Method for controlling operation of electrolysis cell plant

Abstract

There is provided a computer-implemented method for controlling operation of an electrolysis cell plant comprising one or more electrolysis cell modules, each electrolysis cell module comprising at least one stack of electrolysis cells, the method comprising: for each electrolysis cell module of the one or more electrolysis cell modules, determining a target module setpoint by minimizing a total operating cost function associated with operation of the electrolysis cell plant, where the total operating cost function includes a total degradation cost associated with degradation of the one or more electrolysis cell modules; and controlling each of the one or more electrolysis cell modules to operate at the determined target module setpoint.

Description

Technical Field

[0001] The present invention relates to a computer-implemented method, system, computer program product, and computer-readable medium for controlling the operation of an electrolyzer apparatus. Background Art

[0002] The electrolyzer equipment includes one or more electrolyzer modules, each of which includes at least one electrolyzer stack. Each stack can be composed of multiple cells.

[0003] Improving the operation of an electrolyser plant, in particular operating the electrolyser plant at a suitable overall operating set point, allows for a reduction in the costs incurred in operating the plant.

[0004] Some simple examples for reducing costs include utilizing storage of electricity or hydrogen in a way that enables operation of the module when electricity prices are low. As another example, at the module level, the module set point can be selected to be within a power set point range at which the module operates efficiently.

[0005] However, further improvements are needed to control the operation of electrolyser equipment and thereby reduce costs.

[0006] It is therefore an object of the present invention to provide a method for controlling the operation of an electrolysis cell installation which allows a further reduction in costs. Summary of the Invention

[0007] The present invention achieves this object. The present invention provides a method, a system, a computer program product and a computer readable medium according to the independent claims. Preferred embodiments are set forth in the dependent claims.

[0008] The present invention provides a computer-implemented method for controlling the operation of an electrolyzer apparatus comprising one or more electrolyzer modules, each electrolyzer module comprising at least one electrolyzer stack. The method comprises, for each electrolyzer module in the one or more electrolyzer modules, determining a target module setpoint by minimizing a total operating cost function associated with operation of the electrolyzer apparatus, wherein the total operating cost function includes a total degradation cost associated with degradation of the one or more electrolyzer modules. The method further comprises controlling each electrolyzer module in the one or more electrolyzer modules to operate at the determined target module setpoint.

[0009] Thus, using the method of the present disclosure, in addition to the costs associated with the operation itself, the method also considers the costs associated with degradation of the electrolyzer module. For example, operation at a module set point may appear to have a low cost based on efficiency, electricity and hydrogen pricing, etc., but may result in undesirable degradation characteristics of the module, such as rapid degradation or unevenly distributed degradation or degradation that causes irregularities in the maintenance schedule.

[0010] The method disclosed herein proposes using a total operating cost function representing the total operating cost including degradation costs and minimizing the total cost function. Thus, costs can be reduced compared to known methods. Thus, the method disclosed herein at least achieves the aforementioned objectives.

[0011] The electrolyzer apparatus may include a plurality of electrolyzer modules. Each electrolyzer module may include a plurality of stacks. Each stack may include a plurality of battery cells.

[0012] In addition to one or more stacks, an electrolyser module may also include other components, such as a separator tank, a cooling unit, a pump, a rectifier and / or a filter.

[0013] In the present disclosure, a setpoint may be a value representing the power at which an electrolyzer module is to be operated at a given point in time. This is also referred to as the power setpoint of the electrolyzer module. A (module) setpoint may be expressed, for example, as a power value, a current value, or a voltage value. As an example, a module setpoint may determine the current flowing through the module's stack.

[0014] The term "target module set point" may be understood broadly and may, for example, refer to an operating parameter that is set for operation of an electrolyser module.

[0015] Operating the electrolyser module at the determined target set point may include setting the target set point as a control parameter for operation of the electrolyser module.

[0016] The (power) set point of an electrolyser plant may be the sum of the (power) set points of all electrolyser modules of the plant. All modules may be operated at the same set point, or the set points may be different for different modules.

[0017] Electrolyzer module operation can also be described in terms of a hydrogen setpoint, which is the hydrogen output by the electrolyzer module. Similarly, an electrolyzer plant can have an overall plant hydrogen setpoint. The overall plant hydrogen setpoint can be equal to the sum of the module hydrogen setpoints, or it can be different from the sum, for example, when hydrogen is injected into or withdrawn from hydrogen storage.

[0018] According to the present disclosure, the total operating cost function can be a function that expresses the total operating cost as a function of the module set point plus additional aspects of equipment-wide functionality, the so-called BoP (Balance of Plan) including water cleaning, hydrogen drying, compression and storage, power distribution and equipment automation, etc.

[0019] In addition to the total degradation costs associated with degradation of one or more electrolyzer modules, the total operating costs (as will be described in more detail below) may include other costs associated with the operation of the electrolyzer equipment, such as energy costs, energy storage costs, costs associated with hydrogen prices, hydrogen storage costs, costs associated with energy storage degradation and losses, costs associated with hydrogen storage degradation and losses, etc.

[0020] The total (module) degradation cost and the other costs may each be considered as a term in the total operating cost function.

[0021] The total degradation cost associated with degradation of one or more electrolyzer modules may include any costs incurred due to degradation of the electrolyzer, e.g., costs associated with degradation above or below an ideal degradation rate, maintenance costs, module replacement costs, etc. The total degradation cost may be the sum, optionally a weighted sum, of the respective module degradation costs for each module.

[0022] The module degradation costs and how to determine the module degradation costs will be described in more detail below.The module degradation costs may be provided in terms of module set points, ie the module degradation costs may depend on the set points at which the electrolyser modules are operated.

[0023] The method of the present disclosure may include the step of determining a total operating cost function. Determining the total operating cost function may include, for each electrolyzer module in the one or more electrolyzer modules, determining a module degradation cost resulting from operation of the electrolyzer module based on a module setpoint and / or a module setpoint change. Determining the total operating cost function may also include determining a total degradation cost based on the determined module degradation costs.

[0024] Therefore, a prediction component is introduced in the total operating cost function, which allows predicting future costs due to module degradation.

[0025] According to the present disclosure, the module degradation cost can be calculated based on at least one of the following: cycle cost, in particular based on the number of on / off cycles of the electrolyzer module; ramp cost, in particular based on the cumulative amount of module set point ramps of the electrolyzer module; degradation cost due to current, in particular based on the cumulative current or current density of the electrolyzer module; operating temperature, in particular a scaling factor derived from the operating temperature, for example as described by the Arrhenius law.

[0026] The term cycle cost should be understood broadly and may refer to the costs incurred by switching an electrolyzer module on and off. Each switching cycle (or on / off cycle) results in dissolution and passivation of the electrolyzer electrodes. The cycle cost depends on the number of on / off cycles of the electrolyzer module, for example increasing linearly with the number of on / off cycles. Thus, as an example, to reduce the degradation rate, it may be advantageous to keep the electrolyzer module in an on state (i.e., at a module set point other than zero) or at least in hot standby.

[0027] The term ramp cost should be understood broadly and may refer to the costs associated with changing module setpoints during operation, i.e., setpoint ramps. Ramps may, for example, affect the separator and catalyst of an electrolyzer module. Ramping costs may be based on the cumulative amount of module setpoint ramps for the electrolyzer module, e.g., the time-integrated module setpoint ramps.

[0028] The term "current-induced degradation costs" should be understood broadly and may refer to costs associated with degradation due to current flow during operation, particularly due to high current flow, which degrades a module more quickly than low current flow. The current-induced degradation costs may be based on the accumulated current or current density of the electrolyser module, such as the time-integrated current or current density.

[0029] The term operating temperature should be understood broadly and may refer to the temperature of a module during operation. Higher temperatures can increase the rate of chemical reactions, including degradation reactions. This particularly relates to operating temperatures above the nominal operating temperature, for example, provided by the manufacturer. Module degradation costs can be calculated, for example, using a scaling factor derived from the operating temperature, such as that described by the Arrhenius law.

[0030] The module degradation cost may be based on at least one of the following parameters associated with at least one stack of the electrolyser module, one or more of which may be time-dependent: activation energy E of the degradation reaction, nominal temperature T of the stack nom , nominal stack life T lifetime , Maximum stack current I max , heap maintenance cost M at the end of life maintenance , the nominal number of on / off cycles before stack maintenance n lifecycle , a ramp factor r, which relates the ramp from the minimum module set point to the maximum module set point to one on / off cycle.

[0031] The activation energy E of the degradation reaction can be determined or modeled, for example, empirically or semi-empirically.

[0032] Nominal temperature of the stack T nom This is the temperature of the stack during nominal operation. It may be provided, for example, by the stack supplier.

[0033] Nominal stack life T lifetime This may refer to the stack life under nominal operation, for example in terms of full load hours, and may be provided by the stack supplier.

[0034] Maximum stack current I max It can refer to the maximum current when the module is operating.

[0035] Heap maintenance cost at end of life M maintenance It can be the cost of module maintenance through battery cell replacement and can be provided by the stack supplier.

[0036] Nominal number of on / off cycles before heap maintenance, n lifecycle Can be a vendor-supplied value.

[0037] The ramp factor r relating the ramp from the minimum module set point to the maximum module set point to one on / off cycle may be determined, for example, empirically, semi-empirically or modeled.

[0038] At least some of the above parameters may be time-dependent. Specifically, the parameters, especially the ramp factor r, may change during the life of the stack. Therefore, the maintenance costs may also change over time.

[0039] The method of the present disclosure may include determining a cycle cost based on the number of on / off cycles and the cycle cost of a single cycle, in particular by comparing the number of on / off cycles with the stack maintenance cost M at the end of life. maintenance Divide by the nominal number of on / off cycles before maintenance n lifecycle The obtained values ​​are multiplied to determine the cycle cost. For example, reducing the number of cycles can reduce the degradation rate.

[0040] The method of the present disclosure may include determining a ramp cost for operating at a non-constant module set point based on a cumulative ramp and based on the degradation behavior of the electrolyzer module, particularly the separator and / or catalyst of the electrolyzer module, depending on the non-constant module set point. Reducing the cumulative (integrated over time) ramp of the module set point may reduce the degradation rate of the electrolyzer module. The non-constant module set point may be represented, for example, by P(t), U(t), or I(t).

[0041] According to the present disclosure, the ramp cost, in particular the degradation behavior, can be determined based on, in particular, a ramp factor r that associates a ramp from a minimum module set point to a maximum module set point with one on / off cycle, a ratio of the cumulative ramp to the maximum module set point, and a cycle cost for a single cycle. The cost for a single cycle can be the stack maintenance cost M at the end of life. maintenance Divide by the nominal number of on / off cycles before maintenance n lifecycle .

[0042] The method of the present disclosure may include determining a degradation cost due to current based on the cumulative current density in the cell membranes, in particular as simulated by a model or derived from a module set point, or based on an integrated module set point. In particular, the stack maintenance cost M at the end of life may be determined based on the integrated module set point. maintenance , nominal stack life, and maximum module set point to determine the degradation cost due to current. For example, reducing the accumulated current can reduce the degradation rate.

[0043] The method of the present disclosure may include determining a total operating cost function, and determining the total operating cost function may include at least one of: determining degradation parameters based on stack attributes such as stack type and / or stack supplier, determining degradation costs of energy storage associated with using hydrogen storage and / or batteries as energy storage as part of operation of the electrolyzer plant, and determining costs associated with maintenance schedule compliance. Alternatively or additionally, determining the target module setpoint may be performed with maintenance schedule compliance as a constraint.

[0044] It should be noted that, as will be discussed in detail below, degradation at a certain rate also affects factors other than, for example, production efficiency and / or replacement cost of the module (i.e., direct costs associated with degradation). For example, a maintenance plan for the electrolyzer equipment may be appropriate and has been determined based on the expected degradation rate of the module. Modules that degrade faster or slower than the expected degradation rate may increase maintenance costs. This may also result in replacing the module before or after the module reaches a degraded state at which it should be replaced. In addition, hydrogen production efficiency (and corresponding production costs) may depend on the degradation state of the electrolyzer module.

[0045] Determining degradation parameters based on stack properties such as stack type and / or stack vendor may include considering nominal values ​​of one or more of the above-mentioned parameters associated with a given module's stack.

[0046] Determining costs associated with the degree of maintenance plan compliance may include determining costs incurred when a module is fully degraded before a scheduled maintenance time or is not fully degraded at a scheduled maintenance time, such as missing a module for a period of time, additional maintenance actions, or taking a module out of service sooner than necessary.

[0047] As an example, performing the determination of target module setpoints with maintenance schedule compliance as a constraint may include setting constraints such that certain modules will reach a maintenance state at a predetermined time based on expected degradation.

[0048] According to the present disclosure, module degradation costs can be predicted using a model configured to quantitatively determine degradation of at least one electrolyzer stack based on module setpoint history. As an example, the model can consider one or more of the above-mentioned parameters associated with module degradation costs.

[0049] The method of the present disclosure may include monitoring actual module set points and corresponding actual degradation, and based thereon, continuously adjusting model parameters of the model to reflect the actual degradation under operation at a given module set point, optionally with the aid of machine learning (ML) or artificial intelligence (AI).

[0050] Thus, a correction element is provided which allows for an improved prediction accuracy of the degradation costs and thus better results in terms of cost reduction.

[0051] According to the present disclosure, it is possible to determine the target module setpoint so that it is the same for all electrolyzer modules. This can be achieved, for example, by corresponding boundary conditions. This may have computational benefits, automation requirements, for example, if modules cannot be controlled individually, or if it is desirable to uniformly wear the stack. The total plant power setpoint can be generated by the sum of the module setpoints of all (active) electrolyzer modules of the plant. Thus, the total plant power setpoint can be evenly distributed across multiple electrolyzer modules.

[0052] Determining the target module setpoint may include considering constraints on the device setpoint. For example, while the device setpoint may be controlled by some constraints (e.g., sufficient output from the operating and storage devices and / or a limit on the amount of electricity consumed for operation), the device setpoint may vary within the constraints. For example, as described above, flexibility may be provided by hydrogen or electricity storage.

[0053] The operation of the plant may be characterized, for example, by at least the power input and the hydrogen output and / or the hydrogen production efficiency of the entire plant.Additional parameters may be considered to characterize the operation.

[0054] Furthermore, other aspects can also be considered in the optimization, such as the available storage of energy, hydrogen, gas and heat and their respective costs / efficiencies.

[0055] Other aspects that can also be taken into account in the optimization are the characteristics of the electrolyzer modules, the operating conditions or the wear of the equipment.

[0056] Optionally, in addition to the above-mentioned technical aspects, there may also be aspects related to pricing, contractual obligations etc. that may be taken into account in the optimization.

[0057] The present invention also provides a system comprising a processing system configured to perform any of the methods of the present disclosure.

[0058] The system may also include one or more electrolyzer modules of an electrolyzer facility, the processing system being configured to control operation of the one or more electrolyzer modules to operate at the determined target module set point.The system may be or include an electrolyzer facility.

[0059] The system may include a hydrogen storage system and / or an electricity storage system.

[0060] The present invention also provides a computer program product comprising instructions, which, when executed by a computer, cause the computer to perform any method of the present disclosure.

[0061] The present invention also provides a computer-readable medium comprising instructions that, when executed by a computer, cause the computer to perform any of the methods disclosed herein.

[0062] The features and advantages outlined above in the context of the method similarly apply to the system, computer program product, and computer-readable medium described herein.

[0063] Further features, examples and advantages will become apparent from the detailed description taken with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1a and Figure 1b shows a schematic diagram of an electrolyzer apparatus;

[0065] Figure 2 is a flow chart illustrating a method according to the present disclosure;

[0066] Figure 3 is a flow chart illustrating a method according to the present disclosure;

[0067] Figure 4 is a flow chart illustrating a method according to the present disclosure. DETAILED DESCRIPTION

[0068] The system 1 of the present disclosure comprises a processing system 3 (also referred to as a computing system) which is configured to perform the method according to the present disclosure, for example, as in Figures 2 to 4 Optionally, the system may also be or include an electrolyser device comprising a plurality of electrolyser modules 2. Such a system may also be or include an electrolyser device comprising a plurality of electrolyser modules 2. Figure 1a and 1b Shown in.

[0069] Figure 1a and 1b The system in FIG. 4 is shown to include an optional monitoring device 4, an optional electrical storage device 5, an optional hydrogen storage device 6, and an optional oxygen storage device 7. In addition, arrow 8 represents the input of electricity to the electrolyzer apparatus, arrow 9 represents the output of hydrogen from the electrolyzer apparatus, arrow 10 represents the output of oxygen from the electrolyzer apparatus, arrow 11 represents the output of heat from (or input of) the electrolyzer apparatus, and arrow 12 represents the input of water to the electrolyzer apparatus.

[0070] The grid 13 and network 14 into which hydrogen, oxygen and heat are fed are shown for illustration purposes only and are not part of the system of this example.

[0071] Additionally, an optional hydrogen and oxygen separator tank 15 is shown.

[0072] It should be noted that Figure 1a Shows a ratio Figure 1b The devices in which the details of the individual components of the device are presented are presented only to illustrate in an exemplary manner the different levels of detail that may be considered when viewing the operation of the device.

[0073] The method of the present disclosure can be used in Figure 1a and 1b The method steps are performed in the system shown, for example by the processing system 3 or any other suitable system, in particular a system according to the present disclosure.

[0074] Figure 2 is a flow chart illustrating a method according to the present disclosure.

[0075] The present disclosure provides a computer-implemented method for controlling the operation of an electrolyser apparatus comprising one or more electrolyser modules, in particular an apparatus comprising a plurality of electrolyser modules, each electrolyser module comprising at least one electrolyser stack.

[0076] The method includes determining, in step S11, for each of the one or more electrolyzer modules, a target module setpoint by minimizing, in step S11a, a total operating cost function associated with operation of the electrolyzer equipment, wherein the total operating cost function includes a total degradation cost associated with degradation of the one or more electrolyzer modules. Boundary conditions may be set to determine the target module setpoint.

[0077] The method further comprises controlling each of the one or more electrolyser modules to operate at the determined target module set point in step S12.

[0078] The method may further include: step S10 of determining a total operation cost function before step S11 .

[0079] The step of determining the total operating cost function may comprise, in step S10a, for each of the one or more electrolyser modules, determining a module degradation cost caused by operation of the electrolyser module according to the module set point and determining a total degradation cost based thereon.

[0080] The method, in particular determining the total cost function, may comprise one or more of steps S10a-1 to S10a-4.

[0081] In optional step S10a-1, the cycle cost is determined based on the number of on / off cycles and the cycle cost of a single cycle, in particular by comparing the number of on / off cycles with the stack maintenance cost M at end-of-life. maintenance Divide by the nominal number of on / off cycles before maintenance n lifecycle The obtained values ​​are multiplied to determine the cycle cost.

[0082] In optional step S10a-2, a ramp cost for operating at a non-constant module setpoint is determined based on the accumulated ramps and based on degradation behavior of the electrolyser module, in particular the separator and / or catalyst of the electrolyser module, depending on the non-constant module setpoint.

[0083] The ramp costs, in particular the degradation behavior, can be determined based on the ramp factor r that associates the ramp from the minimum module set point to the maximum module set point to one on / off cycle, the ratio of the cumulative ramp to the maximum module set point, and the cycle costs of a single cycle, in particular the stack maintenance cost M at end of life. maintenance Divide by the nominal number of on / off cycles before maintenance n lifecycle .

[0084] In optional step S10a-3, a degradation cost due to current is determined based on the cumulative current density in the cell membrane, in particular simulated by a model or derived from a module set point, or in particular based on an integrated module set point, wherein the stack maintenance cost M at the end of life is determined based on the integrated module set point. maintenance , nominal stack life, and maximum module set point to determine the degradation cost due to current.

[0085] In optional step S10a-4, degradation parameters are determined based on heap properties such as heap type and / or heap vendor.

[0086] A detailed example for determining downgrade costs is provided below.

[0087] Determining the total operating cost function may include an optional step S10b of determining degradation costs associated with using batteries and / or hydrogen storage devices as energy storage devices as part of the operation of the electrolyser plant.

[0088] Determining the total operating cost function may comprise an optional step S10c of determining costs associated with maintenance plan compliance, eg in the form of optimization constraints or the like.

[0089] The method may comprise a step S13 of monitoring the actual module setpoint and the corresponding actual degradation and based thereon, in step S14, continuously adjusting the model parameters of the degradation model to reflect the actual degradation under operation at the given module setpoint, optionally with the aid of machine learning ML or artificial intelligence AI.

[0090] Examples of methods according to the present disclosure

[0091] The disclosed method describes how to incorporate module / stack degradation into a control / optimization model for a hydrogen production facility via electrolysis. By including degradation in the operating model, setpoints can be selected, for example, to minimize the sum of energy costs and stack degradation costs. This results in setpoint selection that optimizes stack lifetime and, therefore, minimizes overall operating costs.

[0092] Like all electrochemical machines (e.g., batteries, fuel cells), electrolyzers degrade over time. This means they lose performance, resulting in reduced efficiency and, therefore, higher power consumption for the same hydrogen production, increased safety risks due to potentially higher crossover (H2 to O2 and vice versa), and shorter maintenance intervals leading to more frequent and, therefore, higher, stack replacement costs.

[0093] Currently, electrolysis setpoints are typically kept fairly constant and close to 100% capacity. For this type of operation, the effects of degradation can be well predicted and modeled as a more or less linear degradation over time. Consequently, electrolyzer stack manufacturers specify a certain number of "full-load operating hours" before the stack must be replaced. This number is typically in the range of 40,000-80,000 hours.

[0094] The shift from a constant to an unstable energy supply, for example, depending on the availability of renewable energy sources (solar, wind), changes the situation. Optimizing operating setpoints based on market conditions (e.g., the electricity spot market) or fluctuating demand (e.g., trailer loading) can reduce operating costs. However, it can also increase degradation.

[0095] Under fluctuating operation, the life of the stack may drop dramatically (e.g., by a factor of 2 to 10). Measures to increase the life under fluctuating conditions have been studied and are based on changes in the production, layout, and materials of the stack. However, there are currently no solutions available to mitigate the effects of fluctuating operation of existing electrolyzers. The present disclosure proposes to mitigate this effect by determining the operating strategy of the electrolyzer so that benefits can be achieved for existing and future electrolyzers. It should be noted that although the beneficial effects of the method of the present disclosure are particularly evident for fluctuating operation scenarios, the beneficial effects are also achieved in non-fluctuating operation scenarios.

[0096] As described above, set point optimization is possible because there is often flexibility that provides the optimizer with alternative options. This flexibility can arise from flexibility in the use of energy from the grid, flexibility in the amount of hydrogen output, hydrogen storage that acts as a buffer between production and demand and thus decouples the production set point from fixed demand requirements, electricity storage (e.g., using a battery energy storage system, BESS) that acts as a buffer between electricity supply and hydrogen production and thus decouples the production set point from fixed electricity availability (e.g., from renewable resources or "power purchase agreements"), and / or the availability of multiple electrolyzer modules that allow the total plant set point to be distributed, for example, evenly or differently, to the modules.

[0097] The method of the present disclosure allows for the consideration of degradation effects when determining operating set points, particularly module set points. A total operating cost function including degradation costs can be used. A model can be employed to determine degradation costs, where:

[0098] • The model allows prediction of the effects of changes in exactly one parameter (ie the module set point).

[0099] • The model allows for quantitative prediction of the degradation state of the stack based on the operating set point history.

[0100] • The model can be used for optimization to control, for example, reducing degradation.

[0101] ●The model relies on only a few parameters that are available for each project.

[0102] • The model can provide optimal control of equipment operation and does not necessarily need to allow chemical reaction prediction or degradation state prediction.

[0103] As will be appreciated from the above description, the method of the present disclosure allows for overall optimization of module set points while taking into account module degradation (among other factors).

[0104] An example for determining a total operating cost function including degradation costs is provided in detail below.

[0105] As an example, as mentioned above, the following parameters may affect the downgrade cost (in order of expected severity):

[0106] ● On / off cycles (also known as open circuit voltage, OCV or shutdown): Shutting down the electrolyser module and returning it to operation dissolves and passivates the electrodes. Only a limited number of such switching cycles can be performed during operation, subject to safety guarantees provided by the module manufacturer, and the number of cycles between such switching cycles is limited. lifecycleAfterwards, the module must be maintained or replaced. This is why, in similar circumstances, it's best to keep the electrolyzer in a "hot standby" state, where the voltage is below the Nernst voltage, causing a small current to flow but no hydrogen to be produced. However, including it in the model allows for the option of shutting down even in beneficial situations, but otherwise preventing it.

[0107] Setpoint ramping (also known as ripple): Frequent changes in the setpoint can lead to increased degradation. This can usually be implemented in the control algorithm, but making it part of the optimization model ensures that it is prevented only when it is beneficial.

[0108] Stack temperature: It is well known that higher temperatures lead to faster chemical reactions. This is also true for degradation. On the other hand, higher temperatures lead to increased stack efficiency. Therefore, a good balance must be found, which can be achieved through a model that includes both effects, such as described in this article.

[0109] High current (almost proportional to high power): Stacks running at higher power may degrade faster. This is why stack manufacturers may provide their lifetime in terms of “full load hours”, which is integrated over time and power.

[0110] Taking the above considerations into account, the degradation model for minimizing the total operating cost function can be configured as follows.

[0111] On / off cycle

[0112] The cycle cost can be defined as follows (M maintenance = heap maintenance cost at end of life)

[0113]

[0114] Here, the number of cycles is counted as the number of times the electrolyser is shut down, and the following abbreviations are used:

[0115]

[0116] Set point ramp

[0117] Operation at non-constant set points also results in degrading behavior of the separator and catalyst and can be quantified using:

[0118]

[0119] To relate this quantity to a penalty, ramp degradation is compared to cycle degradation, where it is assumed that operating the ramp from the minimum power set point to the maximum power set point has the same degradation effect as r off / on cycles, where r is the ratio between 0 (0%) and 1 (100%). Then

[0120]

[0121] High current

[0122] Operation at higher currents results in higher degradation due to anode passivation, growth of inhibition structures and thinning of the separator. To measure operation at high currents weighted by the time the electrolyser module is operated at this high current, the following quantity can be used:

[0123]

[0124] Here, j represents the current density in the cell membrane. The current density j is usually only available in high-detail physics simulations, but is monotonically related to the power of the electrolyzer module. As an alternative, which is also available in simpler models such as the linear model presented, the integrated power can be used:

[0125]

[0126] The derating cost can be attributed to this amount in the following way: If the module is operated at the maximum power set point for time T lifespan , then the maintenance cost M maintenance Therefore,

[0127]

[0128] temperature

[0129] The above effects are generally temperature dependent. They increase with increasing module temperature and decrease with decreasing temperature. The above relationships are for the nominal temperature T nom For temperatures different from the nominal operating temperature, it is rescaled, for example, by the factor described by the following Arrhenius law:

[0130]

[0131] Here, R represents the universal gas constant, and E is the activation energy of the degradation reaction.

[0132] Overall model

[0133] Combining the above degradation effects into a single degradation penalty yields

[0134]

[0135] This formula captures all four mentioned effects and depends only on the following parameters:

[0136]

[0137] Determine set points based on minimization of total operating costs

[0138] The combined degradation penalty is used to calculate the module set point. In general, using optimization to obtain the module set point can produce an optimization problem of the following form:

[0139] min x,y E(x,y)stc(x,y)≥0,y binary

[0140] Among them, x and y represent decision variables, and x includes at least the module points of each module on the time grid, that is,

[0141]

[0142] Where further decision variables represent further decision variables.

[0143] here, represents the DC power setpoint of the i-th electrolyzer module at the j-th time step. Furthermore, c(x,y)≥0 encodes the operating model of the hydrogen production plant, and E(x,y) represents the energy cost associated with the module setpoint encoded over the time horizon by x.

[0144] Including degradation in the model allows the module setpoints to be calculated by optimization:

[0145] min x,y E(x,y)+π degradation (x,y)stc(x,y)≥0,y binary

[0146] Figure 3 An exemplary flow chart of a method according to the present disclosure is shown in FIG. , which may employ the above principles.

[0147] It should be noted that it is not necessary to include all of the above factors when determining the cost function. Improvements are achieved when at least one of the above factors is taken into account. In some practical situations, some factors may not have a significant impact. In any case, the accuracy of the method can be further improved by considering more than one factor.

[0148] Other aspects of the present disclosure

[0149] According to the present disclosure, the cost function may take into account degradation parameters that depend on stack properties, including the type of stack (PEM, alkaline, SOEC, etc.) and / or the supplier.

[0150] In accordance with the present disclosure, the method may entail optimizing the use of storage assets for electricity and / or hydrogen when determining module set points.

[0151] The method may need to account for degradation of batteries used for electrical energy storage when determining module set points in order to prevent excessive battery degradation.

[0152] As a secondary objective or boundary condition for minimization, the method may require controlling degradation of the electrolyzer modules, e.g. to minimize degradation or in order to meet maintenance schedules, e.g. to improve spare parts management and maintenance schedule compliance. The latter may require controlling operations to achieve:

[0153] Faster degradation to ensure the stack is at end-of-life when the planned replacement date is scheduled;

[0154] ● Slower degradation to ensure the stack remains operational and safe until the planned replacement date.

[0155] According to the disclosed method, actual module setpoints can be stored, actual degradation can be monitored, and the model parameters of the aforementioned model can be continuously adjusted / updated to reflect the actual degradation at a given setpoint. This can be accomplished using AI or ML. This can improve accuracy, as degradation parameters typically vary between individual electrolyzer stacks, and because actual degradation typically follows a nonlinear degradation behavior over time. The proposed method can take care to always perform a local linear fit to the degradation curve at the current time.

[0156] Figure 4 An exemplary workflow including such adjustment or updating of model parameters is shown.

[0157] The disclosed method has been shown to reduce total operating costs by approximately 2% for some relatively constant operating scenarios and by approximately 35% for some quite unstable operating scenarios, compared to degradation-independent control.

[0158] Although the present invention has been described in detail in the drawings and the foregoing description, such illustration and description are to be considered illustrative rather than restrictive. The present invention is not limited to the disclosed embodiments. In view of the foregoing description and the drawings, it will be apparent to one skilled in the art that various modifications may be made within the scope of the present invention as defined by the claims.

Claims

1. A computer-implemented method for controlling the operation of an electrolyser apparatus (1), the electrolyser apparatus comprising one or more electrolyser modules (2), each electrolyser module comprising at least one electrolyser stack, the method comprising: determining (S11) a target module set point for each of the one or more electrolyser modules (2) by minimizing (S11a) a total operating cost function associated with operation of the electrolyser apparatus (1), wherein the total operating cost function includes a total degradation cost associated with degradation of the one or more electrolyser modules; as well as Each of the one or more electrolyser modules is controlled (S12) to operate at the determined target module set point.

2. The method according to claim 1, comprising determining (S10) the total operating cost function, Wherein determining the total operation cost function comprises: For each of the one or more electrolyser modules (2), a module degradation cost caused by operation of the electrolyser module is determined (S10a) based on a module set point and / or a set point change, and the total degradation cost is determined based on the module degradation cost.

3. The method of claim 2, wherein the module downgrade cost is calculated based on at least one of the following: Cycle costs, in particular based on the number of on / off cycles of the electrolyser module, ramp costs, in particular the cumulative amount of module set point ramps based on the electrolyser modules, Degradation costs due to current, in particular based on the cumulative current or current density of the electrolyser module, The operating temperature, and in particular the scaling factor derived from said operating temperature, is described, for example, by the Arrhenius law.

4. The method according to claim 2 or claim 3, wherein: The module degradation cost is based on at least one of the following parameters associated with at least one stack of the electrolyser module, one or more of which can be time-dependent: The activation energy E of the degradation reaction, The nominal temperature of the stack, Nominal heap life, Maximum stack current I max , Heap maintenance cost at end of life M maintenance , Nominal number of on / off cycles before heap maintenance, n lifecycle , A ramp factor r that associates the ramp from the minimum module set point to the maximum module set point with one on / off cycle.

5. The method according to claim 3 or claim 4, comprising determining (S10a-1) the cycle cost based on the number of on / off cycles and the cycle cost of a single cycle, in particular by comparing the number of on / off cycles with the stack maintenance cost M at the end of life. maintenance Multiply and divide by the nominal number n of on / off cycles before maintenance lifecycle To determine the cycle cost.

6. Method according to any one of claims 3 to 5, comprising determining (S10a-2) the ramp cost for operating at the non-constant module set point based on a cumulative ramp and based on a degradation behavior of the electrolyzer module, in particular a separator and / or a catalyst of the electrolyzer module, depending on the non-constant module set point.

7. The method according to claim 6, wherein the ramp cost, in particular the degradation behavior, is determined based on a ramp factor r, which combines the ramp from the minimum module set point to the maximum module set point with one on / off cycle, the ratio of the cumulative ramp to the maximum module set point, and the cycle cost of a single cycle, in particular the stack maintenance cost M at the end of life. maintenance Divide by the nominal number of on / off cycles before maintenance n lifecycle associated.

8. The method according to any one of claims 3 to 7, comprising determining (S10a-3) the degradation cost due to current based on the cumulative current density in the cell membrane, in particular simulated by a model or derived from the module set point, or in particular based on an integrated module set point, in particular Wherein the degradation cost due to current is based on the integrated module set point, the stack maintenance cost M at the end of life maintenance , nominal stack life and maximum module set point.

9. The method according to any one of the preceding claims, comprising determining the total operating cost function, wherein determining the total operating cost function comprises at least one of: determining (S10a-4) degradation parameters based on stack properties such as stack type and / or stack supplier, determining (S10b) degradation costs associated with using batteries and / or hydrogen storage as energy storage as part of operation of the electrolyser apparatus (1), and determining (S10c) costs associated with maintenance schedule compliance, and / or Wherein determining the target module set point is performed with the maintenance plan compliance as a constraint.

10. The method of any one of claims 2 to 9, wherein the module degradation cost is predicted using a model configured to quantitatively determine degradation of the at least one electrolyser stack from module set point history.

11. The method according to claim 10, wherein actual module set points and corresponding actual degradation are monitored (S13) and based thereon, model parameters of the model are continuously adjusted (S14) to reflect the actual degradation under operation at a given module set point, optionally with the aid of machine learning (ML) or artificial intelligence (AI).

12. The method according to any of the preceding claims, wherein determining the target module set point is performed such that the target module set point is the same for all electrolyser modules (2).

13. A system (1) comprising a processing system (3) configured to perform the method according to any one of claims 1 to 12, in particular also comprising one or more electrolyser modules (2) of an electrolyser plant, the processing system being configured to control the operation of the one or more electrolyser modules (2) to operate at a determined target module set point, and optionally also comprising a hydrogen storage system and / or an electricity storage system.

14. A computer-readable medium comprising instructions which, when executed by a computer, cause the computer to perform the method according to any one of claims 1 to 12.

15. A computer program product comprising instructions which, when said program is executed by a computer, cause said computer to perform the method according to any one of claims 1 to 12.

Images