Coal-fired furnace hearth semi-physical simulation system based on RT-LAB

Abstract

The application discloses a coal-fired furnace hearth semi-physical simulation system based on RT-LAB, relates to the technical field of coal-fired furnace simulation, and is a coal-fired boiler hearth simulation system with high precision, strong adaptability and good predictability. The coal-fired furnace hearth simulation system can simulate the adverse effects of abnormal working of an induced draft fan on the operation of a boiler hearth in real time, solves the problem that the current coal-fired boiler cannot accurately simulate the working condition of a major abnormal accident, and provides platform support and a theoretical basis for information security protection of a DCS control system.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of coal-fired furnace simulation, in particular to a coal-fired furnace hearth semi-physical simulation system based on RT-LAB. BACKGROUND

[0002] The coal-fired boiler is a boiler that uses coal as fuel, which is a heat energy power equipment that heats the heat medium water or other organic heat carriers (such as heat conducting oil, etc.) to a certain temperature (or pressure) through the combustion of coal in the furnace.

[0003] In the coal-fired boiler, the heat of coal is converted to produce steam or hot water, but not all of the heat is effectively converted, and a part of the heat is consumed without work, so there is an efficiency problem. Generally, larger coal-fired boilers have higher efficiency, between 60% and 80%. Coal-fired boilers are mainly classified according to their uses, which are divided into coal-fired water boiler (supplying boiled water), coal-fired hot water boiler (heating and bathing), coal-fired steam boiler (supplying steam), coal-fired heat conducting oil boiler (steaming and drying), etc.

[0004] However, the coal ash in the coal-fired boiler has serious coking properties, which often leads to boiler coking. The boiler coking is very harmful to the coal-fired boiler, seriously affecting the safety and economy of the coal-fired boiler. Moreover, a considerable proportion of unplanned boiler shutdown accidents is caused by boiler coking. At the same time, the coal-fired boiler produces flue gas containing CO2, SO2 and other toxic and harmful gases during the combustion process. When the combustion is insufficient, a small amount of CO, CH4 and other toxic and harmful gases will also be produced. In this case, if the boiler air distribution is improper or the oxygen supply is insufficient, not only the exhaust gas heat loss is increased, but also the economy of the boiler operation is directly affected.

[0005] There are also some technical solutions in the prior art for studying related problems of coal-fired boilers based on model simulation, such as the Chinese invention patent document with the publication number CN112163380A, the publication date of January 1, 2021, and the name of "Neural network prediction system and method for furnace oxygen concentration based on numerical simulation". The system provided by the document includes a numerical simulation simulation module, a data processing module, an algorithm prediction module, and an implementation module. Through the numerical simulation simulation module, a physical model of the furnace interior is established using numerical simulation software for simulation operation; the data processing module processes the numerical simulation results, and then the algorithm prediction module establishes three neural network modules and performs algorithm prediction, and finally the implementation module selects the best algorithm to predict the oxygen distribution in the furnace. The present invention has the advantages of large information processing capacity, fast calculation speed, and simple and convenient way to process complex furnace oxygen problems, which can accurately predict future trends and improve calculation efficiency. However, this technical solution relies on the input boiler parameters for modeling, and the prediction results are limited to the given data at the time of modeling, and cannot accurately simulate and restore the actual data changes during the operation of the boiler, and it is still difficult to serve as a reference for the safe operation and management of the boiler.

[0006] Therefore, there is an urgent need for a high-precision, highly adaptable, and good-predictive coal-fired boiler furnace simulation system to accurately simulate coal-fired boilers and study the effects of various abnormal conditions on the operation of coal-fired boilers in industrial applications. SUMMARY

[0007] The present invention aims to provide a high-precision, highly adaptable, and good-predictive coal-fired boiler furnace simulation system to address the shortcomings of the prior art. By simulating and testing the possible adverse effects of abnormal operation of the induced draft fan on the operation of the boiler furnace in real time, the problem of being unable to accurately simulate major abnormal accident conditions of coal-fired boilers is solved, providing a platform support and theoretical basis for the information security protection of the DCS control system.

[0008] The purpose of the present invention is achieved through the following technical solutions:

[0009] By connecting a part of the physical semi-physical simulation system in the system, the components can be tested in an environment that meets the overall performance indicators of the system, which is a necessary means to improve the reliability and quality of system design. The RT-LAB-based coal-fired furnace semi-physical simulation system includes an RT-Lab simulation platform, a DCS control system for the coal-fired furnace, and a host computer with a Simulink software simulation model. The RT-Lab simulation platform is connected to the host computer data through TCP / IP protocol, and the DCS control system is connected to the RT-Lab simulation platform data through a data interface as the physical part of the semi-physical simulation system.

[0010] The host sends Simulink soft simulation model data for simulating a coal-fired furnace to the RT-Lab simulation platform, the RT-Lab simulation platform performs simulation of the coal-fired furnace and outputs a simulated furnace pressure signal to the DCS control system, and the DCS control system receives the furnace pressure signal and, on one hand, maintains stable furnace negative pressure by adjusting the induced draft fan pressure through PID negative feedback control, and on the other hand, judges whether the furnace pressure is out of limit, and if so, outputs a furnace fault signal.

[0011] Specifically, the Simulink soft simulation model in the host includes a signal switching module and a furnace combustion model of a coal-fired boiler; the signal switching module judges according to the input fault signal, and if no fault is judged, the furnace combustion model receives an induced draft fan pressure signal from the DCS control system, otherwise, switches to an induced draft fan pressure signal generated internally by the furnace combustion model.

[0012] Preferably, after receiving the furnace pressure signal, the DCS control system, on one hand, maintains stable furnace negative pressure by adjusting the induced draft fan pressure through PID negative feedback control, and on the other hand, judges whether the furnace pressure is out of limit, and if so, outputs a furnace fault signal; specifically, the PID controller in the furnace negative pressure control model is adjusted to adjust the induced draft fan pressure, so that the furnace negative pressure is maintained within a reasonable range, to simulate normal control of stable furnace negative pressure; the PID control function in the furnace negative pressure control model is closed to calculate and judge the furnace negative pressure, to simulate accident conditions of furnace overpressure explosion.

[0013] More preferably, the furnace combustion model is a semi-empirical algorithm based on a zero-dimensional model. The zero-dimensional combustion model, also known as a single-zone model, is a method of establishing an empirical relationship between parameters of a combustion heat release process by statistical analysis of a large number of combustion heat release processes, using an empirical formula or curve fitting method, simplifying the complex combustion process into a relationship between several characteristic parameters, and a semi-empirical algorithm (model) is an algorithm (model) that adds experimental data to a model established by people to describe a mathematical model, which is verified by experiments, and determines the model parameters based on theory, that is, in the process of calculating the furnace combustion model of the coal-fired boiler, some parameters in the formula are obtained by statistical analysis, rather than by mechanism analysis.

[0014] Further, the RT-Lab simulation platform performs simulation of the coal-fired furnace, specifically including the following steps:

[0015] The inlet parameter calculation step collects the content of each element in the coal burned by the simulated coal-fired furnace through a coal quality analyzer, and obtains the air supply amount, air supply temperature, coal supply amount and coal powder temperature entering the coal-fired furnace through measurement, obtains the heat carried by the coal according to the calorific value of the coal, and obtains the enthalpy according to the physical property of the air supply, and the heat and the enthalpy jointly constitute the heat entering the furnace .

[0016] The furnace outlet parameter step calculates the outlet flue gas temperature according to a semi-empirical formula , wherein, is a theoretical combustion temperature, that is, the temperature that can be reached by the combustion product under the condition that the fuel is completely combusted in the absolute system, is an empirical coefficient, is the Stefan-Boltzmann constant, is the furnace wall area, is the furnace blackness, is the furnace heat retention coefficient, is the average heat capacity of the furnace, is the coal supply amount, is the thermal effective coefficient of the furnace; the flue gas mass at the outlet of the furnace can be obtained through mass conservation on the basis of the known furnace inlet parameters, and the enthalpy of the outlet flue gas can be obtained according to the temperature, mass and physical property of the outlet flue gas .

[0017] The furnace pressure calculation step derives the derivative of the furnace pressure with respect to time according to the energy conservation equation and the ideal gas equation as , wherein, is the heat entering the furnace, in the unit of kW; is the enthalpy of the outlet flue gas of the furnace, in the unit of kW; is the coal supply amount, in the unit of kg / s; is the energy absorbed by the heat absorption surface of the furnace, in the unit of kW; and are the specific heat and volume of the flue gas of the boiler furnace, in the unit of kJ / (kg·K) and m³ respectively; is the furnace pressure, in the unit of kPa; is the gas constant.

[0018] Further, the RT-LAB simulation platform comprises a model compiling module, a real-time simulation module and an interface module, the model compiling module mainly receives Simulink soft simulation model data from a host computer, and generates a program that can be run by the RT-LAB simulation platform after compiling and loading by adding opal series modules, the real-time simulation module performs real-time simulation after receiving the program that can be run, realizes rapid control prototyping and hardware-in-the-loop, and meanwhile, the real-time simulation module performs data transmission with the DCS control system through the interface module.

[0019] The real-time simulation module receives logic signals and data signals from the DCS control system, and the DCS control system receives the simulated furnace pressure signal from the real-time simulation module.

[0020] The logic signals include fault signals, and the data signals include coal supply amount, primary air pressure, secondary air pressure and induced draft fan air pressure signals

[0021] The DCS control system includes a field control level subsystem, a process control level subsystem and a process management level subsystem; the field control level subsystem is used for data acquisition and preprocessing of process non-controlled variables, the process control level subsystem is the core part of the DCS control system, and various control logics are implemented to adjust the field production process, that is, after receiving the furnace pressure signal from the RT-Lab simulation platform, on the one hand, the furnace pressure is kept stable by adjusting the induced draft fan pressure through PID negative feedback control, and on the other hand, it is judged whether the furnace pressure is out of limit, if it is out of limit, a furnace fault signal is output, and the process management level subsystem is the core display, operation and management device of the DCS control system, and is used for information input and acquisition, that is, a platform for information exchange between the operator and the DCS control system.

[0022] Compared with the prior art, the above technical scheme has the following innovations and beneficial effects (advantages):

[0023] 1. The coal-fired furnace semi-physical simulation system based on RT-LAB provided by the application is based on the basic thermal process in the coal-fired boiler furnace, uses the semi-empirical algorithm of the zero-dimensional model, proposes a new mechanism modeling and control method, adapts to the new RT-LAB semi-physical simulation technology, uses the semi-empirical algorithm of the zero-dimensional model for modeling, ensures the calculation accuracy and real-time performance, and realizes the prediction simulation of abnormal conditions.

[0024] 2. The coal-fired furnace semi-physical simulation system based on RT-LAB provided by the application avoids the influence of other parameter disturbances on the furnace negative pressure by PID control of the induced draft fan pressure under the conventional running state, ensures the normal operation, and can also simulate the explosion accident caused by the too high furnace negative pressure in real time when the induced draft fan works abnormally, thereby providing a theoretical basis for the safety protection of the boiler control system.

[0025] Thirdly, the RT-LAB-based coal-fired furnace semi-physical simulation system can be used in a coal-fired boiler semi-physical simulation system, abnormal working conditions and accident working conditions that can occur in the coal-fired boiler are simulated through parameter abnormalities, the data acquisition module of the physical object information display system adopts actual DCS control system and actual engineering data, and the conclusion obtained by the test platform is not a theoretical conclusion but an actual corresponding conclusion, and the test result is helpful to improve the engineering design scheme. BRIEF DESCRIPTION OF DRAWINGS

[0026] The foregoing and the following detailed description of the present application will become more apparent when read in conjunction with the following drawings, in which:

[0027] Figure 1 It is a schematic diagram of the furnace negative pressure control logic of the present application. DETAILED DESCRIPTION

[0028] The technical solutions for achieving the object of the present application will be further illustrated by specific embodiments, and it should be noted that the technical solutions claimed by the present application include but are not limited to the following embodiments.

[0029] As shown in the accompanying drawings, Figure 1 The RT-LAB-based coal-fired furnace semi-physical simulation system provided by the present embodiment includes an RT-Lab simulation platform, a DCS control system of a coal-fired furnace, and a host computer with a Simulink soft simulation model, the RT-Lab simulation platform is connected with the host computer data through a TCP / IP protocol, and the DCS control system is connected with the RT-Lab simulation platform data through a data interface as a physical part of the semi-physical simulation system.

[0030] The Simulink soft simulation model in the host computer includes a signal switching module and a furnace combustion model of a coal-fired boiler; the signal switching module judges according to the input fault signal, if no fault occurs, the furnace combustion model receives the induced draft fan pressure signal from the DCS control system, otherwise, the induced draft fan pressure signal generated inside the furnace combustion model is switched to.

[0031] The host sends Simulink soft simulation model data for simulating a coal-fired furnace to the RT-Lab simulation platform, the RT-Lab simulation platform performs simulation of the coal-fired furnace and outputs a simulated furnace pressure signal to the DCS control system, and the DCS control system receives the furnace pressure signal and, on one hand, performs PID negative feedback control to keep the furnace negative pressure stable by adjusting the induced draft fan pressure and, on the other hand, judges whether the furnace pressure is out of limit, and if so, outputs a furnace fault signal.

[0032] The DCS control system receives the furnace pressure signal and, on one hand, performs PID negative feedback control to keep the furnace negative pressure stable by adjusting the induced draft fan pressure and, on the other hand, judges whether the furnace pressure is out of limit, and if so, outputs a furnace fault signal. Specifically, the PID controller in the furnace negative pressure control model is adjusted to adjust the induced draft fan pressure, so that the furnace negative pressure is kept within a reasonable range, to simulate normal control of the furnace negative pressure stability; the PID control function in the furnace negative pressure control model is closed to calculate and judge the furnace negative pressure, to simulate the explosion accident condition of the furnace overpressure. In the normal operation state, the induced draft fan pressure is controlled by the PID to avoid the influence of other parameter disturbances on the furnace negative pressure, to ensure normal operation; when the induced draft fan works abnormally, the explosion accident caused by the too high furnace negative pressure can also be simulated in real time, to provide a theoretical basis for safety protection of the boiler control system.

[0033] Further, the furnace combustion model in the embodiment is a semi-empirical algorithm based on a zero-dimensional model. The zero-dimensional combustion model, also known as a single-zone model, is obtained by statistical analysis of a large number of combustion heat release processes, finding regularity, and using an empirical formula or curve fitting method to establish an empirical relationship between the parameters of the combustion heat release process, to simplify the complex combustion process into the relationship between several characteristic parameters. The semi-empirical algorithm (model) refers to an algorithm (model) that people try to describe the established mathematical model, which needs to be verified by experiments, and the model is corrected by adding experimental data on the basis of theory, and the model parameters are determined. That is, in the process of calculating the coal-fired furnace combustion model, some parameters in the formula are obtained by statistical analysis, rather than by mechanism analysis.

[0034] Further, the RT-Lab simulation platform performs simulation of the coal-fired furnace, specifically including the following steps:

[0035] The inlet parameter calculation step acquires the content of each element in the coal quality burned in the simulated coal-fired furnace by a coal quality analyzer, and obtains the air supply, air supply temperature, coal supply and coal powder temperature entering the coal-fired furnace by measurement, obtains the heat carried by the coal quality according to the calorific value of the coal quality, and obtains the enthalpy according to the physical properties of the air supply, and the heat and the enthalpy jointly constitute the heat entering the furnace ;

[0036] furnace outlet parameter step, the outlet flue gas temperature is calculated according to semi-empirical formula , wherein, is the theoretical combustion temperature, that is, the temperature that the combustion product can reach under the condition that the fuel is in the absolute system and the fuel is completely combusted, is an empirical coefficient, is the Stefan-Boltzmann constant, is the furnace wall area, is the furnace blackness, is the furnace heat retention coefficient, is the average heat capacity of the furnace, is the coal supply amount, is the furnace thermal effective coefficient; the flue gas mass at the outlet of the furnace can be obtained through mass conservation on the basis of the known furnace inlet parameters, and the enthalpy value of the outlet flue gas can be obtained according to the temperature, mass and properties of the outlet flue gas .

[0037] furnace pressure calculation step, the derivative of the furnace pressure with respect to time is derived according to the energy conservation equation and the ideal gas equation , wherein, is the heat entering the furnace, in the unit of kW; is the enthalpy value of the flue gas at the outlet of the furnace, in the unit of kW; is the coal supply amount, in the unit of kg / s; is the energy absorbed by the heat absorption surface of the furnace, in the unit of kW; and are divided into the specific heat and the volume of the flue gas of the furnace, in the unit of kJ / (kg·K) and m³; is the furnace pressure, in the unit of kPa; is the gas constant.

[0038] Further, the RT-LAB simulation platform comprises a model compiling module, a real-time simulation module and an interface module, the model compiling module mainly receives Simulink soft simulation model data from a host, and generates a program that can be run by the RT-LAB simulation platform after compiling and loading by adding opal series modules, the real-time simulation module performs real-time simulation after receiving the program that can be run, realizes rapid control prototype and hardware-in-the-loop, and simultaneously the real-time simulation module transmits data with the DCS control system through the interface module. Moreover, the real-time simulation module receives logic signals and data signals from the DCS control system; the DCS control system receives a furnace pressure signal simulated by the real-time simulation module, the logic signals comprise fault signals, and the data signals comprise coal supply amount, primary air pressure, secondary air pressure and induced draft fan air pressure signals

[0039] Further, the DCS control system comprises a field control level subsystem, a process control level subsystem and a process management level subsystem; the field control level subsystem is used for data acquisition and preprocessing of process non-controlled variables; the process control level subsystem is a core part of the DCS control system, and adjustment of the field production process is realized by implementing various control logics, namely, after receiving the furnace pressure signal from the RT-Lab simulation platform, on one hand, the furnace pressure is kept stable by adjusting the induced draft fan pressure through PID negative feedback control, and on the other hand, whether the furnace pressure is out of limit is judged, and if the furnace pressure is out of limit, a furnace fault signal is output; the process management level subsystem is a core display, operation and management device of the DCS control system, and is used for information input and acquisition, namely, a platform for exchanging information between the operator and the DCS control system.

Claims

1. A coal-fired furnace semi-physical simulation system based on RT-LAB, characterized in that: The RT-Lab simulation platform is connected with the host computer through a TCP / IP protocol, and the DCS control system is connected with the RT-Lab simulation platform through a data interface; The host computer sends Simulink soft simulation model data for simulating the coal-fired furnace to the RT-Lab simulation platform, the RT-Lab simulation platform simulates the coal-fired furnace and outputs a simulated furnace pressure signal to the DCS control system, and the DCS control system receives the furnace pressure signal and, on one hand, adjusts the induced draft fan pressure to keep the furnace negative pressure stable through PID negative feedback control, and on the other hand, judges whether the furnace pressure is out of limit, and if so, outputs a furnace fault signal. The Simulink soft simulation model in the host computer comprises a signal switching module and a furnace combustion model of the coal-fired boiler; the signal switching module judges according to the input fault signal, and if no fault is judged, the furnace combustion model receives the induced draft fan pressure signal from the DCS control system, otherwise, switches to the induced draft fan pressure signal generated internally by the furnace combustion model.

2. The RT-LAB based coal-fired furnace semi-physical simulation system of claim 1, wherein: The DCS control system receives the furnace pressure signal and, on one hand, adjusts the induced draft fan pressure to keep the furnace negative pressure stable through PID negative feedback control, and on the other hand, judges whether the furnace pressure is out of limit, and if so, outputs a furnace fault signal; specifically, the PID controller in the furnace negative pressure control model adjusts the induced draft fan pressure to keep the furnace negative pressure within a reasonable range, simulating normal control of the stable furnace negative pressure; the PID control function in the furnace negative pressure control model is closed to calculate and judge the furnace negative pressure, simulating the accident condition of the furnace overpressure explosion.

3. The RT-LAB based coal-fired furnace semi-physical simulation system according to claim 1 or 2, characterized in that: The furnace combustion model is a semi-empirical algorithm based on a zero-dimensional model.

4. The RT-LAB based coal-fired furnace hardware-in-the-loop simulation system of claim 1, wherein, The RT-Lab simulation platform simulates the coal-fired furnace, specifically including the following steps: The inlet parameter calculating step collects the content of each element in the coal burned by the simulated coal-fired furnace through a coal quality analyzer, and obtains the air supply amount, air supply temperature, coal supply amount and coal powder temperature entering the coal-fired furnace through measurement, obtains the heat carried by the coal according to the calorific value of the coal, and obtains the enthalpy according to the physical property of the air supply, and the heat and the enthalpy jointly constitute the heat entering the furnace ; A furnace outlet parameter step calculates the outlet flue gas temperature according to a semi-empirical formula , wherein, is a theoretical combustion temperature, is an empirical coefficient, is a Stirling-Boltzmann constant, is a furnace wall area, is a furnace blackness, is a furnace heat retention coefficient, is a furnace average heat capacity, is a coal supply amount, is a furnace thermal effective coefficient; knowing the furnace inlet parameters, the flue gas mass at the furnace outlet can be obtained through mass conservation, and the enthalpy of the outlet flue gas can be obtained according to the temperature, mass and physical properties of the outlet flue gas ; The furnace pressure calculation step derives a derivative of the furnace pressure with respect to time according to an energy conservation equation and an ideal gas equation as , wherein is heat entering the furnace, is an enthalpy value of flue gas at the furnace outlet, is a coal supply amount, is energy absorbed by a heat absorbing surface of the furnace, and is divided by a specific heat and a volume of flue gas of the boiler furnace, is the furnace pressure, is a gas constant; The RT-LAB simulation platform comprises a model compiling module, a real-time simulation module and an interface module; the model compiling module receives the Simulink soft simulation model data from the host computer, adds an opal series module, compiles and loads to generate a program that can be run by the RT-LAB simulation platform, the real-time simulation module performs real-time simulation after receiving the program that can be run, and the real-time simulation module transmits data with the DCS control system through the interface module.

5. The RT-LAB based coal-fired furnace hardware-in-the-loop simulation system of claim 4, wherein: The real-time simulation module receives a logic signal and a data signal from the DCS control system; the DCS control system receives a furnace pressure signal simulated by the real-time simulation module.

6. The RT-LAB based coal-fired furnace semi-physical simulation system of claim 5, wherein: The logic signal comprises a fault signal, and the data signal comprises a coal feed amount, a primary air pressure, a secondary air pressure and an induced draft fan pressure signal.

7. The RT-LAB based coal-fired furnace hardware-in-the-loop simulation system of claim 1, wherein: The DCS control system comprises a field control level subsystem, a process control level subsystem and a process management level subsystem; the field control level subsystem is used for data collection and preprocessing of process non-controlled variables, the process control level subsystem is used for adjusting the field production process by implementing various control logics, and the process management level subsystem is used for information input and collection.

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