Boiler real-time data prediction method and device

Abstract

A boiler real-time data prediction method and device, the method comprising: determining a boiler variable load rate according to a current load of the boiler, a current time, a target load of the boiler, a rated load of the boiler and an expected time; determining a boiler load instruction by using a mapping relationship between the boiler load and the boiler energy storage according to a load correction coefficient, a boiler steam output heat, the boiler variable load rate, the rated load of the boiler and the current load of the boiler; determining a boiler real-time combustion amount by using a mapping relationship between the boiler load and the boiler input energy according to a low calorific value of fuel fed into the boiler and the boiler load instruction; and determining a boiler real-time air supply amount by using the mapping relationship between the boiler load and the boiler input energy according to a combustible chemical energy proportion of ash and slag and the boiler load instruction. The present application realizes accurate prediction of the boiler real-time combustion amount and the boiler real-time air supply amount, fully considers the specific influence of multiple factors in combustion, and accurately reflects the actual working condition of the boiler while reducing the calculation complexity.

Description

Technical Field

[0001] This invention relates to the field of boiler control technology, and more particularly to a method and apparatus for real-time boiler data prediction. Background Technology

[0002] Regulating fuel quantity and air supply is one of the basic functions of an automatic boiler output control system. In existing automatic control systems, the main steam pressure and oxygen concentration in the flue gas are often used as the target variables for control. Specifically, the methods are: (1) Fuel quantity tracks the main steam pressure. When the main steam pressure is lower than the target value, the fuel quantity is increased; conversely, the fuel quantity is decreased. The greater the deviation in the main steam pressure, the greater the increase or decrease in the fuel quantity. (2) Air supply tracks the oxygen concentration in the flue gas. When the oxygen concentration in the flue gas is lower than the target value, the air supply is increased; conversely, the air supply is decreased. The greater the deviation in the oxygen concentration in the flue gas, the greater the increase or decrease in the air supply.

[0003] This control method avoids complex calculations of the dynamic process within the boiler, achieving a simple mapping between the target variable and the main control variable. It boasts strong operability and versatility, thus gaining widespread application. However, it also has drawbacks such as lag in the response of the target variable and limited anti-interference capability of the control system. Especially during the boiler's dynamic process, on the one hand, fuel overshoot can easily occur, causing significant fluctuations in steam temperature and reducing the lifespan of the boiler's heating surfaces; on the other hand, even short-term mismatch between air supply and fuel supply can cause combustion conditions to deviate significantly from the design, reducing combustion efficiency and increasing pollutant generation. Summary of the Invention

[0004] To address the problems existing in the prior art, the main objective of this invention is to provide a method and apparatus for real-time boiler data prediction, enabling accurate prediction of real-time boiler fuel quantity and real-time boiler air supply.

[0005] To achieve the above objectives, embodiments of the present invention provide a method for real-time boiler data prediction, the method comprising:

[0006] Obtain the current boiler load, current time, and boiler steam output heat, and determine the boiler load change rate based on the current boiler load and current time, as well as the preset boiler target load, boiler rated load, and desired time.

[0007] Based on the preset load correction coefficient, boiler steam output heat, boiler load change rate, boiler rated load and current boiler load, the boiler load command is determined using the pre-established mapping relationship between boiler load and boiler energy storage.

[0008] Based on the lower heating value of the fuel entering the furnace and the boiler load command, the real-time combustion rate of the boiler is determined using the pre-established mapping relationship between boiler load and boiler input energy.

[0009] Based on the proportion of combustible chemical energy in ash and slag and the boiler load command, the real-time air supply of the boiler is determined by utilizing the mapping relationship between boiler load and boiler input energy.

[0010] Optionally, in one embodiment of the present invention, the boiler load command is determined based on a preset load correction coefficient, boiler steam output heat, boiler load change rate, boiler rated load, and current boiler load, using a pre-established mapping relationship between boiler load and boiler energy storage. This includes:

[0011] Based on the boiler load change rate, the time step is obtained, and based on the boiler load change rate and the time step, the difference between the target load and the actual load is obtained;

[0012] Based on the differences, the current boiler load, and the time step, the rate of change of energy storage is obtained by utilizing the mapping relationship between boiler load and boiler energy storage.

[0013] The theoretical value of load deviation is obtained based on the difference, the rate of change of energy storage, and the boiler steam output heat.

[0014] The boiler load command is determined based on the theoretical value of load deviation, the boiler rated load, the current boiler load, and the load correction factor.

[0015] Optionally, in one embodiment of the present invention, based on the difference, the current boiler load, and the time step, the energy storage change rate is obtained using the mapping relationship between boiler load and boiler energy storage, including:

[0016] Based on the differences, the current boiler load, and the boiler rated load, the energy storage difference between the initial and final states is obtained by utilizing the mapping relationship between boiler load and boiler energy storage.

[0017] The rate of change of energy storage is obtained based on the energy storage difference between the initial and final states and the time step.

[0018] Optionally, in one embodiment of the present invention, the real-time air supply of the boiler is determined by utilizing the mapping relationship between boiler load and boiler input energy, based on the proportion of combustible chemical energy in ash and boiler load instructions.

[0019] The chemical energy ratio of ash combustibles is obtained based on the preset fuel type correction coefficient and excess air coefficient.

[0020] Based on the proportion of combustible chemical energy in ash and slag and the boiler load command, the real-time air supply of the boiler is determined by utilizing the mapping relationship between boiler load and boiler input energy.

[0021] This invention also provides a boiler real-time data prediction device, the device comprising:

[0022] The load rate module is used to obtain the current boiler load, current time, and boiler steam output heat, and to determine the boiler load rate based on the current boiler load and current time, as well as the preset boiler target load, boiler rated load, and desired time.

[0023] The load command module is used to determine the boiler load command based on the preset load correction coefficient, boiler steam output heat, boiler load change rate, boiler rated load and current boiler load, using the pre-established mapping relationship between boiler load and boiler energy storage.

[0024] The real-time combustion module is used to determine the real-time combustion of the boiler based on the lower heating value of the fuel entering the furnace and the boiler load command, using a pre-established mapping relationship between the boiler load and the boiler input energy.

[0025] The real-time air supply module is used to determine the real-time air supply of the boiler based on the proportion of chemical energy of combustible ash and slag and the boiler load command, using the mapping relationship between boiler load and boiler input energy.

[0026] Optionally, in one embodiment of the present invention, the load command module includes:

[0027] The time step unit is used to obtain the time step based on the boiler load change rate, and to obtain the difference between the target load and the actual load based on the boiler load change rate and the time step.

[0028] The energy storage change rate unit is used to obtain the energy storage change rate based on the difference, the current boiler load, and the time step, using the mapping relationship between boiler load and boiler energy storage.

[0029] The load deviation unit is used to obtain the theoretical value of the load deviation based on the difference, the rate of change of energy storage, and the output heat of boiler steam.

[0030] The load command unit is used to determine the boiler load command based on the theoretical value of load deviation, the boiler rated load, the current boiler load, and the load correction factor.

[0031] Optionally, in one embodiment of the present invention, the energy storage rate of change unit includes:

[0032] The energy storage difference subunit is used to obtain the initial and final state energy storage difference based on the difference, the current boiler load, and the boiler rated load, using the mapping relationship between boiler load and boiler energy storage.

[0033] The rate of change subunit is used to obtain the rate of change of energy storage based on the energy storage difference between the initial and final states and the time step.

[0034] Optionally, in one embodiment of the present invention, the real-time air supply module includes:

[0035] The chemical energy ratio unit is used to obtain the chemical energy ratio of ash combustibles based on the preset fuel type correction coefficient and excess air coefficient.

[0036] The real-time air supply unit is used to determine the real-time air supply of the boiler based on the proportion of chemical energy of combustible ash and slag and the boiler load command, using the mapping relationship between boiler load and boiler input energy.

[0037] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0038] The present invention also provides a computer-readable storage medium storing a computer program that performs the above-described methods by a computer.

[0039] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0040] This invention utilizes actual boiler operating data and preset boiler data correlation mapping relationships to achieve accurate prediction of real-time boiler combustion volume and real-time boiler air supply volume. It fully considers the specific influence of multiple factors in combustion, and while reducing computational complexity, it accurately reflects the actual operating conditions of the boiler. Attached Figure Description

[0041] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0042] Figure 1 This is a flowchart of a boiler real-time data prediction method according to an embodiment of the present invention;

[0043] Figure 2 This is a flowchart illustrating the process of determining boiler load commands in an embodiment of the present invention;

[0044] Figure 3 This is a flowchart illustrating the energy storage change rate in an embodiment of the present invention;

[0045] Figure 4 This is a flowchart illustrating the process of determining the real-time air supply of the boiler in an embodiment of the present invention;

[0046] Figure 5 This is a schematic diagram of the structure of a boiler real-time data prediction device according to an embodiment of the present invention;

[0047] Figure 6 This is a schematic diagram of the load instruction module in an embodiment of the present invention;

[0048] Figure 7 This is a schematic diagram of the energy storage rate of change unit in an embodiment of the present invention;

[0049] Figure 8 This is a schematic diagram of the real-time air supply module in an embodiment of the present invention;

[0050] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0051] This invention provides a method and apparatus for real-time boiler data prediction.

[0052] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0053] A prior art method for combustion optimization control based on dynamic operation data analysis is disclosed, comprising the following steps: acquiring relevant historical operation data stored in the unit's DCS; grouping data packets of different loads and temperature ranges into different data subsets, calculating the mean values ​​of each operation parameter for each load and temperature range, and performing gap filling and smoothing filtering to obtain the steady-state component of the operation data for analysis; after obtaining the steady-state component, subtracting the corresponding steady-state component from the total operation dataset to obtain the fluctuating operation dataset; calculating the correlation coefficient between each parameter and the total coal quantity and / or flue gas NOx concentration; and providing optimization suggestions based on the obtained correlation coefficients. By analyzing dynamic operation data including non-steady-state conditions, this method demonstrates the feasibility of revealing unit operating characteristics, extracting optimized operation control laws, and improving the accuracy of operation control.

[0054] The prior art also discloses a smart power plant monitoring method, system, equipment, and storage medium. The method includes acquiring historical data of boiler characteristic parameters; determining whether the historical data of boiler characteristic parameters meets the requirements of stable operating conditions; constructing a boiler combustion model using a core support vector machine based on a preset coal feeder feed rate and the historical data of boiler characteristic parameters that meet the requirements of stable operating conditions; optimizing the adjustable parameters of boiler operation based on a preset multi-objective function and the boiler combustion model, combined with the Chebyshev method, to obtain the optimal solution of the boiler operating parameters; comparing the optimal solution with the real-time data of boiler characteristic parameters and calculating the optimization bias; and adjusting the boiler operating conditions according to the optimization bias.

[0055] The shortcomings of the existing technologies mentioned above include: 1) They rely on processed historical operating datasets, which cannot reflect the deviation of the boiler's actual performance from the design baseline. 2) They do not consider the impact of coal quality fluctuations on the actual boiler operating data and are unable to cope with actual operating conditions with significant coal quality anomalies. 3) Dynamic operating data includes non-steady-state operating conditions; the greater the system deviation of the non-steady-state operating conditions, the more severe the distortion of the obtained data baseline.

[0056] Furthermore, existing technology also provides a combustion control system and method for a circulating fluidized bed boiler, relating to the field of boiler combustion technology, and solving the environmental pollution problem caused by incomplete combustion in circulating fluidized bed boilers. The system includes an optimization controller and a base controller connected to the optimization controller. The optimization controller calculates and outputs an optimized air-fuel ratio in real time according to a preset optimization target. The base controller is used to achieve combustion control of the circulating fluidized bed boiler based on the optimized air-fuel ratio calculated by the optimization controller. For combustion control of online circulating fluidized bed boilers, a multivariate predictive control technology with a dual-layer controller is employed to achieve decoupling of multiple variables and advance prediction and adjustment of key variables, thereby achieving optimal combustion in the online circulating fluidized bed boiler.

[0057] The shortcomings of this existing technology include: 1) Using the air-coal ratio as the lumped parameter for combustion control, it does not adequately consider the specific influence of multiple factors in combustion. 2) It is not suitable for boilers that blend two or more fuels.

[0058] Furthermore, existing technology discloses a boiler temperature field prediction method combining computational fluid dynamics and deep learning, belonging to the field of computer deep learning power plant boiler combustion modeling technology. This method establishes a furnace model of a tangentially circular coal-fired boiler based on computational fluid dynamics. By setting different coal feed rates as inlet conditions, it calculates the temperature field during steady-state combustion of the boiler and extracts two-dimensional temperature data from the plane where the burner is located. A temperature field reconstruction neural network is established, specifically using the characteristic values ​​of the temperature near the burner and process parameters reflecting the boiler's operating conditions as network inputs, and the temperature data of the burner plane as network outputs to complete the training of the neural network. Through the calculation of the neural network, the furnace temperature field at the burner is obtained. This significantly saves the time and space consumption of the calculation process and can obtain the real-time temperature field, providing support for guiding the stable and efficient operation of power plants.

[0059] The drawbacks of this existing technology include: 1) Constructing a two-dimensional temperature field requires relatively high computational resources; the "saving time and space consumption in the computation process" is only relative to computational methods that do not use neural network training results. 2) The temperature field is only an intermediate variable for understanding the combustion conditions inside the boiler; more complex computational models are needed to reflect its impact on combustion efficiency and pollutant emissions.

[0060] To address the shortcomings of existing technologies, such as Figure 1 The diagram shows a flowchart of a boiler real-time data prediction method provided by an embodiment of the present invention. The execution subject of this boiler real-time data prediction method includes, but is not limited to, a computer. This invention utilizes actual boiler operating data and preset boiler data correlation mapping relationships to achieve accurate prediction of real-time boiler combustion output and real-time boiler air supply. It fully considers the specific influence of multiple factors during combustion, reducing computational complexity while accurately reflecting the actual operating conditions of the boiler. The method shown in the diagram includes:

[0061] Step S1: Obtain the current boiler load, current time, and boiler steam output heat, and determine the boiler load change rate based on the current boiler load and current time, as well as the preset boiler target load, boiler rated load, and desired time.

[0062] Step S2: Based on the preset load correction coefficient, boiler steam output heat, boiler load change rate, boiler rated load and current boiler load, determine the boiler load command using the pre-established mapping relationship between boiler load and boiler energy storage.

[0063] Step S3: Based on the lower heating value of the fuel entering the furnace and the boiler load command, determine the real-time combustion rate of the boiler using the pre-established mapping relationship between boiler load and boiler input energy.

[0064] Step S4: Based on the proportion of combustible chemical energy in ash and slag and the boiler load command, determine the real-time air supply of the boiler using the mapping relationship between boiler load and boiler input energy.

[0065] This involves establishing a mapping relationship between boiler load and input energy. Specifically, it involves establishing the boiler input energy Q. i Mapping relationship with load L:

[0066] Q i =f1(L) (1)

[0067] In the formula, Q i The boiler input energy is represented by MW; L is the boiler load, represented by t / h; f1 is the function relating the boiler load and the input energy, and its determination process includes:

[0068] a) Select multiple steady-state operating conditions (each condition corresponds to a set of data) within the operating range of the boiler's automatic control system, and test the boiler's load L and input energy Q. en (en is an abbreviation for enter), obtain a set of test data (L1, Q). en1 (L2,Q) en2 (L3,Q) en3 ...

[0069] b) Use appropriate functional relationships (e.g., second-order or higher polynomials) Fit the test data, where k i These are the coefficients obtained by fitting the experimental data. Specifically, the process of fitting the test data can employ conventional methods, which will not be elaborated upon here.

[0070] Furthermore, the specific process of establishing the mapping relationship between boiler load and boiler energy storage includes:

[0071] Boiler energy storage E refers to the sum of the chemical energy contained in the combustibles inside the boiler and the thermal energy stored in the metals and other materials under different load conditions. When measuring boiler energy storage, 20℃ can be uniformly selected as the reference temperature to establish a mapping relationship between boiler energy storage and boiler load.

[0072] E=f2(L) (2)

[0073] In the formula, E represents boiler energy storage in GJ; f2 is the relationship function between boiler load and boiler energy storage, and the specific determination process includes:

[0074] a) Select multiple steady-state operating conditions within the automatic control operating range of the boiler (each operating condition corresponds to a set of data), test or calculate the boiler energy storage E corresponding to the boiler load L, and obtain a set of data (L1, E1), (L2, E2), (L3, E3)...;

[0075] b) Use appropriate functional relationships (e.g., second-order or higher polynomials) Fit the above data, where c i These are the coefficients obtained by fitting the experimental data. Specifically, the process of fitting the above data can be performed using conventional methods, which will not be elaborated upon here.

[0076] Furthermore, fuel quantity refers to the total amount of fuel consumed by the boiler per unit time, and is the main control variable for boiler output regulation. Air supply is the amount of air participating in boiler combustion per unit time, and is one of the important main control variables for boiler combustion optimization. Real-time load is the output energy of the boiler at the current moment, usually expressed as evaporation rate, in t / h. Load command is the energy that the boiler should output at the current moment, usually expressed as evaporation rate, in t / h.

[0077] Furthermore, by accurately predicting the real-time combustion volume and air supply of the boiler, it is easier to use these figures for subsequent boiler combustion control, thereby improving the accuracy and efficiency of boiler combustion control and achieving the effect of saving fuel and human resources.

[0078] As one embodiment of the present invention, such as Figure 2As shown, based on the preset load correction factor, boiler steam output heat, boiler load change rate, boiler rated load, and current boiler load, and utilizing the pre-established mapping relationship between boiler load and boiler energy storage, the boiler load command is determined, including:

[0079] Step S21: Based on the boiler load change rate, obtain the time step, and based on the boiler load change rate and time step, obtain the difference between the target load and the actual load.

[0080] Step S22: Based on the difference, the current boiler load, and the time step, the energy storage change rate is obtained by utilizing the mapping relationship between boiler load and boiler energy storage.

[0081] Step S23: Based on the difference, energy storage change rate and boiler steam output heat, obtain the theoretical value of load deviation;

[0082] Step S24: Determine the boiler load command based on the theoretical value of load deviation, the rated load of the boiler, the current load of the boiler, and the load correction factor.

[0083] In this embodiment, as Figure 3 As shown, based on the differences, the current boiler load, and the time step, the energy storage change rate is obtained by utilizing the mapping relationship between boiler load and boiler energy storage, including:

[0084] Step S221: Based on the difference, the current load of the boiler and the rated load of the boiler, the energy storage difference between the initial and final states is obtained by using the mapping relationship between the boiler load and the boiler energy storage.

[0085] Step S222: Based on the energy storage difference between the initial and final states and the time step, obtain the energy storage change rate.

[0086] As one embodiment of the present invention, such as Figure 4 As shown, based on the proportion of combustible chemical energy in ash and slag and the boiler load command, the real-time air supply of the boiler is determined using the mapping relationship between boiler load and boiler input energy, including:

[0087] Step S41: Based on the preset fuel type correction coefficient and excess air coefficient, the chemical energy ratio of ash combustibles is obtained.

[0088] Step S42: Based on the proportion of combustible chemical energy in ash and slag and the boiler load command, determine the real-time air supply of the boiler using the mapping relationship between boiler load and boiler input energy.

[0089] Specifically, the process for predicting the real-time fuel quantity of the boiler is as follows:

[0090] 1) Calculate the boiler load change rate

[0091]

[0092] In the formula, dL / dt is the boiler load change rate, in % / min; L′ is the preset target boiler load, in t / h; L is the current actual boiler load, which can be directly read from the dial, in t / h; L e t is the boiler's rated load, in t / h; t′ is the expected time to reach the preset target load, in min; t is the current time that is directly available, in min.

[0093] 2) Predict the real-time fuel quantity of the boiler

[0094]

[0095] In the formula, Q represents the real-time predicted fuel consumption of the boiler, in tons per hour (t / h). net,ar The lower heating value of the fuel entering the furnace is expressed in kJ / kg. When the boiler simultaneously burns multiple fuels, the lower heating value of each fuel can be weighted and averaged according to the weight of the fuel being burned, as shown in the following formula:

[0096]

[0097] Where, α j Let Q be the mass fraction of the j-th type of coal; net,ar,j (where is the lower heating value of the j-th type of coal, kJ / kg). Therefore, this method can be applied to real-time prediction of boilers that blend two or more fuels.

[0098] Furthermore, The boiler load command, in t / h, can be calculated using the following formula:

[0099]

[0100] In the formula, Δt is the time step, in minutes. The smaller the value of Δt, the higher the accuracy of boiler automatic control, but the higher the computational requirements. Δt can be a function related to dL / dt, but its value should preferably not exceed 1 minute. φ is the load correction coefficient, dimensionless, with a value range of (0,1). It may not be a constant, but rather a function related to the boiler load L.

[0101]

[0102]

[0103] Among them, a i The coefficients are obtained by fitting the experimental data. The specific fitting process can be carried out using common methods, which will not be elaborated here.

[0104] In addition, the difference between the target load and the actual load in dL / dt·Δt is %.

[0105] Furthermore, f2(L+dL / dt·Δt·L) e )-f2(L) is the energy difference between the initial and final states, in GJ.

[0106] Furthermore, Energy storage change rate (GJ / min).

[0107] Furthermore, The theoretical value of the load deviation of the boiler at the initial and final states is given in t / h.

[0108] Furthermore, Δh represents the output heat corresponding to a unit mass of steam produced by the boiler, in kJ / kg, i.e., the boiler steam output heat.

[0109] In this embodiment, the specific process of predicting the real-time air supply of the boiler includes: the real-time air supply of the boiler should match the load command.

[0110]

[0111] Wherein, 337.27 is the heat released by the direct combustion of carbon, kJ / kg.

[0112] Furthermore, It is the percentage of the chemical energy of combustibles in ash and slag to the lower heating value of the coal fed into the furnace, i.e., the proportion of the chemical energy of combustibles in ash and slag.

[0113] In the formula, This is the predicted real-time air supply volume for the boiler, in meters. 3 / h;Q net,ar The lower heating value of the fuel entering the furnace is expressed in kJ / kg. When the boiler is simultaneously burning multiple fuels, the lower heating value of each fuel can be weighted and averaged according to the weight of the fuel, as shown in formula (5).

[0114] Furthermore, The boiler load command, in t / h, can be calculated according to formula (6); A ar 1. Ash content of fuel received (obtained by laboratory testing), in %; K is the fuel type correction factor, dimensionless, which can be set to 0.261; α is the excess air coefficient, dimensionless, which can be obtained from boiler design data or determined by boiler combustion adjustment tests. The weighted average of the combustible content of ash residue, expressed as a percentage, can be calculated using the following formula:

[0115]

[0116] In the formula, C lz and C fh These represent the combustible content of slag and fly ash, respectively, in % (based on experimental measurements or design data); α lz and α fhThese represent the percentages of slag and fly ash in the total fuel ash production, in %. These parameters can be obtained through experimental testing or by consulting design data.

[0117] This invention utilizes actual boiler operating data and preset boiler data correlation mapping relationships to achieve accurate prediction of real-time boiler combustion volume and real-time boiler air supply volume. It fully considers the specific influence of multiple factors in combustion, and while reducing computational complexity, it accurately reflects the actual operating conditions of the boiler.

[0118] like Figure 5 The figure shows a schematic diagram of a boiler real-time data prediction device according to an embodiment of the present invention. The device shown in the figure includes:

[0119] The load rate module 10 is used to acquire the current boiler load, current time and boiler steam output heat, and determine the boiler load rate based on the current boiler load and current time, as well as the preset boiler target load, boiler rated load and desired time.

[0120] The load command module 20 is used to determine the boiler load command based on the preset load correction coefficient, boiler steam output heat, boiler load change rate, boiler rated load and boiler current load, using the pre-established mapping relationship between boiler load and boiler energy storage.

[0121] The real-time combustion module 30 is used to determine the real-time combustion of the boiler based on the lower heating value of the fuel entering the furnace and the boiler load command, using a pre-established mapping relationship between the boiler load and the boiler input energy.

[0122] The real-time air supply module 40 is used to determine the real-time air supply of the boiler based on the proportion of chemical energy of combustible ash and slag and the boiler load command, using the mapping relationship between boiler load and boiler input energy.

[0123] As one embodiment of the present invention, such as Figure 6 As shown, the load command module 20 includes:

[0124] The time step unit 21 is used to obtain the time step based on the boiler load change rate, and to obtain the difference between the target load and the actual load based on the boiler load change rate and the time step.

[0125] The energy storage change rate unit 22 is used to obtain the energy storage change rate based on the difference, the current boiler load and the time step, using the mapping relationship between boiler load and boiler energy storage.

[0126] The load deviation unit 23 is used to obtain the theoretical value of the load deviation based on the difference, the energy storage change rate and the boiler steam output heat;

[0127] The load command unit 24 is used to determine the boiler load command based on the theoretical value of load deviation, the rated load of the boiler, the current load of the boiler, and the load correction coefficient.

[0128] In this embodiment, as Figure 7 As shown, the energy storage rate of change unit 22 includes:

[0129] The energy storage difference subunit 221 is used to obtain the initial and final state energy storage difference based on the difference, the current boiler load and the rated boiler load, using the mapping relationship between boiler load and boiler energy storage.

[0130] The rate of change subunit 222 is used to obtain the rate of change of energy storage based on the energy storage difference between the initial and final states and the time step.

[0131] As one embodiment of the present invention, such as Figure 8 As shown, the real-time air supply module 40 includes:

[0132] The chemical energy ratio unit 41 is used to obtain the chemical energy ratio of the ash combustibles according to the preset fuel type correction coefficient and excess air coefficient.

[0133] The real-time air supply unit 42 is used to determine the real-time air supply of the boiler based on the proportion of chemical energy of combustible ash and slag and the boiler load command, using the mapping relationship between boiler load and boiler input energy.

[0134] Based on the same concept as the aforementioned boiler real-time data prediction method, this invention also provides a boiler real-time data prediction device. Since the principle by which this boiler real-time data prediction device solves the problem is similar to that of the boiler real-time data prediction method, the implementation of this boiler real-time data prediction device can refer to the implementation of the boiler real-time data prediction method; repeated details will not be elaborated further.

[0135] This invention utilizes actual boiler operating data and preset boiler data correlation mapping relationships to achieve accurate prediction of real-time boiler combustion volume and real-time boiler air supply volume. It fully considers the specific influence of multiple factors in combustion, and while reducing computational complexity, it accurately reflects the actual operating conditions of the boiler.

[0136] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described method.

[0137] The present invention also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the above-described method.

[0138] The present invention also provides a computer-readable storage medium storing a computer program that performs the above-described methods by a computer.

[0139] like Figure 9 As shown, the electronic device 600 may also include: a communication module 110, an input unit 120, an audio processor 130, a display 160, and a power supply 170. It is worth noting that the electronic device 600 does not necessarily need to include these components. Figure 9 All components shown; in addition, the electronic device 600 may also include Figure 9 For components not shown, please refer to existing technologies.

[0140] like Figure 9 As shown, the central processing unit 100, sometimes also referred to as a controller or operating control, may include a microprocessor or other processor device and / or logic device. The central processing unit 100 receives inputs and controls the operation of various components of the electronic device 600.

[0141] The memory 140 may be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It may store the aforementioned failure-related information, and also store a program for executing that information. The central processing unit 100 may execute the program stored in the memory 140 to perform information storage or processing, etc.

[0142] Input unit 120 provides input to central processing unit 100. Input unit 120 may be, for example, a keypad or touch input device. Power supply 170 provides power to electronic device 600. Display 160 displays images and text. Display may be, for example, an LCD display, but is not limited thereto.

[0143] The memory 140 can be a solid-state memory, such as a read-only memory (ROM), random access memory (RAM), a SIM card, etc. It can also be a memory that retains information even when power is off, can be selectively erased, and contains more data; examples of this type of memory are sometimes referred to as EPROMs. The memory 140 can also be some other type of device. The memory 140 includes a buffer memory 141 (sometimes referred to as a buffer). The memory 140 may include an application / function storage unit 142 for storing application programs and function programs or processes for executing the operation of the electronic device 600 via the central processing unit 100.

[0144] The memory 140 may also include a data storage unit 143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 144 of the memory 140 may include various drivers for the electronic device's communication functions and / or for performing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0145] The communication module 110 is a transmitter / receiver 110 that transmits and receives signals via antenna 111. The communication module (transmitter / receiver) 110 is coupled to the central processing unit 100 to provide input signals and receive output signals, which can be the same as in a conventional mobile communication terminal.

[0146] Based on different communication technologies, multiple communication modules 110 can be configured in the same electronic device, such as cellular network modules, Bluetooth modules, and / or wireless LAN modules. The communication module (transmitter / receiver) 110 is also coupled to a speaker 131 and a microphone 132 via an audio processor 130 to provide audio output via the speaker 131 and receive audio input from the microphone 132, thereby enabling typical telecommunications functions. The audio processor 130 may include any suitable buffer, decoder, amplifier, etc. Additionally, the audio processor 130 is coupled to a central processing unit 100, enabling on-device recording via the microphone 132 and on-device playback of stored audio via the speaker 131.

[0147] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0148] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0149] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0150] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0151] Specific embodiments have been used to illustrate the principles and implementation methods of this invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this invention. Therefore, the content of this specification should not be construed as a limitation of this invention.

Claims

1. A method for real-time data prediction of boilers, characterized in that, The method includes: The boiler's current load, current time, and boiler steam output heat are obtained, and the boiler load change rate is determined based on the current load and current time, as well as the preset boiler target load, boiler rated load, and desired time. Based on the preset load correction coefficient, the boiler steam output heat, the boiler load change rate, the boiler rated load, and the boiler current load, the boiler load command is determined using the pre-established mapping relationship between boiler load and boiler energy storage. Based on the lower heating value of the fuel entering the furnace and the boiler load command, the real-time combustion rate of the boiler is determined using the pre-established mapping relationship between boiler load and boiler input energy. Based on the proportion of combustible chemical energy in ash and the boiler load command, the real-time air supply of the boiler is determined using the mapping relationship between the boiler load and the boiler input energy.

2. The method according to claim 1, characterized in that, Based on the preset load correction coefficient, the boiler steam output heat, the boiler load change rate, the boiler rated load, and the boiler current load, the boiler load command is determined using the pre-established mapping relationship between boiler load and boiler energy storage. This includes: Based on the boiler load change rate, the time step is obtained, and based on the boiler load change rate and the time step, the difference between the target load and the actual load is obtained; Based on the aforementioned differences, the current boiler load, and the time step, the rate of change of energy storage is obtained by utilizing the mapping relationship between boiler load and boiler energy storage. Based on the aforementioned differences, energy storage change rate, and boiler steam output heat, the theoretical value of the load deviation is obtained; The boiler load command is determined based on the theoretical value of the load deviation, the boiler rated load, the current boiler load, and the load correction factor.

3. The method according to claim 2, characterized in that, Based on the aforementioned differences, the current boiler load, and the time step, the energy storage change rate is obtained using the mapping relationship between boiler load and boiler energy storage, including: Based on the aforementioned differences, the current boiler load, and the boiler rated load, the initial and final state energy storage difference is obtained by utilizing the mapping relationship between boiler load and boiler energy storage. The energy storage change rate is obtained based on the energy storage difference between the initial and final states and the time step.

4. The method according to claim 1, characterized in that, Based on the proportion of combustible chemical energy in ash and the boiler load command, and utilizing the mapping relationship between the boiler load and the boiler input energy, the real-time air supply of the boiler is determined, including: The chemical energy ratio of the ash slag combustibles is obtained based on the preset fuel type correction coefficient and excess air coefficient. Based on the chemical energy ratio of the combustible ash and the boiler load command, the real-time air supply of the boiler is determined using the mapping relationship between the boiler load and the boiler input energy.

5. A boiler real-time data prediction device, characterized in that, The device includes: The load rate module is used to acquire the current boiler load, current time, and boiler steam output heat, and to determine the boiler load rate based on the current boiler load and current time, as well as the preset boiler target load, boiler rated load, and desired time. The load command module is used to determine the boiler load command based on the preset load correction coefficient, the boiler steam output heat, the boiler load change rate, the boiler rated load and the current boiler load, using the pre-established mapping relationship between boiler load and boiler energy storage. The real-time combustion module is used to determine the real-time combustion of the boiler based on the lower heating value of the fuel entering the furnace and the boiler load command, using a pre-established mapping relationship between the boiler load and the boiler input energy. The real-time air supply module is used to determine the real-time air supply of the boiler based on the proportion of chemical energy of combustible ash and the boiler load command, using the mapping relationship between the boiler load and the boiler input energy.

6. The apparatus according to claim 5, characterized in that, The load command module includes: The time step unit is used to obtain the time step based on the boiler load change rate, and to obtain the difference between the target load and the actual load based on the boiler load change rate and the time step. The energy storage change rate unit is used to obtain the energy storage change rate based on the difference, the current boiler load, and the time step, using the mapping relationship between boiler load and boiler energy storage. The load deviation unit is used to obtain the theoretical value of the load deviation based on the difference, the energy storage change rate, and the boiler steam output heat. The load command unit is used to determine the boiler load command based on the theoretical value of the load deviation, the rated load of the boiler, the current load of the boiler, and the load correction coefficient.

7. The apparatus according to claim 6, characterized in that, The energy storage rate unit includes: The energy storage difference subunit is used to obtain the initial and final state energy storage difference based on the difference, the current boiler load and the rated boiler load, using the mapping relationship between boiler load and boiler energy storage. The rate of change subunit is used to obtain the energy storage rate of change based on the energy storage difference between the initial and final states and the time step.

8. The apparatus according to claim 5, characterized in that, The real-time air supply module includes: The chemical energy ratio unit is used to obtain the chemical energy ratio of the ash combustibles based on a preset fuel type correction coefficient and excess air coefficient. The real-time air supply unit is used to determine the real-time air supply of the boiler based on the proportion of chemical energy of the combustible ash and the boiler load command, using the mapping relationship between the boiler load and the boiler input energy.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method according to any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that enables a computer to execute the method according to any one of claims 1 to 4.

11. A computer program product, comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 4.

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