Optimized coal blending structure and coke quality prediction system

Abstract

The invention provides a coal blending structure optimization and coke quality prediction system, which comprises a coal blending raw material data module used for obtaining the coal type of coal blending and the basic data of the corresponding coal type; the constraint condition setting module is used for setting a limiting condition according to a limiting factor for realizing the problem target, and taking the index requirement and the resource limit as the constraint condition; the function target setting module takes the lowest coal blending cost as a target function; and the planning, solving and predicting module is used for planning and solving the target function under the corresponding constraint condition by applying a built-in linear planning and solving function of Excel, and taking the solved result as a coke quality predicting result after the coal blending structure is optimized. According to the method, the coal blending cost serves as a target function, solving is carried out through linear programming, workers can be assisted to carry out actual coal blending, it is ensured that the coke quality and the production efficiency are always in the optimal state, and resource waste is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of coal blending systems, and in particular to a system for optimizing coal blending structure and predicting coke quality. Background Art

[0002] At present, my country has many types of coal and abundant reserves, but the distribution is uneven, and there are relatively few high-quality coking coal resources. In order to make full use of coal resources in various places and save production costs, coking enterprises adopt coking coal blending technology to produce coke that meets the requirements. Coal blending is a complex process, involving factors such as the quality of single coal, coking conditions, and coking mechanism. However, in the actual production process, due to the complex source of raw coal and large quality fluctuations, coal blending process personnel need to spend a lot of time calculating the coal blending ratio, and then combine experience or experiments to come up with a better coal blending plan.

[0003] In recent years, with the adjustment of blast furnace production, higher requirements have been put forward for the quality of coke, and the quality of metallurgical coke mainly depends on the quality of coking coal. In the case of low inventory in the coal yard and extremely unbalanced number of coal types, in order to ensure the quality of coke and minimize the cost of coal blending, it is necessary to continuously optimize the current blending ratio. Most of the existing coal blending methods require staff to perform complex calculations based on the blending coal parameters obtained in the actual production process, which is time-consuming and labor-intensive. Summary of the invention

[0004] In order to solve the above problems, the purpose of the present invention is to provide a system for optimizing coal blending structure and predicting coke quality.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A system for optimizing coal blending structure and predicting coke quality, comprising:

[0007] Coal blending raw material data module, used to obtain the coal types for coal blending and the basic data of the corresponding coal types;

[0008] The constraint setting module is used to set constraints according to the limiting factors of achieving the problem objectives, and use indicator requirements and resource limits as constraints;

[0009] Function target setting module, which takes the lowest coal blending cost as the target function;

[0010] The planning and solving prediction module uses the built-in linear planning and solving function of Excel to plan and solve the objective function under the corresponding constraints, and uses the results as the prediction results of coke quality after optimizing the coal blending structure.

[0011] Preferably, in the coal blending raw material data module, the basic data of the coal type includes: ash value, sulfur value, volatile matter value, G value and unit price.

[0012] Preferably, in the coal blending raw material data module, the constraints include: the maximum usage of the blending ratio, ash value, sulfur value, coke drum M40, coke drum M10, thermal reactivity CRI, post-reaction strength CSR, hot strength, and bonding index.

[0013] Preferably, in the coal blending raw material data module, the constraints are: coke drum M40 ≥ 86%, coke drum M10 ≤ 6.6%, thermal reactivity CRI ≤ 30%, post-reaction strength CSR ≥ 62%, ash content ≤ 10%, sulfur content ≤ 0.99%, volatile matter between 27% and 29%, bonding index 78% -82%, and hot strength greater than 50%.

[0014] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0015] The present invention provides a system for optimizing coal blending structure and predicting coke quality. Compared with the prior art, the present invention takes coal blending cost as the objective function and solves it through linear programming, thereby assisting workers in actual coal blending, ensuring that coke quality and production efficiency are always in the best state and reducing resource waste. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0017] Figure 1 A principle block diagram of an optimized coal blending structure and coke quality prediction system provided by the present invention; DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0020] To achieve the above object, the technical solution adopted by the present invention is:

[0021] See also Figure 1 , a system for optimizing coal blending structure and predicting coke quality, comprising:

[0022] Coal blending raw material data module, used to obtain the coal types for coal blending and the basic data of the corresponding coal types;

[0023] A constraint setting module is used to set constraint conditions according to the limiting factors for achieving the problem objectives, and to use the index requirements and resource limits as constraint conditions; in the constraint setting module, the index requirements and resource limits as constraint conditions include the maximum amount of one or more types of coal in the coal blending process, ash value, sulfur value, coke drum M40, coke drum M10, thermal reactivity CRI, post-reaction strength CSR, hot strength, and bonding index;

[0024] The function target setting module takes the lowest coal blending cost as the target function; the target function is:

[0025]

[0026] Where n represents the number of coal types used in coal blending, C j represents the unit price of the j-th coal type, x j Represents the proportion of the j-th coal type.

[0027] The planning and solving prediction module uses the built-in linear planning and solving function of Excel to plan and solve the objective function under the corresponding constraints, and uses the results as the prediction results of coke quality after optimizing the coal blending structure.

[0028] Further, in an embodiment of the present invention, a system for optimizing coal blending structure and predicting coke quality of the present invention comprises a processor 1, a coal blending raw material data module 2, a coal inventory data module 3, a constraint condition setting module 4, a function target setting module 6 and a planning solution prediction module 5, wherein the processor 1 is connected to the coal blending raw material data module 2, the coal inventory data module 3, the constraint condition setting module 4, the function target setting module 6 and the planning solution prediction module 5;

[0029] The coal blending raw material data module 2 contains the coal types used for coal blending and the basic data of the corresponding coal types;

[0030] The constraint condition setting module 4 is used to set constraint conditions according to the limiting factors for achieving the problem goal, and takes the indicator requirements and resource limits as constraint conditions;

[0031] Function target setting module 6 takes the lowest coal blending cost as the target function;

[0032] The planning and solving prediction module 5 uses the built-in linear planning solving function of Excel, and takes the lowest coal blending cost as the objective function through the function target setting module 6. The planning and solving results are obtained according to the coal blending raw material data module 2, the coal inventory data module 3 and the constraint condition setting module 4. This result is the coke quality prediction result after optimizing the coal blending structure.

[0033] The basic data of coal types include ash content, sulfur content, volatile matter value, G value and unit price. Since the unit value will not be constant, it needs to be continuously adjusted according to changes in the actual unit price.

[0034] The unit price of blended coal is obtained through the planning and solving prediction module 5.

[0035] The processor 1 is electrically connected to a log module, which is used to record the past coal blending records of the system.

[0036] The coal type inventory data module 3 stores the inventory remaining quantity of the corresponding coal type.

[0037] In the constraint setting module 4, the index requirements and resource limits as constraints include the maximum proportion of one or more coal types in the coal blending process, ash value, sulfur value, coke drum M40, coke drum M10, thermal reactivity CRI, post-reaction strength CSR, hot strength, and bonding index.

[0038] For example, the quality requirements for coke are: ash ≤ 12.8%, sulfur ≤ 0.80%, coke drum M40 ≥ 86%, coke drum M10 ≤ 6.6%, thermal reactivity CRI ≤ 30%, and post-reaction strength CSR ≥ 62%. The key indicators of blended coal determined by coke quality are ash ≤ 10%, sulfur ≤ 0.99%, volatile matter between 27% and 29%, bonding index 78% -82%, and hot strength greater than 50%. When blending coal, resources limit the amount: Liulin coal is of high quality and high price, and the supply is tight. Therefore, the proportion of Liulin coal does not exceed 5%. Shenmu coal can effectively reduce the ash and sulfur content of coke, but Shenmu coal has no bonding index and the amount does not exceed 4%. The ash content of Mongolian coal 2# fluctuates greatly and the amount cannot exceed 50%. The blending results and predictions are shown in Table 1 below. The lowest unit price of blended coal is 1,362 yuan / t.

[0039]

[0040]

[0041] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0042] The present invention uses the function target setting module to take the lowest coal blending cost as the objective function, and plans and solves the results obtained according to the coal blending raw material data module, the coal type inventory data module and the constraint condition setting module. This result is the coke quality prediction result after the coal blending structure is optimized. The system makes a preliminary prediction of coal blending, which can assist the staff in the actual coal blending, ensure that the coke quality and production efficiency are always in the best state, and reduce resource waste.

[0043] This article uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only used to help understand the method and core ideas of the present invention. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A system for optimizing coal blending structure and predicting coke quality, characterized in that: include: Coal blending raw material data module, used to obtain the coal types for coal blending and the basic data of the corresponding coal types; The constraint setting module is used to set constraints according to the limiting factors of achieving the problem objectives, and use indicator requirements and resource limits as constraints; Function target setting module, which takes the lowest coal blending cost as the target function; The planning and solving prediction module uses the built-in linear planning and solving function of Excel to plan and solve the objective function under the corresponding constraints, and uses the results as the prediction results of coke quality after optimizing the coal blending structure.

2. The system for optimizing coal blending structure and predicting coke quality according to claim 1, characterized in that: In the coal blending raw material data module, the basic data of coal types include: ash value, sulfur value, volatile matter value, G value and unit price.

3. The system for optimizing coal blending structure and predicting coke quality according to claim 1, characterized in that: In the coal blending raw material data module, the constraints include: the maximum usage ratio, ash content, sulfur content, coke drum M40, coke drum M10, thermal reactivity CRI, post-reaction strength CSR, hot strength, and bonding index.

4. The system for optimizing coal blending structure and predicting coke quality according to claim 3, characterized in that: In the coal blending raw material data module, the constraints are: coke drum M40 ≥ 86%, coke drum M10 ≤ 6.6%, thermal reactivity CRI ≤ 30%, post-reaction strength CSR ≥ 62%, ash content ≤ 10%, sulfur content ≤ 0.99%, volatile matter between 27%-29%, bonding index 78%-82%, and hot strength greater than 50%.

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