A process for the conversion of oxygenates to a transportation range fuel

Abstract

The disclosure relates to a process for conversion of oxygenates to a transportation range fuel. The process comprises: setting a target fuel quality parameter of the transportation range fuel; feeding oxygenate compounds to a conversion reactor; converting the oxygenate compounds to a converted oxygenate product in the conversion reactor in the presence of a catalyst, the converted oxygenate product comprising the transportation range fuel; providing input parameters, the input parameters comprising a space velocity and a bed temperature profile; calculating an estimated fuel quality parameter of the transportation range fuel based on the input parameters and on a composition of the oxygenate compounds; comparing the estimated fuel quality parameter with the target fuel quality parameter; and adjusting an inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated and the target fuel quality parameter. The disclosure further relates to a system and a computer program.

Description

[0001] A PROCESS FOR THE CONVERSION OF OXYGENATES TO A TRANSPORTATION RANGE FUEL

[0002] FIELD OF THE INVENTION

[0003] The present invention relates to a process for the conversion of oxygenates to a transportation range fuel, such as a gasoline product, a jet fuel product or a diesel product. The invention further relates to a reactor system and a computer program for converting oxygenates to a transportation range fuel.

[0004] BACKGROUND OF THE INVENTION

[0005] Industrial conversion of oxygenates to a transportation range fuel is often performed with respect to a fuel quality parameter. As an example, conversion of oxygenates to a gasoline product may be performed with respect to a desired octane number of the converted oxygenate product.

[0006] Conversion of oxygenates is affected by a large number of various conditions and parameters. As an example, a catalyst present in a conversion reactor may gradually become deactivated. Such catalyst deactivation may be counteracted by controlling, e.g., an inlet temperature to ensure that the fuel quality parameter of the transportation range fuel does not significantly decrease.

[0007] However, it is generally challenging to perform such control in a manner which ensures conversion of oxygenates such that the obtained transportation range fuel accurately meets a desired fuel quality parameter while ensuring a high yield. If control is performed such that an obtained fuel quality parameter is too large relative to the desired octane number, the yield is correspondingly lower. Further, it is typically a time-consuming and cumbersome task to measure an actual fuel quality parameter. In commercial plants, several reactors often operate in parallel at different conditions, making measurements of the combined product practically useless for determining what the individual reactors yield. Thereby, it is challenging to implement live measurements of the fuel quality parameter of the produced transportation range fuel to monitor to conversion process.

[0008] As a result, conventional processes and systems for conversion of oxygenates to a transportation range fuel are inefficient. Since it is not typically possible to accurately produce a transportation range fuel according to a desired fuel quality parameter, such fuels are instead produced while aiming for a fuel quality parameter which is greater than actually required, resulting a lower product yield. Hence, there is a need for more efficient processes and system for conversion of oxygenates to a transportation range fuel, and in particular for processes and systems which ensures that a transportation range fuel can be produced accurately with respect to a desired fuel quality parameter while ensuring a high yield.

[0009] SUMMARY OF THE INVENTION

[0010] On the above background, it is an object of preferred embodiments of the present disclosure to provide processes and systems which efficiently convert oxygenates to a transportation range fuel. In particular, it is an object of preferred embodiments to ensure that a transportation range fuel can be produced accurately with respect to a desired fuel quality parameter while ensuring a high yield. It is further an object of some embodiments to improve catalyst lifetime, and an object of some embodiments to reduce the amount of manual control of a reactor system.

[0011] A first aspect of the present disclosure relates a process for the conversion of oxygenates to a transportation range fuel, the process comprising the steps of:

[0012] setting a target fuel quality parameter of the transportation range fuel in a process controlling arrangement;

[0013] feeding one or more oxygenate compounds to a conversion reactor, the one or more oxygenate compounds being fed to the conversion reactor with a space velocity and a controlled inlet temperature;

[0014] converting the one or more oxygenate compounds to a converted oxygenate product in the conversion reactor in the presence of a catalyst, the converted oxygenate product comprising the transportation range fuel;

[0015] providing a set of input parameters to the process controlling arrangement, the set of input parameters comprising the space velocity and a bed temperature profile, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature;

[0016] calculating an estimated fuel quality parameter of the transportation range fuel in the process controlling arrangement based on the set of input parameters and based on a composition of the one or more oxygenate compounds; comparing the estimated fuel quality parameter with the target fuel quality parameter in the process controlling arrangement; and

[0017] adjusting the inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated fuel quality parameter and the target fuel quality parameter,

[0018] optionally wherein the transportation range fuel is any of a gasoline product, a jet fuel product, and a diesel product,

[0019] wherein the fuel quality parameter is any of octane number, sulphur content, aromatics content, volatility, and distillation curve characteristics when the transportation range fuel is a gasoline product,

[0020] wherein the fuel quality parameter is any of flash point, freezing point, smoke point, thermal stability, aromatics content, and energy density when the transportation range fuel is a jet fuel product,

[0021] wherein the fuel quality parameter is any of cetane number, cold filter plugging point, cloud point, sulphur content, density, and lubricity when the transportation range fuel is a diesel product.

[0022] It has conventionally been challenging to ensure that a transportation range fuel can be produced accurately with respect to a desired fuel quality parameter while ensuring a high yield, in particular since it is not possible to straightforwardly obtain an indication of the fuel quality parameter of the transportation range fuel provided by the individual reactor.

[0023] As a solution, the present disclosure provides that an estimated fuel quality parameter of the transportation range fuel is calculated. This estimated fuel quality parameter is calculated based on selected parameters and conditions. Such parameters typically include at least a composition of the one or more oxygenate compounds which are converted, and a set of input parameters, the input parameters comprising a space velocity and a bed temperature profile. Further, the estimated fuel quality parameter may be calculated based on a catalyst deactivation state.

[0024] Upon obtaining an estimated fuel quality parameter, it is possible to compare this parameter with a target fuel quality parameter and adjust control of the process accordingly, for example by adjusting an inlet temperature or a recycle-to-oxygenate feed gas ratio. The recycle-to-oxygenate feed gas ratio is indicative of a ratio of recycled gas and oxygenate gas fed to the conversion reactor. This ratio may be controlled to steer the conversion process. The recycled gas is a body of gas which has already been processed through a conversion reactor. This body of gas may be separated from other constituents from the conversion reactor using a separator. The recycled gas may typically comprise or consist of a mixture of reactive species and inert species. The recycled gas may typically consist of constituents which are relatively light. The recycled gas may stem from the same conversion reactor as it is being recycled to, from one or more other conversion reactors, or from a combination thereof.

[0025] According to examples of the present disclosure, the recycle-to-oxygenate feed gas ratio is indicative of a ratio of recycled gas to the one or more oxygenate compounds being fed to the conversion reactor, wherein the recycled gas is a body of gas which has already been processed through a conversion reactor.

[0026] As a result, it may be possible to ensure that a transportation range fuel can be produced efficiently and accurately with respect to a desired fuel quality parameter while ensuring a high yield.

[0027] Further, it may be possible to lower the dealumination rate of the catalyst used in the conversion reactor since the reactor can be operated under milder operational conditions, which in turn can improve catalyst lifetime. A catalyst according to the present disclosure may be a zeolite or a zeolite-based catalyst.

[0028] In addition, operation according to an estimated fuel quality parameter may potentially reduce the amount of manual control required to operate a reactor system.

[0029] The calculation of the estimated fuel quality parameter can be performed using any kind of computational model. However, generally, machine-learning models are suitable for implementation of calculations of estimated fuel quality parameters according to the present disclosure since such models may allow accurate and fast modelling of complex systems.

[0030] In practice, calculations and control according to the present disclosure may be facilitated by a process controlling arrangement. Such a process controlling arrangement may, for example, be a computer system. The process controlling arrangement may comprise one or more processing units (such as CPUs) and one or more digital storages. Such digital storages may store a computer program, such as a computer program comprising a computer model for calculating the estimated fuel quality parameter. Such digital storages may further be arranged to receive and store data, for example data indicative of operation of a reactor system, such as input parameters and composition of oxygenate compounds. The input parameters can be process values measured and logged online. Accordingly, the process controlling arrangement may be communicatively connected with relevant control and sensor systems of a reactor system, such as temperature sensors and temperature control. Moreover, a process controlling arrangement may be configured to receive manual input, such as a target fuel quality parameter, and be configured to display relevant information to an operator. Thereby, a process controlling arrangement can facilitate setting or receiving a target fuel quality parameter, controlling at least an inlet temperature, receiving, e.g., input parameters, calculating an estimated fuel quality, performing a comparison of the estimated and the target fuel quality parameter, and adjusting the inlet temperature and / or a recycle-to-oxygenate feed gas ratio. The process controlling arrangement may optionally be facilitated via internet access, for example with the process controlling arrangement being at least partly implemented on a server.

[0031] In some examples, the calculations performed on the process controlling arrangement may be considered to constitute a soft sensor or a virtual sensor which senses or estimates the (estimated) fuel quality parameter.

[0032] According to examples of the present disclosure, the transportation range fuel is any of: a gasoline product, jet fuel product, and diesel product. However, other examples are not limited to these types of transportation range fuels. That is, the feature of the transportation range fuel being any of a gasoline product, jet fuel product, and diesel product is fully optional.

[0033] When the transportation range fuel is a gasoline product, the fuel quality parameter may optionally be any of an octane number, sulphur content, aromatics content, a volatility, and distillation curve characteristics.

[0034] When the transportation range fuel is a jet fuel product, the fuel quality parameter may optionally be any of a flash point, a freezing point, a smoke point, thermal stability, aromatics content, and an energy density.

[0035] When the transportation range fuel is a diesel product, the fuel quality parameter may optionally be any of a cetane number, a cold filter plugging point, a cloud point, sulphur content, a density, and a lubricity.

[0036] In case of the transportation range fuel being a gasoline product, an example of a suitable fuel quality parameter is an octane number, such as a research octane number or a motor octane number. For example, a gasoline product may be produced according to a research octane number of 92 or 95. In case of the transportation range fuel being a diesel product, an example of a fuel quality parameter is cetane number. That is, the target fuel quality parameter can be a target cetane number, and the estimated fuel quality parameter can be an estimated cetane number. For example, a diesel product may be produced according to a cetane number of 50 or 60. In case of the transportation range fuel being a jet fuel product, examples of a fuel quality parameter are a product density, an aviation lean rating, and an aviation rich rating. For example, a jet fuel product may be produced according to an aviation lean rating of 100. The product density can be a product density during an intermediate step of the production process, such as during oligomerization of olefins.

[0037] According to examples of the present disclosure, the target fuel quality parameter is a target octane number, wherein the estimated fuel quality parameter is an estimated octane number, wherein the transportation range fuel is a gasoline product.

[0038] The processes and method disclosed herein are particularly advantageous for conversion into gasoline, for example for the conversion of oxygenates to C5+hydrocarbons boiling in the gasoline boiling range, wherein the transportation range fuel is a gasoline product. Gasoline products are often produced according to a certain minimum octane number. Yet, since the octane number cannot be straightforwardly monitored during conversion, gasoline products are often produced with an octane number being significantly greater than the required minimum octane number, resulting in a lower yield. Hence, conventional production of gasoline products is inefficient. The solutions offered by the present disclosure can readably be employed to provide gasoline products having a more accurate octane number, thereby improving the product yield. Further, the catalyst lifetime may be improved and a degree of manual control required may be reduced.

[0039] An octane number may also be referred to as an octane rating. In some examples, the target octane number and the estimated octane number are a target research octane number and an estimated research octane number. In some examples, the target octane number and the estimated octane number are a target motor octane number and an estimated motor octane number.

[0040] According to examples of the present disclosure, the set of input parameters further comprises a reactor pressure of the conversion reactor and / or a Reid vapour pressure of the converted oxygenate product.

[0041] The fuel quality parameter can be estimated with reasonable accuracy based on a calculation using space velocity and bed temperature profile, as well as a composition of the one or more oxygenate compounds. Further including a reactor pressure of the conversion reactor and / or a Reid vapour pressure of the converted oxygenate product as input parameters can further improve accuracy of the estimated fuel quality parameters. According to examples of the present disclosure, the space velocity comprises a first space velocity parameter and a second space velocity parameter, wherein the first space velocity parameter is indicative of oxygenate per catalyst volume or mass, wherein the second space velocity parameter is indicative of a total feed flow per catalyst volume or mass.

[0042] Including a first and second space velocities can further improve accuracy of the estimated fuel quality parameters.

[0043] According to examples of the present disclosure, the step of calculating the estimated fuel quality parameter comprises the sub-steps of:

[0044] calculating a reactor activity based on the set of input parameters, the reactor activity comprising an irreversible activity from reactor acidity and a reversible activity from coking;

[0045] calculating a species composition of the converted oxygenate product based on the set of input parameters, the reactor activities, and the composition of the one or more oxygenate compounds, the species composition comprising an aromatic concentration and an olefin concentration; and

[0046] calculating the estimated fuel quality parameter based on the species composition.

[0047] By sub-dividing the calculation of an estimated fuel quality parameter into several sub-steps as exemplified here, the accuracy and / or the efficiency of the calculation may be improved.

[0048] The reactor activity is typically associated with the catalyst of the conversion reactor, which can deactivate (thereby reducing the reactor activity) by, e.g., coking and dealumination. This reactor activity can be calculated by estimating contributions from irreversible activity, and reversible activity by coking. In turn, both of these factors can be straightforwardly calculated by using differential equations. However, other models or methodologies for calculating a reactor activity may also be calculated, such as a machine-learning model.

[0049] Based on the reactor activity, a species composition may then be calculated, which in turn can be used to calculate the estimated fuel quality parameter. Although these sub-steps can also be implemented, at least in part, using e.g. coupled differential equations, it has been found that these steps can efficiently be implemented based on a machine-learning model. In particular, it has been found that an estimated fuel quality parameter can accurately and efficiently provided by first providing the reactor activity via differential equations, and then calculating species composition and estimated fuel quality based on a machine learning model. According to examples of the present disclosure, the step of calculating the estimated fuel quality parameter is further based on the reactor activity, at least some of the input parameters, the composition of the one or more oxygenate compounds, or any combination thereof.

[0050] According to examples of the present disclosure, the sub-step of calculating the reactor activity is performed via differential equations, such as ordinary differential equations, in which the reactor activity is numerically calculated based on the set of input parameters.

[0051] According to examples of the present disclosure, the step of calculating the estimated fuel quality parameter is performed using a computer model which correlates the set of input parameters and the composition of the one or more oxygenate compounds with the estimated fuel quality parameter.

[0052] According to examples of the present disclosure, the computer model comprises a machinelearning model, such as a neural network, which has been trained on a test data set.

[0053] According to examples of the present disclosure, the computer model is configured to perform the sub-steps of: calculating the species composition; and / or calculating the estimated fuel quality parameter.

[0054] According to examples of the present disclosure, the test data set comprises data relating any of the input parameters, the composition of the one or more oxygenate compounds, the reactor activity, and the species composition to the estimated fuel quality parameter.

[0055] Preferably, the computer model is a machine-learning model, preferably a neural network, which has been trained on a test data set to provide a correlation between, e.g., the input parameters and the composition of the one or more oxygenate products with an actual fuel quality parameter, for example an actual octane number.

[0056] The test data set can comprise data from any relevant conversion reactors, including commercial conversion reactors and / or pilot conversion reactors which have been operated by conventional methods. Such test data preferably comprises actual measurements of a fuel quality parameter which the operation yields, such as an octane number which the operation yields. Thereby, through data from conventional operation, the model can identify and establish a correlation between, e.g., the reaction outputs and the estimated octane number, or alternative, correlate the input parameters and the composition of the one or more oxygenate compounds with the estimated octane number. Alternatively or additionally, the test data set can comprise simulated data. Such simulated data may for example be generated by running computationally demanding simulations of a conversion process in a conversion reactor. Since such data is used for training, and not to control live operation, it is in principle possible to perform simulations with arbitrarily high accuracy to provide data of sufficient quality for a test data set.

[0057] Simulated test data may be more computationally demanding to provide than operation of a trained machine-learning model. Further, such simulated test data may be generated at any time at which computational resources are available. Thereby, an efficient machine-learning model can be established based on such data.

[0058] The test data set may for example comprise the parameters upon which calculations are performed. For example, the test data should preferably comprise at least input parameters, composition of one or more oxygenate compounds, and a fuel quality parameter. Further, the test data may preferably further comprise reactor activity. Alternatively or additionally, the test data may comprise a species composition.

[0059] In an example according to the present disclosure, the sub-step of calculating reactor activity is performed via differential equations, and the sub-step of calculating the species composition and the estimated fuel quality parameter is performed using a machine-learning model. The reactor activity can efficiently be calculated via numerically solved differential equations. This in turn allows a relatively simple machine-learning model to be employed to efficiently and accurately perform the sub-steps of calculating a species composition, and calculating a fuel quality parameter. Thereby, the resulting computer model will be more efficient, and a smaller test data set is required to establish the neural network when relevant reaction outputs are already calculated by other means.

[0060] As an example of a machine-learning model suitable for implementation of aspects of the present disclosure is a neural network comprising 5 neurons in a hidden layer trained on 1.4 million data points of test data comprising, at least in part, input parameters, composition of one or more oxygenate compounds, reactor activity, a species composition and a fuel quality parameter, of which 70% of the data points are used for training, 15% are used for validation, and 15% are used for testing. Although this is an example of a relatively simple machinelearning model, other models may also be used, including more complex machine-learning models or models based primarily of differential equations of high complexity. Typically, such models can potentially provide higher accuracy, for example at the expense of requiring more test data and / or being more computationally demanding. According to examples of the present disclosure, the step of adjusting the inlet temperature and / or the recycle-to-oxygenate feed gas ratio comprises:

[0061] decreasing or maintaining the inlet temperature when the estimated fuel quality parameter is greater than the target fuel quality parameter; and

[0062] increasing the inlet temperature when the estimated fuel quality parameter is smaller than the target fuel quality parameter.

[0063] Such adjustment may simply and efficiently ensure that a difference between the target fuel quality parameter and the estimated fuel quality is reduced during operation.

[0064] Generally, the inlet temperature may be adjusted between 200°C and 450°C, such as between 220°C and 370°C

[0065] According to examples of the present disclosure, the steps of calculating an estimated fuel quality parameter and adjusting the inlet temperature and / or the recycle-to-oxygenate feed gas ratio are performed during the step of converting the one or more oxygenate compounds.

[0066] According to examples of the present disclosure, the step of adjusting the inlet temperature is performed iteratively based on iteratively calculating the estimated fuel quality parameter.

[0067] Hence, the aspects according to the present disclosure may be implemented as a live / online feedback mechanism while conversion is ongoing.

[0068] According to examples of the present disclosure, said process is performed using a plurality of conversion reactors, wherein the target fuel quality parameter is a common target fuel quality parameter for each reactor of the plurality of conversion reactors, wherein the inlet temperature is controlled independently for each reactor of the plurality of conversion reactors, wherein the steps of converting the one or more oxygenate compounds, providing the set of input parameters, calculating the estimated fuel quality parameter, and adjusting the inlet temperature and / or the recycle-to-oxygenate feed gas ratio are performed independently for each reactor of the plurality of conversion reactors.

[0069] By implementing the process independently for several conversion reactors, it is possible to operate a plant comprising several reactors to collectively provide a transportation range fuel having a common target fuel quality parameter in an efficient and accurate manner. According to examples of the present disclosure, the set of input parameters comprises the recycle-to-oxygenate feed gas ratio and / or wherein said composition of the one or more oxygenate compounds is provided based on the recycle-to-oxygenate feed gas ratio.

[0070] A second aspect of the present disclosure relates to a reactor system comprising:

[0071] a conversion reactor for converting one or more oxygenate compounds to a converted oxygenate product in the presence of a catalyst, the converted oxygenate product comprising a transportation range fuel;

[0072] an oxygenate compound inlet for feeding one or more oxygenate compounds to the conversion reactor with a space velocity; and

[0073] a process controlling arrangement, wherein the process controlling arrangement is configured to:

[0074] receive a target fuel quality parameter of the transportation range fuel;

[0075] control an inlet temperature at which the one or more oxygenate compounds are fed to the conversion reactor;

[0076] calculate an estimated fuel quality parameter of the transportation range fuel based on a set of input parameters and based on a composition of the one or more oxygenate compounds, the set of input parameters comprising the space velocity and a bed temperature profile, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature;

[0077] compare the estimated fuel quality parameter with the target fuel quality parameter; and

[0078] adjust the inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated fuel quality parameter and the target fuel quality parameter,

[0079] optionally wherein the transportation range fuel is any of a gasoline product, a jet fuel product, and a diesel product, wherein the fuel quality parameter is any of octane number, sulphur content, aromatics content, volatility, and distillation curve characteristics when the transportation range fuel is a gasoline product,

[0080] wherein the fuel quality parameter is any of flash point, freezing point, smoke point, thermal stability, aromatics content, and energy density when the transportation range fuel is a jet fuel product,

[0081] wherein the fuel quality parameter is any of cetane number, cold filter plugging point, cloud point, sulphur content, density, and lubricity when the transportation range fuel is a diesel product.

[0082] A reactor system according to the second aspect of the present disclosure may comprise any of the same or similar advantages, features, and effects as the process according to the first aspect of the present disclosure.

[0083] According to examples of the present disclosure, the oxygenate compound inlet is in thermal communication with a trim heater and / or a heat exchanger through which the inlet temperature is controlled by the process controlling arrangement.

[0084] Thereby, the process controlling arrangement can adjust the inlet temperature via the oxygenate compound inlet in response to a comparison between the estimated fuel quality parameter and the target fuel quality parameter. Such a heat exchanger may, for example, be in thermal communication with an outlet of the conversion reactor.

[0085] A third aspect of the present disclosure relates to a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of:

[0086] receiving a target fuel quality parameter of a transportation range fuel;

[0087] controlling an inlet temperature at which one or more oxygenate compounds are fed to a conversion reactor for converting one or more oxygenate compounds to a converted oxygenate product in the presence of a catalyst, the converted oxygenate product comprising the transportation range fuel;

[0088] calculating an estimated fuel quality parameter of the transportation range fuel based on a set of input parameters and based on a composition of the one or more oxygenate compounds, the set of input parameters comprising a space velocity at which the one or more oxygenate compounds are fed to the conversion reactor and a bed temperature profile, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature;

[0089] comparing the estimated fuel quality parameter with the target fuel quality parameter; and

[0090] adjusting the inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated fuel quality parameter and the target fuel quality parameter,

[0091] optionally wherein the transportation range fuel is any of a gasoline product, a jet fuel product, and a diesel product,

[0092] wherein the fuel quality parameter is any of octane number, sulphur content, aromatics content, volatility, and distillation curve characteristics when the transportation range fuel is a gasoline product,

[0093] wherein the fuel quality parameter is any of flash point, freezing point, smoke point, thermal stability, aromatics content, and energy density when the transportation range fuel is a jet fuel product,

[0094] wherein the fuel quality parameter is any of cetane number, cold filter plugging point, cloud point, sulphur content, density, and lubricity when the transportation range fuel is a diesel product.

[0095] A computer program according to the third aspect of the present disclosure may comprise any of the same or similar advantages, features, and effects as the process according to the first aspect of the present disclosure. The computer program may be implemented or implementable on a process controlling arrangement as described within the present disclosure.

[0096] BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Embodiments of the invention will now be further described by reference to the accompanying drawings, in which: Fig. 1 illustrates a reactor system according to an example of the present disclosure;

[0098] Fig. 2 illustrates a reactor system comprising a plurality of conversion reactors according to an example of the present disclosure;

[0099] Fig. 3 illustrates a fuel quality calculator according to the present disclosure;

[0100] Fig. 4 illustrates method steps according to an example of the present disclosure, and

[0101] Fig. 5a-b illustrate results of a simulation which exemplifies potential improvements provided according to examples of the present disclosure.

[0102] DETAILED DESCRIPTION

[0103] Fig. 1 illustrates a reactor system 1 according to an example of the present disclosure.

[0104] The reactor system 1 comprises a conversion reactor 2 for converting oxygenate compounds into a converted oxygenate product in the presence of a catalyst. The conversion reactor 2 further accommodates said catalyst.

[0105] The reactor system 1 further comprises an oxygenate compound inlet 4 in fluid communication with the conversion reactor 2 for feeding oxygenate compounds to the conversion reactor.

[0106] This inlet 4 can, for example, be used to feed methanol, recycled oxygenate compounds, or a combination thereof at a recycle-to-oxygenate feed gas ratio.

[0107] In addition, the reactor system 1 comprises a process controlling arrangement 3 for controlling the conversion of oxygenate compounds in the conversion reactor 2. The process controlling arrangement controls the conversion by means of process control parameters 5. These parameters 5 can, for example, comprise inlet temperature, space velocity, and / or recycle-to-oxygenate feed gas ratio.

[0108] The process controlling arrangement further receives measurements from the conversion reactor 2. These measurements can, for example, comprise measurements indicative of a bed temperature profile (i.e., inlet temperature, bed temperature, outlet temperature).

[0109] The process controlling arrangement 3 provides at least some of the process control parameters 5 and the measurements from the conversion reactor 2 to a fuel quality calculator 7 to thereby perform a calculation of an estimated fuel quality parameter of a transportation range fuel of a converted oxygenate product produced in the conversion reactor.

[0110] The estimated fuel quality parameter is compared to a target fuel quality parameter 9 in a fuel quality evaluator 8, and based on this comparison, the process controlling arrangement 3 adjusts one or more of the process control parameters 5. Accordingly, the process controlling arrangement 3 can adapt the conversion process in the conversion reactor 2, thereby altering an actual fuel quality parameter of the produced transportation range fuel based on a calculated estimate of the fuel quality parameter. The actual fuel quality parameter is thereby, preferably, altered towards the target fuel quality parameter.

[0111] Such process control may be performed one or more times during the conversion of oxygenate compounds in the conversion reactor 2.

[0112] The process controlling arrangement 3 may be operated according to a computer program as provided in the present disclosure.

[0113] Fig. 2 illustrates a reactor system comprising a plurality of conversion reactors 2a, 2b, ... according to an example of the present disclosure.

[0114] The present illustration shows a first conversion reactor 2a, and a second conversion reactor 2b, but the examples provided herein extend to any number of conversion reactors.

[0115] Each of the conversion reactors 2a, 2b, ... have a separate oxygenate compound inlet for feeding one or more oxygenate compounds.

[0116] The process controlling arrangement 3 is configured to control the processes in each of the conversion reactors 2a, 2b, ... independently. However, the processes are controlled according to a common target fuel quality parameter 9.

[0117] Hence, the first conversion reactor 2a is controlled according to a first set of process control parameters 5a, the process controlling arrangement 3 receives a first set of measurements from the first conversion reactor 2a, and the process controlling arrangement 3 provides at least some parameters from of the first set process control parameters 5a and the first set of measurements to a fuel quality calculator 7 to thereby perform a calculation of a first estimated fuel quality parameter of transportation range fuel of the first conversion reactor 2a. Correspondingly, the second conversion reactor 2b is controlled according to a second set of process control parameters 5b, the process controlling arrangement 3 receives a second set of measurements from the second conversion reactor 2b, and the process controlling arrangement 3 provides at least some parameters from of the second set process control parameters 5b and the second set of measurements to a fuel quality calculator 7 to thereby perform a calculation of a second estimated fuel quality parameter of transportation range fuel of the second conversion reactor 2a.

[0118] The converted oxygenate products provided in the respective reactors 2a, 2b, ... can be mixed after conversion to provide a common oxygenate product or a common transportation range fuel from the plurality of conversion reactors 2a, 2b, ....

[0119] By controlling each of the separate conversion reactors 2a, 2b, ... according to a common target fuel quality parameter 9, a common transportation range fuel provided by the plurality conversion reactors 2a, 2b, ... can thereby be efficiently and accurately produced.

[0120] Fig. 3 illustrates a fuel quality calculator 7 according to the present disclosure.

[0121] The disclosed fuel quality calculator 7 can, for example, be a part of a computer program, for example implemented on a process controlling arrangement.

[0122] The fuel quality calculator 7 receives input parameters 7, the input parameters at least comprising a space velocity and a bed temperature profile.

[0123] The fuel quality calculator comprises an activity module 11, a product composition module 12, and a fuel quality calculation module 13.

[0124] The activity module 11 receives the input parameters 6, and based on this, a reactor activity is calculated, for example as exemplified further below.

[0125] The composition module 12 also receives the input parameters, and based on this, a product species composition is calculated. The composition module 12 may optionally also receive the reactor activity calculated by the activity module 11 as an input. The species composition is at least indicative of an aromatic concentration and an olefin concentration in the converted oxygenate product. The composition module may, for example, be implemented based on a machine learning model or based on numerically solved differential equations.

[0126] Based on the input parameters 6, the reactor activity calculated by the activity module 11, and the species composition calculated by the composition module 12, the fuel quality calculation module 13 calculates an estimated fuel quality parameter 10. The fuel quality calculation module 13 may for example be implemented based on a machine learning model. An example of how reactor activity can be calculated based on differential equations is provided in the following.

[0127] The reactor activity comprises irreversible activity and reversible activity.

[0128] Irreversible activity airtypically refers to the loss of activity or acidity of a catalyst, more specifically the Bronsted acid sites. Such loss of activity is permanent and eventually leads to the need for catalyst replacement. The rate of irreversible activity loss is influenced by temperature and water concentration. Higher temperatures and higher water concentrations result in faster loss of acidity. This irreversible activity loss is caused by a process called dealumination, where water removes aluminium atoms from the zeolite framework, which are responsible for providing the acid sites. The presence of oxygenate compounds, which are the reactants, competes for these acid sites and helps protect them against the effects of steaming. Coke deposition also helps to protect against steaming.

[0129] Reversible activity arrefers to the loss of activity due to coke deposition on the catalyst. This is also a temperature-dependent reaction and is influenced by the concentration of the oxygenate feed. The presence of water inhibits coke deposition and therefore protects against it. The rate of coking is influenced by the activity of the coke itself and the Bronsted acidity of the catalyst. A lower Bronsted acidity airresults in a slower rate of coking.

[0130] The irreversible activity airand the reversible activity arcan be calculated based the coupled differential equations

[0131] fcirexp (-Elr / RT)xH 0

[0132]

[0133] dt - l x + T K ^oxy x^ -Oxya^ar

[0134] and

[0135] darkrexp (-Er / RT)x0

[0136]

[0137] dt - l + K x -

[0138] where T is temperature and R is the gas constant. The term l+KOxyxoxy in the denominator of the top equation represents an inhibition constant Koxymultiplied by the feed mass fraction of the oxygenate compound xOxy. Correspondingly, the term l+KH2o*xH2o in the denominator of the bottom equation represents an inhibition constant for water KH2o multiplied by the feed mass fraction of water xH2o. The model parameters kir, Eir, Koxy, ni, n2, kr, Er, KH2o, mi, and m2are kinetic constants, i.e., pre-exponential factors, activation energies, inhibition constants, and exponents, as well-known from conventional kinetic modelling. These can be determined, for a given set of operation conditions, empirically by simulation or operation of conversion reactors, for example in a pilot plant, acquiring the relevant data, and fitting this data using various trial parameters.

[0139] When solving such differential equations, historical data can be utilized. Loss of acidity starts upon catalyst replacement (i.e., airis set to 1 upon catalyst replacement and decreases towards 0). The reversible activity is regained by performing regenerations, where coke is removed by coke-burn off. Hence, upon catalyst regeneration, aris set to 1 and decreases towards 0.

[0140] Loss of acidity can also be accounted for during regenerations.

[0141] Such a calculation of a reactor activity may, for example, be provided as a sub-step of a calculation of an estimated fuel quality parameter.

[0142] Fig. 4 illustrates method steps S1-S7 according to an example of the present disclosure. The method relates to a process of converting oxygenates to a transportation range fuel.

[0143] In a step SI of the method, a target fuel quality parameter of a transportation range fuel is set. This target fuel quality parameter may for example be set manually by a human operator in a process controlling arrangement which controls operation of a plant or one or more conversion reactors of a plant.

[0144] In a step S2 of the method, one or more oxygenate compounds are fed to a conversion reactor. These one or more oxygenate compounds are fed to the conversion reactor with a space velocity and a controlled inlet temperature. The space velocity and the inlet temperature are typically controlled by the process controlling arrangement.

[0145] In a step S3 of the method, the one or more oxygenate compounds are converted into a converted oxygenate product in the conversion reactor in the presence of a catalyst. This converted oxygenate product comprises the transportation range fuel at which the method is directed at providing. If necessary, the transportation range fuel may be separated from other components of the converted oxygenate product at a later stage of processing.

[0146] In a step S4 of the method, a set of input parameters is provided. These input parameters are provided to the process controlling arrangement. The input parameters may comprise process control parameters upon which the process controlling arrangement controls conversion in the conversion reactor. The input parameters may comprise measured parameters from the conversion reactor. At least, the set of input parameters should preferably comprise the space velocity and a bed temperature profile of the conversion reactor, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature of the conversion reactor. These input parameters are preferably provided automatically and continuously.

[0147] In a step S5 of the method, an estimated fuel quality parameter of the transportation range fuel is calculated based on the set of input parameters and based on a composition of the one or more oxygenate products. This composition may also be provided as an input parameter, for example based on a recycle-to-oxygenate feed gas ratio. Alternatively, it may be pre-set in the process controlling arrangement.

[0148] In a step S6 of the method, the estimated fuel quality parameter is compared with the target fuel quality parameter. This comparison may be performed in the process controlling arrangement. An output of such a this comparison may, for example, be a numerical difference between the estimated fuel quality parameters and the target fuel quality parameter.

[0149] In a step S7 of the method, the inlet temperature and / or a recycle-to-oxygenate feed gas ratio is adjusted based on a difference between the estimated fuel quality parameter and the target fuel quality parameter. This adjustment may, for example, be proportional to a numerical difference between the estimated fuel quality parameters and the target fuel quality parameter. The adjustment may be implemented as a proportional-integral-derivate controlling scheme.

[0150] Thereby, a transportation range fuel can be produced accurately with respect to a desired fuel quality parameter while ensuring a high yield.

[0151] Fig. 5a-b illustrate results of a simulation which exemplifies potential improvements provided according to examples of the present disclosure.

[0152] The simulation considers a single conversion reactor operating over a 30-day cycle, which corresponds to a normalized time of 1. The fuel quality parameter considered is the research octane number, RON.

[0153] The conversion of oxygenate compounds is simulated, and an estimated fuel quality parameter is calculated based on the converted oxygenate product. If the estimated RON deviates from the target RON, the temperature is adjusted accordingly applying simple Boolean control strategy, where the temperature is adjusted in a step-wise manner whenever the estimated RON deviates from the target RON by more than a threshold. The resulting temperature is illustrated in Fig. 5a as a solid line 14 on a normalised scale. The temperature increases in a stepwise manner throughout the normalised time as a result of the control. Fig. 5b shows the resulting estimated RON on a normalised scale. The target RON is illustrated as a horizontal dashed line, and the estimated RON 14 exhibits a sawtooth like behaviour as a result of the control.

[0154] The results of operation based on a fuel quality parameter (RON) 14 are compared to a simulation based on high-temperature operation 15 (suboptimal) and a simulation based on low-temperature operation 16 (suboptimal). When the reactor operates at too high a temperature, RON exceeds the target value. Elevated temperatures promote secondary reactions that form C4- species, reducing productivity, and also accelerate catalyst deactivation due to increased dealumination, both of which negatively impact process performance. This also results in increased production of aromatics, decreased yield due to secondary cracking and excessive aromatics formation, and reduced catalyst lifetime.

[0155] Operating at lower temperatures is also suboptimal; despite favouring yield and catalyst lifetime, it fails to meet the required RON, i.e. the target octane number is not reached. This results in a fuel which do not meet required specifications.

[0156] The truly optimal approach involves dynamically adjusting reaction conditions, here the inlet temperature, to counteract catalyst deactivation while consistently achieving the target octane number. In this way, the desired octane value becomes a strict constraint that must always be met. Operating at this value ensures maximum product yield and extends catalyst lifetime, while delivering exactly what is required by the process.

[0157] The simulation highlights this operational trade-off. Lower temperatures are beneficial for yield and catalyst longevity but compromise fuel quality. Higher temperatures achieve the desired (or even excessive) RON but at the cost of yield and catalyst life. This creates an optimization dilemma, particularly in real-world plants with multiple reactors operating under varying conditions and at different points in their cycles.

[0158] The aspects and examples according to the present disclosure exemplified herein address this challenge by enabling individual optimization of a respective reactor by modelling a relevant fuel quality parameter and combining this with control of operation through, e.g., a simple control algorithm. This approach ensures that each reactor, regardless of its age, activity level, or operating condition, produces fuel with RON precisely at the setpoint. As the above simulation demonstrates, over-optimizing RON brings diminishing returns and unacceptable side effects. Examples herein enforce a fuel quality parameter as a constraint, ensuring consistent product quality while minimizing the trade-offs traditionally associated with reactor temperature control.

[0159] Fig. 3 and the corresponding description outlines one example of a detailed procedure for calculating an estimated fuel quality parameter. The reactor activities and the product species composition are separately calculated based on the set of input parameters, and based on these, an estimated fuel quality parameter is calculated. This can be performed by a combination of numerically solved differential equations and one or more machine-learning models, which in combination can provide an accurate and fast estimated fuel quality parameter.

[0160] Although it is generally preferably to provide a calculation of an estimated fuel quality parameter which is both accurate and fast, in principle, any scheme for calculating the estimated fuel quality parameter can be employed within the scope of the present disclosure.

[0161] As one example, the entire calculation may be performed by a machine learning model, which, during operation, receives the input parameters to the output the estimated fuel quality parameter. Such a model may be trained on data of an actual plant in operation, on data of a pilot plant, on data obtained frrm simulation, or on data from some combination thereof. Preferably, such test data should at least correlate the input parameters with the relevant fuel quality parameter. Test data may preferably also include data relating to reactor activities and / or species composition of the converted oxygenate product.

[0162] Examples as to how a fuel quality parameter, such as an octane number, can be calculated both with and without relying on machine learning are available from, for example, Correa Gonzalez, Sandra, et al. "Prediction of gasoline blend ignition characteristics using machine learning models." Energy & Fuels 35.11 (2021): 9332-9340; Corrubia, Julius A., et al. "RON and MON chemical kinetic modeling derived correlations with ignition delay time for gasoline and octane boosting additives." Combustion and flame 219 (2020): 359-372; and Pulga, Leonardo, et al. "Comparison between Conventional and Non-Conventional Computer Methods to Define Antiknock Properties of Fuel Mixtures." Fuels 3.2 (2022): 217-231.

[0163] A calculation of a fuel quality parameter may be based on a product species composition, such as PIONA. Examples as to how a product species composition can be calculated are available from, for example, Choe, Jina, et al. "Novel kinetic modelling of methanol-to-gasoline (MTG) reaction on HZSM-5 catalyst: Product distribution." Journal of the Indian Chemical Society 98.2 (2021): 100003; and Abdulghaffari, A. S., and M. Kazemeini. "A lumped reaction kinetic model developed for conversion of methanol to gasoline upon an HZSM-5 catalyst". These examples primarily relate to calculation of a fuel quality parameter in the form of an octane number. However, the outlined principles can be extended to any type of fuel quality parameter.

[0164] List of figure references:

[0165] 1 reactor system

[0166] 2 conversion reactor

[0167] 3 process controlling arrangement

[0168] 4 oxygenate compound inlet

[0169] 5 process control parameters

[0170] 6 input parameters

[0171] 7 fuel quality calculator

[0172] 8 fuel quality evaluator

[0173] 9 target fuel quality parameter

[0174] 10 estimated fuel quality parameter

[0175] 11 activity module

[0176] 12 product composition module

[0177] 13 fuel quality calculation module

[0178] 14 operation based on fuel quality parameter

[0179] 15 high-temperature operation (suboptimal operation)

[0180] 16 low-temperature operation (suboptimal operation)

[0181] S1-S7 method steps

Claims

CLAIMS1. A process for the conversion of oxygenates to a transportation range fuel, the process comprising the steps of:setting a target fuel quality parameter of the transportation range fuel in a process controlling arrangement;feeding one or more oxygenate compounds to a conversion reactor, the one or more oxygenate compounds being fed to the conversion reactor with a space velocity and a controlled inlet temperature;converting the one or more oxygenate compounds to a converted oxygenate product in the conversion reactor in the presence of a catalyst, the converted oxygenate product comprising the transportation range fuel;providing a set of input parameters to the process controlling arrangement, the set of input parameters comprising the space velocity and a bed temperature profile, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature;calculating an estimated fuel quality parameter of the transportation range fuel in the process controlling arrangement based on the set of input parameters and based on a composition of the one or more oxygenate compounds;comparing the estimated fuel quality parameter with the target fuel quality parameter in the process controlling arrangement; andadjusting the inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated fuel quality parameter and the target fuel quality parameter,wherein the transportation range fuel is any of a gasoline product, a jet fuel product, and a diesel product,wherein the fuel quality parameter is any of octane number, sulphur content, aromatics content, volatility, and distillation curve characteristics when the transportation range fuel is a gasoline product,wherein the fuel quality parameter is any of flash point, freezing point, smoke point, thermal stability, aromatics content, and energy density when the transportation range fuel is a jet fuel product,wherein the fuel quality parameter is any of cetane number, cold filter plugging point, cloud point, sulphur content, density, and lubricity when the transportation range fuel is a diesel product.

2. The process of claim 1,wherein the target fuel quality parameter is a target octane number and the estimated fuel quality parameter is an estimated octane number when the transportation range fuel is a gasoline product,wherein the target fuel quality parameter is a target cetane number and the estimated fuel quality parameter is an estimated cetane number when the transportation range fuel is a diesel product,wherein the target fuel quality parameter is a target product density, a target aviation lean rating, or a target aviation rich rating and the estimated fuel quality parameter is an estimated product density, an estimated aviation lean rating, or an estimated aviation rich rating when the transportation range fuel is a jet fuel product.

3. The process according to any of the preceding claims, wherein the step of calculating the estimated fuel quality parameter comprises the sub-steps of:calculating a reactor activity based on the set of input parameters, the reactor activity comprising an irreversible activity from reactor acidity and a reversible activity from coking;calculating a species composition of the converted oxygenate product based on the set of input parameters, the reactor activities, and the composition of the one or more oxygenate compounds, the species composition comprising an aromatic concentration and an olefin concentration; andcalculating the estimated fuel quality parameter based on the species composition.

4. The process of claim 3, wherein the sub-step of calculating the reactor activity is performed via differential equations, such as ordinary differential equations, in which the reactor activity is numerically calculated based on the set of input parameters.

5. The process of any of the preceding claims, wherein the step of calculating the estimated fuel quality parameter is performed using a computer model which correlates the set of input parameters and the composition of the one or more oxygenate compounds with the estimated fuel quality parameter.

6. The process of claim 5, wherein the computer model comprises a machine-learning model, such as a neural network, which has been trained on a test data set.

7. The process of any one of claims 5-6, wherein the computer model is configured to perform the sub-steps of: calculating the species composition; and / or calculating the estimated fuel quality parameter.

8. The process of any one of claims 5-7, wherein the test data set comprises data relating any of the input parameters, the composition of the one or more oxygenate compounds, the reactor activity, and the species composition to the estimated fuel quality parameter.

9. The process of any of the preceding claims, wherein the step of adjusting the inlet temperature and / or the recycle-to-oxygenate feed gas ratio comprises:decreasing or maintaining the inlet temperature when the estimated fuel quality parameter is greater than the target fuel quality parameter; andincreasing the inlet temperature when the estimated fuel quality parameter is smaller than the target fuel quality parameter.

10. The process of any of the preceding claims, wherein the steps of calculating an estimated fuel quality parameter and adjusting the inlet temperature and / or the recycle-to-oxygenate feed gas ratio are performed during the step of converting the one or more oxygenate compounds.

11. The process of any of the preceding claims, wherein the step of adjusting the inlet temperature is performed iteratively based on iteratively calculating the estimated fuel quality parameter.

12. The process of any of the preceding claims, wherein said process is performed using a plurality of conversion reactors, wherein the target fuel quality parameter is a common target fuel quality parameter for each reactor of the plurality of conversion reactors, wherein the inlet temperature is controlled independently for each reactor of the plurality of conversion reactors, wherein the steps of converting the one or more oxygenate compounds, providing the set of input parameters, calculating the estimated fuel quality parameter, and adjusting the inlet temperature and / or the recycle-to-oxygenate feed gas ratio are performed independently for each reactor of the plurality of conversion reactors.

13. A reactor system comprising:a conversion reactor for converting one or more oxygenate compounds to a converted oxygenate product in the presence of a catalyst, the converted oxygenate product comprising a transportation range fuel;an oxygenate compound inlet for feeding one or more oxygenate compounds to the conversion reactor with a space velocity; anda process controlling arrangement, wherein the process controlling arrangement is configured to:receive a target fuel quality parameter of the transportation range fuel;control an inlet temperature at which the one or more oxygenate compounds are fed to the conversion reactor;calculate an estimated fuel quality parameter of the transportation range fuel based on a set of input parameters and based on a composition of the one or more oxygenate compounds, the set of input parameters comprising the space velocity and a bed temperature profile, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature;compare the estimated fuel quality parameter with the target fuel quality parameter; andadjust the inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated fuel quality parameter and the target fuel quality parameter,wherein the transportation range fuel is any of a gasoline product, a jet fuel product, and a diesel product,wherein the fuel quality parameter is any of octane number, sulphur content, aromatics content, volatility, and distillation curve characteristics when the transportation range fuel is a gasoline product,wherein the fuel quality parameter is any of flash point, freezing point, smoke point, thermal stability, aromatics content, and energy density when the transportation range fuel is a jet fuel product,wherein the fuel quality parameter is any of cetane number, cold filter plugging point, cloud point, sulphur content, density, and lubricity when the transportation range fuel is a diesel product.

14. A reactor system according to claim 13, wherein the process controlling arrangement is arranged to perform the method according to any of claims 1-12.

15. A computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of:receiving a target fuel quality parameter of a transportation range fuel;controlling an inlet temperature at which one or more oxygenate compounds are fed to a conversion reactor for converting one or more oxygenate compounds to a converted oxygenate product in the presence of a catalyst, the converted oxygenate product comprising the transportation range fuel;calculating an estimated fuel quality parameter of the transportation range fuel based on a set of input parameters and based on a composition of the one or more oxygenate compounds, the set of input parameters comprising a space velocity at which the one or more oxygenate compounds are fed to the conversion reactor and a bed temperature profile, the bed temperature profile comprising the inlet temperature, a bed temperature, and an outlet temperature;comparing the estimated fuel quality parameter with the target fuel quality parameter; andadjusting the inlet temperature and / or a recycle-to-oxygenate feed gas ratio based on a difference between the estimated fuel quality parameter and the target fuel quality parameter,wherein the transportation range fuel is any of a gasoline product, a jet fuel product, and a diesel product,wherein the fuel quality parameter is any of octane number, sulphur content, aromatics content, volatility, and distillation curve characteristics when the transportation range fuel is a gasoline product,wherein the fuel quality parameter is any of flash point, freezing point, smoke point, thermal stability, aromatics content, and energy density when the transportation range fuel is a jet fuel product,wherein the fuel quality parameter is any of cetane number, cold filter plugging point, cloud point, sulphur content, density, and lubricity when the transportation range fuel is a diesel product.

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