light intensity of the X-ray, and the change in the liquid volume over time. When the liquid volume in the first electrolytic cell stack is defined as a first variable group, the spatial and temporal changes in the variable can be understood based on such data.

[0038] Figure 9 shows an example of the analysis results of X-ray imaging of the cross section of the cathode while changing the current density applied to the electrolysis cell. In Figure 9, the amount of liquid present in the target area of ​​the cathode is calculated based on the results of measuring the intensity of transmitted X-ray light, and the ratio of the liquid to the volume of that area is defined as the degree of saturation. Based on such data, the current density dependency of the first group of variables and the dependency of the current application time can be understood.

[0039] Many simulations for simulating the performance of conventional electrolysis cell stacks are known that seek steady-state performance on the assumption that stable operation is performed. In such simulations, it is not necessary to treat time as a variable in the calculation. In contrast, a simulation that takes degradation into account is expected to be able to predict future electrolysis cell stack performance. Therefore, the simulation model of the embodiment may consider time as a variable for input, calculation, and output. In particular, a first group of variables representing at least one of flooding and salt precipitation may be time-dependent.

[0040] For example, there is a phenomenon in which flooding progresses during operation at a constant current density, and the proportion of the liquid phase in the cathode catalyst layer increases over time. To perform a calculation simulating this, there is a method of defining the liquid volume at each time and its increasing rate in a first variable group. As the values ​​of the first variable group change, performance values ​​such as the voltage value and product selectivity obtained as the result of the calculation also change over time. This makes it possible to predict performance beyond the time of interest. It is also possible to create a statistical model predicting performance at a later time based on information on the operating conditions and cell performance from the start of operation of the electrolysis cell stack to a certain time. According to the embodiment, a first variable group representing at least one of flooding and salt precipitation can be incorporated into such a model. For example, when constructing a machine learning model that uses information from a certain time in the past including the time of interest as input and outputs the electrolysis cell performance at a certain time beyond that time, the prediction accuracy can be improved by including the first variable group in the input.

[0041] An electrolysis device including the simulator described in each of the above examples and a first electrolysis cell stack can be realized. Here, the electrolysis device may include components other than the simulator and the first electrolysis cell stack. For example, the electrolysis device may include an analysis device that analyzes the first electrolysis cell stack and a computer that analyzes the analysis results. FIG. 10 shows an example of an electrolysis device according to an embodiment. The electrolysis device 200 shown in FIG. 10 includes a first electrolysis cell stack 10, an analysis device 210 that analyzes the first electrolysis cell stack, and a computer 211 that analyzes the analysis results of the analysis device 210.

[0042] Observation using visible light, ultrasound, or the like, and electrochemical impedance measurement using alternating current and / or voltage can be performed relatively easily, and therefore, analytical equipment (analysis device 210 and computer 211) can be provided next to the first electrolytic cell stack 10, and analysis can be performed directly during operation of the first electrolytic cell stack 10. On the other hand, when using X-ray imaging, neutron imaging, nuclear magnetic resonance imaging, or the like that require large-scale equipment, it is desirable to perform analysis in advance under various operating conditions and material conditions, understand the correspondence between these conditions and the values ​​of the first group of variables, and incorporate the results into the calculation method of the simulator.

[0043] In the electrolysis apparatus of the embodiment, detectors are installed in the first electrolytic cell stack and in the auxiliary devices for driving the first electrolytic cell stack, data acquired using the detectors is input to a simulator, calculations are performed using the input data, and the operation of the first electrolytic cell stack is controlled using the contents of the calculations. Examples of the auxiliary devices include, but are not limited to, a power source, a pump, a heater, and piping. Examples of the detectors include, but are not limited to, a thermometer, a pressure gauge, a dew point meter, an ammeter, a voltmeter, a gas flow meter, and a gas composition analyzer.

[0044] At least one value included in the calculation in the simulator can be used to control the operating conditions of the first electrolytic cell stack. Here, the value included in the calculation refers to at least one selected from the input values ​​to the simulation model, the values ​​of variables defined in the calculation, and the values ​​obtained as the output result. These values ​​may or may not be variables of the first variable group. For example, the current pressure inside the first electrolytic cell stack input to the model, the current or future estimated liquid volume inside the cell calculated based on the operating conditions and material characteristics in the calculation, the future product selectivity and cell voltage obtained as the output of the calculation, etc. can be used, but are not limited to these.

[0045] In controlling the first electrolysis cell stack, a calculation unit and a control unit are provided in the electrolysis device and used. The calculation unit is a calculator for receiving at least one value included in the calculation in the simulator and determining the operating conditions for suppressing deterioration based on the received value. The calculation unit may be a calculator separate from the simulator of the above-mentioned embodiment, or may be provided by implementing an additional calculation function in the simulator of the embodiment. The calculation method implemented in the calculation unit may use an analytical equation, a numerical solution, or machine learning. Examples of the determination of the operating conditions in the calculation unit include increasing the dew point of the supply gas to suppress salt precipitation in response to an increase in pressure inside the cell, and changing the interelectrode differential pressure to suppress flooding in response to an increase in the estimated liquid amount inside the cell. The control unit is a part for sending signals to the first electrolysis cell stack and auxiliary devices, etc., in order to realize the operating conditions obtained as a result of the calculation in the calculation unit.

[0046] Fig. 11 shows another example of the electrolysis apparatus of the embodiment. The electrolysis apparatus 200 shown in Fig. 11 includes a calculation unit 91 and a control unit 92 in addition to the configuration of the electrolysis apparatus 200 shown in Fig. 10. The first electrolysis cell stack 10 also includes auxiliary devices such as a detector. In such an electrolysis apparatus 200, when an analysis device 210 that directly analyzes the first electrolysis cell stack 10 and a computer 211 that analyzes the analysis results are included, it is also possible to use values ​​of the first variable group acquired in real time during operation of the first electrolysis cell stack 10 for the judgment in the calculation unit 91.

[0047] In the embodiment, a simulation model (calculation method) that can be implemented in a simulator is also provided. The model consists of input, calculation, and output. The calculation may be performed using an analytical equation, a numerical solution, or machine learning. In addition, the calculation may be a multiphysics model that couples material balance, energy balance, chemical reaction rate, overvoltage calculation, and the like. These calculations may involve convergence calculation.

[0048] The calculation method of the embodiment utilizes a first set of variables representing at least one of flooding and salt precipitation. As shown in FIG. 12, the first set of variables consists of one or more variables. These variables of the first set of variables may be inputs to the calculation or may be indirectly calculated from other variables in the calculation. The variables of the first set of variables may be selected from the composition, mass, volume, density, temporal and / or spatial changes of the solution or solid in a specific region inside the first electrolytic cell stack, and non-dimensionalized versions of each of the above quantities. Furthermore, in a stack having multiple electrolytic cells, statistics of each of the above quantities in each electrolytic cell in the stack may also be adopted as variables of the first set of variables.

[0049] The embodiment also provides a method for controlling an electrolytic apparatus. The control method follows the flow shown in Fig. 13 or 14, for example. When the electrolytic apparatus does not include an analysis device, the control method follows the flow shown in Fig. 13, for example. When the electrolytic apparatus includes an analysis device and a computer for analyzing the analysis results, the control method follows the flow shown in Fig. 14, for example.

[0050] A simulation performed on a large computer may be replaced with an approximate model, such as a linear or nonlinear model. In this way, by simplifying the simulation, it is expected that a calculation result equivalent to that of a simulation that requires a relatively long calculation time even on a large computer can be obtained in a shorter time. In addition, by implementing the simplified model on an edge device such as a microcomputer, a calculation simulating the simulation can be output on a small device. Furthermore, the simulation may be simplified by preparing results of simulating many combinations of parameters and extracting weights of a machine learning regression model that has learned those results. For example, by installing the weights on an edge device such as a microcomputer, a calculation simulating the simulation can be output on a small device.

[0051] When the simplified model is used for calculations on a central processing unit equipped in an edge device, which is characterized by low power consumption, low clock speed, and a small number of calculation elements, it is expected that the same calculation results can be obtained for the same input in a shorter time than a simulation using a large computer. By inputting the output of the electrolysis device's sensors into such an edge device, the calculation results can be calculated with a shorter delay than a large computer or simulation. This allows the control signal to be sent quickly based on the input from the electrolysis device, resulting in a higher performance electrolysis device.

[0052] In the above-mentioned embodiment, an example in which the simulator of the embodiment is applied to a CO2 electrolysis device and such a CO2 electrolysis device have been mainly described, but the simulator of the embodiment may be applied to electrolysis devices other than a CO2 electrolysis device, and further includes such electrolysis devices. Examples of electrolysis devices other than a CO2 electrolysis device include, but are not limited to, an H2O electrolysis device that electrolyzes water (H2O) to produce hydrogen and oxygen, and an N2 electrolysis device that electrolyzes nitrogen (N2) to produce ammonia (NH3), etc.

[0053] The configurations of the respective embodiments can be applied in combination with each other, and some of them can be replaced. Although several embodiments of the present invention have been described here, these embodiments are presented as examples and are not intended to limit the scope of the invention. These embodiments can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. These embodiments and their modifications are included in the scope and gist of the invention, and are also included in the scope of the invention and its equivalents described in the claims. [Explanation of symbols]

[0054] 10...electrolytic cell stack, 20...electrolytic cell, 31...cathode, 41...anode, 50...separator, 60...gas supply section, 70...anode solution supply section, 80...power supply, 91...calculation section, 92...control section, 100...simulator, 110...input section, 120...calculation section, 130...output section, 200...electrolytic device, 210...analytical device.

Claims

1. A simulator for an electrolysis device that simulates, by calculation, the performance of a first electrolysis cell stack including one or more electrolysis cells each including a cathode that performs a reduction reaction and an anode that performs an oxidation reaction, the simulator comprising: The simulator includes a calculation unit that performs calculations using a first set of variables representative of at least one of flooding and salt deposition in the first electrolytic cell stack.

2. the first set of variables includes variables that are expressed as functions of other variables or parameters in the calculation method; The simulator according to claim 1 , wherein the calculation unit is configured to perform calculations using the first variable group including the variable.

3. The simulator according to claim 1 , wherein the calculation unit is configured to perform calculations using other variables and parameters that are updated depending on the values ​​of the first group of variables.

4. the values ​​of the first set of variables are determined based on a result of analyzing the first electrolytic cell stack or a second electrolytic cell stack having characteristics equivalent to those of the first electrolytic cell stack using at least one of electromagnetic waves, particle beams, sound waves, electromagnetic fields, currents, and voltages; The simulator according to claim 1 , wherein the calculation unit is configured to perform calculations using the first set of variables defined based on a result of the analysis.

5. The simulator of claim 4 , wherein the analysis is an imaging experiment that visualizes conditions inside the first or second electrolysis cell stack.

6. the values ​​of the first group of variables are determined by a result of analyzing a result of the imaging experiment based on the Beer-Lambert law; The simulator according to claim 5 , wherein the calculation unit is configured to perform calculations using the first set of variables defined based on the results of the analysis.

7. the values ​​of the first group of variables are determined from the absorbance obtained by the analysis; The simulator according to claim 6 , wherein the calculation unit is configured to perform calculations using the first set of variables determined from the absorbance.

8. the first set of variables includes time-dependent variables; The simulator according to claim 1 , wherein the calculation unit is configured to perform calculations using the first group of variables including the time-dependent variables.

9. A method for simulating an electrolysis device, comprising: a calculation for simulating performance of a first electrolysis cell stack including one or more electrolysis cells each including a cathode that performs a reduction reaction and an anode that performs an oxidation reaction, the method comprising: The method of the present invention further comprises the step of: utilizing a first set of variables in said computational procedure that represent at least one of flooding and salt deposition in said first electrolysis cell stack.

10. 10. The simulation method of claim 9, wherein the first set of variables includes variables that are expressed as functions of other variables or parameters in the computational technique.

11. The simulation method according to claim 9 , wherein other variables and parameters are updated depending on the values ​​of the first group of variables.

12. The simulation method of claim 9, wherein the values ​​of the first group of variables are determined based on the results of analyzing the first electrolytic cell stack or a second electrolytic cell stack having properties equivalent to those of the first electrolytic cell stack using at least one of electromagnetic waves, particle beams, sound waves, electromagnetic fields, currents, and voltages.

13. 13. The simulation method of claim 12, wherein the analysis is an imaging experiment to visualize conditions inside the first or second electrolysis cell stack.

14. 14. The simulation method according to claim 13, wherein the values ​​of the first group of variables are determined by analyzing the results of the imaging experiment based on the Beer-Lambert law.

15. The simulation method according to claim 14 , wherein the values ​​of the first group of variables are determined from absorbance values ​​obtained in the analysis.

16. 10. The method of claim 9, wherein the first set of variables includes time-dependent variables.

17. A simulator according to any one of claims 1 to 8; the first electrolysis cell stack; An electrolysis device comprising:

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