WO2012103600A2 - Coal blend models for determining coke quality - Google Patents

Coal blend models for determining coke quality Download PDF

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Publication number
WO2012103600A2
WO2012103600A2 PCT/BA2012/000001 BA2012000001W WO2012103600A2 WO 2012103600 A2 WO2012103600 A2 WO 2012103600A2 BA 2012000001 W BA2012000001 W BA 2012000001W WO 2012103600 A2 WO2012103600 A2 WO 2012103600A2
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blend
coke
coal
quality
csr
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French (fr)
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WO2012103600A3 (en
Inventor
Gurram Surya KISHORE
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GLOBAL ISPAT KOKSNA INDUSTRIJA d o o LUKAVAC
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GLOBAL ISPAT KOKSNA INDUSTRIJA d o o LUKAVAC
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/22—Fuels; Explosives
    • G01N33/222—Solid fuels, e.g. coal

Definitions

  • the invention originated from the need to obtain the required coke quality parameters that meet consumer demands with the right coal blend.
  • the process consists of different prediction equations for each output coke quality.
  • knowing the input quality of coals used for coke production it is easy to assume the expected quality of coke.
  • the quality of coke is predetermined, then it is possible to plan a blend of different coals for the required quality of the blend and therefore to obtain coals and produce coke.
  • Model of Ash Pre-condition is such that there was no knowledge of what will be the coke ash knowing the input blend of coal ash and voiatiles (VM).
  • Coke ash could be determined by knowing blend coal ash and Volatile matter.
  • the developed model for this quality parameter is:
  • Blend ash is input blend of coal ash and Blend VM is volatile matter in input coal blend.
  • the developed model for this quality parameter is:
  • Model for M40 Pre-condition is such that there was no knowledge of the kind of M40 coke for input coal, other than the experience that good Swelling coal and good reflecting coal is needed. Precisely, it was not known to what amount each quality should be held.
  • M40 of coke can be determined by knowing Swelling index
  • the developed model for this quality parameter is:
  • Model for M10 Pre-condition is such that there was no knowledge on the kind of the M10 for the input coal, other than experience that Swelling coal and good reflection coal needs to be good. But precisely, it is not known to what amount each quality should be held.
  • M10 of coke can be determined by knowing Swelling Index, Mean Max. Reflectance and Dilatation of coal blend.
  • the developed model for this quality parameter is:
  • CSI Swelling Index
  • Rm Mean Max. value of reflectance
  • D Dilatation of coal blend.
  • Model no.l for CSR In this model CSR is determined by knowing blend quality parameters Swelling Index, Mean Max Reflectance and Coal alkalinity factor.
  • Coal alkalinity factor is defined as below:
  • Coal alkalinity factor (%Fe 2 0 3 +%CaO+%MgO+%Na 2 O+%K 2 O in blend coal ash)/(%Si0 2 +%Al 2 0 3 +%Ti0 2 in blend coal ash)
  • Model no.2 for CSR In this model CSR is determined by knowing blend quality parameters Swelling Index, Mean. Max. Reflectance and Alkaline index.
  • CSI Swelling index
  • Rm Mean Max.
  • Reflectance and AI Alkaline Index.
  • Alkaline Index is defined as below:
  • Model no.3 for CSR In this model CSR is determined by quality parameters of Swelling Index, Mean. Max. Reflectance and Coal alkalinity factor, (coal alkalinity factor) 2 and coal blend ash.
  • CSI Swelling index
  • Rm Mean Max.
  • Reflectance ash blend is coal ash blend and coal alkalinity factor is defined for model no.l .
  • Model no.4 for CSR In this model CSR is determined by blend quality parameters of coal alkalinity factor and total sum of vitrinites VI 1 to V13 on coal blend.
  • V is sum of vitrinites of types Vl l to VI 3 in % Blend coal and alkalinity factor as defined in Model no.1.
  • Models were developed for determining CSR (5 to 8) taking into consideration various dependant variables of blend quality.
  • Coke Ash for an input coal blend ash of 9.01% and blend volatile matter of 24.4%, the equation determines a coke ash of 11.71%.
  • the model helps in planning and control of direction of coke production to achieve the desired coke ash.
  • M40 in coke The model determines M40 of 83.1% for Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172 and Coal Blend Dilatation of 87.7.
  • model indicates the blend quality to be maintained in the parameters of Swelling Index, Reflectance and Dilatation to achieve desired M40 in coke.
  • M10 in coke The model determines M10 of 6% for Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172 and Coal Blend Dilatation of 87.7. Thus the equation indicates the blend quality to be maintained in the parameters of Swelling Index, Reflectance and Dilatation to achieve desired M10 in coke.
  • CSR of coke from model no. 3 For a Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172, alkalinity factor of 0.0789 and Alkaline factor 2 of 0.0062 and Coal Blend Ash of 9.01 the model indicates CSR of 72.5%. Thus the model indicates the Coal Blend Quality to be maintained in the parameters of Swelling Index, Reflectance, alkalinity factor, Alkaline factor 2 and Coal Blend Ash to achieve desired CSR.

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  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Food Science & Technology (AREA)
  • Medicinal Chemistry (AREA)
  • Physics & Mathematics (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
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  • Pathology (AREA)
  • Coke Industry (AREA)

Abstract

Global Ispat Koksna Industrija"d.o.o. (GIKIL) developed Coal blend models linking interdependent input blend coal properties to output coal quality. The invention arose at the necessity of achieving a very high quality in coke quality parameters (about 5nos) with a proper blend mix of different coals. The models have been developed based on the operating data for the last 6 years for the different Coal Blend quality parameters and Coke quality. The models consist of different correlation equations for each output quality of coke with different blend quality parameters. Thus by knowing the input qualities of coals used in coke manufacture, the expected coke quality can be determined. Once the coke quality is predetermined, it allows planning the blend mix of different coals for the required blend quality and accordingly purchasing coals and manufacturing coke as per required quality.

Description

Description of invention:
Name of invention: Coal Blend Models for Determining Coke Quality
Technique area which the invention refers: Industry
Technical problem: Prior to development of process, it was not known which quality of the origin source of coal affects which quality of output coke and also it was not known to what extent it affects the output quality. This results in various penalties for many parameters of the quality of coke and significant amounts of penalties are paid for various discrepancies in the quality of coke and coke quality level especially for CSR which in 2006 amounted to 44% for most of the time. The international market requires CSR at least 65% and quality compliance of approximately 1 1 parameters (not just CSR). This resulted in a challenge to produce high quality coke and to obtain purchase orders in the international market in order to maintain production. For this reason procedure for coal blend linking properties / characteristics of the input coal blend with output quality of coke is developed. The invention originated from the need to obtain the required coke quality parameters that meet consumer demands with the right coal blend. The process consists of different prediction equations for each output coke quality. Thus, knowing the input quality of coals used for coke production, it is easy to assume the expected quality of coke. When the quality of coke is predetermined, then it is possible to plan a blend of different coals for the required quality of the blend and therefore to obtain coals and produce coke.
Condition of technique: The problem is solved by identifying the dependant coal blend quality parameters and linking them to coke quality parameters. The link up is done by following statistical methods for the data of coal blend quality and coke quality generated over years of operations. This data on following statistical techniques has yielded models to find coke quality for particular coal blend quality. Models that have been developed are as bellow: a) Model of Ash: Pre-condition is such that there was no knowledge of what will be the coke ash knowing the input blend of coal ash and voiatiles (VM).
Coke ash could be determined by knowing blend coal ash and Volatile matter.
The developed model for this quality parameter is:
I) Coke ash = 1+1.03*Blend ash+0.058*Blend VM (Chart I)
In this equation Blend ash is input blend of coal ash and Blend VM is volatile matter in input coal blend.
With this, the kind of the ashes of the coke by input blend of coal ash and voiatiles VM now can be known. b) Model for Sulphur: Pre-condition is such that there was no knowledge of the kind of sulphur of coke, knowing sulphur of coal blend. Coke sulphur can be determined by knowing blend coal sulphur.
The developed model for this quality parameter is:
II) Coke sulphur = 0.141+0.66*Sulphur in coal blend (Chart I)
With this, the kind of the coke sulphur now can be known if we know the input sulphur coal blend.
c) Model for M40: Pre-condition is such that there was no knowledge of the kind of M40 coke for input coal, other than the experience that good Swelling coal and good reflecting coal is needed. Precisely, it was not known to what amount each quality should be held.
M40 of coke can be determined by knowing Swelling index,
the Mean Max. Reflectance and Dilatation of blend coal.
The developed model for this quality parameter is:
III) M40 = 38.3+2.23*CSI+23.3*Rm+0.0168*D (Chart 1) In this equation CSI is Swelling Index, Rm is the Mean Max. Reflectance and D is Dilatation of coal blend.
Value of CSI, Reflection and Dilatation of input coal blend maintained for targeted coke M40 now can be known with this. d) Model for M10: Pre-condition is such that there was no knowledge on the kind of the M10 for the input coal, other than experience that Swelling coal and good reflection coal needs to be good. But precisely, it is not known to what amount each quality should be held.
M10 of coke can be determined by knowing Swelling Index, Mean Max. Reflectance and Dilatation of coal blend.
The developed model for this quality parameter is:
IV) M10 = 24.3-0.669*CSI-10.2*Rm-0.0177*D (Chart 1)
In this equation CSI is Swelling Index, Rm is Mean Max. value of reflectance and D is Dilatation of coal blend.
With this, the value of CSI, Reflectance and Dilatation of input coal blend that is maintained for targeted coke M10 now can be known.
Models c) & d) have been developed for the data in range of quality coal blend and process parameters as mentioned in Chart I.
Chart I -Range of quality coal blend and parameters of process quality for procedures M40 & M10
Figure imgf000005_0001
e) Model for CSR: Pre-condition is such that there was no knowledge about the kind of the quality of coal blend which gives a good CSR and resulted that CSR could never been made over 44%.
Model no.l for CSR: In this model CSR is determined by knowing blend quality parameters Swelling Index, Mean Max Reflectance and Coal alkalinity factor.
V) CSR = 33.4+2.34*CSI-10.3*Rm+3.14*(l/coal alkalinity factor) (Chart II) In this equation CSI is Swelling Index, Rm is Mean. Max. Reflectance and Coal alkalinity factor.
Coal alkalinity factor is defined as below:
Coal alkalinity factor = (%Fe203+%CaO+%MgO+%Na2O+%K2O in blend coal ash)/(%Si02+%Al203+%Ti02 in blend coal ash)
Model no.2 for CSR: In this model CSR is determined by knowing blend quality parameters Swelling Index, Mean. Max. Reflectance and Alkaline index.
VI) CSR = 75.5 + 2.58*CSI - 8.99*Rm - 17.9* AI (Chart II)
In this equation CSI is Swelling index, Rm is Mean Max. Reflectance and AI is Alkaline Index.
Alkaline Index is defined as below:
AI = coal blend ash * Coal alkalinity factor.
Model no.3 for CSR: In this model CSR is determined by quality parameters of Swelling Index, Mean. Max. Reflectance and Coal alkalinity factor, (coal alkalinity factor)2 and coal blend ash.
VII) CSR = 86.2 + 1.89*CSI - 5.99*Rm - 246* coal alkalinity factor + 301 * (coal alkalinity factor)2 - 0,303* ash blend (Chart II)
In this equation CSI is Swelling index, Rm is Mean Max. Reflectance, ash blend is coal ash blend and coal alkalinity factor is defined for model no.l .
Model no.4 for CSR: In this model CSR is determined by blend quality parameters of coal alkalinity factor and total sum of vitrinites VI 1 to V13 on coal blend.
VIII) CSR = 47+1.45* 1/coal alkalinity factor+0.164*V (Chart II)
In this equation V is sum of vitrinites of types Vl l to VI 3 in % Blend coal and alkalinity factor as defined in Model no.1. Thus total four Models were developed for determining CSR (5 to 8) taking into consideration various dependant variables of blend quality.
Average value of CSR obtained out of all these four equations is to be taken while determining coke quality.
These models have been developed for the data in the range of blend quality and process parameters as given in Chart II.
Chart II- Range of blend quality and process quality parameters for
Models of CSR
Figure imgf000007_0001
With the equations specified in the procedures for CSR, it can be now known which values have to be maintained for alkalinity, reflection, ash, Swelling Index, and vitrinites in Coal Blend to achieve the desired CSR. Ilustration on use of Models:
Determining Coke Ash: for an input coal blend ash of 9.01% and blend volatile matter of 24.4%, the equation determines a coke ash of 11.71%. Thus the model helps in planning and control of direction of coke production to achieve the desired coke ash.
Determining Coke Sulphur: For a blend coal sulphur of 0.79% the model determines a coke sulphur of 0.66%. Thus the model helps in planning and control of direction of coke production to achieve desired sulphur in coke.
Determining M40 in coke: The model determines M40 of 83.1% for Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172 and Coal Blend Dilatation of 87.7.
Thus the model indicates the blend quality to be maintained in the parameters of Swelling Index, Reflectance and Dilatation to achieve desired M40 in coke.
Determining M10 in coke: The model determines M10 of 6% for Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172 and Coal Blend Dilatation of 87.7. Thus the equation indicates the blend quality to be maintained in the parameters of Swelling Index, Reflectance and Dilatation to achieve desired M10 in coke.
Determining CSR in coke from Model no. 1: For a Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172 and Coal Blend alkalinity factor of 0.0789 the model determines CSR of 78%. Thus the model indicates the blend quality to be maintained in the parameters of Swelling Index, Reflectance and alkalinity to achieve the required CSR.
Determining CSR in coke from Model no.2: For a Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172 and alkalinity index of 0.7101 the model indicates a CSR of 70.8%. Thus the model indicates the Coal Blend Quality to be maintained in the parameters of Swelling Index, Reflectance and alkalinity index to achieve desired CSR.
Determining CSR of coke from model no. 3: For a Coal Blend Swelling Index of 7.2, Coal Blend Reflectance of 1.172, alkalinity factor of 0.0789 and Alkaline factor2 of 0.0062 and Coal Blend Ash of 9.01 the model indicates CSR of 72.5%. Thus the model indicates the Coal Blend Quality to be maintained in the parameters of Swelling Index, Reflectance, alkalinity factor, Alkaline factor2 and Coal Blend Ash to achieve desired CSR.
Determining CSR in coke from model no. 4.: For a Alkaline factor of 0.0789 and vitrinites of 44.3% the model indicates CSR of 72.7%. Thus the model indicates the Coal Blend Quality to be maintained in the parameters of alkalinity factor and vitrinites to achieve desired CSR.
The average value of CSR in the above illustration using al four models is elaborated on 73.2 for the assumed values of different Coal Blend Quality parameters defined in the model.
For„Giobal Ispat Koksna Industrija"d.o.o. Lukavac
MANAGING DIRECTOR

Claims

Patent requests
1. Coal Blend models for determining coke quality are models that are determining output parameters of Coke Quality, knowing input parameters that have determined Coal Blend Quality and percentage of ash, sulphur, volatiles in Coal Blend, Swelling Index, Mean Max. Reflectance and Dilatation, Coal Alkalinity factor, Alkaline Index and total sum of types of vitrinites, characterized by the fact that the procedures for ash coke, sulphur of coke, coke M40, M10 coke and 4 models for determining the mean CSR of coke are determining various quality parameters of coke in a way that it was established by eight equations which determines the procedure of establishing the quality parameters of coke on the basis of Coal Blend input parameters.
2. Model for Coke Ash as per request 1 is the procedure of determining Coke Ash Quality characterized by the fact that Blend parameters of Coal Blend Ash Quality and Blend volatile matters can let us know what will be Coke Ash and the same can be introduced by the following equation:
Coke Ash=l+1.03* Coal Blend Ash +0.058* VM Blend.
3. Model for Coke Sulphur as per request 1. is procedure of determining Coke Sulphur Quality characterized by the fact that if the input Blend Coal Sulphur is known, it also can be known what will be the sulphur of coke, which can be illustrated by the following equation:
Coke sulphur=0.141+0.66*Blend Coal Sulphur
4. Model for M40 as per request 1. is procedure of determining the value of Blend Quality Swelling Index, Mean Max. Reflectance and Dilatation, characterized by the fact that this procedure can let us know about value of CSI, Reflectance and Dilatation of input blend maintained for targeted coke M40, which can be illustrated by the following equation
M40 = 38.3+2.23*CSI+23.3*Rm+0.0168*D.
5. Model for M10 as per request 1. is procedure of determining the value of Blend Quality Swelling Index, Mean Max. Reflectance and Dilatation, characterized by the fact that this procedure can let us know about value of CSI, Reflectance and Dilatation of input blend maintained for targeted coke M10, which can be illustrated by the following equation:
M10=24.3-0.669*CSI-10.2*Rm-0.0177*D.
6. Model no.1 for CSR as per request 1. is procedure of determining the value of Blend Swelling Index, average reflectance and coal alkalinity factor characterized by the fact that this procedure can let us know about parameters value which have to be maintained in the blend to achieve desired CSR, which can be illustrated by the following equation:
CSR = 33.4+2.34*CSI-10.3*Rm+3.14*(l/coal alkalinity factor).
7. Model no. 2 for CSR as per request 1, is procedure of determining the value of Blend Swelling Index, average reflectance and Alkaline Index characterized by the fact that this procedure can let us know about parameters value which have to be maintained in the blend to achieve desired CSR, which can be illustrated by the following equation:
CSR = 75.5 + 2.58*CSI - 8.99*Rm- 17.9* AI.
8. Model no.3 for CSR as per request 1, is procedure of determining the value of Blend Swelling Index, average reflectance and coal alkalinity factor and coal blend ash characterized by the fact that this procedure can let us know about parameters value which have to be maintained in the blend to achieve desired CSR, which can be illustrated by the following equation:
CSR = 86.2 + 1.89*CSI - 5.99*Rm - 246* coal alkalinity factor + 301 * (coal alkalinity factor)2 - 0,303* ash blend
PCT/BA2012/000001 2011-02-01 2012-01-30 Coal blend models for determining coke quality Ceased WO2012103600A2 (en)

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CN104312609A (en) * 2014-11-14 2015-01-28 武汉钢铁(集团)公司 Coal blending method for controlling basicity index of coking coal
CN107525882A (en) * 2017-10-20 2017-12-29 太原理工大学 A kind of method for predicting sulfur content in coke
CN108717506A (en) * 2018-06-25 2018-10-30 华北理工大学 A method of prediction coke hot strength
CN111029577A (en) * 2019-11-12 2020-04-17 山西沁新能源集团股份有限公司 Method for blending coal with precursor of crystalline carbon coke powder
CN112098263A (en) * 2020-09-14 2020-12-18 山西亚鑫新能科技有限公司 Method for parameter comprehensive prediction of coke thermal strength model
CN112731868A (en) * 2020-11-27 2021-04-30 山西焦化股份有限公司 Refined intelligent coal blending system
CN113723668A (en) * 2021-08-02 2021-11-30 华院计算技术(上海)股份有限公司 Coal blending method, system, equipment and storage medium based on robust optimization
CN114955586A (en) * 2022-06-27 2022-08-30 重庆钢铁股份有限公司 Silo coal blending coke quality prediction system
CN117167771A (en) * 2023-07-25 2023-12-05 华能武汉发电有限责任公司 Silo coal blending and burning control system
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CN104312609A (en) * 2014-11-14 2015-01-28 武汉钢铁(集团)公司 Coal blending method for controlling basicity index of coking coal
CN107525882A (en) * 2017-10-20 2017-12-29 太原理工大学 A kind of method for predicting sulfur content in coke
CN108717506B (en) * 2018-06-25 2022-03-18 华北理工大学 Method for predicting hot strength of coke
CN108717506A (en) * 2018-06-25 2018-10-30 华北理工大学 A method of prediction coke hot strength
CN111029577A (en) * 2019-11-12 2020-04-17 山西沁新能源集团股份有限公司 Method for blending coal with precursor of crystalline carbon coke powder
CN111029577B (en) * 2019-11-12 2023-09-29 山西沁新能源集团股份有限公司 Method for blending crystalline coke powder precursor coal
CN112098263A (en) * 2020-09-14 2020-12-18 山西亚鑫新能科技有限公司 Method for parameter comprehensive prediction of coke thermal strength model
CN112098263B (en) * 2020-09-14 2022-07-01 山西亚鑫新能科技有限公司 Method for parameter comprehensive prediction of coke thermal strength model
CN112731868A (en) * 2020-11-27 2021-04-30 山西焦化股份有限公司 Refined intelligent coal blending system
CN113723668A (en) * 2021-08-02 2021-11-30 华院计算技术(上海)股份有限公司 Coal blending method, system, equipment and storage medium based on robust optimization
CN113723668B (en) * 2021-08-02 2022-05-10 华院计算技术(上海)股份有限公司 Coal blending method, system, equipment and storage medium based on robust optimization
JP2023021917A (en) * 2021-08-02 2023-02-14 華院計算技術（上海）股▲ふん▼有限公司 Coal blending method, system, apparatus and storage medium based on robust optimization
CN114955586A (en) * 2022-06-27 2022-08-30 重庆钢铁股份有限公司 Silo coal blending coke quality prediction system
CN114955586B (en) * 2022-06-27 2024-02-20 重庆钢铁股份有限公司 System for predicting quality of coal blending coke of silo
CN117167771A (en) * 2023-07-25 2023-12-05 华能武汉发电有限责任公司 Silo coal blending and burning control system
CN119151068A (en) * 2024-09-20 2024-12-17 北京爱熵科技有限公司 Parameter generation method, coke quality prediction method and device

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