JPS59179582A - Production of coke - Google Patents

Abstract

PURPOSE:To minimize the amount of a fuel gas required for carbonization, by analyzing the relation between the effective necessary quantity of heat and physical properties of raw material coal, obtaining a multiple regression formula, and selecting and mixing the raw material coal, etc. CONSTITUTION:A multiple regression formula containing an effective necessary quantity for carbonization as an independent variable and the ratio between hydrogen and carbon and ratio between oxygen and carbon in the terms of independent variables in the volatile content and elementary analytical values in the raw material coal is previously determined by the statistical technique, and the raw material coal is selected and carbonized to give the aimed coke. A multiple regression formula expressed by the formula (N-HC is the effective quantity of heat necessary for carbonization; VM is the volatile content in the raw material coal; H/C is the ratio between the hydrogen and carbon in the elementary analytical values; O/C is the ratio between the oxygen and carbon in the elementary analytical values; a, a1, b and c are the regression coefficients; alpha and beta are regression constants) is used as the above-mentioned regression formula.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a method for producing coke. More specifically, the present invention relates to a method for producing coke that enables saving of fuel gas for carbonization.

Coke is usually produced by blending multiple brands of raw coal, charging it into a coke oven carbonization chamber, and heating and carbonizing it. The coke thus produced is used as a reducing agent for iron ore.

As mentioned above, coke is obtained by charging raw coal into a coke carbonization chamber, burning a large amount of fuel gas in an adjacent combustion chamber, and then carbonizing it. Therefore, the amount of fuel gas used is is not only a factor that influences the production cost of coke, but also has a great influence on the quality of coke.

Conventionally, when producing coke by carbonizing coking coal, the supply of heating fuel gas to the combustion chamber depends on the coke oven temperature to be maintained, the amount of coking coal charged, and the curing time of the produced coke after carbonization. However, even under the same operating conditions, the actual /lIi cost was significantly different from what was predicted, and as a result, the heating fuel gas was It was not possible to supply the optimal amount of fuel gas by predicting the required supply amount, in other words, the effective required amount of heat in advance.

This resulted in wasteful consumption of fuel gas, increased coke production costs, and went against the national policy of energy conservation.

In order to solve these problems in the conventional method, the present inventors have conducted various studies on heating and feeding methods, focusing on the physical properties of coking coal, and have determined the effective carbonization requirements for coking coal. There is a certain relationship between the calorific value and the physical properties of coking coal, and by creating a regression equation that shows this relationship in advance and selecting coking coal based on this, the fuel power used during carbonization can be adjusted. The present invention was developed based on the knowledge that it is possible to reduce the supply amount by adjusting the supply amount appropriately.

That is, in producing coke by carbonizing coking coal, the present invention uses the effective required carbonization heat as a dependent variable, and calculates the hydrogen-to-carbon ratio and the oxygen A multiple regression equation in which the carbon ratio is included in the independent variable term is determined in advance by a systematic δ1 method, and raw coal is selected and carbonized based on the multiple regression equation.
- The gist is the method for producing sugar.

The method of the present invention will be explained in more detail below.

The effective amount of heat of carbonization (hereinafter abbreviated as N-11C) required to carbonize raw coal to produce coke is the amount of heat (sensible heat) required to raise the temperature from room temperature to the temperature at which each carbonization product is produced, and the amount of heat produced by carbonization from coal. The endothermic reaction between the sum of the fluctuating heat M (reaction heat) generated by a substance, that is, the required heat amount for carbonization (hereinafter abbreviated as 11C), and the water vapor generated in the gases generated as a result of carbonization and the produced coke due to the production of water gas. It can be understood as the sum of i%lJ, which compensates for the amount of heat carried away.

Therefore, the present inventors investigated various carbonization operation conditions (
For example, the temperature of carbonization, the curing time after completion of carbonization, etc.) were varied, the sensible heat and the heat of reaction were determined, and IIc was determined from the summation of the sensible heat and reaction heat. Here, the sensible heat is calculated by multiplying the carbonization yield of the carbonization product by the specific heat of the product and the temperature difference, and the reaction heat is calculated by multiplying the carbonization yield of the carbonization product by the exothermic acid and the carbonization yield. p%59f
It was determined by the sum of the value obtained by subtracting t and the value obtained by multiplying the latent heat of the liquid carbonization product by the carbonization yield.

On the other hand, volatile matter (hereinafter referred to as V
(abbreviated as M) and elemental component ratios were analyzed, and the relationship between the obtained data and 11c was analyzed by statistical methods. As a result, it was found that VM% and elemental analysis chain hydrogen to carbon ratio (hereinafter abbreviated as H/C) had the largest correlation coefficient. In other words, we have found that a multiple regression equation that includes this in the independent variable term can be used with high accuracy. Figure 1 shows the above data in a graph, and when this is statistically analyzed, It(', (local/Kg) -20,6・
VM 1440 ・If/C-door 98 formula is obtained, and when expressed by a general multiple regression formula, 11c (Kca
l/Kg) = a-VM4- b・It/C+α −
■It becomes.

Here, a, b, and α in the formula are a regression coefficient and a regression constant, respectively, and are determined under certain operating conditions, such as carbonization temperature,
If the curing time of coke after carbonization is constant, it shows a constant value. Therefore, if the operating conditions of the coke oven are almost the same, all you need to do is measure the VM% and elemental analysis values in the coking coal. tti * of IIc is possible from . Note that when operating conditions change drastically, a regression equation that corresponds to the changed operating conditions must be calculated based on a large amount of data, but the regression coefficient values that express the degree of contribution of factors are usually left unchanged. Therefore, a method of increasing or decreasing the regression constant is adopted.

Next, while measuring the endothermic amount (hereinafter abbreviated as AC) based on the water gas production reaction for the same large number of commercially available coking coals, we also analyzed the VM% and elemental components in the coking coals.
The relationship between the obtained data and the AC was analyzed by statistical methods. As a result, it was found that VM% and the elemental analysis chain oxygen to carbon ratio (hereinafter abbreviated as 0/C) had the largest correlation coefficient. In other words, we have found that a multiple regression equation that includes this in the independent variable term can be used with high accuracy. Figure 2 shows the above data in a graph, and when this is statistically analyzed, 8C (Kcal/Kg) -0,42・VM→-
The formula 319,7-0/C-12 is obtained, and when expressed as a general multiple regression formula, 8C(Kcal/Kg) -a
1 ・VM+ r, 0/C+ β −−
−■ becomes.

Here, al and C2β in the formula are a regression coefficient and a regression constant, respectively, and exhibit constant values when certain operating conditions such as carbonization temperature and coke curing time after completion of carbonization are constant. . Therefore, if the operating conditions of the coke oven are almost the same, all you need to do is measure 1% of the coking coal and the elemental analysis value, and the AC It is possible to estimate Note that when operating conditions change, a regression equation commensurate with the changed operating conditions must be calculated based on a large amount of data, but usually the value of the regression coefficient that expresses the degree of contribution of a factor is calculated. A method is adopted in which the regression constant is increased or decreased while leaving it as is.

As mentioned earlier, the N-11c required for carbonization of coking coal
(Effective required carbonization heat amount) is the above-mentioned (required carbonization heat N) and A
Since it is considered to be the sum total of C (endothermic amount based on the water gas production reaction), it can be expressed by the following multiple regression equation from the two equations (I-0+, l, .).

N-11c (Kc81/h) = (a+a + )
−VMtob・11/C →～C・0/C + (α→−β)−−−−■ The above formula 0 can be obtained by adding the separately calculated formulas 0 and 0. However, from the beginning, VM, 11/C10
It goes without saying that equation 0 may be directly determined based on experimental data or actual operation data, with /C as an independent variable factor and N-11G as a dependent variable.

Therefore, by analyzing a large number of commercially available coking coals for coke production in advance and analyzing the analytical data, a multiple regression equation like the one shown above can be derived. N-anus can be predicted just by measuring the analytical values. That is, V of each content raw material coal
M, II/C, 0/C is measured in advance by a normal method, and from the expected blending ratio of the blended raw material coal obtained by blending it, the VM of the blended raw material coal, II/C8o, .
'c is calculated and N-11c is calculated by 81. Then, the raw material coal is selected by repeating trial and error on the assumed blend so that the N-anal value is the lowest, and then carbonization is carried out.

Figure 3 shows a graph of the predicted N-11G calculated and the actual N-110 when coke is produced by the method of the present invention, and as can be seen from the graph, there is a large correlation between the two. .

As described above, the present invention analyzes the relationship between the effective amount of carbonization heat required and the physical property values of raw material coal, creates a multiple regression equation obtained as a result from a large amount of data in advance, and selects and blends raw material coal, etc. By doing so, it is possible to supply the minimum amount of fuel gas required for carbonization, and its industrial value is great.

[Brief explanation of the drawing]

Figure 1 shows the VM of coking coal,! It is a scatter diagram showing the relationship between I/C and IIC. FIG. 2 is a scatter diagram showing the relationship between VM, 0/C and AC of raw coal. FIG. 3 is a scatter diagram showing the relationship between total $N-11c and actual 1j1N-11C according to the present invention.

Claims (1)

[Claims] (1) In producing coke by carbonizing coking coal,
A multiple regression equation in which the effective required heat of carbonization is taken as the dependent variable and the hydrogen to carbon ratio and oxygen to carbon ratio of the volatile matter and elemental analysis values in raw coal are included as independent variables is prepared in advance using a statistical method. 1. A method for producing coke, characterized in that raw coal is selected based on the multiple regression equation and carbonized.