CN113705021A - Method for predicting gasoline octane number - Google Patents
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- CN113705021A CN113705021A CN202111078031.5A CN202111078031A CN113705021A CN 113705021 A CN113705021 A CN 113705021A CN 202111078031 A CN202111078031 A CN 202111078031A CN 113705021 A CN113705021 A CN 113705021A
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- TVMXDCGIABBOFY-UHFFFAOYSA-N octane Chemical compound CCCCCCCC TVMXDCGIABBOFY-UHFFFAOYSA-N 0.000 title claims abstract description 57
- 239000003502 gasoline Substances 0.000 title claims abstract description 42
- 238000000034 method Methods 0.000 title claims abstract description 29
- 230000003009 desulfurizing effect Effects 0.000 claims abstract description 10
- 238000007670 refining Methods 0.000 claims abstract description 9
- 238000004523 catalytic cracking Methods 0.000 claims abstract description 8
- 239000000571 coke Substances 0.000 claims abstract description 8
- 238000001179 sorption measurement Methods 0.000 claims abstract description 8
- 239000002994 raw material Substances 0.000 claims abstract description 7
- WKBOTKDWSSQWDR-UHFFFAOYSA-N Bromine atom Chemical compound [Br] WKBOTKDWSSQWDR-UHFFFAOYSA-N 0.000 claims abstract description 4
- 150000001335 aliphatic alkanes Chemical class 0.000 claims abstract description 4
- 150000004945 aromatic hydrocarbons Chemical class 0.000 claims abstract description 4
- GDTBXPJZTBHREO-UHFFFAOYSA-N bromine Substances BrBr GDTBXPJZTBHREO-UHFFFAOYSA-N 0.000 claims abstract description 4
- 229910052794 bromium Inorganic materials 0.000 claims abstract description 4
- 229930195734 saturated hydrocarbon Natural products 0.000 claims abstract description 4
- 230000003197 catalytic effect Effects 0.000 claims description 10
- 239000002737 fuel gas Substances 0.000 claims description 6
- 230000000087 stabilizing effect Effects 0.000 claims description 4
- 239000007789 gas Substances 0.000 claims description 3
- 239000007788 liquid Substances 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 3
- 239000004215 Carbon black (E152) Substances 0.000 claims description 2
- 229930195733 hydrocarbon Natural products 0.000 claims description 2
- 150000002430 hydrocarbons Chemical class 0.000 claims description 2
- 230000008929 regeneration Effects 0.000 claims description 2
- 238000011069 regeneration method Methods 0.000 claims description 2
- 239000000295 fuel oil Substances 0.000 description 4
- 229910052717 sulfur Inorganic materials 0.000 description 4
- 239000011593 sulfur Substances 0.000 description 4
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 description 3
- 239000010779 crude oil Substances 0.000 description 3
- 238000011160 research Methods 0.000 description 3
- 150000001336 alkenes Chemical class 0.000 description 2
- 239000003921 oil Substances 0.000 description 2
- JRZJOMJEPLMPRA-UHFFFAOYSA-N olefin Natural products CCCCCCCC=C JRZJOMJEPLMPRA-UHFFFAOYSA-N 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000002485 combustion reaction Methods 0.000 description 1
- 150000001924 cycloalkanes Chemical class 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000006477 desulfuration reaction Methods 0.000 description 1
- 230000023556 desulfurization Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 239000012535 impurity Substances 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 239000003381 stabilizer Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
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- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G55/00—Treatment of hydrocarbon oils, in the absence of hydrogen, by at least one refining process and at least one cracking process
- C10G55/02—Treatment of hydrocarbon oils, in the absence of hydrogen, by at least one refining process and at least one cracking process plural serial stages only
- C10G55/06—Treatment of hydrocarbon oils, in the absence of hydrogen, by at least one refining process and at least one cracking process plural serial stages only including at least one catalytic cracking step
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/26—Oils; Viscous liquids; Paints; Inks
- G01N33/28—Oils, i.e. hydrocarbon liquids
- G01N33/2829—Mixtures of fuels
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/20—Characteristics of the feedstock or the products
- C10G2300/201—Impurities
- C10G2300/202—Heteroatoms content, i.e. S, N, O, P
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/20—Characteristics of the feedstock or the products
- C10G2300/30—Physical properties of feedstocks or products
- C10G2300/305—Octane number, e.g. motor octane number [MON], research octane number [RON]
-
- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/40—Characteristics of the process deviating from typical ways of processing
- C10G2300/4006—Temperature
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- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2300/00—Aspects relating to hydrocarbon processing covered by groups C10G1/00 - C10G99/00
- C10G2300/40—Characteristics of the process deviating from typical ways of processing
- C10G2300/4012—Pressure
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- C—CHEMISTRY; METALLURGY
- C10—PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
- C10G—CRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
- C10G2400/00—Products obtained by processes covered by groups C10G9/00 - C10G69/14
- C10G2400/02—Gasoline
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/08—Thermal analysis or thermal optimisation
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Abstract
The invention provides a method for predicting the octane number of gasoline. The method comprises the steps of firstly collecting sample data in a catalytic cracking gasoline refining and desulfurizing device, wherein the sample data comprises a raw material octane number RON, saturated hydrocarbon (alkane and cyclane) content, aromatic hydrocarbon content, bromine number, coke content (to-be-regenerated adsorption property), coke content (regenerated adsorption property), hydrogen-oil ratio and the like, and then bringing the sample data to an octane number prediction model for calculation to obtain an octane number prediction value. The method for predicting the octane number of the gasoline is simple to operate and high in accuracy, and can replace a traditional experimental determination method to a certain extent.
Description
Technical Field
The invention belongs to the field of petrochemical industry, and relates to a method for predicting the octane number of gasoline.
Background
The import crude oil of China is mostly sulfur-containing and high-sulfur crude oil in middle east. Heavy oil in crude oil is usually present in a large proportion, and this heavy oil (also having a high content of impurities such as sulfur) is difficult to directly utilize. In order to effectively utilize heavy oil resources, China vigorously develops a heavy oil lightening process technology taking catalytic cracking as a core, more than 70% of gasoline is produced by catalytic cracking, and therefore more than 95% of sulfur and olefin in finished gasoline come from catalytic cracking gasoline. Therefore, the catalytic cracking gasoline must be refined to meet the quality requirement of the gasoline.
Octane number (expressed as RON) is the most important index reflecting the combustion performance of gasoline, and the octane number of gasoline is generally reduced in the processes of desulfurizing and reducing olefin of catalytic cracking gasoline in the prior art. The conventional octane number determination methods have the following three types: the octane number of a motor method is measured, the rotating speed of an engine is 900r/min, the air inlet temperature is 149 ℃, and the antiknock performance of gasoline running under the conditions of high speed and heavy load of an automobile is reflected; research octane number, the rotating speed is 600r/min, the air inlet is room temperature, and the antiknock performance of the gasoline when the automobile runs at low speed in the urban area is reflected; the octane number of the road method is measured by an automobile or a condition for simulating the automobile to run on a highway on a full-power test bed, and can also be calculated by the octane number of the motor method and the octane number of a research method according to an empirical formula.
The three measurement methods all need experiments, and have the advantages of strict experimental conditions, high experimental difficulty and high cost. Therefore, research on an experimental-free octane number prediction mode is needed.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a method for predicting the octane number of gasoline, which solves the problems of strict experimental conditions, high experimental difficulty and high cost of the conventional octane number determination.
The invention is realized by the following technical scheme:
the method for predicting the octane number of the gasoline comprises the following steps of:
step 1, collecting sample data in a catalytic gasoline refining and desulfurizing device;
and 2, bringing the sample data to an octane number prediction model for calculation to obtain an octane number prediction value.
In the step 1, sample data in a catalytic gasoline refining and desulfurizing device is collected, and the sample data comprises the following contents:
the method comprises the steps of collecting sample data in a catalytic cracking gasoline refining and desulfurizing device, wherein the sample data comprises a raw material octane value RON, saturated hydrocarbon (alkane and naphthenic hydrocarbon) content, aromatic hydrocarbon content, a bromine number, coke content (to-be-regenerated adsorption property), coke content (regeneration adsorption property), a hydrogen-oil ratio, a reactor upper portion temperature, a reactor top pressure, a stabilizing tower lower portion temperature, a refined gasoline outlet device temperature, a dry gas outlet device flow rate, a fuel gas inlet device pressure, a fuel gas inlet device flow rate, a steam inlet device temperature, a catalytic gasoline inlet device flow rate, a raw material inlet device flow rate, a condensate water tank liquid level and a stabilizing tower top outlet temperature.
In step 2, bringing the sample data to an octane number prediction model for calculation to obtain an octane number prediction value, wherein the octane number prediction value comprises the following contents:
the octane number prediction model is as follows:
in the formula, y-predicted octane number, x1，x2，…，x19Is 19 variables, beta0，β1，…，β19As model coefficients, the specific parameters are shown in table 1:
TABLE 1 model parameters
And (4) bringing the sample data into an octane number prediction model for calculation to obtain an octane number prediction value.
Due to the adoption of the technical scheme, the invention can achieve the following beneficial effects:
(1) according to the method for predicting the gasoline octane number, the model is a linear model, the calculation operation is simple, and the calculation is easy;
(2) according to the method for predicting the gasoline octane number, the model is obtained based on regression of a large amount of experimental data, and the calculation accuracy is high.
Drawings
FIG. 1 is a diagram of steps of a method for predicting gasoline octane number according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described below with reference to the accompanying drawings in the embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, a method for predicting gasoline octane number includes the following steps:
step 1, collecting sample data in a catalytic gasoline refining and desulfurizing device;
and 2, bringing the sample data to an octane number prediction model for calculation to obtain an octane number prediction value.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The method is characterized by comprising the step of accumulating a large amount of data for long-term operation of a catalytic gasoline exquisite desulfurization device of a petrochemical company enterprise. The method for predicting the octane number of the gasoline comprises the following implementation steps:
step 1, collecting sample data in a catalytic gasoline refining and desulfurizing device, wherein the sample data comprises a raw material octane value RON, a saturated hydrocarbon (alkane and cycloalkane) content, an aromatic hydrocarbon content, a bromine number, a coke content (to-be-regenerated adsorption property), a coke content (regenerated adsorption property), a hydrogen-oil ratio, a reactor upper portion temperature, a reactor top pressure, a stabilizer lower portion temperature, a refined gasoline outlet device temperature, a dry gas outlet device flow, a fuel gas inlet device pressure, a fuel gas inlet device flow, a steam inlet device temperature, a catalytic gasoline inlet device flow, a raw material inlet device flow, a condensate water tank liquid level and a stabilized tower top outlet temperature, and is shown in a table 2:
TABLE 2 sample data
And 2, bringing the sample data to an octane number prediction model for calculation to obtain an octane number prediction value, wherein the octane number prediction value and the prediction error are shown in a table 3.
TABLE 3 octane number prediction and error
As can be seen from Table 3, the difference between the predicted octane number and the actual octane number of the product is small, and the average error is 0.292%. The invention provides a method for predicting the octane number of gasoline. The method is simple in calculation operation and easy to calculate; the model is obtained based on a large amount of experimental data regression, and the calculation accuracy is high.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (3)
1. A method for predicting the octane number of gasoline is characterized by comprising the following steps:
step 1, collecting sample data in a catalytic gasoline refining and desulfurizing device;
and 2, bringing the sample data to an octane number prediction model for calculation to obtain an octane number prediction value.
2. The method for predicting the octane number of gasoline according to claim 1, wherein the step 1 of collecting sample data in a catalytic gasoline refining and desulfurizing device comprises the following steps:
the method comprises the steps of collecting sample data in a catalytic cracking gasoline refining and desulfurizing device, wherein the sample data comprises a raw material octane value RON, saturated hydrocarbon (alkane and naphthenic hydrocarbon) content, aromatic hydrocarbon content, a bromine number, coke content (to-be-regenerated adsorption property), coke content (regeneration adsorption property), a hydrogen-oil ratio, a reactor upper portion temperature, a reactor top pressure, a stabilizing tower lower portion temperature, a refined gasoline outlet device temperature, a dry gas outlet device flow rate, a fuel gas inlet device pressure, a fuel gas inlet device flow rate, a steam inlet device temperature, a catalytic gasoline inlet device flow rate, a raw material inlet device flow rate, a condensate water tank liquid level and a stabilizing tower top outlet temperature.
3. The method for predicting the octane number of gasoline according to claim 1, wherein the step 2 of substituting the sample data into an octane number prediction model to calculate the octane number prediction value comprises the following steps:
the octane number prediction model is as follows:
in the formula, y-predicted octane number, x1，x2，…，x19Is 19 variables, beta0，β1，…，β19The specific parameters are shown in the following table:
TABLE 1 model parameters
And (4) bringing the sample data into an octane number prediction model for calculation to obtain an octane number prediction value.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114724644A (en) * | 2022-03-25 | 2022-07-08 | 中国石油大学(北京) | Method and equipment for predicting gasoline octane number based on intermolecular interaction |
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