4315 results about "Coal fired" patented technology

The invention relates to the technical field of computer programming languages, and particularly discloses a coal-fired power plant safety monitoring system and method. The system comprises a multi-modal data fusion platform, a federal learning agent network and a digital twinborn simulation engine. The edge computing node carries out unified acquisition and feature extraction on multi-source heterogeneous data through multi-protocol conversion, quantum noise suppression and a preprocessing chipset; the multi-modal data fusion platform realizes semantic mapping based on a knowledge graph, and fuses time-space correlation characteristics of data such as an infrared image and gas concentration by adopting a time-space encoder and a cross-modal attention mechanism. According to the method, the problems of early warning delay and high false alarm rate caused by low multi-source data decentralized processing efficiency and insufficient nonlinear correlation analysis in a traditional scheme are solved, efficient data fusion, complex risk accurate prediction and automatic safety response are realized, and the real-time performance and reliability of a coal-fired power plant monitoring system are remarkably improved.

The invention relates to the technical field of boiler engineering and artificial intelligence modeling, in particular to a coal-fired boiler biomass blending combustion working condition intelligent optimization method, which comprises the following steps: constructing a three-dimensional mathematical model of coal-fired boiler biomass blending combustion based on experimental test data; performing multi-working-condition numerical simulation according to boiler combustion working condition fluctuation in the three-dimensional mathematical model; according to the numerical simulation data, constructing a time-space coupling model for co-combustion of biomass in the coal-fired boiler; the modeling accuracy is improved through a numerical simulation technology, the boiler operation condition is dynamically optimized in combination with space-time modeling, and theoretical support is provided for energy conservation and emission reduction and blending combustion proportion optimization; the method is suitable for environment-friendly transformation and operation optimization of the coal-fired boiler, and carbon emission and pollutant emission can be effectively reduced.

The invention provides an intelligent optimization control method and platform under variable load operation of a coal-fired power plant, and relates to the technical field of intelligent optimization control, and the method comprises the steps: calling historical operation data, carrying out the load trend change analysis, and completing the construction of a control analysis module; analyzing and outputting instantaneous PID control parameters according to the real-time load data; after the instantaneous PID control parameters are switched to, a flue gas emission acquisition module is activated; real-time flue gas emission parameters are obtained; performing denitration control optimization to obtain a real-time PID control parameter, and switching to the real-time PID control parameter; presetting a flue gas emission window, dynamically updating real-time flue gas emission parameters, dynamically updating real-time PID (Proportion Integration Differentiation) control parameters and performing seamless switching control on an SCR (Selective Catalytic Reduction) system. The control method solves the technical problem that when a control method in the prior art is used for dealing with an SCR system, efficient control is difficult to achieve under the dynamically-changing load condition, and then the denitration effect and the system stability are affected.

The invention discloses an induced draft fan parameter dynamic early warning method, system and device based on historical data mining and a medium, and relates to the technical field of coal-fired unit intelligent monitoring. The method comprises the steps that characteristic parameters of an induced draft fan are collected, and the characteristic parameters of the induced draft fan are preprocessed; according to the preprocessed data, an induced draft fan characteristic parameter prediction model is established, and an induced draft fan characteristic parameter prediction value is obtained; establishing an early warning threshold value according to the characteristic parameter predicted value of the induced draft fan, and dynamically adjusting the early warning threshold value; establishing an early warning model, and performing early warning on the abnormal characteristic parameters of the induced draft fan according to an early warning threshold value; according to the method, the characteristic parameters of the induced draft fan are collected, data preprocessing is carried out, the early warning threshold value is dynamically adjusted in combination with the predicted value and the environmental factors, the adaptability and accuracy of early warning are improved, the intelligent early warning model is constructed, and targeted fault diagnosis suggestions are provided; the monitoring precision, the early warning accuracy and the fault response efficiency of the operation state of the induced draft fan are effectively improved, and the operation safety and stability of a coal-fired unit are improved.

The invention relates to the technical field of hydrogen energy, and discloses an auxiliary-machine-free solid oxide electrolytic hydrogen production system and an auxiliary coal electricity deep adjustment method, the hydrogen production system comprises an SOE heat box system for electrolytic hydrogen production, a hydrogen circulation subsystem and a hydrogen storage subsystem; the ejector is driven by external heat source steam, part of hydrogen at an outlet of the SOE heat box system is ejected to a low-pressure suction inlet of the ejector through the hydrogen circulation subsystem, and formed reducing mixed gas of steam and hydrogen enters a cathode inlet of the SOE heat box system. The system is driven by an external heat source and operates in an internal stack heating mode, so that the power consumption of the electrolytic hydrogen production system is reduced; by adopting the modes of external material supply, cathode ejector material self-circulation and multi-stream heat exchange, a complex cold and hot auxiliary machine of a traditional solid oxide electrolytic hydrogen production system is omitted, the structure is simple, and the system compactness is greatly improved; electric power-steam-air-condensed water flow coupling is established with a coal-fired power plant, and efficient, flexible and deep peak shaving is adjusted in combination with steam extraction multi-stage adjustment.

The invention relates to a boiler combustion optimization control system of a thermal power plant, relates to the technical field of thermal power generation control, and aims to solve the problems of inaccurate multi-source data perception, slow control response and insufficient multi-target collaborative optimization capability under fire coal quality fluctuation and load change. The system comprises a data perception and fusion module, a working condition self-adaptive identification module, a multi-target dynamic optimization decision module and a distributed execution control module, and through multi-source data acquisition and feature extraction, depth time sequence mode identification, multi-target optimization model solving and distributed coordination control, the multi-target dynamic optimization decision module and the distributed execution control module are subjected to multi-source data fusion. Dynamic balance of boiler heat efficiency improvement and nitrogen oxide emission reduction is achieved, and adaptability and control precision of the system under complex working conditions are enhanced.

The invention relates to a coal-fired unit electrostatic dust collection energy-saving optimization method, system and equipment and a storage medium, and the method comprises the steps: obtaining historically collected system operation data of a coal-fired unit electrostatic dust collection system, and constructing an outlet NOx concentration prediction model and an outlet dust concentration dynamic model according to the system operation data; power optimization control strategies of high-voltage power supplies of all levels of electric fields in the dust removal system are obtained, a model is built based on the outlet NOx concentration prediction model, the outlet dust concentration dynamic model and the optimization control strategies, and an electrostatic dust removal energy-saving optimization model is obtained; acquiring a preset environment-friendly standard concentration, and analyzing the environment-friendly standard concentration through the electrostatic dust collection energy-saving optimization model to obtain an optimal dust collection parameter; and adjusting the current or voltage of each level of electric field in the dust removal system according to the optimal dust removal parameters. Through the constructed energy-saving optimization model, the electrostatic dust collection control system can reduce the dust emission concentration and meet the pollutant emission standard, and meanwhile, the energy consumption of the electric dust collector can be greatly reduced.

The invention discloses a coal-fired power generation steam and heat pump integrated energy storage system and an operation method thereof. The system comprises a coal-fired unit coupling fused salt energy release system and a reheat steam coupling heat pump energy storage system. In the low ebb of electricity utilization, the coal-fired unit outputs electric energy to drive the heat pump charging compressor to compress a heat pump working medium, then the heat pump working medium heats the fused salt, meanwhile, part of reheat steam of the coal-fired unit sequentially heats the fused salt and a working medium at an outlet of the heat pump charging expansion machine, and the load is further reduced; and finally, redundant electric energy and part of heat energy of the reheated steam are converted into fused salt heat energy to be stored. In the peak period of electricity utilization, a part of exhaust steam of the high-pressure cylinder is heated through heat stored in the fused salt storage tank to generate reheated steam, the heat absorption capacity of main steam entering the boiler is increased under the condition that the coal consumption of the boiler is not changed, the flow of the main steam is also increased, and then the output load of the coal-fired unit is increased. According to the method, the peak regulation potential of the coal-fired unit can be exerted, the output load interval of the unit is expanded, and the method is effective for improving the peak regulation capacity of the coal-fired unit and stabilizing power grid fluctuation.

The invention discloses a low-carbon flexible coal-fired unit power control system and method, and relates to the technical field of power systems, and the system comprises a cascade waste heat recovery module, a boiler deep regulation and control module, a thermal coordination module, an environmental protection and emission reduction module, an intelligent operation scheduling module and an energy efficiency monitoring module. The gradient waste heat recovery module carries out gradient recovery on flue gas heat energy according to temperature zone grades; the boiler depth regulation and control module is used for regulating combustion air supply and heat absorption paths to realize low-load stable combustion; the thermal coordination module dynamically distributes thermal loads between the multiple heat sources and the thermal units; the environmental protection and emission reduction module jointly controls desulfurization, denitration and wastewater resourceful treatment; the intelligent operation scheduling module generates a load regulation and control instruction and coordinates multi-module response; the energy efficiency monitoring module collects and analyzes energy consumption and emission indexes and assists strategy optimization. The energy efficiency utilization and emission control capability of the unit under the deep peak regulation condition is improved, and flexible, efficient and low-carbon operation is achieved.

The invention discloses a coal-fired unit SCR denitration system ammonia injection prediction control method based on data driving, which is used for realizing better SCR denitration system ammonia injection control based on a data driving model in combination with an implicit generalized prediction control algorithm. The SCR inlet NOx concentration and the flue gas temperature serve as feedforward of an ammonia spraying amount instruction, the initial control instruction increment of the ammonia spraying amount is calculated through the SCR outlet NOx concentration, the SCR outlet NOx concentration set value and the ammonia spraying amount instruction at the previous moment through an implicit generalized predictive control algorithm, and the final ammonia spraying amount instruction is obtained through summation and amplitude limiting of the last three instructions. Wherein the feedforward instruction of the NOx concentration of the SCR inlet is obtained by a BP neural network prediction model, and the feedforward instruction of the SCR inlet is obtained by a long-short term memory network prediction model fused with an attention mechanism. According to the method, the problem that the concentration of NOx at an SCR outlet fluctuates severely in the frequent load changing process can be effectively solved, meanwhile, transient overshoot of NOx in tail flue gas of a coal-fired unit is restrained, and the SCR denitration control effect is improved.

The invention relates to the technical field of boiler equipment fault prediction, in particular to a boiler four-tube wall tube wear prediction method based on a big data algorithm, comprising the following steps: constructing a three-dimensional digital model of boiler four tubes, and spatially binding design parameters, historical operation and maintenance records and real-time monitoring data to form a multi-source associated database; constructing a pipe wall temperature prediction model by using a heat conduction mechanism model and a neural network algorithm, and outputting wall temperature distribution data of a full heating surface; inputting the data into a wear, creep and corrosion model, and calculating the residual life and generating a life map in combination with a historical pipe explosion case; generating a three-dimensional risk thermodynamic distribution diagram by adopting a leakage risk probability algorithm and a coupling risk coefficient model; and superposing the thermodynamic diagram into the three-dimensional digital model, and displaying the risk level based on color gradient mapping, so that the method can be widely applied to online state monitoring and intelligent early warning of the four tubes of the coal-fired power plant boiler.

The present disclosure provides an energy storage energy system, which converts energy into cold power and / or heat power by utilizing an energy storage mode and stores the cold power and / or heat quantity. The stored cold power is used for a technology and a cold source of an existing freezing or air conditioner refrigeration industry; the stored heat power is used for a technology and heat source of an existing heating or heat supply industry. The energy storage energy system of the present disclosure adopts a large amount of wind power and photovoltaic power generation electric energy. The heat storage is applied to a current heating or heat supply market for sales which is mainly coal-fired. Cold storage subverts the existing refrigerant compression cycle technology, replaces refrigeration compressor freezing and air conditioning refrigeration systems; heat storage subverts boiler heat supply technology, replaces fossil fuel boiler heating and heat supply systems.

The invention discloses a coal-fired power plant operation parameter adaptive optimization method and system. The method comprises the steps of operation data fusion acquisition, dynamic load response modeling, fire coal load coordination optimization, emission efficiency adaptive balance and operation parameter adaptive optimization. The invention relates to the technical field of intelligent adjustment of parameters of a coal-fired power plant, and aims at realizing future load minute-level rolling prediction by constructing a standardized multi-source data structure and adopting a long-short-term memory network, and realizing dynamic generation of combustion parameters by introducing adaptive dual-stage collaborative scheduling and an improved multi-objective optimization algorithm. On the basis, the dynamic causal regulation and control diagram is used for carrying out rolling weighted balance on the emission efficiency, the energy efficiency, the responsiveness and the emission compliance are comprehensively considered, the power generation efficiency is improved, the pollutant emission is reduced, and the adaptability and the stability of the system are enhanced.

The invention discloses a method for preventing main steam pressure fluctuation on the basis of controlling the coal combustion amount. The method comprises the following steps: acquiring running state data of the coal-fired boiler in real time; based on the operation state data and a preset boiler dynamic prediction model, predicting a steam pressure sequence of the boiler in a future preset time range, and judging whether to trigger a control action or not in combination with an event triggering strategy obtained by learning of a reinforcement learning agent; if it is judged that the control action is triggered, the reinforcement learning agent outputs an adjustment instruction of the total coal feeding amount according to the current operation state data; and controlling the total coal feeding amount of the boiler according to the adjusting instruction. According to the method, the timing and the force of control intervention can be intelligently determined according to the real-time state and future trend prediction of the boiler, and the accuracy and the foresight of main steam pressure control are improved.

A thermal battery energy storage system coupled with a coal-fired generator set and its operation method, including a coal-fired generator set system and a heat pump energy storage system coupled with molten salt heat storage; the coal-fired generator set system includes a high-pressure cylinder, a medium-pressure cylinder, a low-pressure cylinder, a generator, a condenser, a condensate pump, a low-pressure heater, a deaerator, a feedwater pump, a high-pressure heater, and a boiler; the invention uses the exhaust steam of the low-pressure cylinder as a heat source to preheat the circulating working fluid in the thermal battery heat pump system, so that the total efficiency and COP of the system are increased, and the exhaust steam recovery and utilization capacity is enhanced. At the same time, the output load of the coal-fired unit is reduced, the peak-shaving range of the unit is expanded, and the peak-shaving depth is increased.

The invention discloses a coal-fired power generation unit operation optimization method and system based on industrial big data, and relates to the technical field of industries. A starting priority analysis module dynamically adjusts a unit starting sequence and obtains unit starting priorities by analyzing real-time data sets and power grid load requirements; the system can quickly judge the starting sequence of the units according to the numerical values and effectively recognize the units with possible fault risks, and the fault recognition module performs fault assessment on the unit operation state and equipment state data in combination with the real-time data set and the historical data set and calculates the current fault assessment index. Through comprehensive analysis of a historical trend and a real-time state, the system can accurately judge whether maintenance operation needs to be carried out on a unit or not, so that early prediction and timely intervention of potential faults are realized, an effect feedback and optimization module evaluates feedback data of an actual operation effect, constructs a performance feedback index, and improves the maintenance efficiency of the unit. And dynamic adjustment and optimization of unit load distribution are realized.

The invention relates to a power plant temperature control system safety protection device and system. The power plant temperature control system safety protection device comprises a redundant temperature acquisition module, a temperature control safety processing module, an actuator control protection module, an intelligent strategy recovery module and a communication and alarm module. Through multi-point temperature data acquisition, abnormal trend intelligent identification and local linkage control, the device realizes quick response and protection control of temperature control abnormity of a key area of a boiler thermodynamic system. The system supports data interconnection with a DCS platform and an alarm analysis platform, has local independent operation and remote centralized management capabilities, and is suitable for temperature control safety protection of high heat load areas such as boilers of coal-fired power plants.

The invention relates to the technical field of multi-energy complementary power generation, and discloses an industrial steam supply peak shaving system and method coupling fused salt heat storage and solar energy, and the industrial steam supply peak shaving system comprises a coal-fired power generation system and an industrial steam supply system; in the heat storage mode, the boiler, the steam cooler and the condenser are sequentially connected; in the heat release mode, the high-pressure heater, the primary feed water heater and the low-pressure cylinder are sequentially connected through pipelines; and the feed pump, the secondary feed water heater and the boiler are connected in sequence. In the low ebb of the electrical load, solar energy is used for heating fused salt to store heat, and part of high-temperature steam is extracted from steam-water circulation of the improved coal-fired power generation system to store the heat in a heat storage device and does not enter a steam turbine for power generation; the power load output is adjusted by adjusting the thermal load output of the thermodynamic system in the power generation process, and load decoupling of the boiler and the steam turbine is achieved. And in the electrical load peak, the stored heat energy is released back to steam-water circulation, and the electrical load of the coal-fired power generation system is increased.

The invention discloses a desert sand-based artificial earthwork lattice sand barrier and a preparation and use method thereof, the artificial earthwork lattice sand barrier comprises the following components in percentage by mass: 93-97% of a coal-sand-ash mixture, 1-10% of an activating agent and 5-15% of externally doped water, and the artificial earthwork lattice sand barrier is prepared by compacting and molding, and the coal-sand-ash mixture accounts for 93-97%, the activating agent accounts for 1-10% and the externally doped water accounts for 5-15%. The desert sand base artificial earthwork grid is horizontally laid in the desert and a water and soil loss area, desert sand stabilization can be achieved, and surface layer floating sand and surface layer sandy soil loss in the water and soil loss area are prevented. Typical coal-fired solid wastes such as the coal ash and the coal slag are used as raw materials for preparing the desert sand-based artificial earthwork grid, collaborative resource utilization of the desert sand, the coal ash and the coal slag is achieved, resource utilization of a large amount of industrial solid wastes is combined with desertification prevention and control engineering, environmental pollution is reduced, and the desertification control cost is reduced.

The invention discloses a cementing material for a solid waste-based road of a coal-fired power plant and a preparation method of the cementing material. The cementing material mainly comprises a cementing component, an alkali-activated component and a reinforcing component, the gelling component is a mixture of coal-fired power plant fly ash and furnace slag; the alkali-activated component is a mixture of alkali residues, red mud, blast furnace slag and coal-fired power plant desulfurized gypsum; the reinforcing component is rice hull ash or peanut hull ash. The mass ratio of the gelling component to the alkali-activated component is (4 / 1)-(10 / 1); and the addition amount of the reinforcing component is 1-3% of that of the main body material. The coal-fired power plant solid waste fly ash, the furnace slag and the desulfurized gypsum are used as main bodies, a small amount of other industrial solid waste is added, and the cementing material belongs to a full-solid-waste low-carbon cementing material and can be applied to a road base, a subbase or a base layer. The invention has the characteristics of low carbon emission, high solid waste consumption, simple production process and strong pavement performance, and in addition, the invention has a good stabilization effect on the problem that part of solid waste heavy metals and sulfate ions in a coal-fired power plant exceed the standard.

The invention discloses a refined ammonia injection control system for a coal-fired power plant, and relates to the technical field of ammonia injection control systems for power plants. The real-time monitoring module is used for monitoring NOx concentration, oxygen content and temperature parameters in flue gas in real time and transmitting data to the central processing unit; and the prediction model construction module is used for constructing an NOx generation prediction model by utilizing a machine learning algorithm according to the historical data and the real-time monitoring data. Through the real-time monitoring module, the system can continuously track key parameters such as NOx concentration, oxygen content and temperature in flue gas; the control decision is ensured to be based on the latest environmental condition, so that the response speed and accuracy of the ammonia spraying system are improved; the NOx generation prediction model constructed by using a machine learning algorithm not only considers historical data, but also integrates real-time monitoring data, so that the model can accurately predict the NOx concentration change trend in a period of time in the future; and the system can predict and adapt to the future emission condition.

The invention discloses a safety assessment method for a heating surface of a coal-fired unit boiler based on a field control signal. The method comprises the following steps: S1, collecting a monitoring signal through a field control end; s2, modifying the monitoring signal to obtain a fault monitoring signal under a simulation condition; s3, establishing a simulation structure model and a reaction model, and obtaining working condition data under simulation conditions; and S4, calculating the predicted residual life of the heating surface under the simulation condition. According to the method, by monitoring the control signal of the control end and combining simulation means for simulation analysis, the problem that monitoring cannot be carried out without a measuring point position in a conventional method can be avoided, and system danger can be early warned as soon as possible by utilizing signal analysis of the control end; the method is high in repeatability and safer to implement, can qualitatively analyze the working state of the boiler system under the abnormal field control signals, does not need to actually adjust parameter tests in the boiler system or collect signals of fixed measuring points at the rear end for safety evaluation, and is relatively low in cost.

The invention discloses a method and a system for evaluating the pollution reduction and carbon reduction collaboration degree in the coal-fired power generation industry based on online monitoring data, related pollutants are typical atmospheric pollutants, and carbon emission particularly refers to carbon dioxide emission. The method comprises three parts: a subsystem for acquiring and preprocessing data of single atmospheric pollutants such as SO2, particulate matters and NOx, a subsystem for accounting the cooperation degree of single atmospheric pollutants and carbon emission reduction in the coal-fired power generation industry, and a subsystem for comprehensively accounting pollution and carbon reduction indexes in the coal-fired power generation industry. According to the method, the typical representative coal-fired power generation enterprise level data in the region is processed and integrated to evaluate the pollution reduction and carbon reduction level of the coal-fired power generation industry in the region range.

The invention relates to the technical field of fire coal control, and discloses a thermal power plant fly ash floating black online detection control method and system, and the method comprises the steps: 1, employing microwave, infrared and laser sensors for cooperative work, detecting carbon dielectric characteristics through microwave dust interference resistance, identifying thermal radiation difference through infrared, and analyzing particle distribution through laser; 2, on the basis of the detection requirements in the step 1, triple protection of air curtain barrier, ultrasonic cleaning and hydrophobic coating is designed, dust condensation is blocked, and it is ensured that the light transmittance of the sensor is larger than 90%; the invention provides a multi-mode sensing fusion-anti-interference current stabilization-closed loop optimization full-link solution for the industrial problem of signal distortion caused by optical window dew formation and dust deposition, airflow disturbance and environmental interference in fly ash floating black online detection. The light transmittance of the optical window is greater than 93% by combining triple protection of air curtain barrier, ultrasonic cavitation stripping and nano hydrophobic coating.

The present invention provides a method and system for calculating the minimum coal consumption amount of a high-backpressure heating unit. The method comprises: selecting unit backpressure; on the basis of the unit backpressure and an actual working condition and a theoretical working condition of a heating unit, respectively calculating a corresponding unit-side steam exhaust heating amount and a corresponding heating-network-side steam exhaust heat load, and on the basis of a first preset rule, the unit-side steam exhaust heating amount, and the heating-network-side steam exhaust heat load, calculating a corresponding steam exhaust heating parameter so as to calculate the optimal steam exhaust amount by means of the steam exhaust heating parameter; on the basis of a second preset rule, calculating steam extraction amounts required by different steam extraction ports corresponding to the heating unit, and comparing unit coal consumption rates of different steam extraction ports under different steam extraction heating parameters to determine the corresponding optimal steam extraction amount; on the basis of the optimal steam exhaust amount and the optimal steam extraction amount, generating a corresponding boundary condition, and on the basis of the boundary condition and an actual electrical load demand, calculating the corresponding minimum coal consumption amount. The present application can accurately calculate the minimum coal consumption amount, thereby improving the use experience of users.

The invention provides a combustion optimization method and system for a coal-fired boiler, electronic equipment and a storage medium. The combustion optimization method for the coal-fired boiler comprises the steps that historical operation data and operation condition data of the boiler are obtained; determining the combustion efficiency of the boiler according to the historical operation data of the boiler; working condition division is carried out according to the boiler combustion efficiency and the operation working condition data, and information of all working condition intervals is obtained; constructing a combustion efficiency prediction model driven by time series data according to the information of each working condition interval; the combustion efficiency prediction model is embedded into a deep reinforcement learning method framework for training, and an optimization model is generated; and inputting real-time operation data of the boiler into the optimization model to generate optimization decision data.

The invention relates to the technical field of denitration and ammonia spraying, in particular to an intelligent denitration and ammonia spraying automatic control system and method for a thermal power coal-fired unit, and the system comprises a control module which is used for controlling and monitoring the whole denitration process; the data analysis and prediction module is used for analyzing by utilizing historical data and real-time data, predicting NOx concentration change and providing decision support for ammonia injection control; the balancing module is responsible for accurately controlling and optimizing the ammonia spraying amount; the monitoring and feedback module is used for monitoring the concentration of NOx and ammonia escape in real time and providing a feedback signal for the control system; and the communication module is responsible for data transmission between the denitration control system module and the DCS program. The method has the beneficial effects that the time stability and the space uniformity of NOx at an SCR outlet are improved through an intelligent feed-forward algorithm and an override algorithm, excessive ammonia spraying is reduced by utilizing an ammonia escape correction system, the ammonia escape rate is effectively reduced, the operation reliability of a unit is improved, and the resistance increase of a flue gas system caused by blockage of an air pre-heater is reduced.

The invention relates to the technical field of environmental monitoring, and discloses an uncertainty evaluation method based on establishment of a carbon emission monitoring method and an accounting method, and the method comprises the following steps: establishing an uncertainty evaluation model of a coal-fired unit carbon emission monitoring method to quantify the uncertainty of the carbon dioxide emission of the monitoring method; establishing a coal-fired unit carbon emission accounting method uncertainty evaluation model to quantify the uncertainty of the carbon dioxide emission of the accounting method; based on results obtained by the monitoring method uncertainty evaluation model and the accounting method uncertainty evaluation model, carbon emission data quality is analyzed, and improvement measures are put forward. By constructing an uncertainty evaluation model of a monitoring method and an accounting method, various error sources in the whole process of flue gas sampling, analysis, fuel metering, coal quality analysis and the like are comprehensively considered, and a rigorous mathematical method is adopted for synthesis. The quantitative evaluation enables the accuracy of the carbon emission data to have a clear measurement standard.

The invention discloses a T-S fuzzy and TD3-based slow dynamic unknown coal-fired power generation system coordination control method, which comprises the following steps: firstly, decomposing a coal-fired power generation system into a fast subsystem and a slow subsystem by using a singular perturbation theory, and decomposing an original control task into a stabilization task of the fast subsystem and a tracking task of the slow subsystem; for the fast subsystem, a fuzzy set is selected on a definition domain of the fast subsystem by using the slow variation characteristic of steam pressure, and a T-S fuzzy model is constructed; a fast subsystem controller is obtained by solving algebraic Riccati equations corresponding to a plurality of linear systems. For a slow subsystem, a double-Q network is adopted to reduce overestimation of a Q value, a dynamic learning rate and a batch size adjustment mechanism are introduced to accelerate training convergence, and learning is carried out under a TD3 algorithm framework to obtain control input of the slow subsystem. The fast subsystem and the slow subsystem control inputs to be combined and then act on the original system to obtain state information at the next moment, and the intelligent agent interacts with the original system to complete collaborative optimization.

The invention belongs to the technical field of coal-fired power plant combustion control, and discloses a boiler combustion control method based on blending combustion proportion dynamic optimization and a related device. The boiler combustion control method based on blending combustion proportion dynamic optimization comprises the steps that combustion efficiency parameters, safety parameters and flue gas environmental protection parameters of a boiler are monitored and collected in real time, and the combustion efficiency parameters, the safety parameters and the flue gas environmental protection parameters are preprocessed; inputting the pretreated combustion efficiency parameters, safety parameters and flue gas environmental protection parameters into the trained RF-LSTM double-layer model to obtain an optimal blending combustion ratio, setting an optimal blending combustion ratio threshold according to the optimal blending combustion ratio, and dynamically regulating and controlling the blending combustion ratio according to the optimal blending combustion ratio threshold and a preset wall temperature threshold through a double-screw feeder; the sludge blending combustion proportion can be dynamically adjusted, the reliability and flexibility of the system are guaranteed, and proportional blending combustion is more stable.