CN112750503A - Storage, hydrogen utilization maximization-based hydrogen network optimization method, device and equipment - Google Patents
Storage, hydrogen utilization maximization-based hydrogen network optimization method, device and equipment Download PDFInfo
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- 239000001257 hydrogen Substances 0.000 title claims abstract description 335
- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 335
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 238
- 238000005457 optimization Methods 0.000 title claims abstract description 99
- 150000002431 hydrogen Chemical class 0.000 title claims abstract description 96
- 238000000034 method Methods 0.000 title claims abstract description 49
- 238000003860 storage Methods 0.000 title abstract description 14
- 238000006243 chemical reaction Methods 0.000 claims abstract description 95
- 238000006477 desulfuration reaction Methods 0.000 claims abstract description 30
- 230000023556 desulfurization Effects 0.000 claims abstract description 30
- 229930195733 hydrocarbon Natural products 0.000 claims abstract description 29
- 150000002430 hydrocarbons Chemical class 0.000 claims abstract description 29
- 238000000746 purification Methods 0.000 claims description 35
- 238000005984 hydrogenation reaction Methods 0.000 claims description 23
- 239000007789 gas Substances 0.000 claims description 21
- 239000004215 Carbon black (E152) Substances 0.000 claims description 19
- 239000000203 mixture Substances 0.000 claims description 19
- 239000000446 fuel Substances 0.000 claims description 15
- 238000013461 design Methods 0.000 claims description 13
- 230000006835 compression Effects 0.000 claims description 12
- 238000007906 compression Methods 0.000 claims description 12
- 239000002737 fuel gas Substances 0.000 claims description 12
- 230000004913 activation Effects 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 9
- 239000002283 diesel fuel Substances 0.000 claims description 8
- 230000006870 function Effects 0.000 claims description 8
- 125000005575 polycyclic aromatic hydrocarbon group Chemical group 0.000 claims description 8
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 7
- 229910052717 sulfur Inorganic materials 0.000 claims description 7
- 239000011593 sulfur Substances 0.000 claims description 7
- 239000003054 catalyst Substances 0.000 claims description 6
- 239000002994 raw material Substances 0.000 claims description 6
- -1 reactor parameters Substances 0.000 claims description 6
- 238000011084 recovery Methods 0.000 claims description 6
- 230000005611 electricity Effects 0.000 claims description 3
- 230000008569 process Effects 0.000 claims description 3
- 239000000376 reactant Substances 0.000 claims description 3
- 230000001502 supplementing effect Effects 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims description 3
- 230000008901 benefit Effects 0.000 abstract description 7
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 abstract description 6
- 229910052760 oxygen Inorganic materials 0.000 abstract description 6
- 239000001301 oxygen Substances 0.000 abstract description 6
- 239000003921 oil Substances 0.000 description 17
- 238000010586 diagram Methods 0.000 description 5
- 239000000463 material Substances 0.000 description 5
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- 238000005859 coupling reaction Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 239000010779 crude oil Substances 0.000 description 2
- 238000009903 catalytic hydrogenation reaction Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 125000004435 hydrogen atom Chemical group [H]* 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
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- 238000007670 refining Methods 0.000 description 1
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Abstract
The invention discloses a storage, a hydrogen network optimization method based on hydrogen utilization maximization, a device and equipment, wherein the method comprises the following steps: establishing a multi-lumped reaction kinetic model and a hydrogen network optimization model; taking specific working condition data as an input parameter, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard; outputting a new hydrogen boundary condition and the generation amount of micromolecular hydrocarbons to a preset hydrogen network optimization model; generating an oxygen supply scheme according to the hydrogen network optimization model; the method can be suitable for obtaining accurate results under various working conditions, further can obtain a practical and feasible optimization scheme, and has remarkable economic benefit.
Description
Technical Field
The invention relates to the field of industrial measurement, in particular to a storage, a hydrogen network optimization method based on hydrogen utilization maximization, a device and equipment.
Background
In order to meet the requirements of crude oil deterioration, product quality upgrading, clean production and the like, the processing capacity of a catalytic hydrogenation device of a refinery is continuously increased, and the operation severity is also continuously increased, so that the demand of hydrogen is increased, and the hydrogen becomes the second most cost factor of the raw material cost of the refinery, which is next to the crude oil cost. Therefore, how to reduce the hydrogen cost becomes a very concerned issue for oil refining enterprises; the hydrogen consumption cost of the refinery is reduced by optimizing the hydrogen network in a mode of improving the management level of the hydrogen of the refinery, and remarkable economic benefit can be obtained.
The design and optimization researchers of the hydrogen network propose a mathematical programming method, and the hydrogen network is optimized through specific constraint conditions according to a set objective function; the specific optimization method in the prior art includes:
and (3) returning the data of the current working condition according to the principle of material conservation by referring to the change of the raw materials and the product compositions of the hydrogen consumption units, developing a material consumption/generation model of the hydrogen consumption device, and establishing a detailed model of hydrogen network optimization.
The inventor finds that the optimization mode in the prior art is more suitable for refineries with single processed oil product and single operation working condition; when the oil type processed by the refinery in China is complex and changeable and the operation working conditions are also changed frequently, the product properties and the material consumption under other working conditions are calculated through the material consumption/generation model regressed by the material balance data under the single working condition, so that the result accuracy is poor and a good optimization effect cannot be achieved.
Therefore, the hydrogen pipe network optimization scheme in the prior art cannot be applied to application scenes with variable working conditions in our country.
The information disclosed in this background section is only for enhancement of understanding of the general background of the invention and should not be taken as an acknowledgement or any form of suggestion that this information forms the prior art already known to a person skilled in the art.
Disclosure of Invention
The invention aims to provide an optimization scheme of a refinery hydrogen resource suitable for various working conditions.
The invention provides a hydrogen network optimization method based on hydrogen utilization maximization, which comprises the following steps:
s11, establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, by using the increase of hydrogen consumption as an available means and the maximum goal of hydrogen network operation income; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model;
s12, using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard;
s13, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to a preset hydrogen network optimization model;
and S14, generating a hydrogen supply scheme of the hydrogen network according to the hydrogen network optimization model.
In the invention, the desulfurization reaction kinetic model is established according to a diesel hydrodesulfurization process and comprises the following steps:
through industrial device data including sulfur composition, reactor parameters, catalyst loading parameters and reaction conditions of raw diesel, regression is performed on preset parameters in a rate equation of a desulfurization reaction kinetic model to determine pre-index parameters, pre-index factors, apparent activation energy and hydrogen partial pressure indexes of the rate equation, and the method comprises the following steps:
s111, acquiring industrial device data including sulfur composition, reactor parameters, catalyst filling parameters and reaction conditions of raw diesel oil;
s112, setting initial values of the pre-indication parameter, the apparent activation energy and the hydrogen partial pressure index;
s113, calculating the reaction rate of the inlet of the reactor; calculating the reaction rate and reactant concentration of each bed layer; calculating the outlet temperature and product properties of the reactor;
s114, obtaining a parameter value of a specific parameter of a desulfurization reaction kinetic model through regression calculation by taking the minimum sum of the calculated values of the outlet temperature and the product properties of the reactor and the variance of an actual measured value as a target function; the specific parameters include pre-finger parameters, pre-finger factors, apparent activation energy and hydrogen partial pressure index.
In the invention, on the premise of not increasing the equipment investment, the hydrogen consumption is increased as an available means, and the maximum income of the hydrogen network operation is used as an objective, the hydrogen network optimization model is established, and the method comprises the following steps:
s121, setting a calculation formula of an objective function of the hydrogen network optimization model as follows:
MaxCoptimization＝△Cproducer-△CConsumer-△Cpurification-△Cfuelformula (1);
wherein, MaxCoptimizationFor the sum of the gains of the hydrogen network obtained by optimization,. DELTA.CproducerHydrogen yield, Δ C, from reduced supply for hydrogen utilitiesLHOptimized light hydrocarbon yield,. DELTA.CConsumerFor increased operating costs, Δ C, after changes in hydrogen conditions for the hydrogen consuming devicepurificationFor the increased operating cost, Delta C, after the change of the raw material of the purification apparatusfuelRecovering hydrogen and light hydrocarbon and supplementing fuel gas value to the fuel gas pipe network;
and S122, setting constraint conditions comprising compressor constraint, purification device constraint, hydrogen source constraint and hydrogen trap constraint.
In the present invention, the method comprises:
according to the formula: delta Cproducer＝∑ipriceproducer×ΔFiEquation (2); obtaining said Δ Cproducer(ii) a Wherein the priceiIs the unit price from the ith hydrogen utility; said Δ FiIs the hydrogen flow rate from the ith hydrogen utility.
In the present invention, the method comprises:
according to the formula:
and,
the formula:
obtaining said Δ CConsumer；
Wherein, Wp: represents the compression power per mole of inlet gas; cpv: denotes the heat capacity ratio Cp/CvCalculating according to the feeding composition by a second dimensional force coefficient model; t: indicating the compressor inlet temperature, which cannot exceed 50 ℃; poutlet: represents the compressor outlet pressure; pinlet: represents the compressor inlet pressure; n iscmp: representing the compression stage number; etaeff-ise-1: representing compressor isentropic efficiency; etaeff-mec: indicating compressor mechanical efficiency; r: represents a gas constant; t is0: 273.15K; wp,i,MThe compression power of a new hydrogen compressor of the ith hydrogenation unit per mole of inlet gas; n isi,MakeupThe mole number of the hydrogen at the inlet of a new hydrogen compressor of the ith hydrogenation unit; wp,i,RThe compression power of the recycle hydrogen compressor of the ith hydrogenation unit per mol of inlet gas; n isi,RecycleThe mole number of the hydrogen at the inlet of the recycle hydrogen compressor of the ith hydrogenation unit; priceeThe price of the local industrial electricity used by the oil refinery.
In the present invention, the method comprises:
according to the formula: delta Cpurification＝△CPress,Purification+△CFlowrateEquation (5); obtaining said Δ Cpurification(ii) a Wherein, Δ CPress,PurificationIncrease of operating cost of the compressor; delta CFlowrateThe operating cost for the purification apparatus after the change of the throughput is increased;
according to the formula:
obtaining said Δ Cfuel(ii) a Wherein, CLHIs the price of light hydrocarbon per unit volume, HLHIs the heat value of the unit volume of light hydrocarbon;
in terms of the price per unit volume of hydrogen,
the calorific value per unit volume of hydrogen; hfuelHeat value of fuel gas per unit volume, CfuelIs the price of fuel gas per unit volume.
In the present invention, the setting of constraint conditions including a compressor constraint, a purification device constraint, a hydrogen source constraint, and a hydrogen trap constraint includes:
compressor restraint: the compressor inlet gas volume must meet the design throughput requirement, and to prevent surge inlet gas from occurring should also meet the design minimum hydrogen concentration requirement, the formula for setting the compressor constraints may include:
ΣiFi，comp≤Fcompmaxformula (7)
∑i(Fi，comp×yi)≥∑iFi，comp×yminFormula (8)
Wherein, FcompmaxTo pressMaximum air intake amount allowed by the compressor, Fi，compFlow of hydrogen stream to compressor for ith hydrogen source, ycompIs the compressor outlet hydrogen concentration.
And (3) restricting a purifying device: the inlet gas flow of the purification device should be less than the designed maximum throughput of the device; the formula for setting the constraints of the purification apparatus may include:
∑iFi，PSA≤FPSAMAXformula (9)
Wherein, Fi，PSAFor the ith stream flow entering the purification plant, FPSAMAXThe maximum design throughput for the PSA unit.
Hydrogen source restraint: the sum of all output streams is required to be less than or equal to the total output flow of the hydrogen source, and the formula for setting the hydrogen source constraint can comprise:
∑jFi，j≤Fi，sourceformula (10)
Wherein, Fi，jThe flow of the ith hydrogen source to the jth hydrogen trap; fi，sourceThe total amount of hydrogen produced for the ith hydrogen source in unit time;
the formula for setting hydrogen source constraints may include:
∑iFi，j＝Fjformula (11)
The meaning of formula (11) is: the supply quantity of the hydrogen trap j is equal to the sum of the supply quantities of all hydrogen sources;
∑iFi，j·yi，j＝Fj·yjformula (12)
The meaning of formula (12) is: the pure hydrogen supply quantity of the hydrogen trap j is equal to the sum of the pure hydrogen supply quantities supplied by all the hydrogen sources;
the meaning of formula (13) is: the pure hydrogen supply amount of any one of the hydrogen traps is larger than the 'minimum pure hydrogen supply amount' of the hydrogen trap;
the meaning of formula (14) is: the hydrogen supply purity of any one of the hydrogen traps is greater than the minimum hydrogen supply purity of the hydrogen trap and is less than 1;
the formula for setting light hydrocarbon constraints may include:
∑iFi，LHR≤FLHRMAXformula (15)
Wherein, Fi，LHRFor the ith stream flow entering the light hydrocarbon recovery plant, FPSAMAXThe method is the maximum design treatment of a light hydrocarbon recovery device.
In another aspect of the embodiments of the present invention, there is also provided a hydrogen grid optimization apparatus based on hydrogen utilization maximization, including:
the system comprises a presetting unit, a hydrogen network optimization unit and a control unit, wherein the presetting unit is used for establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, taking increasing of hydrogen gas consumption as an available means and taking the maximum operation income of a hydrogen network as an objective; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model;
an oil quality verification unit for performing: using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard;
the parameter output unit outputs a new hydrogen boundary condition and the generation amount of micromolecular hydrocarbons to a preset hydrogen network optimization model;
and the scheme generation unit is used for generating an oxygen supply scheme according to the hydrogen network optimization model.
In another aspect of the embodiments of the present invention, there is also provided a memory including a software program adapted to execute the steps of the above-mentioned hydrogen grid optimization method based on hydrogen utilization maximization by a processor.
In another aspect of the embodiments of the present invention, there is also provided a hydrogen network optimization apparatus based on hydrogen utilization maximization, which includes a computer program stored on a memory, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the method of the above aspects and achieve the same technical effects.
Compared with the prior art, the invention has the following beneficial effects:
according to the invention, firstly, a desulfurization reaction kinetic model and a hydrogen network optimization model which can be suitable for various working conditions are respectively established, and then the desulfurization reaction kinetic model and the hydrogen network optimization model are integrated, so that the technical scheme in the embodiment of the invention can be suitable for various working conditions to obtain accurate results after optimizing and correlating the hydrogenation device while optimizing the hydrogen network, and further can obtain a practical and feasible optimization scheme, and has remarkable economic benefits.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical means of the present invention more clearly understood and to make the technical means implementable in accordance with the contents of the description, and to make the above and other objects, technical features, and advantages of the present invention more comprehensible, one or more preferred embodiments are described below in detail with reference to the accompanying drawings.
Drawings
FIG. 1 is a diagram of the steps of a hydrogen net optimization method based on hydrogen utilization maximization according to the present invention;
FIG. 2 is a diagram of the steps for constructing the kinetic model of desulfurization reaction according to the present invention;
FIG. 3 is a schematic flow chart of the present invention for constructing a kinetic model of desulfurization reaction;
FIG. 4 is a schematic diagram of the configuration of the hydrogen net optimization device based on hydrogen utilization maximization according to the invention;
fig. 5 is a schematic structural view of a hydrogen net optimization apparatus based on hydrogen utilization maximization according to the present invention.
Detailed Description
The following detailed description of the present invention is provided in conjunction with the accompanying drawings, but it should be understood that the scope of the present invention is not limited to the specific embodiments.
Throughout the specification and claims, unless explicitly stated otherwise, the word "comprise", or variations such as "comprises" or "comprising", will be understood to imply the inclusion of a stated element or component but not the exclusion of any other element or component.
Spatially relative terms, such as "below," "lower," "upper," "above," "upper," and the like, may be used herein for ease of description to describe one element or feature's relationship to another element or feature in the figures. It will be understood that the spatially relative terms are intended to encompass different orientations of the object in use or operation in addition to the orientation depicted in the figures. For example, if the items in the figures are turned over, elements described as "below" or "beneath" other elements or features would then be oriented "above" the elements or features. Thus, the exemplary term "below" can encompass both an orientation of below and above. The article may be otherwise oriented (rotated 90 degrees or at other orientations) and the spatially relative terms used herein should be interpreted accordingly.
In this document, the terms "first", "second", etc. are used to distinguish two different elements or portions, and are not used to define a particular position or relative relationship. In other words, the terms "first," "second," and the like may also be interchanged with one another in some embodiments.
In order to provide an optimization scheme of refinery hydrogen resources applicable to various working conditions, as shown in fig. 1, in an embodiment of the present invention, a hydrogen grid optimization method based on hydrogen utilization maximization is provided, including the steps of:
s11, establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, by using the increase of hydrogen consumption as an available means and the maximum goal of hydrogen network operation income; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model
The core invention thought of the embodiment of the invention comprises the following steps: integrating a reaction kinetics model and a hydrogen network optimization model to obtain hydrogen network optimization, wherein the reaction kinetics model is constructed firstly; in practical applications, the reaction kinetic model may include a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model, or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model.
The specific working condition data in the embodiment of the invention refers to parameters related to whether the product property data corresponding to the current working condition is judged to meet the preset quality standard or not through the reaction dynamics model in the hydrogen network parameters, and specifically, the specific working condition data can comprise oil product properties, new hydrogen composition, new hydrogen flow and the like. The method comprises adjustable parameters such as new hydrogen composition and new hydrogen flow, and fixed parameters such as oil properties.
In order to ensure that the quality of refinery products (such as diesel oil or wax oil hydrotreating products) can meet preset standards, a corresponding dynamic model needs to be constructed to predict the product properties, so that a combination mode of specific working condition data is obtained on the premise of ensuring the product quality.
Taking the refinery product as diesel oil and the reaction kinetic model as a hydrodesulfurization reaction kinetic model as an example, for a diesel oil hydrogenation device, the sulfur content in the product is a key constraint condition of an integrated model, so that the desulfurization reaction kinetic model of the diesel oil needs to be constructed firstly.
The method specifically comprises the following steps: establishing a multi-lumped desulfurization reaction kinetic model, generally, determining a pre-index parameter k of a rate equation of a desulfurization reaction kinetic model by performing regression on preset parameters in the rate equation through industrial device data including sulfur composition, reactor parameters, catalyst loading parameters and reaction conditions of raw diesel oil0，iPre-finger factor, apparent activation energy EaiAnd hydrogen partial pressure index ni。
In the embodiment of the present invention, a preferred scheme is to establish a four-lumped desulfurization reaction kinetic model, and a specific process of the model can be as shown in fig. 2, which includes:
s111, determining the properties of the raw materials at the inlet of the reactor and reaction conditions, wherein the determination comprises the following steps: acquiring industrial device data comprising sulfur composition, reactor parameters, catalyst filling parameters and reaction conditions of raw diesel oil;
s112, setting the pre-pointing parameter k0，iThe apparent activation energy EaiAnd the hydrogen partial pressure index niAn initial value of (1);
s113, calculating the reaction rate of the inlet of the reactor; calculating the reaction rate and reactant concentration of each bed layer; calculating the outlet temperature and product properties of the reactor;
s114, obtaining a parameter value of a specific parameter of a desulfurization reaction kinetic model through regression calculation by taking the minimum sum of the calculated values of the outlet temperature and the product properties of the reactor and the variance of an actual measured value as a target function; the specific parameter comprises a pre-finger parameter k0，iPre-finger factor, apparent activation energy EaiAnd hydrogen partial pressure index ni；
In this step, the following can be expressed by the formula: obj ═ Min (SUM ((T))cal-Tmeas)2+(Cj,cal–Cj,meas)2) And, determining the conditional expression: obj is less than or equal to sigma, regression calculation is realized to obtain the final pre-pointing parameter k of the desulfurization reaction kinetic model0，iPre-finger factor, apparent activation energy EaiAnd, hydrogen partial pressure index ni。
The following experimental results verify the accuracy of the method for establishing the multi-lumped desulfurization reaction kinetic model in the embodiment of the invention:
the kinetic parameters of the device reaction obtained through steps S111 to S114 are shown in table one:
table 1:
then, experimental result data under ten reaction conditions are respectively collected, and estimation result data obtained by calculation of the desulfurization reaction kinetic model in the embodiment of the invention under corresponding conditions are obtained and compared, and the comparison result is shown in table 2:
table 2:
from the above, it can be seen that the estimation results calculated by the desulfurization reaction kinetic model in the embodiment of the present invention have errors within a range of ± 5%, which indicates that the desulfurization reaction kinetic model in the embodiment of the present invention well conforms to the actual situation, and has a good industrial application value.
The application scenarios of the embodiment of the invention are as follows: because the occupation of land or fund is limited, the refinery can not install new equipment or pipelines, and meanwhile, the hydrogen resource source is wide and not in short supply, but the waste of the hydrogen resource causes the poor overall benefit of the refinery. In this case, the optimization principle of the hydrogen network is as follows: no new equipment or pipeline investment is added; and comprehensively recovering the resources of the hydrogen-rich flow under the guidance of the maximized economic benefit.
Based on the above, the network optimization model in the embodiment of the present invention may be constructed in the following manner: on the premise of not increasing equipment investment, increasing hydrogen consumption is used as an available means, and the maximum income of hydrogen network operation is an objective, the method is constructed, and specifically:
s121, setting a calculation formula of an objective function of the hydrogen network optimization model as follows:
MaxCoptimization＝△Cproducer-△CConsumer-△Cpurification-△Cfuelformula (1);
wherein, MaxCoptimizationFor the sum of the gains of the hydrogen network obtained by optimization，△CproducerHydrogen yield, Δ C, from reduced supply for hydrogen utilitiesLHOptimized light hydrocarbon yield,. DELTA.CConsumerFor increased operating costs, Δ C, after changes in hydrogen conditions for the hydrogen consuming devicepurificationFor the increased operating cost, Delta C, after the change of the raw material of the purification apparatusfuelRecovering hydrogen and light hydrocarbon and supplementing fuel gas value to the fuel gas pipe network;
in formula (1), the specific values of the respective parameters may be calculated as follows:
according to the formula: delta Cproducer＝∑ipriceproducer×ΔFiEquation (2); obtaining said Δ Cproducer(ii) a Wherein the priceiIs the unit price from the ith hydrogen utility; said Δ FiIs the hydrogen flow rate from the ith hydrogen utility.
According to the formula:
and,
the formula:
obtaining said Δ CConsumer；
Wherein, Wp: represents the compression power per mole of inlet gas; cpv: denotes the heat capacity ratio Cp/CvCalculating according to the feeding composition by a second dimensional force coefficient model; t: indicating the compressor inlet temperature, which cannot exceed 50 ℃; poutlet: represents the compressor outlet pressure; pinlet: represents the compressor inlet pressure; n iscmp: representing the compression stage number; etaeff-ise-1: representing compressor isentropic efficiency; etaeff-mec: indicating compressor mechanical efficiency; r: represents a gas constant; t is0: 273.15K; wp,i,MThe compression power of a new hydrogen compressor of the ith hydrogenation unit per mole of inlet gas; n isi,MakeupIs the ithThe mole number of hydrogen at the inlet of a fresh hydrogen compressor of the hydrogenation device; wp,i,RThe compression power of the recycle hydrogen compressor of the ith hydrogenation unit per mol of inlet gas; n isi,RecycleThe mole number of the hydrogen at the inlet of the recycle hydrogen compressor of the ith hydrogenation unit; priceeThe price of the local industrial electricity used by the oil refinery.
According to the formula: delta Cpurification＝△CPress,Purification+△CFlowrateEquation (5); obtaining said Δ Cpurification(ii) a Wherein, Δ CPress,PurificationIncrease of operating cost of the compressor; delta CFlowrateThe operating cost for the purification apparatus after the change of the throughput is increased;
according to the formula:
obtaining said Δ Cfuel(ii) a Wherein the content of the first and second substances,
in terms of the price per unit volume of hydrogen,
the calorific value per unit volume of hydrogen; hfuelHeat value of fuel gas per unit volume, CfuelIs the price of fuel gas per unit volume.
S122, setting constraint conditions including compressor constraint, purification device constraint, hydrogen source constraint and hydrogen trap constraint, and specifically including:
compressor restraint: the compressor inlet gas volume must meet the design throughput requirement, and to prevent surge inlet gas from occurring should also meet the design minimum hydrogen concentration requirement, the formula for setting the compressor constraints may include:
∑iFi，comp≤Fcompmaxformula (7)
∑i(Fi，comp×yi)≥∑iFi，comp×ymin Formula (8)
Wherein, FcompmaxMaximum air intake amount allowed for the compressor, Fi，compFlow of hydrogen stream to compressor for ith hydrogen source, ycompIs the compressor outlet hydrogen concentration.
And (3) restricting a purifying device: the inlet gas flow of the purification device should be less than the designed maximum throughput of the device; the formula for setting the constraints of the purification apparatus may include:
∑iFi，PSA≤FPSAMAXformula (9)
Wherein, Fi，PSAFor the ith stream flow entering the purification plant, FPSAMAXThe maximum design throughput for the PSA unit.
Hydrogen source restraint: the sum of all output streams is required to be less than or equal to the total output flow of the hydrogen source, and the formula for setting the hydrogen source constraint can comprise:
∑jFi，j≤Fi，sourceformula (10)
Wherein, Fi，jThe flow of the ith hydrogen source to the jth hydrogen trap; fi，sourceThe total amount of hydrogen produced for the ith hydrogen source in unit time;
the formula for setting hydrogen source constraints may include:
∑iFi，j＝Fjformula (11)
The meaning of formula (11) is: the supply quantity of the hydrogen trap j is equal to the sum of the supply quantities of all hydrogen sources;
∑iFi，j·yi，j＝Fj·yjformula (12)
The meaning of formula (12) is: the pure hydrogen supply quantity of the hydrogen trap j is equal to the sum of the pure hydrogen supply quantities supplied by all the hydrogen sources;
the meaning of formula (13) is: the pure hydrogen supply amount of any one of the hydrogen traps is larger than the 'minimum pure hydrogen supply amount' of the hydrogen trap;
the meaning of formula (14) is: the hydrogen supply purity of any one of the hydrogen traps is greater than the minimum hydrogen supply purity of the hydrogen trap and is less than 1;
the formula for setting light hydrocarbon constraints may include:
∑iFi，LHR≤FLHRMAXformula (15)
Wherein, Fi，LHRFor the ith stream flow entering the light hydrocarbon recovery plant, FPSAMAXThe method is the maximum design treatment of a light hydrocarbon recovery device.
S12, using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the reaction kinetic model meet the quality standard;
in the embodiment of the invention, the quality of the product (such as product oil) is ensured firstly, therefore, when the product property data is calculated according to the reaction kinetic model and the product quality does not meet the preset requirement, the corresponding working condition data can be updated through corresponding working condition adjustment (such as adjusting the new hydrogen condition), and then the step is returned to for recalculation so as to verify whether the product quality under the updated working condition is qualified or not until the product quality meets the preset requirement (namely meets the preset condition).
S13, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to a preset hydrogen network optimization model;
in the embodiment of the invention, the hydrogen network is optimized on the premise that the product property is required to be in accordance with the preset standard, so that the new hydrogen boundary condition and the generation amount of the micromolecular hydrocarbons which are used as parameters of the hydrogen network optimization model can be obtained through the reaction kinetic model on the premise that the qualified product can be obtained.
And S14, generating an oxygen supply scheme according to the hydrogen network optimization model.
And solving according to the hydrogen network optimization model by taking the boundary condition of the new hydrogen and the generation amount of the micromolecular hydrocarbons as parameters so as to generate an oxygen supply scheme.
In practical application, a desulfurization reaction kinetic model and a hydrogen network optimization model can be modeled by using gams (a planning modeling tool), and a regression model HT PARA REG.gms, a reactor simulation model HT SIMU-adi.gms and a hydrogen network optimization model H2NET OPT.gms which reflect kinetic parameters are obtained. The operation steps of the integrated optimization model program are as follows: running a main program HT PARA REG.gms of the regression model, and after the calculation is finished, adding k to0(reaction indicates a pro-factor), EaParameters (reaction activation energy), alpha (hydrogen partial pressure index), beta (hydrogen-oil ratio index) and the like are transmitted to a main program HT SIMU-adi.
In summary, in the embodiment of the present invention, the desulfurization reaction kinetic model and the hydrogen network optimization model that can be applied to various working conditions are respectively established, and then the desulfurization reaction kinetic model and the hydrogen network optimization model are integrated, so that the technical scheme in the embodiment of the present invention can be applied to various working conditions to obtain accurate results after optimizing and associating the hydrogenation apparatus while optimizing the hydrogen network, and further, a practical and feasible optimization scheme can be obtained, which has significant economic benefits.
In another aspect of the embodiment of the present invention, there is also provided a hydrogen network optimization apparatus based on hydrogen utilization maximization, and fig. 4 illustrates a schematic structural diagram of the hydrogen network optimization apparatus based on hydrogen utilization maximization according to the embodiment of the present invention, where the hydrogen network optimization apparatus based on hydrogen utilization maximization is a device corresponding to the hydrogen network optimization method based on hydrogen utilization maximization in the embodiment corresponding to fig. 1, that is, the hydrogen network optimization method based on hydrogen utilization maximization in the embodiment corresponding to fig. 1 is implemented by using a virtual device, and each virtual module constituting the hydrogen network optimization apparatus based on hydrogen utilization maximization may be executed by an electronic device, such as a network device, a terminal device, or a server. Specifically, the hydrogen network optimization apparatus based on hydrogen utilization maximization according to the embodiment of the present invention includes:
the presetting unit 01 is used for establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, by taking increase of hydrogen gas consumption as an available means and taking maximum hydrogen network operation income as a target; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model;
an oil quality verification unit 02 for performing: using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard;
the parameter output unit 03 is used for outputting a new hydrogen boundary condition and the generation amount of micromolecular hydrocarbons to a preset hydrogen network optimization model;
and the scheme generation unit 04 is used for generating an oxygen supply scheme according to the hydrogen network optimization model.
Since the working principle and the beneficial effects of the hydrogen network optimization device based on hydrogen utilization maximization in the embodiment of the present invention have been described and illustrated in the hydrogen network optimization method based on hydrogen utilization maximization corresponding to fig. 1, they may be referred to each other, and are not described herein again.
In an embodiment of the present invention, a memory is further provided, where the memory includes a software program adapted to be executed by a processor to perform each step in the hydrogen grid optimization method based on hydrogen utilization maximization corresponding to fig. 1.
The embodiment of the present invention may be implemented by way of a software program, that is, by writing a software program (and an instruction set) for implementing each step in the hydrogen grid optimization method based on hydrogen utilization maximization corresponding to fig. 1, where the software program is stored in a storage device, and the storage device is disposed in a computer device, so that the software program can be called by a processor of the computer device to implement the purpose of the embodiment of the present invention.
In an embodiment of the present invention, a hydrogen network optimization device based on hydrogen utilization maximization is further provided, where the hydrogen network optimization device based on hydrogen utilization maximization includes a memory, and includes a corresponding computer program product, where program instructions included in the computer program product, when executed by a computer, may cause the computer to perform the hydrogen network optimization method based on hydrogen utilization maximization described in the above aspects, and achieve the same technical effect.
Fig. 5 is a schematic hardware configuration diagram of a hydrogen network optimization apparatus based on hydrogen utilization maximization according to an embodiment of the present invention, which is an electronic device, and as shown in fig. 5, the apparatus includes one or more processors 610, a bus 630, and a memory 620. Taking one processor 610 as an example, the apparatus may further include: input device 640, output device 650.
The processor 610, the memory 620, the input device 640, and the output device 650 may be connected by a bus or other means, such as the bus connection in fig. 5.
The memory 620, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules. The processor 610 executes various functional applications and data processing of the electronic device, i.e., the processing method of the above-described method embodiment, by executing the non-transitory software programs, instructions and modules stored in the memory 620.
The memory 620 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data and the like. Further, the memory 620 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 620 optionally includes memory located remotely from the processor 610, which may be connected to the processing device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 640 may receive input numeric or character information and generate a signal input. The output device 650 may include a display device such as a display screen.
The one or more modules are stored in the memory 620 and, when executed by the one or more processors 610, perform:
s11, establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, by using the increase of hydrogen consumption as an available means and the maximum goal of hydrogen network operation income; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model;
s12, using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard;
s13, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to a preset hydrogen network optimization model;
and S14, generating an oxygen supply scheme according to the hydrogen network optimization model.
The product can execute the method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage device and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage device includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a ReRAM, an MRAM, a PCM, a NAND Flash, a NOR Flash, a Memory, a magnetic disk, an optical disk, or other various media that can store program codes.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A hydrogen network optimization method based on hydrogen utilization maximization is characterized by comprising the following steps:
s11, establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, by using the increase of hydrogen consumption as an available means and the maximum goal of hydrogen network operation income; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model;
s12, using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard;
s13, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to a preset hydrogen network optimization model;
and S14, generating a hydrogen supply scheme of the hydrogen network according to the hydrogen network optimization model.
2. The hydrogen net optimization method based on hydrogen utilization maximization according to claim 1, characterized in that the desulfurization reaction kinetic model is established according to a diesel hydrodesulfurization process, and comprises:
through industrial device data including sulfur composition, reactor parameters, catalyst loading parameters and reaction conditions of raw diesel, regression is performed on preset parameters in a rate equation of a desulfurization reaction kinetic model to determine pre-index parameters, pre-index factors, apparent activation energy and hydrogen partial pressure indexes of the rate equation, and the method comprises the following steps:
s111, acquiring industrial device data including sulfur composition, reactor parameters, catalyst filling parameters and reaction conditions of raw diesel oil;
s112, setting initial values of the pre-indication parameter, the apparent activation energy and the hydrogen partial pressure index;
s113, calculating the reaction rate of the inlet of the reactor; calculating the reaction rate and reactant concentration of each bed layer; calculating the outlet temperature and product properties of the reactor;
s114, obtaining a parameter value of a specific parameter of a desulfurization reaction kinetic model through regression calculation by taking the minimum sum of the calculated values of the outlet temperature and the product properties of the reactor and the variance of an actual measured value as a target function; the specific parameters include pre-finger parameters, pre-finger factors, apparent activation energy and hydrogen partial pressure index.
3. The method for optimizing a hydrogen network based on hydrogen utilization maximization according to claim 1, wherein the hydrogen network optimization model is established by taking increase of hydrogen consumption as an available means and taking maximum profit of hydrogen network operation as a target on the premise of not increasing equipment investment, and comprises the following steps:
s121, setting a calculation formula of an objective function of the hydrogen network optimization model as follows:
MaxCoptimization＝△Cproducer-△CConsumer-△Cpurification-△Cfuelformula (1);
wherein, MaxCoptimizationFor the sum of the gains of the hydrogen network obtained by optimization,. DELTA.CproducerHydrogen yield, Δ C, from reduced supply for hydrogen utilitiesLHOptimized light hydrocarbon yield,. DELTA.CConsumerFor hydrogen strips for hydrogen-consuming devicesIncreased operating costs, Δ C, after part changespurificationFor the increased operating cost, Delta C, after the change of the raw material of the purification apparatusfuelRecovering hydrogen and light hydrocarbon and supplementing fuel gas value to the fuel gas pipe network;
and S122, setting constraint conditions comprising compressor constraint, purification device constraint, hydrogen source constraint and hydrogen trap constraint.
4. The hydrogen net optimization method based on hydrogen utilization maximization according to claim 3, characterized by comprising:
according to the formula: delta Cproducer＝∑ipriceproducer×ΔFiEquation (2); obtaining said Δ Cproducer(ii) a Wherein the priceiIs the unit price from the ith hydrogen utility; said Δ FiIs the hydrogen flow rate from the ith hydrogen utility.
5. The hydrogen net optimization method based on hydrogen utilization maximization according to claim 3, characterized by comprising:
according to the formula:
the formula:
obtaining said Δ CConsumer；
Wherein, Wp: represents the compression power per mole of inlet gas; cpv: denotes the heat capacity ratio Cp/CvCalculating according to the feeding composition by a second dimensional force coefficient model; t: indicating the compressor inlet temperature, which cannot exceed 50 ℃; poutlet: represents the compressor outlet pressure; pinlet: represents the compressor inlet pressure; n iscmp: representing the compression stage number; etaeff-ise-1: representing compressor isentropic efficiency；ηeff-mec: indicating compressor mechanical efficiency; r: represents a gas constant; t is0: 273.15K; wp,i,MThe compression power of a new hydrogen compressor of the ith hydrogenation unit per mole of inlet gas; n isi,MakeupThe mole number of the hydrogen at the inlet of a new hydrogen compressor of the ith hydrogenation unit; wp,i,RThe compression power of the recycle hydrogen compressor of the ith hydrogenation unit per mol of inlet gas; n isi,RecycleThe mole number of the hydrogen at the inlet of the recycle hydrogen compressor of the ith hydrogenation unit; priceeThe price of the local industrial electricity used by the oil refinery.
6. The hydrogen net optimization method based on hydrogen utilization maximization according to claim 3, characterized by comprising:
according to the formula: delta Cpurification＝△CPress,Purification+△CFlowrateEquation (5); obtaining said Δ Cpurification(ii) a Wherein, Δ CPress,PurificationIncrease of operating cost of the compressor; delta CFlowrateThe operating cost for the purification apparatus after the change of the throughput is increased;
according to the formula:
obtaining said Δ Cfuel(ii) a Wherein, CLHIs the price of light hydrocarbon per unit volume, HLHIs the heat value of the unit volume of light hydrocarbon;
in terms of the price per unit volume of hydrogen,
the calorific value per unit volume of hydrogen; hfuelHeat value of fuel gas per unit volume, CfuelIs the price of fuel gas per unit volume.
7. The method of claim 1, wherein the setting constraints including a compressor constraint, a purification plant constraint, a hydrogen source constraint, and a hydrogen trap constraint comprises:
compressor restraint: the compressor inlet gas volume must meet the design throughput requirement, and to prevent surge inlet gas from occurring should also meet the design minimum hydrogen concentration requirement, the formula for setting the compressor constraints may include:
∑iFi，comp≤Fcompmaxformula (7)
∑i(Fi，comp×yi)≥∑iFi，comp×yminFormula (8)
Wherein, FcompmaxMaximum air intake amount allowed for the compressor, Fi，compFlow of hydrogen stream to compressor for ith hydrogen source, ycompIs the compressor outlet hydrogen concentration.
And (3) restricting a purifying device: the inlet gas flow of the purification device should be less than the designed maximum throughput of the device; the formula for setting the constraints of the purification apparatus may include:
∑iFi，PSA≤FPSAMAXformula (9)
Wherein, Fi，PSAFor the ith stream flow entering the purification plant, FPSAMAXThe maximum design throughput for the PSA unit.
Hydrogen source restraint: the sum of all output streams is required to be less than or equal to the total output flow of the hydrogen source, and the formula for setting the hydrogen source constraint can comprise:
∑jFi，j≤Fi，sourceformula (10)
Wherein, Fi，jThe flow of the ith hydrogen source to the jth hydrogen trap; fi，sourceThe total amount of hydrogen produced for the ith hydrogen source in unit time;
the formula for setting the hydrogen trap constraints may include:
∑iFi，j＝Fjformula (11)
The meaning of formula (11) is: the supply quantity of the hydrogen trap j is equal to the sum of the supply quantities of all hydrogen sources;
∑iFi，j·yi，j＝Fj·yjformula (12)
The meaning of formula (12) is: the pure hydrogen supply quantity of the hydrogen trap j is equal to the sum of the pure hydrogen supply quantities supplied by all the hydrogen sources;
the meaning of formula (13) is: the pure hydrogen supply amount of any one of the hydrogen traps is larger than the 'minimum pure hydrogen supply amount' of the hydrogen trap;
the meaning of formula (14) is: the hydrogen supply purity of any one of the hydrogen traps is greater than the minimum hydrogen supply purity of the hydrogen trap and is less than 1;
the formula for setting light hydrocarbon constraints may include:
∑iFi，LHR≤FLHRMAXformula (15)
Wherein, Fi，LHRFor the ith stream flow entering the light hydrocarbon recovery plant, FPSAMAXThe method is the maximum design treatment of a light hydrocarbon recovery device.
8. A hydrogen network optimization device based on hydrogen utilization maximization, comprising:
the system comprises a presetting unit, a hydrogen network optimization unit and a control unit, wherein the presetting unit is used for establishing a multi-lumped reaction kinetic model, and establishing a hydrogen network optimization model on the premise of not increasing equipment investment, taking increasing of hydrogen gas consumption as an available means and taking the maximum operation income of a hydrogen network as an objective; the reaction kinetic model comprises a hydrodesulfurization reaction kinetic model, a hydrodenitrogenation reaction kinetic model or a polycyclic aromatic hydrocarbon hydrogenation reaction kinetic model;
an oil quality verification unit for performing: using specific working condition data including oil product properties, new hydrogen composition and new hydrogen flow as input parameters, judging whether the product property data corresponding to the current working condition meet a preset quality standard through the reaction kinetic model, and adjusting the specific working condition data when the product property data do not meet the preset quality standard until the product property data obtained according to the desulfurization reaction kinetic model meet the quality standard;
the parameter output unit outputs a new hydrogen boundary condition and the generation amount of micromolecular hydrocarbons to a preset hydrogen network optimization model;
and the scheme generation unit is used for generating a hydrogen supply scheme according to the hydrogen network optimization model.
9. A memory comprising a software program adapted to execute the steps of the method for hydrogen network optimization based on hydrogen utilization maximization of any one of claims 1 to 7 by a processor.
10. A hydrogen network optimization device based on hydrogen utilization maximization, characterized by comprising a bus, a processor and a memory as described in claim 9;
the bus is used for connecting the memory and the processor;
the processor is configured to execute a set of instructions in the memory.
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