Computer implemented method of dynamically operating a fleet of methanation plants and a methanation fleet control device

Abstract

The present disclosure relates to a computer implemented method and to a methanation fleet control unit for dynamically operating a fleet (40) of methanation plants (1) for producing methane and / or methanol. A digital fleet twin (50) of the fleet (40), is provided or accessed, which comprises a plurality of digital methanation plants (52) each representing at least one methanation plant, and respective operating plant boundary conditions (51) for the plurality of digital plants (52). Further, a required methane output profile (60) is received indicative of the required methane output of the fleet (40) of the methanation plants (1). The digital fleet twin (50), is configured to determine control commands (43) for operating the fleet (40) of the methanation plants (1) using the digital fleet twin (50) and the required methane output profile (60).

Description

[0001] P28764PC00

[0002] 1 / 35

[0003] COMPUTER IMPLEMENTED METHOD OF DYNAMICALLY OPERATING A FLEET OF METHANATION PLANTS AND A METHANA- TION FLEET CONTROL DEVICE FOR DYNAMICALLY OPERATING A FLEET OF METHANATION PLANTS

[0004] FIELD OF THE DISCLOSURE

[0005] The present disclosure relates to a computer implemented method of dynamically operating a fleet of methanation plants for producing methane and I or methanol and to a control unit, in particular a methanation fleet control unit, which is configured to dynamically operate a fleet of methanation plants for producing methane and I or methanol. The computer implemented method and I or the control unit use a digital fleet twin as a digital image or reflection of a real fleet of methanation plants.

[0006] BACKGROUND OF THE DISCLOSURE

[0007] Methanation plants are designed to produce methane and I or methanol as an alternative source of these products with respect to natural occurrences. Natural occurrences include e.g. gas and oil fields, which are used to extract the above mentioned products. These products comprise carbon dioxide, which is released in the atmosphere when these products are used. E.g. the burning of methane (natural gas, natural gas liquids or liquefied petroleum gas) produces heat and carbon dioxide. This carbon dioxide gathers in the earth’s atmosphere and is as greenhouse gas jointly responsible for the man-made climate change.

[0008] Nevertheless, natural gas plays a huge role in the industrial energy demand. Many industries rely on natural gas, e.g. for heat production. Further, natural gas is also used as a heat source for individual homes. Reducing the consumption of natural gas is one of P28764PC00

[0009] 2 / 35 the world population targets to reduce or mitigate the negative impacts of the man-made climate change.

[0010] A part of the solution could be to reduce the natural gas consumption or to replace it with other gases like green hydrogen. Nevertheless, the handling of hydrogen is extremely challenging and it cannot be fed into the existing gas pipeline system of countries or regions. Hydrogen would require a completely new pipeline system, which is extremely expensive.

[0011] Another option could be to use green natural gas, in particular, green methane or green methanol. Green natural gas could be defined in that is has been synthesized, in particular via the sabatier-process, using renewable energy and I or renewable base products for the synthesis. The renewable energy may be provided via solar, nuclear or wind power plants etc. and the renewable base products are e.g. provided as waste or byproducts from other processes. E.g. water may be provided from a biogas plant, and carbon dioxide may be also provided from a biogas plant and I or is extracted from the air. Further, water may also be supplied from standard water grid.

[0012] The synthesis of methane is a complex procedure, which requires a plurality of components and input products. Further, the known methanation plants need preferably a constant energy supply and product inflow for an optimized output. The problem with renewable energy, e.g. from wind and solar power plants, is that the supply is not as constant as a conventional energy source like from a coal power plant. The production of green gas therefore requires new devices and methods of controlling the methanation plant in order to dynamically operate the methanation plant for the desired methane production. This requires a completely new control approach for such a methanation plant. Further, the production of green methane in an industrial scale requires to operate a plurality of P28764PC00

[0013] 3 / 35 different methanation plants at different geographical regions such that the different individual customer requests of methane are achievable at the desired location, time and price.

[0014] SUMMARY OF THE DISCLOSURE

[0015] It is an object of the present disclosure to provide a computer-implemented method for dynamically operating a fleet of methanation plants for producing methane and I or methanol and / or a methanation fleet control device, which is configured to determine control commands for dynamically operating a fleet of methanation plants, which address at least one of the disadvantages of the known operating methods and control devices. It is in particular an object of the present disclosure to provide a computer-implemented method and a methanation fleet control device for dynamically operating the fleet of methanation plants in view of changing or varying input variables.

[0016] According to the present disclosure, these objects are addressed by the features of the independent claims. In addition, advantageous embodiments follow from the dependent claims, figures and the description.

[0017] According to the present disclosure, a computer implemented method for dynamically operating a fleet of methanation plants for producing methane and I or methanol is provided. The computer implemented method comprises as a first step to provide or access a digital fleet twin of the fleet of methanation plants. The digital fleet twin is a virtual digital reproduction or digital plan / map of the fleet of the methanation plants. The digital fleet twin comprises a plurality of digital methanation plants each representing at least one of the methanation plants of the fleet or a group of the methanation plants. The digital methanation plants or digital plant twin is a virtual digital reproduction or digital plan / map of the respective methanation plant. The digital methanation plant preferably comprises P28764PC00

[0018] 4 / 35 a plurality of digital components each representing at least one methanation plant component of the methanation plant or a component assembly or group. The methanation plant comprises a plurality of different components, which form in combination the methanation plant, and which are configured to fulfill different tasks for the production of the methane. Such components are e.g. pipes, heaters, reactors, valves, heat exchangers, electrolysers, filters etc. A plurality, preferably all of these components, are virtually represented in the digital methanation plant.

[0019] The digital fleet twin further comprises respective operating plant boundary conditions for the plurality of digital methanation plants, which determine the operation of each of the respective methanation plants. The respective boundary conditions may determine how much methane is producible at what time by the respective methanation plant. Further, the operating plant boundary conditions may comprise information on individual lifetime, ramp-up or ramp-down requirements of the respective methanation plants.

[0020] The computer implemented method further comprises the step of receiving the required methane output profile indicative of the required methane output of the fleet of methanation plants. The required methane output profile determines the amount of methane, which should be produced e.g. 100 cubic meters per hour by the entire fleet of the methanation plants. The target is to produce the methane and directly feed the methane into a natural gas I methane grit or directly provide the methane to a respective industrial plant. Methane could be produced and stored, but storing further increases the costs. It is therefore the target to produce the methane on demand, which is why the required methane output profile may vary over time. In this case it is possible to reduce buffer capacity and to further reduce the production costs.

[0021] The computer implemented method further comprises the step of determining control commands for operating the fleet of the methanation plants using the digital fleet twin P28764PC00

[0022] 5 / 35 and the required fleet methane output profile. The control commands are e.g. determined by the digital fleet twin, which uses the different input variables, in particular the required methane output profile, and calculates the required control commands as output variables. In other words, the digital fleet twin preferably determines the control commands for the real methanation plants such that the desired methane output is realizable with the available input variables. For example, the required methane output profile determines that 40% of the maximum possible methane needs to be produces in a given time. Based on these input variables and the different plant operating boundary conditions of the different digital methanation plants stored in the digital fleet twin, the digital fleet twin calculates and determines the respective control commands to run the plurality of methanation plants for the given timespan such that the required methane is produced as efficient as possible. The control commands may comprise for each methanation plant the expected load profile, which determines the required methane output. The respective methanation plant may determine by itself the control instructions for its components such that the methane is producible as desired. In another embodiment, the control commands may additionally or alternatively comprise instructions for the individual components of the respective methanation plant.

[0023] The digital fleet twin is preferably configured to determine based on respective input variables control commands for operating the fleet of methanation plants. In other words, the digital fleet twin is not only the digital image of the real methanation plant, but is also configured to calculate control commands for the real methanation plants. The different input variables are used by the digital fleet twin to calculate the control commands for the methanation plants, in particular for the different components of each plant. Input variables are information on external influencing factors of the fleet of methanation plants, in particular information on available base products for the methanation, information on the available energy supply, information on the methane demand, and I or information on environmental surrounding conditions. P28764PC00

[0024] 6 / 35

[0025] According to the present disclosure the computer implemented method creates the possibility to dynamically control a fleet of methanation plants with varying input variables, in particular such that the different methanation plants are operable as efficient as possible as a whole. In particular, it is possible to plan ramp up processes and shot down processes the methanation plants due to changing input variables such that the required methane demand is met by the fleet of methanation plants as efficient as possible. Further, the computer implemented method disclosed enables to produce green methane and I or methanol advantageously efficiently, since it allows to operate a methanation plants with renewable input variables.

[0026] The digital fleet twin may use an optimization algorithms for determining the control commands. Determining the control commands is e.g. an optimization problem, solved by the digital fleet twin using the input variables and a respective calculating optimization algorithm. The calculating algorithm may use numerical methods, in particular for nonlinear optimization. The nonlinear optimization algorithm is e.g. an Interior Point Optimizer (IPOPT). The digital fleet twin, in particular at least one processor which uses or runs the digital fleet twin, uses the calculating algorithm to determine the respective control commands. The optimization algorithm may further or additionally use machine learning methods or algorithms for determining the control commands. In particular, the machine learning algorithms may use trained neural networks.

[0027] Further, each digital methanation plant may determine its respective control commands for their components using the received control commands from the digital fleet twin and their individual boundary conditions and I or sensor signals form sensors of the respective methanation plant. Also here, optimization algorithms may be used.

[0028] In an embodiment, the method comprises the step of receiving an estimated electric energy profile for each methanation plant indicative of the expected available electric P28764PC00

[0029] 7 / 35 energy to each of the methanation plants, wherein the control commands are determined further using the estimated electric energy profile for each methanation plant. The expected available electric energy is an important information for the operation of the individual methanation plant. Each of the methanation plants, in particular its different components, require electric energy for its operation. E.g. different heaters, pumps, valves etc. require electric energy for the desired operation. These components and the entire methanation plants are operable within a predetermined range of available electric energy, which produces the desired methane output. E.g. 100% of maximum available electric energy produces 100% of the maximum possible methane, within a given time period. Further, 80% of maximum available electric energy produces 75% of the maximum possible methane, within a given time period e.g. because some components may not be useable in this scenario. According to this embodiment, the expected available electric energy for each methanation plant of the fleet is taken into account. For example, one plant is located in northern Germany and another one in southern Spain. At one day the wind blows strongly in northern Germany and at the same time the sky is clouded in southern Spain resulting in that the plant in northern Germany can expect a high available electric energy and the plant in southern Spain can expect a relative low available electric energy. The methane output of the fleet may in this particular day be produced mainly by the plant in northern Germany. The digital methanation plants may directly receive the estimated electric energy profile or may determine the estimated electric energy profile by itself e.g. by using weather data etc.

[0030] In an embodiment, the estimated electric energy profile comprises an estimated renewable electric energy profile, which determines the expected available renewable electric energy to each of the methanation plants. Renewable electric energy comprises e.g. solar electric energy or wind electric energy. Other renewable electric sources are of course also conceivable. Renewable electric energy often varies over time. In other words, renewable electric energy, in particular from one or small number of sources, is P28764PC00

[0031] 8 / 35 not as constant as e.g. from conventional power sources like a coal power plant. The renewable electric energy profile determines the expected available renewable electric energy to each of the methanation plants for the future, in particular for the predetermined timespan, e.g. for the next week. The renewable electric energy profile may be dependent on predicted weather conditions like wind velocity or a degree of cloudiness. These predicted weather conditions may be updated constantly or periodically, which requires that the estimated renewable electric energy profile is updated. The estimated renewable electric energy profile, preferably constantly updated, is used to determine the control commands, such that the control commands include the estimated renewable electric energy profile.

[0032] In an embodiment, receiving the required methane output profile comprises to receive a plurality of customer individual methane requests, and wherein the control commands are determined using the customer individual methane requests. A plurality of customers may send for the same or different timespans methane requests, which have to be fulfilled by the fleet of methanation plants. These individual methane requests may be combined to the required methane output profile which is used by the digital fleet twin or the individual methane requests are individually used by the digital fleet twin. For example, a first customer requires a specific amount of methane only on next Monday and a second customer requires the same amount of methane on next Monday and T uesday. This means that the fleet needs to produce on Monday twice as much methane as on Tuesday. This could result in the determination of control commands which determine that two of the plants are operational on Monday and that only one of the plants is operational on Tuesday.

[0033] In a further embodiment, the digital fleet twin of the fleet of methanation plants further comprises for each methanation plant, plant location information indicative of the geo- P28764PC00

[0034] 9 / 35 graphical location of the methanation plants, wherein the control commands are determined further using the plant location information. The plant location information determine e.g. in which country, in which state and I or in which municipality the respective methanation plant is located. For example, one plant may be located in southern Spain near Sevilla, another plant may be located in northern Germany near Kiel and a third plant may be located in Finland near Helsinki. The plant location information is not only relevant regarding the determination of the estimated electric energy profile of the individual plant, but also regarding the transportation of the produced methane to the customer.

[0035] In a further embodiment, the customer individual methane requests comprise location information, which determine a geographical target location at which the required methane is to be delivered, and wherein the control commands are determined further using the location information. Not only the plant location may be important for determining which plant should be operated for producing methane but also the target location where the required methane should be delivered. For example, it could be the case that the closer the target location with the plant location the better. But this may not always be possible other factors, like the individual electric energy profile of the respective plant may not enable to produce the required methane by the closest plant. It may therefore be required to use the closest and the second closest. This may of course also chance over time.

[0036] In a further embodiment, the digital fleet twin of the fleet of methanation plants further comprises methane grit information of the methane grit, which is configured to receive the methane produced by a plurality of the methanation plants of the fleet and to deliver the received methane to a target location, and wherein the control commands are determined further using the methane grit information. The methane grit is may be digitally P28764PC00

[0037] 10 / 35 represented in the digital fleet twin and determined if and how methane may be transported from a first geographical location to a second geographical location. The methane grit may connect a methanation plant located in Spain with a customer in Germany, in other words, the produced methane by the plant in Spain is transferable via the methane grit through France to Germany. In another embodiment, the methane grit information may determine that a specific target location is not reachable from a specific methanation plant because they are not linked together. By taking into account the methane grit information it is possible to further optimize the determination of the control commands for the fleet of methanation plants such that the overall production of methane by the fleet is optimized.

[0038] In a further embodiment, the method further comprises the step of receiving methane transfer parameters for at least a plurality of different portions of the methane grit, which are indicative of at least one parameter for transferring methane through the respective portion of the methane grit, and wherein the control commands are further determined using the expected methane transfer parameters. The methane grit is a complex structure with a plurality of feed in locations and a plurality of feed out locations e.g. at the customers. The methane grit connects both parties together. In addition it is of high importance that the parameter of the methane in the grit are kept within predetermined ranges. E.g. the temperature or pressure or composition of the methane needs to be kept within the predetermined ranged. Further, the methane grit may cross state or country boarders, which further add requirements to the methane grit. In addition, different supply and demand situations may cause that parameters of at least a portion of the methane grit change over time, which need to be monitored and controlled. Further, the methane grit may also require maintenance, which may block a specific portion of the methane grit. Overall, many factors influence the current status and operation capabilities of the methane grit. According to this embodiment, methane transfer parameters for at least a plurality of different portions of the methane grit are received. A portion of the P28764PC00

[0039] 11 / 35 methane grit is for example a pipe from A to B. The parameters determine in particular the current transfer capabilities of the respective portion of the methane grit. It is may be determined that this portion is currently interrupted due to maintenance, that the portion transfer capability has reached 80% for a predetermined timespan, or that using this portion requires the payment of a specific fee, which again may be utilization rate dependent. The method according to the present disclosure determines the respective control commands in dependence of these received methane transfer parameters. In particular the digital fleet twin is supplied with the received methane transfer parameters and determines the control commands for operating the fleet of methanation plants further using the methane transfer parameters. For example, transferring methane from the closest plant A to the customer A via a first methane grit portion may currently not be possible or may require the payment of a relative high fee. At the same time, transferring methane from another plant B to the customer A via a second methane grit portion may only require a relative low fee. The control commands are therefore determined that for the specific timeslot, the required methane is produced by plant B. It is therefore possible to control and reduce the overall transfer costs and transfer conditions via the methane grit.

[0040] In a further embodiment, the required methane output profile, the estimated electric energy profile and I or the expected methane transfer parameters are received for a predetermined timespan and the control commands are preferably determined for the predetermined timespan of for another predetermined timespan. For example, the estimated electric energy profile for each or at least one methanation plant and the required methane output profile is received for the predetermined timespan. The predetermined timespan is for example, a plurality of months, one month, a plurality of weeks, one week, a plurality of days, one day, a plurality of hours, one hour, a plurality of minutes or one minute. A combination of the aforementioned timespans is also conceivable. For example, the digital fleet twin receives for a predetermined timespan e.g. of the next week the P28764PC00

[0041] 12 / 35 input variables and determines the control commands for the next week. The next day, new input variables for the next week are received e.g. the same or varying input variables, which may cause the digital fleet twin to update the control commands. For example, the transfer fees for the usage of a portion of the methane grit may have increased. The control commands are e.g. updated every day until the respective day for operation is reached and the respective current control commands are transferred to the methana- tion plants and used for controlling the methanation plants. This updating may be performed for each upcoming timespan until the respective timespan is reached, which triggers the operation of the methanation plants with the respective control commands.

[0042] In a further embodiment, the method further comprises the step of receiving at least one sensor signal, which is indicative of a current operating condition of at least one of the methanation plants and I or which is indicative of a current operating condition or a portion of the methane grit, wherein the control commands are further determined using the at least one sensor signal. Each of the methanation plants comprises preferably a plurality of sensors, which are configured to measure parameters of the different components. E.g. temperature sensors, pressure sensors, flow sensors, gas sensors etc. are provided at the respective positions in the methanation plants or the methane grit. At least one of these sensors provide the respective sensor signal to the digital fleet twin as input variable. E.g. the current temperature of a reactor or the current pressure in an electrolyser or a portion of the methane grit may require that the respective component is controlled deviating from the standard procedure. Further, such sensor signals may determine that one component is fully operable or not. Such information may influence the determination of the control commands by the digital fleet twin, which further increase the efficiency of the operation of the methanation plants. For example, one specific methanation plant may currently not be operational, which is transmitted to the digital fleet twin by a respective sensor signal or manual input signal. The control commands are determined such that the methanation plant is not used until it is operational again. P28764PC00

[0043] 13 / 35

[0044] In an embodiment, determining the control commands comprises that the required methane output profile, the estimated electric energy profile, the expected methane transfer parameters and I or the at least one sensor signal, are processed by the digital fleet twin such that the optimal control commands for the fleet of methanation plants are determined. In other words, the different input variables are used as input variables for the digital fleet twin, which may further use an optimization algorithm in view of the operating boundary conditions, for determining the control commands for the fleet. Determining the optimal control commands is a mathematical optimization problem, which is preferably numerical solved by a preferred optimization algorithm.

[0045] In an embodiment, processing, by the digital fleet twin, comprises that the control commands are determined for each methanation plant of the fleet in that for each individual methane request the optimal at least one methanation plant is determined for producing the required methane, in particular in view of the operating plant boundary conditions, the estimated electric energy profile for each of the methanation plants, the plant location information, the location information of the individual methane requests, the methane grit information, the methane transfer parameters and I or the at least one sensor signal. For example, the digital fleet twin determines for each or at least a plurality of combinations of the possible methanation plants for production and the plurality of individual methane requests the resulting parameters of this combination. E.g. time for production, production possibility rate, cost of production, cost of transfer, etc. The methanation plant further may select the optimal combination or plurality of combinations and determines the respective control commands for the fleet of methanation plants. If required, the control commands may be updated.

[0046] In a further embodiment, the method comprises the step of operating, the fleet of methanation plants using the determined control commands for producing the required methane. The control commands are e.g. transferred to the respective methanation P28764PC00

[0047] 14 / 35 plants, which use the control commands for their operation. The respective methanation plants further may use the digital methanation plant or a digital plant twin of the methanation plant to determine the control commands for their individual components like reactors, electrolysers, heaters etc. such that the desired methane output is produced.

[0048] In a further embodiment, the method further comprises the step of updating the determined control commands, in case at the digital fleet twin, the required methane output profile, the estimated electric energy profile, the at least one sensor signal and / or the expected methane transfer parameters changes. Changing input variables comprise e.g. changing sensor signals, changing estimated electric energy profile and I or changing required methane output profile. Other changing input variables may also require to update the control commands. The control commands are e.g. constantly or after predetermined time intervals updated, in case at least one input variable changed, which requires to update the control commands. The periodical update is e.g. performed each month or each week, preferably, each day, preferably each hour, even more preferably each minute. In case the input variables do not change the methanation plants can be operated, by the control commands, as expected and as determined. This is for example the case, when the estimated electric energy profiles and the required methane output profile do not change and no sensor signal requires any adaptation of the control commands. The operation of the methanation plants can executed, by the control commands, as determined at the beginning. It is of course also possible that the input variables change over time, e.g. the estimated electric energy profiles available may increase or decrease, which determines that more or less electric energy is available to the respective plants. By periodically or constantly updating the control commands it is in particular possible to efficiently control the fleet of methanation plants in case of varying input variables, which further helps to reduce the buffer capacities and increase the overall efficiency. P28764PC00

[0049] 15 / 35

[0050] In a further embodiment, the estimated electric energy profile for one methanation plant is a combination of a plurality of estimated electric energy profiles, which indicate the available electric energy from different power plants, in particular for the predetermined timespan. For example, different electric energy plants are located in the vicinity of the respective methanation plant and are configured to provide electric energy to the methanation plant. One of these plants is e.g. a solar power plant, another one a wind power plant and third one a hydrogen power plant. All of these power plant provide their estimated electric energy profile, which determines the expected available power over time. The digital fleet twin is configured to combine all of the received estimated electric energy profiles together to the combined estimated electric energy profile for the respective methanation plant, which determines the expected available electric energy for the methanation plant. In particular renewable power plants are strongly dependent on weather conditions, combining a plurality of estimated electric energy profiles from different plants helps to increase the reliability and the manageability of deviations from the expected. Further it advantageously helps to reduce buffer capacity.

[0051] It is further preferred that the control commands are determined using boundary conditions, which consider lifespan boundary conditions or efficiency profiles at least of one of the methanation plants. Such boundary conditions may determine that it is more lifespan efficient to operate a specific methanation plant at 80% capacity. The lifespan boundary conditions are in particular no linear curve. Further, also the efficiency profile is not a linear curve but determines at least one or more most efficient operating points for at least one methanation plant or at least component of the methanation plant. The digital fleet twin may be configured to determine the control commands such that as many methanation plants as possible are operated at or as close as possible to their at least one most efficient operating point. The control commands for the electrolysers may comprise a load profile for the next timespan with e.g. second based sampling. P28764PC00

[0052] 16 / 35

[0053] In an embodiment, each of the methanation plants comprises at least one reactor, an electrolyser and I or auxiliary components, which are configured to produce in combination with each other methane using hydrogen and carbon dioxide, wherein these components provides operating boundary conditions to the respective digital methanation plants, which determine the operating efficiency at different operating conditions, and wherein the control commands are further determined using these operating boundary conditions.

[0054] It is further preferred that the control commands are determined using boundary conditions, which consider lifespan boundary conditions and I or efficiency profiles of the components of at least one methanation plant. Such boundary conditions may determine that it is more lifespan efficient to operate the respective methanation plant at 75% capacity. The lifespan boundary conditions are in particular no linear curve. Further, also the efficiency profile is not a linear curve but determines at least one or more most efficient operating points of the respective methanation plant.

[0055] The determination of the control commands of the components of the respective methanation plant may be a sub optimization problem, which is solved by the digital methanation plants in particular using the digital plant twin, further using an calculation algorithm. The calculating algorithm may use numerical methods, in particular for nonlinear optimization. The nonlinear optimization algorithm is e.g. an Interior Point Optimizer (IPOPT). The digital plan twin, in particular at least one processor used by the digital plant twin, uses the calculating algorithm to determine the respective control commands for the at least one component, like a reactor, a heater or an electrolyser.

[0056] By solving all of the sub optimization of the different components of the methanation plants, it is possible to further determine, respective control commands for all components of the methanation plants, such that the methanation plants of the whole fleet are P28764PC00

[0057] 17 / 35 operable as efficient as possible with the available input variables for the fleet and the individual methanation plants of the fleet.

[0058] In an embodiment, the operating plant boundary conditions of the different methanation plants comprise a ramp-up profile of the methanation plant, ramp-down profile of the methanation plant, or a lifetime profile of the methanation plant, wherein the control commands are determined by the digital fleet twin further using at least one of these operating boundary conditions. Conventional methanation plant are designed and developed for a steady state operation. The steady state operation is in view of varying input variables not applicable. It is therefore required to dynamically operate the methanation plant and in particular its components. Dynamically operating in particular includes to control the ramp up and the ramp down of different components e.g. the electrolysers and the reactor, more often compared to a steady state operation. Further, such a dynamic operation may lead to lower lifespans of the different components. This embodiment considers these boundary conditions in order to ensure that the different components and the entire respective methanation plant is operated as efficient as possible in view of varying input variables. In addition, the buffer can be advantageously reduced as much as possible.

[0059] According to a further aspect of the present disclosure, a methanation fleet control unit is specified. The methanation fleet control unis is configured to determine control commands for dynamically operating a fleet of methanation plants, wherein the methanation fleet control device comprises a processor or electric circuit, which is configured to perform the following steps.

[0060] The methanation fleet control unit or device, in particular its processor, is configured to access a digital fleet twin of the fleet of methanation plants, which comprises a plurality of digital methanation plants each representing at least one methanation plant of the P28764PC00

[0061] 18 / 35 fleet. The digital fleet twin further comprises respective operating plant boundary conditions for the plurality of digital methanation plants, which determine the operation of each of the respective methanation plants.

[0062] The methanation fleet control unit, in particular its processor, is configured to receive, the required methane output profile indicative of the required methane output of the fleet of methanation plants.

[0063] The methanation fleet control unit, in particular its processor, is configured to determine control commands for operating the fleet of methanation plants using the digital fleet twin and the required fleet methane output profile.

[0064] In an embodiment, the methanation fleet control unit, in particular its processor, is further configured to determine the control commands for dynamically operating the fleet of methanation plants as described above and hereinafter. Each feature and any respective advantage disclosed and described with respect to the computer implemented method for dynamically operating the fleet of methanation plants is also applicable mutatis mutandis to the above disclosed aspect of the methanation fleet control device. In particular each feature disclosed and described with respect to the computer implemented method may be used to limit the methanation fleet control device and vice versa.

[0065] It is to be understood that both the foregoing general description and the following detailed description present embodiments, and are intended to provide an overview or framework for understanding the nature and character of the disclosure. The accompanying drawings are included to provide a further understanding, and are incorporated into and constitute a part of this specification. The drawings illustrate various embodiments, and together with the description serve to explain the principles and operation of the concepts disclosed. P28764PC00

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[0067] BRIEF DESCRIPTION OF THE DRAWINGS

[0068] The present disclosure will be more fully understood from the detailed description given herein below and the accompanying drawings, which should not be considered limiting to the disclosure described in the appended claims. The drawings are showing: Fig. 1 a schematic view of a methanation of methane and / or methanol using a methanation plant;

[0069] Fig. 2 a schematic representation of the methanation plant of Figure 1 with a detailed representation of the different components;

[0070] Fig. 3 a schematic representations of a control unit of a fleet of methanation plants as shown in the Figures 1 and 2 including the different input variables for determining the control instructions for the fleet of methanation plants;

[0071] Fig. 4 a schematic illustration of a plurality of power plants, which are configured to provide their individual electric energy to one of the methanation plants;

[0072] Fig. 5 a schematic illustration of a plurality of methane customers, which are con- figured to provide their individual methane request to the fleet of methanation plant;

[0073] Fig. 6 shows a flow diagram illustrating schematically a plurality of steps performed by the control unit for dynamically operating the fleet of methanation plants as e.g. illustrated with respect to Figure 3. P28764PC00

[0074] 20 / 35

[0075] DESCRIPTION OF THE EMBODIMENTS

[0076] Reference will now be made in detail to certain embodiments, examples of which are illustrated in the accompanying drawings, in which some, but not all features are shown. Indeed, embodiments disclosed herein may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Whenever possible, like reference numbers will be used to refer to like components or parts.

[0077] Figure 1 shows a schematic view of a methanation of methane and I or methanol using a methanation plant 1. Figure 1 focuses on the fluid and energy input and output, which is required to produce the desired methane and I or methanol. The methanation plant 1 comprises at least one electrolyser 20 and a reactor 25. The electrolyser 10 is configured to produce hydrogen 11 and oxygen 10 using water 5 and electric energy 3, and the reactor 25 is configured to produce methane 8 and I or methanol using the produced hydrogen 6, carbon dioxide 4 and electric energy 3. The electric energy 3, the water 5 and the carbon dioxide 4 are the plant input variables 2. In another embodiment, the hydrogen 6 is not produced by the plant 1 itself, but may be supplied directly to the plant 1. In this case also the hydrogen 6 would be a plant input variable 2. The methanation plant 1 is configured to perform the electrolysis of water 5 using one or more electrolysers 20 to disperse water 5 into hydrogen 6 and oxygen 10. At least the hydrogen 6 is further used in the reactor 25 of the methanation plant 1. The reactor 25 is configured to produce methane 8 and I or methanol using the produced hydrogen 6, supplied carbon dioxide 4 and electric energy 3. A side product of the reactor 25 is waste water 9. The waste water 9 may be reused as input water 5 for the methanation plant 1. A further side product of the at least one electrolysers 20 is the oxygen 20. The methane 8 and I or methanol, the waste water 9 and the oxygen 10 are output variables 7 of the methanation plant 1. P28764PC00

[0078] 21 / 35

[0079] Figure 1 shows the methanation plant 1 in a super simplified manner, nevertheless, the most relevant input variables 2 and the resulting output variables 7 are shown in Figure 1.

[0080] Figure 2 shows the methanation plant 1 schematically in a more detailed manner. The methanation plant 1 comprises six electrolysers 20, which are configured to produce the required hydrogen 6. Each of the electrolysers 20 is supplied with electric energy 3 and water 5. The water 5 may be waste water 9 from the plant 1 itself or fresh water or mixture thereof. The methanation plant 1 further comprises according to this embodiment a CO2 tank 21 , which is configured to provide carbon dioxide 4 to the methanation plant 1. In another embodiment the methanation plant 1 may have access to carbon dioxide 4 via respective carbon dioxide grit or a CO2 tank 21 outside of the methanation plant 1. The carbon dioxide 4 used is preferably biogenic carbon dioxide 4. In another embodiment, the methanation plant 1 may produce its own carbon dioxide 4. The methanation plant 1 further comprises a gas mixer 22, which is configured to collect and mix the hydrogen 6 produced from the electrolysers 20 and the carbon dioxide 4 from the CO2 tank 21. In other words, the gas mixer 22 forms the desired gas composition using at least the hydrogen 6 and the carbon dioxide 4. The methanation plant 1 further comprises a compressor 23, which is configured to set the gas pressure of the hydrogen and carbon dioxide mixture as desired. The compressor 23 is supplied with electric energy 3 for its operation. The methanation plant 1 further comprises a heater 24, which is configured to set the gas mixture temperature as desired e.g. by heating or by cooling of the gas mixture. The compressor 23 and the heater 24 are configured to set the properties of the gas mixture such as desired for the methanation. The methanation plant 1 further comprises two reactors 25 arranged in series, which is configured to receive the gas mixture and to synthesize methane 8 out of the supplied carbon dioxide 4 and hydrogen 6. In other variations, only one or a plurality of reactors 25 may be used, which are arranged P28764PC00

[0081] 22 / 35 parallel or in series with each other. Using a plurality of reactors 25 in series may increase the product yield.

[0082] The synthesis of methane 8 (methanation) from CO2 (as well as CO) is a strongly exothermic reaction that requires efficient heat removal from the reaction zone, particularly when carried out catalytically with short reaction times. Conventionally, random fixed- bed reactors are used. Catalyst pellets may be arranged randomly unstructured and may move freely. An alternative to the random fixed-bed reactors are structured fixed-bed reactors with a plurality of channels, which comprise a catalyst coating. These reactors comprise a solid body structure, which define the channels. The reactants stream through the channels and react in the channels with the catalyst coating. The reaction zone is therefore within the channels. For example, the document DE 10 2016 125 641 A1 discloses a process for production of a natural gas substitute from hydrogen-contain- ing gas mixtures using a reactor with channels.

[0083] The methanation plant 1 further comprises a coolant circuit 26 for controlling of the temperature inside the at least one reactor 25, in the embodiment of figure 2 of the upstream arranged reactor 25, which is important for ensuring a high quality and high purity product and for ensuring high yields of target product. The coolant circuit 26 comprises a coolant heater 27 and a coolant pump 28. The coolant heater 27 is configured to set the temperature of the coolant and the coolant pump 28 is configured to set the flow rate of the coolant. The coolant used are e.g. coolant oils, water etc. The coolant circuit 26, in particular its components are supplied with electric energy 3 for the desired operation.

[0084] The methanation plant 1 further comprises a water separator 29 arranged downstream of the reactor 25 which is configured to separate the water 9 out of the product gas of the reactor 25. The separated waste water 9 may be reused by the methanation plant 1 P28764PC00

[0085] 23 / 35 itself. The water separator 29 may also be supplied with electric energy 3 for its operation. The methanation plant 1 further may comprise additional post processing components 30 like heaters filters etc. These components may also need electric energy 3 for their operation. The methanation plant 1 additionally comprises downstream of the separator 29 a compressor 31 , which is configured to set the pressure of the resulting methane 8 or green natural gas. The compressor 31 may additionally require for its operation electric energy 3. The resulting green natural gas 8 is supplied with the desired high purity quality and pressure to a methane grit 32 or natural gas grit 32, which is configured to transport the methane 8 to customers. In other embodiments, the produced methane 8 may be directly supplied to a customer.

[0086] Figure 2 further indicates a plant control unit 40, which is configured to control the methanation plant 1 , in particular all of the described components such that the components work together as desired for producing the methane 8 using the available input variables 2. Figure 2 further shows a sensor 33, which is configured to provide a sensor signal 34 to the plant control unit 40 indicative of a parameter of a component of the methanation plant 1. A plurality of sensors 33 are also conceivable.

[0087] Figure 3 shows schematically the operation of a fleet 40 of methanation plants 1. The fleet 40 comprises a plurality of methanation plants 1 as described e.g. with respect to Figure 1 and 2. Figure 3 shows a fleet control unit 41 , which is configured to determine control commands 43 for the fleet of methanation plants 1 for dynamically operating them. The control unit 41 is for example a specific control unit at one location or may be a combination of a plurality of control units arranged at different locations. The control unit 41 may be or may access a server structure, in particular a cloud server structure. The control unit 41 may comprise a processor 42 or an electric circuit, which is configured to determine the control commands 43. The control unit 41 may access or use a fleet digital twin 50 for the determination of the control commands 43. The fleet digital twin 50 P28764PC00

[0088] 24 / 35 is a digital representation of the real methanation plants 1 , which form the fleet 40. The fleet digital twin 50 further comprises respective operating plant boundary conditions 51 for the plurality of digital methanation plants 1 , which determine the operation of each of the respective methanation plants 1. The control unit 41 is further configured to receive a required methane output profile 60 from at least one methane customer 61. The required methane output profile 60 is indicative of the required methane output of the fleet 40 of the methanation plants 1 in particular for a given timespan t. The control unit 41 may further be configured to receive an estimated electric energy profile 62 for at least one at least one of the methanation plants 1 indicative of the expected available electric energy to the respective methanation plant 1 . The control unit 41 is further configured to receive methane transfer parameters 64 for at least a plurality of different portions 35 of the methane grit 32, which are indicative of at least one parameter for transferring methane 8 through the respective portion 35 of the methane grit 32. The control unit 41 is configured to determine the control commands for dynamically operating the fleet 40 of methanation plants 1 by using the digital plant twin 50 and the received data I information.

[0089] Figure 4 shows a schematic representation of the control unit 41 of Figure 3 in a more detailed manner. In particular the digital fleet twin 50 is illustrated more detailed. Figure 4 shows the fleet control unit 41 comprising the processor 42, which accesses the fleet digital twin 50 for determining the control commands 43 for the plurality of methanation plants 1 of the fleet 40. Figure 4 shows that a plurality of methane customers 61 provide individual methane requests 65 to the control unit 41 . The control unit 41 may be configured to combine the individual methane requests 65 to the required methane output profile 60. Figure 4 also shows a plurality of power plants 63, which provide individual estimated electric energy profiles 62 to the control unit 41. The individual estimated electric energy profiles 62 may be available for one or a plurality of methanation plants 1. The control unit 41 may determine where the electric energy is used in the fleet 40 in order P28764PC00

[0090] 25 / 35 to meet the methane customer demand. In another embodiment, the received estimated electric energy profiles 62 may only be available to a specific methanation plant 1.

[0091] The digital fleet twin 50 used to determine the control commands 43 is a digital representation of the fleet 40 of the methanation plants 1 comprising the respective plant boundary conditions 51 and of the methane grit 32. The digital fleet twin 50 also comprises a digital methane grit 53, which is a digital representation of the real methane grit 32 connecting the methanation plants 1 with the customers 61. Similarly, the digital fleet twin 50 shows geographical target locations 55 where to the required methane 8 is to be delivered. The geographical target location 55 may be received with the individual methane request. The digital methane grit 53, in particular at least one portion of the digital methane grit 54 comprises the individual methane transfer parameters 64, which determine the parameters for transferring methane 8 through the grit and I or the respective portion. Received methane transfer parameters 64 may update the digital fleet twin 50 accordingly. The digital fleet twin 50 may also comprises plant location information 56 indicative of the geographical location of the methanation plants 1. The digital fleet twin 50 may also comprise the methane grit information 57, which determine e.g. that a specific target location 55 is not reachable from a specific methanation plant 1 because they are not linked together. The control unit 41 may further receive the sensor signal 34 from one or a plurality of the methanation plants 1 , which is indicative of a current operating condition of at least one of the methanation plants 1 and I or which is indicative of a current operating condition of at least a portion of the methane grit 35. By using all of the available information, the control unit 41 determines the control commands 43 for at least one of the methanation plants 1 of the fleet 40.

[0092] Figure 5 shows of individual methane requests 65 from a plurality of methane customers 61. The individual methane requests 65 indicate the methane demand over time t. The P28764PC00

[0093] 26 / 35 individual methane request 65 may also comprise geographical target location information 55, which determine at what location the methane needs to be delivered via the methane grit 32. Figure 5 further shows that the individual methane requests 65 are provided to the fleet control unit 41 , which determines the control commands 43 using the requests 65. The control commands 43 may comprise for each of the methanation plants 1 a target methane output 44, in particular in view of the expected estimated electric energy profile 65 for the individual methanation plants 1. In other words, the control unit 41 determines in view of the expected estimated electric energy profile 65 for the individual methanation plants 1 , in view of the required methane output profile 60 and the further input signals described in particular above, the target methane output 44 for each of the individual methanation plants 45. The individual methanation plant 1 than may determine their individual control commands for the different components to produce the target methane output 44. In another embodiment, the control unit 41 may already determine the control commands for the different components of the different methanation plants 1.

[0094] Figure 6 shows a plurality of power plants 63, which are configured to provide electric energy 3 to at least one or a plurality of the methanation plants 1 of the fleet 40. The control unit 41 is configured to receive from the plants 63 an estimated electric energy profile 62, which determines the expected electric power P over time t deliverable to the fleet 40 of the methanation plants 1. In another embodiment, the control unit 41 may receive power plant information, like weather data, or may access weather models, and determines the estimated electric energy profile 62 by itself. Further, the control unit 41 is in this embodiment configured to determine for each of the methanation plants 1 the plant available electric energy 66 or may also determine for each of the methanation plants 1 the plant available electric energy 66 such that the respective methane demand is met. In other words, the control unit 41 may determine what plant 1 may use the avail- P28764PC00

[0095] 27 / 35 able electric energy by using the received or determined estimated electric energy profiles 62. This may form part of the control commands 43 determined by the control unit 41.

[0096] Figure 7 shows a flow diagram illustrating schematically a plurality of steps performed by the control unit 41 for dynamically operating the fleet 40 of the methanation plant 1 as illustrated e.g. with respect to Figure 4. In the following paragraphs, described with reference to Figure 7 is a possible sequence of steps, performed by the control unit 41 for dynamically operating the fleet 40 of the methanation plants 1.

[0097] In step SO, the control unit 41 accesses the digital fleet twin 50 of the fleet 40 of the methanation plants 1. The digital fleet twin 50 comprises the plurality of digital methanation plants 52 each representing at least one methanation plant 1 . The digital fleet twin 50 further comprises operating plant boundary conditions 51 of these methanation plants 51 , which determine the operation of the respective methanation plants 1. The digital fleet twin 50 is for example stored and maintained directly in the control unit 41. In another embodiment, the digital fleet twin 50 is stored and maintained on a server, preferably a cloud server, which is accessed by the control unit 41. In another embodiment, the control unit 41 may be implemented in a (cloud) server, which is accessed via a user interface.

[0098] In step S1 , the control unit 41 , receives a required methane output profile 60 indicative of the required methane output of the fleet 40 of the methanation plants 1.

[0099] In step S2, the control unit 41 , receives an estimated electric energy profile 62 indicative of the expected available electric energy to at least one of the methanation plants 1.

[0100] In step S3, the control unit 41 , receives methane transfer parameters 64 for at least a plurality of different portions of the methane grit 35, which are indicative of at least one P28764PC00

[0101] 28 / 35 parameter for transferring methane 8 through the respective portion 35 of the methane grit 32.

[0102] In step S4, the control unit 41 , receives at least one sensor signal 34, which is indicative of a current operating condition of at least one of the methanation plants 1 and I or which is indicative of a current operating condition of a portion 35 of the methane grit 32.

[0103] In step S5, the control unit 41 , determines the control commands 43 for dynamically operating the fleet 40 of the methanation plants 1 by using the digital fleet twin 50, the estimated electric energy profile 62 and the required methane output profile 60, the methane transfer parameters 64 and I or the sensor signals 34. In step S6, the control unit 41 , operates the fleet 40 of the methanation plants 1 by using the determined control commands 43. E.g. the control commands 43 are transmitted to the respective plants 1 , which control the respective components accordingly.

[0104] In step S7, the control unit 41 , updates the control commands 43 in case at least one of the input variables change. The expected electric energy profile 62 may chance due to changing weather conditions or the required methane output profile 60 may change because a customer 61 may increases or reduces its individual methane request 65. The other variables may also change.

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[0107] LIST OF DESIGNATIONS

[0108] 1 Methanation Plant 43 control commands

[0109] 2 Plant Input variables 44 target methane output

[0110] 3 Electric energy 50 Digital fleet twin

[0111] 4 Carbon dioxide 51 plant boundary conditions

[0112] 5 Water 35 52 digital methanation plants

[0113] 6 Hydrogen (H2) 53 digital methane grit

[0114] 7 Plant output variables 54 digital methane grit portion

[0115] 8 Methane CH4 55 geographical target location

[0116] 9 waste water 56 plant location information

[0117] 10 Oxygen 40 57 methane grit information

[0118] 20 Electrolyser

[0119] 60 required methane output profile

[0120] 21 CO2 Tank

[0121] 61 CH4 customer

[0122] 22 Gas mixer

[0123] 62 estimated electric energy profile

[0124] 23 Compressor

[0125] 63 power plant

[0126] 24 Heater

[0127] 45 64 methane transfer parameters

[0128] 25 Reactor

[0129] 26 Coolant circuit 65 individual methane requests

[0130] 27 Coolant heater 66 plant available electric energy

[0131] 28 Coolant pump t timespan

[0132] 29 H2O Separator P electric energy

[0133] 30 Post processing (heater etc.) 50 SO Providing / Accessing

[0134] 31 Compressor 51 Receiving Methane output profile

[0135] 32 Methane grit 52 Receiving electric energy profile

[0136] 33 Sensor 53 Receiving transfer parameter

[0137] 34 Sensor signal 54 Receiving Sensor signal

[0138] 35 methane grit portion 55 S5 Determining

[0139] 40 Fleet of methanation plants 56 Operating

[0140] 41 Fleet control unit 57 Updating

[0141] 42 Processor

Claims

P28764PC0030 / 35PATENT CLAIMS1. A computer implemented method for dynamically operating a fleet (40) of methana- tion plants (1) for producing methane (8) and I or methanol, the method comprising the steps of: a. Providing (SO) a digital fleet twin (50) of the fleet (40) of methanation plants (1) comprising: i. a plurality of digital methanation plants (52) each representing at least one of the methanation plants (1) of the fleet (40); ii. respective operating plant boundary conditions (51) for the plurality of digital methanation plants (52), which determine the operation of each of the respective methanation plants (1); b. Receiving (S1) the required methane output profile (60) indicative of the required methane output of the fleet (40) of the methanation plants (1); c. Determining (S5) control commands (43) for operating the fleet (40) of the methanation plants (1) using the digital fleet twin (50) and the required methane output profile (60).

2. The computer-implemented method according to claim 1 , further comprising the step of receiving (S2) an estimated electric energy profile (62) for at least one of the methanation plants (1) indicative of the expected available electric energy to at least one of the methanation plants (1), wherein the control commands (43) are determined (S5) further using the received estimated electric energy profile (62).P28764PC0031 / 353. The computer-implemented method according to claim 2, wherein the estimated electric energy profile (62) comprises an estimated renewable electric energy profile, which determines the expected available renewable electric energy.

4. The computer-implemented method according to any one of the preceding claims, wherein receiving the required methane output profile (60) comprises to receive a plurality of customer individual methane requests (65), and wherein the control commands (43) are determined (S5) using the customer individual methane requests (65).

5. The computer implemented method according to claim 4, wherein the customer individual methane requests (65) comprise location information, which determine a geographical target location (55) where the methane (8) is to be delivered, and wherein the control commands (43) are determined (S5) using the geographical target location (55).

6. The computer implemented method according to any one of the preceding claims, wherein the digital fleet twin (50) of the fleet (40) of methanation plants (1) further comprises for each of the methanation plants (1) plant location information (56) indicative of the geographical location of the methanation plants (1), and wherein the control commands (43) are determined (S5) further using the plant location information (56).

7. The computer implemented method according to any one of the preceding claims, wherein the digital fleet twin (50) of the fleet (40) of methanation plants (1) further comprises methane grit information (57) of a methane grit (32), which is configured to receive the methane (8) produced by the methanation plants (1) of the fleet (40) and to deliver the received methane (8) to a target location, and wherein the controlP28764PC0032 / 35 commands (43) are determined (S5) further using the methane grit information (57).

8. The computer implemented method according to claim 7, wherein the method further comprises the step of receiving (S3) methane transfer parameters (64) for at least a plurality of different portions (35) of the methane grit (32), which are indicative of at least one parameter for transferring methane (8) through the respective portion (35) of the methane grit (32), and wherein the control commands (43) are further determined using the expected methane transfer parameters (64).

9. The computer implemented method according to any one of the preceding claims, wherein the method further comprises the step of receiving at least one sensor signal (34), which is indicative of a current operating condition of at least one of the methanation plants (1) and I or which is indicative of a current operating condition of a portion (35) of the methane grit (32), wherein the control commands (43) are further determined (S5) using the at least one sensor signal (43).

10. The computer implemented method according to any one of the preceding claims, wherein the at least one of: the required methane output profile (60), the estimated electric energy profile (62), the at least one sensor signal (34) or the expected methane transfer parameters (64) are received for a predetermined timespan (t) and the control commands (43) are preferably determined (S5) for the predetermined timespan (t) of for another predetermined timespan.11 . The computer implemented method according to any one of the preceding claims, wherein determining (S5) the control commands (43) comprises that at least one of the required methane output profile (60), the estimated electric energy profile (62), the expected methane transfer parameters (64) or the at least one sensorP28764PC0033 / 35 signal (34), are processed by the digital fleet twin (50) such that the optimal control commands (43) for the fleet (40) of methanation plants (1) are determined based on a requirement to be minimized.

12. The computer implemented method according to claim 11 , wherein processing, by the digital fleet twin (50), comprises that the control commands (43) are determined for each methanation plant (1) of the fleet (40) in that for each individual methane request (65) the optimal at least one methanation plant (1) is determined for producing the required methane (8) in view of at least one of: the operating plant boundary conditions (51), the estimated electric energy profile (65) for each of the methanation plants (1), the plant location information (56), the location information of the individual methane requests (65), the methane grit information (57), the methane transfer parameters (64) or the at least one sensor signal (43).

13. The computer implemented method according to any one of the preceding claims, wherein the computer-implemented method further comprises the step of operating (S6), the fleet (40) of methanation plants (1) using the determined control commands (43) for producing the required methane (8).

14. The computer implemented method according to any one of the preceding claims, wherein the computer-implemented method further comprises the step of updating (S7) the determined control commands (43), in case at least one of: the digital fleet twin (50), the required methane output profile (60), the estimated electric energy profile (62), the sensor signal (43) or the expected methane transfer parameters (64) changes.

15. A methanation fleet control unit (41), which is configured to determine control commands (43) for dynamically operating a fleet (40) of methanation plants (1),P28764PC0034 / 35 wherein the methanation plant control unit (41) comprises a processor (42), which is configured to: a. Access (SO) a digital fleet twin (50) of the fleet (40) of methanation plants (1) comprising: i. a plurality of digital methanation plants (52) each representing at least one of the methanation plants (1) of the fleet (40); ii. respective operating plant boundary conditions (51) for the plurality of the digital methanation plants (52), which determine the operation of each of the respective methanation plants (1); b. Receiving (S1), the required methane output profile (60) indicative of the required methane output of the fleet (40) of the methanation plants (1); c. Determining (S2) control commands (43) for operating the fleet (40) of the methanation plants (1) using the digital fleet twin (50) and the required fleet methane output profile (60).

16. The methanation fleet control unit (41) according to claim 15, wherein the methanation fleet control unit (41), in particular its processor (52), is further configured to determine the control commands (43) for dynamically operating the fleet (40) of the methanation plants (1) by performing the steps of the computer-implemented method of any one of the claims 1 to 14.

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

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