Real-time identification and visualization system for coal type variable density layering based on coal blending bunker

Abstract

The application provides a coal bunker coal variety variable density layering real-time identification and visualization system based on matched coal, and relates to the technical field of power plant energy saving and environmental protection. The system comprises a server, a communication module, a coal bunker coal level height and volume calculation module set on the server through software programming to form an application program, a coal level height-volume Newton forward interpolation model construction module based on mixed data, a coal bunker coal variety variable density layering iteration model construction module based on matched coal, and a real-time combustion mixed coal parameter calculation module of the coal bunker and the unit. The server realizes data mutual communication between the external system and the original unit control system through the communication module, realizes real-time layering calculation of the coal bunker coal variety variable density and parameter calculation of the real-time combustion mixed coal of the unit, and further adjusts the original unit control system based on the real-time parameters of the combustion mixed coal. The system realizes real-time coal bunker coal layering and real-time combustion mixed coal parameter calculation of the coal bunker and the unit.

Description

Technical Field

[0001] This invention relates to the field of energy conservation and environmental protection technology in power plants, and in particular to a real-time identification and visualization system for the layered stratification of coal types based on the blending of coal in coal bunkers. Background Technology

[0002] The coal bunker is a key component of the pulverizing system in a coal-fired power plant. Its structure typically consists of an upper, approximately cylindrical or cuboid shape and a lower, frustum-shaped section. As a buffer unit for boiler fuel, the coal bunker plays a crucial role in storing and stabilizing coal supply, ensuring continuous coal feeding. The coal bunker's volume is relatively large, varying depending on the unit's capacity and model. For example, in a 350 MW unit, the coal level at full capacity is approximately 13–18 meters, capable of continuously supplying approximately 400–700 tons of coal to the pulverizer. During operation, as coal is continuously consumed, operators need to dynamically replenish the coal according to shifts. Furthermore, to adapt to the unit's combustion requirements under different load conditions, the coal stored in the bunker is usually blended in sections according to load. Different batches of blended coal form a layered structure from top to bottom, and each addition of coal can be considered as the formation of a new layer of coal.

[0003] Due to the continuous dynamic flow of coal during the unit's coal consumption and feeding process, especially in multi-coal blending and separate grinding and storage operation modes, the stratification of coal types within the coal bunker is difficult to accurately obtain. The coal quality parameters of the bottom layer of the coal bunker entering the coal mill in real time directly determine the combustion characteristics in the furnace, which is the core information of greatest concern to enterprises. This parameter not only affects the real-time coal consumption calculation of the unit, but also relates to the optimization and adjustment of unit operating parameters under different coal quality conditions and spot market pricing decisions. Therefore, achieving accurate top-to-bottom stratification identification of coal types within the coal bunker is of great significance for improving the refined operation and economic efficiency of thermal power plants.

[0004] The real-time stratification process of coal types in coal bunkers is complex. In actual operation, it often relies on experience to estimate the remaining coal quantity and coal quality parameters of the bottom layer of burning coal, which has significant uncertainties. There is limited research in this field. Some experts, assuming uniform coal density and planar interfaces, have identified interfaces based on the integral of coal level gauge changes and coal loading start and end times. They have also combined moisture parameters with coal type characteristics, further identifying stratified coal types by establishing a soft moisture measurement model and introducing random forests to correct the results, thus improving identification accuracy. While these methods have made some progress, they still have significant limitations: First, the assumption of uniform coal density only applies to situations with similar coal quality; second, the actual surface of the coal bunker is uneven, making it difficult to satisfy the ideal planar assumption; third, relying solely on coal level gauge changes for stratification identification has limited accuracy, as it usually reflects local areas and can easily misjudge coal level fluctuations caused by top collapse as part of the coal loading process; and fourth, the coal type identification capability based on mill moisture matching is significantly limited when dealing with mixed coals with small moisture differences.

[0005] Furthermore, to identify the type of coal burning in real time, related research mainly focuses on three types of coal quality testing methods: First, characteristic parameter tracking based on soft sensing, which establishes a coal quality mapping relationship by analyzing parameters such as furnace flame spectrum, flue gas composition, and exhaust temperature. However, this method is easily affected by on-site operating conditions and has poor stability. Second, manual testing, which is currently a common method in power plants, but suffers from problems such as long processing time and strong lag. Third, online coal quality testing technologies, including X-ray methods, microwave technology, and near-infrared spectroscopy, to achieve rapid determination of indicators such as ash content, moisture, volatile matter, and calorific value. However, due to limitations in safety and anti-interference capabilities, these technologies mostly remain in the experimental stage. Although some domestic and foreign companies have developed and put into operation related testing equipment, their measurement reliability and accuracy still need to be improved. At the same time, the high cost and difficulty in maintenance of the equipment restrict their large-scale promotion and application. Summary of the Invention

[0006] The technical problem to be solved by this invention is to address the shortcomings of the existing technology. Based on the previous digital management of coal types, coal blending, and coal feeding in coal yards, this invention provides a real-time identification and visualization system for the variable density stratification of coal types in coal bunkers based on coal blending and feeding. The system visualizes the remaining coal position, remaining coal quantity, and remaining operating time in the coal bunker. At the same time, it identifies and obtains information on the composition, proportion, and coal quality parameters of each layer of coal in the coal bunker in real time, providing data support for real-time coal consumption, real-time cost calculation, and unit combustion optimization.

[0007] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: A real-time identification and visualization system for coal type variable density stratification based on blended coal in a coal bunker, comprising a server, a communication module, and a coal bunker coal level height and volume calculation module, a coal level height-volume Newton forward interpolation model construction module based on mixed data, a coal bunker coal type variable density stratification iterative model construction module based on blended coal, and a real-time combustion mixed coal parameter calculation module for the coal bunker and the generating unit; the server, as an external system, communicates with the original generating unit control system through the communication module to realize real-time stratification calculation of coal type variable density in the coal bunker and real-time combustion mixed coal parameter calculation of the generating unit, and further adjusts the original generating unit control system based on the real-time parameters of the combustion mixed coal.

[0008] Furthermore, the coal bunker coal level height and volume calculation module adopts a hybrid modeling method that combines analytical modeling of regular regions with experimental sampling of irregular transition regions to calculate the relationship data points between coal level height and volume at different locations within the coal bunker, and constructs an interpolation modeling data point set;

[0009] The module for constructing a coal level height-volume Newton forward interpolation model based on mixed data uses data points in the interpolation modeling data point set as interpolation points and uses the Newton forward interpolation method to establish an interpolation relationship model between any coal level height and volume in the coal bunker.

[0010] The coal bunker coal type variable density stratified iterative model construction module based on coal type input, coal type number, coal tonnage, and coal type density automatically read from the coal type database, iteratively calculates the volume and mass of each layer of coal in the coal bunker based on the interpolation relationship model between the height and volume of any coal position in the coal bunker, constructs the coal type stratification structure of the coal bunker in real time, and finally determines the remaining amount of coal and coal quality parameters of the burning coal type in the bottom layer.

[0011] The real-time combustion mixed coal parameter calculation module of the coal bunker and the unit calculates the mixed coal quality parameters of the corresponding coal bunker or coal mill by acquiring the coal quality parameters of the coal type layer in real-time combustion of the coal bunker. Based on this, the mixed coal quality parameters of each coal mill are weighted and calculated by combining the coal feeding rate of each coal mill and the mixed coal quality parameters of the corresponding coal bunker, so as to obtain the real-time mixed coal quality weighted average parameter at the unit level.

[0012] Furthermore, the server also includes a relational database interface module and a real-time database interface module; the relational database interface module constructs the interface between the application and the relational database, and through this interface, it realizes the interaction with the relational database tables of the coal yard coal type management system, coal blending system and coal feeding system already applied in the power plant, to obtain coal type parameter information and coal feeding parameter information;

[0013] The real-time database interface module establishes an interface between the application and the real-time database. Through this interface, it enables interaction with the real-time database of the power plant's SIS system to obtain information such as the real-time coal level height, coal feeding rate, and cumulative coal feeding volume in the coal bunker.

[0014] Furthermore, the coal bunker coal level height and volume calculation module employs a hybrid modeling method combining analytical modeling in regular regions and experimental sampling in irregular transition regions to calculate data points relating coal level height and volume at different locations within the coal bunker. The specific method for constructing the interpolation modeling data point set is as follows:

[0015] The coal bunker structure is divided into an upper regular cuboid buffer area, a middle irregular transition area, and a lower regular frustum.

[0016] When the coal in the coal bunker is in the lower regular frustum, the radius of any cross-section of the coal body varies with height. The following linear relationship is satisfied:

[0017] (1);

[0018] In the formula, The large radius of the frustum connected to the regular rectangular prism above the coal bunker. The smaller radius of the frustum at the coal outlet of the coal bunker. For any coal seam height in the coal bunker starting from the reference surface, The total height of the truncated cone-shaped coal drop area;

[0019] Volume of coal at any cross-sectional radius along the height within a coal bunker for:

[0020] (2);

[0021] In the formula, This is the reference volume compensation constant for the coal bunker;

[0022] When the coal level in the coal bunker exceeds the frustum and enters the upper regular cuboid buffer zone, the volume of coal in the cuboid buffer zone at this time is... for:

[0023] (3);

[0024] In the formula, Let the height be the topmost height of the cuboid buffer area, and let the length and width of the cross-section of the cuboid buffer area be respectively set as... and ;

[0025] At this point, the total volume of coal in the coal bunker It consists of the constant volume of coal within the lower frustum and the volume of coal within the cuboid:

[0026] (4);

[0027] For the volume at any height in the irregular transition zone in the middle, the cumulative amount of coal fed through the coal mill under the known coal density is used to inversely calculate the coal volume in the transition zone, and test data points on the relationship between coal level height and volume are selected.

[0028] Furthermore, the coal level height-volume Newton forward interpolation model construction module based on mixed data uses data points in the interpolation modeling data point set as interpolation points, and establishes the interpolation relationship model between coal level height and volume using the Newton forward interpolation method as follows:

[0029] An interpolation model for the relationship between coal level and volume is established using Newton's forward interpolation method, as shown in the following formula:

[0030] (5);

[0031] In the formula, The number of interpolation points in the data point set for interpolation modeling. As basis functions, It is the zero-order difference quotient. for Step difference quotient For the first The coal level height corresponding to each interpolation point.

[0032] Furthermore, based on the coal type stratification iterative model construction module for variable density coal, the volume and mass of each layer of coal inside the coal bunker are iteratively calculated to construct the coal type stratification structure of the coal bunker in real time. The specific method for finally determining the remaining amount of combustion coal and coal quality parameters of the bottom layer is as follows:

[0033] Assume the coal bunker contains, from top to bottom Calculate the number of coal seams in the coal bunker. The mass of all remaining coal seams below each coal seam for:

[0034] (6);

[0035] In the formula, For the first Coal type density of each coal seam For the first Coal loading volume of each coal seam For the first The maximum coal level height corresponding to each coal seam, where when At that time, the coal seam height value detected directly by the level gauge is used to calculate its volume by combining the interpolation relationship model between coal level height and volume in formula (5), and the volumes of other layers and all remaining coal seams below are calculated. The calculation is as follows:

[0036] (7);

[0037] In the formula, For the first Coal type density of each coal seam For the first The amount of coal remaining in each coal seam;

[0038] Combining formulas (6) and (7), the first in the coal bunker The mass of all remaining coal seams below each coal seam The iterative expression is as follows:

[0039] (8);

[0040] After each iteration, the following convergence criteria are used to determine the number of coal types in the coal bunker:

[0041] (9);

[0042] In the formula, The number of coal bunker layers obtained through iteration;

[0043] Calculate the first using the cumulative value of the coal mill Real-time remaining coal mass of each coal seam; setting the first The actual remaining coal mass of each coal seam is And record the cumulative value of coal feed into the coal mill at this moment. The real-time coal feed rate of the coal mill is , No. The real-time remaining coal mass of each coal seam is Then the following relationship exists:

[0044] (10);

[0045] when At this time, the first The coal in the previous seam has been burned out; switch to the next seam. Determine the coal type and coal quality parameters, and update the baseline parameters after the switch:

[0046] (11);

[0047] In the formula, It is the first After the coal seam is updated, the next round of tracking is carried out using formulas (10) and (11) until the uppermost coal seam.

[0048] Furthermore, the system also includes a real-time highest coal level filtering module, which filters the detection data of the uppermost coal level in the coal bunker to obtain the filtered coal level height. The specific method is as follows:

[0049] Real-time acquisition of the top layer of the coal bunker within T seconds The set of sampling points detected by the level gauge is as follows: Calculate the sets of the lowest and highest coal position numbers collected within T seconds:

[0050] (12);

[0051] In the formula, and These are the sets of the lowest and highest coal position numbers collected within T seconds, respectively.

[0052] set up and Sets and The number of elements, the total number of the lowest and highest coal position numbers collected within T seconds is set as follows: The set of lowest coal seam heights collected within T seconds Minimum coal level height set The filtered coal level height is:

[0053] (13);

[0054] In the formula, This represents the coal level height after filtering. This is the set of numbers to remove the lowest and highest coal level numbers.

[0055] Furthermore, the real-time combustion and blending parameter calculation module of the coal bunker and unit performs weighted calculations on the blending coal quality parameters of each coal mill to obtain the real-time weighted average parameters of blending coal quality at the unit level. The specific method is as follows:

[0056] Based on the determination of coal type stratification in the coal bunker, and using the coal yard coal type management system, coal blending system, and coal loading system, the corresponding coal type parameter information is read from the relational database interface module. The weighted average parameters of the real-time combustion layer coal type in the coal bunker are then calculated as follows:

[0057] (14);

[0058] In the formula, The parameters are weighted average parameters of the coal types in the real-time combustion layer of the coal bunker. This refers to the number of coal types in the real-time combustion layer of the coal bunker. Let i be the proportion of the i-th coal type. For the i-th coal type parameter;

[0059] The weighted average parameters of the real-time mixed coal quality of the coal bunker corresponding to the coal mill unit are calculated as follows:

[0060] (15);

[0061] In the formula, This refers to the weighted average parameters of the real-time mixed coal quality of the coal mill unit corresponding to the coal bunker. This represents the number of operating coal mills in the coal mill unit corresponding to this coal bunker. Let be the coal feed rate of the j-th coal mill. is the weighted average parameter of the coal type in the real-time combustion layer of the j-th coal bunker corresponding to the j-th coal mill.

[0062] The method of this invention: 1) It proposes for the first time a whole-process collaborative optimization framework centered on fuel. It integrates coal type and storage management, coal blending and loading processes, and real-time stratified monitoring of multiple coal types in the coal bunker into the fuel-level optimization system. It uses the lowest layer (bottom layer) coal quality parameters obtained by real-time stratified identification of the coal bunker as the core driver to realize the dynamic optimization of the operating parameters of the coal mill and boiler, and construct a collaborative optimization mechanism between the fuel level and the equipment level; 2) In response to the problem of real-time stratified identification of coal types in the coal bunker, it proposes for the first time a variable density stratified iterative model for coal types in the coal bunker based on variable density blending and loading. This model utilizes the density characteristics of different coal types and iteratively calculates the coal layer structure within the coal bunker to achieve real-time identification of the combustion layer and the unburned layer, while simultaneously providing information on the remaining coal quantity and corresponding coal quality parameters; 3) Develop supporting software and hardware systems and implement engineering applications to achieve real-time visual monitoring of the remaining coal level, remaining time, and remaining coal quantity in the coal bunker, avoiding the safety risks of operators manually observing the coal level in the bunker; at the same time, it innovatively achieves real-time acquisition of the remaining coal quantity and coal quality parameters of the lowest layer of coal in the coal bunker, providing a key data foundation for real-time coal consumption and cost calculation of the unit and combustion optimization adjustment.

[0063] The beneficial effects of adopting the above technical solution are as follows: The present invention provides a real-time identification and visualization system for coal type density layering based on coal blending in coal bunkers. In response to the problem that coal blending and co-firing are commonly used in thermal power plants, which makes it difficult to accurately identify the coal type in real-time combustion, (1) firstly, through the established digital software system for power plant coal yard management, coal blending and coal feeding, it is possible to obtain information on coal type, proportion, coal density and coal quality parameters for each shift in the unit's coal bunker.

[0064] (2) Combining the regular volume model of the coal bunker with the experimental data, a Newton forward interpolation model between the coal level height and volume is constructed to realize the accurate conversion relationship between the real-time coal level and the coal bunker volume.

[0065] (3) Based on the different coal density, coal loading and ratio data provided by the relational database, establish a coal bunker variable density layered iterative model. The comprehensive coal quality parameters of the coal bunker and the unit's current burning coal type (the lowest layer of coal in each bunker) are obtained in real time through the iterative method, including calorific value, moisture, volatile matter, ash and sulfur content, etc., to provide data support for unit combustion optimization.

[0066] (4) The modules proposed in this invention are implemented on an external server. The external server is connected to the original unit control system via communication. It does not modify the hardware and program of the original control system. It only changes the bias method from the original manual experience to an algorithm-based external computer control and adjustment method. The external server uses heartbeat pulse and non-disruptive switching to ensure system safety. Once communication failure occurs, the original control system can still operate normally.

[0067] This invention addresses the challenge of accurately identifying the coal type (the lowest layer of coal in each coal bunker) in real-time combustion, a problem commonly encountered in thermal power plants due to coal blending. It proposes for the first time a real-time identification and visualization system for variable-density stratified coal types in coal bunkers based on blended coal. The practical application of this invention yields the following conclusions: 1) It achieves the practical application of real-time coal type stratification in coal bunkers, and for the first time integrates coal yard coal type management, blending, coal loading, and real-time monitoring and stratification of coal bunkers as a systematic engineering development; 2) The variable-density coal type quality iteration technology proposed in this invention not only simplifies programming but also considers the density differences of each layer of coal and effectively solves the problem of coal type stratification in coal bunkers; 3) A corresponding software and hardware system was developed based on a coal bunker stratification business architecture oriented towards the entire fuel process, and practical application demonstrates the effectiveness of this architecture and method.

[0068] In summary, this invention has significant economic, social, and scientific value. Attached Figure Description

[0069] Figure 1 This is a diagram illustrating the implementation of a visualized real-time coal bunker coal type stratification technology in an embodiment of the present invention.

[0070] Figure 2 This is a software interface diagram of the coal type management system for power plant coal yards provided in an embodiment of the present invention;

[0071] Figure 3 This is a software interface diagram of a power plant coal blending system provided in an embodiment of the present invention;

[0072] Figure 4 This is a software interface diagram of a power plant coal loading system provided in an embodiment of the present invention;

[0073] Figure 5 The coal bunker layer modeling and real-time tracking diagram of the coal feeding process provided in the embodiments of the present invention are shown in (a) and (b) respectively. (a) is the tracking diagram under variable density conditions and (b) is the final diagram under constant density conditions.

[0074] Figure 6 This is a flowchart of the solution for coal bunker layering provided in an embodiment of the present invention;

[0075] Figure 7 This is a diagram illustrating the implementation effect of real-time visualized coal bunker coal type stratification for a single unit, provided in an embodiment of the present invention.

[0076] Figure 8 This is a visualization of the real-time coal type stratification implementation effect of two generating units provided in an embodiment of the present invention; Detailed Implementation

[0077] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0078] In this embodiment, a real-time identification and visualization system for variable density stratification of coal types in a coal bunker based on coal blending is described, such as... Figure 1 As shown, the system includes a server, a communication module, and software-programmed application modules set on the server, including a coal bunker coal level height and volume calculation module, a coal level height-volume Newton forward interpolation model construction module based on mixed data, a coal bunker coal type variable density stratified iterative model construction module based on blended coal, a real-time maximum coal level filtering module, a real-time combustion mixed coal parameter calculation module for the coal bunker and the unit, a relational database interface module, and a real-time database interface module. The server, as an external system, communicates with the original unit control system through the communication module to realize real-time stratified calculation of coal type variable density in the coal bunker and real-time combustion mixed coal type parameter calculation for the unit. Based on the real-time parameters of the combustion mixed coal type, the original unit control system is further adjusted. The original unit control system sends a heartbeat switch request frame to the server. The server responds with a digital switch signal (0,1) designed by the program to simulate a heartbeat signal. The original unit control system detects whether the communication of the external system is normal through the heartbeat frame response. When the original unit control system does not detect a heartbeat frame response for a set time, it automatically disconnects the external system and switches to the set signal of the original unit control system.

[0079] In this embodiment, the relational database interface module constructs an interface between the application and the relational database. Through this interface, it interacts with the relational database tables of the coal yard coal type management system, coal blending system and coal feeding system already applied in the power plant to obtain coal type parameter information and coal feeding parameter information.

[0080] The real-time database interface module constructs an interface between the application and the real-time database. Through this interface, it realizes real-time database interaction with the power plant's SIS system (Supervisory Information System, i.e., plant-level monitoring information system) to obtain real-time coal level height, coal feeding rate, and cumulative coal feeding information in the coal bunker.

[0081] The coal bunker height and volume calculation module employs a hybrid modeling method combining analytical modeling of regular regions and experimental sampling of irregular transition zones to calculate data points relating coal level height and volume at different locations within the bunker, constructing an interpolation modeling data point set. The coal bunker is a crucial component of the pulverizing system in a coal-fired power plant, its structure divided into an upper regular cuboid buffer zone, a middle irregular transition zone, and a lower regular frustum. In this embodiment, to reduce the cost of leveling the upper surface of the coal bunker, for the upper regular cuboid buffer zone and the lower regular frustum, the relationship between coal level height and volume is directly calculated based on a geometric volume analytical model. For the middle irregular transition zone, under known coal level height and coal density conditions, the volume is calculated by back-calculating the cumulative coal intake using the SIS system (the cumulative increase in coal intake divided by the density), and a small number of typical experimental data points relating coal level height and volume are selected. Finally, the data points relating coal level height and volume calculated theoretically in the regular region are merged with the experimental data points in the irregular region to form an interpolation modeling data point set.

[0082] The module for constructing a coal level height-volume Newton forward interpolation model based on mixed data uses data points in the interpolation modeling data point set as interpolation points and uses the Newton forward interpolation method to establish an interpolation relationship model between any coal level height and volume in the coal bunker.

[0083] The coal bunker coal type variable density stratified iterative model construction module based on coal type input, coal type number, coal tonnage, and coal type density automatically read from the coal type database, iteratively calculates the volume and mass of each layer of coal in the coal bunker based on the interpolation relationship model between the height and volume of any coal position in the coal bunker, constructs the coal type stratification structure of the coal bunker in real time, and finally determines the remaining amount of coal and coal quality parameters of the burning coal type in the bottom layer.

[0084] The real-time highest coal level filtering module addresses the issues of difficulty in maintaining a level coal pile surface and the potential for localized collapses and flows during coal loading at the side of the coal bunker. It filters the coal level detection data of the uppermost layer of the coal bunker to obtain the filtered coal level height, thereby improving the accuracy and stability of the real-time coal level detection results.

[0085] The real-time combustion mixed coal parameter calculation module of the coal bunker and the unit calculates the mixed coal quality parameters of the corresponding coal bunker or coal mill (coal bunker and coal mill correspond one-to-one) by acquiring the coal quality parameters of the coal type layer (bottom layer) of the coal bunker in real time. On this basis, combined with the coal feeding rate of each coal mill and the mixed coal quality parameters of the corresponding coal bunker, the mixed coal quality parameters of each coal mill are weighted and calculated to obtain the real-time mixed coal quality weighted average parameter at the unit level.

[0086] In this embodiment, the overall implementation process of the real-time identification and visualization system for variable density stratification of coal types in a coal bunker with added coal is as follows: Figure 1 As shown. In Figure 2 Based on the coal type management system providing parameter information for each coal type, the software corresponding to the power plant's automatic coal blending system and coal loading system includes, for example: Figure 3 and Figure 4 As shown, the coal type is determined by the coal handling personnel based on the actual site conditions. It is then simultaneously fed into coal bunker A from the coal yard via two stacker-reclaimers and two conveyor belts. The process is similar for other coal bunkers B, C, and D. Since power plants currently widely employ blended coal combustion technology, each coal bunker contains two or one coal type per coal layer. Furthermore, to adapt to varying load requirements, each coal bunker is divided into layers of different coal types from top to bottom. Based on this, this invention, building upon the automatic coal blending system and the coal handling system, will obtain in real-time comprehensive coal quality parameters for the coal type currently to be burned in each coal bunker and coal mill unit, including calorific value, moisture, volatile matter, ash content, and sulfur content. This provides real-time data support for coal consumption calculation and coal mill unit combustion optimization using blended coal parameters.

[0087] In this embodiment, the coal bunker coal level height and volume calculation module uses a hybrid modeling method that combines analytical modeling of regular regions with experimental sampling of irregular transition regions to calculate the relationship data points between coal level height and volume at different locations within the coal bunker. The specific method for constructing the interpolation modeling data point set is as follows:

[0088] When the coal in the coal bunker is in the lower regular frustum, the radius of any cross-section of the coal body varies with height. The following linear relationship is satisfied:

[0089] (1);

[0090] In the formula, The large radius of the frustum connected to the regular rectangular prism above the coal bunker. The smaller radius of the frustum at the coal outlet of the coal bunker. For any coal seam height in the coal bunker starting from the reference surface, The total height of the constricted coal drop zone is the frustum-shaped section.

[0091] Volume of coal at any cross-sectional radius along the height within a coal bunker for:

[0092] (2);

[0093] In the formula, The constant is the reference volume compensation constant for the coal bunker. There is still some material below the zero level of the coal bunker level gauge (such as the coal stored between the bottom of the constriction of the truncated cone and the inlet of the coal mill). This constant ensures the accuracy of the model.

[0094] When the coal level in the coal bunker exceeds the frustum and enters the upper regular cuboid buffer zone, the volume of coal in the cuboid buffer zone at this time is... for:

[0095] (3);

[0096] In the formula, Let the height be the topmost height of the cuboid buffer area, and let the length and width of the cross-section of the cuboid buffer area be respectively set as... and .

[0097] At this point, the total volume of coal in the coal bunker It consists of the constant volume of coal within the lower frustum and the volume of coal within the cuboid:

[0098] (4);

[0099] After approximating the top of the frustum as a pure cuboid, the height of any object can be calculated using the physical and mathematical model described above. The volume of the lower coal bunker; however, there is an irregular transition zone between the cuboid above the actual coal bunker and the frustum below. To accurately calculate the volume at a certain height in the transition zone, the volume of coal in the transition zone can be calculated by the cumulative amount of coal fed into the coal mill under a known coal density. In other words, the volume is obtained by dividing the cumulative amount of coal fed into the mill by the density.

[0100] In this embodiment, the coal level height-volume Newton forward interpolation model construction module based on mixed data uses data points in the interpolation modeling data point set as interpolation points, and establishes an interpolation relationship model between coal level height and volume using the Newton forward interpolation method as follows:

[0101] Considering that coal enterprises typically load coal into light silos and rarely operate at full capacity, a model for the interpolation relationship between coal level and volume is established using Newton's forward interpolation method, as shown in the following formula:

[0102] (5);

[0103] In the formula, The number of interpolation points in the data point set for interpolation modeling. As basis functions, It is the zero-order difference quotient. for Step difference quotient For the first The coal level height corresponding to each interpolation point.

[0104] In this embodiment, based on the coal type stratification iterative model construction module for variable density coal, the volume and mass of each layer of coal inside the coal bunker are iteratively calculated to construct the coal type stratification structure of the coal bunker in real time. The method for finally determining the remaining amount of combustion coal and coal quality parameters of the bottommost layer is as follows: Figure 6 As shown, specifically:

[0105] Assume the coal bunker contains, from top to bottom Calculate the number of coal seams in the coal bunker. The mass of all remaining coal seams below each coal seam for:

[0106] (6);

[0107] In the formula, For the first Coal type density of each coal seam For the first Coal loading volume of each coal seam For the first The maximum coal level height corresponding to each coal seam, where when When it is the uppermost layer, the coal seam height is directly measured by the level gauge and its volume is calculated by combining the interpolation relationship model between coal level height and volume in formula (5). The volumes of other layers and all remaining coal seams below are calculated. The calculation is as follows:

[0108] (7);

[0109] In the formula, For the first Coal type density of each coal seam For the first The amount of coal remaining in the corresponding coal seam.

[0110] Combining formulas (6) and (7), the first in the coal bunker The mass of all remaining coal seams below each coal seam The iterative expression is as follows:

[0111] (8);

[0112] After each iteration, the following convergence criteria are used to determine the number of coal types in the coal bunker:

[0113] (9);

[0114] In the formula, The number of coal bunker layers obtained through iteration.

[0115] Because the coal bunker stratification is constantly changing, this embodiment uses the cumulative value of the coal mill to calculate the first... The real-time remaining coal mass of each coal seam. This is set to be determined after the above iteration process is completed. The actual remaining coal mass of each coal seam is And record the cumulative value of coal feed into the coal mill at this moment. The real-time coal feed rate of the coal mill is , No. The real-time remaining coal mass of each coal seam is Then the following relationship exists:

[0116] (10);

[0117] when When, prove that at this time the first The coal in the previous seam has been burned out; switch to the next seam. Determine the coal type and coal quality parameters, and update the baseline parameters after the switch:

[0118] (11);

[0119] In the formula, It is the first After the coal quality of each coal seam is updated in real time and the remaining coal quality of the coal seam is updated, the next round of tracking is carried out using formulas (10) and (11) until the uppermost coal seam.

[0120] In addition, if a new coal type is detected in the coal data table, return to formula (6) to start the calculation again.

[0121] In this embodiment, since the coal pile surface is difficult to keep level during the coal loading process, and local subsidence and flow are prone to occur, the real-time highest coal level filtering module filters the coal level height data of the uppermost layer of the coal bunker detected by the level gauge to obtain the filtered coal level height. The specific method is as follows:

[0122] Real-time acquisition of the top layer of the coal bunker within T seconds The set of sampling points detected by the level gauge is as follows: Calculate the sets of the lowest and highest coal position numbers collected within T seconds:

[0123] (12);

[0124] In the formula, and These are the sets of the lowest and highest coal position numbers collected within T seconds.

[0125] set up and Sets and The number of elements, the total number of the lowest and highest coal position numbers collected within T seconds is set as follows: The set of lowest coal seam heights collected within T seconds Minimum coal level height set The filtered coal level height is:

[0126] (13);

[0127] In the formula, This represents the coal level height after filtering. This is the set of numbers to remove the lowest and highest coal level numbers.

[0128] Therefore, by combining the filtered coal level height with the coal bunker's variable density stratified iterative model, the real-time burning coal type and the remaining coal quantity in the combustion layer can be calculated.

[0129] In this embodiment, the specific method for the real-time combustion mixed coal parameter calculation module of the coal bunker and the unit to perform weighted calculation of the mixed coal quality of each coal mill is as follows:

[0130] Based on the determination of coal type stratification in the coal bunker, and using the coal yard coal type management system, coal blending system, and coal loading system, the corresponding coal type parameter information can be read from the relational database interface module. The weighted average parameters of the real-time combustion layer coal type in the coal bunker are then calculated as follows:

[0131] (14);

[0132] In the formula, The parameters are weighted average parameters of the coal types in the real-time combustion layer of the coal bunker. This refers to the number of coal types in the real-time combustion layer of the coal bunker. Let i be the proportion of the i-th coal type. Let be the calorific value, moisture content, sulfur content, volatile matter content, or density parameter of the i-th coal type.

[0133] Furthermore, the weighted average parameters of the real-time mixed coal quality of the coal bunker corresponding to the coal mill unit are calculated as follows:

[0134] (15);

[0135] In the formula, This refers to the weighted average parameters of the real-time mixed coal quality of the coal mill unit corresponding to the coal bunker. This represents the number of operating coal mills in the coal mill unit corresponding to this coal bunker. Let be the coal feed rate of the j-th coal mill. is the weighted average parameter of the coal type in the real-time combustion layer of the j-th coal bunker corresponding to the j-th coal mill.

[0136] In this embodiment, the purpose of coal bunker visualization is to monitor the coal level in the bunker in real time, calculate the remaining coal volume in the lowest layer and the sustainable burning time, as well as the real-time coal feeding rate. This is displayed intuitively using visual graphics and accompanied by voice alarms to prevent leaks. Real-time coal type stratification in the bunker aims to accurately identify the coal type stratification, coal type interfaces, the types and proportions of mixed coal in each layer, and coal quality parameters. Furthermore, it provides the quality parameters of the mixed coal being burned by the coal mill unit.

[0137] In this embodiment, the goal of real-time coal type stratification in the coal bunker is to perform refined identification and analysis of the internal structure of the coal bunker, accurately identify the stratification state and interface of each coal type, clarify the composition and proportion of each layer of mixed coal, obtain the corresponding coal quality parameter information, and further calculate the comprehensive coal quality parameters of the coal type currently being burned by the unit, so as to provide a reliable basis for operation optimization and combustion adjustment.

[0138] In this embodiment, to verify the effectiveness of the coal bunker variable density stratified iterative model, the coal level height-volume Newton forward interpolation model (based on a coal level height-volume Newton forward interpolation model construction module for mixed data) is first used to calculate any height. The volume of coal in the lower coal bunker; further considering the irregular transition zone between the upper cuboid and the lower frustum of a cone in the actual coal bunker, to accurately calculate the volume at the transition zone, given the density of the coal (0.85 kg / m³), 3 The volume was calculated by inversely using the cumulative tonnage of coal fed into the coal mill, and the relationship data points in Table 1 are as follows:

[0139] Table 1. Data points relating coal level and volume

[0140]

[0141] Then, real coal loading records and coal yard database data from a power plant's coal bunker over a period of time were selected (see Tables 2 and 3), and the calculation results of the coal bunker coal type variable density stratified iterative model were quantitatively compared with the traditional constant density stratified iterative model (see Table 3). Figure 5 (Table 4).

[0142] In this embodiment, firstly, a variable density stratified iterative model for coal types in a coal bunker under variable density coal blending conditions is used to calculate the stratification state within the coal bunker at that moment, and the static stratification at the initial moment (t = 0:00) is analyzed. According to formulas (12) and (13), the filtered coal level height is 13.778 m, corresponding to a relative coal level height of 79.817%; further, the interpolation model of formula (5) is used to calculate the coal bunker volume as 502.667 m³. As can be seen from formula (6), the remaining coal quantity below the first layer (uppermost layer) is 202.347 t. Since there is still 202.347 t of coal below this layer, it indicates that this layer is not the lowest coal type.

[0143] Secondly, using equation (8), the remaining coal quantity below the second coal type is calculated to be 129.934 t, indicating that the structure of the next layer still needs to be determined; further calculation of the remaining coal quantity below the third coal type yields a result of -130.053 t. According to equation (9), it can be determined that the coal bunker is divided into three layers, that is... Meanwhile, in the calculation process of equation (8), the first term on the right side of equation (8) The remaining coal quantity in the third layer can be directly obtained as 103.947 t.

[0144] Subsequently, based on the coal loading records in Table 2, it can be seen that: the first layer of coal is Huaneng You / Shenhun (13 / 33), which was added to the warehouse the night before the 21st, and the remaining coal quantity in this layer is 240 t; the second layer of coal is Dayou (11), and the remaining coal quantity in this layer is 123 t; the third layer of coal is Huaneng You / Shenhun (13 / 33), which was added to the warehouse during the day shift on the 21st, and the remaining coal quantity in this layer is 103.947 t.

[0145] Finally, based on the coal type number of each layer, the proportion of coal added, and the coal quality parameters listed in Table 3, and combined with equations (14) and (15), the comprehensive coal quality parameters of the target coal bunker or unit can be calculated. It should be noted that the key to coal bunker layer identification lies in the determination of the number of layers and the accurate identification of the remaining amount of coal in the bottom layer; in contrast, matching and calculating the coal quality parameters of each layer according to the coal type number is a routine process and will not be elaborated further.

[0146] To facilitate understanding of the above calculation process and results, the stratification identification results using the coal type variable density stratification iterative model and the traditional constant density stratification iterative model are summarized in Table 4. The stratification dynamic tracking process is as follows: Figure 5 As shown in Table 4, the "variable density" results fully consider the actual differences in density between different coal types, and the calculation process is further explained. Figure 5 In the diagram, the serial numbers ①, ②, ③, and ④ represent the time when the bottom layer of coal is completely burned, the time when the coal in the unburned layer is completely burned, and the start and end times of the fourth layer of coal being fed at night, respectively.

[0147] Table 4 and Figure 5 It can be seen that at the initial moment (t = 0:00 on the 22nd), the coal bunker was in a three-layer structure, with the remaining coal in the third layer (bottom layer) being 103.947 t. However, under the assumption of a constant density of 0.85 kg / m³ for all coal types, the calculated remaining coal in the bottom layer was 64.267 t, a difference of nearly 40 t. This result indicates that when the density of coal types differs significantly, using a constant density model for layered calculations will significantly underestimate the remaining coal in the bottom layer, thus introducing a large error.

[0148] Combined with Table 4 Figure 5 Further analysis can be conducted on the dynamic changes in coal type stratification within the coal bunker. Figure 5 It is evident that from the initial state (t = 0:00 on the 22nd) to t = 02:00, the coal level in the third (bottom) layer of the coal bunker had dropped to 0%. However, in actual operation, when this layer's coal level reaches zero, approximately 30 tons of unburned coal remain between the coal bunker and the mill. Therefore, in Figure 5The first coal replacement was not completed until t = 02:30 (see mark ①). As shown in Table 4, after the first coal replacement, the coal bunker changed from the initial three-layer structure to a two-layer structure, and the original middle layer coal type moved down and was transformed into the new bottom layer coal type.

[0149] Similarly, at t = 05:21 (see...) Figure 5 Mark ②) The second coal replacement is completed. At this point, the original uppermost coal type moves down and transforms into the bottom coal type. Figure 5 It can also be seen that at 06:23 (see mark ③), the night shift operators began loading coal into the coal bunker and completed the loading at mark ④. At this time, a two-layer coal structure was re-formed in the coal bunker; when the system detects the new coal loading data, it will re-execute the layered iterative calculation according to the above method to complete the new layer identification.

[0150] Table 4 further illustrates the dynamic evolution of the three coal types in the coal bunker from t = 0:00 to 05:21 on the 22nd. The remaining coal quantity in the lowest layer changes continuously, while the coal quality parameters show discrete changes; generally, the parameters of coal types within the same layer can be considered consistent. Therefore, it is necessary to integrate coal level gauge data from the real-time database, as well as information from databases on coal types, blending, and coal loading relationships, to comprehensively and dynamically identify the coal types within the coal bunker.

[0151] Figure 5 The dynamic evolution process corresponding to Table 4 is presented in a more intuitive way, and it is further shown that after coal is added at 06:23, the coal bunker will enter a new round of stratification. It should be noted that the above analysis mainly focuses on coal bunker stratification under variable density conditions; for the constant density model, the analysis approach and process are basically the same, only the density of each coal type is considered to be the same.

[0152] In this embodiment, the implementation effect of visualized real-time coal type stratification in a power plant for single-unit and two-unit coal bunkers is shown in the following diagram. Figure 7 , 8 As shown.

[0153] The operational results demonstrate that this system effectively solves the critical challenge of determining the quantity and quality parameters of coal types in coal bunkers in real time, a significant difficulty in the thermal power industry. Its direct engineering value lies in enabling operators to visually monitor the dynamic changes in coal types within the bunker, thereby better guiding safe production and enhancing the unit's adaptability to load variations. Furthermore, the identified real-time combustion coal type at the bottom layer provides crucial coal quality parameters for real-time coal consumption and cost calculations, and lays a vital data foundation for the dynamic optimization and adjustment of the coal mill and boiler combustion processes.

[0154] Table 2. Coal loading database information for a certain coal bunker.

[0155]

[0156] Table 3 Coal Yard Database Information

[0157]

[0158] Table 4 Comparison of key experimental results

[0159]

[0160] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope defined by the present invention.

Claims

1. A real-time identification and visualization system for the stratification of coal types with varying density in a coal bunker based on coal blending, characterized in that, The system includes a server, a communication module, and an application program set on the server via software programming. This application program includes a coal bunker coal level height and volume calculation module, a coal level height-volume Newton forward interpolation model construction module based on mixed data, a coal bunker coal type variable density stratified iterative model construction module based on blended coal, and a real-time combustion mixed coal parameter calculation module for the coal bunker and the generating unit. The server, as an external system, communicates with the original generating unit control system via the communication module, enabling real-time stratified calculation of coal type variable density in the coal bunker and real-time combustion mixed coal parameter calculation for the generating unit. Based on the real-time parameters of the combustion mixed coal, the original generating unit control system is further adjusted.

2. The real-time identification and visualization system for coal type variation density stratification in coal bunkers based on coal blending as described in claim 1, characterized in that, The coal bunker coal level height and volume calculation module uses a hybrid modeling method that combines analytical modeling in regular regions with experimental sampling in irregular transition regions to calculate the relationship between coal level height and volume at different locations within the coal bunker, and constructs an interpolation modeling data point set. The module for constructing a coal level height-volume Newton forward interpolation model based on mixed data uses data points in the interpolation modeling data point set as interpolation points and uses the Newton forward interpolation method to establish an interpolation relationship model between any coal level height and volume in the coal bunker. The coal bunker coal type variable density stratified iterative model construction module based on coal type input, coal type number, coal tonnage, and coal type density automatically read from the coal type database, iteratively calculates the volume and mass of each layer of coal in the coal bunker based on the interpolation relationship model between the height and volume of any coal position in the coal bunker, constructs the coal type stratification structure of the coal bunker in real time, and finally determines the remaining amount of coal and coal quality parameters of the burning coal type in the bottom layer. The real-time combustion mixed coal parameter calculation module of the coal bunker and the unit calculates the mixed coal quality parameters of the corresponding coal bunker or coal mill by acquiring the coal quality parameters of the coal type layer in real-time combustion of the coal bunker. Based on this, the mixed coal quality parameters of each coal mill are weighted and calculated by combining the coal feeding rate of each coal mill and the mixed coal quality parameters of the corresponding coal bunker, so as to obtain the real-time mixed coal quality weighted average parameter at the unit level.

3. The real-time identification and visualization system for coal type variable density stratification in coal bunkers based on coal blending as described in claim 2, characterized in that, The server also includes a relational database interface module and a real-time database interface module; the relational database interface module constructs the interface between the application and the relational database, and through this interface, it realizes the interaction with the relational database tables of the coal yard coal type management system, coal blending system and coal feeding system already applied in the power plant, and obtains coal type parameter information and coal feeding parameter information; The real-time database interface module establishes an interface between the application and the real-time database. Through this interface, it enables interaction with the real-time database of the power plant's SIS system to obtain information such as the real-time coal level height, coal feeding rate, and cumulative coal feeding volume in the coal bunker.

4. The real-time identification and visualization system for coal type variation density stratification in coal bunkers based on blended coal, as described in claim 3, is characterized in that... The coal bunker coal level height and volume calculation module employs a hybrid modeling method combining analytical modeling in regular regions and experimental sampling in irregular transition regions to calculate data points relating coal level height and volume at different locations within the coal bunker. The specific method for constructing the interpolation modeling data point set is as follows: The coal bunker structure is divided into an upper regular cuboid buffer area, a middle irregular transition area, and a lower regular frustum. When the coal in the coal bunker is in the lower regular frustum, the radius of any cross-section of the coal body varies with height. The following linear relationship is satisfied: (1)； In the formula, The large radius of the frustum connected to the regular rectangular prism above the coal bunker. The smaller radius of the frustum at the coal outlet of the coal bunker. For any coal seam height in the coal bunker starting from the reference surface, The total height of the truncated cone-shaped coal drop area; The volume of coal at any cross-sectional radius along the height within the coal bunker for: (2)； In the formula, This is the reference volume compensation constant for the coal bunker; When the coal level in the coal bunker exceeds the frustum and enters the upper regular cuboid buffer zone, the volume of coal in the cuboid buffer zone at this time is... for: (3)； In the formula, Let the height be the topmost height of the cuboid buffer area, and let the length and width of the cross-section of the cuboid buffer area be respectively set as... and ; At this point, the total volume of coal in the coal bunker It consists of the constant volume of coal within the lower frustum and the volume of coal within the cuboid: (4)； For the volume at any height in the irregular transition zone in the middle, the cumulative amount of coal fed through the coal mill under the known coal density is used to inversely calculate the coal volume in the transition zone, and test data points on the relationship between coal level height and volume are selected.

5. The real-time identification and visualization system for coal type variation density stratification in coal bunkers based on coal blending as described in claim 4, characterized in that, The module for constructing the coal level height-volume Newton forward interpolation model based on mixed data uses data points from the interpolation modeling data point set as interpolation points and establishes the interpolation relationship model between coal level height and volume using the Newton forward interpolation method as follows: An interpolation model for the relationship between coal level and volume is established using Newton's forward interpolation method, as shown in the following formula: (5)； In the formula, The number of interpolation points in the data point set for interpolation modeling. As basis functions, It is the zero-order difference quotient. for Step difference quotient For the first The coal level height corresponding to each interpolation point.

6. The real-time identification and visualization system for coal type variable density stratification in coal bunkers based on coal blending as described in claim 5, characterized in that, Based on the coal type stratification iterative model construction module for variable density coal, the volume and mass of each layer of coal inside the coal bunker are iteratively calculated to construct the coal type stratification structure of the coal bunker in real time. The specific method for determining the remaining amount and coal quality parameters of the combustion coal type in the bottom layer is as follows: Assume the coal bunker contains, from top to bottom Calculate the number of coal seams in the coal bunker. The mass of all remaining coal seams below each coal seam for: (6)； In the formula, For the first Coal type density of each coal seam For the first Coal loading volume of each coal seam For the first The maximum coal level height corresponding to each coal seam, where when At that time, the coal seam height value detected directly by the level gauge is used to calculate its volume by combining the interpolation relationship model between coal level height and volume in equation (5), and the volumes of other layers and all remaining coal seams below are calculated. The calculation is as follows: (7) ； In the formula, For the first Coal type density of each coal seam For the first The amount of coal remaining in each coal seam; Combining formulas (6) and (7), the first in the coal bunker The mass of all remaining coal seams below each coal seam The iterative expression is as follows: (8)； After each iteration, the following convergence criteria are used to determine the number of coal types in the coal bunker: (9)； In the formula, The number of coal bunker layers obtained through iteration; Calculate the first using the cumulative value of the coal mill Real-time remaining coal mass of each coal seam; setting the first The actual remaining coal mass of each coal seam is And record the cumulative value of coal feed into the coal mill at this moment. The real-time coal feed rate of the coal mill is , No. The real-time remaining coal mass of each coal seam is Then the following relationship exists: (10)； when At this time, the first The coal in the previous seam has been burned out; switch to the next seam. Determine the coal type and coal quality parameters, and update the baseline parameters after the switch: (11)； In the formula, It is the first After the coal seam is updated, the quality of coal is tracked again using formulas (10) and (11) until the uppermost coal seam is reached.

7. The real-time identification and visualization system for coal type variation density stratification in coal bunkers based on coal blending as described in claim 6, characterized in that, The system also includes a real-time highest coal level filtering module, which filters the coal level detection data of the uppermost layer of the coal bunker to obtain the filtered coal level height. The specific method is as follows: Real-time acquisition of the top layer of the coal bunker within T seconds The set of sampling points detected by the level gauge is as follows: Calculate the sets of the lowest and highest coal position numbers collected within T seconds: (12)； In the formula, and These are the sets of the lowest and highest coal position numbers collected within T seconds, respectively. set up and Sets and The number of elements, the total number of the lowest and highest coal position numbers collected within T seconds is set as follows: The set of lowest coal seam heights collected within T seconds Minimum coal level height set The filtered coal level height is: (13)； In the formula, This represents the coal level height after filtering. This is the set after removing the lowest and highest coal position numbers.

8. The real-time identification and visualization system for coal type variation density stratification in coal bunkers based on blended coal, as described in claim 7, is characterized in that... The real-time combustion and blending parameter calculation module of the coal bunker and unit performs weighted calculations on the blending coal quality parameters of each coal mill to obtain the weighted average parameters of real-time blending coal quality at the unit level. The specific method is as follows: Based on the determination of coal type stratification in the coal bunker, and using the coal yard coal type management system, coal blending system, and coal loading system, the corresponding coal type parameter information is read from the relational database interface module. The weighted average parameters of the real-time combustion layer coal type in the coal bunker are then calculated as follows: (14)； In the formula, The parameters are weighted average parameters of the coal types in the real-time combustion layer of the coal bunker. This refers to the number of coal types in the real-time combustion layer of the coal bunker. Let i be the proportion of the i-th coal type. For the i-th coal type parameter; The weighted average parameters of the real-time mixed coal quality of the coal bunker corresponding to the coal mill unit are calculated as follows: (15)； In the formula, This refers to the weighted average parameters of the real-time mixed coal quality of the coal mill unit corresponding to the coal bunker. This represents the number of operating coal mills in the coal mill unit corresponding to this coal bunker. Let be the coal feed rate of the j-th coal mill. is the weighted average parameter of the coal type in the real-time combustion layer of the j-th coal bunker corresponding to the j-th coal mill.

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