Real-time metering system for carbon emission of coal combustion

Abstract

The invention provides a real-time metering system for coal combustion carbon emission. The real-time metering system comprises a data acquisition module, a data transmission module, a data processing and analysis module, a display and alarm module and an intelligent optimization module, the input end of the data transmission module is wirelessly connected to the output end of the data acquisition module; the input end of the data processing and analyzing module is wirelessly connected to the output end of the data transmission module; the input end of the display and alarm module is wirelessly connected to the output end of the data processing and analysis module; and the input end of the intelligent optimization module is wirelessly connected to the output end of the display and alarm module. According to the coal combustion carbon emission real-time metering system provided by the invention, through multi-source data fusion, a dynamic model library and intelligent error correction, the metering error is reduced compared with the prior art, the hybrid communication network and edge calculation ensure that the data transmission processing response time is short, the intelligent optimization module realizes intelligent management and optimization of carbon emission, and the metering efficiency is improved. And enterprises are assisted to reduce energy consumption and emission.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of carbon emission measurement, in particular to a real-time measurement system for carbon emission of coal combustion. BACKGROUND

[0002] In the global energy structure, coal is one of the main energy sources, and the carbon emission generated in the combustion process has a significant impact on the environment. Accurate real-time measurement of carbon emission of coal combustion is the key to carbon emission reduction, carbon trading and energy management.

[0003] The existing carbon emission measurement system has the problems of single data acquisition dimension, insufficient transmission stability, poor model adaptability and low intelligence level, which is difficult to meet the high-precision real-time measurement demand under complex combustion conditions, and lacks intelligent optimization management function for carbon emission.

[0004] Therefore, it is necessary to provide a real-time measurement system for carbon emission of coal combustion to solve the above technical problems. SUMMARY

[0005] The present application provides a real-time measurement system for carbon emission of coal combustion, which solves the problems of low measurement accuracy, poor real-time performance and insufficient intelligence of the existing system.

[0006] To solve the above technical problems, the present application provides a real-time measurement system for carbon emission of coal combustion, which comprises:

[0007] a data acquisition module, a data transmission module, a data processing and analysis module, a display and alarm module and an intelligent optimization module;

[0008] The input end of the data transmission module is wirelessly connected to the output end of the data acquisition module;

[0009] The input end of the data processing and analysis module is wirelessly connected to the output end of the data transmission module;

[0010] The input end of the display and alarm module is wirelessly connected to the output end of the data processing and analysis module;

[0011] The input end of the intelligent optimization module is wirelessly connected to the output end of the display and alarm module.

[0012] Preferably, the data acquisition module comprises a composite sensor array, an intelligent coal quality analysis unit and a multi-dimensional parameter acquisition subsystem, the composite sensor array comprises a temperature sensor, a piezoresistive pressure sensor, an FTIR gas analyzer, an ultrasonic flow sensor and a carbon isotope sensor.

[0013] Preferably, the temperature sensor is a fiber grating temperature sensor, the piezoresistive pressure sensor is a piezoresistive pressure sensor, and the FTIR gas analyzer is a Fourier transform infrared spectroscopy gas analyzer.

[0014] Preferably, the intelligent coal quality analysis unit comprises an online coal quality analyzer, an XRF spectrometer and an automatic sampling device, and the online coal quality analyzer is used for real-time detection of moisture, ash, volatile matter and fixed carbon content of coal.

[0015] Preferably, the data transmission module comprises a hybrid communication network and an edge computing node, the hybrid communication network adopts a combination of wired and wireless modes, the wired mode is an optical fiber and a cable, the wireless mode is 5G and NB-IoT, and a dual-link backup mechanism is provided.

[0016] Preferably, the edge computing node is used for filtering, aggregating and compressing preprocessing of collected data.

[0017] Preferably, the data processing and analysis module comprises a multi-source data fusion processing unit, a dynamic mathematical model library and an intelligent error correction system, the multi-source data fusion processing unit performs time synchronization, spatial alignment and feature extraction on multi-source data based on a deep learning algorithm.

[0018] Preferably, the dynamic mathematical model library comprises a conservation of mass model, a conservation of energy model, a combustion chemical reaction model and a machine learning carbon emission prediction model, and the intelligent error correction system establishes an error correction model through historical data and actual measurement data.

[0019] Preferably, the display and alarm module comprises a three-dimensional visual interactive interface and a multi-level intelligent alarm system, the three-dimensional visual interactive interface constructs a virtual three-dimensional model of the combustion equipment and system, and supports multi-dimensional interactive operation.

[0020] Preferably, the multi-level intelligent alarm system sets multi-level alarm thresholds, alarms through sound, light and short message, and automatically analyzes alarm causes and provides processing suggestions.

[0021] Compared with the related art, the real-time measurement system for carbon emissions of coal combustion provided by the present application has the following beneficial effects:

[0022] The present application provides a real-time measurement system for carbon emissions of coal combustion,

[0023] High measurement accuracy: through multi-source data fusion, dynamic model library and intelligent error correction, the measurement error is reduced compared with the prior art;

[0024] Strong real-time performance: hybrid communication network and edge computing ensure short data transmission and processing response time;

[0025] High intelligence level: intelligent optimization module realizes intelligent management and optimization of carbon emission, helping enterprises to reduce energy consumption and emission;

[0026] Good reliability: dual-link backup and multi-level alarm guarantee stable operation of the system;

[0027] Comprehensive functions: integrated metering, display, alarm, and optimization, providing a full-process solution. BRIEF DESCRIPTION OF DRAWINGS

[0028] Figure 1 A preferred embodiment of a real-time metering system for coal combustion carbon emission provided by the present application;

[0029] Figure 2 A flowchart of the real-time metering system is shown. Figure 1 DETAILED DESCRIPTION

[0030] The present application will be further described below in conjunction with the drawings and embodiments.

[0031] Please refer to Figure 1 and Figure 2 , wherein, Figure 1 A preferred embodiment of a real-time metering system for coal combustion carbon emission provided by the present application; Figure 2 A flowchart of the real-time metering system is shown. Figure 1 A real-time metering system for coal combustion carbon emission, comprising:

[0032] a data acquisition module, a data transmission module, a data processing and analysis module, a display and alarm module, and an intelligent optimization module;

[0033] The input end of the data transmission module is wirelessly connected to the output end of the data acquisition module;

[0034] The input end of the data processing and analysis module is wirelessly connected to the output end of the data transmission module;

[0035] The input end of the display and alarm module is wirelessly connected to the output end of the data processing and analysis module;

[0036] The input end of the intelligent optimization module is wirelessly connected to the output end of the display and alarm module.

[0037] The data acquisition module includes a composite sensor array, an intelligent coal quality analysis unit, and a multi-dimensional parameter acquisition subsystem, and the composite sensor array includes a temperature sensor, a piezoresistive pressure sensor, an FTIR gas analyzer, an ultrasonic flow sensor, and a carbon isotope sensor.

[0038] ​The temperature sensor is a fiber Bragg grating temperature sensor, the piezoresistive pressure sensor is a piezoresistive pressure sensor, and the FTIR gas analyzer is a Fourier transform infrared spectroscopy gas analyzer.

[0039] The intelligent coal quality analysis unit includes an online coal quality analyzer, an XRF spectrometer and an automatic acquisition device. The online coal quality analyzer is used to detect the moisture, ash, volatile matter and fixed carbon components of coal in real time.

[0040] The data transmission module includes a hybrid communication network and an edge computing node. The hybrid communication network adopts a combination of wired and wireless methods. The wired method is optical fiber and cable, and the wireless method is 5G and NB-IoT, and a dual-link backup mechanism is set.

[0041] The edge computing nodes are used to filter, aggregate, and compress the collected data.

[0042] The data processing and analysis module includes a multi-source data fusion processing unit, a dynamic mathematical model library and an intelligent error correction system. The multi-source data fusion processing unit performs time synchronization, spatial alignment and feature extraction on multi-source data based on a deep learning algorithm.

[0043] The dynamic mathematical model library includes a mass conservation model, an energy conservation model, a combustion chemical reaction model and a machine learning carbon emission prediction model. The intelligent error correction system establishes an error correction model through historical data and actual measurement data.

[0044] The display and alarm module includes a three-dimensional visual interactive interface and a multi-level intelligent alarm system. The three-dimensional visual interactive interface constructs a virtual three-dimensional model of the combustion equipment and system and supports multi-dimensional interactive operations.

[0045] Self-learning and self-adaptation capabilities: The system has self-learning and self-adaptation capabilities and can optimize its own algorithms and models through continuous learning and accumulation of experience. For example, after the system has been running for a period of time, it will automatically adjust the parameters and strategies of the intelligent optimization decision-making system based on actual carbon emission data and optimization results, thereby improving the accuracy and effectiveness of the optimization plan.

[0046] The multi-level intelligent alarm system sets multi-level alarm thresholds, alarms through sound, light, and text message, and automatically analyzes the cause of the alarm and provides treatment suggestions.

[0047] For example, when carbon emissions exceed the first-level threshold, the system will prompt that the combustion efficiency may be reduced and recommend adjusting the combustion parameters; when it exceeds the second-level threshold, the system will issue an emergency alarm and automatically start backup equipment or take other emergency measures.

[0048] The composite sensor array of the data acquisition module is installed at key positions of the boiler furnace and flue, in which the fiber grating temperature sensor monitors the furnace temperature in real time, the piezoresistive pressure sensor monitors the flue gas pressure, the FTIR gas analyzer detects the gas concentrations of CO2, CO and O2 in the flue gas, the ultrasonic flow sensor measures the flow rate of the flue gas, the carbon isotope sensor analyzes the carbon isotope composition, the automatic sampling device of the intelligent coal quality analysis unit automatically collects coal samples according to the combustion load, the online coal quality analyzer detects the moisture content, ash content and other components, the XRF spectrometer analyzes the element content, the power meter of the multi-dimensional parameter acquisition subsystem measures the boiler output power, the tachometer monitors the coal feeder speed, and the weighing sensor measures the coal input quantity of the coal bunker and the ash quantity of the ash bunker in real time.

[0049] In the data transmission module, the equipment in the boiler room transmits data through optical fiber / cable, the equipment around the coal yard transmits data wirelessly through 5G / NB-IoT212, the dual-link backup mechanism ensures automatic switching in case of communication interruption, and the edge computing node filters and denoises the collected temperature and pressure data, aggregates and compresses the data to reduce the amount of transmission data.

[0050] The multi-source data fusion processing unit of the data processing and analysis module uses deep learning algorithms to synchronize the timestamps and align the spatial coordinates of sensor data, coal quality data and operating parameters, extracts features through a neural network, automatically selects a combustion chemical reaction model based on the volatile matter and ash content of coal in a dynamic mathematical model library, calculates carbon emissions in combination with a mass conservation model, predicts emission trends through a machine learning prediction model, compares historical emission data with measured values through an intelligent error correction system, establishes an error correction model, and adjusts model parameters in real time.

[0051] The three-dimensional visualization interface of the display and alarm module constructs a three-dimensional model of the boiler and system, displays the CO2 emissions, emission trends and sensor data in real time, supports operators to scale and rotate the model to query parameters, sets three alarm thresholds in a multi-level intelligent alarm system, sounds and flashes an alarm and prompts to adjust the combustion parameters when the emissions exceed the first threshold, sends a short message to the administrator when the emissions exceed the second threshold, and automatically starts the backup burner when the emissions exceed the third threshold.

[0052] The carbon emission optimization decision system of the intelligent optimization module analyzes historical emission data and production data, generates decision schemes such as coal ratio adjustment and combustion temperature optimization, and automatically adjusts machine learning model parameters through continuous learning of actual emission data and optimization effects to improve the accuracy of optimization schemes.

[0053] Data acquisition step: real-time acquisition of multi-source data such as temperature, pressure, gas composition, flow, coal composition and operating parameters during the coal combustion process through the composite sensor array, intelligent coal quality analysis unit and multi-dimensional parameter acquisition subsystem.

[0054] Data transmission step: use hybrid communication network and edge computing node to transmit the collected data to data processing and analysis module after preliminary processing.

[0055] Data processing and analysis step: multi-source data fusion processing unit fuses the transmitted data, dynamic mathematical model library calculates real-time carbon emissions according to the fused data, and intelligent error correction system corrects the calculation result in real time.

[0056] Display and alarm step: three-dimensional visual interactive interface displays real-time carbon emissions, emission trend and other information, and multi-level intelligent alarm system sends alarm and provides processing suggestions when carbon emissions are abnormal.

[0057] Intelligent optimization step: carbon emission optimization decision system generates optimization decision scheme according to data analysis result, and the system continuously optimizes metering and optimization effect through self-learning and self-adaptation.

[0058] Data acquisition module installation: composite sensor array is installed at key positions of furnace and flue, including fiber bragg grating temperature sensor, piezoresistive pressure sensor, FTIR gas analyzer, ultrasonic flow sensor and carbon isotope sensor; weighing sensor is installed in coal bunker and ash bunker, power meter and speed meter are installed on combustion equipment; intelligent coal quality analysis unit is set near coal yard, including online coal quality analyzer and XRF spectrometer, and automatic sampling device is equipped.

[0059] Data transmission module building: optical fiber is used for wired transmission in boiler room, 5G wireless communication technology is used around coal yard, and edge computing node is set to preliminarily process data.

[0060] Data processing and analysis module configuration: multi-source data fusion processing unit is established, deep learning algorithm is used to fuse data; dynamic mathematical model library is constructed, including mass conservation model, energy conservation model, combustion chemical reaction model and machine learning prediction model; intelligent error correction system is set to collect historical data and actual measurement data for error correction.

[0061] Display and alarm module setting: three-dimensional visual interactive interface is developed to realize three-dimensional display of carbon emission data and equipment running state; multi-level alarm threshold is set, and alarm is sent through sound, light and short message when carbon emissions exceed the threshold.

[0062] Intelligent optimization module operation: carbon emission optimization decision system analyzes historical data to generate optimization decision scheme, such as adjusting coal ratio and optimizing combustion parameters, and continuously optimizes the scheme through self-learning.

[0063] The working principle of the real-time metering system for coal combustion carbon emissions provided by the application is as follows:

[0064] The data acquisition module collects full parameters of combustion in real time, transmits the preprocessed data to the data processing and analysis module through the data transmission module, calculates the carbon emission through multi-source fusion and dynamic model, and displays and alarms in real time through the display and alarm module, and the intelligent optimization module generates optimization instructions and feeds back to the data acquisition and processing module, forming a metering-optimization closed loop.

[0065] Compared with the related art, the real-time metering system for carbon emission of coal combustion has the following beneficial effects:

[0066] The application provides a real-time metering system for carbon emission of coal combustion,

[0067] High metering accuracy: through multi-source data fusion, dynamic model library and intelligent error correction, the metering error is reduced compared with the prior art;

[0068] Strong real-time performance: hybrid communication network and edge computing ensure short data transmission processing response time;

[0069] High intelligent level: the intelligent optimization module realizes intelligent management and optimization of carbon emission, and helps enterprises to reduce energy consumption and emission;

[0070] Good reliability: dual-link backup and multi-level alarm ensure stable operation of the system;

[0071] Comprehensive functions: integrating metering, display, alarm and optimization, the application provides a full-process solution.

Claims

1. A real-time measurement system for carbon emissions from coal combustion, characterized in that: include: Data acquisition module, data transmission module, data processing and analysis module, display and alarm module and intelligent optimization module; The input end of the data transmission module is wirelessly connected to the output end of the data acquisition module; The input end of the data processing and analysis module is wirelessly connected to the output end of the data transmission module; The input end of the display and alarm module is wirelessly connected to the output end of the data processing and analysis module; The input end of the intelligent optimization module is wirelessly connected to the output end of the display and alarm module.

2. The real-time measurement system for coal combustion carbon emissions according to claim 1 is characterized in that: The data acquisition module includes a composite sensor array, an intelligent coal quality analysis unit and a multi-dimensional parameter acquisition subsystem. The composite sensor array includes a temperature sensor, a piezoresistive pressure sensor, an FTIR gas analyzer, an ultrasonic flow sensor and a carbon isotope sensor.

3. The real-time measurement system for coal combustion carbon emissions according to claim 2 is characterized in that: The temperature sensor is a fiber Bragg grating temperature sensor, the piezoresistive pressure sensor is a piezoresistive pressure sensor, and the FTIR gas analyzer is a Fourier transform infrared spectroscopy gas analyzer.

4. The real-time measurement system for coal combustion carbon emissions according to claim 2, characterized in that: The intelligent coal quality analysis unit includes an online coal quality analyzer, an XRF spectrometer and an automatic acquisition device. The online coal quality analyzer is used to detect the moisture, ash, volatile matter and fixed carbon components of coal in real time.

5. The real-time measurement system for coal combustion carbon emissions according to claim 1, characterized in that: The data transmission module includes a hybrid communication network and an edge computing node. The hybrid communication network adopts a combination of wired and wireless methods. The wired method is optical fiber and cable, and the wireless method is 5G and NB-IoT, and a dual-link backup mechanism is set.

6. The real-time measurement system for coal combustion carbon emissions according to claim 5, characterized in that: The edge computing nodes are used to filter, aggregate, and compress the collected data.

7. The real-time measurement system for coal combustion carbon emissions according to claim 1, characterized in that: The data processing and analysis module includes a multi-source data fusion processing unit, a dynamic mathematical model library and an intelligent error correction system. The multi-source data fusion processing unit performs time synchronization, spatial alignment and feature extraction on multi-source data based on a deep learning algorithm.

8. The real-time measurement system for coal combustion carbon emissions according to claim 7, characterized in that: The dynamic mathematical model library includes a mass conservation model, an energy conservation model, a combustion chemical reaction model and a machine learning carbon emission prediction model. The intelligent error correction system establishes an error correction model through historical data and actual measurement data.

9. The real-time measurement system for coal combustion carbon emissions according to claim 1, characterized in that: The display and alarm module includes a three-dimensional visual interactive interface and a multi-level intelligent alarm system. The three-dimensional visual interactive interface constructs a virtual three-dimensional model of the combustion equipment and system and supports multi-dimensional interactive operations.

10. The real-time measurement system for coal combustion carbon emissions according to claim 9, characterized in that: The multi-level intelligent alarm system sets multi-level alarm thresholds, alarms through sound, light, and text message, and automatically analyzes the cause of the alarm and provides treatment suggestions.

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