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Method for optimizing gasoline blending in offline manner

An off-line optimization, gasoline technology, applied in computational models, biological models, instruments, etc., can solve problems such as difficult to solve practical engineering problems

Inactive Publication Date: 2014-04-23
EAST CHINA UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Due to the nonlinear nature of the gasoline blending model, the traditional mathematical programming method often requires a large number of steps such as mathematical transformations, but it is difficult to solve such practical engineering problems in the end

Method used

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  • Method for optimizing gasoline blending in offline manner
  • Method for optimizing gasoline blending in offline manner
  • Method for optimizing gasoline blending in offline manner

Examples

Experimental program
Comparison scheme
Effect test

Embodiment approach

[0058] (1) The oil products to be blended are catalytic gasoline, heavy catalyst gasoline, non-aromatic gasoline, MTBE, and reformed oil, totaling 5 components; the additive is manganese agent;

[0059] (2) Set the unit volume cost of the component oil and the percentage limit of the component formula (that is, the inventory constraint) as shown in the following table:

[0060]

catalytic gasoline

heavy gasoline

Non-aromatic gasoline

MTBE

Reformate

total

component price

4200

4300

3900

6000

5000

23400

Minimal formula

25.34

31.4

0

0

18

74.74

Maximum Recipe

34.52

40.58

45.91

1.84

19.1

141.95

[0061] (3) Set the maximum dosage of manganese agent to 5mg / L, the minimum dosage to 0, and the unit mass cost of manganese agent to 20

[0062] ten thousand yuan / ton.

[0063] (4) The attribute data of component oils are shown in the following table:

[00...

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Abstract

The invention discloses a method for optimizing gasoline blending in an offline manner. The method includes building a gasoline blending model; optimally computing the built model by the aid of a particle swarm optimization algorithm. The minimum blending cost, the minimum product mass surplus and the minimum manganese-additive dosage are comprehensively taken into consideration in the model on the premise that requirements of product index constraints, component inventory constraints, manganese-additive dosage limit and material balance constraints are met. The method has the advantages that equality constraints in the blending model are processed by the aid of the particle swarm optimization algorithm in a novel processing mode, so that a result obtained after particle swarms are updated at every turn can assuredly meet conditions of the equality constraints, the scale of population can be guaranteed, and the arithmetic speed can be increased.

Description

technical field [0001] The invention belongs to the field of gasoline blending and relates to an off-line optimization method for gasoline blending. Background technique [0002] The higher the grade of motor gasoline, the better the performance. The main monitoring items of gasoline internal quality include: antiknock performance (research octane number, motor octane number), vapor pressure, sulfur content, olefin content, aromatics content, benzene content, distillation range, induction period, copper corrosion, etc. . Among these indicators, the anti-knock performance of gasoline is the most important, and the octane number can directly reflect the anti-knock performance of gasoline. Therefore, the octane number is used to indicate the grade of gasoline. The research method octane number and the motor method are generally used in the industry. The average value of octane number. [0003] The composition of gasoline is relatively complex, mainly alkanes, from C4 to C12,...

Claims

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Application Information

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IPC IPC(8): G06F19/00G06N3/00
CPCG01N33/2829
Inventor 钱锋程辉杜文莉
Owner EAST CHINA UNIV OF SCI & TECH
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