Energy-saving combustion intelligent monitoring and optimizing system and method for supercritical carbon dioxide coal-fired boiler

Abstract

The invention discloses an intelligent monitoring and optimizing system and method for energy-saving combustion of a supercritical carbon dioxide coal-fired boiler. The intelligent monitoring and optimizing system comprises a data acquisition and transmission module, a digital twin modeling module, a fault diagnosis and early warning module and an energy efficiency optimization module. The data acquisition and transmission module is used for acquiring real-time data in the operation process of the supercritical carbon dioxide coal-fired boiler; the digital twinborn modeling module is used for constructing a digital twinborn model according to the real-time data and realizing analog simulation of the combustion process of the coal-fired boiler; the fault diagnosis and early warning module is used for simulating the running state of the coal-fired boiler according to the real-time data and carrying out diagnosis and early warning on the fault of the coal-fired boiler; and the energy efficiency optimization module is used for monitoring the energy efficiency of the coal-fired boiler according to the real-time data and performing real-time optimization according to the monitoring result. By considering intelligence, economy, safety and operability and aiming at the large-capacity coal-fired power plant boiler, the monitoring data can be obtained in real time, intelligent judgment is carried out, early warning is sent out, the boiler operation safety and emergency response capability can be improved, and safety accidents possibly occurring in the operation process can be effectively prevented.

Description

Technical Field

[0001] The present invention relates to the field of monitoring and optimization of supercritical carbon dioxide coal-fired boilers, and particularly to an intelligent monitoring and optimization system and method for energy-saving combustion of supercritical carbon dioxide coal-fired boilers. Background Art

[0002] As an important part of the global energy structure, coal-fired power plants not only play a key role in power generation but also have irreplaceable significance in ensuring the stability of energy supply. However, with the continuous improvement of environmental protection and energy efficiency requirements, traditional coal-fired power plants are facing a series of severe challenges, including the pressure of energy conservation and emission reduction, optimization of operation processes, and improvement of equipment reliability. As an important component equipment in coal-fired power plants, coal-fired boilers play a crucial role in the energy conservation, emission reduction, peak shaving, and frequency modulation transformation of coal-fired power plants.

[0003] Although current coal-fired boilers are equipped with many advanced monitoring and control systems, they still face some problems that need to be solved urgently. First of all, the combustion efficiency and thermal energy utilization rate of supercritical carbon dioxide coal-fired boilers still need to be further improved. Currently, common problems in supercritical carbon dioxide coal-fired boilers include incomplete combustion and large heat losses, which not only waste a large amount of energy but also lead to more pollutant emissions. Especially during low-load operation, the thermal efficiency of the boiler will decrease significantly, making it difficult to meet the requirements of flexible dispatching and energy conservation. Secondly, the internal control system of the boiler is often difficult to adjust precisely under different loads and operating conditions, resulting in large fluctuations in the operating state of the boiler, and even problems such as overheating and coking, increasing the risk of equipment failure and affecting the economy and safety of the power plant.

[0004] How to design a digital twin model of an energy-saving combustion, intelligent monitoring, and regulation system for supercritical carbon dioxide coal-fired boilers to achieve real-time monitoring, intelligent regulation, diagnosis, and early warning of the operating characteristics of supercritical carbon dioxide coal-fired boilers under different operating conditions, and to achieve the purpose of operation optimization is a problem that needs to be solved by those skilled in the art. Summary of the Invention

[0005] In order to solve the problems existing in the prior art, the purpose of the present invention is to provide an intelligent monitoring and optimization system and method for energy-saving combustion of supercritical carbon dioxide coal-fired boilers. The system realizes intelligent monitoring, fault early warning, energy efficiency optimization, and predictive maintenance of the equipment by obtaining data of supercritical carbon dioxide coal-fired boilers in real time and using digital twin technology to perform virtual modeling and analysis of the equipment.

[0006] To achieve the above purpose, the present invention provides the following technical solutions:

[0007] An intelligent monitoring and optimization system for energy-saving combustion of a supercritical carbon dioxide coal-fired boiler, including a data acquisition and transmission module, a digital twin modeling module, a fault diagnosis and early warning module, and an energy efficiency optimization module;

[0008] The data acquisition and transmission module is used to collect real-time data and on-site images during the operation of the supercritical carbon dioxide coal-fired boiler. The real-time data includes boiler combustion parameters, boiler operation status parameters, and boiler external environment parameters, and transmits them to the digital twin modeling module, the fault diagnosis and early warning module, and the energy efficiency optimization module;

[0009] The digital twin modeling module is used to construct a digital twin model of the supercritical carbon dioxide coal-fired boiler according to the real-time data, and realize the simulation of the combustion process of the supercritical carbon dioxide coal-fired boiler;

[0010] The fault diagnosis and early warning module is used to simulate the operation status of the supercritical carbon dioxide coal-fired boiler according to the real-time data, and diagnose and early warn the faults of the supercritical carbon dioxide coal-fired boiler;

[0011] The energy efficiency optimization module is used to monitor the energy efficiency of the supercritical carbon dioxide coal-fired boiler according to the real-time data and optimize it in real time according to the monitoring results.

[0012] Further, the real-time data is collected by temperature sensors, pressure sensors, flow sensors, and vibration sensors; the boiler combustion parameters include fuel quantity, air volume, flue gas temperature, and flue gas composition, the boiler operation status parameters include flue gas tail temperature, flue gas tail pressure, and intake air volume, and the boiler external environment parameters include environmental temperature and humidity.

[0013] Further, the data acquisition and transmission module includes a 5G base station antenna, a baseband device, a radio frequency device, an indoor small base station, and a signal repeater.

[0014] Further, the digital twin modeling module includes a physical structure model, a combustion process model, and a heat transfer model of the boiler;

[0015] The physical structure model is used to estimate the pipeline laying according to the actual physical size of the supercritical carbon dioxide coal-fired boiler and the three-dimensional space layout in the auxiliary system;

[0016] The combustion process model is used to simulate and optimize fuel combustion characteristics, combustion stability, and flue gas emission processes;

[0017] The heat transfer model is used to simulate the heat generated by combustion and the heat transfer with the steam side or other circulating working fluid sides.

[0018] Furthermore, when constructing the digital twin model, multi-source data fusion and deep learning algorithms are adopted to achieve data fusion and iterative optimization of information flow, control flow, data flow and decision flow between the physical space and the virtual space; the digital twin model is solved and verified through the defect data of the supercritical carbon dioxide coal-fired boiler.

[0019] Furthermore, the fault diagnosis and early warning module monitors the changes in key parameters of the supercritical carbon dioxide coal-fired boiler, identifies potential fault modes, and combines past fault cases to predict the occurrence time and impact degree of faults. If potential faults are detected, warning signals are sent and corresponding fault diagnosis reports are generated to provide fault handling suggestions for operation and maintenance personnel.

[0020] Furthermore, the energy efficiency optimization module simulates and analyzes the energy efficiency of the boiler under different combustion parameters, determines the optimal combination of combustion parameters through multi-objective optimization algorithms, realizes efficient combustion, energy conservation and emission reduction of the supercritical carbon dioxide coal-fired boiler; and dynamically adjusts the combustion parameters according to real-time operation data to ensure that the supercritical carbon dioxide coal-fired boiler can maintain the best energy efficiency state under different working conditions.

[0021] Furthermore, it also includes a 3D visualization module, a safety application management module and a user operation platform. The safety application management module is used for the safety management and protection of the supercritical carbon dioxide coal-fired boiler and the surrounding environment;

[0022] The 3D visualization module is used to display the internal structure of the supercritical carbon dioxide coal-fired boiler, the combustion process simulated by the digital twin modeling module, and the actual scene around the supercritical carbon dioxide coal-fired boiler;

[0023] The safety application management module includes safety helmets and safety suits equipped with sensors, and cameras installed in fixed scenarios. When it is detected that the staff in the scenario is not equipped with a safety helmet, a reminder will be sent to the user operation platform;

[0024] The user operation platform is used for the operator to operate the platform to realize the function configuration, parameter setting and operation control of each module.

[0025] Furthermore, the 3D visualization module includes a laser scanner, an optical projector, a multi-camera module, intelligent devices equipped with sensors and cameras, and human-computer interaction devices, and the 3D visualization module also has human-computer interaction functions.

[0026] A method for intelligent monitoring and optimization of energy-saving combustion of a supercritical carbon dioxide coal-fired boiler includes:

[0027] Collect real-time data and on-site images during the operation of the supercritical carbon dioxide coal-fired boiler. The real-time data includes boiler combustion parameters, boiler operation status parameters, and boiler external environment parameters;

[0028] Construct a digital twin model of a supercritical carbon dioxide coal-fired boiler based on real-time data to realize the simulation of the combustion process of the supercritical carbon dioxide coal-fired boiler;

[0029] Simulate the operating state of the supercritical carbon dioxide coal-fired boiler according to real-time data, and diagnose and warn of the faults of the supercritical carbon dioxide coal-fired boiler;

[0030] Monitor the energy efficiency of the supercritical carbon dioxide coal-fired boiler according to real-time data and optimize it in real time according to the monitoring results.

[0031] Compared with the prior art, the present invention provides an intelligent monitoring and optimization system for energy-saving combustion of a supercritical carbon dioxide coal-fired boiler, which has the following beneficial effects:

[0032] (1) The intelligent monitoring and optimization system for energy-saving combustion of a supercritical carbon dioxide coal-fired boiler of the present invention has the advantage of being intelligent. Through the data acquisition and transmission module, various operating parameters of the supercritical carbon dioxide coal-fired boiler can be obtained in real time, such as flue gas composition, combustion temperature, pressure, flow rate, etc. These data are accurately transmitted to the digital twin modeling module to construct a digital twin model of the supercritical carbon dioxide coal-fired boiler. The digital twin model can reflect the operating state of the physical boiler in real time. Based on the real-time data and the digital twin model, the energy efficiency optimization module can use multi-objective optimization algorithms to accurately adjust the combustion parameters to achieve the best combustion effect. The combination of this real-time monitoring and precise optimization significantly improves the combustion efficiency of the supercritical carbon dioxide coal-fired boiler, reduces fuel consumption, and realizes the goal of energy conservation and emission reduction.

[0033] (2) The intelligent monitoring and optimization system for energy-saving combustion of a supercritical carbon dioxide coal-fired boiler of the present invention improves the safety during the operation of the boiler. The fault diagnosis and warning module is an important part of this system. Through in-depth analysis of the boiler operation data by the digital twin model, this module can timely detect potential fault hazards and issue warning signals. Operators can take corresponding maintenance measures in advance according to the warning information to avoid the occurrence of faults, thereby ensuring the safe and stable operation of the supercritical carbon dioxide coal-fired boiler. And it can provide a detailed fault analysis report to help operators quickly locate the cause of the fault, shorten the fault handling time, and reduce the losses caused by fault shutdown.

[0034] (3) The energy-saving combustion intelligent monitoring and optimization system for a supercritical carbon dioxide coal-fired boiler of the present invention improves the overall economic efficiency. By applying advanced multi-objective optimization algorithms and energy efficiency optimization models, the combustion process of the supercritical carbon dioxide coal-fired boiler is continuously optimized, achieving efficient utilization of fuel and effective control of emissions. This optimization not only reduces fuel costs but also decreases environmental pollution, enhancing the economic and social benefits of the supercritical carbon dioxide coal-fired boiler. In addition, the system can flexibly adjust the combustion strategy according to the actual operating conditions of the boiler and market demands to meet the energy efficiency requirements under different working conditions. This flexibility and adaptability enable the supercritical carbon dioxide coal-fired boiler to maintain competitiveness in a complex and changing market environment.

[0035] Furthermore, the energy-saving combustion intelligent monitoring and optimization system for a supercritical carbon dioxide coal-fired boiler of the present invention enhances the user experience. The user operation platform is an important interface for operators to interact with the system. The user operation platform provided by this system has a friendly interface and simple operation, enabling operators to easily get started and quickly master the various functions of the system. The user operation platform also supports multiple operation modes and custom setting functions to meet the personalized needs of different operators. At the same time, the system provides detailed operation guides and help documents, providing comprehensive technical support and training services for operators.

[0036] Furthermore, by setting up a three-dimensional visualization module, intuitive display is carried out through the three-dimensional visualization module. Operators can clearly see the combustion situation inside the boiler, thus realizing real-time monitoring of the combustion process. Brief Description of the Drawings

[0037] Figure 1 It is a schematic diagram of an energy-saving combustion intelligent monitoring and optimization system for a supercritical carbon dioxide coal-fired boiler proposed by the present invention. Detailed Embodiment

[0038] To facilitate the understanding of the present invention, the present invention will be described more comprehensively with reference to the relevant drawings. The preferred embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0039] In addition, an element in the present invention is referred to as "fixed to" or "disposed on" another element, and it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation.

[0040] Digital twin technology can achieve comprehensive monitoring and real-time optimization of physical devices, operating states, and energy efficiency by constructing digital models. By feeding key data in real time back into the virtual model, it enables managers to accurately simulate and predict various operating parameters in the virtual environment, so as to detect potential faults in advance and make precise maintenance decisions without disturbing actual production, significantly improving the reliability and service life of the equipment.

[0041] In one embodiment, as Figure 1 shown, there is provided an intelligent monitoring and optimization system for energy-saving combustion of a supercritical carbon dioxide coal-fired boiler, including a data acquisition and transmission module, a digital twin modeling module, a three-dimensional visualization module, a fault diagnosis and early warning module, an energy efficiency optimization module, a safety application management module, and a user operation platform; the supercritical carbon dioxide coal-fired boiler is connected to the digital twin modeling module, the digital twin modeling module is connected to the three-dimensional visualization module, and the three-dimensional visualization module is connected to the user operation platform. The supercritical carbon dioxide coal-fired boiler is also connected to the data acquisition and transmission module, the data acquisition and transmission module is connected to the fault diagnosis and safety application management module, the early warning module, and the energy efficiency optimization module, the fault diagnosis and safety application management module is connected to the safety application management module, and the safety application management module is connected to the supercritical carbon dioxide coal-fired boiler.

[0042] The data acquisition and transmission module is used to collect real-time data and on-site images during the operation of a supercritical carbon dioxide coal-fired boiler, including boiler combustion parameters, boiler operation status parameters, and boiler external environment parameters. These are obtained through acquisition devices such as sensors and transmitted to the digital twin modeling module by wired or wireless means, providing data support for subsequent digital twin modeling and energy efficiency optimization. The sensors include temperature sensors, pressure sensors, flow sensors, vibration sensors, etc., which are used to collect the operation status and environmental parameters of the supercritical carbon dioxide coal-fired boiler equipment. The boiler combustion parameters include fuel quantity, air volume, flue gas temperature, and flue gas composition, etc. The boiler operation status parameters include flue gas tail temperature, flue gas tail pressure, and intake air volume, etc. The boiler external environment parameters include environmental temperature and humidity, etc. 5G base station antennas, baseband equipment, and radio frequency equipment are used, combined with indoor small base stations and signal repeaters, to provide 5G network coverage and communication services. At the same time, a memory is equipped to back up the data of the fault diagnosis and warning module and the energy efficiency optimization module twice in this memory to prevent economic losses to the entire system due to data damage.

[0043] The digital twin modeling module constructs a digital twin model of the supercritical carbon dioxide coal-fired boiler based on the real-time data collected during the operation of the boiler, which is used to simulate and simulate the combustion process of the supercritical carbon dioxide coal-fired boiler, providing a virtual test platform for energy efficiency optimization and fault diagnosis. The digital twin modeling module includes the physical structure model, combustion process model, heat transfer model, etc. of the boiler, which can accurately reflect the actual operation status of the supercritical carbon dioxide coal-fired boiler. The physical structure model, according to the actual physical size of the supercritical carbon dioxide coal-fired boiler and the three-dimensional space layout in the auxiliary system, avoids equipment collisions and estimates pipeline laying, improving the accuracy of economic analysis. The combustion process model is used to simulate and optimize combustion process characteristics such as fuel combustion characteristics, combustion stability, and flue gas emissions. The heat transfer model is used to simulate the heat generated by combustion and the heat transfer on the steam side or other circulating working fluid sides. When constructing the digital twin model, the present invention uses multi-source data fusion and deep learning algorithms to achieve data fusion and iterative optimization of information flow, control flow, data flow, and decision flow between the physical space and the virtual space. By introducing defect data of the supercritical carbon dioxide coal-fired boiler, the digital twin model is solved and verified to ensure the accuracy and reliability of the model.

[0044] A 3D visualization module for intuitively displaying the internal structure, combustion process of a supercritical carbon dioxide coal-fired boiler, and the actual scene around the supercritical carbon dioxide coal-fired boiler; the 3D visualization module includes a laser scanner, a light projector, a multi-camera module, intelligent devices equipped with sensors and cameras, a human-computer interaction device, etc. At the same time, the 3D visualization module also has a human-computer interaction function. Users can perform operations such as zooming, rotating, and translating on the 3D simulation scene through input devices such as a mouse and a keyboard to achieve a full-range observation of the combustion process of the supercritical carbon dioxide coal-fired boiler. In addition, the 3D visualization module can also display the real-time operation data of the supercritical carbon dioxide coal-fired boiler in the form of charts, animations, etc. in the 3D simulation scene to help users more intuitively understand the operation status and energy efficiency of the supercritical carbon dioxide coal-fired boiler.

[0045] A fault diagnosis and early warning module for simulating the operation status of a supercritical carbon dioxide coal-fired boiler, diagnosing and warning of faults in the supercritical carbon dioxide coal-fired boiler to facilitate later daily maintenance and inspection; the fault diagnosis and early warning module includes a processor and a memory. By monitoring the changes in key parameters of the supercritical carbon dioxide coal-fired boiler, potential fault modes are identified, and the occurrence time and impact degree of faults are predicted in combination with past fault cases. Once a potential fault is detected, the fault diagnosis and early warning module will immediately issue an early warning signal and generate a corresponding fault diagnosis report to provide fault handling suggestions for operation and maintenance personnel; during the fault diagnosis and early warning process, the present invention uses machine learning algorithms to mine and analyze fault data, establish a fault knowledge base and a diagnosis model, and improve the accuracy and reliability of fault diagnosis and early warning by continuously learning and updating the fault knowledge base and the diagnosis model.

[0046] An energy efficiency optimization module for monitoring the energy efficiency of a supercritical carbon dioxide coal-fired boiler and optimizing it in real time according to the monitoring results; the energy efficiency optimization module includes a processor and a memory. By simulating and analyzing the energy efficiency of the boiler under different combustion parameters, the optimal combination of combustion parameters is determined to achieve efficient combustion and energy conservation and emission reduction of the supercritical carbon dioxide coal-fired boiler; during the energy efficiency optimization process, the present invention uses a multi-objective optimization algorithm to optimize the energy efficiency of the supercritical carbon dioxide coal-fired boiler. By comprehensively considering multiple objectives such as the operation efficiency, energy consumption, and emissions of the boiler, the comprehensive optimization of the energy efficiency of the supercritical carbon dioxide coal-fired boiler is achieved. At the same time, the energy efficiency optimization module can also dynamically adjust the combustion parameters according to the real-time operation data to ensure that the supercritical carbon dioxide coal-fired boiler can maintain the best energy efficiency state under different working conditions.

[0047] The safety application management module is used for the safety management and protection of supercritical carbon dioxide coal-fired boilers and the surrounding environment. The safety application management module includes safety helmets and safety suits equipped with sensors, and cameras installed in fixed scenarios. When it detects that the staff in the scenario is not equipped with a safety helmet, it will send a reminder to the user operation platform.

[0048] The user operation platform is used for the operator to operate the platform. The operator can realize the function configuration, parameter setting, and operation control of each module. The user operation platform includes functions such as real-time data display, historical data query, alarm information prompt, and fault diagnosis report viewing, which facilitate the operator to understand the operation status and energy efficiency of the supercritical carbon dioxide coal-fired boiler. The user operation platform adopts a friendly user data interaction interface and modular design, and can be extended and customized according to user needs. At the same time, the user operation platform also supports multiple data formats and communication protocols, which is convenient for data exchange and information sharing with other systems. In addition, the user operation platform manages the permissions of operators and sets network security protection measures to ensure that the information in the system is not leaked.

[0049] Another embodiment of the present invention provides a method for intelligent monitoring and optimization of energy-saving combustion of a supercritical carbon dioxide coal-fired boiler, including:

[0050] Collect real-time data and on-site images during the operation of the supercritical carbon dioxide coal-fired boiler. The real-time data includes boiler combustion parameters, boiler operation status parameters, and boiler external environment parameters;

[0051] According to the real-time data, construct a digital twin model of the supercritical carbon dioxide coal-fired boiler to realize the simulation of the combustion process of the supercritical carbon dioxide coal-fired boiler;

[0052] Simulate the operation status of the supercritical carbon dioxide coal-fired boiler according to the real-time data, and diagnose and warn of the faults of the supercritical carbon dioxide coal-fired boiler;

[0053] Monitor the energy efficiency of the supercritical carbon dioxide coal-fired boiler according to the real-time data and optimize it in real time according to the monitoring results.

[0054] Compared with the previous DCS-based control system, this intelligent control and optimization system for energy-saving combustion of coal-fired boilers considers from four aspects: intelligence, economy, safety, and operability. For large-capacity coal-fired power plant boilers, it can obtain monitoring data in real time and make intelligent judgments and issue warnings, which helps to improve the safety and emergency response ability of boiler operation, effectively prevent potential safety accidents during operation, and comprehensively manage and control parameters such as boiler temperature, pressure, and flow through a three-dimensional visualization model and a user operation platform.

[0055] The above description is only for the best embodiments of the present invention, but it should not be construed as a limitation on the claims. The present invention is not limited to the above embodiments, and its specific structure allows for variations. Any variations made within the scope of protection of the independent claims of the present invention are within the scope of protection of the present invention.

[0056] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this invention belongs. The terms used in the description of the present invention herein are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

Claims

1. A supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system, characterized in that: It includes data acquisition and transmission module, digital twin modeling module, fault diagnosis and early warning module and energy efficiency optimization module; The data acquisition and transmission module is used to collect real-time data and on-site images during the operation of the supercritical carbon dioxide coal-fired boiler. The real-time data includes boiler combustion parameters, boiler operating status parameters, and boiler external environment parameters, and transmits them to the digital twin modeling module, the fault diagnosis and early warning module, and the energy efficiency optimization module; The digital twin modeling module is used to construct a digital twin model of the supercritical carbon dioxide coal-fired boiler based on the collected real-time data of the supercritical carbon dioxide coal-fired boiler, so as to simulate the combustion process of the supercritical carbon dioxide coal-fired boiler; The fault diagnosis and early warning module is used to simulate the operating state of the supercritical carbon dioxide coal-fired boiler according to real-time data, and diagnose and warn the fault of the supercritical carbon dioxide coal-fired boiler; The energy efficiency optimization module is used to monitor the energy efficiency of the supercritical carbon dioxide coal-fired boiler according to real-time data and optimize it in real time according to the monitoring results.

2. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: The real-time data is collected through temperature sensors, pressure sensors, flow sensors and vibration sensors; the boiler combustion parameters include fuel quantity, air volume, flue gas temperature and flue gas composition; the boiler operation status parameters include flue gas tail temperature, flue gas tail pressure and air intake volume; the boiler external environment parameters include ambient temperature and humidity.

3. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: The data acquisition and transmission module includes a 5G base station antenna, a baseband device, a radio frequency device, an indoor small base station and a signal repeater.

4. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: The digital twin modeling module includes a physical structure model, a combustion process model, and a heat transfer model of the boiler; The physical structure model is used to estimate the pipeline laying according to the actual physical size of the supercritical carbon dioxide coal-fired boiler and the three-dimensional spatial arrangement of the auxiliary system; The combustion process model is used to simulate and optimize fuel combustion characteristics, combustion stability and smoke emission process; The heat transfer model is used to simulate the heat generated by combustion and the heat transfer between the steam side or other circulating working fluid side.

5. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: When constructing the digital twin model, multi-source data fusion and deep learning algorithms are used to achieve data fusion and iterative optimization of information flow, control flow, data flow and decision flow in physical space and virtual space; the digital twin model is solved and verified through the defect data of supercritical carbon dioxide coal-fired boilers.

6. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: The fault diagnosis and early warning module monitors the changes in key parameters of the supercritical carbon dioxide coal-fired boiler, identifies potential failure modes, and predicts the occurrence time and impact of the failure in combination with previous failure cases. If a potential failure is detected, a warning signal is issued and a corresponding fault diagnosis report is generated to provide fault handling suggestions for operation and maintenance personnel.

7. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: The energy efficiency optimization module simulates the boiler energy efficiency under different combustion parameters, determines the optimal combustion parameter combination through a multi-objective optimization algorithm, and realizes efficient combustion and energy saving and emission reduction of the supercritical carbon dioxide coal-fired boiler; and dynamically adjusts the combustion parameters according to real-time operating data to ensure that the supercritical carbon dioxide coal-fired boiler can maintain the optimal energy efficiency state under different operating conditions.

8. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 1 is characterized in that: It also includes a three-dimensional visualization module, a safety application management module and a user operation platform. The safety application management module is used for the safety management and protection of supercritical carbon dioxide coal-fired boilers and the surrounding environment; The three-dimensional visualization module is used to display the internal structure of the supercritical carbon dioxide coal-fired boiler, the combustion process simulated by the digital twin modeling module, and the real-time scene around the supercritical carbon dioxide coal-fired boiler; The safety application management module includes a safety helmet and safety clothing equipped with sensors, and a camera installed in a fixed scene. When it is detected that a worker in the scene is not equipped with a safety helmet, a reminder will be issued to the user operation platform; The user operation platform is used by operators to operate the platform to realize function configuration, parameter setting and operation control of each module.

9. The supercritical carbon dioxide coal-fired boiler energy-saving combustion intelligent monitoring and optimization system according to claim 8 is characterized in that: The three-dimensional visualization module includes a laser scanner, a light projector, a multi-camera module, an intelligent device equipped with sensors and cameras, and a human-computer interaction device, and the three-dimensional visualization module also has a human-computer interaction function.

10. A method for intelligent monitoring and optimization of energy-saving combustion of a supercritical carbon dioxide coal-fired boiler based on the system according to any one of claims 1 to 9, characterized in that: include: Collect real-time data and on-site images during the operation of supercritical carbon dioxide coal-fired boilers. The real-time data includes boiler combustion parameters, boiler operating status parameters, and boiler external environment parameters; Based on real-time data, a digital twin model of a supercritical carbon dioxide coal-fired boiler is constructed to simulate the combustion process of the supercritical carbon dioxide coal-fired boiler; Simulate the operating status of supercritical carbon dioxide coal-fired boilers based on real-time data, and diagnose and warn of supercritical carbon dioxide coal-fired boiler failures; The energy efficiency of supercritical carbon dioxide coal-fired boilers is monitored based on real-time data and optimized in real time based on the monitoring results.

Images