CN103135443A - AOD (argon oxygen decarburization) furnace energy consumption optimization method based on energy carrier - Google Patents

Abstract

The invention discloses an AOD (argon oxygen decarburization) furnace energy consumption optimization method based on an energy carrier, and belongs to the field of data processing. The AOD furnace energy consumption optimization method includes the steps: determining an AOD furnace energy consumption optimization model parameter set according to a production process; building energy balance constraint conditions of the parameter set based on material balance; building an energy consumption optimization model for an AOD furnace energy carrying value according to the energy balance constraint conditions; solving the energy consumption optimization model by an adaptive mutation rate genetic algorithm to obtain the optimized value of an objective function of the AOD furnace energy consumption optimization model; optimizing/adjusting the burdening amount or the burdening proportion of an AOD furnace and adjusting/controlling material consumption of the AOD furnace according to the optimized value of the objective function of the AOD furnace energy consumption optimization model; and greatly reducing the comprehensive average energy consumption of the AOD furnace based on the energy carrier on the premise of ensuring indexes such as various processed and product performances of the AOD furnace to meet requirements by the aid of existing equipment conditions. The AOD furnace energy consumption optimization method can be widely used for the field of comprehensive average energy consumption control for the AOD furnace.

Description

A kind of AOD stove energy optimization method based on energy carrier

Technical field

The invention belongs to data processing field, relate in particular to a kind of consumption control method for industrial installation.

Background technology

AOD stove (Argon Oxygen Decarburization furnace) is the refining equipment of argon oxygen decarburizing process, with the abbreviation letter designation of this method English name.

The profile of AOD stove (hereinafter to be referred as AOD) and converter are approximate, body of heater be placed in one can before and after on the backing ring of tumbling, fixed by pin.Bottom side at stove is equipped with the spray gun that is blown into gas to the bath level direction, and the quantity of spray gun is generally 2～3 according to the tonnage of stove and different.The meeting point of spray gun extended line overlaps with the vertical pivot of stove.Spray gun is by inner tube (copper) and outer tube (stainless steel) two-layer composition, and inner tube imports main blowing gas (by ArO2.Or Ar-N2 forms), the annulus between inner tube and outer tube imports Ar, N2 or air plays cooling effect with the protection spray gun.Spray gun is deflection type, imbeds refractory masses when brickwork, synchronizes scaling loss in smelting process with furnace lining.The oxygen that is blown into is mainly to heat up for carbonoxide, the argon gas that is blown into is mainly that strong convection stirs, can carry out nitrogen flushing when producing high nitrogen alloy in addition and carry out alloying, be to rush nitrogen, a lot of metal nitrides have been saved in this steel grade to basic production 21-4N class, as the addition of nitrogenize network, save a lot of production costs.

Along with increasingly sharpening of global energy worsening shortages and climate warming, sustainable development path all advocating energy-saving and emission-reduction, is walked in countries in the world.Steel and iron industry is as the energy consumption rich and influential family, and the task of energy-saving and emission-reduction is very heavy, and the most main energy-conservation equipment that is fit to steel mill is used, the great energy-conservation equipment Project well afoot of part.

See on the whole, be difficult to obtain larger energy-saving effect by single equipment or monotechnics again, need to plan as a whole AOD burden structure, mixed carbon comtent, oxygen-supplying amount, add iron water amount, add the many factors such as electric furnace mother liquor of stainless steel amount, mate various technology, can value carry out complex optimum to the AOD stove.

more and more obtain people's attention due to Energy Consumption Evaluation, computing method that energy consumption is estimated have appearred, for example, open day is on Dec 3rd, 2003, publication number is the Chinese invention patent application of CN 145947A, a kind of " determining the computing method of empty minute energy consumption amortization ratio between each product " disclosed, comprise: the Calculation of Physical Properties of oxygen-nitrogen-argon and composition thereof, distillation calculation, empty minute flow process is calculated, it calculates respectively the energy consumption of single high purity product air separation unit of independent production oxygen or nitrogen, produce simultaneously oxygen and nitrogen two high purity product air separation units energy consumption and produce simultaneously oxygen, nitrogen, the energy consumption of the air separation unit of argon product, when oxygen or nitrogen were taken product as the leading factor, the energy consumption of single high purity product air separation unit was the consumption consumption of oxygen or nitrogen, and two high purity product air separation unit energy consumptions deduct the energy consumption that single high purity product air separation unit energy consumption is the non-dominant product, energy consumption when oxygen nitrogen is respectively leading products averages, the energy consumption in the time of can drawing oxygen nitrogen and be leading products, deduct the energy consumption of producing simultaneously oxygen nitrogen product air separation unit with the energy consumption of producing simultaneously oxygen nitrogen and argon product air separation unit, can obtain the energy consumption of argon product.

But, adopt disclosed method in the disclosure file, be only to obtain a kind of energy consumption index, be applicable to energy consumption is estimated, and can't be optimized according to the equipment operation situation.

And for example, open day is on Dec 31st, 2008, publication number is the Chinese invention patent application of CN 10134799A, a kind of " energy consumption model of zinc electrolysis " disclosed, it sets up the mathematical model between current efficiency and tank voltage and current density, electrolytic solution acid concentration, zinc concentration and temperature according to the energy consumption mechanism of process in zinc electrolyzing; By the data that the zinc electrolytic experiment obtains, the parameter in the identification mathematical model, and obtain the energy consumption model of process in zinc electrolyzing according to the relation of energy consumption and current efficiency and tank voltage.

The disclosed technical scheme of this patent application has been set up the quantitative relationship of the impact of each technological parameter and current efficiency and energy consumption, makes the zinc electrolysis reduce energy consumption, has reduced production cost.But this technical scheme is only to have set up the quantitative relationship of each technological parameter and current efficiency and energy consumption, can't plan as a whole each technological parameter, and energy consumption is carried out complex optimum.

Summary of the invention

technical matters to be solved by this invention is to provide a kind of AOD stove energy optimization method based on energy carrier, it plans as a whole the burden structure of AOD stove, mixed carbon comtent, oxygen-supplying amount, add iron water amount, add the many factors such as electric furnace mother liquor of stainless steel amount, take material balance as the basis, set up the energy equilibrium constraint, adopt self-adaptation aberration rate genetic algorithm for solving, utilize the existing equipment condition, guaranteeing AOD stove tapping molten steel chemical composition, temperature, quality, cost, under the prerequisite that the indexs such as the basicity of slag meet the demands, the AOD furnace foundation is reduced significantly in the comprehensive average energy consumption of energy carrier.

Technical scheme of the present invention is: a kind of AOD stove energy optimization method based on energy carrier is provided, comprise the production steel grade for appointment, gather and regulate/control the supplies consumption amount of AOD stove, under the prerequisite that the basicity index that guarantees AOD stove tapping molten steel chemical composition, temperature, quality, cost and slag meets the demands, make the comprehensive average Energy Intensity Reduction of AOD stove, it is characterized in that:

Existing each production material consumption statistics of A, collection/analysis AOD stove;

B, according to production technology and/or existing each production material consumption statistics, determine the parameter set of AOD stove energy optimization model;

C, take material balance as the basis, set up the energy equilibrium constraint condition of described parameter set;

D, according to the energy equilibrium constraint condition of described parameter set, set up the AOD stove carry can value the energy optimization model;

E, employing self-adaptation aberration rate genetic algorithm are found the solution described energy optimization model;

F, obtain the optimum value of AOD stove energy optimization simulated target function;

G, according to the optimum value of AOD stove energy optimization simulated target function, optimize/regulate dosage or the proportion scale of AOD stove;

H, according to the optimum value of AOD stove energy optimization simulated target function, regulate/control the supplies consumption amount of AOD stove;

I, based on the existing equipment condition, under the prerequisite that the basicity index that guarantees AOD stove tapping molten steel chemical composition, temperature, quality, cost and slag meets the demands, make the AOD furnace foundation in the comprehensive average Energy Intensity Reduction of energy carrier.

Further, when determining the parameter set of above-mentioned AOD stove energy optimization model, each production material consumption is converted to the unified expression form of energy carrier form.

In addition, after the optimum value that obtains AOD stove energy optimization simulated target function, with the binary coding formal output of correspondence, regulate/control the supplies consumption amount of AOD stove.

Concrete, each production material consumption of described AOD stove comprises the consumption of electric furnace mother liquor of stainless steel, three deferrization water, lime, small pieces steel scrap, ferrosilicon, coke, high carbon ferro-chrome, general nickel, stainless steel scrap, oxygen, nitrogen and argon gas at least.

Described energy equilibrium constraint condition comprises the restriction of precious alloy, constraint, gas consumption, the duration of heat, ferrosilicon and the lime consumption of molten steel amount at least.

Further, the objective function of above-mentioned AOD stove energy optimization model is:

$\mathrm{\φ}=\min \underset{i=1}{\overset{n}{\mathrm{\Σ}}}(W_i\·E_i)/\mathrm{MS}$

Wherein, φ is energy consumption per ton steel, and unit is J; W _iThe weight of-parameter i, unit is kg; E _iBe being worth of parameter i, unit is J/kg; The molten steel amount of MS for producing, unit is kg;

Subscript i is comprised of 12 energy carriers, is respectively: 1 electric furnace mother liquor of stainless steel, 2 three deferrization water, 3 lime, 4 small pieces steel scraps, 5 ferrosilicon, 6 coke, 7 high carbon ferro-chromes, 8 general nickel, 9 stainless steel scraps, 10 oxygen, 11 nitrogen, 12 argon gas.

Perhaps, the objective function of above-mentioned AOD stove energy optimization model is:

Wherein, φ is energy consumption per ton steel, J; W _iThe weight of-parameter i, kg; The molten steel amount of MS for producing, kg;

Subscript i is comprised of 12 energy carriers, is respectively: 1 electric furnace mother liquor of stainless steel, 2 three deferrization water, 3 lime, 4 small pieces steel scraps, 5 ferrosilicon, 6 coke, 7 high carbon ferro-chromes, 8 general nickel, 9 stainless steel scraps, 10 oxygen, 11 nitrogen, 12 argon gas.

Further, above-mentioned self-adaptation aberration rate genetic algorithm comprises the following steps: at least

Step 1) determine the parameter set of AOD stove energy optimization model;

Step 2) initiation parameter;

Step 3) carry out binary coding, 20 binary strings of each parameter coding, totally 240 binary strings;

Step 4) produce initial population, produce body one by one and forms chromosomal gene code by the binary string of the random generation of string long 240, produce the individuality composition population of some, population scale is 80;

Step 5) calculate fitness, this function is minimized, and adopts the method for penalty function,

Step 6) carry out Selecting operation based on roulette mechanism;

Step 7) carry out the single-point crossing operation, select at random a point of crossing, intersect;

Step 8) make a variation, 1% gene morphs, and each gene has identical chance to morph;

Step 9) increase iterations n=n+1;

Step 10) be n=5000 when reaching maximum iteration time, calculate and finish, the output optimal value; Otherwise, turn back to step 6.

When calculating above-mentioned calculating fitness, the fitness function that adopts is:

f(s)＝NN-(f(x)+n*N)，

Wherein, NN is maximum value, NN=10000000, and f (x) is objective function, and n is that parameter does not satisfy the number of times of constraint, and N is penalties, N=200000.

Further, in above-mentioned energy equilibrium constraint condition, the restriction of its precious alloy comprises at least to the restriction of Cr content with to the restriction of Ni content.

Wherein, being restricted to Cr content:

$\underset{i=0}{\overset{n}{\mathrm{\Σ}}}{m}_i\·{(\mathrm{Cr}\%)}_i=m_{\mathrm{ms}}\·{(\mathrm{Cr}\%)}_{\mathrm{ms}}/{\mathrm{\η}}_{\mathrm{Cr}}$

To being restricted to of Ni content:

$\underset{i=0}{\overset{n}{\mathrm{\Σ}}}{m}_i\·{(\mathrm{Ni}\%)}_i=m_{\mathrm{ms}}\·{(\mathrm{Ni}\%)}_{\mathrm{ms}}/{\mathrm{\η}}_{\mathrm{Ni}}$

In above-mentioned formula, m _iBe the quality of feed stock for blast furnace i, (Cr%) _iCr content for feed stock for blast furnace i; m _msBe AOD stove tapping Metal Weight, (Ni%) _iNi content for feed stock for blast furnace i.

Being constrained to of its molten steel amount:

Q ₁≤m _MS≤Q ₂

In formula, Q ₁Be the lower limit of technological requirement AOD stove molten steel amount, Q ₂The upper limit for technological requirement AOD stove molten steel amount.

Its gas consumption comprises total oxygen-supplying amount at least, and described total oxygen-supplying amount is:

V _O＝V _O0+V _O1+V _O2+V _O3+V _O4+V _O5

In formula, V _O0Be oxygen utilization in early stage, V _O1Be the oxygen utilization of main carbon period C percentage composition from [C]-1 o'clock, V _O2Be the oxygen utilization of main carbon period C percentage composition during from 1-0.35, V _O3Oxygen utilization when dynamically carbon period C percentage composition is from 0.35-0.11, V _O4Oxygen utilization when dynamically carbon period C percentage composition is from 0.11-0.07, V _O5Oxygen utilization when dynamically carbon period C percentage composition is from 0.07-0.03.

Be the carbon/silicon burning time of total duration of heat or exothermic mixture its duration of heat, and wherein, should not surpass 90min total duration of heat; Should not surpass 20min burning time as the carbon of exothermic mixture/silicon.

SiO in slag when its ferrosilicon and lime consumption comprise total ferrosilicon consumption or reduction end at least ₂With the required total amount of lime that adds of slagging;

Wherein, total ferrosilicon consumption can be expressed as:

m _FeSi＝m _{FeSi_h}+m _{FeSi_re}+m _{FeSi_a}

Further, wherein $m_{\mathrm{FeSi}\_a}=\frac{m_{\mathrm{ms}}\·{(\mathrm{Si}\%)}_{\mathrm{ms}}}{{(\mathrm{Si}\%)}_{\mathrm{FeSi}}},$ Wherein $W_{\mathrm{FeSi}\_\mathrm{re}}=\frac{V_{\mathrm{OCr}}\·1.25}{{(\mathrm{Si}\%)}_{\mathrm{FeSi}}};$

In formula, Fe _{Si_re}And Fe _{Si_a}Represent respectively reduction ferrosilicon and alloy ferrosilicon;

SiO in slag when wherein, reduction finishes ₂, total amount of lime is:

$W_{\mathrm{SiO}2}=[\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{m}_i\·{(\mathrm{Si}\%)}_{\mathrm{FeSi}}-m_{\mathrm{ms}}\·{(\mathrm{Si}\%)}_{\mathrm{ms}}]\·\frac{60}{28}$

The required total amount of lime that adds of slagging is divided into:

$W_{\mathrm{lime}}=\frac{W_{\mathrm{SiO}2}}{{\mathrm{CaO}\%}_{\mathrm{lime}}}\·R_s$

Compared with the prior art, advantage of the present invention is:

1. consider AOD burden structure, mixed carbon comtent, oxygen-supplying amount as a whole, add iron water amount, add the many factors such as electric furnace mother liquor of stainless steel amount, utilize the existing equipment condition, under the satisfactory prerequisite of the indexs such as basicity that guarantees AOD stove tapping molten steel chemical composition, temperature, slag, optimum value according to AOD stove energy optimization simulated target function, optimize/regulate dosage or the proportion scale of AOD stove, make the production of AOD stove reduce energy consumption, reduced production cost;

2. according to production technology, set up various constraint conditions and restriction, guaranteed that resulting energy optimization simulated target function optimization value meets technical requirement and the performance index of production technology and product;

3. adopt the application of genetic algorithm in finding the solution optimization problem, make the optimization computation process of whole energy optimization simulated target function have thought simple, the plurality of advantages such as be easy to realize, effect is obvious;

4. whole optimizing process is based on the unified expression form of energy carrier, standard the unified form of presentation of various materials, energy consumption, make between distinct device, different product or different manufacturing enterprise, possessed the comparability of energy consumption index;

5. every consumption indicators is compressed/controlled to the blindness that will pass by, become purpose is arranged, directive optimization/adjusting, control from " qualitative " and rise to " quantitatively " control, under the prerequisite that guarantees AOD stove tapping product quality, make the comprehensive energy consumption control of manufacturing enterprise rise to a new height.

Description of drawings

Fig. 1 is the block flowsheet schematic diagram of energy optimization method of the present invention;

Fig. 2 be the AOD stove be blown into oxygen utilize the situation schematic diagram;

Fig. 3 is AOD capacity of furnace model schematic diagram;

Fig. 4 is the AOD stove energy consumption diagnosis curve of an embodiment;

Fig. 5 is the AOD stove energy consumption diagnosis curve of another embodiment;

Fig. 6 is the AOD stove energy consumption diagnosis curve of another embodiment.

Embodiment

The present invention will be further described below in conjunction with drawings and Examples.

In Fig. 1, this is based on the AOD stove energy optimization method of energy carrier, comprise the production steel grade for appointment, gather and regulate/control the supplies consumption amount of AOD stove, under the prerequisite that the basicity index that guarantees AOD stove tapping molten steel chemical composition, temperature, quality, cost and slag meets the demands, make the comprehensive average Energy Intensity Reduction of AOD stove, its concrete grammar comprises the following steps:

Existing each production material consumption statistics of A, collection/analysis AOD stove;

B, according to production technology and/or existing each production material consumption statistics, determine the parameter set of AOD stove energy optimization model;

C, take material balance as the basis, set up the energy equilibrium constraint condition of described parameter set;

D, according to the energy equilibrium constraint condition of described parameter set, set up the AOD stove carry can value the energy optimization model;

E, employing self-adaptation aberration rate genetic algorithm are found the solution described energy optimization model;

F, obtain the optimum value of AOD stove energy optimization simulated target function;

G, according to the optimum value of AOD stove energy optimization simulated target function, optimize/regulate dosage or the proportion scale of AOD stove;

H, according to the optimum value of AOD stove energy optimization simulated target function, regulate/control the supplies consumption amount of AOD stove;

I, based on the existing equipment condition, under the prerequisite that the basicity index that guarantees AOD stove tapping molten steel chemical composition, temperature, quality, cost and slag meets the demands, make the AOD furnace foundation in the comprehensive average Energy Intensity Reduction of energy carrier.

Further, when determining the parameter set of above-mentioned AOD stove energy optimization model, each production material consumption is converted to the unified expression form of energy carrier form.

In addition, after the optimum value that obtains AOD stove energy optimization simulated target function, with the binary coding formal output of correspondence, regulate/control the supplies consumption amount of AOD stove.

So-called energy carrier refers to the object that has consumed energy in manufacture process, and itself can energy-producing object.When final energy consumption is added up, need to be converted to corresponding primary energy amount as secondary energy such as electric power.Give an example, power plant is with 500 tons of standard coal equivalents, sent out the electric power (processing conversion loss 100 tons of standard coal equivalents) of 400 tons of standard coal equivalents, delivered to certain enterprise by transmission line of electricity (50 tons of standard coal equivalents of transmission loss) and produce, 350 tons of standard coal equivalents of having used up and having sent here.In this example, finally for the production of quantity of energy be 350 tons of standard coal equivalents, but total energy consumption should be 500 tons of standard coal equivalents, and carbon dust is owing to being primary energy, there is no consumed energy in manufacture process, coke and ferrosilicon consume less energy in manufacture process, be energy-conservation so replace electric energy with coke, carbon dust and ferrosilicon.

The various materials that consume in AOD stove smelting process can value not only comprise the energy that they are contained, also comprise the gross energy of various starting material, power and fuel that they consume in manufacture process.

Take Baogang's water as research object, the objective function of its AOD stove energy optimization model is:

$\mathrm{\φ}=\min \underset{i=1}{\overset{n}{\mathrm{\Σ}}}(W_i\·E_i)/\mathrm{MS}$

Wherein, φ is energy consumption per ton steel, and unit is J; W _iThe weight of-parameter i, unit is kg; E _iBe being worth of parameter i, unit is J/kg; The molten steel amount of MS for producing, unit is kg;

Subscript i is comprised of 12 energy carriers, is respectively: 1 electric furnace mother liquor of stainless steel, 2 three deferrization water, 3 lime, 4 small pieces steel scraps, 5 ferrosilicon, 6 coke, 7 high carbon ferro-chromes, 8 general nickel, 9 stainless steel scraps, 10 oxygen, 11 nitrogen, 12 argon gas.

Perhaps, the objective function of above-mentioned AOD stove energy optimization model is:

Wherein, φ is energy consumption per ton steel, J; W _iThe weight of-parameter i, kg; The molten steel amount of MS for producing, kg;

Subscript i is comprised of 12 energy carriers, is respectively: 1 electric furnace mother liquor of stainless steel, 2 three deferrization water, 3 lime, 4 small pieces steel scraps, 5 ferrosilicon, 6 coke, 7 high carbon ferro-chromes, 8 general nickel, 9 stainless steel scraps, 10 oxygen, 11 nitrogen, 12 argon gas.

When implementing the technical program, substep and description that some are concrete are as follows:

Concrete, each production material consumption of above-mentioned AOD stove comprises the consumption of electric furnace mother liquor of stainless steel, three deferrization water, lime, small pieces steel scrap, ferrosilicon, coke, high carbon ferro-chrome, general nickel, stainless steel scrap, oxygen, nitrogen and argon gas at least.

Above-mentioned energy equilibrium constraint condition comprises the restriction of precious alloy, constraint, gas consumption, the duration of heat, ferrosilicon and the lime consumption of molten steel amount at least.

AOD stove in technical solution of the present invention carries the emergy synthesis Optimized model, and constraint is complicated, the more difficult analytic expression that finds constraint condition, and traditional operational research Methods such as linear programming is difficult to find the solution.Successful Application due to genetic algorithm in finding the solution optimization problem, and genetic algorithm have thought simple, the advantage such as be easy to realize, effect is obvious, this paper finds the solution the energy optimization model based on self-adaptation aberration rate genetic algorithm.Genetic algorithm be simulation biological in physical environment the heredity and evolution process and a kind of adaptive global optimization probability search method of forming.

Further, above-mentioned self-adaptation aberration rate genetic algorithm comprises the following steps: at least

Step 1) determine the parameter set of AOD stove energy optimization model;

Step 2) initiation parameter;

Step 3) carry out binary coding, 20 binary strings of each parameter coding, totally 240 binary strings;

Step 4) produce initial population, produce body one by one and forms chromosomal gene code by the binary string of the random generation of string long 240, produce the individuality composition population of some, population scale is 80;

Step 5) calculate fitness, this function is minimized, and adopts the method for penalty function,

Step 6) carry out Selecting operation based on roulette mechanism;

Step 7) carry out the single-point crossing operation, select at random a point of crossing, intersect;

Step 8) make a variation, 1% gene morphs, and each gene has identical chance to morph;

Step 9) increase iterations n=n+1;

Step 10) be n=5000 when reaching maximum iteration time, calculate and finish, the output optimal value; Otherwise, turn back to step 6.

When calculating above-mentioned calculating fitness, the fitness function that adopts is:

f(s)＝NN-(f(x)+n*N)，

Wherein, NN is maximum value, NN=10000000, and f (x) is objective function, and n is that parameter does not satisfy the number of times of constraint, and N is penalties, N=200000.

Further, a, in above-mentioned energy equilibrium constraint condition, the restriction of its precious alloy comprises at least to the restriction of Cr content with to the restriction of Ni content.

Wherein, being restricted to Cr content:

$\underset{i=0}{\overset{n}{\mathrm{\Σ}}}{m}_i\·{(\mathrm{Cr}\%)}_i=m_{\mathrm{ms}}\·{(\mathrm{Cr}\%)}_{\mathrm{ms}}/{\mathrm{\η}}_{\mathrm{Cr}}$

To being restricted to of Ni content:

$\underset{i=0}{\overset{n}{\mathrm{\Σ}}}{m}_i\·{(\mathrm{Ni}\%)}_i=m_{\mathrm{ms}}\·{(\mathrm{Ni}\%)}_{\mathrm{ms}}/{\mathrm{\η}}_{\mathrm{Ni}}$

In above-mentioned formula, m _iBe the quality of feed stock for blast furnace i, (Cr%) _iCr content for feed stock for blast furnace i; m _msBe AOD stove tapping Metal Weight, (Ni%) _iNi content for feed stock for blast furnace i.

Being constrained to of b, above-mentioned molten steel amount:

Q ₁≤m _MS≤Q ₂

In formula, Q ₁Be the lower limit of technological requirement AOD stove molten steel amount, Q ₂The upper limit for technological requirement AOD stove molten steel amount.

During AOD stove smelting stainless steel, if the molten iron that adds more (especially 300 series), the heat breach is larger, except dropping into essential alloy and slag making materials, should reduce as far as possible or avoid the heat burden that other factors causes, desirable adding amount of scrap steel is 0; If full electric furnace mother liquor is smelted, can suitably add the steel scrap cooling.

C, above-mentioned gas consumption comprise total oxygen-supplying amount at least, and its described total oxygen-supplying amount is:

V _O＝V _O0+V _O1+V _O2+V _O3+V _O4+V _O5

In formula, V _O0Be oxygen utilization in early stage, V _O1Be the oxygen utilization of main carbon period C percentage composition from [C]-1 o'clock, V _O2Be the oxygen utilization of main carbon period C percentage composition during from 1-0.35, V _O3Oxygen utilization when dynamically carbon period C percentage composition is from 0.35-0.11, V _O4Oxygen utilization when dynamically carbon period C percentage composition is from 0.11-0.07, V _O5Oxygen utilization when dynamically carbon period C percentage composition is from 0.07-0.03.

In AOD stove refining process, oxygen is blown into from top rifle and air port (side rifle).Primary period, the oxygen that the air port feeds nearly all are used for the oxidation of silicon.The oxygen that the main stage of blowing is supplied with by top rifle and air port, except being used for the secondary combustion of reaction between carbon and oxygen product C O that the part top blast is supplied with, major part is used for decarburization, and fraction is consumed in the oxidation of the elements such as chromium and nickel, and few part is directly discharged with waste gas.Dynamic carbon period, along with the reduction of carbon content, the oxygen that the air port is blown into also has considerable part to be consumed in the oxidation of chromium except being used for decarburization, and small part is overflowed with waste gas.

The decarburization utilization factor of definition oxygen is:

CRE＝V _OC/V _O

In formula, V _OC---be used for the amount of oxygen of decarburization; V _O---total oxygen utilization;

According to above-mentioned hypothesis, each definite stage blowing oxygen quantity is as shown in table 1 below:

D, the duration of heat

Compare with silicon, the thermal value of equal quality carbon is less than normal, and the identical temperature of a certain amount of molten steel rising is needed more carbon amount, and this must cause the prolongation of the duration of heat.Cause lining durability sharply to reduce the long duration of heat, also is unfavorable for the direct motion of sequence casting and production.Produced on-site shows, during the full molten iron smelting of AOD stove, should not surpass 90min total duration of heat, in 65min averaging time of two step method mother liquor smelting SUS304, should not surpass 20min burning time as the carbon of exothermic mixture/silicon.

The oxidation product of heating silicon is silicon dioxide, and the lime that needs to add extra quantity alleviates the erosion of furnace lining with it in conjunction with the balance basicity of slag, suppresses possible splash, is beneficial to smelting operation, also causes the quantity of slag to increase simultaneously.The excessive quantity of slag also easily causes splash except causing the increasing of expensive alloys loss amount, be unfavorable for operation.Experience shows, the consumption maximum of ferrosilicon can not surpass 3000kg.Therefore, when with the heat of carbon and silica during as AOD stove smelting stainless steel process heat additional, the proportioning of exothermic mixture is also needed to make constraint.

E, above-mentioned ferrosilicon and lime consumption comprise when total ferrosilicon consumption or reduction finish SiO in slag at least ₂With the required total amount of lime that adds of slagging;

Wherein, total ferrosilicon consumption can be expressed as:

m _FeSi＝m _{FeSi_h}+m _{FeSi_re}+m _{FeSi_a}

Further, wherein $m_{\mathrm{FeSi}\_a}=\frac{m_{\mathrm{ms}}\·{(\mathrm{Si}\%)}_{\mathrm{ms}}}{{(\mathrm{Si}\%)}_{\mathrm{FeSi}}},$ Wherein $W_{\mathrm{FeSi}\_\mathrm{re}}=\frac{V_{\mathrm{OCr}}\·1.25}{{(\mathrm{Si}\%)}_{\mathrm{FeSi}}};$

In formula, Fe _{Si_re}And Fe _{Si_a}Represent respectively reduction ferrosilicon and alloy ferrosilicon.

SiO in slag when wherein, reduction finishes ₂Be respectively with the required total amount of lime that adds of slagging

$W_{\mathrm{SiO}2}=[\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{m}_i\·{(\mathrm{Si}\%)}_{\mathrm{FeSi}}-m_{\mathrm{ms}}\·{(\mathrm{Si}\%)}_{\mathrm{ms}}]\·\frac{60}{28},$ $W_{\mathrm{lime}}=\frac{W_{\mathrm{SiO}2}}{{\mathrm{CaO}\%}_{\mathrm{lime}}}\·R_s.$

During AOD stove smelting stainless steel, the purposes of ferrosilicon comprises heating, reduction and alloying etc.The relation of ferrosilicon amount and hot metal ratio, scrap ratio is as shown in table 2,3.

Table 2 ferrosilicon addition and iron water amount add relation:

Mother liquor of stainless steel amount: iron water amount	100.0∶0.0	70.0∶30.0	50.0∶50.0	30.0∶70.0	0.0∶100.0
						Ferrosilicon addition (kg/t)	18.5	18.5	20.4	22.0	24.0

Table 3 ferrosilicon addition and steel scrap add relation:

Electric furnace mother liquor of stainless steel: adding amount of scrap steel	90.0∶10.0	85.0∶15.0	80.0∶20.0	75.0∶25.0	70.0∶30.0
						Ferrosilicon addition (kg/t)	21.8	24.7	27.7	30.6	33.1

Also need add part lime or rauhkalk in the oxygen supply converting process, with protection furnace lining and inhibition splash; Continue to add lime during reduction, adjust basicity of slag to rational scope, promote the carrying out of reduction process, be beneficial to eliminating and the control of deoxidation products.

In Fig. 2, in AOD stove smelting stainless steel process, heat income and energy output item should be equal as far as possible, in order to avoid the unnecessary loss of heat (energy consumption).

The heat balance process is as follows:

(1) heat income

In AOD stove smelting stainless steel process, enter furnace charge and comprise molten iron and slag making materials (all be similar to and be considered as rauhkalk) and the oxygen that is blown into and the assist gass (nitrogen and argon) such as slag, electric furnace mother liquor of stainless steel, steel scrap alloy material (mainly comprising ferrochrome, eilex, reduction ferrosilicon and alloy ferrosilicon and nickel etc.), lime and rauhkalk.

1. element oxidation thermal discharge

In smelting process, the element and the material that participate in oxidation have C, Cr, Si and CO etc.The oxidation reaction formula of each element and material and the heat that discharges are as follows respectively

C+1/2O ₂＝CO ΔH _C(J/kgC)

m _{C_R}·ΔH _C＝V _OC·ΔH _C/0.933

CO+1/2O ₂＝CO2 ΔH _CO(J/kgCO)

η _{CO_h}·W _{CO_sb}·ΔH _CO＝2.5·η _{CO_h}·V _OCO·ΔH _CO

Here η _{CO_h}Be the efficiency of heating surface of CO secondary combustion to molten steel.

Cr+3/4O ₂＝1/2Cr ₂O ₃ ΔH _C(J/kgCr)

m _{Cr_s}·ΔH _Cr＝3.095·VO _Cr·ΔH _Cr

Si+O ₂＝SiO ₂ ΔH _Si(J/kgSi)

m _ΔSi·ΔH _Si

Total chemical heat is

ΔH _r＝V _OC·ΔH _C/0.933+3.095·V _OCr·ΔH _Cr+

m _ΔSi·ΔH _Si+2.5·η _{CO_h}·V _OCO·ΔH _CO

2. the slagging of material is hot

SiO ₂Slagging heat: Q _SiO2=m _{Δ Si}* 1620

In formula, Q _SiO2Be the slagging heat of SiO2, kJ, m _SiSlagGenerate the amount of SiO2 for the Si oxidation, kJ.

P ₂O ₅Slagging heat: Q _P2O5=m " _P* 4880

In formula, Q _P2O5Be the slagging heat of P2O5, kJ, m _PSlagGenerate the amount of P2O5 for the P oxidation, kJ.

Total slagging heat: Q _ToSlag=Q _SiO2+ Q _P2O5

3. enter the stove material and bring physical thermal into

The molten iron fusing point is: T _MeltMI=1536-(a _CMI* 100+a _SiMI* 8+a _MnMI* 5+a _PMI* 30+a _SMI* 25)-6

The physical thermal that molten iron is brought into is: Q _mi=m _MI* (C _SMI(T _MeltMI-25)+218+C _LMI(T _MI-T _MeltMI))

The electric furnace mother liquor of stainless steel is brought physical thermal into:

Q _ms，in＝m _ms，in×(C _SMS×(T _meltMS-25)+H _mMS+C _LMS×(T _MS-T _meltMS))

In formula, Q _{Ms, in}Be molten steel physical thermal, kJ; m _{Ms, in}For entering stove molten steel amount, kg; C _SMSBe solid steel specific heat, kJ/kgK; T _MeltMSBe the molten steel fusing point, get 1450 ℃; H _mMSBe molten steel fusion enthalpy, kJ/kgK; C _LMSBe molten steel specific heat, kJ/kgK; T _MSBe liquid steel temperature, ℃;

(2) energy output item:

1. thermonegative reaction heat dissipation

Metal takes off the heat that C consumes: Q _C=V _OC/ 0.933 * 6244

In formula, Q _CBe the heat that decarburizing reaction consumes, kJ;

Metal takes off the heat that S consumes: Q _S=m " _S* 2143

In formula, Q _SThe heat that consumes for taking off the S reaction, kJ; m″ _SBe the amount of removing of S, kJ;

2. entrained sensible heats such as molten steel, slag, emergent gas, refractory lining and furnace shell; The sensible heat of each material can be expressed as follows

The physical thermal of furnace gas:

q _gas，out＝q _O2+q _N2+q _Ar+q _CO+q _CO2

Wherein the entrained heat of oxygen, nitrogen, argon gas, carbon monoxide and carbon dioxide can be expressed as respectively

q _O2＝V _O ^g·ρ _O·c _p，O·T _g

q _N2＝V _N·ρ _N·c _p，N·T _g

q _Ar＝V _Ar·ρ _Ar·c _p，Ar·T _g

q _CO＝V _CO·ρ _CO·c _p，CO·T _g＝2·(V _OC-V _OCO)·ρ _CO·c _p，CO·T _g

q _CO2＝V _CO2·ρ _CO2·c _p，CO2·T _g＝2·V _OCO·ρ _CO2·c _p，CO2·T _g

Molten steel physical thermal: Q _{Ms, out}=m _{Ms, out}* (C _SMS* (T _MeltMS-25)+H _mMS+ C _LMS* (T _MS-T _MeltMS))

In formula, Q _{Ms, out}Be molten steel physical thermal, kJ; m _{Ms, out}For generating molten steel amount, kg; C _SMSBe solid steel specific heat, kJ/kgK; T _MeltMSBe the molten steel fusing point, ℃; H _mMSBe molten steel fusion enthalpy, kJ/kgK; C _LMSBe molten steel specific heat, kJ/kgK; T _MSBe liquid steel temperature, ℃;

Slag is taken physical thermal out of

The slag growing amount is: $m_{\mathrm{Slag}}=\frac{60}{28}\·m_{\mathrm{Si}}^{\′\′}/\mathrm{\α}$

In formula, m " _SiThe amount of removing for Si; α is the content of SiO2 in slag.

Q _Slag＝m _Slag×(C _Slag×(T _Slag-25)+H _Slag)

In formula: Q _SlagFor slag is taken physical thermal out of, kJ; m _SlagBe slag growing amount, kg, kJ; C _SlagBe slag specific heat, kJ/kgK; T _SlagBe slag temperature, ℃; H _SlagBe slag fusion enthalpy, kJ/kgK.

3. body of heater surface radiating

$Q_{\mathrm{boby}}=\frac{\mathrm{\τ}}{G}\mathrm{\Σ}{q}_i\·A_i$

In formula, Q _BodyBe body of heater surface radiating, kJ; τ is the smelting cycle time, h; G is molten steel output, t; A _iBe body of heater i part area of dissipation, m ²q _iThe heat radiation of body of heater i part surface, kJ/m ²H.

$q_i=\left\{4.88\mathrm{\&epsiv;}\right[{\left(\frac{273+t_b}{100}\right)}^4-{\left(\frac{273+{\mathrm{<figure-callout\; id="0"\; label="t"\; filenames="HDA0000111614850000031.png,HDA0000111614850000032.png"\; state="\{\{state\}\}">t</figure-callout>}}_0}{100}\right)}^4]+{\mathrm{\&alpha;}}_d(t_b-t_0)\}\&times;4.1867$

In formula, ε is the surperficial blackness of body of heater; t _bBe the body of heater hull-skin temperature, ℃; t _eBe environment temperature, ℃; α _dBe body of heater outside surface convection transfer rate, kcal/ (m ²H ℃);

4. radiation loss heat dissipation capacity

The radiation position is the fire door place, because the AOD fire door is open type, on suspended hood is arranged, fire door is the sustained radiation heat release in smelting process.

$Q_{\mathrm{rad}}=4.1867\&times;\left\{4.88\mathrm{\&epsiv;}\right[{\left(\frac{273+t_f}{100}\right)}^4-{\left(\frac{273+t_e}{100}\right)}^4\&CenterDot;F\&CenterDot;\mathrm{\&Phi;}\&CenterDot;\frac{\mathrm{\&tau;}}{G}\}$

In formula, Q _radBe radiation loss heat dissipation capacity, kJ; F is the swept area of fire door, m2; Φ is the angle of radiation coefficient of fire door; τ is the radiated time of fire door, h; t _fBe the radiation temperature of fire door, ℃.

5. furnace lining recepts the caloric

Q _lin=G ₅(C _{Go out}t _{Go out}-C _Entert _Enter)

In formula, Q _linBe furnace lining caloric receptivity, kJ; G _{Furnace lining}Be furnace lining weight, kg; C _{Go out}Be specific heat under outside medial temperature in when tapping furnace lining, kJ/kg ℃; C _EnterSpecific heat under the medial temperature of the outside in furnace lining when entering steel, kJ/kg ℃; t _{Go out}Outside medial temperature in furnace lining during for tapping, ℃; t _{Go out}Outside medial temperature in furnace lining when entering steel, ℃;

(3) total amount of heat balance

In conjunction with above-mentioned analysis, the total amount of heat balance equation is:

ΔH _r+Q _toSlag+Q _mi+Q _ms，in＝Q _C+Q _S+q _gas，out+Q _ms，out+Q _Slag+Q _body+Q _rad+Q _lin。

Because the concrete computation process of self-adaptation aberration rate genetic algorithm and above steps realizes by software, these algorithms and computation process are prior art, those skilled in the art is after understanding and grasped the thinking that technical solution of the present invention is dealt with problems, need not to carry out performing creative labour, can realize goal of the invention of the present invention and technique effect, therefore above-mentioned algorithm and concrete computation process are no longer narrated at this.

Embodiment 1:

For certain AOD of steel mill stove, select steel grade SUS304, to use and carried out energy optimization with upper type, after its current power consumption values and optimization, the contrast of power consumption values is as shown in Figure 4.

In Fig. 4 a following line represent the AOD stove after optimizing can value, can be worth after steel grade SUS304 optimizes is 361kgce/t, above line represent the average energy value of AOD stove actual production, be 504kgce/tt, the average energy consumption 28.4% that reduces, result of calculation shows, uses genetic algorithm and carries out and can value optimization calculating obtain effect preferably.

Feed proportioning optimization is as shown in the table, and the energy optimization model is by planning as a whole electric furnace mother liquor of stainless steel, three deferrization water, coke, and the batchings such as ferrosilicon have realized reducing the goal of the invention of energy consumption.

AOD stove steel grade SUS304 feed proportioning optimization and corresponding binary coding are as follows:

The batching title	Steel grade SUS304 feed proportioning optimization/kg	The corresponding binary coding of feed proportioning optimization
			Raw material 1	70496.4	01111000101011001001
Raw material 2	40741.9	11111000101011100001
			Auxiliary material 1	11498.5	11110010000000111011
Raw material 3	743.9	10000110001100001100
			Auxiliary material 2	2676.3	11010011111101101011
Auxiliary material 3	1832.4	11000101110101110111
			Alloy 1	250.0	00100000110110000100
Alloy 2	3965.4	10110110110001011110
			Alloy 3	5977.3	10110000010001101100
Other auxiliary materials	11781.3	10010101010101111110

It is as follows to marking that batching is optimized forward and backward and corresponding various power consumption values:

The SUS304 list of ingredients

The batching title	Former batching/the kg of steel grade SUS304	Steel grade SUS304 feed proportioning optimization/kg
			Raw material 1	121600.0	70496.4
Raw material 2	0	40741.9
			Auxiliary material 1	1980.0-2500.0	11498.5
Raw material 3	300.0-400.0	743.9
			Auxiliary material 2	2000.0-2200.0	2676.3
Auxiliary material 3	1000.0-1200.0	1832.4

Alloy 1	0	250.0
			Alloy 2	4000.0-4500.0	3965.4
Alloy 3	3000.0	5977.3
			Other auxiliary materials	10791.0	11781.3

Embodiment 2:

For certain AOD of steel mill stove, select steel grade BN1D, to use and carry out energy optimization with upper type, after its current power consumption values and optimization, the contrast of power consumption values is as shown in Figure 5.

In Fig. 5 a following line represent the AOD stove after optimizing can value, can be worth after steel grade BN1D optimization is 341kgce/t, above line represent the average energy value of AOD stove actual production to be 500kgce/t, on average Energy Intensity Reduction 31.8%.

All the other are with embodiment 1.

AOD stove steel grade BN1D feed proportioning optimization and corresponding binary coding

The batching title	Steel grade SUS304 feed proportioning optimization/kg	The corresponding binary coding of feed proportioning optimization
			Raw material 1	63038.5	11100011110011011001
Raw material 2	38428.5	11010001010011011010
			Auxiliary material 1	14299.6	01000100010010001010
Raw material 3	133.3	00011000000101001001
			Auxiliary material 2	2855.4	00100000110011000000
Auxiliary material 3	285.7	11101011101001010010
			Alloy 1	18070.6	11000010010011110110
Alloy 2	5867.0	01111111001001110100
			Alloy 3	546.9	11101000110100011110
Other auxiliary materials	11549.8	11000110000010111110

It is as follows to marking that batching is optimized forward and backward and corresponding various power consumption values:

AOD stove steel grade BN1D list of ingredients

The batching title	Former batching/the kg of steel grade BN1D	Steel grade BN1D feed proportioning optimization/kg
			Raw material 1	111600.0	63038.5
Raw material 2	0	38428.5
			Auxiliary material 1	2580.0-3900.0	14299.6
Raw material 3	59.0-80.0	133.3
			Auxiliary material 2	2000.0-2200.0	2855.4
Auxiliary material 3	500.0-600.0	285.7
			Alloy 1	0	18070.6
Alloy 2	4500.0-5000.0	5867.0
			Alloy 3	300.0	546.9
Other auxiliary materials	8790.0	11549.8

Embodiment 3:

For certain AOD of steel mill stove, select steel grade SUH409L, to use and carried out energy optimization with upper type, after its current power consumption values and optimization, the contrast of power consumption values is as shown in Figure 6.

In Fig. 6 a following line represent the AOD stove after optimizing can value, can be worth after steel grade SUH409L optimization is 406kgce/t, above line represent the average energy value of AOD stove actual production to be 495kgce/t, energy consumption has on average reduced by 220.0%.

All the other are with embodiment 1.

AOD stove steel grade SUH409L feed proportioning optimization and corresponding binary coding

The batching title	Steel grade SUS304 feed proportioning optimization/kg	The corresponding binary coding of feed proportioning optimization
			Raw material 1	105746.2	00101100000111101111
Raw material 2	2593.7	11010101001010011110
			Auxiliary material 1	3708.9	10110001110010001101
Raw material 3	1338.7	00000001001100000111
			Auxiliary material 2	2117.6	11101000100010111011

Auxiliary material 3	918.4	11010101111101010010
			Alloy 1	9510.3	11010000101101010111
Alloy 2	1634.6	00110110010000010001
			Alloy 3	7323.5	11010110100011001000
Other auxiliary materials	11134.5	01011101111100100110

It is as follows to marking that batching is optimized forward and backward and corresponding various power consumption values:

AOD stove steel grade SUH409L list of ingredients

The batching title	Former batching/the kg of steel grade SUH409L	Steel grade SUH409L feed proportioning optimization/kg
			Raw material 1	121700.0	105746.2
Raw material 2	0	2593.7
			Auxiliary material 1	100.0-200.0	3708.9
Raw material 3	500.0-1000.0	1338.7
			Auxiliary material 2	1500.0-2000.0	2117.6
Auxiliary material 3	600.0-700.0	918.4
			Alloy 1	0	9510.3
Alloy 2	900.0-1000.0	1634.6
			Alloy 3	2000.0	7323.5
Other auxiliary materials	9790.0	11134.5

To sum up, due to the present invention planned as a whole the AOD stove burden structure, mixed carbon comtent, oxygen-supplying amount, add iron water amount, add the many factors such as electric furnace mother liquor of stainless steel amount, take material balance as the basis, set up the energy equilibrium constraint, adopt self-adaptation aberration rate genetic algorithm for solving, utilize the existing equipment condition, under the prerequisite that the indexs such as basicity that guarantee AOD stove tapping molten steel chemical composition, temperature, quality, cost, slag meet the demands, the AOD furnace foundation is reduced significantly in the comprehensive average energy consumption of energy carrier.

The present invention can be widely used in the comprehensive average energy consumption control field of AOD stove.

Claims (14)

1. AOD stove energy optimization method based on energy carrier, comprise the production steel grade for appointment, gather and regulate/control the supplies consumption amount of AOD stove, under the prerequisite that the basicity index that guarantees AOD stove tapping molten steel chemical composition, temperature, quality, cost and slag meets the demands, make the comprehensive average Energy Intensity Reduction of AOD stove, it is characterized in that:

Existing each production material consumption statistics of A, collection/analysis AOD stove;

B, according to production technology and/or existing each production material consumption statistics, determine the parameter set of AOD stove energy optimization model;

C, take material balance as the basis, set up the energy equilibrium constraint condition of described parameter set;

D, according to the energy equilibrium constraint condition of described parameter set, set up the AOD stove carry can value the energy optimization model;

E, employing self-adaptation aberration rate genetic algorithm are found the solution described energy optimization model;

F, obtain the optimum value of AOD stove energy optimization simulated target function;

G, according to the optimum value of AOD stove energy optimization simulated target function, optimize/regulate dosage or the proportion scale of AOD stove;

H, according to the optimum value of AOD stove energy optimization simulated target function, regulate/control the supplies consumption amount of AOD stove;

I, based on the existing equipment condition, under the prerequisite that the basicity index that guarantees AOD stove tapping molten steel chemical composition, temperature, quality, cost and slag meets the demands, make the AOD furnace foundation in the comprehensive average Energy Intensity Reduction of energy carrier.

2. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that each production material consumption being converted to the unified expression form of energy carrier form when determining the parameter set of described AOD stove energy optimization model.

3. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that after the optimum value that obtains AOD stove energy optimization simulated target function, with the binary coding formal output of correspondence, regulate/control the supplies consumption amount of AOD stove.

4. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, each production material consumption that it is characterized in that described AOD stove comprises the consumption of electric furnace mother liquor of stainless steel, three deferrization water, lime, small pieces steel scrap, ferrosilicon, coke, high carbon ferro-chrome, general nickel, stainless steel scrap, oxygen, nitrogen and argon gas at least.

5. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that described energy equilibrium constraint condition comprises constraint, gas consumption, the duration of heat, ferrosilicon and the lime consumption of the restriction of precious alloy, molten steel amount at least.

6. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that the objective function of described AOD stove energy optimization model is:

$\mathrm{\&phi;}=\min \underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}(W_i\&CenterDot;E_i)/\mathrm{MS}$

Wherein, φ is energy consumption per ton steel, and unit is J; W _iThe weight of-parameter i, unit is kg; E _iBe being worth of parameter i, unit is J/kg; The molten steel amount of MS for producing, unit is kg;

Subscript i is comprised of 12 energy carriers, is respectively: 1 electric furnace mother liquor of stainless steel, 2 three deferrization water, 3 lime, 4 small pieces steel scraps, 5 ferrosilicon, 6 coke, 7 high carbon ferro-chromes, 8 general nickel, 9 stainless steel scraps, 10 oxygen, 11 nitrogen, 12 argon gas.

7. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that the objective function of described AOD stove energy optimization model is:

Wherein, φ is energy consumption per ton steel, J; W _iThe weight of-parameter i, kg; The molten steel amount of MS for producing, kg;

Subscript i is comprised of 12 energy carriers, is respectively: 1 electric furnace mother liquor of stainless steel, 2 three deferrization water, 3 lime, 4 small pieces steel scraps, 5 ferrosilicon, 6 coke, 7 high carbon ferro-chromes, 8 general nickel, 9 stainless steel scraps, 10 oxygen, 11 nitrogen, 12 argon gas.

8. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that described self-adaptation aberration rate genetic algorithm comprises the following steps: at least

Step 1) determine the parameter set of AOD stove energy optimization model;

Step 2) initiation parameter;

Step 3) carry out binary coding, 20 binary strings of each parameter coding, totally 240 binary strings;

Step 4) produce initial population, produce body one by one and forms chromosomal gene code by the binary string of the random generation of string long 240, produce the individuality composition population of some, population scale is 80;

Step 5) calculate fitness, this function is minimized, and adopts the method for penalty function,

Step 6) carry out Selecting operation based on roulette mechanism;

Step 7) carry out the single-point crossing operation, select at random a point of crossing, intersect;

Step 8) make a variation, 1% gene morphs, and each gene has identical chance to morph;

Step 9) increase iterations n=n+1;

Step 10) be n=5000 when reaching maximum iteration time, calculate and finish, the output optimal value; Otherwise, turn back to step 6.

9. according to the AOD stove energy optimization method based on energy carrier claimed in claim 8, it is characterized in that the fitness function that adopts is when calculating described calculating fitness:

f(s)＝NN-(f(x)+n*N)，

Wherein, NN is maximum value, NN=10000000, and f (x) is objective function, and n is that parameter does not satisfy the number of times of constraint, and N is penalties, N=200000.

10. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, the restriction that it is characterized in that described precious alloy comprises at least to the restriction of Cr content with to the restriction of Ni content, wherein, and to being restricted to of Cr content:

$\underset{i=0}{\overset{n}{\mathrm{\&Sigma;}}}{m}_i\&CenterDot;{(\mathrm{Cr}\%)}_i=m_{\mathrm{ms}}\&CenterDot;{(\mathrm{Cr}\%)}_{\mathrm{ms}}/{\mathrm{\&eta;}}_{\mathrm{Cr}}$

To being restricted to of Ni content:

$\underset{i=0}{\overset{n}{\mathrm{\&Sigma;}}}{m}_i\&CenterDot;{(\mathrm{Ni}\%)}_i=m_{\mathrm{ms}}\&CenterDot;{(\mathrm{Ni}\%)}_{\mathrm{ms}}/{\mathrm{\&eta;}}_{\mathrm{Ni}}$

In formula, m _iBe the quality of feed stock for blast furnace i, (Cr%) _iCr content for feed stock for blast furnace i;

m _msBe AOD stove tapping Metal Weight, (Ni%) _iNi content for feed stock for blast furnace i.

11. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that being constrained to of described molten steel amount:

Q ₁≤m _MS≤Q ₂

In formula, Q ₁Be the lower limit of technological requirement AOD stove molten steel amount, Q ₂The upper limit for technological requirement AOD stove molten steel amount.

12. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that described gas consumption comprises total oxygen-supplying amount at least, its described total oxygen-supplying amount is:

V _O＝V _O0+V _O1+V _O2+V _O3+V _O4+V _O5

In formula, V _O0Be oxygen utilization in early stage, V _O1Be the oxygen utilization of main carbon period C percentage composition from [C]-1 o'clock, V _O2Be the oxygen utilization of main carbon period C percentage composition during from 1-0.35, V _O3Oxygen utilization when dynamically carbon period C percentage composition is from 0.35-0.11, V _O4Oxygen utilization when dynamically carbon period C percentage composition is from 0.11-0.07, V _O5Oxygen utilization when dynamically carbon period C percentage composition is from 0.07-0.03.

13. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that be the carbon/silicon burning time of total duration of heat or exothermic mixture the described duration of heat, wherein, should not surpass 90min total duration of heat; Should not surpass 20min burning time as the carbon of exothermic mixture/silicon.

14. according to the AOD stove energy optimization method based on energy carrier claimed in claim 1, it is characterized in that described ferrosilicon and lime consumption comprise when total ferrosilicon consumption or reduction finish SiO in slag at least ₂With the required total amount of lime that adds of slagging;

Wherein, total ferrosilicon consumption can be expressed as:

m _FeSi＝m _{FeSi_h}+m _{FeSi_re}+m _{FeSi_a}

Further, wherein $m_{\mathrm{FeSi}\_a}=\frac{m_{\mathrm{ms}}\&CenterDot;{(\mathrm{Si}\%)}_{\mathrm{ms}}}{{(\mathrm{Si}\%)}_{\mathrm{FeSi}}},$ Wherein $W_{\mathrm{FeSi}\_\mathrm{re}}=\frac{V_{\mathrm{OCr}}\&CenterDot;1.25}{{(\mathrm{Si}\%)}_{\mathrm{FeSi}}};$

In formula, Fe _{Si_re}And Fe _{Si_a}Represent respectively reduction ferrosilicon and alloy ferrosilicon;

SiO in slag when wherein, reduction finishes ₂Be respectively with the required total amount of lime that adds of slagging

$W_{\mathrm{SiO}2}=[\underset{i=1}{\overset{n}{\mathrm{\&Sigma;}}}{m}_i\&CenterDot;{(\mathrm{Si}\%)}_{\mathrm{FeSi}}-m_{\mathrm{ms}}\&CenterDot;{(\mathrm{Si}\%)}_{\mathrm{ms}}]\&CenterDot;\frac{60}{28};$

$W_{\mathrm{lime}}=\frac{W_{\mathrm{SiO}2}}{{\mathrm{CaO}\%}_{\mathrm{lime}}}\&CenterDot;R_s.$

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