134 results about "Boiler efficiency" patented technology

The invention provides a multi-target combustion optimization method based on economic predictive control, and aims to solve the problems that the power generation load and the in-furnace coal quality are frequently changed, conventional DCS control has defects in the aspects of air quantity and oxygen quantity optimization, boiler efficiency balancing, NOx emission, steam temperature control and the like, part of boiler parameters are difficult to accurately measure, and the existing combustion optimization technology is limited in applicability. The method comprises the following steps: collecting and preprocessing historical operation data, classifying and screening according to steady-state working conditions, and constructing a correlation model to perform preliminary combustion optimization; a load and coal quality change prediction model and a combustion process dynamic relation model are established according to unit characteristics and historical data; then, in the online secondary optimization stage, an initial parameter combination is selected according to the current state and the prediction state, and the combustion parameter adjustment amount meeting the multiple constraints is calculated through an economic prediction control algorithm and applied and corrected. Experiments show that the method can improve the boiler efficiency, reduce NOx emission, optimize steam temperature control, relieve the labor intensity of personnel and effectively improve the combustion performance.

The invention discloses a machine learning multi-objective optimization control method based on coal quality characteristics and combustion state feedback, and belongs to the technical field of industrial process automatic control. According to the method, collaborative optimization control over the combustion efficiency, NOx emission and combustion stability is achieved under the multi-working-condition operation condition of the combustor. According to the method, coal quality characteristic parameters and combustion state data are collected, working condition clustering is carried out after data fusion, and a historical combustion operation data set coupling coal quality characteristics and combustion states is constructed; a combustion state evaluation model and a combustion control model are established by adopting machine learning, on the basis of identifying working conditions in real time and evaluating combustion performance, a control parameter adjustment amount is generated in combination with trend extrapolation and a multi-objective cost function, and a combustion state feedback rolling correction model and a control strategy are utilized to realize combustion control. The self-adaptive closed-loop collaborative optimization control of the combustion process under multiple coal types and multiple working conditions is realized, the boiler efficiency is improved, the NOx emission is reduced, and the operation robustness is enhanced.

The invention discloses a coal-fired boiler intelligent optimization method, system, equipment and medium based on multi-source perception, and belongs to the technical field of thermal power generation, and the method comprises the steps: carrying out the collection of boiler coal data of a coal-fired boiler, and carrying out the feedback compensation; collecting hearth data to reconstruct a combustion field, formulating an optimization control strategy, and constructing an optimization target to perform tail flue multi-component cooperative control; and carrying out dynamic adjustment based on an implementation result of the control strategy, and carrying out real-time monitoring to carry out coking early warning. According to the method, full-closed-loop intelligent control of coal quality perception, combustion optimization and coking prevention and control is formed, and by means of edge calculation layering processing, the boiler efficiency is improved, the power supply coal consumption is reduced and the cost is saved while it is ensured that emission reaches the standard.

The invention discloses a boiler efficiency optimization method based on big data. The method comprises the following steps: S01, carrying out real-time multi-modal data acquisition and verification fusion; s02, performing adaptive data processing and feature engineering on the high-quality data stream, and dynamically adjusting verification depth and frequency; s03, performing dynamic prediction model management and adaptive re-calibration; s04, executing multi-target robust optimization based on dynamic preference, automatically generating preference setting by using a reinforcement learning agent, searching a Pareto optimal solution by using an evolutionary algorithm, and ensuring the security of reinforcement learning; and S05, executing optimization control and fine regulation and control of a specific subsystem. The invention aims to solve the problems of low data quality, poor model adaptability, single optimization target and the like in the prior art, and comprehensively improves the operation efficiency, economical efficiency and intelligent level of the boiler through systematic data processing, self-adaptive modeling, multi-target intelligent decision and fine control.

The invention provides a deep peak regulation method for a coal-fired unit, relates to the technical field of thermal power generation, and can solve the problem of low-load flame shift, stabilize the combustion core and inhibit the fluctuation of NOx emission concentration by dynamically regulating and controlling a combustion field in a boiler. The energy storage system and the boiler are configured for cooperative operation, the energy storage system is used for rapidly transferring / releasing heat energy, the limitation of the heat storage rate of the boiler is broken through, the two-way peak regulation capacity and the regulation speed of the coal-fired unit in the load reducing stage and the load increasing stage can be remarkably improved, and therefore the boiler efficiency is improved under the low load, and the station service power consumption rate is reduced. By constructing an intelligent control system in communication connection with the DCS, automatic control can be realized.

The invention discloses a boiler direct carbon emission intensity correction method and a related device, and relates to the technical field of boiler carbon emission, and the method comprises the following steps: obtaining boiler efficiency, boiler direct carbon emission and boiler output heat obtained by performing an energy efficiency test and a carbon emission test on a boiler under a test condition; calculating a correction coefficient based on carbon in the fuel and a correction coefficient based on sulfur in the fuel based on the analysis value of the element or the component of the test fuel and the analysis value of the element or the component of the reference fuel; based on the boiler efficiency, the boiler direct carbon emission, the boiler output heat, the correction coefficient based on the carbon in the fuel and the correction coefficient based on the sulfur in the fuel, the corrected boiler direct carbon emission intensity corrected to the reference condition is obtained through calculation, and correction of the boiler direct carbon emission intensity when the test condition is inconsistent with the reference condition can be achieved; therefore, scientific evaluation of the carbon emission level of the boiler is realized.

The invention discloses a CNN-ELM-based boiler efficiency soft measurement method and system, and a medium. The method comprises the following steps: step 1, collecting historical operation data; step 2, preprocessing the data; step 3, a CNN-ELM model is constructed; 4, training the CNN-ELM model by using the training set, and determining an optimal network structure and parameter setting; step 5, inputting test set data into the optimized CNN-ELM model, obtaining a prediction result, performing reverse normalization processing, and then analyzing and evaluating the prediction result by using an evaluation function; and step 6, inputting boiler operation data collected in real time into the trained CNN-ELM model, and outputting a dynamic thermal efficiency prediction value. The method can effectively overcome the defects of a single model, achieves the high-precision dynamic measurement of the thermal efficiency of the boiler, and remarkably improves the precision and real-time performance of the measurement of the efficiency of the boiler.

The invention provides a biomass and coal coupled combustion high-efficiency low-nitrogen optimization method and device.The biomass and coal coupled combustion high-efficiency low-nitrogen optimization method comprises the steps that a first characteristic parameter of a target boiler is obtained, a genetic algorithm and a BP neural network are used for constructing a NOx emission prediction model, and the NOx emission prediction model is used for predicting the first characteristic parameter of the target boiler; the NOx emission concentration is output based on the first characteristic parameter; obtaining a second characteristic parameter of the target boiler, building a boiler efficiency prediction model by using a genetic algorithm and a support vector machine, and outputting boiler efficiency based on the second characteristic parameter; constructing a fuel cost model and a denitration cost model based on mechanism analysis, and determining a comprehensive cost calculation model by combining the fuel cost and the denitration cost; based on the NOx emission concentration and the boiler efficiency, the comprehensive cost of the target boiler is obtained through the comprehensive cost calculation model; with the purpose of minimizing the comprehensive cost of the target boiler, boiler operation parameters of the target boiler are optimized, and a parameter optimal set is obtained; and the boiler operation parameters of the target boiler are updated according to the parameter optimal set. Through the method and the device, the relationship among the parameters of the system can be directly mined from the data, and the problems of single boiler operation parameter optimization object and poor effect in the prior art are solved.

The invention discloses a combustion optimization method and device for an ammonia-coal co-combustion boiler, electronic equipment and a storage medium, the method and device are applied to the electronic equipment, and specifically, various parameters of the ammonia-coal co-combustion boiler are obtained, a typical working condition data set is constructed based on the various parameters, and the typical working condition data set comprises a training set and a test set; model training is carried out based on the typical working condition data set, a combustion optimization model is obtained, and the combustion optimization model comprises a boiler efficiency model, a nitrogen oxide prediction model and an optimization model; and real-time operation parameters of the ammonia-coal mixed combustion boiler are input into the combustion optimization model to be processed, optimal operation parameters are obtained, the optimal operation parameters are used as control parameters of the ammonia-coal mixed combustion boiler, and therefore a control system can control the ammonia-coal mixed combustion boiler to operate under the optimal working condition. According to the scheme, mixed ammonia combustion factors are considered on the basis of an original coal-fired boiler, so that optimized operation parameters for the ammonia-coal mixed combustion boiler are obtained, and low-carbon, efficient and environment-friendly operation of the ammonia-coal mixed combustion boiler can be achieved.

The invention discloses a catalyst addition test correction method, system, equipment and medium, and belongs to the technical field of power system energy storage equipment, and the method comprises the steps: obtaining boiler operation parameters, and constructing a boiler efficiency model; a load-coal consumption correction curve is generated through the boiler efficiency model in combination with blank period test data and used for correcting load differences; based on the adding period test conditions, the blank period boiler efficiency is corrected, and corrected blank reference coal consumption is obtained; and the heat loss calculation is adjusted by correcting the air inlet temperature, the feed water temperature, the fuel characteristics and the air moisture deviation design value, and the boiler efficiency under the corrected condition is obtained. By correcting key parameters such as the air inlet temperature, the feed water temperature, the fuel characteristics and the air moisture, boiler efficiency fluctuation caused by operation condition differences is eliminated, and the comparability of test results in the blank period and the adding period is ensured.

The invention discloses a thermal power plant boiler combustion control method and system, and relates to the field of boiler combustion system control technical equipment. By collecting control loop data of a boiler combustion system in real time, dynamic characteristics, stability and response efficiency of a loop can be analyzed through a multi-dimensional performance evaluation model (including six indexes of steady-state tracking performance, static tracking performance, maximum control deviation, steady-state error, over-limit time and comprehensive tracking performance); based on the evaluation result, the air-coal ratio, the oxygen amount set value and the over-fire air door opening degree are dynamically adjusted through a combustion linkage algorithm, and intervention correction is conducted on set values of loops such as superheat degree control, primary air, secondary air and the coal amount of a coal mill when the performance of the control loop is deteriorated; combining a least square support vector machine to predict NOx concentration and boiler efficiency; and finally, combustion optimization is realized through closed-loop control. The problems that traditional PID control lags behind and loop coordination is poor are solved, boiler efficiency is improved, and pollutant emission is reduced.

An intelligent production scheduling optimization method for environment-friendly power generation waste incineration comprises the steps that S1, according to boiler operation and related data of waste, an objective function and constraint conditions which contribute to maximum total gross benefit (TCM) are established; s2, judging whether the next state of the boiler meets a constraint condition or not according to the related data of the boiler; s3, generating a start-stop scheduling sequence of each boiler; s4, calculating a start-stop sequence and an inventory ratio with maximized revenue; the algorithm is combined with the continuous start-stop period of each boiler, the daily start-stop state is judged and selected, and the loss caused by the fact that the boiler is turned from shutdown to operation is reduced. The boiler efficiency is associated with the inventory ratio, so that the boiler efficiency during incineration is improved, and the heat value of garbage combustion is increased. The data volume for arranging the start-stop state of equipment in a long time period is huge, so that the algorithm greatly reduces unreasonable data by optimizing the generation of a start-stop matrix, and an efficient and economical environment-friendly power plant production scheduling mode is realized by calculating and solving the total contribution gross benefit (TCM) through multiple iterations.

The invention discloses a boiler oxygen amount self-adaptive optimization method and device and a storage medium. According to the technical scheme, the method comprises the steps that a boiler efficiency model containing undetermined parameters is established; actual operation data are obtained in real time in the boiler operation process, and filtering preprocessing is conducted on the data; updating undetermined parameters of the efficiency model in real time according to the processed data by applying online identification algorithms such as a recursive least square method, and generating a real-time correction model capable of reflecting the current characteristics of the boiler; and finally, on the basis of the real-time correction model, calculating and outputting an optimal oxygen amount set value by solving a multi-objective optimization function giving consideration to energy-saving benefits and equipment loss. Preferably, the method further includes utilizing a predictive model to perform prospective control. Compared with the prior art, the method has the advantages that the accuracy, the robustness and the comprehensive economic benefit of oxygen control are remarkably improved through online self-adaption and prospective optimization of the model.

The invention relates to a heat pump coupling frame kit (1) for a hybrid energy transformation device (600). The heat pump coupling frame kit (1) comprises a frame (2) for connecting the heat pump coupling frame kit (1) to a wall and to a boiler unit (500), in particular a boiler frame kit (100). Further provided is a distributor (10) arranged in the frame (2), in particular connected to the frame (2). The distributor (10) comprises at least one load connector set (17, 18) for connecting the distributor (10) with at least one load circuit (300) of an energy system (400), the load connector set (17, 18) comprising a first load connector configured to connect the load circuit of the energy system (400) to an output of the distributor (10) and a second load connector configured to connect a return from the load circuit to the distributor (10); a boiler connector set (15), comprising a first boiler connector configured to connect the distributor (10) to an output line of the boiler unit (500) and a second boiler connector configured to connect the distributor (10) to a return line of the boiler unit (500); and an energy monitoring module (1000) configured to determine a thermal energy production of the boiler unit (500) by: (a) querying the boiler unit (500) via a local connection, bus, or network; and / or (b) determining a first temperature and first flow volume at the first boiler connector, and calculating the thermal energy output of the boiler unit (500) based, at least in part, on the first temperature and the first flow volume, wherein the energy monitoring module (1000) comprises a first temperature sensor and a first flow sensor; and / or (c) determining the first temperature and the first flow volume at the first load connector or at a combined output of the distributor (10) to the at least one load circuit (300), and calculating the thermal energy output of the boiler unit (500) based, at least in part, on the first temperature and the first flow volume, wherein the energy monitoring module (1000) comprises a first temperature sensor (1110) and a first flow sensor (1112); and / or (d) determining the heat demand of the boiler unit (500), and calculating the thermal energy output of the boiler unit (500) based, at least in part, on the heat demand of the boiler unit (500) and a boiler efficiency; and / or (e) determining an energy consumption of the boiler unit (500) and determining the thermal energy output of the boiler unit (500) based, at least in part, on the energy consumption of the boiler unit (500) and the heat boiler efficiency; and / or (f) receiving information from a heat meter via a local connection, bus, or network.

The invention discloses a boiler efficiency correction method considering coal quality change and temperature difference, which is based on the GB / T10184-2015 standard and comprises the following steps of: acquiring coal quality data (industrial analysis and element analysis) and operation parameters of two working conditions before and after a system is put into operation; the coal calorific value average value and the carbon content average value of the comparison working conditions are taken as references; calculating the heat value deviation and the carbon content deviation of the exhaust heat loss correction quantity by adopting a differential deviation method; carrying out ash content and calorific value coupling correction on solid incomplete combustion loss; and finally correcting the boiler efficiency according to the environment temperature difference value + / -10 DEG C. According to the method, the objective comparability of boiler efficiency before and after the intelligent system is put into operation is realized by isolating the interference of coal quality fluctuation and temperature difference.

The invention discloses an offshore platform fuel gas and supercritical carbon dioxide Rankine cycle combined power generation system, and relates to the technical field of offshore platform power generation systems. The problems that an existing thermal power generation technology in which a gas turbine and a steam turbine jointly operate is very low in power generation efficiency and high in carbon emission no matter in the low-temperature heat source field or the high-temperature heat source field are solved. Compressed air is mixed with fuel and combusted, high-temperature and high-pressure flue gas is generated, and a gas turbine is pushed to drive a gas turbine generator to generate power; high-temperature flue gas exhausted by the gas turbine enters the waste heat boiler, heat of the flue gas is used for heating a CO2 working medium in the waste heat boiler to generate high-temperature and high-pressure sCO2, an sCO2 turbine is pushed to drive a turbine generator to generate power, and gas and supercritical carbon dioxide Rankine cycle combined power generation is formed. The exhaust gas temperature of the boiler can be reduced by increasing the inlet smoke temperature of the waste heat boiler, so that the boiler efficiency can be improved after the flue type afterburning device is added, and the purposes of energy conservation and emission reduction are achieved. The invention is suitable for the technical field of offshore power generation.

This utility model discloses a biomass boiler ash removal device with anti-clogging function, comprising: a conveying pipe, one end of which is connected to the boiler, a first pipe extending upwards from the other end of the conveying pipe, and a second pipe extending downwards from the other end of the conveying pipe; and an ash removal structure disposed inside the conveying pipe, which scrapes away the accumulated soot inside the conveying pipe. This utility model can effectively and promptly remove soot, prevent clogging, ensure normal boiler operation, improve boiler efficiency, and reduce the frequency of downtime maintenance.

The invention relates to a thermal power plant boiler efficiency prediction method and system based on cloud computing. The method comprises the steps of collecting historical operation data of thermal power plant boiler operation efficiency; inputting the historical operation data after data preprocessing into a pre-constructed big data model, completing training of the pre-constructed big data model, and obtaining a pre-trained boiler efficiency prediction model; deploying the boiler efficiency prediction model in a cloud production environment; continuously acquiring real-time operation data of the boiler operation efficiency of the thermal power plant; the continuously-collected real-time operation data is subjected to data preprocessing and then input into a pre-trained boiler efficiency prediction model, and a boiler efficiency real-time prediction value is output through the pre-trained boiler efficiency prediction model. The invention discloses a thermal power plant boiler efficiency prediction method based on cloud computing. Based on an anti-balance method, reference efficiency is quickly calculated by using real-time sensor data (exhaust gas temperature, oxygen content and the like).

The utility model discloses a boiler energy efficiency test flue gas sampling device which comprises an assembly, a protection assembly, a wrapping assembly and a pipe body, the protection assembly is arranged at the top end of the assembly, the wrapping assembly is arranged at the tip end of the protection assembly, and the pipe body is arranged on the side of the wrapping assembly. The protection assembly comprises a connecting pipe, an inner cavity channel, a clamping block and a net plate. According to the boiler energy efficiency test flue gas sampling device, the length of the telescopic rod is adjusted through the height of the boiler through pipe and the height of the clamping ring, internal flue gas circulation is facilitated, a heat insulation material is arranged on the outer side of the clamping ring of the boiler through pipe, and heat insulation materials are arranged in the heat-resistant air bag and the heat-resistant cloth in the cover body; leakage is reduced through extrusion of the air bag, due to the fact that the connecting pipe is wrapped in the clamping ring of the boiler through pipe through the tip cover body, built-in smoke circulates through the connecting pipe, the net plate is arranged in the middle, dust in the boiler smoke can be blocked conveniently, and therefore the energy efficiency of the smoke can be efficiently detected.

The denitration and dust removal integrated biomass grate boiler comprises a second flue, a third flue and a fourth flue which are sequentially connected with an outlet of a hearth, the lower end of the second flue is communicated with the lower end of the third flue, and the upper end of the third flue is connected with the upper end of the fourth flue through a furnace top turning flue. A first platen superheater is arranged at the upper part of the hearth, a second platen superheater is arranged in the second flue, a coiled pipe superheater is arranged in the third flue, and denitration equipment, an economizer and a tail heating surface are sequentially arranged in the fourth flue according to the flowing direction of flue gas; dust removal equipment is arranged in the furnace top turning flue, and the dust removal equipment and denitration equipment are supported on a boiler body steel frame. The dust removal equipment and the denitration equipment are also arranged in the range of the boiler body, so that compared with the prior art, the lengths of the inlet flue and the outlet flue are greatly shortened, the heat dissipation loss is reduced, the boiler efficiency is improved, and the dust removal and denitration effects can be improved; and the floor area is small, and the construction cost is low.

The invention provides an automatic coal blending control method and device based on real coal price calculation. The method comprises the following specific steps: combining real-time coal prices with boiler operation characteristics under different conditions to establish a dynamic coal quality cost database about boiler efficiency, coal consumption rate, environmental protection cost and heating surface wear cost; taking the blending proportion of coal as a decision variable, establishing a coal blending strategy optimization model taking the power supply comprehensive cost minimization as a target, and determining a model constraint condition; the real-time boiler operation characteristics are input into a coal blending strategy optimization model, and the coal blending strategy optimization model is optimized in a dynamic coal quality cost database based on model constraint conditions to obtain a coal blending scheme with the minimum power supply comprehensive cost; the coal blending scheme is converted into the running time of the coal conveying belt, and automatic coal blending control is achieved. According to the invention, boiler operation characteristics, fuel cost, environmental protection expenditure and equipment maintenance loss are fused, and intelligent fire coal blending decision and execution can be realized.

The utility model discloses a combustion control device for a garbage incinerator grate furnace, which comprises a fan, a blowpipe and a bypass cold air pipeline, the fan is communicated with the blowpipe and the bypass cold air pipeline, one side of the blowpipe close to the fan is provided with a heating unit, and the other side of the blowpipe is provided with a first air outlet pipe and a second air outlet pipe which are respectively communicated with the front section and the middle section of a combustion chamber; a third air outlet pipe and a fourth air outlet pipe are arranged on the other side of the bypass cold air pipeline, the third air outlet pipe is communicated with the second air outlet pipe, and the fourth air outlet pipe is communicated with the rear section of the combustion chamber; and an adjusting valve is arranged on each air outlet pipe. Controllable air blowing is independently arranged for the front section (drying section), the middle section (combustion section) and the rear section (after-combustion section) of the combustion chamber, the primary air temperature of the drying section is increased, the garbage drying effect is better, the primary air temperature of the combustion section can be adjusted according to the combustion condition, and therefore the combustion intensity is controlled, and the deslagging temperature of the after-combustion section can be effectively reduced; and the boiler efficiency is improved.

This invention provides a method for synergistic optimization of secondary air volume in coal-biomass coupled combustion, belonging to the field of intelligent power generation technology. This method uses machine vision and online spectral monitoring of the boiler furnace to acquire flame images and emission spectra, analyzing the flame center position, furnace outlet temperature, and potassium alkali metal signal value. The monitoring data is fused with unit operating parameters to construct a deep learning database. Based on this database, a multi-objective model of boiler coupled combustion is built, establishing a mapping relationship between unit operating parameters, combustion state, and flue gas emission parameters. A multi-objective weighted sum function is constructed, and the optimal air distribution parameter combination is obtained through iterative optimization using an optimization algorithm. Finally, the control unit interacts with the distributed control system to generate control commands to complete the closed-loop regulation of secondary air volume. This invention can effectively balance boiler efficiency and NOx levels. X The contradiction between emissions and the release of gaseous alkali metal potassium needs to be addressed to improve boiler efficiency and reduce NO in flue gas. X This addresses emissions and mitigates the problem of ash and slag buildup on heated surfaces.

The application discloses a kind of based on neural network and genetic algorithm's thermal power unit working condition dynamic optimization method, system, equipment and storage medium, it is related to thermal power unit intelligent dynamic optimization technical field, including determining fitness function parameter, constructs BP neural network model;Establish the boundary line equation of parameter to be optimized, the upper and lower boundary lines of parameter to be optimized under different loads are fitted out;Using genetic algorithm receives BP neural network model and boundary line equation, publishes working condition optimization AI model, configures non-optimized parameter;Boiler efficiency working condition optimization real-time model is constructed, and based on non-optimized parameter real-time optimization is carried out to parameter to be optimized, obtains efficiency deviation and corresponding parameter to be optimized deviation;The method described in the application realizes thermal power unit working condition dynamic optimization, parameter to be optimized reasonable boundary constraint and efficiency deviation and parameter deviation linkage output, improves the pertinence, coherence and executability of optimization result under complex load condition.

The utility model discloses a novel boiler manhole door device which comprises a furnace shell protection plate, a door frame connected with the furnace shell protection plate and a manhole door cover, a heat preservation layer is arranged in the manhole door cover, and a sealing piece used for sealing is arranged between the door frame and the manhole door cover. The heat preservation layer formed by combining the aluminum silicate fiber blanket and the high-aluminum refractory castable is arranged in the manhole cover, and the sealing piece composed of the ceramic fiber braided ropes is arranged between the door frame and the manhole door cover, so that loss of heat in the boiler is prevented, a good heat preservation effect is achieved, the temperature of the manhole door and the nearby area can be effectively reduced, and the service life of the boiler is prolonged. The boiler efficiency is improved, and the safety near the manhole cover of the boiler is improved; the door frame and the manhole door cover are made of steel plates and are not prone to damage, and the service life of the manhole door is effectively prolonged.

The application discloses a kind of furnace temperature prediction and control system based on deep learning, it is related to thermal power generation technology field.The system includes: data preprocessing module, for obtaining and processing DCS operation data, constructs historical time series data;Key parameter prediction module, using the deep learning time series prediction model of fusion quality balance, energy balance and NOx generation dynamics constraint, output the future change trend of multiple parameters;Multi-objective rolling optimization module, generate optimal control set value sequence;Instruction safety fusion module, after the safe fusion of optimization instruction and DCS original protection logic, issue and execute;And man-machine interaction and performance monitoring module.The application is through the integration framework of physical guided deep learning prediction and rolling time domain optimization, effectively solve the problem of large delay and strong coupling in thermal power unit combustion control, while improving load response speed, guarantee main steam parameter stability, improve boiler efficiency and reduce pollutant emission.

This invention discloses a multi-cold source system and method for a gas-fired steam boiler coupled with a two-stage heat pump. The flue gas from the gas-fired boiler releases heat through two stages of flue gas-water heat exchangers, then enters a parallel first-stage flue gas-air heat exchanger, a third-stage flue gas-water heat exchanger, and a flue gas-circulating water heat exchanger. The flue gas-circulating water heat exchanger provides a heat source for a low-temperature heat pump or a lithium bromide absorption heat pump, or an air-source heat pump can replace the flue gas-circulating water heat exchanger and the low-temperature heat pump. The heat from the flue gas in the parallel structure is distributed, and the released heat from the flue gas heats the air and feedwater. The flue gas then heats the feedwater through the low-temperature heat pump, air-source heat pump, or lithium bromide absorption heat pump. The heated feedwater then absorbs heat through a high-temperature heat pump and the first-stage flue gas-water heat exchanger before entering the gas-fired boiler along with the air. This invention fully absorbs the latent heat of water vapor in the flue gas of a gas-fired steam boiler, reducing the flue gas temperature to below 30°C, raising the feedwater temperature from 20°C to 120-140°C, raising the air temperature from 20°C to 50-90°C, and increasing the boiler efficiency to over 107%.

The invention relates to the field of waste incineration power generation, and discloses a secondary air switching air suction source system and method for a waste incineration power plant. The air inlet end of the first air suction channel is located at the top of the incinerator, and the air outlet end of the first air suction channel communicates with the air inlet side of a secondary fan; the air inlet end of the second air suction channel is located in the garbage pool, and the air outlet end communicates with the air inlet side of the secondary fan; the first control device and the second control device are arranged on the two air suction channels respectively to control on-off. And the control unit is electrically connected with the two control devices respectively, and is switched between two air suction states according to the change of operating parameters of the garbage incinerator and pressure parameters of the garbage pool: air suction is performed from the furnace top by opening one and closing two or air suction is performed from the garbage pool by opening two and closing one. The problem that due to the fact that an existing secondary air system is single in air suction source and fixed in path, garbage pool negative pressure stability and boiler efficiency cannot be considered at the same time during load fluctuation is solved.

The invention discloses a boiler bottom air leakage treatment device and method for a power station boiler dry slag machine, and particularly relates to the field of energy conservation and emission reduction of power station boilers, the boiler bottom air leakage treatment device comprises a dry slag machine body, and boiler bottom air leakage is led out through a cooling air discharge connector, a boiler bottom air leakage discharge connector and a machine tail air leakage discharge connector; a connecting pipe; an air feeder I and an air feeder II; a booster fan; a secondary air box outlet; a slag bin and a slag discharging chamber; and a transition slag hopper. According to the device and method for treating furnace bottom air leakage of the power station boiler slag dryer, through redesign of a traditional mode that cooling air of the slag dryer enters a hearth, the problem that the cooling air of the slag dryer completing heat exchange with furnace bottom slag directly enters the hearth from the furnace bottom as furnace bottom air leakage to disturb combustion is solved; cooling air of the slag drying machine is changed from disordered furnace bottom air leakage into ordered air of secondary air organization, the combustion stability of a hearth can be effectively improved, the smoke exhaust temperature is reduced, and the carbon content of fly ash combustible materials is reduced, so that the boiler efficiency is improved, and the coal consumption is reduced.

The invention provides a carbon emission data detection method and a carbon emission data detection platform. The detection method comprises the following steps: acquiring carbon emission data of the generator set, wherein the carbon emission data comprises as received basis element carbon content, low calorific value, boiler efficiency, turbine efficiency, heat supply carbon emission intensity, heat supply coal consumption, power generation carbon emission intensity and power generation coal consumption; based on a preset calculation formula, calculating design values corresponding to heat supply carbon emission intensity, heat supply coal consumption, power generation carbon emission intensity and power generation coal consumption according to the obtained as received basis element carbon content, the obtained low heating value, the obtained boiler efficiency and the obtained steam turbine efficiency; comparing the corresponding design value with the obtained corresponding carbon emission data to obtain a corresponding comparison result; and according to the corresponding comparison result, judging the rationality of the obtained corresponding carbon emission data. The method can help a power enterprise to check the reasonability of the carbon emission data by themselves.