Soft Sensing Method for Carbon Content in Fly Ash, Combustion Optimization Method and System for Coal-Fired Boiler

Abstract

The present invention discloses a soft measurement method for fly ash carbon content, a combustion optimization method and system for a coal-fired boiler. The soft measurement method for fly ash carbon content comprises the following steps: Step 1, collect historical operation parameters of the coal-fired boiler under multiple basic working conditions, and establish a correlation relationship between the historical flue gas CO concentration and the historical fly ash carbon content under multiple basic working conditions; Step 2, determine the real-time working condition and real-time operation parameters of the coal-fired boiler, and calculate the real-time fly ash carbon content under the corresponding real-time working condition according to the real-time operation parameters and the correlation relationship established in Step 1. The present invention proposes a combustion optimization method for the boiler based on the fly ash carbon content of the coal-fired boiler, thereby adjusting the total air volume of the boiler according to the real-time fly ash carbon content of the coal-fired boiler, and finally realizing the optimization of the boiler combustion and improving the boiler combustion performance.

Description

Technical Field

[0001] The present invention relates to the technical field of combustion equipment, and particularly to a soft measurement method for carbon content in fly ash, a combustion optimization method and system for a coal-fired boiler. Background Art

[0002] In recent years, the attention to environmental problems and energy problems has been increasing. As a major energy-consuming industry in China, the power generation industry urgently needs to solve the hot issue of how to improve the efficiency of power station boilers as much as possible. Improving the boiler efficiency can not only improve the economic benefits of power plants, but also improve the energy use efficiency and save resources. The carbon content in fly ash is one of the important parameters for measuring the combustion efficiency of boilers. Online monitoring of the carbon content in fly ash is beneficial to guiding on-site operators to timely adjust the total boiler air volume to improve the economic efficiency of power plant operation.

[0003] The prior art has disclosed methods for measuring the carbon content in fly ash. For example, the Chinese invention patent with the publication number CN102778538A discloses a soft measurement method for the carbon content in fly ash of a boiler based on an improved support vector machine, and the Chinese invention patent with the publication number CN112446156A discloses a measurement method for the carbon content in fly ash of a power station boiler based on the residence time of fly ash in the furnace.

[0004] Moreover, the prior art does not disclose how to use the carbon content in fly ash to guide the optimized combustion of boilers. Other common measurements of the carbon content in fly ash are off-line measurements, which have strong hysteresis and large errors. They not only have high maintenance costs, but also cannot timely guide on-site staff to optimize the combustion of boilers. Summary of the Invention

[0005] To solve the above technical problems, the present application provides a soft measurement method for the carbon content in fly ash of a coal-fired boiler, a combustion optimization method and system for a coal-fired boiler based on the soft measurement method for the carbon content in fly ash, realizing online monitoring of the carbon content in fly ash and enabling real-time optimization of the combustion performance of the boiler according to the carbon content in fly ash.

[0006] The soft measurement method for the carbon content in fly ash includes the following steps:

[0007] Step 1: Collect historical operation parameters of a coal-fired boiler under multiple basic operating conditions, and establish a correlation relationship between the historical flue gas CO concentration and the historical carbon content in fly ash under multiple basic operating conditions;

[0008] Step 2: Determine the real-time operating condition and real-time operation parameters of the coal-fired boiler, and calculate the real-time carbon content in fly ash under the corresponding real-time operating condition according to the real-time operation parameters and the correlation relationship established in Step 1.

[0009] Preferably, each of the multiple basic operating conditions corresponds to a typical boiler load and a typical range of coal volatile matter. The multiple typical boiler loads are distributed at intervals within the range of the operating load of the coal-fired boiler, and the multiple typical ranges of coal volatile matter are evenly distributed within the range of coal volatile matter.

[0010] Preferably, when the real-time boiler load of the coal-fired boiler determined in step 2 belongs to the typical boiler load, the real-time operating parameters are substituted into the correlation established under the condition of the same typical range of coal volatile matter and the same typical boiler load to calculate the real-time carbon content in fly ash.

[0011] When the real-time boiler load of the coal-fired boiler determined in step 2 does not belong to the typical boiler load, the real-time operating parameters are substituted into the two correlations established under the condition of the same typical range of coal volatile matter and two adjacent typical boiler loads, and the carbon content in fly ash under two adjacent basic operating conditions is calculated. Then, interpolation calculation is performed on the carbon content in fly ash under two adjacent basic operating conditions to obtain the real-time carbon content in fly ash.

[0012] Preferably, the multiple typical boiler loads include 50% of the boiler load. When the real-time boiler load of the coal-fired boiler is less than 50%, the real-time operating parameters are directly substituted into the correlation established under the condition of the same typical range of coal volatile matter and a boiler load of 50% to calculate the real-time carbon content in fly ash.

[0013] Preferably, the typical boiler loads include 50%, 75%, and 100% of the boiler load. The correlation between the carbon content in fly ash and the CO concentration in the flue gas under any one of the basic operating conditions of the coal-fired boiler is:

[0014] N = f(c),

[0015] Then, when the real-time boiler load of the coal-fired boiler does not belong to the typical boiler load and belongs to the same typical range of coal volatile matter,

[0016] When the boiler load x ≤ 50%, N = f 50 (c);

[0017] When the boiler load 50% < x < 75%,

[0018] When the boiler load x = 75%, N = f 75 (c);

[0019] When the boiler load 75% < x < 100%,

[0020] When the boiler load x = 75%, N = f 100 (c);

[0021] Wherein, N is the carbon content in fly ash, c is the CO concentration in the flue, and f 50 (c), f 75 (c) and f 100 (c) are respectively the correlation relationships when the coal-fired boiler is within the typical range of volatile matter of the same coal quality and the real-time boiler load is 50%, 75% and 100%.

[0022] Preferably, it further includes step 3: collecting fly ash samples in the coal-fired boiler, measuring the carbon content in the samples, comparing the error between the carbon content in the samples and the real-time carbon content in fly ash. If the error is less than the set value, continue to calculate the real-time carbon content in fly ash using the existing correlation relationship established by the historical flue CO concentration and historical carbon content in fly ash; if the error is greater than the set value, re-execute step 1 and step 2 to re-establish the correlation relationship.

[0023] A combustion optimization method for a coal-fired boiler, the specific method is as follows:

[0024] Step 1: Calculate the real-time carbon content in fly ash in the coal-fired boiler using the above soft measurement method of carbon content in fly ash;

[0025] Step 2: Compare the real-time carbon content in fly ash calculated in the most recent two times, and adjust the total boiler air volume according to the change in the real-time carbon content in fly ash in the most recent two times.

[0026] Preferably, the specific method for adjusting the total boiler air volume according to the real-time carbon content in fly ash is as follows:

[0027] When the real-time carbon content in fly ash in the most recent time increases by 0.1% each time, increase the total boiler air volume by 0.04%. After the adjustment, calculate the reduction amount ΔQ1 of q3, the reduction amount ΔQ2 of q4, and the increase amount ΔQ3 of q5. If ΔQ1 + ΔQ2 > ΔQ3, maintain the adjusted total air volume. If ΔQ1 + ΔQ2 ≤ ΔQ3, maintain the total air volume before the adjustment;

[0028] When the real-time carbon content in fly ash in the most recent time decreases by 0.1% each time, reduce the total boiler air volume by 0.04%. After the adjustment, calculate the increase amount ΔQ4 of q3, the increase amount ΔQ5 of q4, and the reduction amount ΔQ6 of q5. If ΔQ4 + ΔQ5 < ΔQ6, maintain the adjusted total air volume. If ΔQ4 + ΔQ5 ≥ ΔQ6, maintain the total air volume before the adjustment;

[0029] Wherein, q3 is the heat loss due to incomplete chemical combustion, q4 is the heat loss due to incomplete mechanical combustion, and q5 is the heat loss due to exhaust gas.

[0030] A combustion optimization system for a coal-fired boiler, including:

[0031] A data acquisition module for collecting historical operation parameters of the coal-fired boiler under multiple basic working conditions, and collecting the real-time working conditions and real-time operation parameters of the coal-fired boiler;

[0032] An association relationship establishment module for establishing an association relationship between the historical flue gas CO concentration and the historical carbon content in fly ash of a coal-fired boiler under multiple basic operating conditions;

[0033] A soft sensor module for carbon content in fly ash for calculating the real-time carbon content in fly ash according to the real-time operating parameters of the coal-fired boiler and the association relationship established by the association relationship establishment module;

[0034] A combustion optimization module for adjusting the total air volume of the coal-fired boiler according to the carbon content in fly ash at two adjacent times.

[0035] Preferably, it further includes a correction module for obtaining the carbon content in fly ash of a fly ash sample, comparing the error between the carbon content in fly ash of the fly ash sample and the real-time carbon content in fly ash. If the error is greater than the set value, the association relationship establishment module re-establishes the association relationship between the historical flue gas CO concentration and the historical carbon content in fly ash; if the error is less than the set value, the soft sensor module for carbon content in fly ash calculates the real-time carbon content in fly ash according to the real-time operating parameters of the coal-fired boiler and the association relationship established by the association relationship establishment module.

[0036] The present invention proposes a soft sensor model for carbon content in fly ash and a boiler combustion optimization method based on the carbon content in fly ash of a coal-fired boiler, so as to adjust the total air volume of the boiler according to the real-time carbon content in fly ash of the coal-fired boiler, ultimately realizing the optimization of boiler combustion and improving the boiler combustion performance.

[0037] The above description is only an overview of the technical solution of the present invention. In order to be able to understand the technical means of the present invention more clearly and implement it according to the content of the specification, the following takes the preferred embodiments of the present invention and combines with the drawings to elaborate in detail as follows. The specific implementation manners of the present invention are given in detail by the following embodiments and their drawings. Description of the Drawings

[0038] The drawings described herein are used to provide a further understanding of the present invention, form a part of this application, and the schematic embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation to the present invention. In the drawings:

[0039] Figure 1 It is a schematic diagram of the steps of the soft sensor method for carbon content in fly ash described in Embodiment 1 of this application;

[0040] Figure 2 It is a layout diagram of the CO on-line monitoring equipment in a single flue boiler described in Embodiment 1 of this application;

[0041] Figure 3 It is a flow chart of the coal-fired boiler combustion optimization method described in Embodiment 2 of this application;

[0042] Figure 4For the coal-fired boiler described in Embodiment 2 of the present application, when the boiler load is 50%, 75% and 100%, and the typical range of the volatile matter content of the coal quality is 30.33% ≤ V daf ≤ 37%, the correlation relationship between the historical operation parameters and the historical carbon content in fly ash under the basic working conditions;

[0043] Figure 5 It is the framework diagram of the combustion optimization system of the coal-fired boiler described in Embodiment 3 of the present application.

[0044] The realization, functional characteristics and advantages of the object of the present invention will be further described in conjunction with the embodiments with reference to the accompanying drawings. Detailed implementation manners

[0045] The following combines the attached Figures 1-5 Describe the principles and features of the present invention. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention. The present invention will be described more specifically by way of example in the following paragraphs with reference to the accompanying drawings. According to the following description and claims, the advantages and features of the present invention will be clearer. It should be noted that the attached drawings are all in a very simplified form and use non-precise scales, and are only used to facilitate and clearly assist in explaining the purpose of the embodiments of the present invention.

[0046] It should be noted that when a component is referred to as "fixed to" another component, it can be directly on the other component or there may also be an intermediate component. When a component is considered to be "connected to" another component, it can be directly connected to the other component or there may be an intermediate component at the same time. When a component is considered to be "disposed on" another component, it can be directly disposed on the other component or there may be an intermediate component at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are only for the purpose of illustration.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used herein in the description of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0048] Embodiment 1

[0049] Refer to Figure 1 , and propose Embodiment 1 of the present application. Embodiment 1 proposes a soft measurement method for the carbon content in fly ash, including the following steps:

[0050] Step 1: Collect the historical operation parameters of the coal-fired boiler under multiple basic working conditions, and establish the correlation relationship between the historical flue gas CO concentration and the historical carbon content in fly ash under multiple basic working conditions;

[0051] Step 2: Determine the real-time operating conditions and real-time operating parameters of the coal-fired boiler, and calculate the real-time carbon content in fly ash under the corresponding real-time operating conditions according to the real-time operating parameters and the correlation established in Step 1.

[0052] Each of the multiple basic operating conditions of the coal-fired boiler in Step 1 corresponds to a typical boiler load and a typical range of coal quality volatile matter. Moreover, the multiple boiler typical loads are distributed at intervals within the range of the operating load of the coal-fired boiler, and the multiple typical ranges of coal quality volatile matter are evenly distributed within the range of coal quality volatile matter.

[0053] The operating parameters of the coal-fired boiler include coal quality of the coal fed, CO concentration in the flue gas, and carbon content in fly ash.

[0054] In this embodiment, the three boiler typical loads of the boiler are 50%, 75%, and 100% of the boiler load. The range of coal quality volatile matter should be determined according to the actual range of the volatile matter of the coal fed to the coal-fired boiler. The dividing points of the multiple typical ranges of coal quality volatile matter should be distributed at intervals within the volatile matter of the coal fed, and the multiple dividing points evenly divide the range of the volatile matter of the coal fed into multiple typical ranges of coal quality volatile matter. An example of the division of the multiple typical ranges of the volatile matter of the coal fed is: 17% ≤ V daf ≤ 23.67%, 23.67% < V daf < 30.33%, 30.33% ≤ V daf ≤ 37%.

[0055] In this embodiment, nine basic operating conditions are formed by combining the three boiler typical loads and the three coal quality volatile matters. The historical operating parameters of the coal-fired boiler under the nine basic operating conditions are collected respectively, and a correlation between the historical CO concentration in the flue gas and the historical carbon content in fly ash is established under the nine basic operating conditions by using a non-linear mathematical method, so as to construct a soft measurement model for the carbon content in fly ash suitable for the complex operating conditions of coal-fired power station boilers.

[0056] In Step 1, the CO concentration data in the flue gas is collected by a CO on-line monitoring device. For a double-flue boiler, two sets of CO concentration on-line detection devices are symmetrically installed at positions close to the outlet of the economizer on the four inner walls of each flue; for a single-flue boiler, as Figure 2 shown, two sets of CO concentration on-line detection devices 1 are symmetrically installed at positions close to the outlet of the economizer on the four inner walls of the boiler 2 flue.

[0057] In Step 2, determine the real-time operating conditions and real-time operating parameters of the coal-fired boiler, and calculate the real-time carbon content in fly ash by using the real-time operating parameters and the correlation established in Step 1.

[0058] Specifically, when the real-time boiler load of the coal-fired boiler determined in Step 2 belongs to the typical boiler load, the real-time operating parameters are substituted into the correlation relationship corresponding to the typical interval range of the same coal quality volatile matter and the same boiler typical load to calculate the real-time carbon content in fly ash;

[0059] When the real-time boiler load of the coal-fired boiler does not belong to the typical boiler load, the real-time operating parameters are substituted into the typical interval range of the same coal quality volatile matter and the correlation relationships corresponding to two adjacent boiler typical loads, and the carbon content in fly ash under the two closest basic operating conditions is calculated. Then, interpolation calculation is performed on the carbon content in fly ash under the two closest basic operating conditions to obtain the real-time carbon content in fly ash.

[0060] Specifically, the correlation relationship between the carbon content in fly ash and the CO concentration in the flue gas is:

[0061] N = f(c),

[0062] where N is the carbon content in fly ash and c is the CO concentration in the flue gas.

[0063] Specifically, when the boiler load x = 50%,

[0064] N = f 50 (c);

[0065] When the boiler load 50% < x < 75%,

[0066]

[0067] When the boiler load x = 75%,

[0068] N = f 75 (c);

[0069] When the boiler load 75% < x < 100%,

[0070]

[0071] When the boiler load x = 100%,

[0072] N = f 100 (c),

[0073] where f 50 (c), f 75 (c), and f 100 (c) are the correlation relationships of the coal-fired boiler at 50%, 75%, and 100% of the real-time boiler load in the typical interval range of the same coal quality volatile matter, respectively.

[0074] Among them, when calculating the real-time carbon content in fly ash, multiple typical boiler loads include 50% of the boiler load. When the real-time boiler load of the coal-fired boiler is less than 50%, the real-time operating parameters are directly substituted into the correlation established within the typical range of the same coal quality volatile matter and at a boiler load of 50% to calculate the real-time carbon content in fly ash.

[0075] When collecting historical flue gas CO concentration data and historical carbon content in fly ash data, the fly ash residence time must be taken into account to ensure that the historical carbon content in fly ash of the coal-fired boiler corresponds to the historical carbon monoxide concentration.

[0076] Preferably, the soft measurement method for the carbon content in fly ash further includes step 3: collecting fly ash samples in the coal-fired boiler, measuring the carbon content in the samples, comparing the error between the carbon content in the samples and the real-time carbon content in fly ash. If the error is less than the set value, the correlation established with the existing historical flue gas CO concentration and historical carbon content in fly ash is used to calculate the real-time carbon content in fly ash; if the error is greater than the set value, steps 1 and 2 are re-executed.

[0077] When performing soft measurement of the carbon content in fly ash, if there is a large error between the real-time carbon content in fly ash calculated according to the correlation established based on the historical operating data of the coal-fired boiler and the actual carbon content in fly ash, it is necessary to re-collect the historical operating parameters to establish a correlation with a smaller error to ensure the accuracy of the correlation.

[0078] Specifically, the staff samples the fly ash in the coal-fired boiler every three months and measures the carbon content in the fly ash samples, compares the error between the carbon content in the samples and the real-time carbon content in fly ash. If the error is greater than the set value, the historical operating parameters of the coal-fired boiler within three months are re-collected and the correlation between the historical flue gas CO concentration and historical carbon content of the coal-fired boiler is established before calculating the real-time carbon content in fly ash. If the error is less than the set value, the correlation established with the existing historical flue gas CO concentration and historical carbon content in fly ash of the coal-fired boiler is used to calculate the real-time carbon content in fly ash.

[0079] Example 2

[0080] Refer to Figure 3 , Example 2 proposes a combustion optimization method for a coal-fired boiler, which specifically includes the following steps:

[0081] Step 1: Calculate the real-time carbon content in fly ash in the coal-fired boiler by using the soft measurement method for the carbon content in fly ash as described in Example 1;

[0082] Step 2: Compare the real-time carbon content in fly ash calculated in the most recent two times, and adjust the total boiler air volume according to the change in the real-time carbon content in fly ash in the most recent two times.

[0083] In step 2, specifically, when the real-time carbon content in fly ash increases by 0.1% each time, the total boiler air volume is increased by 0.04%. After adjustment, calculate the reduction amount ΔQ1 of q3, the reduction amount ΔQ2 of q4, and the increase amount ΔQ3 of q5. If ΔQ1 + ΔQ2 > ΔQ3, maintain the adjusted total air volume; if ΔQ1 + ΔQ2 ≤ ΔQ3, maintain the total air volume before adjustment.

[0084] When the real-time carbon content in fly ash decreases by 0.1% each time, the total boiler air volume is decreased by 0.04%. After adjustment, calculate the increase amount ΔQ4 of q3, the increase amount ΔQ5 of q4, and the reduction amount ΔQ6 of q5. If ΔQ4 + ΔQ5 < ΔQ6, maintain the adjusted total air volume; if ΔQ4 + ΔQ5 ≥ ΔQ6, maintain the total air volume before adjustment.

[0085] Among them, q3 is the heat loss due to incomplete chemical combustion, q4 is the heat loss due to incomplete mechanical combustion, q5 is the heat loss of flue gas. The changes of q3, q4, and q5 with the total boiler air volume and the calculation methods are all well-known constants, and will not be described in detail in this embodiment.

[0086] Select the basic operating conditions of the coal-fired boiler at loads of 50%, 75%, and 100%, and the typical range of coal volatile matter is 30.33% ≤ V daf ≤ 37%. The historical flue gas CO concentration data and historical carbon content in fly ash collected under the above three basic operating conditions, and 50 groups of data are collected under each basic operating condition. A non-linear mathematical method is used to establish the correlation between the flue gas CO concentration and the carbon content in fly ash, and a soft measurement model of the carbon content in fly ash adapted to the complex operating conditions of the boiler in this embodiment is constructed as Figure 3 shown.

[0087] The real-time boiler load of the coal-fired boiler unit is 50%, the coal volatile matter is 32%, the fixed carbon content is 39%, the previously calculated real-time carbon content in fly ash is 1.8%, the most recent real-time carbon content in fly ash is 2.3%, and the real-time carbon content in fly ash has increased by 0.5%. The real-time boiler efficiency is 94.74%; the boiler efficiency after optimization according to the combustion optimization model is 94.84%. It can be seen that the comprehensive cost after optimization using the optimization method of the present invention is significantly reduced.

[0088] Embodiment 3

[0089] Refer to Figure 4 Based on the coal-fired boiler combustion optimization method of Embodiment 2, Embodiment 3 proposes a coal-fired boiler combustion optimization system, including:

[0090] A data acquisition module for acquiring the historical operating parameters of the coal-fired boiler under multiple basic operating conditions, and acquiring the real-time operating conditions and real-time operating parameters of the coal-fired boiler.

[0091] An association relationship establishment module for establishing an association relationship between the historical flue gas CO concentration and the historical carbon content in fly ash of a coal-fired boiler under multiple basic operating conditions;

[0092] A soft measurement module for carbon content in fly ash for calculating the real-time carbon content in fly ash according to the real-time operating parameters of the coal-fired boiler and the association relationship established in the association relationship establishment module;

[0093] A combustion optimization module for adjusting the total air volume of the coal-fired boiler according to the real-time carbon content in fly ash for two adjacent times.

[0094] Specifically, the combustion optimization system of the coal-fired boiler further includes a correction module for obtaining the carbon content in the fly ash sample and comparing the error between the carbon content in the fly ash sample and the real-time carbon content in fly ash. If the error is greater than the set value, the association relationship establishment module re-establishes the association relationship between the historical flue gas CO concentration and the historical carbon content in fly ash; if the error is less than the set value, the soft measurement module for carbon content in fly ash calculates the real-time carbon content in fly ash according to the real-time operating parameters of the coal-fired boiler and the association relationship established in the association relationship establishment module.

[0095] The correction model is used to determine the error of the association relationship between the historical flue gas CO concentration and the historical carbon content in fly ash of the coal-fired boiler according to the carbon content in the fly ash sample. When the error is too large, historical operation data needs to be re-collected and the association relationship needs to be re-established. When the error meets the set range, the association relationship between the historical flue gas CO concentration and the historical carbon content in fly ash of the coal-fired boiler can be used to calculate the real-time carbon content in fly ash.

[0096] The above is only a preferred embodiment of the present invention and does not impose any form of limitation on the present invention; any ordinary technician in the industry can smoothly implement the present invention as shown in the accompanying drawings of the specification and described above; however, any minor changes, modifications and evolutions made by those skilled in the art within the scope of the technical solution of the present invention using the technical content disclosed above are equivalent embodiments of the present invention; at the same time, any equivalent changes, modifications and evolutions made to the above embodiments based on the essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A soft measurement method for carbon content in fly ash, characterized in that It includes the following steps: Step 1: Collect the historical operation parameters of the coal-fired boiler under multiple basic operating conditions, and establish the correlation relationship between the historical flue gas CO concentration and the historical carbon content in fly ash under multiple basic operating conditions; Step 2: Determine the real-time operating condition and real-time operation parameters of the coal-fired boiler, and calculate the real-time carbon content in fly ash corresponding to the real-time operating condition according to the real-time operation parameters and the correlation relationship established in Step 1; Each basic operating condition corresponds to a typical boiler load and a typical range of coal volatile matter respectively, and multiple boiler typical loads are distributed at intervals within the range of the coal-fired boiler operating load, and multiple typical ranges of coal volatile matter are evenly distributed within the range of coal volatile matter; When the real-time boiler load of the coal-fired boiler determined in Step 2 belongs to the boiler typical load, substitute the real-time operation parameters into the correlation relationship established under the conditions of the same typical range of coal volatile matter and the same boiler typical load to calculate the real-time carbon content in fly ash; When the real-time boiler load of the coal-fired boiler determined in Step 2 does not belong to the boiler typical load, substitute the real-time operation parameters into the two correlation relationships established under the same typical range of coal volatile matter and two adjacent boiler typical loads, and calculate the carbon content in fly ash under two adjacent basic operating conditions, and then perform interpolation calculation on the carbon content in fly ash under two adjacent basic operating conditions to obtain the real-time carbon content in fly ash; Multiple said boiler typical loads include a boiler load of 50%, and when the real-time boiler load of the coal-fired boiler is less than 50%, directly substitute the real-time operation parameters into the correlation relationship established under the same typical range of coal volatile matter and a boiler load of 50% to calculate the real-time carbon content in fly ash; The said boiler typical loads include boiler loads of 50%, 75% and 100%, and the correlation relationship between the carbon content in fly ash and the flue gas CO concentration of the coal-fired boiler under any basic operating condition is: ， Then when the real-time boiler load of the coal-fired boiler does not belong to the boiler typical load and belongs to the same typical range of coal volatile matter, When the boiler load x ≤ 50%, ; When the boiler load is 50% < x < 75%, ; When the boiler load x = 75%, ; When the boiler load is 75% < x < 100%, ; When the boiler load x = 75%, ; Where N is the carbon content of fly ash and c is the CO concentration in the flue, , and are the correlation relationships when the coal-fired boiler is in the typical range of the same coal quality volatile matter and the real-time boiler load is 50%, 75% and 100% respectively.

2. The soft measurement method for carbon content in fly ash according to claim 1, characterized in that, It also includes Step 3: Collect fly ash samples in the coal-fired boiler, measure the carbon content in the fly ash samples, compare the error between the carbon content in the fly ash samples and the real-time carbon content in fly ash. If the error is less than the set value, use the existing correlation relationship between the historical flue gas CO concentration and the historical carbon content in fly ash to calculate the real-time carbon content in fly ash; if the error is greater than the set value, re-execute Step 1 and Step 2.

3. A combustion optimization method for a coal-fired boiler, characterized in that, The specific method is: Step 1: Calculate the real-time carbon content in fly ash in the coal-fired boiler by using the soft measurement method for carbon content in fly ash according to any one of claims 1-2; Step 2: Compare the real-time carbon content in fly ash calculated in the last two times, and adjust the total boiler air volume according to the change of the real-time carbon content in fly ash in the last two times.

4. The combustion optimization method for a coal-fired boiler according to claim 3, characterized in that The specific method for adjusting the total boiler air volume according to the real-time carbon content in fly ash is: When the carbon content in the fly ash of the most recent real-time measurement increases by 0.1%, increase the total boiler air volume by 0.04%. After the adjustment, calculate the reduction in q3, ΔQ1, the reduction in q4, ΔQ2, and the increase in q5, ΔQ3. If ΔQ1 + ΔQ2 > ΔQ3, maintain the adjusted total air volume. If ΔQ1 + ΔQ2 ≤ ΔQ3, maintain the total air volume before the adjustment; When the carbon content in the fly ash of the most recent real-time measurement decreases by 0.1%, reduce the total boiler air volume by 0.04%. After the adjustment, calculate the increase in q3, ΔQ4, the increase in q4, ΔQ5, and the reduction in q5, ΔQ6. If ΔQ4 + ΔQ5 < ΔQ6, maintain the adjusted total air volume. If ΔQ4 + ΔQ5 ≥ ΔQ6, maintain the total air volume before the adjustment; Wherein, q3 is the heat loss due to incomplete combustion of fuel, q4 is the heat loss due to mechanical incomplete combustion, and q5 is the heat loss due to exhaust gas; 5. A combustion optimization system for a coal-fired boiler, characterized in that, Including: A data acquisition module for collecting historical operation parameters of the coal-fired boiler under multiple basic operating conditions, identifying the operating conditions of the coal-fired boiler, and collecting real-time operation parameters; A correlation relationship establishment module for establishing the correlation relationship between the historical flue gas CO concentration and the historical fly ash carbon content of the coal-fired boiler under multiple basic operating conditions; A fly ash carbon content soft measurement module for calculating the real-time fly ash carbon content based on the real-time operation parameters of the coal-fired boiler and the correlation relationship established by the correlation relationship establishment module; Wherein, when the real-time boiler load of the coal-fired boiler determined in step 2 belongs to the typical boiler load, substitute the real-time operation parameters into the correlation relationship established under the typical interval range of the same coal quality volatile matter and the same typical boiler load to calculate the real-time fly ash carbon content; When the real-time boiler load of the coal-fired boiler determined in step 2 does not belong to the typical boiler load, substitute the real-time operation parameters into the two correlation relationships established under the typical interval range of the same coal quality volatile matter and two adjacent typical boiler loads, calculate the fly ash carbon content under two adjacent basic operating conditions, and then perform interpolation calculation on the fly ash carbon content under two adjacent basic operating conditions to obtain the real-time fly ash carbon content; Multiple said typical boiler loads include a boiler load of 50%. When the real-time boiler load of the coal-fired boiler is less than 50%, directly substitute the real-time operation parameters into the correlation relationship established under the typical interval range of the same coal quality volatile matter and a boiler load of 50% to calculate the real-time fly ash carbon content; The said typical boiler loads include boiler loads of 50%, 75%, and 100%. The correlation relationship between the fly ash carbon content and the flue gas CO concentration of the coal-fired boiler under any one basic operating condition is: ， Then when the real-time boiler load of the coal-fired boiler does not belong to the typical boiler load and belongs to the typical interval range of the same coal quality volatile matter, When the boiler load x ≤ 50%, ; When the boiler load is 50% < x < 75%, ; When the boiler load x = 75%, ; When the boiler load is 75% < x < 100%, ; When the boiler load x = 75%, ; where N is the carbon content of fly ash and c is the CO concentration in the flue gas, , and are the correlation relationships when the coal-fired boiler is in the typical range of the same coal quality volatile matter and the real-time boiler load is 50%, 75% and 100% respectively; A combustion optimization module for adjusting the total air volume of the coal-fired boiler according to the carbon content in the fly ash of two adjacent real-time measurements.

6. The combustion optimization system for a coal-fired boiler according to claim 5, characterized in that, It further includes a correction module, which is used to obtain the carbon content in fly ash of the fly ash sample, and compare the error between the carbon content in fly ash of the fly ash sample and the real-time carbon content in fly ash. If the error is greater than the set value, the correlation relationship establishment module re-establishes the correlation relationship between the historical flue gas CO concentration and the historical carbon content in fly ash; if the error is less than the set value, the soft measurement module of the carbon content in fly ash calculates the real-time carbon content in fly ash according to the real-time operation parameters of the coal-fired boiler and the correlation relationship established by the correlation relationship establishment module.

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