Energy-saving and carbon-reducing evaluation method and system for pulverized coal fired boiler

Abstract

The invention relates to the technical field of pulverized coal boilers, and particularly discloses an energy-saving and carbon-reducing evaluation method and system for a pulverized coal boiler, and the method comprises the steps: obtaining the historical operation data of the pulverized coal boiler, building a first evaluation index according to the historical operation data of the pulverized coal boiler, and building a second evaluation index according to the change condition of the historical operation data of the pulverized coal boiler; determining an evaluation weight corresponding to each evaluation index according to a first evaluation index and a second evaluation index of the historical operation data, and constructing a target evaluation function according to the first evaluation index, the second evaluation index and the evaluation weights; and establishing an energy-saving and carbon-reducing evaluation model according to the target evaluation function, and determining an energy-saving and carbon-reducing evaluation grade of the pulverized coal boiler operation data to be evaluated according to the energy-saving and carbon-reducing evaluation model. According to the method, the energy-saving and carbon-reducing indexes of the boiler are accurately evaluated according to the operation data of the pulverized coal boiler, and analysis, diagnosis, optimization and improvement work of the pulverized coal boiler of a power plant can be effectively guided.

Description

Technical Field

[0001] The present application relates to the technical field of pulverized coal boilers, and more specifically, to an energy-saving and carbon-reducing evaluation method and system for pulverized coal boilers. Background Art

[0002] At present, the characteristics of energy resources are rich in coal, short of oil, and scarce in gas. This means that coal will be the dominant part of the energy structure in the current and quite a long time to come. However, coal-fired industrial boilers have the disadvantages of serious pollution and low energy efficiency. Air pollution control is an important task and a task that must be completed. The flue gas discharged from boilers is an important part of air pollution. Therefore, the requirements for boiler emissions are gradually becoming stricter, and the flue gas emission indexes are getting lower and lower. Now, in some places where conditions permit, the project of converting coal-fired to gas-fired is being implemented. However, due to the high price of gas and the limited gas sources, most places still mainly use coal, and the clean combustion transformation of coal has become the main means to solve ultra-low emissions. Pulverized coal boilers use pulverized coal with a fineness of less than 200 meshes. The pulverized coal burns suspended in the furnace, increasing the contact area with air, having a fast combustion speed and high combustion efficiency. In the prior art, the energy-saving and carbon-reducing evaluation of pulverized coal boilers is only limited to simply showing each index value in isolation, lacking a comprehensive consideration of the energy-saving and carbon-reducing indexes of pulverized coal boilers. Summary of the Invention

[0003] The present invention provides an energy-saving and carbon-reducing evaluation method and system for pulverized coal boilers to solve the problem of single evaluation dimension of energy-saving and carbon-reducing evaluation of pulverized coal boilers in the prior art, including: Obtain the historical operation data of the pulverized coal boiler, establish a first evaluation index according to the historical operation data of the pulverized coal boiler, and establish a second evaluation index according to the change situation of the historical operation data of the pulverized coal boiler; Determine the evaluation weight corresponding to each evaluation index according to the first evaluation index and the second evaluation index of the historical operation data, and construct a target evaluation function according to the first evaluation index, the second evaluation index and the evaluation weight; Establish an energy-saving and carbon-reducing evaluation model according to the target evaluation function, and determine the energy-saving and carbon-reducing evaluation grade of the operation data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-reducing evaluation model.

[0004] Further, the establishing the first evaluation index according to the historical operation data of the pulverized coal boiler includes: Determine the boiler thermal efficiency index, the exhaust gas temperature index and the carbon content in fly ash index of the pulverized coal boiler according to the historical operation data of the pulverized coal boiler, perform normalization processing on the historical operation data of the pulverized coal boiler to obtain the normalized historical operation data of the pulverized coal boiler; Establish a center point, and evenly draw rays around the center point to establish an index axis, and fill the normalized historical operation data of each pulverized coal boiler into the index axis; Connect the historical operation data of each pulverized coal boiler on the index axis in sequence to obtain a radar chart of boiler evaluation indicators; Calculate the area value of the radar chart of boiler evaluation indicators, and determine the first evaluation indicator according to the area value of the radar chart of boiler evaluation indicators.

[0005] Furthermore, establishing a second evaluation indicator according to the change situation of the historical operation data of the pulverized coal boiler includes: Determine the coal consumption per unit steam of the pulverized coal boiler according to the change situation of the historical operation data of the pulverized coal boiler, and draw a change curve of the coal consumption per unit steam according to the change situation of the coal consumption per unit steam of the pulverized coal boiler within one operation cycle; Obtain a preset sliding time window, and divide the change curve of the coal consumption per unit steam according to the preset sliding time window to obtain a number of sub-change curves; Calculate the average value of the coal consumption per unit steam of each sub-change curve, and draw an average value change curve according to the average value of the coal consumption per unit steam of each sub-change curve; Collect the absolute value of the slope of adjacent average values of the coal consumption per unit steam in the average value change curve, and calculate the average value of the absolute values of the slopes according to the absolute values of the slopes of all adjacent average values of the coal consumption per unit steam in the average value change curve to obtain the second evaluation indicator.

[0006] Furthermore, determining the evaluation weights corresponding to each evaluation indicator according to the first evaluation indicator and the second evaluation indicator of the historical operation data includes: Obtain the historical evaluation indicators of the pulverized coal boiler and the corresponding carbon emission severity levels, and establish a training sample set according to the historical evaluation indicators of the pulverized coal boiler and the corresponding carbon emission severity levels; Establish an initial evaluation weight evaluation model according to the training sample set and train the initial evaluation weight evaluation model to obtain a trained evaluation weight evaluation model; Input the first evaluation indicator and the second evaluation indicator of the pulverized coal boiler into the trained evaluation weight evaluation model to obtain the corresponding evaluation weights.

[0007] Furthermore, constructing an objective evaluation function according to the first evaluation indicator, the second evaluation indicator and the evaluation weights includes: Construct an initial objective evaluation function according to the first evaluation indicator, the second evaluation indicator and the corresponding evaluation weights, and optimize the initial objective evaluation function based on the particle swarm algorithm to obtain an objective evaluation function. The specific form of the initial objective evaluation function is,

[0008] where, is the initial objective evaluation function, is the first evaluation indicator, is the second evaluation indicator, is the weight of the first evaluation index, is the weight of the second evaluation index.

[0009] Furthermore, the optimization of the initial objective evaluation function based on the particle swarm algorithm includes: Initializing the particle swarm parameters, where the initial particle swarm parameters include population size, maximum number of iterations, inertia weight, and learning factor; Taking the objective evaluation function as the fitness function, calculating the fitness function value of each particle, and determining the individual optimal value and the global optimal value; Updating the global optimal position and the historical optimal position of the particles based on the fitness function values of the particles; Eliminating the particle with the lowest fitness, and updating the velocity and position of the particles based on the fitness values; Performing clustering division on the particle swarm based on the k-means clustering algorithm; Performing crossover and selection on the particles based on the differential evolution algorithm, updating the final particles, and calculating the individual optimal value and the global optimal value; Repeating the above steps until the maximum number of iterations is reached or the convergence condition is satisfied, ending the optimization, and outputting the optimal solution, that is, the weight of the first evaluation index and the weight of the second evaluation index.

[0010] Furthermore, the performing clustering division on the particle swarm based on the k-means clustering algorithm includes: Randomly selecting k initial clustering centers of particles, and calculating the Euclidean distance from each particle to the initial clustering centers; Clustering the particles into the nearest clustering partition according to the Euclidean distance from each particle to the initial clustering centers, calculating the mean value of the particles in the clustering partition, and recalculating the clustering centers according to the mean value of the particles in the clustering partition; Repeating and iterating the above steps until the clustering centers no longer change or the number of iterations reaches the preset maximum number of iterations, and updating the particles according to the clustering centers of each final clustering partition.

[0011] Furthermore, the determining the energy-saving and carbon-reduction evaluation level of the operating data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-reduction evaluation model includes: Inputting the operating data of the pulverized coal boiler to be evaluated into the energy-saving and carbon-reduction evaluation model to obtain the evaluation score of the pulverized coal boiler; Obtaining the preset standard evaluation score, and calculating the difference between the evaluation score of the pulverized coal boiler and the preset standard evaluation score; Judging whether the difference between the evaluation score and the preset standard evaluation score is less than the first preset threshold. If the difference between the evaluation score and the preset standard evaluation score is less than the first preset threshold, setting the first level as the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler; If the difference between the evaluation score and the preset standard evaluation score is greater than or equal to the first preset threshold, then determine whether the difference between the evaluation score and the preset standard evaluation score is less than the second preset threshold; If the difference between the evaluation score and the preset standard evaluation score is less than the second preset threshold, then set the second level as the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler; If the difference between the evaluation score and the preset standard evaluation score is greater than or equal to the second preset threshold, then set the third level as the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler.

[0012] Further, the method further includes: When the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler is the third level, send a warning signal for warning the pulverized coal boiler.

[0013] To achieve the above object, the present invention also provides an energy-saving and carbon-reduction evaluation system for a pulverized coal boiler, including: An acquisition module, configured to acquire historical operation data of the pulverized coal boiler, establish a first evaluation index according to the historical operation data of the pulverized coal boiler, and establish a second evaluation index according to the change situation of the historical operation data of the pulverized coal boiler; A construction module, configured to determine the evaluation weight corresponding to each evaluation index according to the first evaluation index and the second evaluation index of the historical operation data, and construct a target evaluation function according to the first evaluation index, the second evaluation index and the evaluation weight; An evaluation module, configured to establish an energy-saving and carbon-reduction evaluation model according to the target evaluation function, and determine the energy-saving and carbon-reduction evaluation level of the operation data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-reduction evaluation model.

[0014] The beneficial effect of the present invention is: By applying the above technical solutions, the present invention evaluates all-round indicators in the boiler operation data by constructing an energy-saving and carbon-reduction evaluation model for the pulverized coal boiler, which can effectively improve the accuracy of the energy-saving and carbon-reduction evaluation of the pulverized coal boiler, thereby guiding the analysis diagnosis and optimization improvement work of the pulverized coal boiler in the power plant. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present application. For those skilled in the art, without creative efforts, other drawings can be obtained according to these drawings.

[0016] Figure 1 Shows the overall flowchart of an energy-saving and carbon-reduction evaluation method for a pulverized coal boiler proposed in an embodiment of the present invention; Figure 2The structural schematic diagram of an energy-saving and carbon-reducing evaluation system for a pulverized coal boiler proposed by an embodiment of the present invention is shown. Detailed implementation manners

[0017] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0018] The embodiment of the present application provides an energy-saving and carbon-reducing evaluation method for a pulverized coal boiler, as Figure 1 shown, including: S101, obtaining the historical operation data of the pulverized coal boiler, establishing a first evaluation index according to the historical operation data of the pulverized coal boiler, and establishing a second evaluation index according to the change situation of the historical operation data of the pulverized coal boiler; In some embodiments of the present application, the establishing of the first evaluation index according to the historical operation data of the pulverized coal boiler includes: determining the boiler thermal efficiency index, the flue gas temperature index and the carbon content in fly ash index of the pulverized coal boiler according to the historical operation data of the pulverized coal boiler, performing normalization processing on the historical operation data of the pulverized coal boiler to obtain the normalized historical operation data of the pulverized coal boiler; establishing a center point, evenly drawing rays around the center point to establish an index axis, and filling the normalized historical operation data of each pulverized coal boiler into the index axis; connecting the historical operation data of each pulverized coal boiler on the index axis in sequence to obtain a radar chart of the boiler evaluation index; calculating the area value of the radar chart of the boiler evaluation index, and determining the first evaluation index according to the area value of the radar chart of the boiler evaluation index.

[0019] In this embodiment, by extracting the boiler thermal efficiency, the flue gas temperature and the carbon content in fly ash during the historical operation of the pulverized coal boiler, and performing standardization processing on the three indexes to convert them into indexes in the same direction, the boiler thermal efficiency index, the flue gas temperature index and the carbon content in fly ash index are obtained. Based on these three indexes, a radar chart is established, which can comprehensively reflect the energy-saving and carbon-reducing indexes of the pulverized coal boiler.

[0020] In some embodiments of the present application, establishing the second evaluation index according to the change of the historical operation data of the pulverized coal boiler includes: determining the coal consumption per unit steam of the pulverized coal boiler according to the change of the historical operation data of the pulverized coal boiler, and drawing a change curve of the coal consumption per unit steam according to the change of the coal consumption per unit steam of the pulverized coal boiler within an operation cycle; obtaining a preset sliding time window, and dividing the change curve of the coal consumption per unit steam according to the preset sliding time window to obtain a plurality of sub-change curves; calculating the average value of the coal consumption per unit steam of each sub-change curve, and drawing an average value change curve according to the average value of the coal consumption per unit steam of each sub-change curve; collecting the absolute value of the slope of adjacent average values of the coal consumption per unit steam in the average value change curve, and calculating the average value of the absolute values of the slopes according to the absolute values of the slopes of all adjacent average values of the coal consumption per unit steam in the average value change curve to obtain the second evaluation index.

[0021] In this embodiment, the fluctuation of the coal consumption per unit steam is accurately calculated through the change of the coal consumption per unit steam of the pulverized coal boiler, and the quality of the overall operation state of the pulverized coal boiler is sensitively reflected through the fluctuation of the coal consumption per unit steam, so as to establish an energy-saving and carbon-emission reduction evaluation model in combination with the first evaluation index subsequently.

[0022] S102. Determine the evaluation weights corresponding to each evaluation index according to the first evaluation index and the second evaluation index of the historical operation data, and construct an objective evaluation function according to the first evaluation index, the second evaluation index and the evaluation weights. In some embodiments of the present application, determining the evaluation weights corresponding to each evaluation index according to the first evaluation index and the second evaluation index of the historical operation data includes: obtaining the historical evaluation index of the pulverized coal boiler and the corresponding carbon emission severity level, and establishing a training sample set according to the historical evaluation index of the pulverized coal boiler and the corresponding carbon emission severity level; establishing an initial evaluation weight evaluation model according to the training sample set and training the initial evaluation weight evaluation model to obtain a trained evaluation weight evaluation model; inputting the first evaluation index and the second evaluation index of the pulverized coal boiler into the trained evaluation weight evaluation model to obtain the corresponding evaluation weights.

[0023] In this embodiment, a deep learning neural network model is established and trained based on the historical evaluation index of the pulverized coal boiler and the corresponding carbon emission severity level, so as to output the corresponding carbon emission severity level according to the first evaluation index and the second evaluation index of the current pulverized coal boiler, and allocate the corresponding evaluation weights to each evaluation index through the carbon emission severity level.

[0024] In some embodiments of the present application, constructing the target evaluation function according to the first evaluation index, the second evaluation index, and the evaluation weights includes: constructing an initial target evaluation function according to the first evaluation index, the second evaluation index, and the corresponding evaluation weights, and optimizing the initial target evaluation function based on the particle swarm optimization algorithm to obtain the target evaluation function. The specific form of the initial target evaluation function is,

[0025] where, is the initial target evaluation function, is the first evaluation index, is the second evaluation index, is the weight of the first evaluation index, is the weight of the second evaluation index.

[0026] In some embodiments of the present application, optimizing the initial target evaluation function based on the particle swarm optimization algorithm includes: initializing the particle swarm parameters, where the initial particle swarm parameters include population size, maximum number of iterations, inertia weight, and learning factors; using the target evaluation function as the fitness function, calculating the fitness function value of each particle, and determining the individual optimal value and the global optimal value; updating the global optimal position and the historical optimal position of the particle based on the fitness function values of each particle; eliminating the particle with the lowest fitness, and updating the velocity and position of the particle based on the fitness value; performing clustering division on the particle swarm based on the k-means clustering algorithm; performing crossover and selection on the particles based on the differential evolution algorithm, updating the final particles, and calculating the individual optimal value and the global optimal value; repeating the above steps until the maximum number of iterations is reached or the convergence condition is satisfied, and the optimization ends, outputting the optimal solution, that is, the weight of the first evaluation index and the weight of the second evaluation index.

[0027] In this embodiment, the initial target evaluation function is solved based on the particle swarm optimization algorithm combined with the differential evolution algorithm, so as to output the optimal weights of the first evaluation index and the second evaluation index, realizing the accurate evaluation of the energy-saving and carbon-reduction indicators of the pulverized coal boiler.

[0028] In some embodiments of the present application, performing clustering division on the particle swarm based on the k-means clustering algorithm includes: randomly selecting k initial clustering centers of the particles, and calculating the Euclidean distance from each particle to the initial clustering center; clustering the particles into the nearest clustering partition according to the Euclidean distance from each particle to the initial clustering center, calculating the mean value of the particles in the clustering partition, and recalculating the clustering center according to the mean value of the particles in the clustering partition; repeating the above steps iteratively until the clustering center no longer changes or the number of iterations reaches the preset maximum number of iterations, and updating the particles according to the clustering centers of each final clustering partition.

[0029] In this embodiment, the particle swarm is clustered and divided based on the k-means clustering algorithm. By assigning each particle to the center point closest to it, the convergence speed of the algorithm is improved, and the computational efficiency of the algorithm is effectively enhanced.

[0030] S103. Establish an energy-saving and carbon-emission reduction evaluation model according to the target evaluation function, and determine the energy-saving and carbon-emission reduction evaluation level of the operating data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-emission reduction evaluation model.

[0031] In some embodiments of the present application, the determining the energy-saving and carbon-emission reduction evaluation level of the operating data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-emission reduction evaluation model includes: inputting the operating data of the pulverized coal boiler to be evaluated into the energy-saving and carbon-emission reduction evaluation model to obtain the evaluation score of the pulverized coal boiler; obtaining the preset standard evaluation score, and calculating the difference between the evaluation score of the pulverized coal boiler and the preset standard evaluation score; determining whether the difference between the evaluation score and the preset standard evaluation score is less than the first preset threshold. If the difference between the evaluation score and the preset standard evaluation score is less than the first preset threshold, set the first level as the energy-saving and carbon-emission reduction evaluation level of the pulverized coal boiler; if the difference between the evaluation score and the preset standard evaluation score is greater than or equal to the first preset threshold, determine whether the difference between the evaluation score and the preset standard evaluation score is less than the second preset threshold; if the difference between the evaluation score and the preset standard evaluation score is less than the second preset threshold, set the second level as the energy-saving and carbon-emission reduction evaluation level of the pulverized coal boiler; if the difference between the evaluation score and the preset standard evaluation score is greater than or equal to the second preset threshold, set the third level as the energy-saving and carbon-emission reduction evaluation level of the pulverized coal boiler.

[0032] In some embodiments of the present application, the method further includes: when the energy-saving and carbon-emission reduction evaluation level of the pulverized coal boiler is the third level, sending a warning signal to give a warning to the pulverized coal boiler.

[0033] Based on the same technical concept, as Figure 2 shown, the present invention also provides an energy-saving and carbon-emission reduction evaluation system for a pulverized coal boiler, including: an acquisition module, configured to acquire the historical operation data of the pulverized coal boiler, establish a first evaluation index according to the historical operation data of the pulverized coal boiler, and establish a second evaluation index according to the change situation of the historical operation data of the pulverized coal boiler; a construction module, configured to determine the evaluation weight corresponding to each evaluation index according to the first evaluation index and the second evaluation index of the historical operation data, and construct a target evaluation function according to the first evaluation index, the second evaluation index and the evaluation weight; an evaluation module, configured to establish an energy-saving and carbon-emission reduction evaluation model according to the target evaluation function, and determine the energy-saving and carbon-emission reduction evaluation level of the operating data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-emission reduction evaluation model.

[0034] By applying the above technical solutions, the present invention obtains the historical operation data of the pulverized coal boiler, establishes the first evaluation index according to the historical operation data of the pulverized coal boiler, and establishes the second evaluation index according to the change situation of the historical operation data of the pulverized coal boiler; determines the evaluation weights corresponding to each evaluation index according to the first evaluation index and the second evaluation index of the historical operation data, and constructs a target evaluation function according to the first evaluation index, the second evaluation index and the evaluation weights; establishes an energy-saving and carbon-reducing evaluation model according to the target evaluation function, and determines the energy-saving and carbon-reducing evaluation level of the operation data of the pulverized coal boiler to be evaluated according to the energy-saving and carbon-reducing evaluation model. The present invention accurately evaluates the energy-saving and carbon-reducing indicators of the boiler for the operation data of the pulverized coal boiler, and can effectively guide the analysis, diagnosis and optimization improvement work of the pulverized coal boiler in the power plant.

[0035] Through the description of the above embodiments, those skilled in the art can clearly understand that the present invention can be implemented by hardware or by means of software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention 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 USB flash drive, a mobile hard disk, etc.), including several 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 implementation scenarios of the present invention.

[0036] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application.

Claims

1. A method for evaluating energy conservation and carbon reduction of a pulverized coal boiler, characterized in that: include: Acquire historical operation data of the pulverized coal boiler, establish a first evaluation index based on the historical operation data of the pulverized coal boiler, and establish a second evaluation index based on changes in the historical operation data of the pulverized coal boiler; Determine the evaluation weight corresponding to each evaluation indicator according to the first evaluation indicator and the second evaluation indicator of the historical operation data, and construct the target evaluation function according to the first evaluation indicator, the second evaluation indicator and the evaluation weight; An energy-saving and carbon-reduction evaluation model is established according to the target evaluation function, and the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler operation data to be evaluated is determined according to the energy-saving and carbon-reduction evaluation model.

2. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 1 is characterized in that: The first evaluation index is established according to the historical operation data of the pulverized coal boiler, including: Determine the boiler thermal efficiency index, flue gas temperature index and fly ash carbon content index of the pulverized coal boiler according to the historical operation data of the pulverized coal boiler, perform normalization processing on the historical operation data of the pulverized coal boiler, and obtain the normalized historical operation data of the pulverized coal boiler; Establish the center of the circle, draw rays evenly from the center of the circle to the surroundings to establish the index axis, and fill the normalized historical operation data of each pulverized coal boiler into the index axis; The historical operation data of each pulverized coal boiler on the index axis are connected in sequence to obtain a radar chart of boiler evaluation index; An area value of the boiler evaluation index radar chart is calculated, and a first evaluation index is determined according to the area value of the boiler evaluation index radar chart.

3. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 2 is characterized in that: The second evaluation index is established according to the change of historical operation data of the pulverized coal boiler, including: Determine the unit steam coal consumption of the pulverized coal boiler according to the changes in the historical operation data of the pulverized coal boiler, and draw a unit steam coal consumption change curve according to the changes in the unit steam coal consumption of the pulverized coal boiler within an operation cycle; Obtain a preset sliding time window, and divide the unit steam coal consumption change curve according to the preset sliding time window to obtain a plurality of sub-change curves; Calculate the average value of unit steam coal consumption of each sub-change curve, and draw an average value change curve according to the average value of unit steam coal consumption of each sub-change curve; The absolute values ​​of the slopes of the average values ​​of adjacent unit steam coal consumption in the average value change curve are collected, and the average value of the absolute values ​​of the slopes is calculated according to the absolute values ​​of the slopes of all adjacent unit steam coal consumption in the average value change curve to obtain the second evaluation index.

4. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 3 is characterized in that: Determining the evaluation weights corresponding to the evaluation indicators according to the first evaluation indicator and the second evaluation indicator of the historical operation data includes: Obtain historical evaluation indicators of pulverized coal boilers and corresponding carbon emission severity levels, and establish a training sample set based on the historical evaluation indicators of pulverized coal boilers and corresponding carbon emission severity levels; Establishing an initial evaluation weight assessment model according to the training sample set and training the initial evaluation weight assessment model to obtain a trained evaluation weight assessment model; The first evaluation index and the second evaluation index of the pulverized coal boiler are input into the trained evaluation weight assessment model to obtain the corresponding evaluation weights.

5. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 4 is characterized in that: The constructing of the target evaluation function according to the first evaluation index, the second evaluation index and the evaluation weight comprises: An initial target evaluation function is constructed according to the first evaluation index, the second evaluation index and the corresponding evaluation weights, and the initial target evaluation function is optimized based on the particle swarm algorithm to obtain a target evaluation function. The initial target evaluation function is specifically: in, is the initial objective evaluation function, is the first evaluation index, is the second evaluation index, is the weight of the first evaluation index, is the weight of the second evaluation index.

6. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 5 is characterized in that: The optimization of the initial target evaluation function based on the particle swarm algorithm includes: Initializing particle swarm parameters, wherein the initial particle swarm parameters include population size, maximum number of iterations, inertia weight, and learning factor; The target evaluation function is used as the fitness function, the fitness function value of each particle is calculated, and the individual optimal value and the global optimal value are determined; Update the global optimal position and historical optimal position of the particle based on the fitness function value of each particle; Eliminate the particle with the lowest fitness, and update the particle speed and position based on the fitness value; The particle swarm is clustered based on the k-means clustering algorithm; Based on the differential evolution algorithm, the particles are crossed and selected, the final particles are updated, and the individual optimal value and the global optimal value are calculated; Repeat the above steps until the maximum number of iterations is reached or the convergence condition is met, the optimization ends, and the optimal solution, i.e., the weight of the first evaluation index and the weight of the second evaluation index, is output.

7. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 6 is characterized in that: The clustering of the particle swarm based on the k-means clustering algorithm includes: Randomly select k initial cluster centers of particles and calculate the Euclidean distance from each particle to the initial cluster center; Cluster the particles to the nearest cluster partition according to the Euclidean distance from each particle to the initial cluster center, calculate the mean of the particles in the cluster partition, and recalculate the cluster center according to the mean of the particles in the cluster partition; Repeat the above steps until the cluster center no longer changes or the number of iterations reaches the preset maximum number of iterations, and update the particles according to the cluster center of each final cluster partition.

8. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 1 is characterized in that: The step of determining the energy conservation and carbon reduction evaluation level of the pulverized coal boiler operation data to be evaluated according to the energy conservation and carbon reduction evaluation model includes: Input the operating data of the pulverized coal boiler to be evaluated into the energy-saving and carbon reduction evaluation model to obtain the evaluation score of the pulverized coal boiler; Obtaining a preset standard evaluation score, and calculating the difference between the evaluation score of the pulverized coal boiler and the preset standard evaluation score; Determine whether the difference between the evaluation score and the preset standard evaluation score is less than a first preset threshold value, and if the difference between the evaluation score and the preset standard evaluation score is less than the first preset threshold value, set the first level as the energy-saving and carbon reduction evaluation level of the pulverized coal boiler; If the difference between the evaluation score and the preset standard evaluation score is greater than or equal to the first preset threshold, then determine whether the difference between the evaluation score and the preset standard evaluation score is less than the second preset threshold; If the difference between the evaluation score and the preset standard evaluation score is less than the second preset threshold, the second level is set as the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler; If the difference between the evaluation score and the preset standard evaluation score is greater than or equal to the second preset threshold, the third level is set as the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler.

9. The energy-saving and carbon-reduction evaluation method for pulverized coal boilers according to claim 8, characterized in that: The method further comprises: When the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler is the third level, an early warning signal is issued to carry out early warning of the pulverized coal boiler.

10. An energy-saving and carbon-reduction evaluation system for a pulverized coal boiler, characterized in that: include: An acquisition module is used to acquire historical operation data of the pulverized coal boiler, establish a first evaluation index based on the historical operation data of the pulverized coal boiler, and establish a second evaluation index based on changes in the historical operation data of the pulverized coal boiler; A construction module, used to determine the evaluation weight corresponding to each evaluation indicator according to the first evaluation indicator and the second evaluation indicator of the historical operation data, and to construct a target evaluation function according to the first evaluation indicator, the second evaluation indicator and the evaluation weight; The evaluation module is used to establish an energy-saving and carbon-reduction evaluation model according to the target evaluation function, and determine the energy-saving and carbon-reduction evaluation level of the pulverized coal boiler operation data to be evaluated according to the energy-saving and carbon-reduction evaluation model.

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