CN103276125A - Iron-making furnace charge total cost comprehensive optimization - Google Patents

Abstract

An iron-making furnace charge total cost comprehensive optimization mathematical model is built according to the principle of optimality and method as well as application of a computer technology, with comprehensive consideration to factors such as iron making yield, sintering yield, pellet yield balance, raw fuel price, available ore resource quantity, batching, furnace slag component setting, sintering and distributing batching, sintering batching, pellet batching, blast furnace input raw material structure, fuel consumption correction, furnace slag composition and the like, and under the premise of ensuring that input raw material components and furnace slag composition conform to prescribed requirements. By using the method, unique and optimal charging proportion and corresponding minimum input charging total cost can be obtained through batching calculation at the same time under conventional charging resource conditions and according to market raw fuel price variation, so that batching can be adjusted at the same time, and further potential tapping and efficiency increase can be achieved. The figure in the abstract of description refers to iron-making furnace charge total cost comprehensive optimization calculating process.

Description

Iron-smelting furnace charge total cost complex optimum

Technical field

The invention relates to ferrous metallurgy blast furnace ironmaking field quantitative Application iron-smelting furnace charge total cost comprehensive optimization method feed proportioning optimization, with charge composition and the corresponding minimum technology of going into the furnace charge total cost that obtains unique the best simultaneously.

Background technology

It is to realize centered by the greatest benefit that enterprise produces, and in recent years along with output of steel increases year by year, is subjected to the dual extruding that upstream materials appreciate and the downstream price of steel product glides, and the profit margin of steel industry is more and more littler.Ironmaking cost accounts for iron and steel enterprise's cost more than 70%, the charge calculation of in the past smelting iron has been considered ironmaking output, sintering output, pelletizing output, crude fuel price, available ore resource amount, the even ore deposit of sintering batching, sintered material, pelletizing batching, blast furnace feeding raw material mix and slag composition, only select proportioning raw materials to calculate the feed stock for blast furnace cost artificially, do not consider the influence that feed stock for blast furnace grade etc. changes blast furnace fuel consumption.Economic ironmaking must be considered furnace charge total costs such as crude fuel, so that the reasonable disposition resource under the existing resource condition, changes according to the crude fuel market value, in time adjusts, and Optimization Ore Matching reduces and goes into the furnace charge total cost, excavates enterprise's greatest benefit.

Summary of the invention

According to principle of optimality and method and utilization computer technology, factors such as ironmaking output, sintering output, pelletizing output balance, crude fuel price, available ore resource amount, batching and slag composition setting, the even ore deposit of sintering batching, sintered material, pelletizing batching, blast furnace feeding raw material mix, fuel consumption correction and slag composition have been taken all factors into consideration, guarantee that feed stock for blast furnace composition and slag form requirement up to specification, set up iron-smelting furnace charge total cost complex optimum mathematical model.Utilize this method to help iron work under existing furnace charge resources supplIes, according to market crude fuel price change, calculate with the charge composition that obtains unique the best simultaneously and the corresponding minimum furnace charge total cost of going into by feed proportioning optimization, in time adjust batching, further enhancing efficiency by relying on tapping internal latent power.

Batching data such as table 1 signal are calculated as follows:

Target: furnace charge total cost optimum, that is:

Table 1 batching data

$\min (\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{E}_{1i}\·Y_{1i})$

Constraint condition (St.):

X _1i≥0 i=1,2,···,m

Y _1i≤U _1i i=1,2,···,m

$\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{X}_{1i}=100$

$A_j=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{X}_{1i}{A}_{\mathrm{ij}}/100j=\mathrm{1,2},...,n$

$E_1=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{X}_{1i}{E}_{1i}/100$

Y _1i =X _1i Y ₁/100 i=1,2,···,m

$Y_1=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{Y}_{1i}$

$U_1=\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{U}_{1i}$

Sintering is spared ore deposit, agglomerate, pellet batching and blast furnace feeding raw material mix and is in like manner calculated, and considers material balance, increases constraint condition.

Agglomerate: consider to convert after the scaling loss, composition requires: TTe 〉=set(ting)value, SiO ₂≤ set(ting)value, MgO 〉=set(ting)value, Al ₂O ₃≤ set(ting)value, CaO/SiO ₂=set(ting)value.

Pellet: consider to convert after the wilkinite proportioning, composition requires: TTe 〉=set(ting)value, SiO ₂≤ set(ting)value, Al ₂O ₃≤ set(ting)value, CaO/SiO ₂=set(ting)value.

The blast furnace feeding raw material mix: consider to contain the powder rate, composition requires: TTe 〉=set(ting)value, SiO ₂≤ set(ting)value, S≤set(ting)value.

Fuel: consider that batching is gone into the stove grade, ore contains factors such as S, grog rate, coke ash, sulfur content in coke and basicity of slag to the benchmark value variable effect, proofread and correct ratio of putting coke into furnace.

The slag moiety requires: MgO 〉=set(ting)value, Al ₂O ₃≤ set(ting)value, CaO/SiO ₂=set(ting)value.

Description of drawings

Fig. 1 is iron-smelting furnace charge total cost complex optimum calculated with mathematical model flow process.

Embodiment

1) collects relevant crude fuel data and require information.

2) set up iron-smelting furnace charge total cost complex optimum mathematical model.

3) input related data parameter in iron-smelting furnace charge total cost complex optimum mathematical model.

4) feed proportioning optimization is calculated and is selected, further enhancing efficiency by relying on tapping internal latent power.

The effect simulation check

Main furnace charge data statistics such as table 2 signal, normal and feed proportioning optimization is calculated illustrating such as table 3, therefrom find with price change, various burden structures are all inequality, but feed proportioning optimization is all low than the needed furnace charge total cost of normal batching, remarkable benefit, be conducive to enterprise under existing furnace charge resources supplIes, according to market crude fuel price change, feed proportioning optimization, enhancing efficiency by relying on tapping internal latent power.

The main furnace charge data statistics of table 2

Normal and the feed proportioning optimization calculating contrast of table 3

Claims (2)

1. one kind according to principle of optimality and method with use computer technology, factors such as ironmaking output, sintering output, pelletizing output balance, crude fuel price, available ore resource amount, batching and slag composition setting, the even ore deposit of sintering batching, sintered material, pelletizing batching, blast furnace feeding raw material mix, fuel consumption correction and slag composition have been taken all factors into consideration, guarantee that feed stock for blast furnace composition and slag form requirement up to specification, set up iron-smelting furnace charge total cost complex optimum mathematical model.

2. calculate with the charge composition that obtains unique the best simultaneously and the corresponding minimum furnace charge total cost of going into by feed proportioning optimization.

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