Method and system for providing a catalyst composition

Abstract

The invention relates to a computer-implemented method for generating and / or providing a target catalyst composition to be used in a production plant, the method comprising the steps of: - providing a digital representation associated with the production plant, one or more target plant performance(s) of the production plant and a starting catalyst composition; - determining a target catalyst composition by optimizing the starting catalyst composition with respect to the one or more target plant performance(s) using the digital representation associated with the production plant; and - generating and / or providing the target catalyst composition for use in the production plant.

Description

[0001] Method and system for providing a catalyst composition

[0002] TECHNICAL FIELD

[0003] The invention relates to a method for providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant and a method for providing a target catalyst composition to be used in a production plant. The invention further relates to a system for generating and / or providing a catalyst performance indicator or a target catalyst composition and to a computer element with instructions for determining catalyst performance indicator or a target catalyst composition. The methods and systems disclosed herein may be employed as part of industrial production, in particular, in chemical industry.

[0004] BACKGROUND OF THE INVENTION

[0005] Catalysts are widely used in industrial production. For instance, in refineries crude oil is converted into value products by catalytic cracking. Catalytic cracking, and particularly fluid catalytic cracking (FCC), is routinely used to convert heavy hydrocarbon feedstocks to lighter products, such as gasoline. FCC units comprise a reactor and a regenerator to circulate FCC catalyst. In a first step, preheated feedstock is injected into the catalyst riser of the reactor, where it is vaporized and cracked into smaller molecules of vapour by contact and mixing with the catalyst. Since the cracking reactions produce catalytic coke, which very quickly reduces the catalyst reactivity, the catalyst is fed to the regenerator in a second step, where it is regenerated by burning off the deposited coke. The regenerated catalyst is then fed to the reactor.

[0006] The catalysts used in FCC processing have been tailored to maximize the performance in specific conversion processes. For instance, FCC catalysts may be based on four major components: crystalline zeolite, matrix, binder, and filler. Such catalysts compositions may be tailored to different performance criteria, e.g., by using promoters for fluidization or certain products to accommodate the needs of a specific production plant. To date such tailoring of FCC catalysts has been done with respect to the general conversion processes and the plant specific needs provided by plant operators.

[0007] It would therefore be desirable if it were possible to more efficiently tailor catalysts to specific needs or requirements associated with a certain catalytic process or a certain production plant.

[0008] SUMMARY OF THE INVENTION

[0009] The present invention is based in the objective of providing methods and systems that enable an efficient and reliable way of providing a tailored catalyst composition for a catalytic reactor in a production plant.

[0010] According to the invention, a computer-implemented method for generating and / or providing a target catalyst composition to be used in a production plant is proposed. The method comprises the steps of:

[0011] - providing a digital representation associated with the production plant, one or more target plant performance(s) of the production plant and a starting catalyst composition;

[0012] - determining a target catalyst composition by optimizing the starting catalyst composition with respect to the one or more target plant performance(s) using the digital representation associated with the production plant; and

[0013] - generating and / or providing the target catalyst composition for use in the production plant.

[0014] The invention includes the recognition that a performance decrease of a production plant may generally be counteracted by either exchanging the catalyst completely, or partially, with either a fresh catalyst of the same recipe, a catalyst with an adapted recipe, or a regenerated catalyst. Other conditions, which may lead to an adaption, or a change of the catalyst recipe, or, a full, or partial exchange of the catalyst, may be, but are not limited to, a change in the chemical composition of a feed of the reactor (e.g., crude oil), or the plan to have a different product chemical composition of the reactor. It may thus be beneficial to know whether a catalyst composition is actually yielding the desired performance of a production plant, i.e., whether a catalyst composition used or to-be-used is actually the target catalyst composition. It is thus considered beneficial to start with one or more target plant performance(s) and a starting catalyst composition and to tailor the starting catalyst composition to achieve the one or more target plant performance(s). To this end, an optimization of the starting catalyst composition with respect to the one or more target plant performance^) is suggested. The optimization shall make use of the digital representation associated with the production plant.

[0015] Accordingly, by optimizing the starting catalyst composition with respect to one or more target plant performance(s), the catalyst composition can be tailored to the needs of specific production plants. This way plant performances may be enhanced, reliable operations may be ensured and the risk of performance losses may be reduced. The method for providing a target catalyst composition to be used in a production plant, thus, allows an operator of a production plant to determine the effect of the catalyst on the reactor or plant performance before the catalyst is ever placed inside of the reactor with a given feed. For catalysts, this is particularly advantageous, since catalysts have a detrimental impact on the plant performance.

[0016] Preferably, the optimization includes determining for one or more catalyst composition(s) a catalyst performance indicator. By means of the catalyst performance indicator(s), it is possible to compare different catalyst compositions and to evaluate and assess their expected impact on the performance of the production plant prior or during operation of that production plant.

[0017] In the method it is preferred that for each catalyst component of the catalyst composition a catalyst component specific indicator is provided, that relates to a property or properties of the catalyst component, and the catalyst performance indicator is determined based on the provided catalyst component specific indicator(s).

[0018] Preferably, the determining of the catalyst performance indicator includes:

[0019] - providing a catalyst composition indicative of one or more catalyst component(s) of the catalyst composition,

[0020] - providing one or more catalyst component specific indicator(s) relating to a property of the one or more catalyst components), - determining the catalyst performance indicator based on the provided catalyst component specific indicator(s) and the provided catalyst composition, and

[0021] - providing the catalyst performance indicator associated with the performance of the catalyst used or to be used in a production plant.

[0022] The present invention includes the further recognition that catalysts deactivate over time and replacements has to be done in regular intervals, which can range from multiple daily refilling of a fraction to yearly refilling of the full catalyst. Catalyst exchanges, additions or adaptations of existing catalyst recipes are hence crucial for improvement or maintenance of future plant performance. If the catalyst composition is not chosen appropriately, the production plant may not run effectively and the performance may be reduced.

[0023] With the method for providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant, it is possible to improve the performance of a production plant. For example, with the method or providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant it is possible to more accurately determine when it is time to refill or exchange a catalyst. Moreover, with the method or providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant it is possible to evaluate or assess the performance of a catalyst used or to be used prior and during operation of the production plant.

[0024] In particular, the catalyst performance indicator may be indicative of a performance or a to- be-expected performance of the catalysts used or to be used in the production plant. By providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant, it is thus possible to assess or evaluate a current performance or a to- be-expected performance of a catalyst used or to be used in the production plant. Thereby, it is possible to assess or evaluate whether a currently used catalyst or a to-be-used catalyst is conform with one or more performance targets of the production plant. It is a particular advantage of the method for providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant that the performance of the used or to be used catalyst can be assessed or evaluated prior to an actual exchange of the catalyst during operation. It is thus possible to exchange the catalyst only when it is actually required based on the provided catalyst performance indicator. Accordingly, a catalyst may be used as long as a sufficient performance is indicated by the catalyst performance indicator. Only, when the performance of the catalyst as indicted by the catalyst performance indicator drops below a predefined threshold value, the catalyst may actually be exchanged. Thereby, the performance of a production plant may be improved and unnecessary downtime may be avoided.

[0025] In addition, by providing a catalyst performance indicator associated with a catalyst used or to be used in a production plant, it is possible to assess or evaluate a to-be-expected performance of a catalyst even before the filling in a reactor. It can thus be avoided to start using a catalyst and to find out during operation that the composition of the catalyst needs to be adapted to achieve a target performance of the production reactor. By means of providing a catalyst performance indicator, it is thus possible to assess or evaluate in advance whether a certain catalyst is actually suitable for achieving a predefined target performance of a production plant.

[0026] Providing a component-based catalyst performance indicator thus allows for providing more specific and tailored catalysts to production plants. In particular, known methods to characterize the performance of production plants may be employed and extended by the component-based catalyst performance indicators.

[0027] It is further preferred that the catalyst component specific indicator is derived from reference measurements associated with each catalyst component. The catalyst component specific indicator may be directly or indirectly derived from reference measurements. For instance, the catalyst component specific indicator may be determined for different catalyst compositions and a relation may be derived by correlating the catalyst component specific indicator with one or more catalyst components of the catalyst composition. From such relation, the catalyst component specific indicator may be determined based on one or more catalyst components of the catalyst composition.

[0028] Preferably, the catalyst component specific indicator is associated with a chemical, a physical, a kinetic, a structural and / or a mechanical property of the catalyst component. The chemical, physical, structural and / or mechanical property may be derived directly or indirectly from reference measurements. For instance, the chemical, physical, structural and / or mechanical property may be determined for different catalyst compositions and a relation may be derived correlating the chemical, physical, kinetic, structural and / or mechanical property with one or more catalyst components of the catalyst composition. From such relation the chemical, physical, structural and / or mechanical property may be determined based on the one or more catalyst components of the catalyst composition. It is further preferred that the catalyst component specific indicator is related to one or more of the following catalyst performance indicators: selectivity, activity, stability, yield, surface area, metal content, metal tolerance, attrition resistance, hydrothermal stability, coke selectivity, accessibility or fluidization.

[0029] Preferably, the catalyst performance indicator is determined based on a chemical, kinetic, structural, physical and / or mechanical rule relating to a fraction of the catalyst components. The rule may be a weighted component rule, such as a weighted component mass fraction or activity fraction. An example of a chemical rule may be a relation based on mass fraction, activity fraction, selectivity fraction for desired product(s), yield fraction for desired reaction product(s). An example of a physical or mechanical rule may be a mechanical resistance fraction or a hydrothermal stability fraction. An example for a structural rule may be an accessibility fraction. Other rules and any combination of such rules may be possible.

[0030] Preferably, the plant performance is related to one or more of the following indicators: reaction product output, in particular reaction product output composition, plant resource usage or plant maintenance intervals. In particular, the plant performance of a production plant may refer to a fluid catalytic reactor performance of a fluid catalytic reactor of the production plant. The plant performance may be determined using one or more kinetic models of the production plant or parts therefor, e.g., including one or more catalytic reactors. Reaction product output may relate to the desired reaction produces) to be produced by the catalytic reactor. Reaction product output composition may relate to the relative fraction of desired reaction product(s) to be produced by the catalytic reactor. Plant resource usage may relate to the energy or catalyst consumption of the production plant. Plant maintenance intervals may relate to the time between maintenance intervals that require a shut-down of the plant. The plant performance may relate to one or any combination of such indicators. In case of a combination of indicators, the plant performance may include a relation between such indicators.

[0031] Preferably, the optimization for determining the target catalyst composition is based on multiple catalyst components and one or more plant performance(s). For example, the optimization for determining the target catalyst composition may include constraints relating to the catalyst composition and / or the digital representation of the production plant. In particular, the plant performance(s) may relate to an output of the production plant, in particular a product output composition or a product output composition in relation to a feedstock, a reactor performance, one or more operating condition(s) of the production plant, one or more environmental condition(s) of the production plant, one or more feedstock(s) of the production plant, a resource usage of the production plant, and / or plant maintenance intervals.

[0032] Preferably, determining the target catalyst composition with respect to the provided target performance(s) by optimization includes an optimization routine determining the target catalyst composition based on an objective function reaching a target objective. The objective function may relate to the plant performance and the target objective may relate to the target plant performance^) and / or maximizing profitability.

[0033] Preferably, the target catalyst composition fulfilling the target objective or target plant performance^) is determined based on different optimization routines and the resulting target catalyst compositions as determined via different optimization routines are provided. For instance, a local optimization method, a global optimization method and / or a statistical meth-od may be used for optimization. A global target composition, a statistical target composition and / or a local target composition may then be provided. Deviations between the target catalyst compositions generated via different methods may be determined. This way the target catalyst composition may be determined and compared for different optimization methods. Depending on the deviations between the target catalyst compositions generated via different methods a confidence level may be generated, provided, e.g. displayed to a user. One target catalyst composition may be selected. Such selection may be based on prioritizing one target objective or by a metric correlating the target composition to an economic risk. This way more than one feasible target catalyst composition may be generated. The selection of one target catalyst composition may be done by a user or based on further criteria.

[0034] The objective function used in a method disclosed herein may be related to target plant performance(s), which may relate to targets on an output of the production plant, in particular a product output composition, a catalyst performance, one or more operating parameters) of the production plant, a resource usage of the production plant, or plant maintenance intervals. The objective function may relate to the reaction product output, reaction product output composition, catalyst performance, reactor performance, one or more operating parameter(s) of the production plant, plant resource usage, plant maintenance intervals and or any combination thereof. The objective function may include multiple objectives. The target objective may relate to maximizing or minimizing the objective function or the objective function reaching a predefined value. The optimization may be constrained or unconstrained based on physical and / or chemical constraints for the catalyst, the catalytic reactor, or the production plant. The invention also relates to a method for manufacturing a catalyst by using the target catalyst composition as generated and / or provided according to any of the methods described herein.

[0035] The invention furthermore relates to a method for using a catalyst in a catalytic reactor, wherein the catalyst is manufactured based on the target catalyst composition as provided according to any of methods described herein.

[0036] The invention also relates to a method for using a catalyst performance indicator associated with a catalyst composition as generated and / or provided according to any of methods described herein to generate based on the catalyst performance indicator a plant performance and / or an operating parameter for a production plant.

[0037] The invention also relates to a method for using the target catalyst composition, as generated and / or provided according to any of the methods described herein, for operating a production plant, in particular, a fluid cracking catalyst unit.

[0038] The invention also relates to a computer element with instructions for determining catalyst performance indicator or a target catalyst composition, which when executed on one or more computing device(s) carry out any of the methods described herein.

[0039] Moreover, the invention relates to a system for generating and / or providing a catalyst performance indicator or a target catalyst composition, the system comprising one or more computing device(s) including instructions, which when executed on the one or more computing device(s) execute the steps of any of the methods described herein.

[0040] In summary, the methods, systems and computer elements disclosed herein provide an efficient and more reliable way for operating plants including a catalytic reactor. Furthermore, with the methods, systems and computer programs described herein operators are provided with a catalyst composition that safeguards plant performance and is conform with the performance targets of the production plant before the actual catalyst exchange occurs. With the methods, systems and computer programs described herein operators are provided with a catalyst composition that safeguards plant performance and is conform with the performance targets of the production plant before the actual catalyst exchange occurs.

[0041] Explanations of terms used herein: A catalyst performance indicator as disclosed herein may be construed broadly and may refer to a chemical, physical, mechanical and / or structural property associated with the catalyst. Such properties may include properties that effect the performance of catalysts used or to be used in the production plant. Examples include activity, yield, selectivity, attrition resistance, hydrothermal stability, metals tolerance, coke selectivity, fluidizability of the catalyst.

[0042] A catalyst component may be construed broadly and may refer to the components of the catalyst used or to be used in the production plant or the catalytic reactor of the production plant. The catalyst component may refer to a chemical component of the catalyst material used or to be used in the production plant or the catalytic reactor of the production plant. In particular, the catalyst components may refer to components making up a fluid cracking catalyst. For fluid cracking, the catalyst component(s) may include crystalline zeolite(s), matrix material(s), binder(s), or additive(s). For fluid cracking catalysts the catalyst components may particularly include, but are not limited to:

[0043] - one or more porous, e.g., macroporous or nanoporous, zeolite(s) such as zeolite X, REX, zeolite Y, ultrastable Y (USY), rare earth exchanged Y (REY), rare earth exchanged USY (REUSY), dealumi-nated Y (DeAl Y), superhydrophobic Y (UHPY) and / or dealuminated silica-rich zeolites such as LZ-210. ZSM-20, zeolite L and naturally occurring zeolites such as octahedral zeolite, mordenite and the like may also be used;

[0044] - one or more microporous zeolite(s) such as the ZSM family of zeolites such as ZSM-5 (as described for instance in U.S. Patent No. 3,702,886 or U.S. Patent No. 3,758,403, the disclosure of which is incorporated herein by reference), or 10-MR zeolites, or MCM-22 zeolites;

[0045] - one or more matrix material(s) such as clays forming the matrix derived from e.g. kaolin or attapulgite sources such as kaolinite and attapulgite, amorphous alumina or silica clays, or amorphous alumina or silica;

[0046] - one or more binder(s) or fillers) such as silica, silica-alumina, alumina, clay or other known inorganic binders;

[0047] - one or more additive(s) such as beta zeolite, phosphorus, boron and / or transition metals (as described for instance in U.S. Patent No. 5,279,726, U.S. Patent No. 5,279,726, CN1103105A or EP-2-075-068A1 , the disclosure of which is incorporated herein by reference) or promoters that enhance specific performances or production plants.

[0048] A catalyst composition, e.g., a starting catalyst composition, may generally refer to the chemical composition of one or more catalytic materials. The catalyst composition may refer to a combination of catalytic materials comprising one or more catalyst component(s) making up the catalytic material(s). The catalytic material may refer to a catalytic particle, a catalytic pellet or a catalytic product comprising catalyst components. The catalyst composition may refer to a combination of catalytic particles, pellets or products comprising catalyst components. The catalyst composition may also refer to one catalytic particle, pellet or product comprising catalyst components.

[0049] A catalyst component specific indicator may be construed broadly and may refer to a chemical, physical, mechanical and / or structural property associated with the catalyst component. Such properties may include properties that effect the performance of catalysts. Examples of chemical, physical, mechanical and / or structural properties include:

[0050] - the catalyst component’s activity, selectivity, or yield fraction in combination with other components,

[0051] - the catalyst component’s impact on accessibility of active sites for feedstock components or surface area of the catalyst,

[0052] - the catalyst component’s impact on attrition resistance in relation to other catalyst components and components of production plants, such as chemical components of equipment or feedstocks,

[0053] - the catalyst component’s impact on hydrothermal stability with respect to operating conditions of the production plant, such as pressure or temperature conditions in the catalytic reactor of production plants,

[0054] - the catalyst component’s impact on precious metal content, metal tolerance, coke selectivity or fluidization.

[0055] A catalyst composition indicative of a catalyst component may refer to the digital representation of the catalyst composition. Such digital representation may include an identifier for the one or more catalytic material(s) and the catalyst components related to the identifier of the catalytic material(s). The catalyst composition indicative of the catalyst components may refer to an indicator associated with or based on the chemical composition of the catalyst. The indicator may be based on a fraction of the catalyst component in relation to a reference such as another catalytic particle or product, another catalyst component, or the catalyst composition. The indicator may include fractions such as percentage by weight, percentage by mass, percentage by mole, percentage by volume, mass percent composition, or the like.

[0056] A target catalyst composition indicative of the catalyst components may refer to a catalyst composition indicative of the catalyst components that fulfils certain criteria for the production plant. Criteria may include a target performance of the production plant or the catalytic reactor.

[0057] A digital representation of the production plant as used herein may be construed broadly and may refer to a kinetic process model of a production plant. The digital representation may include unit operations associated with physical process components of the production plant, operating conditions associated with the production plant, such as composition of feed streams, pressure, temperature or the like, and connections associated with connections between process components. Typical parameters included in such a digital representation may comprise chemical input parameters, unit operations and operating conditions. The digital representation of the production plant may further one or more process constraint(s) associated with the production plant.

[0058] A plant performance as disclosed herein may be construed broadly and may refer to a performance indicator of the production plant. This may relate to the output requirements of the production plant or operating parameters of the production plant. A plant performance may be obtained based on kinematic process model(s) of the production plant or a part therefor such as reactors and connections and valves between these reactors etc.

[0059] A target plant performance of the production plant may refer to a plant performance that fulfils certain criteria for the production plant, in particular in combination with the catalytic reactor of the production plant. Criteria may include but is not limited to yields, resource consumption, selectivity or the like of the production plant or the catalytic reactor.

[0060] It shall be understood that any of the apparatuses as described above, any of the systems as described above, any of the methods as described above, and any of the computer program elements as described above have similar and / or identical preferred embodiments, in particular, as defined in the dependent claims and above described embodiments.

[0061] It shall be understood that a preferred embodiment of the present disclosure can also be any combination of the dependent claims or above embodiments with the respective independent claim.

[0062] These and other aspects of the disclosure will be apparent from and elucidated with reference to the embodiments described hereinafter.

[0063] BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Non-limiting and non-exhaustive examples of the present disclosure are described with reference to the following drawings. In the drawings, like reference numerals refer to like parts throughout the various figures unless otherwise specified. These drawings are not necessarily drawn to scale.

[0065] Fig. 1 illustrates one example of a fluid cracking catalyst unit.

[0066] Fig. 2 illustrates one example of a refinery including a fluid cracking catalyst unit.

[0067] Fig. 3 illustrates a block diagram of one example environment with computing device^) and production plant.

[0068] Fig. 4 illustrates a flow diagram of one example method for providing or generating a catalyst performance indicator associated with a catalyst used or to be used in a production plant.

[0069] Fig. 5 illustrates a flow diagram of one example method for providing or generating a target catalyst composition used or to be used in a production plant.

[0070] Fig. 6 illustrates a flow diagram of one example method for operating a refinery based on the methods of Figs. 4 and 5.

[0071] DETAILED DESCRIPTION OF EMBODIMENTS Fig. 1 illustrates one example of a fluid cracking catalyst (FCC) unit 10. Several different designs exist for the FCC units. The example shown is only schematically illustrating the functional principles and should not be considered limiting.

[0072] Generally, the cracking reaction is an endothermic process. The FCC unit 10 includes a regenerator 12 and a reactor 14. The regenerator 12 comprises the FCC catalyst. The catalyst from the regenerator 12 is provided via connection line 16 to the riser 18 of the reactor 14. At the riser 18, the catalyst is combined with the feedstock 20. The temperature at the riser bottom may be in a range of 400 °C to 600 °C. The reactant mixture expands due to the cracking reaction as gases are formed, and the catalyst / feedstock mixture is transported up the riser 18. At the top of the riser 18, the temperature has dropped as catalytic cracking is an endothermic process.

[0073] At the top of the riser 22, the reactant mixture is fed to a stripper 22. In the stripper 22, the catalyst is separated from the product mixture. The product mixture is further refined downstream 24. The catalyst material, on which a certain amount of carbon or coke has been deposited during the cracking process, is transported to the regenerator 12 through connection 26. In the regenerator 12, the coke is burned off. The catalyst is thus regenerated and re-used continuously. Depending on the exact conditions (such as the oxygen availability), the regenerator temperature may be more than 700 °C. For regeneration, the catalyst is provided to the regenerator from air blower unit 32 via connection 34 and flue gas is released at the top of the regenerator 12 through connection 36. Regenerated FCC catalyst is provided to the riser 18 via connection 16.

[0074] Owing to the temperature and reaction conditions, the FCC catalyst deactivates over time. A conservative estimate is that a typical FCC catalyst particle has an average lifetime in the order of one or more month(s). To reduce the effect of catalyst deactivation, FCC catalyst is removed through connection 28 over the course of use and a portion of FCC catalyst is refilled through connection 30 to replace the removed catalyst with fresh catalyst. Depending on the size of the FCC unit and the operational parameters, catalyst withdrawal rates can be between 1 and 30 tons per day.

[0075] Fig. 2 illustrates one example of a refinery, in particular, of a production plant, including a fluid cracking catalyst unit 10. Several different designs exist for refineries. The example shown is only schematically illustrating the functional principles and should not be considered limiting. Once the feedstock passed the FCC unit 10 as described in connection with Fig. 1 , the product mixture released from the FCC unit is fed into a fractionator 38. The fractionator 38 separates the different product components from the product mixture. Examples of product components are dry gas 40, liquefied petroleum gas (LPG) 42, gasoline 44, light cycle oil 46, heavy cycle oil 48 and slurry oil 50.

[0076] Fig. 3 illustrates a block diagram of one example environment with computing device(s) 62, 64, 66 configured to perform the methods described herein.

[0077] The distributed computing system 60 includes a catalyst computing system 62 with a processor 68, persistent or non-persistent storage devices 70 and a communication interface 72, a plant model computing system 64 with a processor 74, persistent or non-persistent storage devices 76 and a communication interface 78, an industrial plant system 66 for operating the plant and a network 80 enabling communication between the computing devices 62, 64, 66.

[0078] The storage devices shown in Fig. 3 may be configured to store catalyst component specific indicators, catalyst composition(s) indicative of catalyst components, plant performance(s) signifying plant performance parameter(s) function(s), target plant performance(s) signifying target plant performance parameter(s) or function(s), plant data from one or more industrial plants or lab scale plants, plant process models, one or more digital representation^) of production plant(s) or the like. The methods disclosed herein may be implemented in a cloud-based model execution environment with a web-based graphical user interface.

[0079] The computing device(s) 62, 64, 66 may be configured to execute instructions to provide catalyst performance indicators, catalyst compositions indicative of catalyst components, target catalyst compositions, plant performance(s), or operating conditions. The distributed computing system 60 may further be configured to execute instructions to provide kinetic process models, to determine plant performance based on kinetic process model(s) or to determine optimal catalyst compositions reaching target performances for the production plant.

[0080] The catalyst computing system 62, the plant model computing system 44 and the industrial plant system 66 may be connected via an external network 80 to transfer data between the components of the distributed computing system 60. For instance, a client device may trigger the determination of the optimal catalyst composition via the distributed computing sys- tern 60. The distributed computing system 60 may provide the determined catalyst composition to the client device or directly to the industrial plant to monitor filling of the catalytic reactor. Similarly, during production, operating conditions may be provided in connection with the catalyst composition for optimizing, monitoring, or controlling the industrial plant.

[0081] This way an optimal catalyst composition fulfilling the technical performance requirements of the industrial plant may be provided and the catalyst performance indicator orthe kinetic process models may be further improved based on operating conditions from the industrial plant. This allows analysing the performance of a catalyst composition in FCC units. The systems and methods allow making determinations on catalyst composition achieving technical performance requirements of the production process. For example, different catalyst compositions and their impact on the performances of a production plant may be compared. Thereby, it is possible to determine a target catalyst composition that suits best to a catalyst reaction performed in a production plant.

[0082] Fig. 4 illustrates a flow diagram of one example method for determining a catalyst performance indicator.

[0083] In a first step 100, one or more catalyst component specific indicators) relating to a property of 1 to n catalyst components are provided. The catalyst component specific indicators) relate to chemical, physical, mechanical and / or structural properties of each catalyst component. This may include indicators such as:

[0084] - the catalyst component’s activity, selectivity, or yield fraction for reaction pathways,

[0085] - the catalyst component’s impact on accessibility of active sites for feedstock components or surface area of the catalyst,

[0086] - the catalyst component’s impact on attrition resistance in relation to other catalyst components and components of production plants, such as chemical components of equipment or feedstocks,

[0087] - the catalyst component’s impact on hydrothermal stability with respect to operating conditions of the production plant, such as pressure or temperature conditions in the catalytic reactor of production plants, or - the catalyst component’s impact on precious metal content, metal tolerance, coke selectivity or fluidization.

[0088] The catalyst component specific indicators may be derived from reference measurements e.g. in a test plant. In such a test plant, different catalyst compositions may be used for an FCC unit. For example, a reference feedstock may be provided to the FCC unit 10 as described with reference to Fig. 1 and different reference measurements characterizing the kinetics of the catalyst components may be measured in the test plant. Reference measurements may include measurement of catalyst selectivity, catalyst yields, catalyst activity, catalyst coking, catalyst deactivation or the like. From such reference measurements, catalyst component specific indicators may be derived and used as descriptors characterizing the kinetics of individual catalyst components. Reference measurements may be further extended by machine learning approaches like transfer learning based on chemical structure or quantum chemical simulation.

[0089] More than one catalyst component specific indicator may be provided per catalyst component. Catalyst component specific indicators may relate to an activity of the component, a stability of the component, a metal tolerance of the component and a yield or a selectivity of the component. Catalyst component specific indicators may be provided by a database. Any set of catalyst component specific indicators may be provided for individual catalyst components or for individual catalyst components in relation to a catalytic material composed of respective catalyst components.

[0090] As an example, FCC catalytic material is typically provided as particles made of different catalyst components including crystalline zeolite, filler, binder, matrix, and additives. Depending on the catalyst components, each catalytic material may provide different performance characteristics. Known examples include additives that are incorporated into the FCC catalytic material such as CO promoters that catalyse oxidation of CO to CO2 in an FCC regenerator, low NOx promoters for the catalytic oxidation of CO to CO2 in an FCC regenerator at low NOx emissions, product promoters increasing propylene or butylene yields, or fluidization promoters that optimize Average Particle Size (APS) distribution. With the aid of reference measurements and the definition of catalyst component indicators, catalytic components and the resulting catalytic material may be characterized to enhance catalytic compositions or products.

[0091] In a second step 102, a catalyst composition indicative of the catalyst components 1 to n is provided. The catalyst composition indicator may be provided based on the chemical composition of the catalyst. It may include a fraction of the catalyst component in relation to the catalyst composition such as percentage by weight, percentage by mass, percentage by mole, percentage by volume, mass percent composition, or the like. The catalyst composition indicator and its associated components may be used to retrieve the catalyst component specific indicators, e.g. from a database.

[0092] In a third step 104, the catalyst performance indicator based on the provided catalyst component specific indicators and the provided catalyst composition indicator is determined. Based on the catalyst composition indicator referencing the catalyst components, each components’ specific indicators may be retrieved to determine the catalyst performance indicator. The catalyst performance indicator may include any chemical, physical, mechanical and / or structural property associated with the catalyst. Such properties may include properties that effect the performance of catalysts or the reactor used or to be used in the production plant. Examples include activity, yield, selectivity, attrition resistance, hydrothermal stability, metals tolerance, coke selectivity, fluidizability.

[0093] The catalyst performance indicator may be determined based on a chemical rule relating to, e.g., the mass fraction and / or activity fraction of the catalyst components. The rule may include weights relating to mass, activity, component or molecule specific yield, component, or molecule specific conversion. Options for the rule include weighted average by mass, weighted average by activity, weighted average by volume or the like. Components that are more specialized may have a molecule specific mapping of the catalyst component indicator, for which yield or conversion for specific molecules or molecule classes may be provided. Other options include the use of reaction network analysis to map out overall reaction pathways and determine product outputs, from which catalyst component specific indicators may be generated.

[0094] In a fourth step 106, the catalyst performance indicator associated with the performance of the catalyst used or to be used in a production plant is provided. Using one or more catalyst performance indicator(s) being associated with a certain catalyst composition, it is possible to find a target catalyst composition, e.g., as described in the following with reference to Fig. 5. The determination of a catalyst performance indicator thus allows starting from a desired performance and to find the target catalyst composition is allows to achieve the desired performance. The present approach is thus based on defining a performance combined with kinetics to determine the best composition through a digital optimization. This stands in contrast to known approaches that start with a catalyst composition and try to determine the performance associated with that catalyst composition for improving a plant performance. Fig. 5 illustrates a flow diagram of one example method for providing and / or generating a target catalyst composition used or to be used in a production plant.

[0095] In a first step 108, a digital representation associated with the production plant and one or more target plant performance(s) of the production plant are provided.

[0096] The digital representation may include a piping and instrumentation diagram (P&ID), which specifies the major components of the plant including feed composition, process diagram, operation parameters, equipment capacities, operational constraint like temperatures, pressures, flowrates, volumetric holdup, storage volumes. From such P&ID diagram, a kinetic process model may be derived. The digital representation of the production plant may include a kinetic process model. The kinetic process model may be generated with known tools such as FCC-SIM® of KBC Advanced Technologies Ltd. FCC-SIM® (or “KBC”) may be used to simulate refineries and the effects of process changes on unit operations or profitability. The kinetic process model may be generated based on specifying unit operations, unit operating conditions, feed compositions and yields. In addition, constraints may be provided as part of or separately to the kinetic process model. Such constraints may include constraints on feed and product rates (flow rate minimum and maximum values), or pro-cess conditions (maximum and minimum temperature, heating / cooling duty, compressor power, environmental limits, etc.). An unconstrained process model may optimize to a very different reactor performance and feed rate, and thus may generate non-optimized catalyst solution. For example, if a catalyst formulation can increase conversion, but there is no more room in the refinery to process the increase in gasoline, incremental conversion needs to produce other valuable products that can be recovered and ultimately sold. This way the kinetic process model and its constraints may be generated which allows the model to predict responses to changing operating conditions and catalyst compositions.

[0097] The one or more target plant performance(s) of the production plant may specify a plant performance that fulfils certain criteria for the production plant, in particular in combination with the catalytic reactor of the production plant. Criteria may include target performance indicators of the production plant or the catalytic reactor. Examples may be product compositions and respective yields. Such criteria may be provided in the form of an objective function relating the catalyst composition and the digital representation of the plant with performance indicator(s) and a target objective relating the performance indicator(s) to target performance indicator(s). The target objective may be a minimum or a maximum to select the target catalyst composition achieving the target performance indicator(s). In a second step 1 10, one or more catalyst performance indicator(s) associated with one or more catalyst composition(s) are provided, wherein for each catalyst composition one or more catalyst performance indicator(s) are determined, e.g., according to example method of Fig. 4 is provided.

[0098] In a third step 112, for each catalyst composition a plant performance indicator based on the digital representation associated with the production plant and the catalyst performance indicator(s) is determined. The digital representation may include the kinetic process model of the production plant and constraints, where constraints may be specified on a model basis through numerical process limits, e.g., feed rates, product rates, temperature limits, compressor power limits, etc. In addition, a profitability model may be provided to convert the plant performance indicators into profitability based on cost assumptions. Such profitability models typically specify feed cost as well as product values for dry gas (C2-), LPG (C3, C3=, C4, C4=), naphtha, light cycle oil, main column bottoms, and coke. Profitability models may include raw material costs, utility cost, revenue generated from product, revenue generated for maximum product outputs or the like.

[0099] In a fourth step 114, the target catalyst composition with respect to the provided target plant performance(s) is determined based on the plant performance determined for each catalyst composition. Target performance parameters may relate to parameters directly linked to the catalyst composition. For instance, the catalyst compositions determine reactions and thus product, product composition, yield, selectivity, conversion, energy consumption or throughput. Constraints provide for limitations on the downstream component’s capacity.

[0100] The target composition may be determined by iteratively determining the catalyst composition, the respective catalyst performance indicators) and the respective plant performance indicator(s) until an objective function reaches a target objective signifying the target composition. Here, the result from the kinetic process model may be included into the objective function until the target objective, e.g. an extremum such as a maximum or a minimum is reached. One or more objective functions may be used and a Pareto optimization (multi-objective optimization) may be employed to determine the optimal target catalyst compositions and decide on trade-offs between different objectives. Alternative ways to decide in case of multiple objective functions may include constraints or target objectives for some objective functions and finding the optimum for one of the target objectives. The target objective signifying the target composition may be determined based on a local optimization method, such as sequential quadratic programming, gradient based optimization, or the like, a global optimization method, such as simplicial homology global optimization or a metaheuristic method or a combination these methods. The global target composition, the statistical target composition and / or the local target composition may be provided to select one target catalyst composition. For selection, one target objective may be given a higher weight and the results with the result scoring the highest for such target objective may be selected. In another option, a predefined metric may be employed, which signifies the risk, e.g. a cost risk. The target composition associated with the lowest risk according to such metric may be selected. Such metrics are commonly known, e.g., from finance such as the sharp ratio, which signifies the risk of investments.

[0101] This way tailored catalyst performance indicators may be combined with kinetic process models for individual plants, such that depending on the target plant performance(s) an optimal catalyst composition may be provided. In particular, by using the kinetic process model for different catalyst compositions, a target catalyst composition suitable for achieving a desired plant performance can be determined for different. By programmatically adjusting the catalyst composition and observing the response, the optimal composition may be determined for each plant. The objective function can be fine-tuned to allow for balancing of plant objectives (e.g. maximum product value generation vs. resource consumption minimization). The use of a profitability model advantageously correlates technical performance indicators with economic indicators.

[0102] In a fifth step 116, the target catalyst composition used orto be used in the production plant is provided.

[0103] The method as just described with reference to Fig. 5 may be used for a refinery. The refinery may provide the target plant performance of achieving a maximal gasoline output with a maximum LPG output constraint and a maximum regenerator temperature constraint. The target catalyst composition may be a traditional gasoline maximizing catalyst (high Z / M) with fine-tuned high RE / Z and surface area, such as Naphthamax® catalyst. For the same refinery, when market shifts diesel yields and / or gasoline de-emphasis, emphasis may shift toward HDxtra® (low Z / M with maybe emphasis on Light cycle oil).

[0104] For example, the catalyst solution can be tailored based on the units’ needs as well as the changes in a value of the product stream. In case, in such an adapted method, the refinery is trying to maximize the LPG olefins yields, a catalyst solution with low ReO / Z may be employed to maximize the profit through maximization of LPG olefins yields. Yet, if the objective is to maximize the gasoline yield, the solution could be altered in a way that gasoline yields are favoured through using increased ReO / Z solutions. Fig. 6 illustrates a flow diagram of one example method for operating a refinery based on the methods of Figs. 4 and 5.

[0105] FCC units 10 as depicted in Fig. 1 typically include a refilling process, in which fresh catalyst is provided to the regenerator to reduce the effect of deactivation. If during refinery operations the target plant performance changes, the method of Fig. 5 may be employed for generating and / or providing a target catalyst composition to accommodate such change. In particular, the catalyst refilling may be tailored to a catalyst composition corresponding to the target catalyst composition. In a first step 118, the new target plant performance may be provided. In the second step 120, the target catalyst composition may be updated based on the method described in connection with Fig. 5. Here, additional constraints may be added to the catalyst composition dimension of the optimization problem. Such constraints may relate to the catalyst composition used in the production plant and refilling rate(s). In a third step 122, the updated catalyst composition and optionally updated refilling rate(s) may be provided. Such results, in particular the refilling rate(s), may be used to control the refilling cycle of the FCC unit 10. This way, refineries can adapt to market needs without having to exchange the catalyst by way of shut down, but by gradually adapting the catalyst to their requirements.

[0106] Any disclosure and embodiments described herein relate to the methods, the systems, the computer element lined out above and vice versa. Advantageously, the benefits provided by any of the embodiments and examples equally apply to all other embodiments and examples and vice versa.

[0107] As used herein ..determining" also includes ..initiating or causing to determine", “generating" also includes ..initiating or causing to generate" and “providing” also includes “initiating or causing to determine, generate, select, send or receive”. “Initiating or causing to perform an action” includes any processing signal that triggers a computing device or system to perform the respective action.

[0108] Other variations to the disclosed embodiments can be understood and effected by those skilled in the art in practicing the claimed invention, from a study of the drawings, the disclosure, and the appended claims.

[0109] For the processes and methods disclosed herein, the operations performed in the processes and methods may be implemented in differing order. Furthermore, the outlined op- erations are only provided as examples, and some of the operations may be optional, combined into fewer steps and operations, supplemented with further operations, or expanded into additional operations without detracting from the essence of the disclosed embodiments.

[0110] In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality.

[0111] A single unit or device may fulfil the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage.

[0112] Procedures like the providing of the plant representation, the providing of the reactor model, the determining of the performance, the generating of the reactor model, etc. performed by one or several units or devices can be performed by any other number of units or devices. These procedures can be implemented as program code means of a computer program and / or as dedicated hardware.

[0113] A computer program product may be stored / distributed on a suitable medium, such as an optical storage medium or a solid-state medium, supplied together with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless tele-communication systems.

[0114] Any units described herein may be processing units that are part of a computing system. Pro-cessing units may include a general-purpose processor and may also include a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit. Any memory may be a physical system memory, which may be volatile, non-volatile, or some combination of the two. The term “memory” may include any computer-readable storage media such as a non-volatile mass storage. If the computing system is distributed, the processing and / or memory capability may be distributed as well. The computing sys-tem may include multiple structures as “executable components”.

[0115] The term “executable instruction or component” is a structure well understood in the field of computing as being a structure that can be software, hardware, or a combination thereof. For instance, when implemented in software, one of ordinary skill in the art would understand that the structure of an executable component may include software objects, routines, methods, and so forth, that may be executed on the computing system. This may include both an executable component in the heap of a computing system, or on computer- readable storage media. The structure of the executable component may exist on a computer-readable medium such that, when interpreted by one or more processors of a computing system, e.g., by a processor thread, the computing system is caused to perform a function. Such structure may be computer readable directly by the processors, for instance, as is the case if the executable component were binary, or it may be structured to be interpretable and / or compiled, for instance, whether in a single stage or in multiple stages, so as to generate such binary that is directly interpretable by the processors. In other instances structures may be hard coded or hard wired logic gates, that are implemented exclusively or near-exclusively in hardware, such as within a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or any other specialized circuit.

[0116] Accordingly, the term “executable instruction or component” is a term for a structure that is well understood by those of ordinary skill in the art of computing, whether implemented in software, hardware, or a combination. Any embodiments herein are described with reference to acts that are performed by one or more processing units or computing devices of the computing system. If such acts are implemented in software, one or more processors direct the operation of the computing system in response to having executed computerexecutable instructions that constitute an executable component.

[0117] Computing system may also contain communication channels that allow the computing system to communicate with other computing systems over, for example, network. A “network” is defined as one or more data links that enable the transport of electronic data between computing systems and / or modules and / or other electronic devices. When information is transferred or provided over a network or another communications connection, for example, either hardwired, wireless, or a combination of hardwired or wireless, to a computing system, the computing sys-tem properly views the connection as a transmission medium. Transmission media can include a network and / or data links which can be used to carry desired program code means in the form of computer-executable instructions or data structures and which can be accessed by a general-purpose or special-purpose computing system or combinations. While not all computing systems require a user interface, in some embodiments, the computing system includes a user interface system for use in interfacing with a user. User interfaces act as input or output mechanism to users for instance via displays.

[0118] Those skilled in the art will appreciate that the invention may be practiced in network computing environments with many types of computing system configurations, including, personal computers, desktop computers, laptop computers, message processors, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, mobile telephones, PDAs, pagers, routers, switches, data centres, wearables, such as glasses, and the like. The invention may also be practiced in distributed system environments where local and remote computing system, which are linked, for example, either by hardwired data links, wireless data links, or by a combination of hardwired and wireless data links, through a network, both perform tasks. In a distributed system environment, program modules may be located in both local and remote memory storage devices.

[0119] Those skilled in the art will also appreciate that the invention may be practiced in a cloudcomputing environment. Cloud computing environments may be distributed, although this is not required. When distributed, cloud computing environments may be distributed internationally within an organization and / or have components possessed across multiple organizations. In this description and the following claims, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources, e.g., networks, servers, storage, applications, and services. The definition of “cloud computing” is not limited to any of the other numerous advantages that can be obtained from such a model when deployed. The computing systems of the figures include various components or functional blocks that may implement the various embodiments disclosed herein as explained. The various components or functional blocks may be implemented on a local computing system or may be implemented on a distributed computing system that includes elements resident in the cloud or that implement aspects of cloud computing. The various components or functional blocks may be implemented as software, hardware, or a combination of software and hardware. The computing systems shown in the figures may include more or less than the components illustrated in the figures and some of the components may be combined as circumstances warrant.

[0120] Any reference signs in the claims should not be construed as limiting the scope of the disclosure or claims.

Claims

CLAIMS1. A computer-implemented method for generating and / or providing a target catalyst composition to be used in a production plant, the method comprising the steps of: providing a digital representation associated with the production plant, one or more target plant performance(s) of the production plant and a starting catalyst composition; determining a target catalyst composition by optimizing the starting catalyst composition with respect to the one or more target plant performance(s) using the digital representation associated with the production plant; and generating and / or providing the target catalyst composition for use in the production plant.

2. The method of claim 1 , wherein the optimization includes determining for one or more catalyst composition(s) a catalyst performance indicator.

3. The method of claim 2, wherein for each catalyst component of the catalyst composition a catalyst component specific indicator is provided, that relates to a property or properties of the catalyst component, and the catalyst performance indicator is determined based on the provided catalyst component specific indicator(s).

4. The method of claim 2 or 3, wherein the determining for one or more catalyst composition^) a catalyst performance indicator includes providing a catalyst composition indicative of one or more catalyst components) of the catalyst composition, providing one or more catalyst component specific indicator(s) relating to a property of the one or more catalyst component(s), determining the catalyst performance indicator based on the provided catalyst component specific indicator(s) and the provided catalyst composition, andproviding the catalyst performance indicator associated with the performance of the catalyst used or to be used in a production plant.

5. The method of claim 3 or 4, wherein the catalyst component specific indicator is derived from reference measurements associated with the catalyst component.

6. The method of claim 3 to 5, wherein the catalyst component specific indicator is associated with a chemical, a physical, a kinetic, a structural and / or a mechanical property of the catalyst component.

7. The method of any of claims 2 to 5, wherein the catalyst performance indicator is determined based on a chemical, structural, kinetic, physical and / or mechanical rule relating to the catalyst composition.

8. The method of any of claims 1 to 7, wherein the optimization for determining the target catalyst composition is based on multiple catalyst components and one or more plant performance(s).

9. The method of claim 8, wherein the optimization for determining the target catalyst composition includes constraints relating to the catalyst composition and / or the digital representation of the production plant.

10. The method of claim 8 or 9, wherein the plant performance^) relate to an output of the production plant, in particular a product output composition or a product output composition in relation to a feedstock, a reactor performance, one or more operating condition(s) of the production plant, one or more environmental condition(s) of the production plant, one or more feedstock(s) of the production plant, a resource usage of the production plant, and / or plant maintenance intervals.

11. A method for manufacturing a catalyst by using the target catalyst composition as generated and / or provided according to any of claims 1 to 10.

12. A method for using a catalyst in a catalytic reactor, wherein the catalyst is manufactured based on the target catalyst composition as generated and / or provided according to any of claims 1 to 10.

13. A method for using the target catalyst composition, as generated and / or provided according to any of claims 1 to 10, for operating a production plant, in particular a fluid cracking catalyst unit.

14. A computer element with instructions for determining a target catalyst composition, which when executed on one or more computing apparatus(es), carry out the methods of any of claims 1 to 10.

15. An apparatus for generating and / or providing a target catalyst composition, the system comprising one or more computing apparatus(es) including instructions, which when executed on the one or more apparatus(es) execute the steps of the methods 1 to 10.

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