Boiler soot blowing method, device, medium and equipment for coal-fired unit

Abstract

The invention discloses a boiler soot blowing method and device of a coal-fired unit, a medium and equipment, and the method comprises the steps that the radiation entropy production of a water cooling wall and the entropy production of a heating surface are obtained through calculation when soot blowing is not carried out, and the radiation entropy production of the water cooling wall, the entropy production of the heating surface, the steam heat dissipation entropy production, the mass transfer entropy production and the motor entropy production are obtained through calculation when soot blowing is carried out; on the basis of radiation entropy production and heating surface entropy production of the water cooling wall during no soot blowing and radiation entropy production, heating surface entropy production, steam heat dissipation entropy production, mass transfer entropy production and motor entropy production of the water cooling wall during soot blowing, a soot blowing income model is constructed with the maximum soot blowing pure income as the target, the soot blowing income model is solved, and the optimal soot blowing frequency is obtained. According to the method, the entropy production in the normal operation and soot blowing process of the water cooling wall and each heating surface of the boiler is analyzed, irreversible energy loss in the heat transfer process and the soot blowing process is fully considered, the optimal soot blowing frequency is obtained by taking the maximum soot blowing pure income as the target, the optimal soot blowing frequency is provided from the dimensions of economy, safety and the like, and the soot blowing income is maximized.

Description

Technical Field

[0001] The present invention relates to the technical field of boiler soot blowing, and particularly to a boiler soot blowing method, device, medium and equipment for a coal-fired unit. Background Art

[0002] Due to some impurities in the fuel, the boilers of coal-fired power plants have the phenomenon of fouling on the heating surfaces. The more impurities there are, the more serious the fouling on the heating surfaces becomes. Serious fouling on the heating surfaces will have an adverse impact on the safety and economy of boiler operation. For example, furnace fouling will cause the flue gas temperature at the furnace outlet, superheated steam temperature and exhaust gas temperature to rise. In severe cases, it will cause the overheating and over-temperature of the tube walls of the superheater and reheater, damaging the safety of the heating surfaces. At the same time, due to the uneven distribution of fouling in the furnace, it will lead to an increase in the flue gas temperature deviation at the furnace outlet and an increase in the thermal deviation of the superheated steam. In addition, the falling of the coke blocks in the upper part of the furnace will also affect the combustion stability. In severe cases, it may even cause safety accidents such as the water-cooled wall being punctured and the furnace extinguishing. Therefore, it is very important to blow soot on the heating surfaces of the boiler through the soot blowing system to avoid serious ash accumulation and slagging on the heating surfaces.

[0003] At present, the soot blowing system blows soot on the boiler heating surfaces regularly, that is, the number of soot blowing times is fixed. When blowing soot, a soot blowing medium is used. If the number of soot blowing times is relatively large, a large amount of soot blowing medium will be used, increasing the cost. At the same time, a relatively large number of soot blowing times will also cause the pipe wall to become thinner, affecting the service life of the equipment. If the number of soot blowing times is relatively small, there may still be ash accumulation and slagging on the heating surfaces. Thus, it can be seen that the determination of the number of soot blowing times is extremely important. Therefore, a boiler soot blowing method is needed to achieve on-demand soot blowing, which can minimize the soot blowing frequency while avoiding slagging on the heating surfaces, so as to achieve the purpose of energy conservation and consumption reduction. Summary of the Invention

[0004] In view of this, the present invention provides a boiler soot blowing method, device, medium and equipment for a coal-fired unit, mainly aiming to solve the problem that the number of soot blowing times in the current boiler soot blowing method is fixed and cannot be determined in combination with the actual situation.

[0005] According to one aspect of the present application, a boiler soot blowing method for a coal-fired unit is provided, and the method includes:

[0006] Obtain the first flame image in the furnace without soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the first flame image to obtain the first radiation characteristic parameters and the first temperature distribution value, and calculate based on the first radiation characteristic parameters and the first temperature distribution value to obtain the first in-furnace medium radiation entropy production and the first water-cooled wall surface radiation heat transfer entropy production without soot blowing;

[0007] Obtain the first basic data of the heating surface when soot blowing is not performed, and calculate based on the first basic data to obtain the first total heat transfer entropy generation and the first total flow resistance entropy generation when soot blowing is not performed;

[0008] Obtain the second flame image in the furnace when soot blowing is performed, calculate the radiation characteristic parameters and the temperature field distribution based on the second flame image to obtain the second radiation characteristic parameters and the second temperature distribution value, and calculate based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second in-furnace medium radiation entropy generation and the second water-cooled wall surface radiation heat transfer entropy generation when soot blowing is performed;

[0009] Obtain the second basic data of the heating surface when soot blowing is performed, calculate based on the second basic data to obtain the second total heat transfer entropy generation and the second total flow resistance entropy generation when soot blowing is performed, obtain the working medium data of soot blowing, and calculate based on the working medium data to obtain the steam heat dissipation entropy generation, the mass transfer entropy generation and the motor entropy generation when soot blowing is performed;

[0010] Based on the first in-furnace medium radiation entropy generation, the first water-cooled wall surface radiation heat transfer entropy generation, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second in-furnace medium radiation entropy generation, the second water-cooled wall surface radiation heat transfer entropy generation, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation and the motor entropy generation, with the maximum pure soot blowing benefit as the goal, construct a soot blowing benefit model, solve the soot blowing benefit model, and obtain the optimal number of soot blowing times.

[0011] Optionally, the obtaining of the first flame image in the furnace when soot blowing is not performed, and the calculation of the radiation characteristic parameters and the temperature field distribution based on the first flame image to obtain the first radiation characteristic parameters and the first temperature distribution value includes:

[0012] Obtain the first flame image in the furnace when soot blowing is not performed, and convert the first flame image into a first radiation intensity image based on the conversion relationship between pixel points and radiation intensity;

[0013] Based on Wien's law, perform temperature back-calculation for each pixel point in the first radiation intensity image to obtain a first radiation temperature image;

[0014] Make an initial setting for the first radiation characteristic parameters, establish a first temperature distribution mathematical model based on the initially set first radiation characteristic parameters and the relationship between the first radiation temperature image and the true temperature field, add regularization constraints to the first temperature distribution mathematical model to obtain a first objective function, and solve the first objective function to obtain the first temperature distribution value;

[0015] Establish a first forward model of simulated radiation intensity based on the first temperature distribution value and a preset radiation transfer equation. Construct a second objective function based on the first forward model of simulated radiation intensity and the actual intensity values in the first radiation intensity image, and solve the second objective function to obtain the first radiation characteristic parameters;

[0016] Substitute the first radiation characteristic parameters into the first objective function, solve the first objective function to obtain a new first temperature distribution value, substitute the new first temperature distribution value into the second objective function, solve the second objective function to obtain a new first radiation characteristic parameter, and repeat this process until the iteration condition is met, so as to obtain the optimal first temperature distribution value and the optimal first radiation characteristic parameters.

[0017] Optionally, the first radiation characteristic parameters include the first medium absorption coefficient and the first medium scattering coefficient. The following formula is used to calculate the radiation entropy production of the medium in the first furnace:

[0018]

[0019] The following formula is used to calculate the radiation heat transfer entropy production of the first water-cooled wall surface:

[0020]

[0021] where, T 01 is the ambient temperature when not sootblowing; q is the radiation heat flux density between the medium and the water-cooled wall surface; V is the volume of the boiler furnace; K j1 is the first medium absorption coefficient; σ1 is the first medium scattering coefficient; I1 is the blackbody monochromatic spectral radiation intensity; I2 is the monochromatic spectral radiation intensity; T p is the Planck temperature; T1 is the temperature of the medium in the furnace when not sootblowing; λ is the wavelength; I3 is the monochromatic spectral scattering intensity; φ is the radiation phase function; n is the normal vector of the water-cooled wall surface; θ is the solid angle; L is the spectral radiation intensity of the water-cooled wall surface; I4 is the spectral radiation intensity at wavelength λ; A is the area of the water-cooled wall.

[0022] Optionally, based on the first radiation entropy production of the medium in the furnace, the first radiation heat transfer entropy production of the water-cooled wall surface, the first total heat transfer entropy production, the first total flow resistance entropy production, the second radiation entropy production of the medium in the furnace, the second radiation heat transfer entropy production of the water-cooled wall surface, the second total heat transfer entropy production, the second total flow resistance entropy production, the steam heat dissipation entropy production, the mass transfer entropy production, and the motor entropy production, with the maximum sootblowing net benefit as the goal, construct a sootblowing benefit model, including:

[0023] Construct a soot blowing benefit model of entropy generation based on the radiation entropy generation of the medium in the first furnace, the radiation heat transfer entropy generation of the first water wall surface, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the radiation entropy generation of the medium in the second furnace, the radiation heat transfer entropy generation of the second water wall surface, the second total heat transfer entropy generation, and the second total flow resistance entropy generation;

[0024] Construct a soot blowing cost model of entropy generation based on the steam heat dissipation entropy generation, the mass transfer entropy generation, and the motor entropy generation;

[0025] Based on the soot blowing benefit model and the soot blowing cost model, with the maximum net soot blowing benefit as the goal, construct a soot blowing benefit model.

[0026] Optionally, the soot blowing benefit model is:

[0027]

[0028] where, t0 is the time of t0, t0 + Δt is the time of t0 + Δt; N in is the soot blowing benefit model, N out is the soot blowing cost model, and n0 is the optimal number of soot blowing times.

[0029] Optionally, calculate the first total heat transfer entropy generation using the following formula:

[0030]

[0031] ΔS ΔT1 = n1zΔS g,ΔT1

[0032] where, ΔS g,ΔT1 is the first heat transfer entropy generation of a tube row, K z is the total heat transfer coefficient; T ∞ 1 is the average inlet and outlet flue gas temperature without soot blowing; d i is the inner diameter of the tube; C pi 1 is the specific heat of the steam without soot blowing; G 1 is the steam flow rate without soot blowing; l is the tube length; T fii 1 is the steam inlet temperature without soot blowing; n1 is the number of tube rows; z is the number of tube coils, ΔS ΔT1 is the first total heat transfer entropy generation;

[0033] Calculate the first total flow resistance entropy generation using the following formula:

[0034]

[0035] ΔS Δp1 = n1zΔS g,ΔP1

[0036] Among them, ΔS g,ΔP1 is the first flow-blocking entropy generation of a tube row, and ΔS Δp1 is the first total flow-blocking entropy generation.

[0037] U ∞ 1 is the average velocity of flue gas flow without soot blowing; T o1 is the ambient temperature without soot blowing; C D 1 is the local resistance coefficient without soot blowing.

[0038] Optionally, the steam heat dissipation entropy generation is calculated by the following formula:

[0039] △S q = m(S2 - S1)

[0040] Among them, m is the soot blowing steam consumption; S1 is the specific entropy of the steam in the first state; S2 is the specific entropy of the steam in the second state;

[0041] The mass transfer entropy generation is calculated by the following formula:

[0042] △S g = G 2 (C pi 2 ln(T’ / T0’)-R(lnP i / P0))

[0043] Among them, C pi 2 is the specific heat of the steam during soot blowing; G 2 is the steam flow rate during soot blowing; T0’ is the temperature of the steam before mixing; T’ is the temperature of the steam after mixing; R is the gas constant; P i is the pressure of the working fluid before mixing; P0 is the partial pressure of the working fluid after mixing;

[0044] The motor entropy generation is calculated by the following formula:

[0045] △S m = P / T q

[0046] Among them, P is the power of the soot blower motor; T q is the temperature of the working fluid used in the steam soot blower.

[0047] According to another aspect of the present application, a boiler soot blowing device for a coal-fired unit is provided, including:

[0048] The entropy production acquisition module for the water-cooled wall without soot blowing is used to obtain the first flame image in the furnace without soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the first flame image, obtain the first radiation characteristic parameters and the first temperature distribution value, and calculate based on the first radiation characteristic parameters and the first temperature distribution value to obtain the first radiation entropy production of the furnace medium and the first radiation heat transfer entropy production of the water-cooled wall surface without soot blowing;

[0049] The entropy production acquisition module for the heating surface without soot blowing is used to obtain the first basic data of the heating surface without soot blowing, and calculate based on the first basic data to obtain the first total heat transfer entropy production and the first total flow resistance entropy production without soot blowing;

[0050] The entropy production acquisition module for the water-cooled wall with soot blowing is used to obtain the second flame image in the furnace during soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image, obtain the second radiation characteristic parameters and the second temperature distribution value, and calculate based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second radiation entropy production of the furnace medium and the second radiation heat transfer entropy production of the water-cooled wall surface during soot blowing;

[0051] The entropy production acquisition module for the heating surface with soot blowing is used to obtain the second basic data of the heating surface during soot blowing, calculate based on the second basic data to obtain the second total heat transfer entropy production and the second total flow resistance entropy production during soot blowing, obtain the working medium data of soot blowing, and calculate based on the working medium data to obtain the steam heat dissipation entropy production, mass transfer entropy production and motor entropy production during soot blowing;

[0052] The optimal soot blowing times acquisition module is used to construct a soot blowing benefit model with the maximum net soot blowing benefit as the goal based on the first radiation entropy production of the furnace medium, the first radiation heat transfer entropy production of the water-cooled wall surface, the first total heat transfer entropy production, the first total flow resistance entropy production, the second radiation entropy production of the furnace medium, the second radiation heat transfer entropy production of the water-cooled wall surface, the second total heat transfer entropy production, the second total flow resistance entropy production, the steam heat dissipation entropy production, the mass transfer entropy production and the motor entropy production, and solve the soot blowing benefit model to obtain the optimal soot blowing times.

[0053] Optionally, the entropy production acquisition module for the water-cooled wall without soot blowing is further used for:

[0054] Obtain the first flame image in the furnace without soot blowing, and convert the first flame image into a first radiation intensity image based on the conversion relationship between pixel points and radiation intensity;

[0055] Based on Wien's law, perform temperature back-calculation on each pixel point in the first radiation intensity image to obtain a first radiation temperature image;

[0056] Initial set the first radiation characteristic parameter, establish the first temperature distribution mathematical model based on the initially set first radiation characteristic parameter and the relationship between the first radiation temperature image and the true temperature field, add regularization constraints to the first temperature distribution mathematical model to obtain the first objective function, solve the first objective function to obtain the first temperature distribution value;

[0057] Based on the first temperature distribution value and the preset radiation transfer equation, establish the first forward model of simulated radiation intensity. Based on the first forward model of simulated radiation intensity and the actual intensity value in the first radiation intensity image, construct the second objective function, and solve the second objective function to obtain the first radiation characteristic parameter;

[0058] Substitute the first radiation characteristic parameter into the first objective function, solve the first objective function to obtain a new first temperature distribution value, substitute the new first temperature distribution value into the second objective function, solve the second objective function to obtain a new first radiation characteristic parameter, until the iteration condition is reached, and obtain the optimal first temperature distribution value and the optimal first radiation characteristic parameter.

[0059] Optionally, the first radiation characteristic parameter includes the first medium absorption coefficient and the first medium scattering coefficient. The following formula is used to calculate the radiation entropy production of the first furnace medium:

[0060]

[0061] The following formula is used to calculate the radiation heat transfer entropy production of the first water wall surface:

[0062]

[0063] where, T 01 is the ambient temperature when not sootblowing; q is the radiation heat flux density between the medium and the water wall surface; V is the volume of the boiler furnace; K j1 is the first medium absorption coefficient; σ1 is the first medium scattering coefficient; I1 is the blackbody monochromatic spectral radiation intensity; I2 is the monochromatic spectral radiation intensity; T p is the Planck temperature; T1 is the temperature of the furnace medium when not sootblowing; λ is the wavelength; I3 is the monochromatic spectral scattering intensity; φ is the radiation phase function; n is the normal vector of the water wall surface; θ is the solid angle; L is the spectral radiation intensity of the water wall surface; I4 is the spectral radiation intensity at wavelength λ; A is the area of the water wall.

[0064] Optionally, the optimal sootblowing times acquisition module is further used for:

[0065] Based on the radiation entropy production of the medium in the first furnace, the radiation heat transfer entropy production of the first water wall surface, the first total heat transfer entropy production, the first total flow resistance entropy production, the radiation entropy production of the medium in the second furnace, the radiation heat transfer entropy production of the second water wall surface, the second total heat transfer entropy production, and the second total flow resistance entropy production, a soot blowing benefit model of entropy production is constructed;

[0066] Based on the steam heat dissipation entropy production, the mass transfer entropy production, and the motor entropy production, a soot blowing expenditure model of entropy production is constructed;

[0067] Based on the soot blowing benefit model and the soot blowing expenditure model, with the maximum soot blowing net benefit as the goal, a soot blowing benefit model is constructed.

[0068] Optionally, the soot blowing benefit model is:

[0069]

[0070] where t0 is the time of t0, and t0 + Δt is the time of t0 + Δt; N in is the soot blowing benefit model, N out is the soot blowing expenditure model, and n0 is the optimal soot blowing times.

[0071] Optionally, the following formula is used to calculate the first total heat transfer entropy production:

[0072]

[0073] ΔS ΔT1 = n1zΔS g,ΔT1

[0074] where ΔS g,ΔT1 is the first heat transfer entropy production of a tube row, K z is the total heat transfer coefficient; T ∞ 1 is the average inlet and outlet flue gas temperature without soot blowing; d i is the inner diameter of the tube; C pi 1 is the specific heat of the steam without soot blowing; G 1 is the steam flow rate without soot blowing; l is the tube length; T fii 1 is the steam inlet temperature without soot blowing; n1 is the number of tube rows; z is the number of tube circles, ΔS ΔT1 is the first total heat transfer entropy production;

[0075] The following formula is used to calculate the first total flow resistance entropy production:

[0076]

[0077] ΔS Δp1 = n1zΔS g,ΔP1

[0078] wherein, ΔS g,ΔP1 is the first throttling entropy generation of a tube bank, and ΔS Δp1 is the total first throttling entropy generation;

[0079] U ∞ 1 is the average velocity of flue gas flow without soot blowing; T o1 is the ambient temperature without soot blowing; C D 1 is the local resistance coefficient without soot blowing.

[0080] Optionally, the steam heat dissipation entropy generation is calculated by the following formula:

[0081] △S q = m(S2 - S1)

[0082] wherein, m is the consumption of soot blowing steam; S1 is the specific entropy of steam in the first state; S2 is the specific entropy of steam in the second state;

[0083] The mass transfer entropy generation is calculated by the following formula:

[0084] △S g = G 2 (C pi 2 ln(T’ / T0’)-R(lnP i / P0))

[0085] wherein, C pi 2 is the specific heat of steam during soot blowing; G 2 is the steam flow rate during soot blowing; T0’ is the temperature of steam before mixing; T’ is the temperature of steam after mixing; R is the gas constant; P i is the pressure of the working medium before mixing; P0 is the partial pressure of the working medium after mixing;

[0086] The motor entropy generation is calculated by the following formula:

[0087] △S m = P / T q

[0088] wherein, P is the power of the soot blower motor; T q is the temperature of the working medium used by the steam soot blower.

[0089] According to another aspect of the present application, a storage medium is provided, in which at least one executable instruction is stored, and the executable instruction causes the processor to execute the operations corresponding to the boiler soot blowing method of the coal-fired unit described above.

[0090] According to another aspect of the present application, a computer device is provided, including: a processor, a memory, a communication interface, and a communication bus, and the processor, the memory, and the communication interface complete communication with each other through the communication bus;

[0091] The memory is used to store at least one executable instruction, and the executable instruction causes the processor to execute the operations corresponding to the above-mentioned boiler soot blowing method for a coal-fired unit.

[0092] By means of the above technical solution, the technical solution provided by the embodiment of the present invention has at least the following advantages:

[0093] A boiler soot blowing method, device, medium and equipment for a coal-fired unit provided by the present application starts from the second law of thermodynamics, analyzes the entropy generation during the normal operation and soot blowing process of the water wall and each heating surface of the boiler, fully considers the irreversible energy loss in the heat transfer process and the soot blowing process, constructs a soot blowing benefit model with the maximum net soot blowing benefit as the goal, solves the net benefit model of the soot blowing, obtains the optimal number of soot blowing times, and proposes the optimal number of soot blowing times from multiple dimensions of economy, safety and environmental protection, so as to realize the maximization of the net soot blowing benefit in the true sense.

[0094] 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, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are specifically given below. BRIEF DESCRIPTION OF THE DRAWINGS

[0095] By reading the following detailed description of the preferred embodiments, various other advantages and benefits will become clear to those of ordinary skill in the art. The drawings are only for the purpose of showing the preferred embodiments and are not considered to be a limitation of the present invention. And throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0096] Figure 1 The flowchart of a boiler soot blowing method for a coal-fired unit provided by an embodiment of the present application is shown;

[0097] Figure 2 Another flowchart of a boiler soot blowing method for a coal-fired unit provided by an embodiment of the present application is shown;

[0098] Figure 3 Another flowchart of a boiler soot blowing method for a coal-fired unit provided by an embodiment of the present application is shown;

[0099] Figure 4 Another flowchart of a boiler soot blowing method for a coal-fired unit provided by an embodiment of the present application is shown;

[0100] Figure 5Shows a block diagram of the composition of a boiler soot blowing device for a coal-fired unit provided by an embodiment of the present application;

[0101] Figure 6 Shows a schematic structural diagram of a computer device provided by an embodiment of the present invention.

[0102] Among them,

[0103] Figure 5 In it: 502 - Water-cooled wall entropy generation acquisition module without soot blowing; 504 - Heating surface entropy generation acquisition module without soot blowing; 506 - Water-cooled wall entropy generation acquisition module with soot blowing; 508 - Heating surface entropy generation acquisition module with soot blowing;

[0104] Figure 6 In it: 602 - Processor; 604 - Communication interface; 606 - Memory; 608 - Communication bus; 610 - Program. Specific embodiments

[0105] The present invention will be described in detail below with reference to the drawings and in combination with embodiments. It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0106] To further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following combines the drawings and preferred embodiments to detail the specific embodiments, structures, features, and their effects of the application according to the present invention. In the following description, different "one embodiment" or "embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0107] Regarding the problem that the number of soot blowing times in the current boiler soot blowing method is fixed and cannot be determined in combination with the actual situation, an embodiment of the present application provides a boiler soot blowing method for a coal-fired unit, as Figure 1 shown, the method includes:

[0108] 102: Obtain the first flame image in the furnace without soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the first flame image to obtain the first radiation characteristic parameters and the first temperature distribution value, and calculate based on the first radiation characteristic parameters and the first temperature distribution value to obtain the first in-furnace medium radiation entropy generation and the first water-cooled wall surface radiation heat transfer entropy generation without soot blowing;

[0109] 104: Obtain the first basic data of the heating surface without soot blowing, and calculate based on the first basic data to obtain the first total heat transfer entropy generation and the first total flow resistance entropy generation without soot blowing;

[0110] 106: Obtain the second flame image in the furnace during soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image to obtain the second radiation characteristic parameters and the second temperature distribution value, and perform calculations based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second in-furnace medium radiation entropy generation and the second water-cooled wall surface radiation heat transfer entropy generation during soot blowing;

[0111] 108: Obtain the second basic data of the heating surface during soot blowing, perform calculations based on the second basic data to obtain the second total heat transfer entropy generation and the second total flow resistance entropy generation during soot blowing, obtain the working medium data of soot blowing, and perform calculations based on the working medium data to obtain the steam heat dissipation entropy generation, mass transfer entropy generation, and motor entropy generation during soot blowing;

[0112] 110: Based on the first in-furnace medium radiation entropy generation, the first water-cooled wall surface radiation heat transfer entropy generation, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second in-furnace medium radiation entropy generation, the second water-cooled wall surface radiation heat transfer entropy generation, the second total heat transfer entropy generation, the second total flow resistance entropy generation, steam heat dissipation entropy generation, mass transfer entropy generation, and motor entropy generation, construct a soot blowing revenue model with the maximum pure soot blowing revenue as the goal, solve the soot blowing revenue model, and obtain the optimal number of soot blowing times.

[0113] In this embodiment, use a high-temperature camera to take the first flame image in the furnace when not performing soot blowing. According to Wien's radiation law and the radiation imaging model, obtain the first radiation intensity image and the first radiation temperature image. Use the Lasso regularization method to calculate the in-furnace temperature distribution from the first radiation temperature image, use the gradient descent method to obtain the numerical values of the radiation characteristics, substitute the finally obtained first temperature distribution value and the first radiation characteristic parameters into the medium radiation entropy generation formula to obtain the first in-furnace medium radiation entropy generation, and substitute the finally obtained first temperature distribution value and the first radiation characteristic parameters into the radiation heat transfer entropy generation formula to obtain the first water-cooled wall surface radiation heat transfer entropy generation.

[0114] Use a high-temperature camera to take the second flame image in the furnace during soot blowing. According to Wien's radiation law and the radiation imaging model, obtain the second radiation intensity image and the second radiation temperature image. Use the Lasso regularization method to calculate the in-furnace temperature distribution from the second radiation temperature image, use the gradient descent method to obtain the numerical values of the radiation characteristics, substitute the finally obtained second temperature distribution value and the second radiation characteristic parameters into the medium radiation entropy generation formula to obtain the second in-furnace medium radiation entropy generation, and substitute the finally obtained second temperature distribution value and the second radiation characteristic parameters into the radiation heat transfer entropy generation formula to obtain the second water-cooled wall surface radiation heat transfer entropy generation.

[0115] From the perspective of irreversible thermodynamics, irreversible energy losses, i.e., heat transfer entropy generation, will occur in each heating surface of the boiler during the convective heat transfer process due to the existence of temperature differences. Irreversible energy losses, i.e., flow resistance entropy generation, will occur during the flow process due to the existence of flow resistance. Calculate the first heat transfer entropy generation, the first flow resistance entropy generation when not sootblowing, and the second heat transfer entropy generation and the second flow resistance entropy generation when sootblowing respectively.

[0116] When the boiler uses steam sootblowing, steam is purged onto the heating surfaces in the furnace during the sootblowing process, and irreversible energy losses, i.e., mass transfer entropy generation, will occur due to the rapid mixing of steam and flue gas. During the operation of the boiler, motor work entropy generation, etc. also occurs in the driving motor of the sootblower due to the existence of irreversibility during the process of converting electrical energy into mechanical energy.

[0117] The sootblowing benefit is equivalent to the decrease values of the entropy generation of the water wall, the heat transfer entropy generation of the heating surfaces, and the flow resistance entropy generation before and after sootblowing. The sootblowing cost is equivalent to the sum of the mass transfer entropy generation, the sootblowing heat dissipation entropy generation, and the sootblower motor entropy generation generated by sootblowing. The net sootblowing benefit is the difference between the sootblowing benefit and the sootblowing cost. Based on the first in-furnace medium radiation entropy generation, the first water wall surface radiation heat transfer entropy generation, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second in-furnace medium radiation entropy generation, the second water wall surface radiation heat transfer entropy generation, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation, and the motor entropy generation, a sootblowing benefit model is constructed with the maximum net sootblowing benefit as the goal, and the net sootblowing benefit model is solved to obtain the optimal number of sootblowing times.

[0118] The present application provides a boiler sootblowing method for a coal-fired unit. Compared with the prior art, starting from the second law of thermodynamics, the entropy generation during the normal operation and sootblowing process of the water wall and each heating surface of the boiler is analyzed, fully considering the irreversible energy losses in the heat transfer process and the sootblowing process. With the maximum net sootblowing benefit as the goal, a sootblowing benefit model is constructed, and the net sootblowing benefit model is solved to obtain the optimal number of sootblowing times. The optimal number of sootblowing times is proposed from multiple dimensions of economy, safety, and environmental protection to achieve the maximization of the sootblowing benefit in the true sense.

[0119] In one embodiment, as Figure 2 shown, obtain the first flame image in the furnace when not sootblowing, calculate the radiation characteristic parameters and the temperature field distribution based on the first flame image, and obtain the first radiation characteristic parameters and the first temperature distribution values, including:

[0120] 202: Obtain the first flame image in the furnace when not sootblowing, and convert the first flame image into the first radiation intensity image based on the conversion relationship between pixel points and radiation intensity;

[0121] 204: Based on Wien's law, inversely deduce the temperature of each pixel point in the first radiation intensity image to obtain the first radiation temperature image;

[0122] 206: Initially set the first radiation characteristic parameter. Based on the initially set first radiation characteristic parameter and the relationship between the first radiation temperature image and the true temperature field, establish the first mathematical model of temperature distribution. Add a regularization constraint to the first mathematical model of temperature distribution to obtain the first objective function, and solve the first objective function to obtain the first temperature distribution value;

[0123] 208: Based on the first temperature distribution value and the preset radiation transfer equation, establish the first forward model of simulated radiation intensity. Based on the first forward model of simulated radiation intensity and the actual intensity value in the first radiation intensity image, construct the second objective function, and solve the second objective function to obtain the first radiation characteristic parameter;

[0124] 210: Substitute the first radiation characteristic parameter into the first objective function, solve the first objective function to obtain a new first temperature distribution value, substitute the new first temperature distribution value into the second objective function, solve the second objective function to obtain a new first radiation characteristic parameter, and repeat this process until the iteration condition is met, so as to obtain the optimal first temperature distribution value and the optimal first radiation characteristic parameter.

[0125] In this embodiment, high-temperature cameras are arranged along the furnace height direction to capture the flame conditions in the furnace. The arrangement positions of the high-temperature cameras are: at the furnace bottom, one layer is arranged above each layer of sootblowers, and one layer is arranged at the furnace outlet.

[0126] Take the first flame image inside the furnace when soot blowing is not carried out by a high-temperature camera. Each pixel value corresponds to the brightness of the flame (gray value or RGB value). Based on the conversion relationship formula between the pixel value and the radiation intensity, map the pixel value of each pixel point to the actual radiation intensity to obtain the first radiation intensity image. Based on Wien's law, solve the temperature of each pixel point based on the radiation intensity of each pixel point to obtain the first radiation temperature image. Set the initial values of the first medium absorption coefficient and the first medium scattering coefficient. Based on the relationship between the initial values of the first medium absorption coefficient, the first medium scattering coefficient, the first radiation temperature image, and the true temperature field, establish the first mathematical model of temperature distribution. Introduce the L1 or L2 regularization term constraint solution in the first mathematical model of temperature distribution to obtain the first objective function. Use an optimization algorithm to solve the first objective function to obtain the first temperature distribution value. Based on the radiation transfer equation, use the first temperature distribution value and the preset radiation transfer equation to construct the first forward model of simulated radiation intensity. Calculate the error between the intensity actual value in the first forward model of simulated radiation intensity and the first radiation intensity image. Take the minimum error as the second objective function and solve the second objective function to obtain the new first medium absorption coefficient and the new first medium scattering coefficient. Based on the relationship between the new first medium absorption coefficient, the new first medium scattering coefficient, and the true temperature field, establish the new first mathematical model of temperature distribution. Repeat the above process until the iteration condition is reached. Take the first medium absorption coefficient and the first medium scattering coefficient obtained last time as the optimal first medium absorption coefficient and the optimal first medium scattering coefficient.

[0127] In this embodiment, the first radiation characteristic parameters include the first medium absorption coefficient and the first medium scattering coefficient. The following formula is used to calculate the radiation entropy production of the first in-furnace medium:

[0128]

[0129] The following formula is used to calculate the radiation heat transfer entropy production of the first water-cooled wall surface:

[0130]

[0131] where, T 01 is the ambient temperature when soot blowing is not carried out; q is the radiation heat flux density between the medium and the water-cooled wall surface; V is the volume of the boiler furnace; K j1 is the first medium absorption coefficient; σ1 is the first medium scattering coefficient; I1 is the blackbody monochromatic spectral radiation intensity; I2 is the monochromatic spectral radiation intensity; T p is the Planck temperature; T1 is the in-furnace medium temperature when soot blowing is not carried out; λ is the wavelength; I3 is the monochromatic spectral scattering intensity; φ is the radiation phase function; n is the normal vector of the water-cooled wall surface; θ is the solid angle; L is the spectral radiation intensity of the water-cooled wall surface; I4 is the spectral radiation intensity at wavelength λ; A is the area of the water-cooled wall.

[0132] Specifically, among the various heating surfaces of the boiler unit, except for the furnace water wall heat transfer which is mainly radiation heat transfer, the rest of the heating surfaces are mainly convective heat transfer.

[0133] Entropy is one of the parameters characterizing the state of matter in thermodynamics, used to measure the degree of disorder of a system or the uniformity of energy distribution. The larger the entropy value, the higher the degree of disorder of the system. Entropy production is the entropy increment generated by the system in irreversible processes (such as heat dissipation, mixing, friction, etc.), reflecting the degree of irreversibility of the process.

[0134] From the perspective of irreversible thermodynamics, irreversible energy losses will occur during the convective heat transfer process of each heating surface of the boiler due to the existence of temperature differences, that is, heat transfer entropy production. When not sootblowing, the first heat transfer entropy production is generated. During the flow process, irreversible energy losses will occur due to the existence of flow resistance, that is, flow resistance entropy production. When not sootblowing, the first flow resistance entropy production is generated.

[0135] For a certain convective heating surface, when the boiler is operating normally and not sootblowing it, only heat transfer entropy production and flow resistance entropy production exist.

[0136] In one embodiment, the following formula is used to calculate the first total heat transfer entropy production:

[0137]

[0138] ΔS ΔT1 =n1zΔS g,ΔT1

[0139] Where, ΔS g,ΔT1 is the first heat transfer entropy production of a tube row, K z is the total heat transfer coefficient; T ∞ 1 is the average flue gas temperature at the inlet and outlet when not sootblowing; d i is the inner diameter of the tube; C pi 1 is the specific heat of the steam when not sootblowing; G 1 is the steam flow rate when not sootblowing; l is the tube length; T fii 1 is the steam inlet temperature when not sootblowing; n1 is the number of tube rows; z is the number of tube coils, ΔS ΔT1 is the first total heat transfer entropy production;

[0140] The following formula is used to calculate the first total flow resistance entropy production:

[0141]

[0142] ΔS Δp1 =n1zΔS g,ΔP1

[0143] Where, ΔS g,ΔP1The first flow-blocking entropy generation of a tube bank, ΔS Δp1 is the first total flow-blocking entropy generation,

[0144] U ∞ 1 is the average velocity of flue gas flow when soot blowing is not performed; T o1 is the ambient temperature when soot blowing is not performed; C D 1 is the local resistance coefficient when soot blowing is not performed.

[0145] The total entropy generation of the heating surface when soot blowing is not performed:

[0146] N1 = T 01 (ΔS ΔT1 +ΔS Δp1 ) / dq.

[0147] In one embodiment, as Figure 3 shown, obtain the second flame image in the furnace during soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image, and obtain the second radiation characteristic parameters and the second temperature distribution value, including:

[0148] 302: Obtain the second flame image in the furnace during soot blowing, and convert the second flame image into a second radiation intensity image based on the conversion relationship between pixel points and radiation intensity;

[0149] 304: Based on Wien's law, inversely deduce the temperature of each pixel point in the second radiation intensity image to obtain a second radiation temperature image;

[0150] 306: Make an initial setting for the second radiation characteristic parameters, establish a second temperature distribution mathematical model based on the relationship between the initially set second radiation characteristic parameters and the second radiation temperature image and the real temperature field, add regularization constraints to the second temperature distribution mathematical model to obtain a third objective function, and solve the third objective function to obtain the second temperature distribution value;

[0151] 308: Based on the second temperature distribution value and the preset radiation transfer equation, establish a second simulated radiation intensity forward model, construct a fourth objective function based on the second simulated radiation intensity forward model and the actual intensity value in the second radiation intensity image, and solve the fourth objective function to obtain the second radiation characteristic parameters;

[0152] 310: Substitute the second radiation characteristic parameters into the third objective function, solve the third objective function to obtain a new second temperature distribution value, substitute the new second temperature distribution value into the fourth objective function, solve the fourth objective function to obtain a new second radiation characteristic parameter, and repeat until the iteration condition is reached to obtain the optimal second temperature distribution value and the optimal second radiation characteristic parameter.

[0153] In this embodiment, a second flame image inside the furnace when soot blowing is not performed is captured by a high-temperature camera, and each pixel value corresponds to the brightness of the flame (gray value or RGB value). Based on the conversion relationship formula between the pixel value and the radiation intensity, the pixel value of each pixel point is mapped to the actual radiation intensity to obtain a second radiation intensity image. Based on Wien's law, the temperature of each pixel point is solved based on the radiation intensity of each pixel point to obtain a second radiation temperature image. The initial values of the second medium absorption coefficient and the second medium scattering coefficient are set, and based on the relationship between the initial values of the second medium absorption coefficient and the second medium scattering coefficient, the second radiation temperature image and the true temperature field, a second temperature distribution mathematical model is established. An L1 or L2 regularization term is introduced in the second temperature distribution mathematical model to constrain the solution, obtaining a third objective function. An optimization algorithm is used to solve the third objective function to obtain a second temperature distribution value. Based on the radiation transfer equation, a second simulated radiation intensity forward model is constructed using the second temperature distribution value and a preset radiation transfer equation. The error between the intensity actual value in the second simulated radiation intensity forward model and the second radiation intensity image is calculated. Taking the minimum error as the fourth objective function, the fourth objective function is solved to obtain new second medium absorption coefficient and second medium scattering coefficient. Based on the relationship between the new second medium absorption coefficient and second medium scattering coefficient and the true temperature field, a new second temperature distribution mathematical model is established. The above process is repeated until the iteration condition is reached, and the second medium absorption coefficient and second medium scattering coefficient obtained last time are used as the optimal second medium absorption coefficient and second medium scattering coefficient.

[0154] In this embodiment, the second radiation characteristic parameters include the second medium absorption coefficient and the second medium scattering coefficient, and the following formula is used to calculate the radiation entropy generation of the second in-furnace medium:

[0155]

[0156] The following formula is used to calculate the radiation heat transfer entropy generation of the second water-cooled wall surface:

[0157]

[0158] where, T 02 is the ambient temperature during soot blowing; q is the radiation heat flux density between the medium and the water-cooled wall surface; V is the volume of the boiler furnace; K j2 is the second medium absorption coefficient; σ2 is the second medium scattering coefficient; I1 is the blackbody monochromatic spectral radiation intensity; I2 is the monochromatic spectral radiation intensity; T p is the Planck temperature; T2 is the in-furnace medium temperature during soot blowing; λ is the wavelength; I3 is the monochromatic spectral scattering intensity; φ is the radiation phase function; n is the normal vector of the water-cooled wall surface; θ is the solid angle; L is the spectral radiation intensity of the water-cooled wall surface; I4 is the spectral radiation intensity at wavelength λ; A is the area of the water-cooled wall.

[0159] From the perspective of irreversible thermodynamics, irreversible energy losses, i.e., heat transfer entropy generation, will occur during the convective heat transfer process in each heating surface of the boiler due to the temperature difference. When soot blowing is carried out, a second heat transfer entropy generation is generated. During the flow process, irreversible energy losses, i.e., flow resistance entropy generation, will occur due to the existence of flow resistance. When soot blowing is carried out, a second flow resistance entropy generation is generated. When steam soot blowing is adopted in the boiler, steam is purged onto the heating surface in the furnace during the soot blowing process, and irreversible energy losses, i.e., mass transfer entropy generation, will occur due to the rapid mixing of steam and flue gas. The irreversible energy losses generated during the heat dissipation process of steam are the steam heat dissipation entropy generation. During the operation of the boiler, the driving motor of the soot blower also generates motor work entropy generation due to the existence of irreversibility during the process of converting electrical energy into mechanical energy.

[0160] By calculating the mass transfer entropy generation, motor entropy generation, and steam heat dissipation entropy generation, the energy losses of the irreversible process of the thermodynamic analysis quantification system can be obtained, and then the economy of the soot blowing system can be optimized.

[0161] For a certain convective heating surface, when the boiler is operating normally and no soot blowing is carried out on it, only heat transfer entropy generation and flow resistance entropy generation exist; when soot blowing is carried out on the boiler, the soot blowing process will consume soot blowing steam and electrical energy. At this time, in addition to heat transfer entropy generation and flow resistance entropy generation, there will also be mass transfer entropy generation, soot blowing medium entropy generation, and soot blower motor entropy generation.

[0162] The following formula is used to calculate the second total heat transfer entropy generation:

[0163]

[0164] ΔS ΔT2 =n1zΔS g,ΔT2

[0165] Among them, ΔS g,ΔT2 is the second heat transfer entropy generation of a tube bank, K z is the total heat transfer coefficient; T ∞ 2 is the average flue gas temperature at the inlet and outlet during soot blowing; d i is the inner diameter of the tube; C pi 2 is the specific heat of the steam during soot blowing; G 2 is the steam flow rate during soot blowing; l is the tube length; T fii 2 is the steam inlet temperature during soot blowing; n1 is the number of tube banks; z is the number of tube coils, ΔS ΔT2 is the second total heat transfer entropy generation;

[0166] The following formula is used to calculate the second total flow resistance entropy generation:

[0167]

[0168] ΔSΔp2 = n1zΔS g,ΔP2

[0169] where ΔS g,ΔP2 is the second flow resistance entropy production of a tube bank, and ΔS Δp2 is the second total flow resistance entropy production.

[0170] U ∞ 2 is the average velocity of flue gas flow without soot blowing; T o2 is the ambient temperature during soot blowing; C D 2 is the local resistance coefficient during soot blowing.

[0171] In one embodiment, the following formula is used to calculate the entropy production of steam heat dissipation:

[0172] △S q = m(S2 - S1)

[0173] where m is the consumption of soot blowing steam; S1 is the specific entropy of steam in the first state; S2 is the specific entropy of steam in the second state;

[0174] The following formula is used to calculate the entropy production of mass transfer:

[0175] △S g = G 2 (C pi 2 ln(T’ / T0’) - R(lnP i / P0))

[0176] where C pi 2 is the specific heat of steam during soot blowing; G 2 is the steam flow rate during soot blowing; T0’ is the temperature of steam before mixing; T’ is the temperature of steam after mixing; R is the gas constant; P i is the pressure of the working fluid before mixing; P0 is the partial pressure of the working fluid after mixing;

[0177] The following formula is used to calculate the entropy production of the motor:

[0178] △S m = P / T q )

[0179] where P is the power of the soot blower motor; T q is the temperature of the working fluid used in the steam soot blower.

[0180] The total entropy production of the boiler heating surface during soot blowing:

[0181] N2 = T 02 (ΔS ΔT2 +ΔSΔp2 +ΔS g +ΔS q +ΔS m ) / dq。

[0182] As Figure 4 shown, after capturing the actual flame image in the furnace, according to Wien's radiation law and the radiation imaging model, the radiation intensity image and the radiation temperature image are obtained, the values of the radiation characteristic parameters are initialized, the temperature distribution in the furnace is calculated from the radiation temperature image using the Lasso regularization method, the values of the radiation characteristics are obtained using the gradient descent method, it is judged whether the convergence condition is reached. If the convergence condition is not reached, based on the calculated temperature distribution values and the values of the radiation characteristic parameters, recalculation is performed to obtain new temperature distribution values and values of the radiation characteristic parameters, and this process is repeated until the iteration condition is reached. The final temperature distribution value is taken as the optimal temperature distribution value, and the final value of the radiation characteristic parameter is taken as the optimal radiation characteristic parameter.

[0183] In one embodiment, based on the first radiative entropy generation of the furnace internal medium, the first radiative heat transfer entropy generation of the water-cooled wall surface, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second radiative entropy generation of the furnace internal medium, the second radiative heat transfer entropy generation of the water-cooled wall surface, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation, and the motor entropy generation, with the maximum sootblowing net benefit as the objective, a sootblowing benefit model is constructed, including:

[0184] Based on the first radiative entropy generation of the furnace internal medium, the first radiative heat transfer entropy generation of the water-cooled wall surface, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second radiative entropy generation of the furnace internal medium, the second radiative heat transfer entropy generation of the water-cooled wall surface, the second total heat transfer entropy generation, and the second total flow resistance entropy generation, a sootblowing benefit model of entropy generation is constructed;

[0185] Based on the steam heat dissipation entropy generation, the mass transfer entropy generation, and the motor entropy generation, a sootblowing expenditure model of entropy generation is constructed;

[0186] Based on the sootblowing benefit model and the sootblowing expenditure model, with the maximum sootblowing net benefit as the objective, a sootblowing benefit model is constructed.

[0187] Specifically, the sootblowing benefit is equivalent to the decrease values of the entropy generation of the water-cooled wall, the heat transfer entropy generation of the heating surface, and the flow resistance entropy generation before and after sootblowing. The sootblowing expenditure is equivalent to the sum of the mass transfer entropy generation, the sootblowing heat dissipation entropy generation, and the sootblowing device motor entropy generation caused by sootblowing. And the net benefit of sootblowing is the difference between the sootblowing benefit and the sootblowing expenditure. Finally, determining the maximum value of the sootblowing net benefit can obtain the optimal sootblowing frequency.

[0188] Sootblowing benefit of entropy generation: Nin = T 01 (ΔS ΔT1 -ΔS ΔT2 +ΔS Δp1 -ΔSΔp2 +D jz1 -Djz2 + Dslb1 - Dslb2 / dq

[0189] Entropy production sootblowing expenditure: Nout = T 02 (ΔS g +ΔS q +ΔS m ) / dq

[0190] During the time period from t0 to t0 + △t, the net income from n0 sootblowings is:

[0191] The sootblowing income model is:

[0192]

[0193] where t0 is the time of t0, t0 + △t is the time of t0 + △t; N in is the sootblowing income model, N out is the sootblowing expenditure model, and n0 is the optimal number of sootblowings.

[0194] The net sootblowing income ΔNs > 0, and sootblowing can bring certain economic benefits. When the number of sootblowings exceeds the critical number n s , at this time the net sootblowing income ΔNs < 0, and sootblowing is uneconomical. The main goal of optimizing sootblowing is to find an optimal sootblowing frequency n0 within the maximum number of sootblowings, so that the net sootblowing income is maximized at this time.

[0195] Furthermore, as an implementation of the method shown above Figure 1 , an embodiment of the present invention provides a boiler sootblowing device for a coal-fired unit, as Figure 5 shown, the device includes:

[0196] The water-cooled wall entropy production acquisition module 502 that does not perform sootblowing is used to acquire the first flame image in the furnace when not performing sootblowing, calculate the radiation characteristic parameters and temperature field distribution based on the first flame image, obtain the first radiation characteristic parameters and the first temperature distribution value, and calculate based on the first radiation characteristic parameters and the first temperature distribution value to obtain the first in-furnace medium radiation entropy production and the first water-cooled wall surface radiation heat transfer entropy production when not performing sootblowing;

[0197] The heating surface entropy production acquisition module 504 that does not perform sootblowing is used to acquire the first basic data of the heating surface when not performing sootblowing, and calculate based on the first basic data to obtain the first total heat transfer entropy production and the first total flow resistance entropy production when not performing sootblowing;

[0198] The soot blowing water-cooled wall entropy generation acquisition module 506 is used to obtain the second flame image in the furnace during soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image, obtain the second radiation characteristic parameters and the second temperature distribution value, and calculate based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second in-furnace medium radiation entropy generation and the second water-cooled wall surface radiation heat transfer entropy generation during soot blowing;

[0199] The heating surface entropy generation acquisition module 508 for soot blowing is used to obtain the second basic data of the heating surface during soot blowing, calculate based on the second basic data to obtain the second total heat transfer entropy generation and the second total flow resistance entropy generation during soot blowing, obtain the working medium data for soot blowing, and calculate based on the working medium data to obtain the steam heat dissipation entropy generation, mass transfer entropy generation and motor entropy generation during soot blowing;

[0200] The optimal soot blowing times acquisition module 510 is used to construct a soot blowing benefit model with the maximum soot blowing net benefit as the goal based on the first in-furnace medium radiation entropy generation, the first water-cooled wall surface radiation heat transfer entropy generation, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second in-furnace medium radiation entropy generation, the second water-cooled wall surface radiation heat transfer entropy generation, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation and the motor entropy generation, and solve the soot blowing benefit model to obtain the optimal soot blowing times.

[0201] The present application provides a boiler soot blowing device for a coal-fired unit. Starting from the second law of thermodynamics, it analyzes the entropy generation during the normal operation and soot blowing process of the water-cooled wall and each heating surface of the boiler, fully considers the irreversible energy loss in the heat transfer process and the soot blowing process, constructs a soot blowing benefit model with the maximum soot blowing net benefit as the goal, solves the net benefit model of this soot blowing, obtains the optimal soot blowing times, and proposes the optimal soot blowing times from multiple dimensions of economy, safety and environmental protection to achieve the maximization of the soot blowing benefit in the true sense.

[0202] In one embodiment, the water-cooled wall entropy generation acquisition module without soot blowing is further used for:

[0203] Obtain the first flame image in the furnace without soot blowing, and convert the first flame image into the first radiation intensity image based on the conversion relationship between the pixel point and the radiation intensity;

[0204] Based on Wien's law, perform temperature back-calculation for each pixel point in the first radiation intensity image to obtain the first radiation temperature image;

[0205] Make an initial setting for the first radiation characteristic parameters, establish a first temperature distribution mathematical model based on the relationship between the initially set first radiation characteristic parameters and the first radiation temperature image and the real temperature field, add regularization constraints to the first temperature distribution mathematical model to obtain the first objective function, and solve the first objective function to obtain the first temperature distribution value;

[0206] Establish a first forward model of simulated radiation intensity based on the first temperature distribution value and the preset radiation transfer equation. Construct a second objective function based on the first forward model of simulated radiation intensity and the actual intensity values in the first radiation intensity image, and solve the second objective function to obtain the first radiation characteristic parameters;

[0207] Substitute the first radiation characteristic parameters into the first objective function, solve the first objective function to obtain a new first temperature distribution value, substitute the new first temperature distribution value into the second objective function, solve the second objective function to obtain a new first radiation characteristic parameter, and repeat until the iteration condition is met to obtain the optimal first temperature distribution value and the optimal first radiation characteristic parameters.

[0208] In one embodiment, the first radiation characteristic parameters include the first medium absorption coefficient and the first medium scattering coefficient. The following formula is used to calculate the radiation entropy production of the medium in the first furnace:

[0209]

[0210] The following formula is used to calculate the radiation heat transfer entropy production of the first water wall surface:

[0211]

[0212] where, T 01 is the ambient temperature when no soot blowing is performed; q is the radiation heat flux density between the medium and the water wall surface; V is the volume of the boiler furnace; K j1 is the first medium absorption coefficient; σ1 is the first medium scattering coefficient; I1 is the blackbody monochromatic spectral radiation intensity; I2 is the monochromatic spectral radiation intensity; T p is the Planck temperature; T1 is the temperature of the medium in the furnace when no soot blowing is performed; λ is the wavelength; I3 is the monochromatic spectral scattering intensity; φ is the radiation phase function; n is the normal vector of the water wall surface; θ is the solid angle; L is the spectral radiation intensity of the water wall surface; I4 is the spectral radiation intensity at wavelength λ; A is the area of the water wall.

[0213] In one embodiment, the optimal soot blowing times acquisition module is further configured to:

[0214] Based on the first radiation entropy production of the medium in the furnace, the first radiation heat transfer entropy production of the water wall surface, the first total heat transfer entropy production, the first total flow resistance entropy production, the second radiation entropy production of the medium in the furnace, the second radiation heat transfer entropy production of the water wall surface, the second total heat transfer entropy production, and the second total flow resistance entropy production, construct a soot blowing benefit model of entropy production;

[0215] Based on the steam heat dissipation entropy production, the mass transfer entropy production, and the motor entropy production, construct a soot blowing expenditure model of entropy production;

[0216] Based on the soot blowing revenue model and the soot blowing expenditure model, with the maximum net soot blowing revenue as the goal, a soot blowing revenue model is constructed.

[0217] In one embodiment, the soot blowing revenue model is:

[0218]

[0219] where t0 is the time of t0, and t0 + Δt is the time of t0 + Δt; N in is the soot blowing revenue model, N out is the soot blowing expenditure model, and n0 is the optimal number of soot blowing times.

[0220] In one embodiment, the following formula is used to calculate the first total heat transfer entropy generation:

[0221]

[0222] ΔS ΔT1 = n1zΔS g,ΔT1

[0223] where ΔS g,ΔT1 is the first heat transfer entropy generation of a tube row, K z is the total heat transfer coefficient; T ∞ 1 is the average flue gas temperature at the inlet and outlet without soot blowing; d i is the inner diameter of the tube; C pi 1 is the specific heat of steam without soot blowing; G 1 is the steam flow rate without soot blowing; l is the tube length; T fii 1 is the steam inlet temperature without soot blowing; n1 is the number of tube rows; z is the number of tube circles, and ΔS ΔT1 is the first total heat transfer entropy generation;

[0224] The following formula is used to calculate the first total flow resistance entropy generation:

[0225]

[0226] ΔS Δp1 = n1zΔS g,ΔP1

[0227] where ΔS g,ΔP1 is the first flow resistance entropy generation of a tube row, and ΔS Δp1 is the first total flow resistance entropy generation,

[0228] U ∞ 1 is the average velocity of flue gas flow without soot blowing; T o1 is the ambient temperature without soot blowing; C D 1is the local resistance coefficient when soot blowing is not performed.

[0229] In one embodiment, the following formula is used to calculate the steam heat dissipation entropy production:

[0230] △S q = m(S2 - S1)

[0231] where m is the soot blowing steam consumption; S1 is the specific entropy of the steam in the first state; S2 is the specific entropy of the steam in the second state;

[0232] The following formula is used to calculate the mass transfer entropy production:

[0233] △S g = G 2 (C pi 2 ln(T’ / T0’)-R(lnP i / P0))

[0234] where C pi 2 is the specific heat of the steam during soot blowing; G 2 is the steam flow rate during soot blowing; T0’ is the temperature of the steam before mixing; T’ is the temperature of the steam after mixing; R is the gas constant; P i is the pressure of the working fluid before mixing; P0 is the partial pressure of the working fluid after mixing;

[0235] The following formula is used to calculate the motor entropy production:

[0236] △S m = P / T q

[0237] where P is the power of the soot blower motor; T q is the temperature of the working fluid used in the steam soot blower.

[0238] According to an embodiment of the present invention, a storage medium is provided. The storage medium stores at least one executable instruction, and the computer executable instruction can execute the boiler soot blowing method of the coal-fired unit in any of the above method embodiments.

[0239] Figure 6 FIG. shows a schematic structural diagram of a computer device provided according to an embodiment of the present invention. The specific implementation of the computer device is not limited in the specific embodiments of the present invention.

[0240] As Figure 6 shown, the computer device may include: a processor 602, a communication interface 604, a memory 606, and a communication bus 608.

[0241] Among them: The processor 602, the communication interface 604, and the memory 606 communicate with each other through the communication bus 608.

[0242] The communication interface 604 is used to communicate with network elements of other devices such as clients or other servers.

[0243] The processor 602 is used to execute the program 610, and specifically can execute the relevant steps in the above-mentioned embodiments of the boiler soot blowing method for coal-fired units.

[0244] Specifically, the program 610 may include program codes, and the program codes include computer operation instructions.

[0245] The processor 602 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. The computer device includes one or more processors, which may be of the same type of processor, such as one or more CPUs; or may be of different types of processors, such as one or more CPUs and one or more ASICs.

[0246] The memory 606 is used to store the program 610. The memory 606 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory.

[0247] The program 610 is specifically used to enable the processor 602 to perform the following operations:

[0248] Obtain the first flame image in the furnace when not soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the first flame image, obtain the first radiation characteristic parameters and the first temperature distribution value, and calculate based on the first radiation characteristic parameters and the first temperature distribution value to obtain the first radiation entropy production of the furnace medium and the first radiation heat transfer entropy production of the water wall surface when not soot blowing;

[0249] Obtain the first basic data of the heating surface when not soot blowing, and calculate based on the first basic data to obtain the first total heat transfer entropy production and the first total flow resistance entropy production when not soot blowing;

[0250] Obtain the second flame image in the furnace when soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image, obtain the second radiation characteristic parameters and the second temperature distribution value, and calculate based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second radiation entropy production of the furnace medium and the second radiation heat transfer entropy production of the water wall surface when soot blowing;

[0251] Obtain the second basic data of the heating surface during soot blowing, perform calculations based on the second basic data to obtain the second total heat transfer entropy generation and the second total flow resistance entropy generation during soot blowing, obtain the working fluid data of soot blowing, and perform calculations based on the working fluid data to obtain the steam heat dissipation entropy generation, mass transfer entropy generation, and motor entropy generation during soot blowing;

[0252] Based on the first in-furnace medium radiation entropy generation, the first water wall surface radiation heat transfer entropy generation, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second in-furnace medium radiation entropy generation, the second water wall surface radiation heat transfer entropy generation, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation, and the motor entropy generation, with the maximum pure soot blowing benefit as the goal, construct a soot blowing benefit model, solve the soot blowing benefit model, and obtain the optimal number of soot blowing times.

[0253] Obviously, those skilled in the art should understand that the above-mentioned modules or steps of the present invention can be implemented by a general computing device. They can be concentrated on a single computing device or distributed on a network composed of multiple computing devices. In one embodiment, they can be implemented by program codes executable by the computing device. Thus, they can be stored in a storage device and executed by the computing device. And in some cases, the steps shown or described can be executed in a different order than here, or they can be separately made into individual integrated circuit modules, or multiple of them can be made into a single integrated circuit module to implement. In this way, the present invention is not limited to any specific combination of hardware and software.

[0254] The above embodiments are only exemplary embodiments of the present application and are not used to limit the present application. The protection scope of the present application is defined by the claims. Those skilled in the art can make various modifications or equivalent replacements within the essence and protection scope of the present application, and such modifications or equivalent replacements should also be regarded as falling within the protection scope of the present application.

Claims

1. A boiler soot blowing method for a coal-fired unit, characterized in that, Including: Obtain the first flame image in the furnace when soot blowing is not performed, calculate the radiation characteristic parameters and temperature field distribution based on the first flame image to obtain the first radiation characteristic parameters and the first temperature distribution value, and perform calculations based on the first radiation characteristic parameters and the first temperature distribution value to obtain the first radiative entropy generation of the in-furnace medium and the first radiative heat transfer entropy generation of the water wall surface when soot blowing is not performed; Obtain the first basic data of the heating surface when soot blowing is not performed, and perform calculations based on the first basic data to obtain the first total heat transfer entropy generation and the first total flow resistance entropy generation when soot blowing is not performed; Obtain the second flame image in the furnace when soot blowing is performed, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image to obtain the second radiation characteristic parameters and the second temperature distribution value, and perform calculations based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second radiative entropy generation of the in-furnace medium and the second radiative heat transfer entropy generation of the water wall surface when soot blowing is performed; Obtain the second basic data of the heating surface when soot blowing is performed, perform calculations based on the second basic data to obtain the second total heat transfer entropy generation and the second total flow resistance entropy generation when soot blowing is performed, obtain the working medium data of soot blowing, and perform calculations based on the working medium data to obtain the steam heat dissipation entropy generation, mass transfer entropy generation, and motor entropy generation when soot blowing is performed; Based on the first radiative entropy generation of the in-furnace medium, the first radiative heat transfer entropy generation of the water wall surface, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second radiative entropy generation of the in-furnace medium, the second radiative heat transfer entropy generation of the water wall surface, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation, and the motor entropy generation, construct a soot blowing benefit model with the maximum net soot blowing benefit as the goal, solve the soot blowing benefit model, and obtain the optimal number of soot blowing times.

2. The boiler soot blowing method of a coal-fired unit according to claim 1, characterized in that The obtaining of the first flame image in the furnace when soot blowing is not performed, calculating the radiation characteristic parameters and temperature field distribution based on the first flame image to obtain the first radiation characteristic parameters and the first temperature distribution value, includes: Obtain the first flame image in the furnace when soot blowing is not performed, and convert the first flame image into a first radiation intensity image based on the conversion relationship between pixel points and radiation intensity; Based on Wien's law, perform inverse temperature calculation for each pixel point in the first radiation intensity image to obtain the first radiation temperature image; Perform initial setting on the first radiation characteristic parameters, establish a first temperature distribution mathematical model based on the initially set first radiation characteristic parameters and the relationship between the first radiation temperature image and the true temperature field, add regularization constraints to the first temperature distribution mathematical model to obtain a first objective function, and solve the first objective function to obtain the first temperature distribution value; Based on the first temperature distribution value and a preset radiation transfer equation, establish a first forward model of simulated radiation intensity, construct a second objective function based on the first forward model of simulated radiation intensity and the actual intensity value in the first radiation intensity image, and solve the second objective function to obtain the first radiation characteristic parameters; Substitute the first radiation characteristic parameter into the first objective function, solve the first objective function to obtain a new first temperature distribution value, substitute the new first temperature distribution value into the second objective function, solve the second objective function to obtain a new first radiation characteristic parameter, and repeat this process until the iteration condition is met, so as to obtain the optimal first temperature distribution value and the optimal first radiation characteristic parameter.

3. The boiler soot blowing method of a coal-fired unit according to claim 2, wherein The first radiation characteristic parameter includes the first medium absorption coefficient and the first medium scattering coefficient. The following formula is used to calculate the radiation entropy production of the medium in the first furnace: The following formula is used to calculate the radiation heat transfer entropy production of the first water-cooled wall surface: where, T 01 is the ambient temperature when soot blowing is not performed; q is the radiative heat flux density between the medium and the water wall surface; V is the volume of the boiler furnace; K j1 is the absorption coefficient of the first medium; σ1 is the scattering coefficient of the first medium; I1 is the blackbody monochromatic spectral radiation intensity; I2 is the monochromatic spectral radiation intensity; T p is the Planck temperature; T1 is the temperature of the furnace medium when soot blowing is not performed; λ is the wavelength; I3 is the monochromatic spectral scattering intensity; φ is the radiation phase function; n is the normal vector of the water wall surface; θ is the solid angle; L is the spectral radiation intensity of the water wall surface; I4 is the spectral radiation intensity at wavelength λ; A is the area of the water wall.

4. The boiler soot blowing method for a coal-fired unit according to claim 1, characterized in that, Based on the first furnace medium radiation entropy production, the first water-cooled wall surface radiation heat transfer entropy production, the first total heat transfer entropy production, the first total flow resistance entropy production, the second furnace medium radiation entropy production, the second water-cooled wall surface radiation heat transfer entropy production, the second total heat transfer entropy production, the second total flow resistance entropy production, the steam heat dissipation entropy production, the mass transfer entropy production, and the motor entropy production, a soot blowing benefit model is constructed with the maximum soot blowing net benefit as the goal, including: Based on the first furnace medium radiation entropy production, the first water-cooled wall surface radiation heat transfer entropy production, the first total heat transfer entropy production, the first total flow resistance entropy production, the second furnace medium radiation entropy production, the second water-cooled wall surface radiation heat transfer entropy production, the second total heat transfer entropy production, and the second total flow resistance entropy production, a soot blowing benefit model of entropy production is constructed; Based on the steam heat dissipation entropy production, the mass transfer entropy production, and the motor entropy production, a soot blowing expenditure model of entropy production is constructed; Based on the soot blowing benefit model and the soot blowing expenditure model, a soot blowing benefit model is constructed with the maximum soot blowing net benefit as the goal.

5. The boiler soot blowing method for a coal-fired unit according to claim 4, characterized in that, The soot blowing benefit model is: Among them, t0 is the time of t0, and t0+Δt is the time of t0+Δt; N in is the soot blowing revenue model, N out is the soot blowing expenditure model, and n0 is the optimal number of soot blowing times.

6. The boiler soot blowing method of a coal-fired unit according to any one of claims 1-5, characterized in that, The following formula is used to calculate the first total heat transfer entropy production: ΔS ΔT1 = n1zΔS g,ΔT1 Among them, ΔS g,ΔT1 is the first heat transfer entropy generation of a tube bank, K z is the overall heat transfer coefficient; T ∞ 1 is the average flue gas temperature at the inlet and outlet without soot blowing; d i is the inner diameter of the tube; C pi 1 is the specific heat of the steam without soot blowing; G 1 is the steam flow rate without soot blowing; l is the tube length; T fii 1 is the steam inlet temperature without soot blowing; n1 is the number of tube banks; z is the number of tube rows, ΔS ΔT1 is the first total heat transfer entropy generation; The following formula is used to calculate the first total flow resistance entropy production: ΔS Δp1 = n1zΔS g,ΔP1 Among them, ΔS g,ΔP1 is the first flow resistance entropy production of a tube bank, and ΔS Δp1 is the total first flow resistance entropy production. U ∞ 1 is the average velocity of the flue gas flow without soot blowing; T o1 is the ambient temperature without soot blowing; C D 1 is the local resistance coefficient without soot blowing.

7. The soot blowing method for the boiler of a coal-fired unit according to any one of claims 1-5, characterized in that The following formula is used to calculate the steam heat dissipation entropy production: △S q = m(S2 - S1) where m is the soot blowing steam consumption; S1 is the specific entropy of the steam in the first state; S2 is the specific entropy of the steam in the second state; The following formula is used to calculate the mass transfer entropy production: △S g = G 2 (C pi 2 ln(T’ / T0’)-R(lnP i / P0)) Among them, C pi 2 is the specific heat of steam during soot blowing; G 2 is the steam flow rate during soot blowing; T0’ is the temperature of steam before mixing; T’ is the temperature of steam after mixing; R is the gas constant; P i is the pressure of the working medium before mixing; P0 is the partial pressure of the working medium after mixing; The following formula is used to calculate the motor entropy production: △S m = P / T q Among them, P is the power of the soot blower motor; T q is the temperature of the working medium used by the steam soot blower.

8. A boiler sootblowing device for a coal-fired unit, characterized in that, including: A water-cooled wall entropy production acquisition module without soot blowing, which is used to obtain the first flame image in the furnace without soot blowing, calculate the radiation characteristic parameter and the temperature field distribution based on the first flame image to obtain the first radiation characteristic parameter and the first temperature distribution value, and calculate the first furnace medium radiation entropy production and the first water-cooled wall surface radiation heat transfer entropy production without soot blowing based on the first radiation characteristic parameter and the first temperature distribution value; A heating surface entropy production acquisition module without soot blowing, which is used to obtain the first basic data of the heating surface without soot blowing and calculate the first total heat transfer entropy production and the first total flow resistance entropy production without soot blowing based on the first basic data; The soot-blowing water-cooled wall entropy generation acquisition module is used to obtain the second flame image in the furnace during soot blowing, calculate the radiation characteristic parameters and temperature field distribution based on the second flame image, obtain the second radiation characteristic parameters and the second temperature distribution value, and calculate based on the second radiation characteristic parameters and the second temperature distribution value to obtain the second in-furnace medium radiation entropy generation and the second water-cooled wall surface radiation heat transfer entropy generation during soot blowing; The soot-blowing heating surface entropy generation acquisition module is used to obtain the second basic data of the heating surface during soot blowing, calculate based on the second basic data to obtain the second total heat transfer entropy generation and the second total flow resistance entropy generation during soot blowing, obtain the working medium data of soot blowing, and calculate based on the working medium data to obtain the steam heat dissipation entropy generation, mass transfer entropy generation and motor entropy generation during soot blowing; The optimal soot-blowing times acquisition module is used to construct a soot-blowing benefit model with the maximum soot-blowing net benefit as the goal based on the first in-furnace medium radiation entropy generation, the first water-cooled wall surface radiation heat transfer entropy generation, the first total heat transfer entropy generation, the first total flow resistance entropy generation, the second in-furnace medium radiation entropy generation, the second water-cooled wall surface radiation heat transfer entropy generation, the second total heat transfer entropy generation, the second total flow resistance entropy generation, the steam heat dissipation entropy generation, the mass transfer entropy generation and the motor entropy generation, and solve the soot-blowing benefit model to obtain the optimal soot-blowing times.

9. A storage medium storing at least one executable instruction, characterized in that, The executable instructions cause the processor to perform the operations corresponding to the boiler soot-blowing method of the coal-fired unit according to any one of claims 1-7.

10. A computer device, comprising: A processor, a memory, a communication interface and a communication bus, and the processor, the memory and the communication interface complete communication with each other through the communication bus; The memory is used to store at least one executable instruction, and is characterized in that the executable instruction causes the processor to perform the operations corresponding to the boiler soot-blowing method of the coal-fired unit according to any one of claims 1-7.

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