Coal feed and consumption dynamic analysis method based on multi-dimensional perception and related device

Abstract

The invention discloses a multi-dimensional perception-based dynamic analysis method for fuel coal input, consumption and storage and a related device, and belongs to the field of coal-fired power plant management.The method comprises the following steps of: acquiring storage data, furnace input data and inventory data of fuel coal of a thermal power plant, and performing data association in combination with an inventory batch; carrying out inventory structure analysis on the inventory data after data association to obtain the inventory and proportion of the coal types and the weighted average of the inventory index parameters, carrying out visual display, carrying out consumption trend analysis on the warehousing data and the in-furnace data after data association to obtain fire coal consumption trend data, and carrying out visual display; and calculating a storage plan amount according to the fire coal consumption trend data, and adjusting a fire coal purchase amount and the storage plan amount in real time in combination with the inventory amount and the proportion of the coal type and the fire coal quality level value, so as to realize dynamic analysis of fire coal input, consumption and storage. According to the invention, the problem that the fuel coal consumption cannot be accurately and dynamically monitored in the prior art can be solved.

Description

Technical Field

[0001] The present invention belongs to the field of management of coal-fired power plants, and particularly relates to a dynamic analysis method and related devices for coal intake, consumption, and inventory based on multi-dimensional perception. Background Art

[0002] In the field of thermal power generation, the management of coal intake, consumption, and inventory is a core link to ensure production continuity and cost control. However, the traditional management mode has significant limitations: the data collection link relies on manual statistics and decentralized systems, resulting in lagging data acquisition, high error rates, and limited analysis methods that are confined to simple statistics and empirical judgments, making it difficult to achieve in-depth mining and trend prediction.

[0003] With the sharp increase in industry competition pressure, thermal power enterprises have an increasingly urgent need for refined management of coal. The existing management mode often leads to the disconnection of procurement plans from market fluctuations and production demands due to the inability to grasp the coal inventory distribution of multiple power plants in real time, thus triggering supply chain risks; at the same time, the lack of accurate quantitative analysis of coal consumption characteristics makes it difficult to balance cost optimization and environmental protection indicators in the coal blending plan, invisibly pushing up the power generation cost. Therefore, the research and development of an efficient and accurate coal intake, consumption, and inventory perception system to achieve dynamic monitoring, abnormal warning, and decision support for the entire coal process through multi-source data fusion and intelligent analysis technology has become a key technical requirement for improving the management efficiency of thermal power enterprises. Summary of the Invention

[0004] The purpose of the present invention is to provide a dynamic analysis method and related devices for coal intake, consumption, and inventory based on multi-dimensional perception to solve the problem that the existing technology cannot accurately and dynamically monitor coal intake, consumption, and inventory.

[0005] To achieve the above object, the present invention adopts the following technical solutions: In a first aspect, a dynamic analysis method for coal intake, consumption, and inventory based on multi-dimensional perception includes the following steps: Collect the warehousing data, furnace feeding data, and inventory data of coal in a thermal power plant, and perform data association in combination with inventory batches; Conduct an inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters and perform visual display, and conduct a consumption trend analysis on the warehousing data and furnace feeding data after data association to obtain coal consumption trend data and perform visual display; Calculate the planned warehousing quantity according to the coal consumption trend data, and in combination with the inventory quantity and proportion of coal types, as well as the coal quality level value, adjust the coal procurement quantity and the planned warehousing quantity in real time to achieve dynamic analysis of coal intake, consumption, and inventory.

[0006] In some embodiments, the step of performing inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters, specifically includes: Performing weighted averaging on the index parameters of the inventory data for different inventory batches to obtain the weighted average value of the corresponding inventory index parameters. The index parameters of the inventory data include: total coal quantity, calorific value, high-alkali coal quantity, Mar (%), St,ar (%), Vdaf (%), and Ad (%). Calculating the proportion of the coal type structure of the inventory data in real time to obtain the inventory quantity and proportion of the blended coal types and suitable combustion coal types in each coal yard.

[0007] In some embodiments, the blended coal types include: anthracite, high-sulfur lean coal, low-sulfur lean coal, medium-high-sulfur bituminous coal, low-sulfur bituminous coal, and high-alkali metal coal.

[0008] In some embodiments, the consumption trend adopts the simple moving average method, which specifically includes the following steps: Presetting the number of time series data points N of the input quantity in the input furnace data, and each time series data point is arranged in sequence according to the time series. After calculating the average value of the input quantity of the first N time series data points, shifting one time series data point backward and then calculating the average value of the input quantity of N time series data points, and repeating this step until the entire time series is traversed to obtain the coal consumption trend data.

[0009] In some embodiments, it further includes the following step: when the inventory quantity of the coal type is lower than the preset safety inventory threshold, or there is an abnormal consumption in the coal consumption trend data, a warning message is issued.

[0010] In a second aspect, a dynamic analysis system for coal-fired intake, consumption, and inventory based on multi-dimensional perception includes: A coal-fired data acquisition module, configured to collect the incoming coal data, input furnace data, and inventory data of a thermal power plant, and perform data association in combination with inventory batches. A coal-fired associated data analysis and display module, configured to perform inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters and perform visual display, perform consumption trend analysis on the incoming coal data and input furnace data after data association to obtain the coal consumption trend data and perform visual display. An intake, consumption, and inventory dynamic analysis module, configured to calculate the planned incoming coal quantity according to the coal consumption trend data, and in combination with the inventory quantity and proportion of the coal type, as well as the coal quality level value, adjust the coal purchase quantity and the planned incoming coal quantity in real time to achieve dynamic analysis of coal-fired intake, consumption, and inventory.

[0011] In some embodiments, it further includes: An early warning module, configured to issue an early warning message when the inventory of the coal type is lower than a preset safety inventory threshold, or when there is an abnormal consumption in the coal consumption trend data.

[0012] In a third aspect, an electronic device includes a memory, a processor, and a computer program stored in the memory and executable in the processor. When the processor executes the computer program, the steps of the dynamic analysis method for coal combustion input, consumption, and inventory based on multi-dimensional perception are implemented.

[0013] In a fourth aspect, a computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the dynamic analysis method for coal combustion input, consumption, and inventory based on multi-dimensional perception are implemented.

[0014] In a fifth aspect, a computer program product includes a computer program, characterized in that when the computer program is executed by a processor, the steps of the dynamic analysis method for coal combustion input, consumption, and inventory based on multi-dimensional perception are implemented.

[0015] Compared with the prior art, the present invention has the following beneficial effects: The present invention collects the incoming coal data, coal data into the furnace, and inventory data of the coal-fired power plant, and performs data association in combination with the inventory batch. Through multi-dimensional data perception and association, the error rate can be reduced, and the time synchronization can reach the second-level response. In addition, the inventory structure analysis is performed on the inventory data after data association to obtain the inventory quantity and proportion of the coal type, as well as the weighted average value of the inventory index parameters. At the same time, the consumption trend analysis is performed on the incoming coal data and the coal data into the furnace after data association to obtain the coal consumption trend data, and a weighted evaluation system including key coal combustion indicators can be established, providing a basis for the dynamic analysis of coal combustion input, consumption, and inventory in combination with the consumption trend. Finally, the planned incoming coal quantity is calculated according to the coal consumption trend data, and the coal purchase quantity and the planned incoming coal quantity are adjusted in real time in combination with the inventory quantity and proportion of the coal type, as well as the coal quality level value, which can solve the problem that the prior art cannot accurately and dynamically monitor the coal combustion input, consumption, and inventory. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a visualization display diagram of the weighted average value of the inventory index parameters for the inventory structure analysis in this embodiment; Figure 2 It is a visualization display diagram of the inventory quantity and proportion of the coal type for the inventory structure analysis in this embodiment; Figure 3 It is a flowchart of the dynamic analysis method for coal combustion input, consumption, and inventory based on multi-dimensional perception provided in this embodiment; Figure 4 It is a structural diagram of the dynamic analysis system for coal combustion input, consumption, and inventory based on multi-dimensional perception provided in this embodiment. Specific Embodiments

[0017] To enable those skilled in the art to better understand the solution of the present invention, the technical solution of the present invention will be further described in detail below in conjunction with the accompanying drawings. The content described below is an explanation of the present invention rather than a limitation thereof.

[0018] It should be noted that the terms "comprising" and "having" in the description and claims of the present invention and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, systems, products or devices.

[0019] As Figure 3 shown, this embodiment provides a dynamic analysis method for coal consumption, input, and inventory based on multi-dimensional perception, including the following steps: S1. Collect the incoming coal data, coal-in-furnace data, and inventory data of the thermal power plant, and perform data association in combination with the inventory batch. Specifically, the incoming coal data can be associated with the plan, measurement, and coal quality. The incoming coal data includes the following indicators: incoming date, supplier, mine name, mine output, acceptance quantity, net weight, incoming quantity, and inventory batch. The coal-in-furnace data corresponds to the incoming coal data and includes the following indicators: outgoing quantity, unit, belt scale, and inventory batch. The inventory data is updated in real time when the coal is incoming and in the furnace, and then the inventory is adjusted after data inventory. The inventory data includes the following indicators: coal yard, sub-area, inventory batch, real-time coal quantity, and coal quality information.

[0020] S2. Perform inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters and perform visual display. Perform consumption trend analysis on the incoming coal data and coal-in-furnace data after data association to obtain coal consumption trend data and perform visual display. Specifically, perform weighted average on the index parameters of the inventory data of different inventory batches to obtain the corresponding weighted average value of inventory index parameters. The index parameters of the inventory data include: total coal quantity, calorific value, high-alkali coal quantity, Mar(%), St,ar(%), Vdaf(%), and Ad(%). Calculate the proportion of coal type structure of the inventory data in real time to obtain the inventory quantity and proportion of the blended coal types and suitable combustion coal types in each coal yard.

[0021] Mar (%) is the moisture content on as-received basis, representing the percentage of moisture contained in coal in the as-received state (i.e., in its natural state), including inherent moisture (water adsorbed inside coal particles) and extrinsic moisture (water attached to the surface of coal). The moisture content affects the calorific value and combustion efficiency of coal. Excessive moisture will reduce the effective combustible components of coal and increase transportation and storage costs.

[0022] St,ar (%) is the total sulfur on as-received basis, representing the percentage of total sulfur (including organic sulfur and inorganic sulfur) contained in coal in the as-received state. Sulfur is a harmful element in coal, and when burned, it will produce pollutants such as sulfur dioxide, causing harm to the environment. At the same time, the presence of sulfur will also corrode equipment such as boilers.

[0023] Vdaf (%) is the volatile matter on dry ash-free basis, representing the percentage of volatile substances released during the heating process of coal in the dry ash-free state (i.e., after deducting moisture and ash). Volatile matter is the main combustible gas produced during coal combustion, and its content directly affects the combustion performance and calorific value of coal. The higher the volatile matter content, the better the combustion performance of coal, but too high a volatile matter content may also lead to unstable combustion.

[0024] Ad (%) is the ash content on air-dried basis, representing the percentage of ash contained in coal in the air-dried state (i.e., under laboratory conditions, the coal sample is naturally air-dried until it reaches equilibrium with the air humidity). Ash is the non-combustible substance remaining after coal combustion, mainly composed of minerals. Too high an ash content will reduce the calorific value and combustion efficiency of coal, and at the same time increase the ash discharge, putting pressure on the environment.

[0025] Mar (%) and Ad (%) reflect the proportion of effective combustible components in coal, St,ar (%) reflects the impact on the environment after coal combustion, and Vdaf (%) is directly related to the combustion efficiency and economic value of coal.

[0026] Conduct a consumption trend analysis on the warehousing data and furnace data after data correlation. Since the furnace data is relatively stable in the short term, the simple moving average method is adopted. This method is applicable to situations with relatively small data fluctuations. The principle of the simple moving average method: According to time series data, move item by item, and calculate the sequential average value containing a certain number of items in turn to reflect the long-term trend. Therefore, when the values of the time series are affected by periodic fluctuations and random fluctuations and fluctuate greatly, making it difficult to show the development trend of events, using the moving average method can eliminate the influence of these factors, show the development direction and trend of events (i.e., the trend line), and then analyze and predict the long-term trend of the series based on the trend line. The calculation formula for the simple moving average is as follows:

[0027] Among them, is the predicted value for the next period, is the number of time series data points for the moving average, is the actual value of the previous period, is the actual value of the two previous periods, is the actual value of the three previous periods, is the previous period's actual value.

[0028] Therefore, the consumption trend analysis includes the following steps: Preset the number N of time series data points of the input amount in the input furnace data, and each time series data point is arranged in sequence according to the time series; After calculating the average value of the input amount of the first N time series data points, shift one time series data point backward and then calculate the average value of the input amount of N time series data points. Repeat this step until the entire time series is traversed to obtain the coal consumption trend data.

[0029] Table 1 Incoming quantity, input furnace quantity and inventory quantity in the past year

[0030] As shown in Table 1, the incoming quantity, input furnace quantity and inventory quantity data in the past year are collected, and a simple moving average of 3 months (i.e., N is 3 above) is used to analyze the consumption trend, that is, the input furnace quantity data for consecutive 3 months are taken for averaging each time to obtain the average consumption trend during this time period. The calculation process is as follows: Average input furnace quantity from the 1st to the 3rd month (i.e., simple moving average consumption in the 2nd month):

[0031] Average input furnace quantity from the 2nd to the 4th month (i.e., simple moving average consumption in the 3rd month):

[0032] Average input furnace quantity from the 3rd to the 5th month (i.e., simple moving average consumption in the 4th month):

[0033] Until the entire time series is traversed, the coal consumption trend data can be obtained. These data can help the power plant roughly estimate the future coal consumption situation, so as to reasonably arrange the procurement plan, production plan, etc. For example, if it is found that there is a sign of an upward trend in the coal consumption trend, more inventory can be prepared in advance to ensure the smooth progress of production.

[0034] Such as Figure 1 and Figure 2An example of the visualized result is to visually display the weighted average of inventory index parameters, the inventory quantity and proportion of coal types. Other visualized results can be presented in the form of such charts and reports, intuitively showing the situation of coal intake, consumption and inventory, including: planned quantity, coal intake quantity, inventory quantity, expected available days, standard coal unit price, plan fulfillment rate, coal intake situation, coal inventory composition, consumption situation, inventory trend.

[0035] S3. Calculate the planned intake quantity according to the coal consumption trend data, and in combination with the inventory quantity and proportion of the coal type, as well as the coal quality level value, adjust the coal procurement quantity and the planned intake quantity in real time to achieve dynamic analysis of coal intake, consumption and inventory. S4. When the inventory quantity of the coal type is lower than the preset safety inventory threshold, or there is an abnormal consumption in the coal consumption trend data, send a warning message to remind relevant personnel to take measures.

[0036] Based on the above analysis results and warning information, it can provide decision-making support for enterprises, such as adjusting the procurement plan, optimizing the coal blending plan, etc. Specifically, the following indicators can be optimized: coal inventory proportion, comprehensive coal inventory days, overdue coal quantity, upper limit of inventory warning, lower limit of inventory warning.

[0037] Therefore, the dynamic analysis method of coal intake, consumption and inventory provided by this embodiment realizes the real-time collection and dynamic monitoring of coal intake, consumption and inventory data, reduces manual intervention, improves the accuracy and timeliness of data; and can quickly and accurately provide information such as inventory structure and consumption trend, providing a decision-making basis for enterprise managers and optimizing the management process. Through precise inventory management and consumption analysis, it avoids inventory backlog and shortage phenomena, reduces inventory costs, optimizes the coal blending plan, improves the combustion efficiency of coal, reduces energy waste, and reduces power generation costs.

[0038] Such as Figure 4 As shown, this embodiment also provides a dynamic analysis system for coal intake, consumption and inventory based on multi-dimensional perception, including: A coal data collection module, used to collect the intake data, furnace data and inventory data of coal in a thermal power plant, and perform data association in combination with inventory batches. A coal associated data analysis and display module, used to perform inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average of inventory index parameters and perform visual display, and perform consumption trend analysis on the intake data and furnace data after data association to obtain coal consumption trend data and perform visual display. A dynamic analysis module for intake, consumption and inventory, used to calculate the planned intake quantity according to the coal consumption trend data, and in combination with the inventory quantity and proportion of the coal type, as well as the coal quality level value, adjust the coal procurement quantity and the planned intake quantity in real time to achieve dynamic analysis of coal intake, consumption and inventory.

[0039] An early warning module, configured to issue an early warning message when the inventory of the coal type is lower than a preset safety inventory threshold or there is an abnormal consumption in the coal consumption trend data.

[0040] The division of modules in the embodiments of the present invention is illustrative. It is only a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of the present invention, the functional modules can be integrated in one processor, or exist separately physically, or two or more modules can be integrated in one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules.

[0041] In this embodiment, a computer device is further provided. The computer device includes a processor and a memory. The memory is used to store a computer program (in this embodiment, the computer program includes a calculation component and an iteration component, capable of performing model calculation and model update). The computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function. The processor described in the embodiments of the present invention can be used for the operation of a dynamic analysis method for coal input, consumption and inventory based on multi-dimensional perception.

[0042] This embodiment also provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device and is used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and, of course, the extended storage medium supported by the computer device. The computer-readable storage medium provides storage space, and this storage space stores the operating system of the terminal. And, in this storage space, there is also stored one or more instructions suitable for being loaded and executed by the processor. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The one or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of a method for dynamic analysis of coal consumption, input, and inventory based on multi-dimensional perception in the above embodiment.

[0043] This embodiment also provides a computer program product. The computer program product includes a computer program, and when the computer program is executed by the processor, it implements the corresponding steps of a method for dynamic analysis of coal consumption, input, and inventory based on multi-dimensional perception in the above embodiment.

[0044] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0045] The present invention is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one Figure 1 one flow or multiple flows and / or blocks Figure 1 one block or multiple blocks.

[0046] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to work in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction device that implements the functions specified in one or more processes and / or blocks Figure 1 in one or more processes and / or blocks Figure 1 specified in the function.

[0047] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one or more processes and / or blocks Figure 1 in one or more processes and / or blocks Figure 1 specified in the function.

[0048] 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 above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A dynamic analysis method for coal consumption, input, and inventory based on multi-dimensional perception, characterized in that, It includes the following steps: Collect the incoming coal data, in-furnace coal data and inventory data of the coal-fired power plant, and perform data association in combination with the inventory batch; Conduct an inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters, and perform visual display. Conduct a consumption trend analysis on the incoming coal data and in-furnace coal data after data association to obtain the coal consumption trend data and perform visual display; Calculate the planned incoming quantity according to the coal consumption trend data, and in combination with the inventory quantity and proportion of the coal types, as well as the coal quality level value, adjust the coal purchase quantity and the planned incoming quantity in real time to achieve dynamic analysis of coal incoming, consumption and inventory.

2. The dynamic analysis method for coal combustion input, consumption and inventory based on multi-dimensional perception according to claim 1, wherein The step of conducting an inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters specifically includes: Perform weighted averaging on the index parameters of the inventory data of different inventory batches to obtain the corresponding weighted average value of inventory index parameters. The index parameters of the inventory data include: total coal quantity, calorific value, high-alkali coal quantity, Mar(%), St,ar(%), Vdaf(%) and Ad(%); 3. The dynamic analysis method for coal combustion input, consumption and inventory based on multi-dimensional perception according to claim 2, characterized in that Calculate the proportion of the coal type structure of the inventory data in real time to obtain the inventory quantity and proportion of the blended coal types and suitable combustion coal types in each coal yard.

4. A dynamic analysis method for coal consumption, input, and inventory based on multi-dimensional perception according to claim 1, characterized in that The blended coal types include: anthracite, high-sulfur lean coal, low-sulfur lean coal, medium-high-sulfur bituminous coal, low-sulfur bituminous coal and high-alkali metal coal. The consumption trend adopts the simple moving average method, which specifically includes the following steps: Preset the number of time series data points N of the in-furnace quantity in the in-furnace coal data, and each time series data point is arranged in sequence according to the time series; 5. A dynamic analysis method for coal consumption, input, and inventory based on multi-dimensional perception according to claim 1, characterized in that, After calculating the average value of the in-furnace quantity of the first N time series data points, shift one time series data point backward and then calculate the average value of the in-furnace quantity of N time series data points. Repeat this step until the entire time series is traversed to obtain the coal consumption trend data. It also includes the following steps:

6. A dynamic analysis system for coal consumption, input, and inventory based on multi-dimensional perception, characterized in that When the inventory quantity of the coal type is lower than the preset safety inventory threshold, or there is an abnormal consumption in the coal consumption trend data, an early warning message is sent. It includes: A coal data collection module, which is used to collect the incoming coal data, in-furnace coal data and inventory data of the coal-fired power plant, and perform data association in combination with the inventory batch; A coal association data analysis and display module, which is used to conduct an inventory structure analysis on the inventory data after data association to obtain the inventory quantity and proportion of coal types, as well as the weighted average value of inventory index parameters, and perform visual display. Conduct a consumption trend analysis on the incoming coal data and in-furnace coal data after data association to obtain the coal consumption trend data and perform visual display; 7. A dynamic analysis system for coal consumption, input, and inventory based on multi-dimensional perception according to claim 6, characterized in that A dynamic analysis module for incoming, consumption and inventory, which is used to calculate the planned incoming quantity according to the coal consumption trend data, and in combination with the inventory quantity and proportion of the coal types, as well as the coal quality level value, adjust the coal purchase quantity and the planned incoming quantity in real time to achieve dynamic analysis of coal incoming, consumption and inventory. It also includes: An early warning module, which is used to send an early warning message when the inventory quantity of the coal type is lower than the preset safety inventory threshold, or there is an abnormal consumption in the coal consumption trend data.

8. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable in the processor. When the processor executes the computer program, it implements the steps of the method for dynamic analysis of coal intake, consumption, and inventory based on multi-dimensional perception according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, it implements the steps of the method for dynamic analysis of coal intake, consumption, and inventory based on multi-dimensional perception according to any one of claims 1 to 6.

10. A computer program product, the computer program product comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method for dynamic analysis of coal intake, consumption, and inventory based on multi-dimensional perception according to any one of claims 1 to 6.

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