Coal blending control methods, devices, computer equipment and storage media

Abstract

The present invention discloses a coal blending and combustion control method, device, computer equipment and storage medium, the method comprising: establishing a coal blending and combustion case library according to preset stable working conditions, and determining the scoring parameters of a single case in the coal blending and combustion case library according to a preset coal evaluation mechanism; obtaining the operating constraints of the coal-fired power generation system; screening the coal blending and combustion cases in the coal blending and combustion case library according to the operating constraints, and determining a target coal blending and combustion case set according to the screening results; sorting the single cases in the target coal blending and combustion case set according to the scoring parameters, and determining the optimal blending scheme according to the sorting results; and controlling the coal-fired power generation system to blend and load the warehouse according to the optimal blending scheme. The present invention establishes a case library and forms a blending scheme that can guide the warehouse operation in combination with the actual needs of power generation, which is conducive to improving the practicality and accuracy of the blending scheme and improving the economy of coal used for power generation.

Description

Technical Field

[0001] The present invention relates to the field of power generation technology, and in particular to a coal blending and combustion control method, device, computer equipment and storage medium. Background Art

[0002] Coal-fired power generation is currently an important source of power supply. Among them, fuel cost is the main cost of coal-fired power generation enterprises. On the premise of ensuring the safe operation of the units, power generation enterprises need to increase the utilization rate of low-priced coal and reduce the price of coal entering the furnace by blending coal.

[0003] Coal blending and combustion are affected by different coal types and different mill layouts, resulting in significant variations in blending results. Existing coal blending methods typically use the quality of the blended coal as a target for calculation. Some coal-fired power generation companies rely on manual blending experience or lack sufficient blending methods to complete pre-furnace blending, making it difficult to accurately determine and achieve the desired results. Furthermore, in actual production, coal quality fluctuates, and the operating status of the generator set significantly influences combustion results. Calculating blending based on the quality of the blended coal results in significant deviations in the algorithmic data, affecting the blending calculation results. Consequently, existing technologies are unable to develop a practical solution to guide coal loading operations. Summary of the Invention

[0004] The present invention provides a coal blending and combustion control method, device, computer equipment and storage medium, so as to form a blending scheme that can guide the loading operation in combination with the actual demand of power generation, thereby improving the practicality and economy of the blending scheme.

[0005] In a first aspect, an embodiment of the present invention provides a method for controlling coal blending and combustion, comprising the following steps:

[0006] Establishing a coal blending and combustion case library based on preset stable operating conditions, and determining scoring parameters for individual cases in the coal blending and combustion case library based on a preset coal evaluation mechanism;

[0007] Obtain the operating constraints of coal-fired power generation systems;

[0008] screening the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraint conditions, and determining a target coal blending and combustion case set according to the screening results;

[0009] Sorting individual cases in the target coal blending and combustion case set according to the scoring parameters, and determining an optimal blending scheme according to the sorting results;

[0010] The coal-fired power generation system is controlled by blending and loading according to the optimal blending scheme.

[0011] Optionally, the coal blending and combustion control method also includes the following steps: obtaining the predicted blending and combustion results of the optimal blending scheme; obtaining the actual blending and combustion data after the optimal blending scheme is executed, and determining the predicted average coal quality data based on the actual blending and combustion data; and eliminating invalid cases based on the predicted blending and combustion results and / or the predicted average coal quality data.

[0012] Optionally, after obtaining the coal blending and combustion case library, the coal blending and combustion control method also includes the following steps: obtaining dynamic parameters associated with the preset coal combustion evaluation mechanism; obtaining variable data of the dynamic parameters; and updating the dynamic parameters in the coal blending and combustion case library in real time according to the variable data to obtain the coal blending and combustion case library after data update.

[0013] Optionally, before determining the target coal blending and combustion case set, the following steps are also included: discretizing all coal blending and combustion cases in the coal blending and combustion case library according to preset key parameters to obtain multiple case grids; refining cases on a single case grid based on a preset clustering algorithm to obtain a representative case for each case grid; establishing a representative case library based on the representative cases; selecting the coal blending and combustion cases in the representative case library according to the operating constraints, and determining the target coal blending and combustion case set based on the screening results.

[0014] Optionally, the preset key parameters include: load section, location of coal mill in use, number of coal mills in use and type of coal used by the coal mill.

[0015] Optionally, the coal-fired power generation system is controlled by blending and loading according to the optimal blending scheme, including: splitting the optimal blending scheme according to time sequence, coal bin number and coal type to obtain multiple loading information; splitting the loading information for a second time according to the equipment location and the system to which the equipment belongs in the coal-fired power generation system to obtain multiple equipment operation instructions; controlling the equipment operation in the coal-fired power generation system according to the equipment operation instructions to perform coal blending and combustion.

[0016] Optionally, a coal blending and combustion case library is established according to preset stable operating conditions, including: obtaining real-time operating parameters and / or historical operating parameters of the coal-fired power generation system; performing a stable operating condition judgment on the real-time operating parameters or the historical operating parameters according to the preset stable operating conditions, and screening the real-time operating parameters or the historical operating parameters according to the judgment result; and establishing the coal blending and combustion case library according to the screening parameters.

[0017] Optionally, the preset coal evaluation mechanism includes at least one of the following: an economic evaluation mechanism, a safety evaluation mechanism, an environmental evaluation mechanism and a rationality evaluation mechanism; wherein the economic evaluation mechanism is used to calculate the economic score based on preset cost parameters; the safety evaluation mechanism is used to calculate the safety score based on preset safe operation parameters; the environmental evaluation mechanism is used to calculate the environmental score based on preset environmental parameters; and the rationality evaluation mechanism is used to calculate the rationality score based on preset reasonable operation parameters.

[0018] In a second aspect, an embodiment of the present invention further provides a coal blending and combustion control device, comprising:

[0019] A case library acquisition unit is used to establish a coal blending and combustion case library according to a preset stable operating condition, and determine a scoring parameter of a single case in the coal blending and combustion case library according to a preset coal evaluation mechanism;

[0020] A constraint condition detection unit, used to obtain the operating constraint conditions of the coal-fired power generation system;

[0021] a blending scheme acquisition unit, configured to screen the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraints, determine a target coal blending and combustion case set according to the screening results, and sort individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine an optimal blending scheme according to the sorting results;

[0022] The upper bunker execution unit is used to control the blending and upper bunkering of the coal-fired power generation system according to the optimal blending plan.

[0023] In a third aspect, an embodiment of the present invention further provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned coal blending and combustion control method when executing the program.

[0024] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned coal blending and combustion control method when executed by a processor.

[0025] The coal blending and combustion control method, device, computer equipment and storage medium provided by the embodiments of the present invention establish a coal blending and combustion case library according to the preset stable operating conditions by setting preset stable operating conditions and a preset coal combustion evaluation mechanism, and determine the scoring parameters of individual cases in the coal blending and combustion case library according to the preset coal combustion evaluation mechanism; obtain the operating constraints during the actual operation of the coal-fired power generation system, screen the coal blending and combustion cases in the coal blending and combustion case library according to the operating constraints, and determine the target coal blending and combustion case set according to the screening results; sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme according to the sorting results; control the blending and loading of the coal-fired power generation system according to the optimal blending scheme, thereby solving the problem that the existing coal blending and combustion algorithm has large data deviation and low accuracy, resulting in the inability of the blending calculation to actually guide the coal loading operation, and forming a blending scheme that can guide the loading operation in combination with the actual power generation needs, which is conducive to improving the practicality and accuracy of the blending scheme and improving the economy of coal used for power generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 This is a flow chart of a coal blending and combustion control method provided in Example 1 of the present invention;

[0027] Figure 2 This is a flow chart of a coal blending and combustion control method provided in Example 2 of the present invention;

[0028] Figure 3 This is a flow chart of a coal blending and combustion control method provided in Example 3 of the present invention;

[0029] Figure 4 This is a flow chart of a coal blending and combustion control method provided in Example 4 of the present invention;

[0030] Figure 5 This is a flow chart of a coal blending and combustion control method provided in Example 5 of the present invention;

[0031] Figure 6 A schematic structural diagram of a coal blending and combustion control device provided in Example 6 of the present invention;

[0032] Figure 7 A structural diagram of a computer device provided in Example 7 of the present invention. DETAILED DESCRIPTION

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and examples. It will be understood that the specific embodiments described herein are intended only to illustrate the present invention and are not intended to limit the present invention. It should also be noted that, for ease of description, the accompanying drawings only illustrate portions relevant to the present invention, not all structures.

[0034] Figure 1This is a flow chart of a coal blending and burning control method provided in Example 1 of the present invention. This embodiment can be applied to application scenarios of guiding coal bunkers and pulverizers for coal-fired power generation to perform coal blending operations. The method can be executed by a coal blending and burning control device, which is implemented by specific functional modules and / or software programs.

[0035] like Figure 1 As shown, the coal blending and combustion control method specifically includes the following steps:

[0036] Step S1: establishing a coal blending and combustion case library according to preset stable operating conditions, and determining scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism.

[0037] Among them, the coal blending and combustion case is a coal-fired power generation unit operation plan formed by data such as the coal-fired power generation unit load, main steam pressure, main steam flow, main steam temperature, type of coal burned, amount of coal burned, coal price, mill operating status and various scoring-related parameters.

[0038] Preset stable operating conditions refer to the data conditions that ensure stable operation of a coal-fired power generation unit. Typically, these conditions include: the coal-fired power generation unit load is within a preset load range, the main steam pressure is within a preset pressure range, the main steam flow is within a preset flow range, the type of coal burned remains unchanged, the pulverizer output is within a preset output range, and the sootblowing status remains unchanged.

[0039] A pre-defined coal evaluation mechanism analyzes the real-time performance of coal-fired power generation units based on multi-faceted evaluation rules and evaluates them using various metrics, such as scores. Typically, this mechanism uses one or more of the following parameters: economy, safety, environmental performance, or rationality.

[0040] Optionally, a coal blending and combustion case library is established based on preset stable operating conditions, including: obtaining real-time operating parameters and / or historical operating parameters of the coal-fired power generation system; making a stable operating condition judgment on the real-time operating parameters or historical operating parameters based on the preset stable operating conditions, and screening the real-time operating parameters or historical operating parameters based on the judgment results; and establishing a coal blending and combustion case library based on the screening parameters.

[0041] In this embodiment, a stable operating condition judgment can be made based on the real-time operating parameters or historical operating parameters of the coal-fired power generation system. When it is judged that the coal-fired power generation unit is in a stable operating condition, all data used for operating condition judgment and combustion condition analysis at the same sampling moment are extracted to form a single coal blending and combustion case. The data in the single coal blending and combustion case is scored and calculated using a preset coal evaluation mechanism. The obtained scoring parameters correspond one-to-one to the single case. Within the preset sampling period, a collection of multiple coal blending and combustion cases forms a coal blending and combustion case library.

[0042] Step S2: Obtain the operating constraints of the coal-fired power generation system.

[0043] The operating constraints refer to the unit operating constraints determined based on the actual operating status of the coal-fired power generation system. Typically, the constraints include data such as equipment maintenance, coal storage volume, and coal storage structure.

[0044] In this embodiment, the operation constraint condition may be an inherent operation constraint condition detected by the system or a manual operation constraint condition set by an operator.

[0045] Exemplarily, the inherent operating constraints of the coal-fired power generation system include but are not limited to: the maintenance status of the pulverizer, the predicted load segment conditions, the types of coal stored in the coal yard, and the amount of coal of different types; the manual operating constraints include but are not limited to: SO2 emissions are less than the preset emission threshold.

[0046] Step S3: screening the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraints, and determining the target coal blending and combustion case set according to the screening results.

[0047] In this embodiment, based on inherent operating constraints such as equipment maintenance, coal storage volume, coal storage structure, and manual operating constraints set by operators, coal blending and combustion cases that meet all operating constraints can be screened out from the coal blending and combustion case library to form a target coal blending and combustion case set.

[0048] Step S4: Sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme based on the sorting results.

[0049] In this embodiment, under the preset coal evaluation mechanism, each coal blending case has a set of scoring parameters. The cases in the target coal blending case set can be sorted according to the scoring level under the same evaluation standard. Based on the sorting results, the case with the best score is selected as the optimal blending plan.

[0050] Step S5: Control the blending and loading of the coal-fired power generation system according to the optimal blending scheme.

[0051] Among them, blending and loading control refers to the control process of controlling the equipment of the coal-fired power generation system to complete coal collection, transportation and blending according to the optimal blending plan.

[0052] Specifically, the above step S1 records the method of establishing a case library. When establishing the case library, data extraction can be performed based on the historical system parameters or real-time system parameters of the coal-fired power generation system. At each preset sampling time, the system parameters associated with the preset coal evaluation mechanism and the preset stable operating conditions in the historical system parameters or real-time system parameters are collected, such as the load of the coal-fired power generation unit, the main steam pressure, the main steam flow, the main steam temperature, the type of coal burned, the amount of coal burned, the coal price, the operating status of the pulverizer and various scoring-related parameters, and whether the coal-fired power generation unit is in a stable operating condition is judged based on the system parameters. After the stable operating condition judgment, all parameters under unstable operating conditions are eliminated, the system parameters under stable operating conditions are recorded and stored, and the preset coal evaluation mechanism is used to score and calculate the system parameters under stable operating conditions. The system parameters and corresponding scoring parameters of each case under stable operating conditions are stored in the server to form a coal blending and combustion case library.

[0053] Steps S2 through S4 describe a method for determining a practical, feasible coal blending scheme based on a case library. After the coal-fired power generation system is operational, the system's operating constraints are monitored in real time. Coal blending cases in the case library that meet all operating constraints are combined into a target coal blending case set. The case with the highest score in this target coal blending case set is then determined as the optimal blending scheme. This optimal blending scheme includes data on coal type and mill output for different coal bunker numbers.

[0054] Step S5 describes the method for executing the blending scheme. After obtaining the optimal blending scheme, the time sequence of different instructions in the optimal blending scheme, different coal bunker numbers, and different coal types are converted into a text scheme that can be recognized by operators, or directly converted into control instructions that can be executed by system equipment, directly or through operators indirectly controlling the equipment of the coal-fired power generation system to complete coal collection, transportation, and blending operations. This solves the problem that the existing coal blending and combustion algorithm has large data deviations and low accuracy, resulting in the blending calculation being unable to actually guide coal loading operations. Combining the actual needs of power generation to form a blending scheme that can guide bunkering operations is conducive to improving the practicality and accuracy of the blending scheme and improving the economic efficiency of coal used for power generation.

[0055] Optionally, the preset coal evaluation mechanism includes at least one of the following: an economic evaluation mechanism, a safety evaluation mechanism, an environmental evaluation mechanism and a rationality evaluation mechanism; wherein the economic evaluation mechanism is used to calculate the economic score based on preset cost parameters; the safety evaluation mechanism is used to calculate the safety score based on preset safe operation parameters; the environmental evaluation mechanism is used to calculate the environmental score based on preset environmental parameters; and the rationality evaluation mechanism is used to calculate the rationality score based on preset reasonable operation parameters.

[0056] Optionally, the preset cost parameters may include at least one of the following: coal combustion cost, plant electricity cost, boiler efficiency variation cost, turbine heat rate variation cost, and ammonia injection cost. Specifically, each cost can be directly weighted to obtain a total cost, and the economic efficiency score is calculated using the total cost and the preset cost scoring coefficient.

[0057] Optionally, the preset safety operating parameters may include at least one of the following: coal spontaneous combustion characteristics, coking and fouling characteristics, furnace negative pressure, thermal deviation, pulverizer safety, fan safety, and wall temperature safety. Specifically, a safety sub-score may be calculated based on each safety operating parameter, and the safety score may be determined by the lowest safety sub-score.

[0058] Optionally, the preset environmental parameters may include at least one of the following: NOx levels before and after the desulfurization device, SO2 levels before and after the desulfurization device, and dust levels after the dust collector. Specifically, an environmental performance sub-score may be calculated based on each environmental parameter, with the lowest environmental performance sub-score determining the environmental performance score.

[0059] Optionally, the preset reasonable operation parameters may include at least one of the following: coal Halfords grindability coefficient, coal fineness, coal uniformity, fire detection intensity, and furnace temperature. Specifically, a reasonableness sub-item score may be calculated based on each reasonable operation-related parameter, and the reasonableness score may be determined by the lowest reasonableness sub-item score.

[0060] For example, if the preset coal evaluation mechanism is defined as an economic evaluation mechanism, the cases in the target coal blending case set can be sorted according to the economic scores of each case, and the case with the highest economic score can be used as the optimal blending scheme. Coal blending can be implemented through this scheme to improve the economic efficiency of coal-fired power generation.

[0061] It should be noted that, in the embodiment of the present invention, the scoring parameters may be represented in the form of scores, grading levels, or graphs and charts, and there is no limitation to this.

[0062] Optionally, Figure 2 This is a flow chart of a coal blending and combustion control method provided in Example 2 of the present invention.

[0063] like Figure 2 As shown, the coal blending and combustion control method specifically includes the following steps:

[0064] Step S1: establishing a coal blending and combustion case library according to preset stable operating conditions, and determining scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism.

[0065] Step S2: Obtain the operating constraints of the coal-fired power generation system.

[0066] Step S3: screening the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraints, and determining the target coal blending and combustion case set according to the screening results.

[0067] Step S4: Sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme based on the sorting results.

[0068] Step S5: Control the blending and loading of the coal-fired power generation system according to the optimal blending scheme.

[0069] Step S601: Obtaining the predicted blending result of the optimal blending scheme.

[0070] The predicted blending result may be a predicted load rate or a predicted power generation corresponding to the optimal blending scheme.

[0071] Step S602: Acquire actual blending and combustion data after the optimal blending scheme is executed, and determine predicted average coal quality data based on the actual blending and combustion data.

[0072] The actual blending data includes actual blending results and coal-fired power generation system operating parameters. The actual blending results may be the actual load rate of the system or the actual power generation of the system after the optimal blending scheme is executed.

[0073] In this embodiment, the coal quality data may include data representing the quality of the coal, such as the calorific value, moisture content, and sulfur content of the coal used for combustion.

[0074] Step S603: Eliminate invalid cases based on the predicted blending results and / or the predicted average coal quality data.

[0075] Specifically, steps S601 through S603 describe a method for identifying and screening invalid blending scenarios. Before implementing blending control, based on system parameters such as main steam pressure, main steam flow, main steam temperature, bunker number, coal type, and mill output in the optimal blending scenario, a coal blending scenario with the same system parameters is matched from a coal blending and combustion case library. The unit load or power generation of the matched scenario is then determined as the predicted blending result.

[0076] After controlling the blending and loading according to the optimal blending scheme, the combustion and power generation conditions of the coal-fired power generation system are analyzed to determine whether the current blending scheme is an invalid case.

[0077] In this embodiment, the predicted power generation in the predicted blending result can be compared with the actual power generation in the actual blending result to determine whether the deviation rate between the predicted power generation and the actual power generation is greater than the preset power generation deviation threshold. If the deviation rate between the predicted power generation and the actual power generation is greater than the preset power generation deviation threshold, the current optimal blending scheme is determined to be an invalid case, and the blending and loading control through this case is stopped, and the invalid case is deleted from the coal blending case library.

[0078] In this embodiment, the predicted average coal quality data of the burned coal, such as calorific value, moisture content, and sulfur content, can also be inferred based on the actual blending data. At the same time, the actual quality and type of the burned coal are read from the plant-level monitoring information system (SIS system) of the coal-fired power plant or other plant-level monitoring systems. The average coal quality data entering the furnace is calculated based on the type and amount of coal used in the optimal blending scheme. The predicted average coal quality data is compared with the average coal quality data entering the furnace to determine whether the deviation rate between the predicted average coal quality data and the average coal quality data entering the furnace is greater than a preset coal quality deviation threshold. If the deviation rate between the predicted average coal quality data and the average coal quality data entering the furnace is greater than the preset coal quality deviation threshold, the current optimal blending scheme is determined to be an invalid case, and the blending and loading control through this case is stopped, and the invalid case is deleted from the coal blending and combustion case library.

[0079] If the deviation rate between the predicted power generation and the actual power generation is less than or equal to the preset power generation deviation threshold, and the deviation rate between the predicted average coal quality data and the average coal quality data entering the furnace is less than or equal to the preset coal quality deviation threshold, the current optimal blending scheme is determined to be a valid case, the case is retained, and the blending and storage control continues according to the case.

[0080] It should be noted that embodiments of the present invention can also perform invalid case analysis based on either the predicted blending results or the predicted average coal quality data. The specific process is the same as described above and will not be repeated here. By introducing an invalid case screening extreme value, the coal-fired power generation system can self-check the accuracy of coal type data, which helps improve the accuracy and practicality of case matching.

[0081] Optionally, Figure 3 This is a flow chart of a coal blending and combustion control method provided in Example 3 of the present invention. In this embodiment, after obtaining a coal blending and combustion case library, the data in the case library is updated in real time, and the final blending scheme is matched according to the updated case library.

[0082] like Figure 3 As shown, the coal blending and combustion control method specifically includes the following steps:

[0083] Step S1: establishing a coal blending and combustion case library according to preset stable operating conditions, and determining scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism.

[0084] Step S101: Acquire dynamic parameters associated with a preset coal combustion evaluation mechanism.

[0085] The dynamic parameters are parameters that change according to the actual time in the preset coal evaluation mechanism. Typically, the dynamic parameters include but are not limited to coal price parameters and ammonia injection cost parameters.

[0086] Step S102: Obtain variable data of dynamic parameters.

[0087] Among them, variable data is real-time data after dynamic parameters change.

[0088] Step S103: updating the dynamic parameters in the coal blending and combustion case library in real time according to the variable data, and obtaining the coal blending and combustion case library after data update.

[0089] Step S2: Obtain the operating constraints of the coal-fired power generation system.

[0090] Step S3: screening the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraints, and determining the target coal blending and combustion case set according to the screening results.

[0091] Step S4: Sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme based on the sorting results.

[0092] Step S5: Control the blending and loading of the coal-fired power generation system according to the optimal blending scheme.

[0093] Specifically, steps S101 to S103 describe a method for updating dynamic variables in a case library in real time. After establishing a coal blending and combustion case library, variable data for dynamic parameters is received in real time. If a dynamic parameter changes, all cases in the coal blending and combustion case library involving that dynamic parameter are searched, and the dynamic parameters in the searched cases are replaced with the variable data. This is then saved to form a new case library, completing a data refresh. In subsequent steps, case matching is performed based on the refreshed case library.

[0094] For example, using the dynamic parameter coal price as an example, a fuel procurement system can be connected. At preset intervals, the system reads the real-time coal price parameter within the fuel procurement system. If the price of coal type A changes, the system searches the coal blending case library for all cases using coal type A and replaces the price data for coal A in all cases using coal type A based on the latest price, dynamically updating the case library data. By introducing dynamic variable data update extreme values, the parameters in the case library can respond to changes in time in real time, ensuring the real-time effectiveness of case and blending calculations, and improving the accuracy and practicality of case matching.

[0095] Optionally, Figure 4 This is a flow chart of a coal blending and combustion control method provided in the fourth embodiment of the present invention. In this embodiment, the representative cases formed by extraction are matched with the target coal blending and combustion case set.

[0096] like Figure 4 As shown, the coal blending and combustion control method specifically includes the following steps:

[0097] Step S1: establishing a coal blending and combustion case library according to preset stable operating conditions, and determining scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism.

[0098] Step S2: Obtain the operating constraints of the coal-fired power generation system.

[0099] Step S701: discretize all coal blending and combustion cases in the coal blending and combustion case library according to preset key parameters to obtain multiple case grids.

[0100] Optionally, the preset key parameters include: load section, location of coal mill in use, number of coal mills in use and type of coal used by the coal mill.

[0101] Step S702: extract cases from a single case grid based on a preset clustering algorithm to obtain representative cases for each case grid.

[0102] Optionally, the preset clustering algorithm may be any one of the following: a data density-based clustering algorithm, a K-means clustering algorithm, a mean shift clustering algorithm, or a graph group detection clustering algorithm.

[0103] Step S703: Establish a representative case library based on the representative cases.

[0104] Step S704: screening the coal blending and combustion cases in the representative case library according to the operation constraints, and determining the target coal blending and combustion case set according to the screening results.

[0105] Step S4: Sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme based on the sorting results.

[0106] Step S5: Control the blending and loading of the coal-fired power generation system according to the optimal blending scheme.

[0107] Specifically, the above steps S701 to S703 describe a specific method for case refinement. Before determining the target coal blending and combustion case set, case refinement is performed on the cases stored in the coal blending and combustion case library.

[0108] First, key parameters for clustering, i.e., preset key parameters, are set, such as one or more combinations of load segment, position of coal mill, number of coal mills, and type of coal used by coal mills. All coal blending and combustion cases in the coal blending and combustion case library are divided into discrete data grids according to parameters such as load segment, position of coal mill, number of coal mills, and type of coal used by coal mills. For example, coal blending and combustion cases belonging to the same load segment range are divided into the same case grid.

[0109] Then, all cases in a single case grid are refined according to a preset clustering algorithm. For example, the most representative one or more representative cases in a single case grid can be determined through graph group detection, and all representative cases are stored to form a representative case library.

[0110] Finally, a method for determining practical coal blending schemes based on a representative case library is developed. After the coal-fired power generation system is started up, the system's operating constraints are monitored in real time. The coal blending cases in the representative case library that meet all operating constraints are combined into a target coal blending case set. The case with the highest score in this target coal blending case set is then selected as the optimal blending scheme. This optimal blending scheme includes data for different coal bunker numbers, coal types, and mill output. By introducing a case refinement mechanism, a more representative case library is formed to guide actual coal blending operations, improve the accuracy and practicality of case matching, and enhance the effectiveness of actual coal blending.

[0111] In one embodiment, after obtaining the representative case library, the data in the representative case library may be updated in real time. The real-time updating of the representative case library data may adopt the method described in steps S101 to S103 above, which will not be described in detail here.

[0112] Based on any of the above embodiments, embodiment five of the present invention further provides a coal blending and combustion control method. On the basis of the control method provided in any of the above embodiments, a specific implementation method for performing blending and upper storage control is exemplified.

[0113] Optionally, Figure 5 This is a flow chart of a coal blending and combustion control method provided in Example 5 of the present invention.

[0114] like Figure 5As shown in FIG, the coal-fired power generation system is controlled by blending and loading according to the optimal blending scheme, including:

[0115] Step S1: establishing a coal blending and combustion case library according to preset stable operating conditions, and determining scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism.

[0116] Step S2: Obtain the operating constraints of the coal-fired power generation system.

[0117] Step S3: screening the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraints, and determining the target coal blending and combustion case set according to the screening results.

[0118] Step S4: Sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme based on the sorting results.

[0119] Step S501: Split the optimal blending solution according to the time sequence, coal bunker number and coal type to obtain multiple bunker information.

[0120] Step S502: splitting the upper warehouse information twice according to the equipment location and the system to which the equipment belongs in the coal-fired power generation system to obtain multiple equipment operation instructions.

[0121] Step S503: Control the operation of equipment in the coal-fired power generation system according to the equipment operation instruction and perform coal blending and combustion.

[0122] Specifically, steps S501 to S503 describe a specific method for implementing coal blending and loading control. After obtaining the optimal blending solution, data from the optimal blending solution is first extracted, and the bunker number, coal type, and coal quantity are determined based on the extracted data. The optimal blending solution is then broken down based on time sequence, bunker number, and coal type, resulting in multiple loading information. For example, the loading information may be for coal type A with a loading quantity of n in bunker number m. After obtaining the loading information, the system breaks the loading information down into equipment operation instructions based on the equipment location and equipment at each site. The equipment operation instructions may include linked reclaiming equipment operation instructions and conveying instructions. The linked reclaiming equipment operation instructions can be used to drive the reclaiming equipment (e.g., a bucket wheel stacker reclaimer) to the storage area of ​​coal type A and begin automatic reclaiming. The conveying instructions can be used to activate multiple coal conveyor belts between the reclaiming equipment and bunker number m, and to drive related material guide equipment to ensure a smooth transportation path for the coal.

[0123] It should be noted that the warehouse information can be directly used in text form to guide operators to control equipment, or it can be directly sent to the relevant control system in the form of instructions to link coal transportation equipment. There is no restriction on this.

[0124] The specific process of the present invention is exemplarily described below with reference to specific examples.

[0125] For example, inherent system constraints are defined as the coal mill being unmaintained, the predicted load segment being full load, the number of available coal types A, B, ..., T stored in the coal yard, and the quantities of different coal types being Xa, Xb, ..., Xt, etc.; manual operational constraints include, but are not limited to, SO2 emissions being less than a preset emission threshold. After the coal-fired power generation system is started, data in a coal blending and combustion case library or a representative case library is updated in real time. Based on the aforementioned operational constraints, cases that meet all constraints are searched from the coal blending and combustion case library or the representative case library, such as Coal Blending and Combustion Case 1, Coal Blending and Combustion Case 2, ..., Coal Blending and Combustion Case Z. All selected cases are sorted by economic efficiency score, and the highest-scoring Coal Blending and Combustion Case Y is output as the optimal blending solution. Data from Coal Blending and Combustion Case Y is extracted, and the coal utilization plan for each coal bunker is calculated based on the extracted data. For example, the extracted data may be: coal bunker number 1, coal type A, coal mill output V1; coal bunker number 2, coal type B, coal mill output V2; coal bunker number 3, coal type C, coal mill output V3; coal bunker number 4, coal types D and E mixed in a 1:1 ratio, coal mill output V4; coal bunker number 5, coal type A, coal mill output V5; coal bunker number 6, coal type C, coal mill output V6. At the same time, the calorific value of each type of coal is read. The calorific value of coal type A is Wa, the calorific value of coal type B is Wb, the calorific value of coal type C is Wc, the calorific value of coal type D is Wd, and the calorific value of coal type E is We.

[0126] Substitute the above data into Formula 1 and calculate the total coal demand Q by weighted average of calorific value:

[0127]

[0128] Where W is the total calorific value of the power plant required according to the total power generation of the predicted load period and the power plant conversion efficiency, V p Provide power for the coal mill in coal bunker No. P.

[0129] Furthermore, the coal consumption of each coal bunker is calculated based on the output ratio of each coal mill.

[0130] For example, the predicted coal consumption of coal type A in coal bunker No. 1

[0131] Therefore, the present invention establishes a coal blending and combustion case library, accumulates actual combustion case data, and provides an economical and feasible coal blending and combustion plan that meets current actual needs based on objective conditions such as the unit, coal storage conditions, and real-time coal prices. It can directly guide the cases of coal loading operations, which is conducive to improving the practicality and accuracy of the blending plan and improving the economy of coal used for power generation.

[0132] Based on any of the above embodiments, embodiment six of the present invention also provides a coal blending and burning control device. The coal blending and burning control device provided by the embodiment of the present invention can execute the coal blending and burning control method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0133] Figure 6 This is a structural schematic diagram of a coal blending and combustion control device provided in Example 6 of the present invention.

[0134] like Figure 6 As shown, the coal blending and combustion control device 00 includes: a case library acquisition unit 101, a constraint condition detection unit 102, a blending scheme acquisition unit 103 and a storage execution unit 104. Among them, the case library acquisition unit 101 is used to establish a coal blending and combustion case library according to preset stable operating conditions, and determine the scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism; the constraint condition detection unit 102 is used to obtain the operating constraints of the coal-fired power generation system; the blending scheme acquisition unit 103 is used to screen the coal blending and combustion cases in the coal blending and combustion case library according to the operating constraints, and determine the target coal blending and combustion case set according to the screening results, and sort the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine the optimal blending scheme according to the sorting results; the storage execution unit 104 is used to perform blending and storage control on the coal-fired power generation system according to the optimal blending scheme.

[0135] Optionally, the case library acquisition unit 101 is provided with an invalid case screening subunit, which is used to obtain the predicted blending and burning results of the optimal blending scheme and the actual blending and burning data after the optimal blending scheme is executed, and determine the predicted average coal quality data based on the actual blending and burning data, and eliminate invalid cases based on the predicted blending and burning results and / or the predicted average coal quality data.

[0136] Optionally, the case library acquisition unit 101 is also used to obtain dynamic parameters associated with a preset coal combustion evaluation mechanism, and obtain variable data of the dynamic parameters based on wireless communication technology, and update the dynamic parameters in the coal blending and combustion case library in real time according to the variable data to obtain a coal blending and combustion case library with updated data.

[0137] Optionally, the case library acquisition unit 101 is also used to discretize all coal blending and combustion cases in the coal blending and combustion case library according to preset key parameters to obtain multiple case grids; perform case refinement on a single case grid based on a preset clustering algorithm to obtain a representative case for each case grid; establish a representative case library based on the representative cases; select the coal blending and combustion cases in the representative case library according to the operating constraints, and determine the target coal blending and combustion case set based on the screening results.

[0138] Optionally, the preset key parameters include: load section, location of coal mill in use, number of coal mills in use and type of coal used by the coal mill.

[0139] Optionally, the upper warehouse execution unit 104 is used to split the optimal blending plan according to the time sequence, coal bunker number and coal type to obtain multiple upper warehouse information; split the upper warehouse information for the second time according to the equipment location in the coal-fired power generation system and the system to which the equipment belongs to obtain multiple equipment operation instructions; control the equipment operation in the coal-fired power generation system according to the equipment operation instructions to execute coal blending and combustion.

[0140] Optionally, a coal blending and combustion case library is established based on preset stable operating conditions, including: obtaining real-time operating parameters and / or historical operating parameters of the coal-fired power generation system; making a stable operating condition judgment on the real-time operating parameters or historical operating parameters based on the preset stable operating conditions, and screening the real-time operating parameters or historical operating parameters based on the judgment results; and establishing a coal blending and combustion case library based on the screening parameters.

[0141] Optionally, the preset coal evaluation mechanism includes at least one of the following: an economic evaluation mechanism, a safety evaluation mechanism, an environmental evaluation mechanism and a rationality evaluation mechanism; wherein the economic evaluation mechanism is used to calculate the economic score based on preset cost parameters; the safety evaluation mechanism is used to calculate the safety score based on preset safe operation parameters; the environmental evaluation mechanism is used to calculate the environmental score based on preset environmental parameters; and the rationality evaluation mechanism is used to calculate the rationality score based on preset reasonable operation parameters.

[0142] Based on any of the above embodiments, embodiment seven of the present invention further provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above coal blending and combustion control method when executing the program.

[0143] Figure 7 A structural diagram of a computer device provided in Example 7 of the present invention. Figure 7 A block diagram of an exemplary computer device 12 suitable for use in implementing embodiments of the present invention is shown. Figure 7 The computer device 12 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0144] like Figure 7 As shown, the computer device 12 is implemented as a general-purpose computing device. Components of the computer device 12 may include, but are not limited to, one or more processors 16, a memory 28, and a bus 18 that connects various system components (including the memory 28 and the processor 16).

[0145] Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. Examples of these architectures include, but are not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MAC) bus, an Enhanced ISA bus, a Video Electronics Standards Association (VESA) local bus, and a Peripheral Component Interconnect (PCI) bus.

[0146] The computer device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the computer device 12, including volatile and non-volatile media, removable and non-removable media.

[0147] The memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. The computer device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, the storage system 34 may be configured to read and write non-removable, non-volatile magnetic media ( Figure 7 Not shown, often called a "hard drive"). Although Figure 7 Not shown, a magnetic disk drive for reading and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of various embodiments of the present invention.

[0148] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. Program modules 42 generally implement the functions and / or methods of the embodiments described herein.

[0149] The device / terminal / server 12 can also communicate with one or more external devices 14 (e.g., a keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the computer device 12, and / or any device that enables the computer device 12 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication can occur via an input / output (I / O) interface 22. Furthermore, the computer device 12 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 20. As shown, the network adapter 20 communicates with the other modules of the computer device 12 via a bus 18. It should be understood that, although not shown, other hardware and / or software modules can be used in conjunction with the computer device 12, including but not limited to microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0150] The processor 16 executes various functional applications and data processing by running the programs stored in the memory 28, such as implementing the coal blending and combustion control method provided in the embodiment of the present invention.

[0151] The eighth embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the above-mentioned coal blending and combustion control method when executed by a processor.

[0152] The coal blending and combustion control method of the embodiment of the present invention sets preset stable operating conditions and a preset coal combustion evaluation mechanism, establishes a coal blending and combustion case library according to the preset stable operating conditions, and determines the scoring parameters of individual cases in the coal blending and combustion case library according to the preset coal combustion evaluation mechanism; obtains the operating constraints during the actual operation of the coal-fired power generation system, screens the coal blending and combustion cases in the coal blending and combustion case library according to the operating constraints, and determines the target coal blending and combustion case set according to the screening results; sorts the individual cases in the target coal blending and combustion case set according to the scoring parameters, and determines the optimal blending scheme according to the sorting results; controls the blending and loading of the coal-fired power generation system according to the optimal blending scheme, thereby solving the problem that the existing coal blending and combustion algorithm has large data deviation and low accuracy, resulting in the inability of the blending calculation to actually guide the coal loading operation, and forms a blending scheme that can guide the loading operation in combination with the actual power generation needs, which is conducive to improving the practicality and accuracy of the blending scheme and improving the economy of coal used for power generation.

[0153] The computer storage medium of the embodiment of the present invention may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or component, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device.

[0154] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0155] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0156] Computer program code for performing the operations of the present invention may be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0157] Note that the above are only preferred embodiments of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments and may include many other equivalent embodiments without departing from the concept of the present invention. The scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for controlling coal blending and combustion, characterized in that: The following steps are involved: A coal blending and combustion case library is established according to preset stable operating conditions, and scoring parameters of individual cases in the coal blending and combustion case library are determined according to a preset coal evaluation mechanism; wherein the preset stable operating conditions include: the load of the coal-fired power generation unit is within a preset load range, the main steam pressure is within a preset pressure range, the main steam flow is within a preset flow range, the type of coal used remains unchanged, the pulverizer output is within a preset output range, and the soot blowing state does not change; Obtaining the operating constraints of the coal-fired power generation system; wherein the operating constraints are inherent operating constraints detected by the system or manual operating constraints set by operators; the inherent operating constraints include the maintenance status of the coal mill, the predicted load segment, the types of coal stored in the coal yard and the amount of coal of different types; the manual operating constraints include SO2 emissions being less than a preset emission threshold; Screening the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraint conditions, and determining a target coal blending and combustion case set according to the screening results; Sorting individual cases in the target coal blending and combustion case set according to the scoring parameters, and determining an optimal blending scheme according to the sorting results; Controlling the coal-fired power generation system by mixing and loading according to the optimal mixing scheme; Obtaining a predicted blending result of the optimal blending scheme; wherein the predicted blending result is a predicted load rate or predicted power generation corresponding to the optimal blending scheme; Acquire actual blending data after the optimal blending scheme is executed, and determine predicted average coal quality data based on the actual blending data; Invalid cases are eliminated based on the predicted blending results and / or the predicted average coal quality data.

2. The coal blending and combustion control method according to claim 1, characterized in that: After obtaining the coal blending and combustion case library, the following steps are also included: Acquiring dynamic parameters associated with the preset coal evaluation mechanism; Obtaining variable data of the dynamic parameter; The dynamic parameters in the coal blending and combustion case library are updated in real time according to the variable data to obtain the coal blending and combustion case library after data update.

3. The coal blending and combustion control method according to claim 1, characterized in that: Before determining the target coal blending case set, the following steps are also included: Discretize all coal blending and combustion cases in the coal blending and combustion case library according to preset key parameters to obtain multiple case grids; Based on a preset clustering algorithm, case extraction is performed on a single case grid to obtain a representative case of each case grid; Establishing a representative case library based on the representative cases; The coal blending and combustion cases in the representative case library are screened according to the operation constraints, and a target coal blending and combustion case set is determined according to the screening results.

4. The coal blending and combustion control method according to claim 1, characterized in that: The coal-fired power generation system is controlled to be blended and loaded into the warehouse according to the optimal blending scheme, including: The optimal blending scheme is split according to the time sequence, coal bunker number and coal type to obtain multiple bunker information; The upper warehouse information is split twice according to the location of the equipment in the coal-fired power generation system and the system to which the equipment belongs, to obtain multiple equipment operation instructions; The operation of equipment in the coal-fired power generation system is controlled according to the equipment operation instruction to perform coal blending and combustion.

5. The coal blending and combustion control method according to claim 1, characterized in that: A coal blending and combustion case library is established based on preset stable operating conditions, including: Acquiring real-time operating parameters and / or historical operating parameters of the coal-fired power generation system; Performing a stable operating condition judgment on the real-time operating parameter or the historical operating parameter according to a preset stable operating condition, and screening the real-time operating parameter or the historical operating parameter according to the judgment result; The coal blending and combustion case library is established according to the screening parameters.

6. The coal blending and combustion control method according to any one of claims 1 to 5, characterized in that: The preset coal evaluation mechanism includes at least one of the following: an economic evaluation mechanism, a safety evaluation mechanism, an environmental evaluation mechanism, and a rationality evaluation mechanism; Wherein, the economic evaluation mechanism is used to calculate the economic score according to the preset cost parameters; The safety evaluation mechanism is used to calculate the safety score based on the preset safety operation parameters; The environmental protection evaluation mechanism is used to calculate the environmental protection score according to the preset environmental protection parameters; The rationality evaluation mechanism is used to calculate the rationality score according to preset reasonable operation parameters.

7. A coal blending and combustion control device, characterized in that: include: A case library acquisition unit is used to establish a coal blending and combustion case library according to preset stable operating conditions, and determine the scoring parameters of individual cases in the coal blending and combustion case library according to a preset coal evaluation mechanism; wherein the preset stable operating conditions include: the load of the coal-fired power generation unit is within a preset load range, the main steam pressure is within a preset pressure range, the main steam flow is within a preset flow range, the type of coal used remains unchanged, the coal mill output is within a preset output range, and the soot blowing state does not change; A constraint condition detection unit, used to obtain the operating constraint conditions of the coal-fired power generation system; wherein the operating constraint conditions are inherent operating constraint conditions detected by the system or manual operating constraint conditions set by operators; the inherent operating constraint conditions include the maintenance status of the coal mill, the predicted load segment conditions, the types of coal stored in the coal yard and the amount of coal of different types, and the manual operating constraint conditions include SO2 emissions being less than a preset emission threshold; a blending scheme acquisition unit, configured to screen the coal blending and combustion cases in the coal blending and combustion case library according to the operation constraint conditions, determine a target coal blending and combustion case set according to the screening results, and sort individual cases in the target coal blending and combustion case set according to the scoring parameters, and determine an optimal blending scheme according to the sorting results; A storage execution unit, used for controlling the blending storage of the coal-fired power generation system according to the optimal blending scheme; The case library acquisition unit includes an invalid case screening subunit; The invalid case screening subunit is used to obtain the predicted blending and combustion result of the optimal blending scheme; wherein the predicted blending and combustion result is the predicted load rate or predicted power generation corresponding to the optimal blending scheme; obtain the actual blending and combustion data after the optimal blending scheme is executed, and determine the predicted average coal quality data based on the actual blending and combustion data; and eliminate invalid cases based on the predicted blending and combustion result and / or the predicted average coal quality data.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the coal blending and combustion control method as described in any one of claims 1-6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the coal blending and combustion control method as described in any one of claims 1 to 6 is implemented.

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