Coal yard blending data analysis method and system

Abstract

The application discloses a coal yard blending combustion data analysis method and system, relates to the technical field of coal yard data analysis, and comprises the following steps: acquiring multiple parameters; acquiring combustion records satisfying preset constraint conditions in the historical combustion data as optimal combustion records, sorting combustion characteristics of the optimal combustion records, and obtaining target coal quality; if a difference between the target coal quality and a design value is within a preset reasonable interval, acquiring multiple combinations of the target coal quality components according to a coal quality range of coal stored in the coal yard, formulating a warehouse loading scheme based on an optimization principle and the multiple combinations; after combustion, comparing coal combustion effects in a previous preset time period with a current target coal quality combustion effect, optimizing the warehouse loading scheme according to a comparison result, and establishing multiple evaluation systems to evaluate the combustion condition. The application meets the actual demand of the coal yard. According to the optimization principle, the combination is selected, so that the blending accuracy is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal yard data analysis, and more particularly to a coal yard blending data analysis method and system. BACKGROUND

[0002] Blending technology is a process in which several different kinds of coal with different properties are mixed according to a certain proportion to generate electricity. The basic principle is to use the composition of different coal types to mix according to requirements, so that the final mixed coal meets or approaches the design requirements of the boiler, so as to achieve high boiler efficiency, sufficient output, and good environmental performance. Intermittent blending, also known as periodic blending, is generally used in power plants where coal supply is difficult or the coal yard is small and not suitable for storage. If a single coal type is burned for a period of time and there is a heavy slagging problem, another coal type or a mixture of other coals can be used for a period of time, and then the single coal burning can be switched back after the slagging problem is alleviated. The coal feeding is generally controlled according to the slagging condition in the furnace.

[0003] Pre-mixing blending before the furnace can be pre-mixed when the coal is stacked in the coal yard or by different belts feeding into the same coal hopper. It can also be pre-mixed at the coal terminal. This coal blending method is not easy to implement in power plants with small coal yards. In addition, for the method of feeding different belts into the same coal hopper, the proportion of mixed coal is not easy to control accurately (a metering device should be provided on each coal feeding belt). However, for large group companies with railway transportation and sea transportation capabilities, two types of coal that need to be blended (such as Shenhua Jurassic coal and Carboniferous coal) can be concentrated at the railway transfer station or the coal terminal, and then blended in appropriate proportions according to the anti-sludging capacity of the boiler to be supplied to the power plant. The mixed coal can be directly used by the boiler of the power plant, reducing the number of intermediate links and improving the use proportion and efficiency of the blended coal.

[0004] The traditional management mode makes it extremely complex to control the stacking, feeding and blending proportion of different coals. It is difficult to adjust the blending proportion to keep up with the change of boiler load, and the coal stacking period is long, the mixed stacking pressure is high, and the loss is large. Simple blending relying on experience cannot guarantee the accuracy of the blending proportion, which affects the stable and economic operation of the boiler.

[0005] Therefore, how to improve the accuracy of blending is a technical problem to be solved at present. SUMMARY

[0006] The present application provides a coal yard blending data analysis method to solve the technical problem of low blending accuracy in the prior art. The method comprises:

[0007] Obtaining multiple parameters, including load parameter conditions, coal quality range of coal storage in the coal yard, and historical combustion data;

[0008] acquire a combustion record meeting a preset constraint condition in the historical combustion data as an optimal combustion record, rank combustion characteristics of the optimal combustion record, and obtain a target coal quality;

[0009] If a difference between the target coal quality and a design value is within a preset reasonable interval, acquire multiple combinations of components of the target coal quality according to a coal quality range of the coal yard, and formulate a warehouse loading scheme based on a selection principle and the multiple combinations;

[0010] After combustion, compare a coal combustion effect in a preset time period last time with a target coal combustion effect, optimize the warehouse loading scheme according to a comparison result, and establish multiple evaluation systems to evaluate the combustion.

[0011] In some embodiments of the present application, after establishing the multiple evaluation systems to evaluate the combustion, the method further includes:

[0012] predict a load parameter situation of a next procurement cycle, a coal quality range of the coal yard, combustion data, and a price of the coal quality, and formulate a next procurement strategy according to the load parameter situation, the coal quality range of the coal yard, the combustion data, and the price of the coal quality.

[0013] In some embodiments of the present application, before acquiring the multiple parameters, the method further includes:

[0014] acquire historical data of the multiple parameters, remove non-steady-state data from the historical data to obtain steady-state data, perform noise reduction processing on the steady-state data to obtain first data, sequentially perform data cleaning of an over-limit and an environmental protection index on the first data to obtain second data, and acquire the multiple parameters according to the second data.

[0015] In some embodiments of the present application, the combustion characteristics of the optimal combustion record are ranked, and the target coal quality is obtained, specifically as follows:

[0016] The coal quality of the optimal combustion record ranked first in the combustion characteristics is taken as the target coal quality.

[0017] In some embodiments of the present application, after taking the coal quality of the optimal combustion record ranked first in the combustion characteristics as the target coal quality, the method further includes:

[0018] If a difference between the coal quality of the optimal combustion record ranked first in the combustion characteristics and the design value exceeds a preset reasonable interval, the ranking of the combustion characteristics is sequentially extended until the difference between the coal quality and the design value is within the preset reasonable interval.

[0019] In some embodiments of the present application, the warehouse loading scheme is formulated based on the selection principle and the multiple combinations, specifically as follows:

[0020] The selection principle includes a cost principle, an environmental protection principle, an ash principle and a combustion principle.

[0021] According to one or more of the cost principle, the environmental protection principle, the ash principle and the combustion principle, a combination of target coal quality components is selected as a preferred combination, and a warehouse planning scheme is formulated according to the preferred combination, the warehouse planning scheme including a coal type ratio.

[0022] In some embodiments of the present application, after the preferred combination is selected, the method further includes:

[0023] According to the load parameter condition, the coal type ratio of the preferred combination is adjusted.

[0024] In some embodiments of the present application, the combustion effect of the coal material in the last preset time period is compared with the combustion effect of the current target coal quality, and the warehouse planning scheme is optimized according to the comparison result, specifically:

[0025] The combustion effect of the coal material in the last preset time period is recorded as a first effect, and the combustion effect of the current target coal quality is recorded as a second effect.

[0026] If the first effect is better than the second effect, the warehouse planning scheme is adjusted according to the combustion condition of the coal material in the last preset time period.

[0027] If the second effect is better than the first effect, the warehouse planning scheme is not optimized.

[0028] In some embodiments of the present application, a plurality of evaluation systems are established to evaluate the combustion condition, specifically:

[0029] For the combustion condition, a comprehensive evaluation, an efficiency evaluation, a parameter evaluation, an emission evaluation and a dust evaluation are established.

[0030] Correspondingly, the present application also provides a coal yard blending combustion data analysis system, which includes:

[0031] An acquisition module is configured to acquire a plurality of parameters, including a load parameter condition, a coal quality range of stored coal in a coal yard and historical combustion data.

[0032] A determination module is configured to acquire, from the historical combustion data, a combustion record satisfying a preset constraint condition as an optimal combustion record, sort combustion characteristics of the optimal combustion record, and obtain a target coal quality.

[0033] A formulation module is configured to, if a difference between the target coal quality and a design value is within a preset reasonable interval, acquire a plurality of combinations of the target coal quality components according to the coal quality range of the stored coal in the coal yard, and formulate a warehouse planning scheme based on a selection principle and the plurality of combinations.

[0034] An optimization module is configured to compare the coal combustion effect in the last preset time period with the current target coal quality combustion effect after combustion, optimize the coal storage scheme according to the comparison result, and establish multiple evaluation systems to evaluate the combustion condition.

[0035] By applying the above technical solution, multiple parameters are obtained, including load parameter conditions, coal quality ranges of stored coal in the coal yard, and historical combustion data; combustion records meeting preset constraint conditions are obtained from the historical combustion data as optimal combustion records, the combustion characteristics of the optimal combustion records are sorted, and a target coal quality is obtained; if the difference between the target coal quality and a design value is within a preset reasonable interval, multiple combinations of components of the target coal quality are obtained according to the coal quality ranges of the stored coal in the coal yard, and a coal storage scheme is formulated based on a selection principle and the multiple combinations; after combustion, the coal combustion effect in the last preset time period is compared with the current target coal quality combustion effect, the target coal quality is optimized according to the comparison result, and multiple evaluation systems are established to evaluate the combustion condition. The present application processes data such as noise reduction and cleaning to ensure the accuracy of obtaining multiple parameters and reduce redundant and useless data. By obtaining the target coal quality and multiple combinations, a coal storage scheme with strong adaptability is formulated, which meets the actual needs of the coal yard. According to the selection principle, the combination is selected, so that the accuracy of blending is improved. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0037] Figure 1 A flowchart of a coal yard blending data analysis method according to an embodiment of the present application is shown;

[0038] Figure 2 A structure diagram of a coal yard blending data analysis system according to an embodiment of the present application is shown;

[0039] Figure 3 A schematic diagram of the flow of the present application scheme is shown. DETAILED DESCRIPTION

[0040] The technical solutions in the embodiments of the present application will be described clearly and completely in the following with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0041] The embodiment of the present application provides a coal yard blending data analysis method, as shown in the figure, the method comprises the following steps: Figure 1

[0042] In step S101, multiple parameters are acquired, wherein the multiple parameters comprise load parameter conditions, a coal quality range of stored coal in the coal yard and historical combustion data.

[0043] In the embodiment, the multiple parameters comprise but are not limited to load parameter conditions, a coal quality range of stored coal in the coal yard and historical combustion data, the load parameter conditions comprise real-time load parameters and load change conditions in a period of time, and the historical combustion data is past combustion data of coal.

[0044] In order to improve the accuracy of acquiring the multiple parameters, in some embodiments of the present application, before the multiple parameters are acquired, the method further comprises the following steps: acquiring historical data of the multiple parameters, removing non-steady-state data from the historical data to obtain steady-state data, performing noise reduction processing on the steady-state data to obtain first data, sequentially performing data cleaning of over-limit and environmental protection indexes on the first data to obtain second data, and acquiring the multiple parameters according to the second data.

[0045] In the embodiment, a clustering analysis algorithm is used to divide intervals of unit condition parameters of a thermal power plant to form operation conditions corresponding to the condition parameters, and the condition parameters mainly comprise load of the unit, a coal quality interval, an environmental temperature, equipment technical improvement and time, etc. Historical data of the unit of the thermal power plant under the above production conditions is acquired, non-steady-state data of the obtained historical data is removed to obtain steady-state data. The obtained steady-state data is subjected to noise reduction processing to improve the quality of the steady-state data. The specific noise reduction means will not be described here again and is a conventional technology in the field. The steady-state data (first data) after noise reduction is sequentially subjected to data cleaning of over-limit and environmental protection indexes to obtain second data. The over-limit comprises temperature over-limit, current over-limit, voltage over-limit and moisture over-limit, etc.

[0046] In step S102, combustion records meeting preset constraint conditions are acquired from the historical combustion data as optimal combustion records, combustion characteristics of the optimal combustion records are sorted, and target coal quality is obtained.

[0047] In the embodiment, the combustion characteristics are sorted, and the earlier the ranking is, the better the combustion effect is. The target coal quality is suitable coal quality required by the coal yard in the period of time.

[0048] ​In order to improve the accuracy of blending, in some embodiments of the present application, the combustion characteristics of the optimal combustion records are ranked, and the target coal quality is obtained, specifically: the coal quality of the optimal combustion record with the first ranked combustion characteristics is taken as the target coal quality. In some embodiments of the present application, after the coal quality of the optimal combustion record with the first ranked combustion characteristics is taken as the target coal quality, the method further comprises: if the difference between the coal quality of the optimal combustion record with the first ranked combustion characteristics and the design value exceeds the preset reasonable interval, the ranking of the combustion characteristics is sequentially extended until the difference between the coal quality and the design value is within the preset reasonable interval.

[0049] In this embodiment, in general, the coal quality of the optimal combustion record with the first ranked combustion characteristics is taken as the target coal quality, if the coal quality cannot meet the design value, the second ranked coal quality is selected as the target coal quality, and if it still cannot meet the design value, the ranking is sequentially extended until the coal quality meets the design value. Because different coal species are blended, the blended coal quality tends to the design value (specified value).

[0050] In step S103, if the difference between the target coal quality and the design value is within the preset reasonable interval, a plurality of combinations of the target coal quality components are obtained according to the coal quality range of the coal stored in the coal yard, and a warehouse loading scheme is formulated based on the optimization principle and the plurality of combinations.

[0051] In this embodiment, after the target coal quality is selected, a plurality of combinations of the target coal quality components are obtained according to the coal quality range of the coal stored in the existing coal yard, a suitable combination is selected according to different optimization principles, and a warehouse loading scheme is formulated according to the combination.

[0052] In order to improve the reliability of blending, in some embodiments of the present application, a warehouse loading scheme is formulated based on the optimization principle and the plurality of combinations, specifically: the optimization principle includes cost principle, environmental protection principle, ash content principle and combustion principle; one combination of the target coal quality components is selected as an optimal combination according to one or more of the cost principle, the environmental protection principle, the ash content principle and the combustion principle, and a warehouse loading scheme is formulated according to the optimal combination, the warehouse loading scheme including coal species ratio.

[0053] In this embodiment, the optimization principle includes but is not limited to cost principle, environmental protection principle, ash content principle and combustion principle, the cost principle is mainly selected based on economic cost, the environmental protection principle is mainly selected based on the pollution degree of exhaust gas or substance, the ash content principle is mainly selected based on the amount of dust or ash discharged, and the combustion principle is mainly selected based on the combustion effect. One combination of the target coal quality components is selected according to one or more of the above principles. A warehouse loading scheme is formulated according to the combination, and the warehouse loading scheme includes power generation capacity, coal consumption, coal species ratio, etc.

[0054] In order to improve the reliability of the coal charging scheme, in some embodiments of the present application, after the preferred combination is selected, the method further comprises adjusting the coal type ratio of the preferred combination according to the load parameter condition.

[0055] In this embodiment, when multiple coal types are mixed, the mixture needs to be adjusted according to the change of the boiler load. The total moisture, volatile matter, sulfur content and the like are ensured to meet the requirements of boiler combustion.

[0056] In step S104, after combustion, the coal combustion effect in the last preset time period is compared with the current target coal combustion effect, and the coal charging scheme is optimized according to the comparison result, and multiple evaluation systems are established to evaluate the combustion condition.

[0057] In order to improve the reliability of the coal charging scheme, in some embodiments of the present application, the coal combustion effect in the last preset time period is compared with the current target coal combustion effect, and the coal charging scheme is optimized according to the comparison result, specifically: the coal combustion effect in the last preset time period is recorded as the first effect, and the current target coal combustion effect is recorded as the second effect; if the first effect is better than the second effect, the coal charging scheme is adjusted according to the coal combustion condition in the last preset time period; if the second effect is better than the first effect, the coal charging scheme is not optimized.

[0058] In this embodiment, the current target coal combustion condition is compared with the previous combustion condition, and if the previous combustion condition is better than the current one, the coal charging scheme is adjusted according to the coal combustion condition in the last preset time period. If the previous combustion condition is not better than the current one, the coal charging scheme is not optimized.

[0059] In some embodiments of the present application, multiple evaluation systems are established to evaluate the combustion condition, specifically:

[0060] For the combustion condition, a comprehensive evaluation, efficiency evaluation, parameter evaluation, emission evaluation and dust evaluation are established.

[0061] In this embodiment, the specific evaluation system can be adjusted or changed according to actual needs.

[0062] In order to improve the reliability of the blending, in some embodiments of the present application, after the multiple evaluation systems are established to evaluate the combustion condition, the method further comprises: predicting the load parameter condition, the coal quality range of the coal yard stored coal, the combustion data and the price of the coal type and quality in the next procurement cycle, and formulating the next round of procurement strategy according to the load parameter condition, the coal quality range of the coal yard stored coal, the combustion data and the price of the coal type and quality.

[0063] In this embodiment, according to the predicted load parameter condition, the coal quality range of the coal yard stored coal, the combustion data and the price of the coal type and quality in the next procurement cycle, the optimal solution is sought to obtain the next round of procurement strategy.

[0064] By applying the above technical solutions, multiple parameters are obtained, including load parameter conditions, a coal quality range of stored coal in the coal yard, and historical combustion data; a combustion record meeting a preset constraint condition is obtained from the historical combustion data as an optimal combustion record, the combustion characteristics of the optimal combustion record are sorted, and a target coal quality is obtained; if a difference between the target coal quality and a design value is within a preset reasonable interval, multiple combinations of components of the target coal quality are obtained from the coal quality range of the stored coal in the coal yard, and an upper storage scheme is formulated based on a selection principle and the multiple combinations; after combustion, the combustion effect of coal in a previous preset time period is compared with the combustion effect of the current target coal quality, the target coal quality is optimized according to a comparison result, and multiple evaluation systems are established to evaluate the combustion condition. The present application processes data such as noise reduction and cleaning to ensure the accuracy of obtaining multiple parameters and reduce redundant and useless data. By obtaining the target coal quality and multiple combinations, an upper storage scheme with strong adaptability is formulated, which meets the actual needs of the coal yard. According to the selection principle, the combination is selected, so that the accuracy of blending is improved.

[0065] Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by hardware, or by means of software and a necessary general hardware platform. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a U disk, a mobile hard disk, etc.), and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present application.

[0066] In order to further illustrate the technical idea of the present application, the technical solutions of the present application will be described in combination with specific application scenarios.

[0067] The present application also provides a coal yard blending data analysis system, as shown in Figure 2 The system comprises:

[0068] The obtaining module 201 is configured to obtain multiple parameters, including load parameter conditions, a coal quality range of stored coal in the coal yard, and historical combustion data;

[0069] The determining module 202 is configured to obtain a combustion record meeting a preset constraint condition from the historical combustion data as an optimal combustion record, sort the combustion characteristics of the optimal combustion record, and obtain a target coal quality;

[0070] The establishing module 203 is configured to, if the difference between the target coal quality and the design value is within a preset reasonable interval, acquire a plurality of combinations of the target coal quality composition according to the coal quality range of the coal stored in the coal yard, and establish a coal storage scheme based on a selection principle and the plurality of combinations.

[0071] The optimization module 204 is configured to, after combustion, compare the coal combustion effect in a last preset time period with the target coal combustion effect, optimize the coal storage scheme according to a comparison result, and establish a plurality of evaluation systems to evaluate the combustion situation.

[0072] In addition, the system further comprises:

[0073] In some embodiments of the present application, the system further comprises a first module configured to:

[0074] The load parameter situation of the next procurement cycle, the coal quality range of the coal stored in the coal yard, the combustion data and the price of the coal quality are predicted, and a next round of procurement strategy is established according to the load parameter situation, the coal quality range of the coal stored in the coal yard, the combustion data and the price of the coal quality.

[0075] In some embodiments of the present application, the system further comprises a second module configured to:

[0076] The historical data of the plurality of parameters are acquired, and non-steady-state data of the historical data are removed to obtain steady-state data, the steady-state data are subjected to noise reduction processing to obtain first data, the first data are subjected to data cleaning of over-limit and environmental protection indicators in sequence to obtain second data, and the plurality of parameters are acquired according to the second data.

[0077] In some embodiments of the present application, the establishing module 203 is specifically configured to:

[0078] The coal quality of the optimal combustion record ranked first in the combustion characteristics is taken as the target coal quality.

[0079] In some embodiments of the present application, the system further comprises a third module configured to:

[0080] If the difference between the coal quality of the optimal combustion record ranked first in the combustion characteristics and the design value exceeds a preset reasonable interval, the order of the combustion characteristics is sequentially extended until the difference between the coal quality and the design value is within the preset reasonable interval.

[0081] In some embodiments of the present application, the establishing module 203 is specifically configured to:

[0082] The selection principle includes a cost principle, an environmental protection principle, an ash content principle and a combustion principle;

[0083] According to one or more of the cost principle, the environmental protection principle, the ash principle and the combustion principle, a combination of target coal quality components is selected as a preferred combination, and a storage scheme is formulated according to the preferred combination, the storage scheme including a coal type ratio.

[0084] In some embodiments of the present application, the system further includes a fourth module configured to:

[0085] According to the load parameter condition, the coal type ratio of the preferred combination is adjusted.

[0086] In some embodiments of the present application, the optimization module 204 is specifically configured to:

[0087] The coal combustion effect in the last preset time period is recorded as a first effect, and the combustion effect of the current target coal quality is recorded as a second effect.

[0088] If the first effect is better than the second effect, the storage scheme is adjusted according to the coal combustion condition in the last preset time period.

[0089] If the second effect is better than the first effect, the storage scheme is not optimized.

[0090] In some embodiments of the present application, the optimization module 204 is specifically configured to:

[0091] For the combustion condition, a comprehensive evaluation, an efficiency evaluation, a parameter evaluation, an emission evaluation and a dust evaluation are established.

[0092] Those skilled in the art can understand that the modules in the system in the implementation scenario can be distributed in the system in the implementation scenario according to the description of the implementation scenario, or can be changed and located in one or more systems different from the implementation scenario. The modules in the above implementation scenario can be combined into one module, or can be further split into multiple sub-modules.

[0093] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not drive the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A coal yard blending data analysis method, characterized in that, The method comprises: acquiring multi-parameters, wherein the multi-parameters comprise load parameter conditions, a coal quality range of stored coal in a coal yard, and historical combustion data; acquiring historical data of the multi-parameters, removing non-steady-state data from the historical data to obtain steady-state data, performing noise reduction processing on the steady-state data to obtain first data, sequentially performing data cleaning of the first data according to an over-limit and environmental protection index to obtain second data, and acquiring multi-parameters according to the second data; acquiring, from the historical combustion data, combustion records that meet preset constraint conditions as optimal combustion records, sorting combustion characteristics of the optimal combustion records, and obtaining a target coal quality; the target coal quality is a coal quality of an optimal combustion record with a combustion characteristic ranked first; if a difference between the target coal quality and a design value is within a preset reasonable interval, acquiring a plurality of combinations of target coal quality components according to the coal quality range of stored coal in the coal yard, selecting one combination of target coal quality components according to one or more of a cost principle, an environmental protection principle, an ash content principle, and a combustion principle, formulating a coal yard loading scheme according to the one combination of target coal quality components, and the coal yard loading scheme comprises formulating a coal yard loading scheme according to a coal type ratio; if a difference between the coal quality of the optimal combustion record with the combustion characteristic ranked first and the design value exceeds the preset reasonable interval, sequentially extending in order according to the sorting of the combustion characteristics until the difference between the coal quality and the design value is within the preset reasonable interval; after combustion, comparing a coal combustion effect in a last preset time period with a current target coal combustion effect, optimizing the coal yard loading scheme according to a comparison result, and establishing a plurality of evaluation systems to evaluate the combustion situation; predicting load parameter conditions, a coal quality range of stored coal in a coal yard, combustion data, and a coal type coal quality price of a next procurement cycle, and formulating a next round of procurement strategy according to the load parameter conditions, the coal quality range of stored coal in the coal yard, the combustion data, and the coal type coal quality price.

2. The method of claim 1, wherein, After one combination of target coal quality components is selected, the method further comprises: adjusting a coal type ratio of the determined one combination of target coal quality components according to the load parameter conditions.

3. The method of claim 1, wherein, comparing a coal combustion effect in a last preset time period with a current target coal combustion effect, optimizing the coal yard loading scheme according to a comparison result, and establishing a plurality of evaluation systems to evaluate the combustion situation; if the first effect is better than the second effect, adjusting the coal yard loading scheme according to the coal combustion situation in the last preset time period; if the second effect is better than the first effect, not optimizing the coal yard loading scheme.

4. The method of claim 1, wherein, establishing a plurality of evaluation systems to evaluate the combustion situation, and the plurality of evaluation systems comprise: a comprehensive evaluation, an efficiency evaluation, a parameter evaluation, an emission evaluation, and a dust evaluation.

5. A coal yard blending data analysis system, characterized in that, The system comprises: an acquisition module configured to acquire multi-parameters, wherein the multi-parameters comprise load parameter conditions, a coal quality range of stored coal in a coal yard, and historical combustion data; Obtaining the historical data of the multi-element parameter, and removing non-steady-state data from the historical data to obtain steady-state data, and performing noise reduction processing on the steady-state data to obtain first data, sequentially performing data cleaning of the first data according to the super limit and environmental protection indicators to obtain second data, and obtaining the multi-element parameter according to the second data; A determination module is configured to obtain, from the historical combustion data, a combustion record satisfying a preset constraint condition as an optimal combustion record, sort combustion characteristics of the optimal combustion record, and obtain a target coal quality; The target coal quality is the coal quality of the optimal combustion record ranked first in the combustion characteristics; A preparation module is configured to, if a difference between the target coal quality and a design value is within a preset reasonable interval, obtain a plurality of combinations of components of the target coal quality according to a coal quality range of the coal stored in the coal yard, select one combination of components of the target coal quality according to one or more of a cost principle, an environmental protection principle, an ash content principle and a combustion principle, and prepare a coal yard loading scheme according to the one combination of components of the target coal quality, the coal yard loading scheme including preparation of a coal type ratio; If the difference between the coal quality of the optimal combustion record ranked first in the combustion characteristics and the design value exceeds the preset reasonable interval, the ranking is sequentially extended until the difference between the coal quality and the design value is within the preset reasonable interval; An optimization module is configured to, after combustion, compare a coal combustion effect in a last preset time period with a current target coal combustion effect, optimize the coal yard loading scheme according to a comparison result, and establish a plurality of evaluation systems to evaluate the combustion situation; Predicting a load parameter situation of a next procurement cycle, a coal quality range of the coal stored in the coal yard, combustion data and a price of the coal type and coal quality, and preparing a next round of procurement strategy according to the load parameter situation, the coal quality range of the coal stored in the coal yard, the combustion data and the price of the coal type and coal quality.

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