34 results about "Embodied carbon" patented technology

The invention provides an evaluation method and system for carbon emission factors of fuel and a storage medium, and relates to the technical field of environmental protection and energy conservation, and the method comprises the steps: obtaining a plurality of historical carbon emission factors corresponding to the fuel and historical data of external factors; based on the historical carbon emission factors and the historical data of the external factors, screening out influence factors corresponding to the carbon emission factors from the external factors; based on the influence factors, determining significant influence factors corresponding to the carbon emission factors; matching each significant influence factor with different weight coefficients, and acquiring actual data of each significant influence factor; and determining an actual carbon emission factor based on the weight coefficient and the actual data. Under the condition that the carbon emission does not need to be accurately measured, a professional laboratory is not needed to carry out chemical analysis on the carbon content and the carbon oxidation rate of fossil fuel to obtain the fuel carbon emission factor, the time hysteresis of carbon emission accounting is effectively shortened, and the requirements of enterprises for real-time monitoring of carbon emission and dynamic adjustment of the production process are met.

The application discloses a circulating fluidized bed boiler with ash partition measurement, comprising: a furnace, a separator and an ash parameter analysis system; the furnace has at least two regions in the circumferential direction, and a bottom slag sampling device for obtaining a bottom slag sample of each region is arranged below each region; a separator is correspondingly arranged above each region, and a fly ash sampling device is arranged at the separator outlet flue at the top of each separator, which is used for obtaining a fly ash sample of the corresponding region; the ash parameter analysis system is in communication with the bottom slag sampling device and the fly ash sampling device. The ash parameter partition measurement method is adopted to quickly obtain the particle size distribution and carbon content of the ash in different regions, the obtained data are used to guide the operation personnel to accurately adjust the fuel quantity, air quantity, circulating material and slag discharge quantity of different regions, the local fluidization is reduced, the combustion in the oxygen deficiency region is improved, the content of combustible substances in the ash is reduced, and the overall fuel combustion efficiency is improved.

The invention discloses a simplified online monitoring method for the combustion efficiency of a power station boiler, and belongs to the technical field of thermal equipment performance state monitoring and diagnos.The method comprises the steps that unit generation power, the fuel quantity, the total air volume and coal composition parameters are collected; calculating fuel converted carbon content, lower calorific value, theoretical air quantity and excess air coefficient; defining a carbon burnout coefficient and a fuel characteristic coefficient, and constructing and iteratively solving an incomplete combustion equation taking the carbon burnout coefficient as an unknown number; and calculating the combustion efficiency of the boiler according to the solved carbon burnout coefficient. According to the method, the carbon contents of the fly ash and the slag are unified to the carbon burn-out coefficient, and based on combustion mechanism derivation, high-precision and all-working-condition online monitoring of the boiler combustion efficiency can be realized without an additional expensive monitoring instrument, and the technical problem that the boiler combustion efficiency is difficult to accurately monitor online is solved.

The invention relates to the technical field of bituminous coal carbon content prediction, and discloses a bituminous coal coal quality industrial analysis-based unit calorific value carbon content prediction method, which comprises the following steps of 1, sampling a target coal type for industrial analysis, and detecting the total moisture Mt, the ash content Aar, the volatile component Var and the fixed carbon FCar content of the target coal type; measuring the calorific value of the sampled coal to obtain the lower calorific value Qnet, ar of the coal type; step 2, calculating a dry ash-free basis volatile component Vdaf and a lower calorific value Qnet, daf of the target coal type; 3, predicting the carbon content CQdaf of the dry ash-free basis unit calorific value of the target coal type; and step 4, calculating the unit calorific value carbon content CQar of the target coal type. According to the method, the unit calorific value carbon content of the bituminous coal can be accurately predicted, and coal purchase is guided; the coal carbon content is further calculated by using the unit calorific value carbon content calculated by the method, the prediction precision is very high, and the correlation coefficient can reach 1-10-10.

This invention discloses a low-carbon peak-shaving system and method for using ammonia-blended fuel. The low-carbon peak-shaving system includes a coal-fired boiler, a coal-fired burner, an ammonia burner, a coal-fired generator, a clean energy generator, an ammonia preparation device, an ammonia storage system, ammonia pipelines, a first switch, a second switch, a third switch, a first transformer, a second transformer, a third transformer, output lines, and a power grid. The ammonia preparation device, the ammonia storage system, and the ammonia burner are connected via ammonia pipelines. This invention utilizes the excess electricity generated by the coal-fired unit to produce ammonia, enabling the actual grid-connected power of the coal-fired unit to reach the required grid-connected power. Under full load of the coal-fired unit, ammonia is injected into the main combustion zone of the furnace using a suitable flow rate and method, while controlling the combustion stability within the furnace and the NO at the furnace outlet. X Under the premise that the concentration and carbon content of fly ash have a relatively small impact, the system's renewable energy absorption capacity and carbon emissions can be effectively improved.

The invention discloses a coal gasification fine slag incineration system which comprises a sorting device, a first drying device, a conveying device, a granulating device and an incineration device. Wherein the sorting device is used for separating the gas refining slag into a first material and a second material, and the carbon content of the first material is larger than that of the second material; the first drying device is used for drying a first material, and the first drying device is communicated with the black water tank; the conveying device is used for conveying the dried first material; the granulating device is used for treating the dried first material and obtaining a granular material; the incineration device is used for incinerating particle materials. According to the coal gasification fine slag incineration system, due to the fact that the first material is sorted out and incinerated, the heat value of the material entering the incineration device can be increased; the first material forms a particle material and enters the incineration device, so that the retention time of the material in the incineration device can be prolonged. Therefore, the combustion efficiency and the burn-off rate of the coal gasification fine slag can be improved.

The application discloses a multi-parameter regulated boiler combustion efficiency dynamic optimization method. The specific operation steps are as follows: real-time acquisition of combustion parameters from a power plant system, pre-processing of the collected original data, and feature selection after data pre-processing; the feature data selected and pre-processed are taken as input according to time sequence to construct an IGWO-transformer prediction model; taking the degree of electricity coal consumption, nitrogen oxide emission concentration and fly ash carbon content as optimization targets, a NSGA-III algorithm is used for multi-objective optimization; aiming at the control requirements of the feature data, an independent PID controller is configured for each control object, the actual value collected is compared with the target set value, the control deviation is calculated as the input signal of the PID controller, and the controller is driven to perform dynamic adjustment. The application has the beneficial effects that the data processing and generalization ability are enhanced, accurate prediction and regulation are realized, and the combustion efficiency is improved; the economy and environmental protection are balanced, and dynamic optimization is realized.

The application discloses a method for determining a blast furnace gas blending ratio of a coal-fired power plant boiler, which comprises the following steps: firstly, assuming a mass ratio z of the blast furnace gas entering the boiler to the actual burned coal; secondly, performing CO2 balance calculation by using the input coal quality characteristic parameters, the blast furnace gas characteristic data, the fly ash carbon content, the slag carbon content, the existing operation flue gas dry basis oxygen content, the dry basis CO2 volume fraction and the dry basis CO volume fraction; thirdly, obtaining the real mass ratio z of the blast furnace gas entering the boiler to the actual burned coal by iterative calculation of the CO2 balance; and finally, determining the final blast furnace gas blending ratio by combining the unburned combustible material with the supplied fuel mass ratio l u The application can determine the blast furnace gas blending ratio of the coal-fired power plant boiler, so as to meet the thermal state operation requirements of the coal-fired power plant, improve the economic operation level of the unit, and also can strengthen the accurate supervision on the blast furnace gas blending ratio.

Various embodiments include cementitious compositions with low levels of embodied greenhouse gas emissions, in particular carbon dioxide, as a result of its production and / or use compared to conventional cementitious materials, such as portland cement. Various embodiments include any cementitious material or materials with low embodied carbon, as well as any material produced using this cement.

The application discloses a kind of boiler combustion monitoring method and device, including to monitoring unit injection flue gas;Carbon dioxide concentration is detected to air inlet end and data is recorded;By injecting oxygen in reaction furnace, carbon particles in flue gas can be fully combusted in furnace;Carbon dioxide concentration is detected to air outlet end and data is recorded;The difference of carbon dioxide concentration in different ports determines how much residual carbon carried in flue gas.The beneficial effects of the present application are that by real-time detection of fly ash carbon content, it is convenient for staff to quickly record data and feedback maintenance, which is beneficial to guide the correct adjustment of wind-coal ratio and improve the level of boiler combustion control;Reasonably control the index of fly ash carbon content, which is beneficial to reduce power generation cost and improve the economy of unit operation.

This invention discloses a method, system, and medium for calculating emissions from fuel engines based on the hydrogen balance method, relating to the field of data processing technology. The method first acquires data such as fuel composition, emission concentration, intake air flow rate, temperature, and humidity; then calculates the actual exhaust mass flow rate based on the intake air flow rate or fuel flow rate; finally, it combines the exhaust molar mass and NO... x The system calculates pollutant mass flow rate by applying correction factors and pollutant concentrations. It includes data acquisition, exhaust flow calculation, and pollutant flow calculation units. This invention replaces carbon balance with hydrogen balance, is not limited by fuel carbon content, and is compatible with low-carbon and zero-carbon fuels such as highly hydrogen-blended fuels, methanol, pure hydrogen, and pure ammonia. Coupled with intake air humidity, turbocharging and intercooling, and exhaust component correction, it significantly improves the accuracy of exhaust flow rate and pollutant emission calculations, solving the problem of traditional carbon balance methods failing under zero-carbon fuel conditions. It is suitable for accurate emission measurement and certification of various engines.

Disclosed in the present invention is a systematic carbon emissions reduction method for a whole process of steel production and casting, comprising the steps of: hydrogen injection in a blast furnace. Hydrogen comes from a nuclear hydrogen production system, hydrogen production based on water electrolysis, and hydrogen production based on coke oven gas-steam reforming; electric energy consumed by hydrogen production based on water electrolysis comes from gas power generation, steam residual pressure power generation, solar power generation, wind energy power generation, and nuclear power generation; combustible gas used for gas power generation is coke oven gas, blast furnace gas, and converter gas; steam in steam residual pressure power generation comes from a sintering waste heat boiler; steam in hydrogen production based on coke oven gas-steam reforming is low-pressure steam after residual pressure power generation; the final product is a cast steel profile, a casting material of a high-carbon spheroidal graphite cast iron profile having a carbon content of 2-4% and a silicon content of 2-4%, and a casting material of a high-carbon spheroidal graphite cast steel profile having a carbon content of 1-2% and a silicon content of 1-1.9%; the waste of the final product enters a converter or an electric furnace for cyclic smelting.

The invention discloses a sintering method and system for grading carbon distribution. Comprising a batching unit, a mixing unit and a grading storage unit, the batching unit consists of a plurality of sintering batching bins and is used for preparing various sintering raw materials with different carbon contents in different time periods according to process requirements; the mixing unit at least comprises a primary mixing chamber and a secondary mixing chamber, raw materials are preliminarily mixed in the primary mixing chamber, so that various raw material components are preliminarily and uniformly distributed, and then the raw materials enter the secondary mixing chamber to be deeply mixed, so that the mixing uniformity of the raw materials is ensured; the graded storage unit comprises an unloader and a plurality of blending bins, the mixed materials are conveyed to the graded storage unit through a sealing-tape machine, the unloader unloads the materials to the corresponding blending bins, and graded storage of the materials with different carbon contents is achieved; wherein each blending bin is used for storing a material with one carbon content. According to the method, accurate carbon supply can be achieved in a graded carbon distribution mode, waste of carbon resources is reduced, sintering energy consumption is remarkably reduced, and the economical efficiency of sintering production is improved.

The invention discloses a method for predicting unit calorific value carbon content based on coal quality industrial analysis data. The method comprises the following steps: 1, acquiring multi-database coal type industrial analysis data, element analysis data and calorific value; 2, calculating dry ash-free basis volatile components, hydrogen elements, carbon elements, sulfur elements and lower calorific values of the database coal types; step 3, calculating a carbon hydrogen ratio and a unit calorific value carbon content of a dry ash-free base of the coal type in the database; step 4, through linear fitting, respectively obtaining a function relationship between a volatile component, a sulfur content, a calorific value and a carbon content per unit calorific value of the coal type drying ash-free basis in the database; 5, a new parameter A0 is obtained, and the new parameter and the unit calorific value carbon content are subjected to linear fitting; 6, sampling the target coal for industrial analysis, and detecting the calorific value and the sulfur content of the target coal at the same time; step 7, calculating dry ash-free basis volatile sulfur content, lower calorific value and parameter A0 of the target coal type; 8, predicting the dry ash-free basis unit calorific value carbon content of the target coal type; step 9, calculating the unit calorific value carbon content of the target coal type; the method can accurately predict the unit calorific value carbon content of the bituminous coal, and guides the coal purchase.

The application provides a building construction unit-based building materialization stage carbon emission calculation method, according to building design and building construction atlas, the building is divided into several building construction units, and the carbon emission of the building construction unit in the building materialization stage is calculated, and the calculation result is taken as the carbon emission factor of the building construction unit; the building construction unit family coding information is given in the Revit model, and the number of various building construction units is obtained by using the detail table. Then the carbon emission of the building materialization stage is calculated by using the Excel VBA program. The application provides the building construction unit carbon emission factor, by means of the building construction unit carbon emission factor, the carbon emission calculation process of the building in the materialization stage is simplified; the building construction unit carbon emission factor database is formed, which can be used for multiple times of the same type of project, so that the carbon emission calculation work of the building materialization stage of the subsequent project is simplified.

A construction system utilizes a post-and-beam structure that supports major gravity loads of a building in combination with prefabricated exterior and / or interior wall panels that are not required to support gravity loads beyond self-weight. Studs within the prefabricated wall panels are oriented such that a widest face thereof is other than normal to the wall surfaces attached thereto. Such an orientation of the wall studs reduces or eliminates thermal bridging in the structure without adding materials, thereby reducing embodied carbon and embodied energy content. The orientation of the wall studs also maximizes the available space within the wall panels to accommodate electrical and plumbing utilities and insulation material and utilizes the studs along their strong axis to resist lateral loads.

The utility model discloses a flexible and adjustable ammonia-doped pulverized coal boiler combustion system, which comprises a pulverizing device, a combustor and a horizontal boiler which are connected in sequence, a plurality of ammonia injection devices are arranged below the horizontal boiler, each ammonia injection device comprises a nozzle with adjustable angle, flow and / or flow velocity, and the nozzle is connected with the combustor. The input end of the ammonia injection device is connected with the ammonia storage device through an ammonia conveying pipeline; and the tail part of the horizontal boiler is connected with the SNCR denitration device. According to the utility model, the combustion efficiency of pulverized coal is improved by doping ammonia, and particularly, stable combustion is ensured by adjusting the proportion of ammonia under the condition that the coal quality changes greatly; ammonia and nitrogen oxide can react to generate nitrogen and water, so that the emission of NOx is reduced; ammonia is injected from the lower portion of the boiler, the mixing uniformity of pulverized coal particles and air is improved, an outlet of the combustor is in a local air-rich area, combustion and burnout of pulverized coal are facilitated, the carbon content of fly ash is reduced, and the higher the ammonia doping proportion is, the higher the burnout rate of the pulverized coal is.

The application relates to the field of carbon emission operation and maintenance analysis, and specifically discloses a carbon emission operation and maintenance data calling and analysis method, which comprises the following steps: obtaining carbon emission intensity of a power plant in an accounting period and comparing the carbon emission intensity with historical same period and industry average level to identify abnormal power plants; determining an abnormal reason based on fuel carbon content deviation as fuel quality fluctuation or unit operation abnormality; if the reason is fuel problem, correcting an emission factor through a machine learning model and recalculating the carbon emission intensity; if the reason is unit fault, drawing a load-emission intensity curve to identify an inefficient unit with emission sudden increase and obtaining an abnormal period and abnormal degree of the unit; determining whether the inefficient unit is single to determine whether a source point is a unit equipment or a shared auxiliary equipment, and then formulating a reasonable troubleshooting order in combination with historical fault records; the method solves the problems of difficult carbon emission abnormality attribution of the power plant, slow operation and maintenance response, realizes dynamic correction of the emission factor, accurate positioning of a fault source point and optimization of a troubleshooting path, and improves carbon management efficiency.

The application relates to the technical field of energy control, in particular to a boiler combustion carbon reduction and pollution reduction control method, device, equipment, medium and program, wherein the method comprises the following steps: acquiring coal quality data, fly ash images and boiler operation parameters of a boiler; inputting the fly ash images into a carbon content prediction model, and outputting corresponding fly ash carbon contents by the carbon content prediction model; determining boiler efficiency and carbon emission intensity according to the coal quality data, the fly ash carbon contents and the boiler operation parameters; taking maximization of the boiler efficiency, minimization of the carbon emission intensity, minimization of operation coal consumption and minimization of nitrogen oxide emission concentration as targets, and calculating corresponding target control parameters under different working conditions; and controlling the boiler to perform corresponding carbon reduction and pollution reduction control operations according to the target control parameters. Therefore, the problems, such as low combustion efficiency, increased pollutants and carbon emissions, caused by the fact that the artificial experience and PID control strategy in the related art lead to combustion regulation lag and insufficient precision and are difficult to adapt to coal quality fluctuation and load change, are solved.

Various embodiments include cementitious compositions with low levels of embodied greenhouse gas emissions, in particular carbon dioxide, as a result of its production and / or use compared to conventional cementitious materials, such as portland cement. Various embodiments include any cementitious material or materials with low embodied carbon, as well as any material produced using this cement.

The invention provides a coal dust ammonia-doped combustion carbon emission reduction calculation method based on LIBS detection. The coal dust ammonia-doped combustion carbon emission reduction calculation method comprises the following steps that (1) the fly ash carbon content generated in the coal dust ammonia-doped combustion process is obtained through an LIBS fly ash detection device; (2) collecting ammonia escape data, coal basic fuel attribute data and combustion operation data; and (3) calculating the actual fuel demand quantity in the actual combustion process under the condition of the fixed calorific value, and further calculating the carbon emission reduction proportion. According to the coal powder ammonia-doped combustion carbon emission reduction calculation method, the influence of ammonia escape on the coal powder ammonia-doped combustion process is considered, the dynamic correlation model of the combustion process and the carbon emission reduction effect is constructed, real-time and dynamic calculation of the CO2 emission reduction effect under different ammonia doping proportions is achieved, and the method has important significance on accurate accounting of carbon emission in the thermal power industry.

The application discloses a coal underground gasification resource gasification rate measuring method, and relates to the technical field of coal mining. First, the total volume of coal resources in a gasification region and the carbon content in the gasification region are obtained, then equipment is arranged in an air inlet well and a production well, the gas density, gas flow and gas carbon content of a gasification agent in the air inlet well are obtained, the carbon content of the production well in a gasification period of the gasification region is obtained, the gas density, gas flow and gas carbon content of a gasification product in the production well are obtained, the carbon output of the production well is obtained according to the obtained parameters, and the gasification rate of the coal resources in the gasification period of the gasification region is calculated according to the obtained parameters. According to the principle of carbon content conservation, the coal gasification rate in the gasification period of the gasification region can be effectively obtained, and technical support is provided for the improvement of the gasification industry.

This invention discloses a method and system for verifying the quality of coal-fired carbon emission data in thermal power plants. The method includes: S1) collecting key indicator data of thermal power units; S2) constructing quality verification indicators based on the key indicator data; S3) comprehensively analyzing and evaluating various quality verification indicators, and issuing early warnings based on the comprehensive analysis and evaluation; S4) formulating a verification plan based on the comprehensive analysis and evaluation results of various quality verification indicators in S3) and the early warning output results, and verifying the coal-fired carbon emission data of thermal power plants according to the verification plan. This invention provides a method for analyzing and evaluating the reliability of monitoring data such as key indicators of coal-fired carbon emissions, carbon content per unit calorific value of coal, and comprehensive sample representativeness, thereby improving the internal data quality monitoring capabilities of enterprises. Through the implementation of the early warning plan, it is possible to effectively trace and verify problematic links in data anomalies and correct and improve them in a timely manner, reducing the adverse risks caused by data quality and non-compliance in data verification by relevant departments.

This invention discloses a method for assessing building-embedded carbon emissions based on multimodal remote sensing and graph neural networks. The method includes: constructing a building structure type classification system for building-wide lifecycle carbon emissions; identifying building structure types and calculating lifecycle carbon emissions based on a building project inventory to generate a sample dataset; extracting and fusing building features based on multimodal remote sensing data to generate a unified building feature vector; jointly training a multi-task graph neural network using the sample dataset and the building feature vector to obtain a model capable of simultaneously predicting building structure type and lifecycle carbon emissions; and mapping and spatial analysis of building-wide lifecycle carbon emissions based on the model's prediction results. This invention achieves high-precision joint prediction of building structure identification and lifecycle carbon emissions, overcoming the limitations of traditional methods in data completeness and spatial accuracy, and enabling intelligent monitoring of urban carbon emissions.

The invention relates to the technical field of carbon emission statistics of thermal power enterprises, and discloses a carbon emission data abnormity identification and early warning method and device. According to the method, a multi-dimensional anomaly identification and early warning mechanism is constructed by fusing multi-source data such as carbon emission online monitoring data, daily coal quality test data, coal quality parameter reference values and the like; comprising abnormity identification and early warning based on comparison of a monitoring method and an accounting method, abnormity identification and early warning based on element carbon content fitting and abnormity identification and early warning based on a unit heat value carbon content recommendation value, and accurate identification and timely early warning of carbon emission data abnormity of thermal power enterprises are realized. By establishing an elemental carbon content fitting formula and calculating a fitting value by using daily coal quality data, daily monitoring of the elemental carbon content is realized, the problem of elemental carbon content detection lag is solved, and carbon emission data abnormity can be identified in time.

The invention discloses a combustion carbon loss and thermal efficiency optimization method based on carbon content inversion of CO concentration. According to the method, the carbon content of fly ash and the carbon content of slag are inversed through CO concentration data in a DSC database, a KAN-FM neural network model capable of obtaining a better result in a small sample is adopted, after a thermal efficiency value is calculated based on an inversion result, the relation between the CO concentration and the thermal efficiency is further obtained, and combustion carbon loss and the thermal efficiency are optimized. The method has the advantages that the relation between the CO concentration and the fly ash and slag carbon content is considered and established, the boiler thermal efficiency is calculated through the counter balance method, the relation between the CO concentration and the combustion carbon loss and the boiler thermal efficiency is established, and the problem that the thermal power plant efficiency is difficult to optimize is effectively solved.

This invention discloses a systematic method for reducing carbon dioxide emissions throughout the entire steelmaking and casting process, the method comprising a hydrogen injection step into a blast furnace, the hydrogen gas being supplied from a nuclear hydrogen production system, a water electrolysis hydrogen production system, and a coke oven gas-steam reforming hydrogen production system, the electricity consumed in water electrolysis hydrogen production being supplied from natural gas thermal power generation, steam residual pressure power generation, solar power generation, wind power generation, and nuclear power generation, and the combustible gas used in natural gas thermal power generation being coke oven gas, blast furnace The gas and converter gas are used. The steam used for residual steam power generation is supplied from a sintering waste heat boiler. The steam used for coke oven gas-steam reforming hydrogen production is low-pressure steam after residual steam power generation. The end products are cast steel profiles, casting materials for high-carbon spheroidal graphite cast iron profiles with a carbon content of 2-4% and a silicon content of 2-4%, and casting materials for high-carbon spheroidal graphite cast steel profiles with a carbon content of 1-2% and a silicon content of 1-1.9%. The waste from the end products is recycled and smelted in a converter or electric furnace.

The invention relates to the technical field of coal-fired boilers, in particular to an on-line monitoring system and electronic equipment for blending combustion of organic fuel in a coal-fired boiler, and the system comprises a collection assembly which is used for collecting component data of various fuels before and after blending combustion of the boiler, and the various fuels comprise fuel, organic fuel and mixed fuel, the component data comprises a lower calorific value, moisture and ash content; the detection assembly is used for monitoring operation state change data after boiler combustion, and the operation state change data comprise the fly ash carbon content and the exhaust gas temperature; and the processing assembly is in communication connection with the acquisition assembly and the detection assembly and is used for calculating the carbon emission of the organic fuel according to the component data of the various fuels before and after the blending combustion of the boiler and the operation state change data after the combustion of the boiler. Therefore, the problems that in the prior art, in the organic fuel blending combustion process of a coal-fired boiler, due to the fact that fuel components are changeable, carbon emission metering is inaccurate and economical efficiency evaluation is difficult, the blending combustion process cannot be monitored in real time, and efficient and economical operation cannot be achieved are solved.

The invention discloses a multi-parameter adjustment boiler combustion efficiency dynamic optimization method. The method comprises the following specific operation steps: acquiring combustion parameters from a power plant system in real time, preprocessing the acquired original data, and performing feature selection after data preprocessing; taking the feature data after feature selection and preprocessing as input according to a time sequence, and constructing an IGWO-transform prediction model; taking coal consumption per kilowatt hour, nitrogen oxide emission concentration and fly ash carbon content as optimization objectives, and adopting an NSGA-III algorithm to carry out multi-objective optimization; and aiming at the control requirement of the characteristic data, an independent PID controller is configured for each control object, an acquired actual value is compared with a target set value, a control deviation is calculated to serve as an input signal of the PID controller, and the controller is driven to carry out dynamic adjustment. The method has the beneficial effects that the data processing and generalization capability is enhanced, accurate prediction and regulation are realized, and the combustion efficiency is improved; the economical efficiency and the environmental protection property are balanced, and dynamic optimization is realized.

The invention relates to a coal gas data management and dynamic distribution method and system for process-level carbon emission accounting in the iron and steel industry. The method comprises the following steps: collecting flow and component parameters of coal gas in coal gas channels corresponding to a blast furnace, a coke oven and a converter; performing real-time data quality control processing and statistical calculation processing on the acquired data, and screening to obtain effective data; calculating the low calorific value and the carbon content per unit calorific value of the coal gas based on the effective data, and carrying out uncertainty analysis; and constructing a mixed gas carbon emission distribution model based on a mass energy conservation equation, solving the proportion of each source gas in the mixed gas based on the low calorific value and the unit calorific value carbon content, and verifying and correcting a distribution result in combination with an uncertainty analysis result to complete splitting and distribution of carbon emission. Compared with the prior art, the method has the advantages that the carbon data quality reliability is improved, the labor cost and the efficiency loss are reduced, and the data are traceable.