Coal-fired boiler industrial steam supply system and using method thereof

Abstract

The invention provides a coal-fired boiler industrial steam supply system and a use method thereof, and relates to the field of industrial steam supply, the coal-fired boiler industrial steam supply system comprises: a combustion optimization module, which is used for realizing efficient combustion and reducing pollutant generation through dynamic combustion optimization and pollutant feedforward inhibition; the pollution co-processing module is used for realizing efficient removal of pollutants and cyclic utilization of resources through multi-stage co-pollution processing logic; the intelligent steam supply module is used for realizing efficient distribution of steam and energy utilization through a demand-driven steam network and energy gradient recovery; and the autonomous control module is used for realizing autonomous optimization and fault pre-judgment of the system through digital twin mirroring and swarm intelligence decision. Through the combustion optimization module and the pollution cooperative processing module, combustion characteristic prediction through machine learning is realized, and in combination with reverse adjustment of pollutant generation trend, dual optimization of combustion efficiency and environmental protection performance is realized, and the response speed and operation stability of the system are improved.

Description

Technical Field

[0001] The present invention relates to the field of industrial steam supply, and in particular to an industrial steam supply system for a coal-fired boiler and a method of using the same. Background Art

[0002] The industrial steam supply system of a coal-fired boiler is a heat energy supply device widely used in the fields of electricity, chemical industry, metallurgy, etc. Its core function is to generate high-temperature and high-pressure steam by burning coal, providing a stable and reliable heat source for industrial production.

[0003] Traditional combustion optimization technology aims to improve thermal efficiency, which often leads to an increase in the generation of pollutants (such as SOx and NOx); while end-of-pipe pollution control technology can reduce emissions, it will increase system energy consumption and operating costs.

[0004] Therefore, we have made improvements to this and proposed an industrial steam supply system for coal-fired boilers and a method for using the same. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem that the current combustion optimization technology aims to improve thermal efficiency, which leads to an increase in pollutant generation.

[0006] In order to achieve the above-mentioned purpose of the invention, the present invention provides the following coal-fired boiler industrial steam supply system and its use method to improve the above-mentioned problems.

[0007] The specific application is as follows: An industrial steam supply system for a coal-fired boiler, comprising: Combustion Optimization Module for achieving efficient combustion and reducing pollutant generation through dynamic combustion optimization and pollutant feedforward suppression; The pollution collaborative treatment module is used to achieve efficient removal of pollutants and resource recycling through multi-level collaborative pollution treatment logic; Intelligent steam supply module for efficient steam distribution and energy utilization through demand-driven steam networking and energy gradient recovery; The autonomous control module is used to achieve autonomous optimization and fault prediction of the system through digital twin mirroring and swarm intelligent decision-making.

[0008] As a preferred technical solution of this application, the combustion optimization module includes an adaptive fuel matching unit for dynamically controlling the air volume control based on real-time analysis of coal quality; The adaptive fuel matching unit comprises: Air volume regulation: Based on real-time analysis of coal quality, the ratio of primary air to secondary air is dynamically adjusted. The primary air volume is controlled at 180,000-260,000 Nm³ / h, and the secondary air volume is dynamically supplemented according to load demand. Bed temperature control, which is used to stabilize the bed temperature between 800°C and 950°C through multi-point temperature monitoring and adjust the bed temperature according to the sulfur content of the coal to optimize desulfurization efficiency and reduce nitrogen oxide generation; The fuel mixing ratio is used to dynamically adjust the mixing ratio of high calorific value coal and low calorific value coal according to the calorific value and volatile matter content of the coal, with a control range of 3:7 to 7:3.

[0009] As the preferred technical solution of this application, the pollution collaborative processing module includes: The pollutant intelligent routing unit is used to dynamically allocate treatment paths based on real-time monitoring data of flue gas composition, where high-sulfur, low-nitrogen flue gas preferentially enters the biological-chemical coupled desulfurization channel, and low-sulfur, high-nitrogen flue gas activates the plasma catalytic denitrification unit; The resource recycling trap unit is used to reinject desulfurization by-products and dust removal ash into the combustion zone and reconstruct them into porous adsorption materials in a high-temperature environment. The porosity of the adsorption material is controlled at 60%-70%, and the specific surface area reaches 200-300 m² / g.

[0010] As a preferred technical solution of this application, the intelligent steam supply module includes: The steam topology unit is used to build a steam supply neural network. It collects the pressure and temperature requirements of each steam-consuming equipment in real time through edge computing nodes, dynamically reconstructs the flow direction of the steam pipeline, and ensures that pressure fluctuations are controlled within ±5%; Condensate energy gradient recovery unit is used to recover heat energy in a graded manner according to the temperature difference of condensate. High-temperature condensate (>90°C) is directly reused to the boiler inlet, while medium- and low-temperature condensate (30-90°C) is used to preheat fuel or drive absorption refrigeration units. The phase change energy storage buffer unit is used to embed nanocomposite phase change materials in the steam main pipeline. The phase change temperature of the phase change material is controlled at 120℃-150℃, and the energy storage density reaches 200-300 kJ / kg.

[0011] As a preferred technical solution of this application, the autonomous control module includes: The digital twin mirror unit is used to build a three-dimensional dynamic model of the entire system. It combines real-time sensor data with historical operation records to simulate system behavior under different operating conditions, predict faults 10-15 minutes in advance, and generate optimization strategies. The swarm intelligence decision-making unit is used to deploy distributed AI agents in the control system. Each agent is responsible for a specific submodule and dynamically coordinates the global optimal solution through a competitive game mechanism. The communication delay between agents is controlled within 10ms.

[0012] As a preferred technical solution of this application, the combustion optimization module also includes: The pollutant feedforward suppression unit uses an algorithm to predict the formation trends of sulfur oxides and nitrogen oxides during the combustion phase, and adjusts the fuel mixture ratio and the oxygen concentration in the combustion zone inversely. When high sulfur oxide formation is predicted, the limestone injection rate is increased (the Ca / S molar ratio is controlled at 2.5-3.0); when high nitrogen oxide formation is predicted, the oxygen concentration in the combustion zone is reduced (the oxygen concentration is controlled at 3%-5%), thus inhibiting pollutant formation in advance.

[0013] The combustion flow field optimization unit ensures sufficient mixing of fuel and oxygen by dynamically adjusting the airflow distribution. The system automatically adjusts the airflow speed and direction according to the real-time temperature distribution in the combustion area to reduce unburned carbon residue and improve combustion efficiency.

[0014] As a preferred technical solution of this application, the autonomous control module also includes: The carbon traceability and transaction interface unit is used to integrate blockchain technology to record carbon emission data for each ton of steam in real time and automatically generate tradable carbon quota certificates.

[0015] A method for using an industrial steam supply system for a coal-fired boiler comprises the following steps: The adaptive fuel matching unit analyzes coal quality in real time and dynamically adjusts primary air volume (180,000-260,000 Nm³ / h) and secondary air volume to ensure sufficient combustion and reduce nitrogen oxide generation; According to the bed temperature monitoring data, the bed temperature is controlled between 800℃-950℃. For high-sulfur coal, the temperature is preferably between 850℃-950℃ to optimize the desulfurization efficiency, while for low-sulfur coal, the temperature is preferably between 800℃-850℃ to reduce the generation of nitrogen oxides. The optimal combustion curve is generated through a machine learning prediction model, and the fuel mixture ratio and oxygen concentration in the combustion area (3%-5%) are adjusted in advance to inhibit the formation of sulfur oxides and nitrogen oxides.

[0016] As the preferred technical solution of this application, the following steps are also included: Based on the real-time monitoring data of flue gas composition, the treatment path is dynamically allocated: high-sulfur and low-nitrogen flue gas enters the biological-chemical coupling desulfurization channel, and low-sulfur and high-nitrogen flue gas enters the plasma catalytic denitrification channel; The desulfurization by-products and dust removal ash are reinjected into the combustion zone and reconstructed into porous adsorption materials (porosity 60%-70%, specific surface area 200-300 m² / g) under high temperature environment to capture escaped pollutants for a second time.

[0017] As the preferred technical solution of this application, the following steps are also included: Build a demand-driven steam supply neural network, collect the pressure and temperature requirements of steam-consuming equipment in real time through edge computing nodes, and dynamically adjust the steam distribution path to ensure that pressure fluctuations are controlled within ±5%; Gradual recovery of condensate heat: high-temperature condensate (>90°C) is recycled to the boiler inlet, and medium- and low-temperature condensate (30-90°C) is used to preheat fuel or drive absorption refrigeration units; Embed nanocomposite phase change materials (phase change temperature 120-150°C, energy storage density 200-300 kJ / kg) in the steam main pipeline to smooth out steam load fluctuations; By building a 3D dynamic model of the entire system through digital twin mirror units and combining real-time sensor data with historical operation records, faults can be predicted 10-15 minutes in advance and optimization strategies can be generated. Deploy swarm intelligent decision-making units to coordinate the global optimal solution through the competitive game mechanism of distributed AI agents, and control the communication delay within 10ms; Integrate blockchain technology to record carbon emission data for each ton of steam in real time and automatically generate tradable carbon quota certificates.

[0018] Compared with the prior art, the present invention has the following beneficial effects: In the scheme of this application: 1. Through the combustion optimization module and pollution collaborative processing module, the system achieves dual optimization of combustion efficiency and environmental performance by predicting combustion characteristics through machine learning and combining it with reverse regulation of pollutant generation trends. This improves the system's response speed and operational stability, and solves the problem in existing technologies where combustion optimization technology focuses on improving thermal efficiency but leads to increased pollutant generation. 2. By setting up a swarm intelligence decision-making unit, the system achieves autonomous optimization and fault prediction for the coal-fired boiler industrial steam supply system by deploying distributed AI agents, combining digital twins with a competitive game mechanism. This significantly improves the system's intelligence level and operational efficiency, resolving the problem of existing technologies where the system can only passively handle faults after they occur, lacking the ability to predict potential faults in advance and proactively intervene. 3. The condensed water energy gradient recovery unit is installed to achieve graded recovery and efficient utilization of condensed water heat energy, solving the problems of insufficient waste heat recovery and serious energy waste in existing technologies. 4. By setting up a phase change energy storage buffer unit, the steam load fluctuation is smoothed and the system stability is improved, solving the problems of large load fluctuations and unstable system operation in the existing technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 System flow chart of the industrial steam supply system for coal-fired boilers provided for this application; Figure 2 This is a system flow chart of the fuel optimization module in the industrial steam supply system of a coal-fired boiler provided in this application; Figure 3This is a system flow chart of the pollution collaborative treatment module in the coal-fired boiler industrial steam supply system provided by this application; Figure 4 This is a system flow chart of the intelligent steam supply module in the coal-fired boiler industrial steam supply system provided in this application; Figure 5 This is a system flow chart of the autonomous control module in the coal-fired boiler industrial steam supply system provided in this application; Figure 6 This is a system flow chart of the autonomous control module and fuel optimization module in the coal-fired boiler industrial steam supply system provided in this application. DETAILED DESCRIPTION

[0020] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0021] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0022] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features and technical solutions therein may be combined with each other.

[0023] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0024] Example 1 Please refer to Figure 1 , an industrial steam supply system for a coal-fired boiler, comprising: Combustion Optimization Module, which achieves efficient combustion and reduces pollutant generation through dynamic combustion optimization and pollutant feedforward suppression; The pollution collaborative treatment module achieves efficient removal of pollutants and recycling of resources through multi-level collaborative pollution treatment; Intelligent steam supply module, which realizes efficient steam distribution and energy utilization through demand-driven steam network and energy gradient recovery; The autonomous control module realizes autonomous optimization and fault prediction of the system through digital twin mirroring and swarm intelligent decision-making.

[0025] The combustion optimization module reduces pollutant generation by dynamically adjusting combustion parameters (such as air volume, bed temperature, and fuel mixture ratio), providing a basis for "source emission reduction" for the subsequent pollution collaborative treatment module; the pollutant feedforward suppression unit predicts the generation trend of sulfur oxides and nitrogen oxides, adjusts the limestone injection amount and oxygen concentration in advance, and forms a "prediction-processing" system with the intelligent routing unit of the pollution collaborative treatment module.

[0026] The pollution co-treatment module reinjects desulfurization by-products and ash into the combustion zone through a resource recycling trap unit, which not only reduces waste emissions but also improves combustion efficiency and indirectly optimizes the steam generation process.

[0027] The treated clean flue gas enters the steam supply module to ensure that the steam quality is not affected by pollutants.

[0028] The intelligent steam supply module optimizes steam distribution and energy utilization in real time through the demand-driven steam topology unit and the condensate energy gradient recovery unit, providing rich operating data for the autonomous control module.

[0029] Further, such as Figure 1 and Figure 2 As shown, the combustion optimization module includes an adaptive fuel matching unit for dynamically controlling the air volume control based on real-time analysis of coal quality; The adaptive fuel matching unit includes: Air volume regulation: Based on real-time analysis of coal quality, the ratio of primary air to secondary air is dynamically adjusted. The primary air volume is controlled at 180,000-260,000 Nm³ / h, and the secondary air volume is dynamically supplemented according to load demand. Bed temperature control, which is used to stabilize the bed temperature between 800°C and 950°C through multi-point temperature monitoring and adjust the bed temperature according to the sulfur content of the coal to optimize desulfurization efficiency and reduce nitrogen oxide generation; Fuel mixing ratio, used to dynamically adjust the mixing ratio of high calorific value coal to low calorific value coal according to the calorific value and volatile matter content of coal, with a control range of 3:7 to 7:3; Machine learning prediction: Using historical data and real-time monitoring data, a combustion characteristics prediction model is trained to automatically generate an optimal combustion curve. The model can predict combustion efficiency and pollutant generation trends under different coal qualities and adjust combustion parameters in advance to ensure the system is always in optimal operation.

[0030] The combustion optimization module also includes: The pollutant feedforward suppression unit uses an algorithm to predict the formation trends of sulfur oxides and nitrogen oxides during the combustion phase, and adjusts the fuel mixture ratio and the oxygen concentration in the combustion zone inversely. When high sulfur oxide formation is predicted, the limestone injection rate is increased (the Ca / S molar ratio is controlled at 2.5-3.0); when high nitrogen oxide formation is predicted, the oxygen concentration in the combustion zone is reduced (the oxygen concentration is controlled at 3%-5%), thus inhibiting pollutant formation in advance.

[0031] The combustion flow field optimization unit dynamically adjusts airflow distribution to ensure adequate mixing of fuel and oxygen. Based on the real-time temperature distribution in the combustion area, the system automatically adjusts airflow speed and direction to reduce unburned carbon residue and improve combustion efficiency.

[0032] Further, such as Figure 1 and Figure 3 As shown, the pollution collaborative processing module includes: The intelligent pollutant routing unit dynamically allocates treatment paths based on real-time flue gas composition monitoring data. High-sulfur, low-nitrogen flue gas preferentially enters the bio-chemical desulfurization pathway, leveraging the synergistic effects of microbial metabolism and chemical adsorption. Low-sulfur, high-nitrogen flue gas activates the plasma catalytic denitrification unit, which decomposes nitrogen oxides through an electric field-induced free radical chain reaction. Flue gas with sulfur dioxide concentrations exceeding 500 mg / m³ preferentially enters the wet desulfurization pathway; flue gas with nitrogen oxide concentrations exceeding 300 mg / m³ preferentially enters the SCR denitrification pathway.

[0033] The resource recycling trap unit reinjects desulfurization byproducts (such as calcium sulfate) and dust removal ash into the combustion zone. Using the high-temperature environment, they are reconstituted into a porous adsorption material, capturing escaped pollutants for a second time. The adsorption material has a porosity of 60%-70% and a specific surface area of 200-300 m² / g, ensuring efficient capture of pollutants.

[0034] Example 2 The industrial steam supply system for coal-fired boilers provided in Example 1 is further optimized. Specifically, Figure 1 and Figure 4 As shown, the intelligent steam supply module includes: The steam topology unit builds a "neural network" for steam supply. Using edge computing nodes, it collects the pressure and temperature requirements of each steam-consuming device in real time and dynamically reconfigures the flow of steam pipelines. If the demand of a steam-consuming device fluctuates by more than 10%, the system automatically adjusts the steam distribution path to ensure pressure fluctuations are within ±5%.

[0035] The condensate energy gradient recovery unit recovers heat energy in a graded manner based on condensate temperature differences. High-temperature condensate (>90°C) is directly reused in the boiler inlet; medium- and low-temperature condensate (30-90°C) is used to preheat fuel or drive absorption chillers, assisting the plant's cooling system. The condensate recovery rate can exceed 95%.

[0036] The phase-change energy storage buffer unit, which embeds nanocomposite phase-change materials in the steam main pipeline, smooths out fluctuations in steam demand through latent heat storage. The phase-change material's transition temperature is controlled between 120°C and 150°C, and its energy storage density reaches 200-300 kJ / kg, ensuring system stability during load fluctuations.

[0037] Further, such as Figure 1 and Figure 5 As shown, the autonomous control module includes: The digital twin mirror unit builds a 3D dynamic model of the entire system, combining real-time sensor data with historical operating records to simulate system behavior under different operating conditions. The model can predict failures 10-15 minutes in advance and generate optimization strategies to ensure system stability.

[0038] The swarm intelligence decision-making unit deploys distributed AI agents within the control system. Each agent is responsible for a specific submodule (such as combustion, denitrification, and steam separation), dynamically coordinating the global optimal solution through a competitive game mechanism. Communication latency between agents is controlled within 10ms to ensure system responsiveness.

[0039] The carbon traceability and trading interface unit integrates blockchain technology to record carbon emissions data for each ton of steam in real time and automatically generate tradable carbon quota certificates. The carbon emissions data accuracy reaches ±2%, ensuring the transparency and credibility of carbon trading.

[0040] like Figure 6 As shown in the figure, the autonomous control module adjusts the parameters of the combustion optimization module (such as fuel mixture ratio, air volume, and bed temperature) in real time through the swarm intelligent decision-making unit and the digital twin mirror unit to ensure that the system is always in the optimal operating state.

[0041] Example 3 Please refer to Figure 2 、 Figure 3 、 Figure 4 and Figure 5 A method for using an industrial steam supply system for a coal-fired boiler comprises the following steps: The adaptive fuel matching unit analyzes coal quality in real time and dynamically adjusts primary air volume (180,000-260,000 Nm³ / h) and secondary air volume to ensure sufficient combustion and reduce nitrogen oxide generation; According to the bed temperature monitoring data, the bed temperature is controlled between 800℃-950℃. For high-sulfur coal, the temperature is preferably between 850℃-950℃ to optimize the desulfurization efficiency, while for low-sulfur coal, the temperature is preferably between 800℃-850℃ to reduce the generation of nitrogen oxides. The optimal combustion curve is generated through a machine learning prediction model, and the fuel mixture ratio and oxygen concentration in the combustion area (3%-5%) are adjusted in advance to inhibit the formation of sulfur oxides and nitrogen oxides.

[0042] Based on the real-time monitoring data of flue gas composition, the treatment path is dynamically allocated: high-sulfur and low-nitrogen flue gas enters the biological-chemical coupling desulfurization channel, and low-sulfur and high-nitrogen flue gas enters the plasma catalytic denitrification channel; The desulfurization by-products and dust removal ash are reinjected into the combustion zone and reconstructed into porous adsorption materials (porosity 60%-70%, specific surface area 200-300 m² / g) under high temperature environment to capture escaped pollutants for a second time.

[0043] Build a demand-driven steam supply neural network, collect the pressure and temperature requirements of steam-consuming equipment in real time through edge computing nodes, and dynamically adjust the steam distribution path to ensure that pressure fluctuations are controlled within ±5%; Gradual recovery of condensate heat: high-temperature condensate (>90°C) is recycled to the boiler inlet, and medium- and low-temperature condensate (30-90°C) is used to preheat fuel or drive absorption refrigeration units; Embed nanocomposite phase change materials (phase change temperature 120-150°C, energy storage density 200-300 kJ / kg) in the steam main pipeline to smooth out steam load fluctuations; By building a 3D dynamic model of the entire system through digital twin mirror units and combining real-time sensor data with historical operation records, faults can be predicted 10-15 minutes in advance and optimization strategies can be generated. Deploy swarm intelligent decision-making units to coordinate the global optimal solution through the competitive game mechanism of distributed AI agents, and control the communication delay within 10ms; Integrate blockchain technology to record carbon emission data for each ton of steam in real time and automatically generate tradable carbon quota certificates.

[0044] In the present invention, unless otherwise specified or limited, the terms "installed," "connected," "connect," "fixed," etc. should be understood in a broad sense. For example, they can refer to fixed connection, detachable connection, or integration; mechanical connection, electrical connection, or communication; direct connection or indirect connection through an intermediate medium; internal communication between two elements or interaction between two elements, unless otherwise specified. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0045] Obviously, the embodiments described above are only some embodiments of the present invention, rather than all embodiments. The preferred embodiments of the present invention are given in the accompanying drawings, but they do not limit the patent scope of the present invention. The present invention can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present invention more thorough and comprehensive. Although the present invention has been described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned specific embodiments, or to make equivalent replacements for some of the technical features therein. Any equivalent structure made using the contents of the present invention specification and drawings, directly or indirectly used in other related technical fields, is also within the scope of patent protection of the present invention.

Claims

1. An industrial steam supply system for a coal-fired boiler, characterized in that: include: Combustion Optimization Module for achieving efficient combustion and reducing pollutant generation through dynamic combustion optimization and pollutant feedforward suppression; The pollution collaborative treatment module is used to achieve efficient removal of pollutants and resource recycling through multi-level collaborative pollution treatment logic; Intelligent steam supply module for efficient steam distribution and energy utilization through demand-driven steam networking and energy gradient recovery; The autonomous control module is used to achieve autonomous optimization and fault prediction of the system through digital twin mirroring and swarm intelligent decision-making.

2. The industrial steam supply system for coal-fired boilers according to claim 1, characterized in that: The combustion optimization module includes an adaptive fuel matching unit for dynamically controlling air volume control based on real-time analysis of coal quality; The adaptive fuel matching unit comprises: Air volume regulation: Based on real-time analysis of coal quality, the ratio of primary air to secondary air is dynamically adjusted. The primary air volume is controlled at 180,000-260,000 Nm³ / h, and the secondary air volume is dynamically supplemented according to load demand. Bed temperature control, which is used to stabilize the bed temperature between 800°C and 950°C through multi-point temperature monitoring and adjust the bed temperature according to the sulfur content of the coal to optimize desulfurization efficiency and reduce nitrogen oxide generation; The fuel mixing ratio is used to dynamically adjust the mixing ratio of high calorific value coal and low calorific value coal according to the calorific value and volatile matter content of the coal, with a control range of 3:7 to 7:

3.

3. The industrial steam supply system for coal-fired boilers according to claim 2, characterized in that: The pollution collaborative processing module includes: The pollutant intelligent routing unit is used to dynamically allocate treatment paths based on real-time monitoring data of flue gas composition, where high-sulfur, low-nitrogen flue gas preferentially enters the biological-chemical coupled desulfurization channel, and low-sulfur, high-nitrogen flue gas activates the plasma catalytic denitrification unit; The resource recycling trap unit is used to reinject desulfurization by-products and dust removal ash into the combustion zone and reconstruct them into porous adsorption materials in a high-temperature environment. The porosity of the adsorption material is controlled at 60%-70%, and the specific surface area reaches 200-300 m² / g.

4. The industrial steam supply system for coal-fired boilers according to claim 3, characterized in that: The intelligent steam supply module comprises: The steam topology unit is used to build a steam supply neural network. It collects the pressure and temperature requirements of each steam-consuming equipment in real time through edge computing nodes, dynamically reconstructs the flow direction of the steam pipeline, and ensures that pressure fluctuations are controlled within ±5%; Condensate energy gradient recovery unit is used to recover heat energy in a graded manner according to the temperature difference of condensate. High-temperature condensate (>90°C) is directly reused to the boiler inlet, while medium- and low-temperature condensate (30-90°C) is used to preheat fuel or drive absorption refrigeration units. The phase change energy storage buffer unit is used to embed nanocomposite phase change materials in the steam main pipeline. The phase change temperature of the phase change material is controlled at 120℃-150℃, and the energy storage density reaches 200-300 kJ / kg.

5. The industrial steam supply system for coal-fired boilers according to claim 4, characterized in that: The autonomous control module includes: The digital twin mirror unit is used to build a three-dimensional dynamic model of the entire system. It combines real-time sensor data with historical operation records to simulate system behavior under different operating conditions, predict faults 10-15 minutes in advance, and generate optimization strategies. The swarm intelligence decision-making unit is used to deploy distributed AI agents in the control system. Each agent is responsible for a specific submodule and dynamically coordinates the global optimal solution through a competitive game mechanism. The communication delay between agents is controlled within 10ms.

6. The industrial steam supply system for coal-fired boilers according to claim 5, characterized in that: The combustion optimization module also includes: The pollutant feedforward suppression unit uses an algorithm to predict the formation trends of sulfur oxides and nitrogen oxides during the combustion phase, and adjusts the fuel mixture ratio and the oxygen concentration in the combustion zone inversely. When high sulfur oxide formation is predicted, the limestone injection rate is increased (Ca / S molar ratio is controlled at 2.5-3.0); when high nitrogen oxide formation is predicted, the oxygen concentration in the combustion zone is reduced (oxygen concentration is controlled at 3%-5%), thus suppressing pollutant formation in advance. The combustion flow field optimization unit ensures sufficient mixing of fuel and oxygen by dynamically adjusting the airflow distribution. The system automatically adjusts the airflow speed and direction according to the real-time temperature distribution in the combustion area to reduce unburned carbon residue and improve combustion efficiency.

7. The industrial steam supply system for coal-fired boilers according to claim 6, characterized in that: The autonomous control module further includes: The carbon traceability and transaction interface unit is used to integrate blockchain technology to record carbon emission data for each ton of steam in real time and automatically generate tradable carbon quota certificates.

8. A method for using a coal-fired boiler industrial steam supply system, using the coal-fired boiler industrial steam supply system according to claim 7, characterized in that: The following steps are involved: The adaptive fuel matching unit analyzes coal quality in real time and dynamically adjusts primary air volume (180,000-260,000 Nm³ / h) and secondary air volume to ensure sufficient combustion and reduce nitrogen oxide generation; According to the bed temperature monitoring data, the bed temperature is controlled between 800℃-950℃. For high-sulfur coal, the temperature is preferably between 850℃-950℃ to optimize the desulfurization efficiency, while for low-sulfur coal, the temperature is preferably between 800℃-850℃ to reduce the generation of nitrogen oxides. The optimal combustion curve is generated through a machine learning prediction model, and the fuel mixture ratio and oxygen concentration in the combustion area (3%-5%) are adjusted in advance to inhibit the formation of sulfur oxides and nitrogen oxides.

9. The method for using the industrial steam supply system for a coal-fired boiler according to claim 8, characterized in that: The following steps are also included: Based on the real-time monitoring data of flue gas composition, the treatment path is dynamically allocated: high-sulfur and low-nitrogen flue gas enters the biological-chemical coupling desulfurization channel, and low-sulfur and high-nitrogen flue gas enters the plasma catalytic denitrification channel; The desulfurization by-products and dust removal ash are reinjected into the combustion zone and reconstructed into porous adsorption materials under high temperature environment to capture the escaped pollutants for a second time.

10. The method for using the industrial steam supply system for a coal-fired boiler according to claim 9, characterized in that: The following steps are also included: Build a demand-driven steam supply neural network, collect the pressure and temperature requirements of steam-consuming equipment in real time through edge computing nodes, and dynamically adjust the steam distribution path to ensure that pressure fluctuations are controlled within ±5%; Gradual recovery of condensate heat energy: high-temperature condensate is recycled to the boiler inlet, and medium- and low-temperature condensate is used to preheat fuel or drive absorption refrigeration units; Nanocomposite phase change materials are embedded in the main steam pipeline to smooth out fluctuations in steam load; By building a 3D dynamic model of the entire system through digital twin mirror units and combining real-time sensor data with historical operation records, faults can be predicted 10-15 minutes in advance and optimization strategies can be generated. Deploy swarm intelligent decision-making units to coordinate the global optimal solution through the competitive game mechanism of distributed AI agents, and control the communication delay within 10ms; Integrate blockchain technology to record carbon emission data for each ton of steam in real time and automatically generate tradable carbon quota certificates.

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