Sodium occurrence form and ash composition-based high-alkali coal contamination and slagging tendency discrimination method

Abstract

This application provides a method and system for judging the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition. The method includes: performing sodium speciation analysis on the coal sample to obtain a sodium activity coefficient; performing ash composition analysis on the coal sample to obtain a silica-alumina correction coefficient and an iron-calcium ratio; calculating a dynamic fouling and slagging index based on the sodium activity coefficient, silica-alumina correction coefficient, and iron-calcium ratio; and determining the slagging judgment result based on the dynamic fouling and slagging index. This method introduces the key activity indicator of sodium chemical speciation into the judgment system, reflecting the release and migration capacity of sodium more accurately from the root, overcoming the limitations of judging solely based on total sodium content, and improving the judgment accuracy and universality.

Description

Technical Field

[0001] This application belongs to the technical field of clean coal combustion and safe operation of power plant boilers. Specifically, it relates to a method for judging the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition. Background Technology

[0002] In some regions, high-alkali coal reserves are abundant. However, during combustion, the high sodium (Na) content and other alkali metals in the coal easily volatilize, migrate, and co-melt with the ash at high temperatures, leading to severe fouling and slagging on boiler heating surfaces (such as water-cooled walls and superheaters). This not only reduces boiler thermal efficiency but also easily causes safety problems and economic losses.

[0003] Currently, the industry commonly uses empirical index methods based on coal ash composition (such as the alkali-acid ratio (B / A), silica-alumina ratio (S / A), and iron-calcium ratio) to preliminarily predict slagging tendency. However, these methods have significant shortcomings: (1) The differences in chemical activity of sodium in different occurrence forms were not considered: Sodium in coal exists in various forms such as water-soluble sodium, organic sodium (carboxylate), and aluminosilicate (such as nepheline), and their volatilization temperatures and reactivity vary greatly. The release behavior cannot be accurately assessed based solely on the total sodium content.

[0004] (2) Low discrimination accuracy and poor universality: Existing empirical discrimination indices are mostly based on statistical data of specific regions and coal types. The prediction results for high-alkali coal often deviate significantly from the actual situation.

[0005] Therefore, developing a comprehensive discrimination system that combines sodium occurrence forms and ash composition is crucial for the safe, efficient, and large-scale utilization of high-alkali coal. Summary of the Invention

[0006] The technical problem addressed by this application is: how to provide a method for judging the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition, which fully considers the differences in chemical activity of sodium in different occurrence forms to improve the accuracy and universality of discrimination.

[0007] This application provides a method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition. The method includes: The sodium speciation of the coal sample to be tested was analyzed to obtain the sodium activity coefficient. Ash composition analysis was performed on the coal sample to be tested to obtain the silicon-aluminum correction coefficient and the iron-calcium ratio; The dynamic fouling and slagging index is calculated based on the sodium activity coefficient, the silicon-aluminum correction coefficient, and the iron-calcium ratio. The slagging discrimination result is determined based on the dynamic fouling and slagging index.

[0008] Optionally, methods for obtaining the sodium activity coefficient by performing sodium speciation analysis on the coal sample to be tested include: The coal sample to be tested was subjected to stepwise chemical extraction to obtain the content of sodium in four different forms; The sodium activity coefficient was calculated based on the content of four different forms of sodium, using the following formula: ; In the formula, , , , This indicates the content of four different forms of sodium. This represents the sodium activity coefficient.

[0009] Optionally, methods for analyzing the ash composition of the coal sample to obtain the silica-alumina correction factor and the iron-calcium ratio include: The ash composition of the coal sample was analyzed using X-ray fluorescence spectrometry to obtain the mass percentage of the main oxide components, including the mass of SiO2, Al2O3, Na2O, K2O, Fe2O3, CaO, and MgO. The formula for calculating the silicon-aluminum correction factor (SAC) is as follows: ; In the formula, , , , , , , These represent the mass percentages of SiO2, Al2O3, Na2O, K2O, Fe2O3, CaO, and MgO, respectively. The formula for calculating the iron-calcium ratio (FCR) is as follows: .

[0010] Optionally, dynamic fouling and slagging index The calculation formula is as follows: ; In the formula, , , , These are the model weight coefficients, is a constant term, and B / A is the traditional base-acid ratio.

[0011] Optionally, the method for determining the slagging discrimination result based on the dynamic fouling slagging index includes: The slagging index is used to determine the slagging tendency, which is classified as low, medium, high, or severe.

[0012] Optionally, the method further includes: The coal sample to be tested is ground to the specified fineness and then dried.

[0013] This application also provides a system for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition. The system includes: A sodium speciation analysis module is configured to perform sodium speciation analysis on a coal sample to be tested to obtain a sodium activity coefficient. Ash composition analysis module, which is configured to perform ash composition analysis on the coal sample to be tested to obtain the silicon-aluminum correction coefficient and the iron-calcium ratio; A data fusion module is configured to calculate a dynamic fouling and slagging index based on the sodium activity coefficient, the silicon-aluminum correction coefficient, and the iron-calcium ratio. A slagging discrimination module is configured to determine the slagging discrimination result based on the dynamic fouling slagging index.

[0014] This application provides a method and system for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition, which has the following technical advantages: (1) High prediction accuracy: For the first time, the key activity indicator of sodium chemical form is introduced into the discrimination system, which reflects the release and migration ability of sodium more accurately from the source and overcomes the limitation of discrimination based solely on total sodium content.

[0015] (2) Quantification: The DSFI index provides quantitative results, which is superior to traditional qualitative descriptions and facilitates power plants in calculating fuel costs and risks.

[0016] (3) High system integration: It integrates sample processing, component analysis, intelligent computing and decision support into one, which can realize automated or semi-automated operation, reduce the dependence on human experience, and is easy to promote and deploy in power generation groups or large power plants. Attached Figure Description

[0017] Figure 1 This is a flowchart of a method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition, according to one or more embodiments.

[0018] Figure 2 This is a schematic diagram of a high-alkali coal fouling and slagging tendency discrimination system based on sodium occurrence form and coal ash composition, according to one or more embodiments. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0020] Before describing the various embodiments of this application in detail, the technical concept of this application is first briefly described: Current methods for analyzing slagging tendency do not consider the differences in chemical activity of sodium in different occurrence forms, and have low discrimination accuracy and poor universality. Therefore, this application provides a method for judging the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition. The key improvement lies in performing sodium speciation analysis and ash composition analysis on the coal sample to be tested to obtain the sodium activity coefficient, silicon-aluminum correction coefficient, and iron-calcium ratio, and further obtaining the dynamic fouling and slagging index based on these, thereby performing slagging discrimination. This method introduces the key activity indicator of sodium chemical speciation into the discrimination system, reflecting the release and migration capacity of sodium more accurately from the root, overcoming the limitations of judging solely based on total sodium content. The specific principles of the method for judging the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition of this application are described below with reference to more embodiments.

[0021] Specifically, such as Figure 1 As shown, the method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition in this embodiment includes: Step S10: Perform sodium speciation analysis on the coal sample to be tested to obtain the sodium activity coefficient; Step S20: Perform ash composition analysis on the coal sample to be tested to obtain the silicon-aluminum correction coefficient and the iron-calcium ratio; Step S30: Calculate the dynamic fouling and slagging index based on the sodium activity coefficient, the silicon-aluminum correction coefficient, and the iron-calcium ratio; Step S40: Determine the slagging judgment result based on the dynamic fouling and slagging index.

[0022] For example, there is no necessary sequential relationship between step S10 and step S20 here; the two steps can be performed in parallel and synchronously.

[0023] In one or more embodiments, prior to performing the above steps, the method further includes: grinding the coal sample to be tested to a specified fineness and drying it.

[0024] In one or more embodiments, a method for analyzing the sodium speciation of a coal sample to obtain a sodium activity coefficient includes: The coal sample to be tested was subjected to stepwise chemical extraction to obtain the content of sodium in four different forms; The sodium activity coefficient was calculated based on the content of four different forms of sodium, using the following formula: ; In the formula, , , , This indicates the content of four different forms of sodium. The sodium activity coefficient is represented by 0.7 and 0.3, which are weighting factors based on the ease of volatilization and can be corrected experimentally. The sodium activity coefficient reflects the volatility of sodium.

[0025] For example, a stepwise chemical extraction device was used to extract the coal sample stepwise with deionized water, ammonium acetate solution, and hydrochloric acid solution. The sodium content in the filtrate of each step was quantitatively determined by atomic absorption spectrometry (AAS) or inductively coupled plasma mass spectrometry (ICP-MS), thereby obtaining the content of four different forms of sodium: water-soluble sodium (Na-H2O), organic sodium (Na-NH4Ac), hydrochloric acid-soluble sodium (Na-HCl), and insoluble sodium (Na-Residual). , , , .

[0026] In one or more embodiments, a method for performing ash composition analysis on a coal sample to obtain the silica-alumina correction factor and the iron-calcium ratio includes: The ash composition of the coal sample was analyzed using X-ray fluorescence spectrometry to obtain the mass percentage of the main oxide components, including the mass of SiO2, Al2O3, Na2O, K2O, Fe2O3, CaO, and MgO. The formula for calculating the silicon-aluminum correction factor (SAC) is as follows: ; In the formula, , , , , , , These represent the mass percentages of SiO2, Al2O3, Na2O, K2O, Fe2O3, CaO, and MgO, respectively. The silicon-aluminum correction factor reflects the potential of the ash itself to fix sodium.

[0027] The formula for calculating the iron-calcium ratio (FCR) is as follows: .

[0028] Among them, the iron-calcium ratio affects the ash melting point and the characteristics of the initial deposit layer.

[0029] In one or more embodiments, the dynamic fouling index The calculation formula is as follows: ; In the formula, , , , These are the model weight coefficients, These are constant terms. The values ​​of these coefficients and constant terms were determined using a large sample of coal types with known fouling and slagging behavior, trained using multiple linear regression or machine learning algorithms (such as support vector machines and random forests). B / A is the traditional alkali-acid ratio.

[0030] In one or more embodiments, the method for determining the slagging discrimination result based on the dynamic fouling slagging index includes: making a discrimination based on a preset threshold range in which the dynamic fouling slagging index falls, wherein the slagging discrimination result includes low tendency, medium tendency, high tendency, and severe tendency.

[0031] For example, the calculated DSFI value is compared with a pre-set threshold range for judgment: DSFI < 0.5: Low propensity, safe to use.

[0032] 0.5≤DSFI<1.2: Moderate tendency, monitoring of operating parameters is recommended.

[0033] 1.2≤DSFI<2.0: High tendency, it is recommended to use coal blending or add additives (such as kaolin, coal gangue).

[0034] DSFI ≥ 2.0: Severe tendency, not suitable for use alone, strong prevention and control measures must be taken.

[0035] The following section uses Hongshaquan coal (HSQ) as the sample coal to be tested to illustrate the overall process of the discrimination method.

[0036] 1. Sample preparation and testing

[0037] A sample of Hongshaquan coal (HSQ) from Zhundong, Xinjiang, was ground to 200 mesh and dried at 75°C for 24 hours. The following tests were performed according to the method described in this embodiment: (1) Sodium speciation analysis (stepwise chemical extraction method): Water-soluble sodium (Na-H2O): Weigh 10.00g of the coal sample to be tested, add 500mL of deionized water, shake at room temperature for 2 hours, filter, and determine the sodium content of the filtrate by ICP-MS to obtain the residue.

[0038] Sodium acetate soluble (Na-NH4Ac): The residue was extracted with 500 mL of 1 mol / L ammonium acetate solution for 2 hours and filtered. The sodium content of the filtrate was determined by ICP-MS.

[0039] Sodium soluble in hydrochloric acid (Na-HCl): The residue was extracted with 500 mL of 1 mol / L hydrochloric acid solution for 2 hours, filtered, and the sodium content of the filtrate was determined by ICP-MS.

[0040] Insoluble sodium (Na-Res): determined after digestion of residue.

[0041] Measurement results: , , , , .

[0042] (2) Ash composition analysis:

[0043] The coal sample was ashed at 500℃ for 2 hours, and the ash composition (mass percentage) was determined by XRF. The results are shown in the table below.

[0044]

[0045] 2. Calculation of key parameters

[0046] (1) Sodium activity coefficient (NAC): .

[0047] (2) Silicon-aluminum correction factor SAC: .

[0048] (3) Iron-to-calcium ratio (FCR): .

[0049] (4) Base-to-acid ratio B / A: .

[0050] 3. DSFI Calculation

[0051] Use the weights after training: , , , , .

[0052] .

[0053] 4. Judgment Results

[0054] The calculated DSFI value is 1.156, which falls within the range of 1.2 ≤ DSFI < 2.0, indicating a high tendency for fouling and slagging.

[0055] 5. Prevention and Control Recommendations

[0056] Based on the judgment results, the system automatically outputs suggestions: 1) It is recommended to add 3-6% kaolin or coal gangue additives; 2) It can be blended with 20-30% low-sodium coal; 3) Optimize operating parameters: control the furnace temperature at 1400-1450℃ and appropriately reduce the primary air temperature.

[0057] 6. Practical Verification

[0058] In actual combustion of this type of coal at a power plant, without any intervention, severe slagging occurred on the water-cooled walls after 15 days of operation, requiring frequent soot blowing. Adopting the system's recommendation to add 5% kaolin, no significant slagging was observed after 30 days of continuous operation, verifying the accuracy of this identification method.

[0059] In one or more embodiments, such as Figure 2 As shown, the high-alkali coal fouling and slagging tendency discrimination system based on sodium occurrence form and coal ash composition includes the following modules: sodium speciation analysis module 100, ash composition analysis module 200, data fusion module 300, and slagging discrimination module 400. Sodium speciation analysis module 100 is configured to perform sodium speciation analysis on the coal sample to obtain the sodium activity coefficient; ash composition analysis module 200 is configured to perform ash composition analysis on the coal sample to obtain the silica-alumina correction coefficient and iron-calcium ratio; data fusion module 300 is configured to calculate the dynamic fouling and slagging index based on the sodium activity coefficient, silica-alumina correction coefficient, and iron-calcium ratio; and slagging discrimination module 400 is configured to determine the slagging discrimination result based on the dynamic fouling and slagging index. The specific processes of each module can be referred to the relevant descriptions in the method embodiments, and will not be repeated here.

[0060] The specific embodiments of this application have been described in detail above. Although some embodiments have been shown and described, those skilled in the art should understand that modifications and improvements can be made to these embodiments without departing from the principles and spirit of this application as defined by the claims and their equivalents, and such modifications and improvements should also be within the protection scope of this application.

Claims

1. A method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition, characterized in that, The method includes: The sodium speciation of the coal sample to be tested was analyzed to obtain the sodium activity coefficient. Ash composition analysis was performed on the coal sample to be tested to obtain the silicon-aluminum correction coefficient and the iron-calcium ratio; The dynamic fouling and slagging index is calculated based on the sodium activity coefficient, the silicon-aluminum correction coefficient, and the iron-calcium ratio. The slagging discrimination result is determined based on the dynamic fouling and slagging index.

2. The method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition according to claim 1, characterized in that, Methods for obtaining the sodium activity coefficient by analyzing the sodium speciation of the coal sample include: The coal sample to be tested was subjected to stepwise chemical extraction to obtain the content of sodium in four different forms; The sodium activity coefficient was calculated based on the content of four different forms of sodium, using the following formula: ； In the formula, , , , This indicates the content of four different forms of sodium. This represents the sodium activity coefficient.

3. The method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition according to claim 1, characterized in that, Methods for analyzing the ash composition of coal samples to obtain the silica-alumina correction factor and iron-calcium ratio include: The ash composition of the coal sample was analyzed using X-ray fluorescence spectrometry to obtain the mass percentage of the main oxide components, including the mass of SiO2, Al2O3, Na2O, K2O, Fe2O3, CaO, and MgO. The formula for calculating the silicon-aluminum correction factor (SAC) is as follows: ； In the formula, , , , , , , These represent the mass percentages of SiO2, Al2O3, Na2O, K2O, Fe2O3, CaO, and MgO, respectively. The formula for calculating the iron-calcium ratio (FCR) is as follows: 。 4. The method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition according to claim 1, characterized in that, Dynamic fouling and slagging index The calculation formula is as follows: ； In the formula, , , , These are the model weight coefficients, is a constant term, and B / A is the traditional base-acid ratio.

5. The method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition according to claim 1, characterized in that, The method for determining the slagging discrimination result based on the dynamic fouling and slagging index includes: The slagging index is used to determine the slagging tendency, which is classified as low, medium, high, or severe.

6. The method for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition according to claim 1, characterized in that, The method further includes: The coal sample to be tested is ground to the specified fineness and then dried.

7. A system for determining the fouling and slagging tendency of high-alkali coal based on sodium occurrence form and coal ash composition, characterized in that, The system includes: A sodium speciation analysis module is configured to perform sodium speciation analysis on a coal sample to be tested to obtain a sodium activity coefficient. Ash composition analysis module, which is configured to perform ash composition analysis on the coal sample to be tested to obtain the silicon-aluminum correction coefficient and the iron-calcium ratio; A data fusion module is configured to calculate a dynamic fouling and slagging index based on the sodium activity coefficient, the silicon-aluminum correction coefficient, and the iron-calcium ratio. A slagging discrimination module is configured to determine the slagging discrimination result based on the dynamic fouling slagging index.

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