CN112750504A - Storage, original equipment-based hydrogen network optimization method, device and equipment - Google Patents
Storage, original equipment-based hydrogen network optimization method, device and equipment Download PDFInfo
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- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 351
- 239000001257 hydrogen Substances 0.000 title claims abstract description 351
- 238000005457 optimization Methods 0.000 title claims abstract description 108
- 238000000034 method Methods 0.000 title claims abstract description 53
- 238000003860 storage Methods 0.000 title description 12
- 125000004435 hydrogen atom Chemical class [H]* 0.000 title description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 claims abstract description 241
- 150000002431 hydrogen Chemical class 0.000 claims abstract description 105
- 238000006243 chemical reaction Methods 0.000 claims abstract description 68
- 238000006477 desulfuration reaction Methods 0.000 claims abstract description 44
- 230000023556 desulfurization Effects 0.000 claims abstract description 44
- 238000011084 recovery Methods 0.000 claims abstract description 14
- 230000008569 process Effects 0.000 claims abstract description 11
- 229930195733 hydrocarbon Natural products 0.000 claims abstract description 10
- 150000002430 hydrocarbons Chemical class 0.000 claims abstract description 10
- 238000000746 purification Methods 0.000 claims description 40
- 239000007789 gas Substances 0.000 claims description 23
- 238000005984 hydrogenation reaction Methods 0.000 claims description 19
- 239000000446 fuel Substances 0.000 claims description 16
- 239000002737 fuel gas Substances 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 13
- 239000000203 mixture Substances 0.000 claims description 13
- 230000006835 compression Effects 0.000 claims description 12
- 238000007906 compression Methods 0.000 claims description 12
- 230000004913 activation Effects 0.000 claims description 11
- 238000013461 design Methods 0.000 claims description 10
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 9
- 230000008859 change Effects 0.000 claims description 9
- 239000002283 diesel fuel Substances 0.000 claims description 9
- 229910052717 sulfur Inorganic materials 0.000 claims description 9
- 239000011593 sulfur Substances 0.000 claims description 9
- 230000006870 function Effects 0.000 claims description 8
- 239000002994 raw material Substances 0.000 claims description 7
- 239000003054 catalyst Substances 0.000 claims description 6
- -1 reactor parameters Substances 0.000 claims description 5
- 230000005611 electricity Effects 0.000 claims description 4
- 239000000376 reactant Substances 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 238000012795 verification Methods 0.000 claims description 3
- 230000008901 benefit Effects 0.000 abstract description 7
- 239000003921 oil Substances 0.000 description 23
- 238000010586 diagram Methods 0.000 description 7
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 6
- 230000000694 effects Effects 0.000 description 5
- 239000000463 material Substances 0.000 description 5
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- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 239000003345 natural gas Substances 0.000 description 3
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- 238000007670 refining Methods 0.000 description 2
- 238000002407 reforming Methods 0.000 description 2
- 238000004088 simulation Methods 0.000 description 2
- 239000004215 Carbon black (E152) Substances 0.000 description 1
- 238000009903 catalytic hydrogenation reaction Methods 0.000 description 1
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Abstract
The invention discloses a memory, a hydrogen network optimization method based on original equipment, a device and equipment, wherein the method comprises the steps of establishing a multi-lumped desulfurization reaction kinetic model according to a diesel hydrodesulfurization process; on the premise of not increasing equipment investment, the maximized hydrogen recovery is taken as a guide, and a hydrogen network optimization model is established with the maximum goal of the operation income of the hydrogen network; calculating to obtain product property data by taking specific working condition data as input parameters through the desulfurization reaction kinetic model; when the product property data do not accord with the preset conditions, updating the working condition data; when the product property data meet the preset conditions, outputting a new hydrogen boundary condition and the generation amount of the micromolecular hydrocarbons to the hydrogen network optimization model; and generating a hydrogen optimization 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 memory, a hydrogen network optimization method based on original equipment, 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 original equipment, which comprises the following steps:
s11, establishing a multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process;
s12, establishing a hydrogen network optimization model on the premise of not increasing equipment investment and with the aim of maximizing hydrogen recovery as a guide and maximizing hydrogen network operation income;
s13, calculating product property data through the desulfurization reaction kinetic model by taking specific working condition data at least comprising oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions as input parameters;
s14, when the product property data do not meet the preset conditions, updating the working condition data and returning to the step S13;
s15, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to the hydrogen network optimization model when the product property data meet preset conditions;
and S16, generating a hydrogen optimization scheme according to the hydrogen network optimization model.
In the invention, the building of a multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process 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 recovery maximization is used as a guide, and the maximum income of the hydrogen network operation is used as a target, a 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＝ΔCproducer-ΔCConsumer-ΔCpurification-ΔCfuelformula (1);
wherein, MaxCoptimizationFor the sum of gains of the hydrogen network, Δ C, obtained by optimizationproducerHydrogen yield, Δ C, from decreasing supply for hydrogen utilitiesConsumerFor increased operating costs, Δ C, after changes in hydrogen conditions for the hydrogen-consuming unitpurificationIncreased operating costs, Δ C, for the purification plant after a change of raw materialsfuelThe value of fuel gas supplemented to a fuel gas pipe network for recovering hydrogen;
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 combination of (a) and (b),
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:
formula (6); 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.
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:
∑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，sourceAnd producing the total hydrogen for the ith hydrogen source in unit time.
The formula for setting the hydrogen trap constraints may include:
the meaning of formula (11) is: the supply amount of the hydrogen trap j is equal to the sum of the supply amounts of the hydrogen from all the hydrogen sources.
The meaning of formula (12) is: the pure hydrogen supply amount of the hydrogen trap j is equal to the sum of the pure hydrogen supply amounts of 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 that 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 that hydrogen trap and less than 1.
In another aspect of the embodiments of the present invention, there is also provided a hydrogen grid optimization apparatus based on original equipment, including:
the desulfurization model generation unit is used for establishing a multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process;
the hydrogen network model generation unit is used for establishing a hydrogen network optimization model on the premise of not increasing equipment investment, taking maximized hydrogen recovery as guidance and taking the maximum operating income of the hydrogen network as a target;
an oil quality verification unit for performing: when the product property data do not accord with preset conditions, updating the specific working condition data, taking the specific working condition data as an input parameter, and calculating to obtain the product property data through the desulfurization reaction kinetic model; the specific working condition data comprises oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions;
the parameter generation unit is used for outputting a new hydrogen boundary condition and the generation amount of micromolecular hydrocarbons to the hydrogen network optimization model when the product property data meet preset conditions;
and the scheme generation unit is used for generating a hydrogen optimization scheme according to the hydrogen network optimization model.
In another aspect of the embodiment of the present invention, there is further provided a memory including a software program adapted to be executed by a processor for performing the steps of the original equipment-based hydrogen grid optimization method.
In another aspect of the embodiments of the present invention, there is also provided an original equipment-based hydrogen network optimization apparatus, where the original equipment-based hydrogen network optimization apparatus includes a computer program stored on a memory, where the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes the method in the above aspects, and achieves the same technical effect.
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 primary-based hydrogen grid optimization method of 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 hydrogen supply network of the present invention;
FIG. 5 is a schematic structural diagram of a hydrogen net optimization device based on original equipment;
fig. 6 is a schematic structural diagram of the original equipment-based hydrogen network optimization equipment.
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.
Example one
In order to provide an optimization scheme of a refinery hydrogen resource that can be suitable for various working conditions, as shown in fig. 1, in an embodiment of the present invention, a method for optimizing a refinery hydrogen resource is provided, which includes the steps of:
s11, establishing a multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process;
with the continuous upgrade of the requirements of China on the quality of diesel oil, the refining enterprises can improve the quality of the diesel oil by reducing the sulfur content in the diesel oil as one of the core tasks of diesel oil production.
For a diesel hydrogenation device, the sulfur content in the product is a key constraint condition of an integrated model, so a desulfurization reaction kinetic model of diesel needs to be constructed firstly.
The method specifically comprises the following steps: building a multi-lumped desulfurization reaction kinetic model generally requires industrial equipment including the sulfur composition of the raw diesel, reactor parameters, catalyst loading parameters and reaction conditionsSetting data, and performing regression on preset parameters in a rate equation of the desulfurization reaction kinetic model to determine a pre-index parameter k of the rate equation0，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 the specific process thereof can be as shown in fig. 2 and with reference to fig. 3, including:
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:
| parameter(s) | k0,1 | k0,2 | k0,3 | k0,4 |
| Numerical value | 6630 | 9.761E+08 | 2.945E+08 | 1.618E+10 |
| Parameter(s) | n0,1 | n0,2 | n0,3 | n0,4 |
| Numerical value | 0.0892 | 0.146 | 0.786 | 1.431 |
| Parameter(s) | Ea1 | Ea2 | Ea3 | Ea4 |
| Numerical value | 52 | 118 | 143 | 230 |
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.
S12, on the premise of not increasing equipment investment, taking maximized hydrogen recovery as guidance, and taking the maximum income of hydrogen network operation as a target, establishing a hydrogen network optimization model, comprising the following steps:
the application scenarios of the embodiment of the invention are as follows: because the occupied area or the fund of a refinery is limited, equipment or pipelines cannot be newly added, and the set oil quality is ensured under the condition that the hydrogen resource is limited; the embodiment of the invention optimizes the hydrogen network based on the current situation, so that the maximum operation benefit of the hydrogen network is obtained.
The core goal of the embodiments of the present invention is to maximize the operating revenue of the hydrogen network by maximizing the hydrogen recovery without increasing the equipment investment.
Based on the core objectives, the specific steps of establishing the hydrogen network optimization model in the embodiment of the present invention include:
s121, setting a calculation formula of an objective function of the hydrogen network optimization model as follows:
MaxCoptimization＝△Cproducer-△CConsumer-△Cpurification-△Cfuel(ii) a Formula (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 utilitiesConsumerFor 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 apparatusfuelThe value of fuel gas supplemented to a fuel gas pipe network for recovering hydrogen;
the obtaining manner of each parameter in formula (1) may specifically be as follows:
1) hydrogen yield ac associated with hydrogen utility reduction supplyproducerThe specific obtaining manner may include the following formula:
ΔCproducer＝∑ipriceproducer×ΔFiformula (2)
Therein, priceiIs the unit price from the ith hydrogen utility; delta FiIs the hydrogen flow rate from the ith hydrogen utility.
2) Increased operating costs Δ C associated with changes in hydrogen conditions for a hydrogen-consuming deviceConsumerIt means the increase of the operation cost of the hydrogenation unit due to the change of the flow rate and the composition of the fresh hydrogen and the recycle hydrogen, and mainly comprises the increase of the operation cost of the compressor (if the cost is reduced, the numerical value is negative), and the increase of the operation cost of the compressor is realizedThe specific obtaining manner may include the formula:
the calculation formula of the operating cost of the compressor is as follows:
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.
3) Regarding the increased operating cost Δ C after the change of the raw material of the purification apparatuspurificationTwo aspects are considered, including in particular: first, the increase in compressor operating costs after the feed to the purification unit is changed; second, the operation cost after the change of the treatment capacity of the purification apparatus is increased except for the compressor, and a specific obtaining manner thereof may include the formula:
△Cpurification＝△CPress,Purification+△CFlowrateformula (5)
Wherein, Δ CPress,PurificationIncrease of operating cost of the compressor; delta CFlowrateThe operating costs for the purification plant after the throughput has been changed are increased.
4) Value of fuel gas to be supplemented to a fuel gas pipe network after hydrogen recoveryfuelThe specific obtaining manner may include the following formula:
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;
the compressor constraint, the purification device constraint, the hydrogen source constraint and the hydrogen trap constraint in the step may specifically include:
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，sourceAnd producing the total hydrogen 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 amount of the hydrogen trap j is equal to the sum of the supply amounts of the hydrogen from all the hydrogen sources.
∑iFi，j·yi，j＝Fj·yjFormula (12)
The meaning of formula (12) is: the pure hydrogen supply amount of the hydrogen trap j is equal to the sum of the pure hydrogen supply amounts of 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 that 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 that hydrogen trap and less than 1.
S13, calculating product property data through the desulfurization reaction kinetic model by taking specific working condition data at least comprising oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions as input parameters;
in the embodiment of the invention, the current working condition data is taken as a parameter, and product property data can be obtained and calculated according to a preset desulfurization 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.
S14, when the product property data do not meet the preset conditions, updating the working condition data and returning to the step S13;
in the embodiment of the invention, the quality of the product oil is ensured firstly, so that when the product property data is calculated according to the desulfurization reaction kinetic model and the quality of the product oil does not meet the preset requirement, the corresponding working condition data can be updated through corresponding working condition adjustment (for example, new hydrogen condition is adjusted), and then the step is returned to for recalculation so as to verify whether the quality of the oil under the updated working condition is qualified or not until the quality of the oil meets the preset requirement (namely, meets the preset condition).
S15, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to the hydrogen network optimization model when the product property data meet preset conditions;
and on the premise of obtaining an oil product with qualified quality, taking the corresponding new hydrogen boundary condition and the generation amount of the micromolecular hydrocarbon as the parameters of a preset hydrogen network optimization model.
And S16, generating a hydrogen optimization 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 micromolecule hydrocarbons as parameters, thereby obtaining the hydrogen optimization scheme of the whole plant.
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: and (3) running a main program HT PARA REG.gms of the regression model, after the calculation is finished, transmitting parameters such as k0 (reaction pre-pointing factor), Ea (reaction activation energy), alpha (hydrogen partial pressure index) and beta (hydrogen-oil ratio index) to a main program HT SIMU-adi.gms of the reactor simulation model, outputting a new hydrogen boundary condition to the hydrogen network optimization model after the calculation is finished, and solving an output hydrogen network optimization scheme through the hydrogen network optimization model.
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.
The practical effects of the embodiments of the present invention are illustrated as an example below:
the hydrogen supply network of a certain refinery enterprise is shown in figure 4. I reforming hydrogen is directly supplied to a hydrogen supply network, II reforming new hydrogen (the purity is about 93% v) is purified to 99% v by pressure swing adsorption PSA and then is sent into a pipe network, and a related device at the downstream of the pipe network is a diesel hydrogenation device.
The preliminary diagnosis shows that: diesel oil hydrogenation hydrogen supplementThe gas sources include reformed hydrogen I and PSA hydrogen, the purity of the hydrogen is higher than 97.20% v, and the hydrogen is excessive and the product quality is excessive. After the detailed calculation of the integrated reaction dynamics hydrogen net model, the proposal is as follows: part of II reformed hydrogen can be directly supplied to the pipe network, and the direct supply amount is about 5400Nm3And h, meeting the requirement of product quality on the premise of ensuring the normal operation of the device.
The implementation of the above scheme has the following implementation effects:
1) and hydrogen saving benefit: the reduction of the severity of the device brings about the reduction of hydrogen consumption, and meanwhile, the reformed hydrogen direct supply pipe network also reduces the purification waste, and the comprehensive hydrogen saving amount is 2057Nm 3/h.
Referring to Table 3, assuming natural gas as a supplemental heating value for the fuel after hydrogen recovery and natural gas and hydrogen prices calculated at 3378 and 13000 j/t, respectively, the value of hydrogen recovered per ton is 5051.76 yuan. It can be calculated that the yield of saving hydrogen per year by the optimization is 784.78 ten thousand yuan.
Table 3: hydrogen recovery value conversion table
| Calorific value (MJ/kg) | Price (/ t) | Recovery price ([ gamma ]/t) | |
| Natural gas | 51.00 | 3378.00 | - |
| Hydrogen gas | 120.00 | 13000.00 | 5051.76 |
2) And operation cost accounting: after the diesel hydrogenation device supplies reformed hydrogen, the electricity consumption and the steam consumption of a new hydrogen and recycle hydrogen compressor are increased, and the annual operation cost is increased by 253.51 ten thousand yuan. But after the reformed hydrogen is directly supplied to the hydrogen pipe network, the load of a tail gas compressor is reduced, and the operation cost is saved by 264.52 ten thousand yuan all the year.
3) And the pipe network and the compressor are not modified, and the modification cost is 0.
4) After comprehensive calculation, the implementation of the optimization scheme brings about the comprehensive annual yield of 795.79 ten thousand yuan.
Although the sulfur content of the product in the device before and after optimization is increased from 3.03ppm to 6.47ppm, the operation severity of the device is increased; with the reduction of the make-up hydrogen amount and the purity, the hydrogen consumption per ton of oil of the device is reduced, and the hydrogen consumption is reduced; the operation condition of the device is changed after the implementation of the scheme, but the normal operation of the device is not influenced.
In another aspect of the embodiment of the present invention, an original-equipment-based hydrogen network optimization apparatus is further provided, and fig. 5 illustrates a schematic structural diagram of the original-equipment-based hydrogen network optimization apparatus provided in the embodiment of the present invention, where the original-equipment-based hydrogen network optimization apparatus is an apparatus corresponding to the original-equipment-based hydrogen network optimization method in the embodiment corresponding to fig. 1, that is, the original-equipment-based hydrogen network optimization method in the embodiment corresponding to fig. 1 is implemented by using a virtual apparatus, and each virtual module constituting the original-equipment-based hydrogen network optimization apparatus may be executed by an electronic device, such as a network device, a terminal device, or a server. Specifically, the hydrogen network optimization device based on the original equipment in the embodiment of the present invention includes:
the desulfurization model generation unit 01 is used for establishing a multi-lumped desulfurization reaction kinetic model according to a diesel hydrodesulfurization process;
the hydrogen network model generation unit 02 is used for establishing a hydrogen network optimization model on the premise of not increasing equipment investment, taking maximized hydrogen recovery as guidance and taking the maximum operating income of the hydrogen network as a target;
an oil quality verification unit 03 for performing: when the product property data do not accord with preset conditions, updating the specific working condition data, taking the specific working condition data as an input parameter, and calculating to obtain the product property data through the desulfurization reaction kinetic model; the specific working condition data comprises oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions;
the parameter generation unit 04 is used for outputting a new hydrogen boundary condition and the generation amount of the micromolecular hydrocarbons to the hydrogen network optimization model when the product property data meet a preset condition;
and the scheme generating unit 05 is used for generating a hydrogen optimization scheme according to the hydrogen network optimization model.
Since the working principle and the beneficial effects of the original equipment-based hydrogen network optimization device in the embodiment of the present invention have been described and illustrated in the original equipment-based hydrogen network optimization method 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, and the software program is adapted to enable the processor to execute each step in the original equipment-based hydrogen network optimization method corresponding to fig. 1.
The embodiment of the present invention may be implemented by a software program, that is, by writing a software program (and an instruction set) for implementing each step in the original device-based hydrogen grid optimization method corresponding to fig. 1, 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 an original device is further provided, where a memory included in the hydrogen network optimization device based on the original device includes a corresponding computer program product, and program instructions included in the computer program product, when executed by a computer, enable the computer to perform the method for optimizing a hydrogen network based on an original device in the foregoing aspects, and achieve the same technical effects.
Fig. 6 is a schematic diagram of a hardware structure of an original equipment-based hydrogen network optimization device as an electronic device according to an embodiment of the present invention, and as shown in fig. 6, the device 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. 6.
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 desulfurization reaction kinetic model according to the diesel hydrodesulfurization process;
s12, establishing a hydrogen network optimization model on the premise of not increasing equipment investment and with the aim of maximizing hydrogen recovery as a guide and maximizing hydrogen network operation income;
s13, calculating product property data through the desulfurization reaction kinetic model by taking specific working condition data at least comprising oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions as input parameters;
s14, when the product property data do not meet the preset conditions, updating the working condition data and returning to the step S13;
s15, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to the hydrogen network optimization model when the product property data meet preset conditions;
and S16, generating a hydrogen optimization 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 original equipment is characterized by comprising the following steps:
s11, establishing a multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process;
s12, establishing a hydrogen network optimization model on the premise of not increasing equipment investment and with the goal of maximizing the operation income of the hydrogen network;
s13, calculating product property data through the desulfurization reaction kinetic model by taking specific working condition data at least comprising oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions as input parameters;
s14, when the product property data do not meet the preset conditions, updating the working condition data and returning to the step S13;
s15, outputting a new hydrogen boundary condition and the generation amount of micromolecule hydrocarbons to the hydrogen network optimization model when the product property data meet preset conditions;
and S16, generating a hydrogen optimization scheme according to the hydrogen network optimization model.
2. The hydrogen net optimization method according to claim 1, wherein the building of the multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process 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 the hydrogen network according to claim 1, wherein the establishing of the optimization model of the hydrogen network with the goal of maximizing the operational profit of the hydrogen network and with the guidance of maximizing the hydrogen recovery without increasing the equipment investment comprises:
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 utilitiesConsumerFor 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 apparatusfuelThe value of fuel gas supplemented to a fuel gas pipe network for recovering hydrogen;
and S122, setting constraint conditions comprising compressor constraint, purification device constraint, hydrogen source constraint and hydrogen trap constraint.
4. The hydrogen net optimization method according to claim 3, 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 according to claim 3, comprising:
according to the formula:
and the combination of (a) and (b),
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.
6. The hydrogen net optimization method according to claim 3, 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 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.
7. The hydrogen net optimization method according to claim 1, wherein the setting constraints including a compressor constraint, a purification device 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，sourceAnd producing the total hydrogen 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 amount of the hydrogen trap j is equal to the sum of the supply amounts of the hydrogen from all the hydrogen sources.
∑iFi，j·yi，j＝Fj·yjFormula (12)
The meaning of formula (12) is: the pure hydrogen supply amount of the hydrogen trap j is equal to the sum of the pure hydrogen supply amounts of 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 that 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 that hydrogen trap and less than 1.
8. A hydrogen net optimizing apparatus based on original equipment is characterized by comprising:
the desulfurization model generation unit is used for establishing a multi-lumped desulfurization reaction kinetic model according to the diesel hydrodesulfurization process;
the hydrogen network model generation unit is used for establishing a hydrogen network optimization model on the premise of not increasing equipment investment, taking maximized hydrogen recovery as guidance and taking the maximum operating income of the hydrogen network as a target;
an oil quality verification unit for performing: when the product property data do not accord with preset conditions, updating the specific working condition data, taking the specific working condition data as an input parameter, and calculating to obtain the product property data through the desulfurization reaction kinetic model; the specific working condition data comprises oil product properties, supplemented hydrogen flow, supplemented hydrogen purity and device reaction conditions;
the parameter generation unit is used for outputting a new hydrogen boundary condition and the generation amount of micromolecular hydrocarbons to the hydrogen network optimization model when the product property data meet preset conditions;
and the scheme generation unit is used for generating a hydrogen optimization scheme according to the hydrogen network optimization model.
9. A memory comprising a software program adapted to be executed by a processor for performing the steps of the original equipment based hydrogen network optimization method according to any one of claims 1 to 7.
10. A hydrogen network optimization device based on original equipment, which is characterized by comprising a bus, a processor and a memory as claimed 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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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115860267A (en) * | 2023-02-20 | 2023-03-28 | 新疆独山子石油化工有限公司 | Refinery logistics value estimation method and device, equipment and storage medium |
| CN115860267B (en) * | 2023-02-20 | 2023-06-06 | 新疆独山子石油化工有限公司 | Method, device, equipment and storage medium for estimating logistics value of refinery |
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