System and method for predicting and calculating carbon dioxide emission of thermal power plant

Abstract

The invention relates to the technical field of carbon emission prediction, and discloses a system for predicting and calculating the carbon dioxide emission of a thermal power plant, which comprises a library module comprising an actual carbon emission factor associated data table of different coal types under different working conditions; the acquisition module is used for acquiring real-time working condition data and fire coal data; the control module is used for receiving / transmitting data; and the carbon emission prediction module is used for obtaining actual carbon emission factor data according to the carbon emission factor calculation model, and predicting carbon emission data according to the fire coal data transmitted by the acquisition module in real time and the actual carbon emission factor data. The system and the method for predicting and calculating the carbon dioxide emission of the thermal power plant can be applied to prediction and control of the carbon emission of various thermal power plants, can help thermal power plant managers to realize accurate control and management of the emission through real-time monitoring prediction and data analysis, reduce the influence of the carbon emission on the environment, and meanwhile, improve the reliability of the carbon dioxide emission of the thermal power plant. The system can also provide technical support for global climate change control and promote sustainable development.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission prediction, and in particular to a system and method for predicting and calculating carbon dioxide emission of a thermal power plant. Background Art

[0002] With the accelerated development of global industrialization and urbanization, carbon dioxide emissions continue to increase, leading to increasingly serious problems of global climate change. As one of the main sources of carbon dioxide emissions, thermal power plants have a significant impact on the global climate. Therefore, in the control of global climate change and the promotion of sustainable development, data on carbon emissions from thermal power plants can provide good technical support.

[0003] At present, if various thermal power plants need to collect and integrate carbon emission data, they need to have monitoring systems to obtain carbon emission data through long-term monitoring. However, the cost and maintenance cost of the monitoring system are not available in every thermal power plant. Therefore, there are great differences in carbon emission data, which cannot provide good technical support for global climate change control.

[0004] Moreover, as the main source of carbon emissions, thermal power plants are the focus of carbon emission assessment. If carbon emissions exceed the standard and no additional carbon emissions are purchased in advance, it will bring a series of negative impacts to thermal power plants, such as economic losses.

[0005] Therefore, in view of the current carbon emissions from thermal power plants, there is a need for a method that can be widely used in various thermal power plants and can accurately obtain carbon emissions, which can help thermal power plant managers to manage emissions.

[0006] Therefore, a system and method for predicting and calculating carbon dioxide emissions from thermal power plants are proposed to solve the above problems. Summary of the invention

[0007] 1. Technical issues to be solved

[0008] In view of the shortcomings of the prior art, the present invention provides a system and method for predicting and calculating carbon dioxide emissions from thermal power plants, which has the advantages of being applicable to carbon emissions monitoring and control of various thermal power plants, and solves the problem that the current configuration problems of carbon emission monitoring systems in various thermal power plants lead to differences in carbon emission data, and cannot provide good technical support for global climate change control. In addition, the inability to accurately control carbon emissions will also bring economic losses to thermal power plants and a series of negative impacts.

[0009] (II) Technical solution

[0010] The technical solution of the present invention to solve the above technical problem is as follows: A system for predicting and calculating carbon dioxide emissions from thermal power plants, comprising:

[0011] Library module: including the data table of actual carbon emission factors of different coal types under different working conditions;

[0012] Collection module: obtain real-time operating data and coal combustion data;

[0013] Control module: used to receive / transmit data;

[0014] Carbon emission prediction module: obtains actual carbon emission factor data based on the carbon emission factor calculation model, and predicts carbon emission data based on the coal combustion data and actual carbon emission factor data transmitted in real time by the acquisition module.

[0015] The beneficial effects of the present invention are: the system is easy to use and low-cost, and can be applied to the prediction and control of carbon emissions from various types of thermal power plants. Through real-time monitoring, prediction and data analysis, it can help thermal power plant managers to achieve precise control and management of emissions, reduce the impact of carbon emissions on the environment and prevent economic losses in thermal power plants. At the same time, the system can also provide technical support for global climate change control and promote sustainable development.

[0016] Based on the above technical solution, the present invention can also be improved as follows.

[0017] Furthermore, it also includes cloud servers:

[0018] The cloud server includes a library module for storing data, a data acquisition module for crawling and / or receiving data, and an analysis module for data processing.

[0019] Further, the library module includes:

[0020] The ideal carbon emission factor data, ideal carbon emission data, actual carbon emission data and actual carbon emission factor correlation data table for different types of coal under different working conditions.

[0021] Furthermore, the data acquisition module includes:

[0022] Internet crawling module: obtain coal type data and thermal power plant operating data through Ethernet;

[0023] Data receiving module: receives data transmitted by the control module.

[0024] Further, the analysis module includes:

[0025] Based on the data provided by the data acquisition module, the ideal carbon emission factor data, ideal carbon emission data, actual carbon emission data and the actual carbon emission factor related data table of different types of coal under different working conditions are calculated through analysis algorithms.

[0026] Furthermore, the coal burning data includes coal consumption and coal types.

[0027] Furthermore, it also includes:

[0028] Monitoring module: used to monitor and obtain actual carbon emission data of different types of coal under different working conditions.

[0029] Furthermore, the monitoring module includes:

[0030] Monitoring sensor group: set up at multiple locations in the flue gas channel of a thermal power plant to measure data.

[0031] A method for predicting and calculating carbon dioxide emissions from thermal power plants is as follows:

[0032] The acquisition module acquires coal type data, coal consumption data and operating condition data in real time;

[0033] The carbon emission prediction module obtains the actual carbon emission factor data according to the carbon emission factor calculation model;

[0034] The carbon emission prediction module calculates the actual carbon emission based on the real-time coal consumption data;

[0035] Specifically:

[0036] M CO2 =M coal ×EF i

[0037] in:

[0038] M co2 : Carbon emissions;

[0039] M coal : Coal consumption;

[0040] EF i : Carbon emission factors of coal types under actual working conditions.

[0041] Furthermore, the process of obtaining the actual carbon emission factor data by the carbon emission factor calculation model is as follows;

[0042] Obtain the coal type data, operating condition data and the actual carbon emission data matching the coal type data and operating condition data in the library module to calculate the carbon emission factor of the coal type under actual operating conditions:

[0043] Specifically:

[0044]

[0045] EF i =EF 理想 ×K i ;

[0046] EF 理想 : Carbon emission factor of coal type under ideal working conditions;

[0047] η 碳 : Carbon content of coal type;

[0048] K i : The ratio of the actual carbon emission factor to the ideal carbon emission factor under actual working conditions, the ratio of the carbon emissions obtained by actual measurement to the carbon emissions under ideal conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a system diagram of the present invention;

[0050] Figure 2 It is a structural schematic diagram of the monitoring module of the present invention;

[0051] Figure 3 This is a graph of carbon content of common coal types;

[0052] Figure 4 A comparison chart of the actual carbon emissions of a power plant and the carbon emissions predicted by the system of the present invention;

[0053] Figure 5 This is a flow chart for calculating the actual carbon emissions of the present invention;

[0054] Figure 6 This is a flow chart of the actual carbon emission factor calculation of the present invention;

[0055] Figure 7 This is a graph showing the relationship between carbon emission factor and unit type.

[0056] 1) Boiler; 2) First dust collector; 3) induced draft fan; 4) Booster fan; 5) Desulfurization equipment; 6) Chimney; 7) Second dust collector; 8) Heater; 9) Heating pipeline; 10) Third dust collector; 11) Condenser; 12) Pump; 13) Flow meter; 14) U23 multi-component infrared gas analyzer; A) Monitoring point. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments 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 creative work are within the scope of protection of the present invention.

[0058] In the embodiment, Figure 1 A system for predicting and calculating carbon dioxide emissions from thermal power plants is provided, comprising:

[0059] Library module: including the data table of actual carbon emission factors of different coal types under different working conditions;

[0060] Collection module: obtain real-time operating data and coal combustion data;

[0061] Among them, coal data include coal consumption and coal types;

[0062] Control module: used to receive / transmit data;

[0063] Carbon emission prediction module: obtains actual carbon emission factor data based on the carbon emission factor calculation model, and predicts carbon emission data based on the coal combustion data and actual carbon emission factor data transmitted in real time by the acquisition module.

[0064] Also includes cloud servers:

[0065] The cloud server includes a library module for storing data, a data acquisition module for crawling and / or receiving data, and an analysis module for data processing.

[0066] Further, the library modules include:

[0067] The ideal carbon emission factor data, ideal carbon emission data, actual carbon emission data and actual carbon emission factor correlation data table for different types of coal under different working conditions.

[0068] Furthermore, the data acquisition module includes:

[0069] Internet crawling module: obtain coal type data and thermal power plant operating data through Ethernet;

[0070] Data receiving module: accepts data transmitted by the upload module.

[0071] Furthermore, the analysis module includes:

[0072] Based on the data provided by the data acquisition module, the ideal carbon emission factor data, ideal carbon emission data, actual carbon emission data and the actual carbon emission factor related data table of different types of coal under different working conditions are calculated through analysis algorithms.

[0073] Through the above system, for thermal power plants and regions that have not installed monitoring systems, it is only necessary to determine the real-time coal type and operating conditions of the thermal power plant to obtain initial parameters, and then obtain the corresponding data parameters calculated by the analysis module in the library module through this system, so as to determine the carbon emission factor of the real-time coal type of the thermal power plant under the real-time operating conditions, and then the carbon emission data of the thermal power plant can be predicted and calculated;

[0074] The above system model can be applied to various types of thermal power plants to predict carbon emissions. It needs to be trained based on at least one historical data of the same type of thermal power plant. The process of training and forming the application of this system also includes:

[0075] Monitoring module: used to monitor and obtain actual carbon emission data of different types of coal under different working conditions;

[0076] The monitoring modules include:

[0077] Monitoring sensor group: set up at multiple locations in the flue gas channel of the thermal power plant to measure data;

[0078] By adopting a multi-sensor monitoring method, multiple sensors can be installed at different locations in the thermal power plant to monitor multiple data indicators at the same time, so as to fully understand the operating status and carbon emissions of the thermal power plant and improve the coverage and monitoring accuracy of the monitoring system;

[0079] like Figure 2 As shown, an embodiment of a monitoring sensor group for monitoring greenhouse gas emissions and sampling in a thermal power plant is now provided, which is specifically as follows:

[0080] After being generated, the flue gas from boiler 1 passes through the first dust collector 2, the induced draft fan 3, the booster fan 4 and the desulfurization equipment 5, and is finally discharged from the chimney 6;

[0081] Monitoring point A is set at the outlet of the first dust collector 2 or the outlet of the desulfurization equipment 5;

[0082] The monitored flue gas is firstly dedusted by the second dust collector 7 and heated by the heater 8 before entering the heating pipeline 9. The flue gas is heated to 140e in the pipeline. After being dedusted again by the third dust collector 10, it is condensed by the condenser 11 to remove moisture from the flue gas. The condensed water is discharged from the condenser pipe. After condensation, the flue gas flows through the multi-component infrared gas analyzer 14 to measure U (CO2) and Q (N2O) that have absorption in the infrared band. The measurement data is directly read out on the analyzer and can be recorded in one group every 15min.

[0083] While measuring the smoke components, the smoke volume is measured. The smoke volume is measured three times in parallel within the control period and the average value is taken;

[0084] Among them, the parameters such as dynamic pressure, static pressure and moisture content required for flue gas volume calculation are measured using a flue gas analyzer;

[0085] Flue gas temperature was measured by a mercury thermometer;

[0086] The atmospheric pressure at the measuring point is read by a portable barometer;

[0087] The flue size is provided by the power plant or measured in practice;

[0088] The fuel consumption rate and actual load data during the measurement period are recorded once every 30 minutes. The industrial analysis report of the fuel is provided by the power plant. The entire control period is generally not less than 3 hours, and the unit maintains stable operation during the control period.

[0089] The above monitoring can obtain the actual carbon emission data of a type of thermal power plant, which can be used as a historical data reference for the system of the present invention;

[0090] By obtaining the historical actual carbon emission data of a type of coal in a type of thermal power plant under a certain operating condition, the carbon emission factor can be introduced as the main parameter:

[0091] By comparing the carbon emissions released by a certain amount of coal burning under ideal conditions with the carbon emissions released by a certain amount of coal burning under actual conditions, the ratio K of actual carbon emissions to ideal carbon emissions under different conditions is obtained. i , that is, the ratio of the actual carbon emission factor to the ideal carbon emission factor under actual working conditions.

[0092] Based on this, a carbon emission factor calculation model is established, and a carbon emission prediction module for coal consumption and carbon emissions is established, so that carbon emissions can be calculated by collecting coal consumption;

[0093] Since different types of thermal power plants have different operating conditions for different units, their coal oxidation rates and boiler heat transfer efficiencies are different. Therefore, the carbon emissions and coal consumption data under different operating conditions require corresponding historical data for analysis, which can be obtained through the Internet crawling module, or can be transmitted to the data receiving module based on the data of the actual thermal power plant;

[0094] Among them, the operating condition type is classified according to the unit type. Common unit types include ultra-supercritical, supercritical, subcritical, etc. The combustion efficiency of each unit is roughly fixed;

[0095] like Figure 7 The carbon emission factor and unit type are shown in the figure:

[0096] Among them, the thermal efficiency of ultra-supercritical (S1) units exceeds 42%, while the thermal efficiency of supercritical (S2) and subcritical (S3) units can reach 35% to 38%. For small units, their thermal efficiency is lower than that of large units, such as the thermal efficiency of medium-temperature and medium-pressure S6U1 units;

[0097] In addition to the differences in units, it is also necessary to consider that the carbon content of each type of coal is different, which will also lead to different carbon emission factors;

[0098] like Figure 3 The carbon content of several common types of coal is listed in the figure. The carbon content of standard coal is about 90%, so the carbon emission factor of standard coal under ideal conditions is about 3.6*0.9=3.3, and the same applies to other different types of coal.

[0099] By multiplying the carbon emission factor of each type of coal under ideal working conditions and the ratio under corresponding working conditions, the actual carbon emission factor required can be obtained;

[0100] Therefore, if Figure 5 and Figure 6 As shown, a method for predicting and calculating carbon dioxide emissions from thermal power plants is proposed, as follows:

[0101] The acquisition module acquires coal type data, coal consumption data and operating condition data in real time;

[0102] The carbon emission prediction module obtains the actual carbon emission factor data according to the carbon emission factor calculation model;

[0103] The carbon emission prediction module calculates the actual carbon emission based on the real-time coal consumption data;

[0104] Specifically:

[0105]

[0106] in:

[0107] Carbon emissions;

[0108] M coal : Coal consumption;

[0109] EF i : Carbon emission factors of coal types under actual working conditions.

[0110] Furthermore, the process of obtaining the actual carbon emission factor data by the carbon emission factor calculation model is as follows;

[0111] Obtain the coal type data, operating condition data and the actual carbon emission data matching the coal type data and operating condition data in the library module to calculate the carbon emission factor of the coal type under actual operating conditions:

[0112] Specifically:

[0113]

[0114] EF i =EF 理想 ×K i ;

[0115] Among them, 44 / 12 in formula 1: represents the ratio of the relative atomic mass of carbon dioxide to the relative atomic mass of carbon;

[0116] EF 理想 : Carbon emission factor of coal type under ideal working conditions;

[0117] η 碳 : Carbon content of coal type;

[0118] K i : The ratio of the actual carbon emission factor to the ideal carbon emission factor under actual working conditions, the ratio of the carbon emissions obtained by actual measurement to the carbon emissions under ideal conditions.

[0119] like Figure 4 As shown, a power plant is provided to calculate the ratio of actual to ideal after actual measurement. The carbon emissions predicted by the system of the present invention have a small error with the actual data, and have good feasibility. It provides a method for power plants and regions without monitoring means, and can also be used synchronously with power plants and regions with monitoring means for auxiliary correction, providing prediction and control effects. At the same time, the system can also provide technical support for global climate change control and promote sustainable development.

[0120] In the figure:

[0121] actual emissions represent actual emissions;

[0122] Emissions from the energy-carbon model represents emissions from the energy-carbon model.

[0123] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0124] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A system for predicting and calculating carbon dioxide emissions from thermal power plants, characterized in that: include: Library module: including the data table of actual carbon emission factors of different coal types under different working conditions; Collection module: obtain real-time operating data and coal combustion data; Control module: used to receive / transmit data; Carbon emission prediction module: obtains actual carbon emission factor data based on the carbon emission factor calculation model, and predicts carbon emission data based on the coal combustion data and actual carbon emission factor data transmitted in real time by the acquisition module.

2. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to claim 1, characterized in that: Also includes cloud servers: The cloud server includes a library module for storing data, a data acquisition module for crawling and / or receiving data, and an analysis module for data processing.

3. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to claim 2, characterized in that: The library modules include: The ideal carbon emission factor data, ideal carbon emission data, actual carbon emission data and actual carbon emission factor correlation data table for different types of coal under different working conditions.

4. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to claim 2, characterized in that: The data acquisition module comprises: Internet crawling module: obtain coal type data and thermal power plant operating data through Ethernet; Data receiving module: receives data transmitted by the control module.

5. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to claim 2, characterized in that: The analysis module comprises: Based on the data provided by the data acquisition module, the ideal carbon emission factor data, ideal carbon emission data, actual carbon emission data and the actual carbon emission factor related data table of different types of coal under different working conditions are calculated through analysis algorithms.

6. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to claim 1, characterized in that: The coal burning data includes coal consumption and coal types.

7. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to any one of claims 1 to 6, characterized in that: Also includes: Monitoring module: used to monitor and obtain actual carbon emission data of different types of coal under different working conditions.

8. A system for predicting and calculating carbon dioxide emissions from thermal power plants according to claim 7, characterized in that: The monitoring module comprises: Monitoring sensor group: set up at multiple locations in the flue gas channel of a thermal power plant to measure data.

9. A method for predicting and calculating carbon dioxide emissions from a thermal power plant, characterized in that: The details are as follows: The acquisition module acquires coal type data, coal consumption data and operating condition data in real time; The carbon emission prediction module obtains the actual carbon emission factor data according to the carbon emission factor calculation model; The carbon emission prediction module calculates the actual carbon emission based on the real-time coal consumption data; Specifically: in: Carbon emissions; M coal : Coal consumption; EF i : Carbon emission factors of coal types under actual working conditions.

10. A method for predicting and calculating carbon dioxide emissions from a thermal power plant according to claim 9, characterized in that: The process of obtaining the actual carbon emission factor data by the carbon emission factor calculation model is as follows; Obtain the coal type data, operating condition data and the actual carbon emission data matching the coal type data and operating condition data in the library module to calculate the carbon emission factor of the coal type under actual operating conditions: Specifically: IF i =EF 理想 ×K i EF 理想 : Carbon emission factor of coal type under ideal working conditions; η 碳 : Carbon content of coal type; K i : The ratio of the actual carbon emission factor to the ideal carbon emission factor under actual working conditions, the ratio of the carbon emissions obtained by actual measurement to the carbon emissions under ideal conditions.

Images