CN102021007B - Low-cost coking coal blending system - Google Patents

Abstract

The invention relates to a low-cost coking coal blending system which can be applied to controlling the precise coal blending and the procurement plan making of a coking plant. In the system, a coal and coke record management module, a coke quality prediction module, a by-product value prediction module and an optimizing coal blending module are tightly combined by a server and a network, real-time update is carried out, and the lowest-net-cost coal blending scheme meeting the coke quality requirements and all technology, warehousing and procurement limiting conditions is automatically obtained by a programming solver method under the limiting conditions such as coal quality, coke quality prediction, coal net price, coal reserve and procurement, thereby precisely controlling the automaticcoal blending system and achieving the purposes of improving and stabilizing the coke quality and reducing the coking cost.

Description

Low cost coke making and coal blending system

Technical field

The present invention relates to be applied to the coke making and coal blending system in coking field, particularly a kind of coke making and coal blending system that realizes low pure cost.

Background technology

Along with development of global economy, it is particularly in short supply that Nonrenewable resources such as coal become, and price rapidly goes up, and this brings huge cost pressure to steel industry.Meanwhile because the fluctuation of domestic Coal Quality is bigger, and detection means is not comprehensive, most coke-oven plants can only determine the coal blending ratio by the method for experience and small coke oven experiment, make that the coke quality fluctuation is bigger, have a strong impact on the normal running of blast furnace.For solving the quality problems of coke, domestic scholars has been carried out the research of a large amount of prediction of coke quality, but mostly need very comprehensively coal and small coke oven experimental analysis data, the prognoses system complexity, and do not considered that the byproduct that produces in the coal process of coking to the influence of coking coal cost, was difficult to use in real work.

Summary of the invention

The objective of the invention is to propose a kind of low-cost coke making and coal blending system, it can be under restricted conditions such as Coal Quality, prediction of coke quality, coal net price (coal price-by-product price), coal deposit and buying, draw the minimum coal blending scheme of pure cost that satisfies coke quality requirement and all technology, storage and buying restricted condition, satisfy the needs of practical application, thereby overcome deficiency of the prior art.

For achieving the above object, the present invention has adopted following technical scheme:

A kind of low-cost coke making and coal blending system is characterized in that, described low-cost coke making and coal blending system comprises:

Coal and coke characteristic records administration module, in order to the characteristic to coal import, revise, two secondary qualities calculate and average value in interval is calculated, and detect data thereby replenish coal, are convenient to the prediction of coke strenth;

By-product value forecasting module is worth in order to calculate the by-product that every kind of coal produces in process of coking, thereby selects the minimum coal blending procurement scheme of net price in coal buying optimization system;

And, optimize the coal blending module, be used for integrating coal and coke characteristic records administration module, prediction of coke quality module and by-product value forecasting module, and the method for utilizing planning to find the solution obtain net price minimum, simultaneously satisfy that coke quality requires and all restricted conditions under the coal blending scheme, send to the Automatic coal blending system again and carry out accurate coal blending.

Say further, described coal and coke characteristic records administration module be according to following formula to the characteristic of coal import, revise, two secondary qualities calculate and average value in interval is calculated, and detect data thereby replenish coal:

Ro _max＝3.9+0.069×MF-0.238×Vm _daf-0.085×MF ²-0.003×MF×Vm _daf+0.001×Vm _daf ²+0.007×MF ²×Vm _daf+0.0012×MF×Vm _daf ²-0.0029×MF ²×Vm _daf ²

Wherein, the dry ash-free basis fugitive constituent Vm of caking index G=12～100 of mixed coal, mixed coal _Daf=15～37, the maximum vitrinite reflectance Ro of mixed coal _Max=1.1～1.3, Ji Shi maximum fluidity MF=0～4 of mixed coal, and

MF=0.08837 * G-3.2697 is when G＞37

MF=0 is when G≤37;

The prediction of coke quality module, it utilizes following formula to calculate the performance perameter X of mixed coal according to the historical coal blending data of coal and the collection of coke characteristic records administration module:

$X=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\mathrm{NiXi}$

X wherein _iBe single coal performance perameter, n of planting _iBe single coal blending ratio of planting coal in the mixed coal,

And comprise the prediction of coke quality of coke barrate strength M40, coke ash A and coke sulfur S prediction,

M40＝0.18G+26.1 Ro _max-0.13A+40.25，

A=A _{Mixed coal}/ (1-0.894 * V _{The d mixed coal})

S=0.567 * S _{Mixed coal}/ (1-0.894 * V _{The d mixed coal})

In the following formula, M40=80～92, mixed coal ash content A _{Mixed coal}=9～13;

Described by-product value forecasting module is to calculate the by-product value that every kind of coal produces according to following formula in process of coking, thereby the coal blending procurement scheme that the selection net price is minimum in coal buying optimization system:

By-product is worth=changes product price+coke powder dedusting ash price

Change the price of product price=change production capacity * unit energy product correspondence,

Net price=coal price-by-product price.

Describedization product price=change production capacity * unit energy product actual average price=C * Q _{The bp theoretical value)}* m unit/MJ,

Q _{The bp theoretical value}(MJ/kgcoal)=Q _Coal-Q _Cokc-Q _H2S-H _React

＝(1-A/100)×(-0.00508×(V _mdaf)2+0.2305×Vm _daf+34.19)×1.0689-3.5103-33.18×(1-A/100-Cv×Vm _d/100)-16.51×Ts/100×(1-Ys/100)-ΔH _react

Work as Vm _Daf≤ 23.34 o'clock, Δ H _React(MJ/kg coal)=0.006968 * Vm _Daf,

Work as Vm _Daf＞23.34 o'clock, Δ H _React(MJ/kg coal)=-0.002695 * Vm _Daf ²+ 0.132755 * Vm _Daf-1.4677,

Q in the formula _BpFor changing production capacity, Q _TarBe tar energy, Q _BenBe clumsy energy, Q _GasBe coke-oven gas energy, Q _CoalHeat, Q for coal _CokeHeat, Q for coke _H2SHeat, Δ H for hydrogen sulfide _ReactBe the pyrogenic reaction heat, Cv is that volatile matter correction factor, C are coefficient of production.

Q _coke(MJ/kg coal)＝33.18×(1-A/100-Cv×Vm _d/100)。

Q _H2S(MJ/kg coal)＝16.51×Ts/100×(1-Ys/100)，

Ts=0.15% in the following formula～2% is the sulphur content in the mixed coal, and Ys=55%～60% is the transformation efficiency of sulphur in the process of coking.

Description of drawings

Below in conjunction with drawings and the specific embodiments technical scheme of the present invention is further described.

Fig. 1 is maximum fluidity MF, fugitive constituent Vm _DafWith maximum vitrinite reflectance Ro _MaxGraph of a relation;

Fig. 2 is coke strenth M40 predictor and the contrast synoptic diagram of producing measured value;

Fig. 3 is low-cost coke making and coal blending system flowchart;

Fig. 4 is the measured value graphic representation of coke strenth after the low-cost coke making and coal blending of the employing system.

Embodiment

The present invention combines closely coal and coke characteristic records administration module, prediction of coke quality module, by-product value forecasting module and the optimization coal blending module set up by server and network, real-time update, can be under restricted conditions such as Coal Quality, prediction of coke quality, coal net price (coal price-by-product price), coal deposit and buying, the method of utilizing planning to find the solution draws automatically and satisfies the coal blending scheme that coke quality requires and the pure cost of all technology, storage and buying restricted condition is minimum, realizes low-cost accurately coal blending.

The present invention is achieved through the following technical solutions:

1. set up coal and coke characteristic records administration module

This module comprises data gathering and the calculating of coal performance, production coal blending ratio, coke quality, collect results of performance analysis, production coal blending ratio and the corresponding coke quality parameter of factory's coal in real time by terminal computer, and set up database, and then realize the coal performance input, modification, calculate, average, and the input of production coal blending ratio and coke quality parameter, become prediction of coke quality module, by-product value forecasting module and optimize the source data of coal blending module.

Because the restriction of appointed condition, quality testing department can only provide the conventional technical analysis result of coal usually, as volatile matter Vm _Daf, ash content Ash, sulphur content S, moisture and parameters such as caking index G, cuticle thickness Y, but can not provide the vital coal of prediction coke strenth rank parameter-maximum vitrinite reflectance Ro _MaxThis case contriver is by G and Vm _DafSuccessfully calculate the maximum vitrinite reflectance Ro of coal _MaxAt first the caking index G value of coal is converted to maximum fluidity MF under study for action, wherein the G value (scope of application; 12～100), Vm _Daf(scope of application exists; 15～37);

Conversion formula is: MF=0.08837 * G-3.2697, and when G＞37

MF=0 is when G≤37

Then by coal maximum fluidity MF, volatile matter Vm _DafAnd the relation between maximum vitrinite reflectance calculates Ro _Max(consult Transaction ISIJ, 417-424, Vol 23,1983).

Fig. 1 has represented the maximum vitrinite reflectance (RO of coal _Max) with the dry ash-free basis fugitive constituent (Vm of coal _Daf) and Ji Shi maximum fluidity (MF) between relation, its corresponding calculation formula is:

Ro _max＝3.9+0.069×MF-0.238×Vm _daf-0.085×MF ²-0.003×MF×Vm _daf+0.001×Vm _daf ²+0.007×MF ²×Vm _daf+0.0012×MF×Vm _daf ²-0.0029×MF ²×Vm _daf ²

Wherein, the scope of application of MF: 0～4, Vm _DafThe scope of application: 15～37.

2. set up the prediction of coke quality module

Under certain coking working condition, the quality of coal is the deciding factor that influences coke quality.

Coke strength index F=f (mixed coal performance perameter G, Y, Ash, S, Ro _Max, Vm _Daf)

At first call in the historical coal blending data of gathering in coal and the coke characteristic records management system.The performance perameter that calculates mixed coal by single kind coal detect parameters and coal blending ratio is as follows:

$X=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\mathrm{NiXi}$

X-mixed coal performance perameter

X _i-single coal performance perameter of planting

n _iSingle coal blending ratio of planting coal in the-mixed coal

(2.1) coke strenth M40 prediction

The cold strength M40 of the coke that uses every kind of mixed coal to produce has been carried out regression analysis to different mixed coal parameters combination respectively, drawn by three variable: G, Ro after relatively _MaxWith ash content prediction coke cold strength M40, be to have higher relation conefficient and littler standard deviation under 0.95 the situation in degree of confidence, can effectively predict the cold strength of coke.Developed the predictive equation of coke strenth M40 accordingly.During prediction M40, with coal analytical data (G value, fugitive constituent etc.), calculate and convert auxiliary data Ro to _Max, predictive equation and predict the outcome as follows:

M40＝0.18G+26.1 Ro _max-0.13A+40.25

M40 wherein: the coke barrate strength (scope of application; 80～92)

G: the caking index (scope of application of mixed coal; 60～85)

Ro _Max: the maximum vitrinite reflectance (scope of application of mixed coal; 1.1～1.3)

A: the mixed coal ash content (scope of application; 9～13)

M40 predict the outcome with the relation of coke oven production measuring result as shown in Figure 2, under the condition of degree of confidence 0.95, relation conefficient 0.726, standard deviation 0.682 illustrates that Forecasting Methodology is effective.

(2.2) ash content of coke: A=A _{Mixed coal}/ (1-0.894 * V _{The d mixed coal})

(2.3) coke sulfur: S=0.567 * S _{Mixed coal}/ (1-0.894 * V _{The d mixed coal})

3. by-product value forecasting module

Can calculate the net price (coal price-by-product price) of every kind of coal by the by-product value forecasting in the process of coking, thereby calculate the minimum scheme of mixed coal net price.

The prediction that by-product is worth is divided into two portions: change the prediction of product price expectation and coke powder+dedusting ash price

(3.1) prediction of change product product price;

The price of the energy * unit energy product correspondence of the price=change product of change product

Change production capacity Q _Bp=Q _Tar+ Q _Ben+ Q _Gas=Q _Coal-Q _Coke-Q _H2S-Δ H _React

Q in the following formula _Bp: change production capacity Q _Tar: the tar energy

Q _Ben: clumsy energy Q _Gas: the coke-oven gas energy

Q _Coal: the heat Q of coal _Coke: the heat of coke

Q _H2S: the heat Δ H of hydrogen sulfide _React: pyrogenic reaction heat

(3.1.1) the energy Q of coal _Coal(consulting http://www.energy.psu.edu/copl/doesb.html) Q _Coal(MJ/kg)=(1-A/100) * (0.00508 * (Vm _Daf) ²+ 0.2305 * Vm _Daf+ 34.19) * 1.0689-3.5103

Vm in the following formula _Daf: the dry ash-free basis volatile matter of coal, (scope of application exists; 15～37);

A: the pit ash, (scope of application; 9～13).

(3.1.2) the energy Q of the coke of every kg dry coal generation _Coke

(consulting www.docstoc.com/docs/2480818/Aval-7):

Q _coke(MJ/kg coal)＝33.18×(1-A/100-Cv×Vm _d/100)

Cv in the following formula: volatile matter correction factor; A: pit ash; Vm _d: the butt volatile matter of coal.

(3.1.3) H ₂The energy Q of S _H2S

Q _H2S(MJ/kg coal)＝16.51×Ts/100×(1-Ys/100)

Ts in the following formula: the sulphur content in the mixed coal, the scope of application (0.15%～2%).

Ys: the transformation efficiency of sulphur in the process of coking, the scope of application (55%～60%)

(3.1.4) reaction heat Δ H _React

Work as Vm _Daf≤ 23.34 o'clock, Δ H _React(MJ/kg coal)=0.006968 * Vm _Daf,

Work as Vm _Daf＞23.34 o'clock, Δ H _React(MJ/kg coal)=-0.002695 * Vm _Daf ²+ 0.132755 * Vm _Daf-1.4677

The energy of changing product in theory is:

Q _bp(MJ/kgcoal)＝Q _coal-Q _coke-Q _H2S-H _react

＝(1-A/100)×(-0.00508×(Vm _daf)2+0.2305×Vm _daf+34.19)×1.0689-3.5103-33.18×(1-A/100-Cv×Vm _d/100)-16.51×Ts/100×(1-Ys/100)-ΔH _react

Certainly exist a large amount of losses in the actual production, thereby need multiply by a coefficient of production C in front.

The predictive equation of pragmatize production capacity is: Q _{Bp (actual value)}(MJ/kgcoal)=C * Q _{Bp (theoretical value)}Change the calculating of product price

According to energy and the price of each main by-product in the production report, the actual average price of unit energy product is m unit/MJ.Change product price P (unit/kg)=C * Q _{Bp (theoretical value)}* m

(3.2) prediction of coke powder+dedusting ash price

The metallurgical coke rate is 89% among present full Jiao per ton in coke-oven plant.The average complete burnt price that produces coke powder and dedusting ash per ton is n unit, and the metallurgical coke rate is Ym.The price that metallurgical coke per ton produces coke powder+dedusting ash is n/Ym (unit/ton metallurgical coke)

(3.3) price of the by-product of the generation of 1 ton of metallurgical coke of every smelting

=(changing product price/ton coal)/coke yield/metallurgical coke rate+(n unit/complete burnt)/metallurgical coke rate.

=C * Q _{Bp (theoretical value)}* m * 1000/ (1-Cv * Vm _d/ 100)/Ym+n/Ym (unit)

4. set up and optimize the coal blending module

By master server and each terminal computer, coal and coke characteristic records administration module, prediction of coke quality module, by-product value forecasting module are integrated, it is minimum that the method for utilizing planning to find the solution is obtained net price, satisfies the coal blending scheme under coke quality requirement and all restricted conditions simultaneously.

Comprise in the coal buying optimization module:

1) technical limitation input (M40, the ash content in the coke and sulfur, coke output etc.);

2) supply restriction input (price, the upper and lower bound of storage amount, amount of purchase);

3) the coal blending scheme optimization calculates.

The technical limitation condition is as shown in table 1.The limited range of G value, Romax value and the volatile matter Vdaf of mixed coal is determined in test according to the 40kg small coke oven; The ash content of coke, sulfur and M40 value require to limit according to blast furnace operating; Parameters such as coal blending ratio can be according to coke oven historical operation parameter setting.

The technical indicator restricted condition of table 1 mixed coal

The supply restricted condition is respectively by two terminal inputs of purchasing department and coke-oven plant, and the buying terminal is imported coal price and buying limit, coking terminal input storage amount.

The supply restricted condition of table 2 mixed coal

The supply condition

The A coal

The B coal

The C coal

The D coal

The E coal

The F coal

The G coal

The H coal

The I coal

The G coal

Coal

Price

The storage amount

The upper limit (ton)

Lower limit (ton)

The coal blending optimizing process only need be clicked the computation optimization forms, import the coke oven coke scheduled production in this month, system can call coal data, prediction of coke quality, by-product value forecasting, technical limitation, supply restricting data automatically, the method of utilizing planning to find the solution, minimum with the net price of producing 1 ton of required mixed coal of coke is objective function, provide the optimization coal blending ratio that satisfies all qualificationss, this result is input to silo Automatic coal blending system and carries out accurate coal blending.Can significantly reduce the mixed coal cost, stabilize and increase coke quality.The total system operating process as shown in Figure 3.

5. the field experiment of coke-oven plant's coke oven

In order to verify the validity of low-cost coke making and coal blending systematic direction coal blending, we have carried out the experiment of coke oven coal-blending coking in the coke-oven plant.

5.1 content of the test

Optimize: available coal is carried out the SOPCC computation optimization in during the use-testing

Coal blending: be adjusted into the optimization proportioning step by step from daily proportioning, blending ratio is for example shown in table 4, the table 5.

Equipment: two the 6m coke ovens in coke-oven plant;

Coking time: 18.5 hours

Table .3 coke-oven plant coke oven experiment proportioning

Test No..	I	II	III	IV	V
						Daily proportioning (%)	100	50	35	20	0
Optimize proportioning (%)	0	50	65	80	100
						Coking coal (%)	41.0	40.5	40.3	40.2	40.0

Rich coal (%)	26.0	22.0	20.8	19.6	18.0
						1/3 coking coal (%)	25.0	27.5	28.3	29.0	30.0
Lean coal (%)	8.0	10.0	10.6	11.2	12.0
						The cost ratio that reduces	0	41	54	66	83

Table 4 coke oven experiment coal blending ratio

Test No..	I	II	III	IV
					Coal	Ratio %	Ratio %	Ratio %	Ratio %
The X1 coking coal	10.0	5.3	4.7	2.7
					The X2 coking coal	10.0	14.7	15.7	18.0
The X3 coking coal	7.0	13.3	14.7	15.7
					The X4 coking coal	3.3	1.7	1.7	1.7
The X5 coking coal	10.7	5.0	3.3	2.0
					The X6 rich coal	5.3	2.7	2.0	1.1
The X7 rich coal	10.7	5.3	5.3	4.3
					The X8 rich coal	5.3	2.7	1.7	1.1
The X9 rich coal	4.7	11.3	12.0	13.0
					Jiao X101/3	4.7	7.7	8.0	14.7
X11 1/3 Jiao	12.0	13.3	14.7	8.2
					X12 1/3 Jiao	6.7	5.3	4.0	5.0
The X13 lean coal	1.7	1.7	1.7	1.7
					The X14 lean coal	4.0	5.0	5.3	5.5
The X15 lean coal	4.0
					The X16 lean coal			5.3

5.2 test-results

From the contrast of experimental result shown in Figure 4 and predictor (A-predictor, B-measured value) as can be seen, the coke strenth M40 that records and predictor basically identical.The coke oven evidence, this low cost coke making and coal blending system is effectively, reliably.Calculating shows uses about 30～80 yuan of/ton coke of the reducible cost of this optimization system.

Above embodiment only is used for explanation content of the present invention, and in addition, the present invention also has other embodiment.But all employings are equal to replaces or technical scheme that the equivalent deformation mode forms all drops in protection scope of the present invention.

Claims (1)

1. a low-cost coke making and coal blending system is characterized in that, described low-cost coke making and coal blending system comprises:

Coal and coke characteristic records administration module, its according to following formula to the characteristic of coal import, revise, two secondary qualities calculate and average value in interval is calculated, and detect data thereby replenish coal, are convenient to the prediction of coke strenth:

Ro _max＝3.9+0.069×MF-0.238×Vm _daf-0.085×MF ²-0.003×MF×Vm _daf+0.001×Vm _{da f} ²+0.007×MF ²×Vm _daf+0.0012×MF×Vm _daf ²-0.0029×MF ²×Vm _daf ²

Wherein, the dry ash-free basis fugitive constituent Vm of caking index G=12～100 of mixed coal, mixed coal _Daf=15～37, the maximum vitrinite reflectance Ro of mixed coal _Max=1.1～1.3, Ji Shi maximum fluidity MF=0～4 of mixed coal, and

MF=0.08837 * G-3.2697 is when G＞37

MF=0 is when G≤37;

The prediction of coke quality module, it utilizes following formula to calculate the performance perameter X of mixed coal according to the historical coal blending data of coal and the collection of coke characteristic records administration module:

$X=\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\mathrm{NiXi}$

X wherein _iBe single coal performance perameter, N of planting _iBe single coal blending ratio of planting coal in the mixed coal,

And comprise coke barrate strength M40, coke ash A _CokePredict at interior prediction of coke quality with coke sulfur S,

M40=0.18G+26.1Ro _Max-0.13A _{Mixed coal}+ 40.25,

A _Coke=A _{Mixed coal}/ (1-0.894 * V _{The d mixed coal})

S=0.567 * S _{Mixed coal}/ (1-0.894 * V _{The d mixed coal})

In the following formula, M40=80～92, mixed coal ash content A _{Mixed coal}=9～13;

By-product value forecasting module is worth in order to calculate the by-product that every kind of coal produces in process of coking according to following formula, thereby selects the minimum coal blending procurement scheme of net price in coal buying optimization system:

By-product is worth=changes product price+coke powder dedusting ash price

Change the price of product price=change production capacity * unit energy product correspondence,

Coal net price=coal price-by-product is worth;

And, optimize the coal blending module, be used for integrating coal and coke characteristic records administration module, prediction of coke quality module and by-product value forecasting module, and the method for utilizing planning to find the solution obtain net price minimum, simultaneously satisfy that coke quality requires and all restricted conditions under the coal blending scheme, send to the Automatic coal blending system again and carry out accurate coal blending;

Price=C * the Q of describedization product price=change production capacity * unit energy product correspondence _{The bp theoretical value}* m unit/MJ,

Q _{The bp theoretical value}(MJ/kgcoal)=Q _Tar+ Q _Ben+ Q _Gas=Q _Coal-Q _Coke-Q _H2S-Δ H _React=(1-A _Coal/ 100) * (0.00508 * (Vm _Daf) ²+ 0.2305 * Vm _Daf+ 34.19) * 1.0689-3.5103-33.18 * (1-A _Coal/ 100-Cv * Vm _d/ 100)-16.51 * T _S/ 100 * (1-Y _S/ 100)-Δ H _React,

Work as Vm _Daf≤ 23.34 o'clock, Δ H _React(MJ/kg coal)=0.006968 * Vm _Daf,

Work as Vm _Daf＞23.34 o'clock, Δ H _React(MJ/kg coal)=-0.002695 * Vm _Daf ²+ 0.132755 * Vm _Daf-1.4677,

Q in the formula _{The bp theoretical value}Be theoreticization production capacity, Q _TarBe tar energy, Q _BenBe crude benzol energy, Q _GasBe coke-oven gas energy, Q _CoalHeat, Q for coal _CokeHeat, Q for coke _H2SHeat, Δ H for hydrogen sulfide _ReactBe the pyrogenic reaction heat, Cv is that volatile matter correction factor, C are coefficient of production;

Q _Coke(MJ/kg coal)=33.18 * (1-A _Coal/ 100-Cv * Vm _d/ 100), Vm in the formula _dBe the butt volatile matter of coal, A _CoalBe pit ash;

Q _H2S(MJ/kg coal)=16.51 * T _S/ 100 * (1-Y _S/ 100), wherein, T _S=0.15%～2%, be the sulfur-bearing ratio in the mixed coal; Y _S=55%～60%, be the productive rate of sulphur in the process of coking.

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