A method for optimizing the operation of denitrification and air preheater

Abstract

The present invention provides an operation optimization method for denitration and air preheater, which relates to the technical field of coal-fired power denitration and desulfurization, including: step 1: real-time acquisition of denitration process data and air preheater operation data, and output of initial data; step 2: combining the initial data, and using a preset software system to respectively construct simulation models of a cyclone separator, a denitration device, and an air preheater; step 3: based on the simulation model, simulation analysis is performed on the initial data, and simulation analysis results are output, and optimization analysis is performed on the simulation analysis results in combination with preset optimization indicators, and optimization analysis is performed, and optimization analysis results are output; step 4: combined with a preset result-strategy-method comparison table, an optimization strategy and optimization method matching the optimization analysis result are selected in a strategy-method database, and the denitration process and the air preheater operation process are optimized based on the optimization strategy and optimization method. The present invention can improve the denitration and desulfurization efficiency of a thermal power generating set, thereby improving the environmental protection of the thermal power generating set.

Description

Technical Field

[0001] The invention relates to the technical field of coal-fired power denitration and desulfurization, and in particular to an operation optimization method for a denitration and air preheater. Background Art

[0002] One of the core elements of building a new power system is to enhance the grid's ability to absorb new energy. On the one hand, coal-fired power serves as a "stabilizer" and "ballast" to ensure national energy security. On the other hand, it must also serve as a "regulator" for the grid to absorb new energy. Therefore, the deep peak-shaving capability of coal-fired power is a capability that power generation companies must possess.

[0003] One of the key technical issues facing deep peak regulation of coal-fired power is that when the flue gas temperature decreases during low-load operation, the operational stability and reliability of the denitrification and air preheater will be greatly reduced. This is because the flue gas temperature is lower than the temperature window of the denitrification reaction, resulting in reduced denitrification efficiency or shutdown, increased SO3 generation, and increased ammonia escape. SO3 reacts with NH3 to form ammonium bisulfate (ABS), which is deposited on the catalyst or in the air preheater, causing excessive nitrogen oxide emissions or blockage of the air preheater, increasing the power consumption of the induced draft fan, and making it difficult to adjust the unit load, which directly reduces the unit's environmental performance, economy, and peak regulation capability.

[0004] Therefore, the present invention provides a method for optimizing the operation of a denitrification and air preheater. Summary of the invention

[0005] The present invention provides a denitrification and air preheater operation optimization method for establishing a desulfurization and air preheater simulation model, and based on the simulation model, simulates and optimizes the denitrification and desulfurization processes, thereby continuously improving the denitrification and desulfurization efficiency of thermal power generating sets, thereby improving the environmental protection of thermal power generating sets.

[0006] The present invention provides a method for optimizing the operation of a denitrification and air preheater, comprising:

[0007] Step 1: Obtain denitrification process data and air preheater operation data in real time through preset monitoring equipment, and output initial data;

[0008] Step 2: Combine the initial data and use the preset software system to construct simulation models of the cyclone separator, the denitrification equipment and the air preheater respectively;

[0009] Step 3: performing simulation analysis on the initial data based on the simulation model, outputting simulation analysis results, and performing optimization analysis on the simulation analysis results in combination with preset optimization indicators, and outputting optimization analysis results;

[0010] Step 4: In combination with the preset result-strategy-method comparison table, select the optimization strategy and optimization method that match the optimization analysis results in the strategy-method database, and optimize the denitrification process and the air preheater operation process based on the optimization strategy and optimization method.

[0011] Preferably, before obtaining the denitration process data and air preheater operation data in real time through the preset monitoring equipment, the method includes:

[0012] Obtain users' monitoring demand information in real time, conduct comparative analysis on monitoring demand information at different times, and output demand change information;

[0013] Based on the monitoring demand information and demand change information, data collection requirements and preset monitoring equipment are determined, and based on the data collection requirements and preset monitoring equipment, denitrification process data and air preheater operation data are collected.

[0014] Preferably, before step 2, the method further comprises:

[0015] Feature extraction is performed on the monitoring demand information, and a demand feature set is constructed based on the extracted features. In combination with a preset demand feature-software mapping table, a preset software system adapted to the demand feature set is selected from a software database.

[0016] Preferably, step 2 includes:

[0017] The initial data is divided to obtain first initial data corresponding to the cyclone separator, second initial data corresponding to the denitration equipment, and third initial data corresponding to the air preheater;

[0018] Through the preset software system, and based on the first initial data, the second initial data and the third initial data, a cyclone separator simulation model, a denitrification equipment simulation model and an air preheater simulation model are constructed respectively.

[0019] Preferably, performing simulation analysis on the initial data based on the simulation model and outputting simulation analysis results includes:

[0020] Acquire the simulation analysis requirements of the user, and extract the data to be analyzed from the first initial data, the second initial data, and the third initial data based on the simulation analysis requirements, and at the same time, acquire the target historical data matching the data to be analyzed from the historical database;

[0021] The cyclone separator simulation model, the denitrification equipment simulation model and the air preheater simulation model are used to perform simulation analysis on the data to be analyzed and the target historical data, and a first simulation result, a second simulation result and a third simulation result are obtained respectively, and the simulation analysis results are summarized.

[0022] Preferably, the optimizing analysis of the simulation analysis results in combination with preset optimization indicators and outputting the optimization analysis results include:

[0023] Feedback the simulation analysis results to the system end and the user end, and obtain the self-selected optimization indicators generated by the system and the manual optimization indicators input by the user in real time, and output the preset optimization indicator set according to the execution priorities corresponding to the self-selected optimization indicators and the manual optimization indicators;

[0024] Based on the preset optimization index set, the simulation analysis result is optimized and analyzed using a preset optimization algorithm, and the optimization analysis result is output.

[0025] Preferably, after outputting the simulation analysis results, the simulation analysis results are optimized and analyzed in combination with preset optimization indicators, and before outputting the optimization analysis results, the steps include:

[0026] Analyze the simulation analysis results to obtain first analytical data corresponding to the cyclone separator, second analytical data corresponding to the denitration equipment, and third analytical data corresponding to the air preheater;

[0027] At the same time, first measured data corresponding to the first parsed data, second measured data corresponding to the second parsed data, and third measured data corresponding to the third parsed data are acquired in real time;

[0028] Comparing and verifying the first analytical data with the first measured data, the second analytical data with the second measured data, and the third analytical data with the third measured data, respectively, to obtain a model verification result, and selecting a denitrification numerical analysis model and an air preheater numerical analysis model that meet preset performance conditions from a plurality of numerical analysis models constructed by the preset software system based on the model verification result;

[0029] Wherein, the denitrification numerical analysis model includes a chemical reaction rate model, a SNCR reaction model and a drag model;

[0030] Wherein, the chemical reaction rate model includes a urea droplet evaporation sub-model and a urea thermal decomposition sub-model based on a preset urea droplet evaporation algorithm;

[0031] The urea droplet evaporation submodel is as follows:

[0032] ;

[0033] in, represents the change rate of the urea droplet diameter corresponding to the process from the beginning of boiling to complete evaporation of the urea droplet in the preset urea droplet evaporation algorithm; represents the droplet density of urea; represents the gas phase thermal conductivity of urea; represents the latent heat of vaporization of urea; represents the droplet diameter of urea; It represents the Reynolds number defined by the diameter of urea droplet as the qualitative size and the relative velocity between urea droplet and urea solution fluid; represents the ambient temperature, i.e. the temperature away from the surface of the urea droplet; represents the temperature of the urea droplet surface; represents the surface thermal radiation emissivity of the urea droplet; represents the Stefan-Boltzmann constant used to describe thermal radiation; represents the urea vapor temperature on the surface of urea droplets;

[0034] Performing numerical simulation on the denitration process under the first preset working condition by using the denitration numerical analysis model to obtain a denitration simulation result, wherein the first preset working condition includes a first preset reference working condition and a first preset optimized working condition;

[0035] Combining the first measured data and the second measured data, performing data comparison and analysis on the denitration simulation results under the first preset working condition, obtaining the inlet and outlet NO mass concentration, denitration efficiency and ammonia slip data of the cyclone separator under the first preset working condition, and outputting the denitration analysis results;

[0036] The air preheater numerical analysis model is used to perform numerical simulation on the flue gas temperature, SO3 concentration and NH3 concentration data in the air preheater under the second preset working condition to obtain an air preheater simulation result;

[0037] Analyze the air preheater simulation results in combination with the third measured data to obtain the smoke temperature distribution, SO3 concentration distribution and NH3 concentration distribution results of the air preheater under the second preset operating condition;

[0038] Based on the temperature distribution, SO3 concentration distribution and NH3 concentration distribution results, a temperature change diagram, a SO3 concentration change diagram and an NH3 concentration change diagram under the second preset operating condition are constructed to analyze the temperature change of the flue gas temperature in the air preheater under different unit load conditions, the SO3 concentration change, the NH3 concentration change and the generation of ammonium bisulfate, and output the air preheater analysis results;

[0039] Based on the denitrification analysis results and the air preheater analysis results, the results to be optimized are summarized and output.

[0040] Preferably, step 4 includes:

[0041] Analyze the optimization analysis results and obtain optimization analysis data based on the analysis content;

[0042] Performing keyword recognition and extraction on the optimized parsed data, and constructing a keyword set based on the extracted keywords;

[0043] Matching the keyword set with preset keywords in a preset word library, and outputting the matched keywords as keyword matching results;

[0044] Combined with a preset keyword-factor comparison table, the matching factor corresponding to each keyword in the keyword matching result is obtained, and a matching factor set is output;

[0045] In combination with a preset matching factor-strategy-method comparison table, an optimization strategy and an optimization method corresponding to each matching factor in the matching factor set are selected from a strategy-method database;

[0046] Based on the optimization strategy and optimization method, the denitration reaction process in the cyclone separator, the SO3 removal process in the air preheater and the ammonium bisulfate generation process are optimized;

[0047] Obtain parameter change data in the optimized cyclone separator and air preheater, output feedback data, and adjust the optimization strategy and optimization method based on the feedback data.

[0048] The present invention provides a method for optimizing the operation of denitrification and air preheater. The present invention can optimize the operation of denitrification and air preheater by real-time monitoring data, establishing a simulation model, performing optimization analysis, and selecting optimization strategies and methods. The optimized system has the advantages of higher efficiency, lower energy consumption, more stable operation, etc., thereby improving the performance of denitrification equipment and reducing operating costs. The present invention can help engineers and operators better manage and optimize the operation of denitrification systems and air preheaters. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 It is a flow chart of a method for optimizing the operation of a denitrification and air preheater provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] like Figure 1 As shown, an operation optimization method of a denitrification and air preheater provided by an embodiment of the present invention comprises:

[0053] Step 1: Obtain denitrification process data and air preheater operation data in real time through preset monitoring equipment, and output initial data;

[0054] Step 2: Combine the initial data and use the preset software system to build simulation models of the cyclone separator, denitrification equipment and air preheater respectively;

[0055] Step 3: Perform simulation analysis on the initial data based on the simulation model, output the simulation analysis results, and optimize the simulation analysis results in combination with preset optimization indicators, and output the optimization analysis results;

[0056] Step 4: Combined with the preset result-strategy-method comparison table, select the optimization strategy and optimization method that match the optimization analysis results from the strategy-method database, and optimize the denitrification process and air preheater operation process based on the optimization strategy and optimization method.

[0057] In this embodiment, the preset monitoring device: a preset device for monitoring denitration process data and air preheater operation data;

[0058] In this embodiment, denitration process data: data related to the denitration process, including nitrogen oxide concentration, reaction temperature, reaction time, etc.;

[0059] In this embodiment, air preheater operation data: data describing the operation status of the air preheater, such as air flow, temperature, pressure, etc.;

[0060] In this embodiment, the initial data is a summary of the denitration process data and air preheater operation data acquired in real time by the monitoring equipment;

[0061] In this embodiment, the preset software system: a pre-set software system for building a simulation model, for example, the Barracuda software used in the present invention, has built-in multiple chemical reaction types and reaction kinetic forms, such as volume average reaction, discrete phase reaction, core shrinkage reaction, Arrhenius kinetics, polynomial kinetics, etc. Based on the theoretical basis of chemical reaction kinetics, the chemical reaction phenomena between different phases and between different components in the same phase in the particle-fluid system can be analyzed. It supports gas-gas, solid-gas, and solid-solid chemical reactions, and includes a chemical component database, which can simulate catalytic reactions and solid consumption reactions. The software can define chemical reactions and reaction rates through parameter input in a graphical interface, and it is very convenient to set the entire chemical reaction process generated by ABS;

[0062] In this embodiment, the simulation model: simulation models constructed for the cyclone separator, the denitration equipment and the air preheater are respectively used to simulate the actual operation;

[0063] In this embodiment, simulation analysis results: simulation analysis results obtained by the simulation model reflect the operation of the system;

[0064] In this embodiment, preset optimization index: an index set in advance for evaluating system performance and optimizing, including but not limited to energy consumption, emission concentration, system stability, etc.;

[0065] In this embodiment, the optimization analysis result: the result obtained after optimizing the simulation analysis result to achieve the preset optimization index;

[0066] In this embodiment, the result-strategy-method comparison table: a comparison table used to match the optimization analysis results and select corresponding optimization strategies and methods;

[0067] In this embodiment, strategy-method database: a database storing various optimization strategies and methods;

[0068] In this embodiment, optimization strategy and optimization method: specific strategy and method selected according to the optimization analysis results, used to optimize the denitration process and air preheater operation.

[0069] Implementation principle and beneficial effects of this embodiment: The present invention can optimize the operation of denitration and air preheater by real-time monitoring data, establishing simulation models, performing optimization analysis and selecting optimization strategies and methods. The optimized system has the advantages of higher efficiency, lower energy consumption, more stable operation, etc., thereby improving the performance of denitration equipment and reducing operating costs. The present invention can help engineers and operators better manage and optimize the operation of denitration systems and air preheaters.

[0070] An operation optimization method for denitration and air preheater provided by an embodiment of the present invention includes: before obtaining denitration process data and air preheater operation data in real time through a preset monitoring device, the method includes:

[0071] Obtain users' monitoring demand information in real time, conduct comparative analysis on monitoring demand information at different times, and output demand change information;

[0072] Based on the monitoring demand information and demand change information, the data collection requirements and preset monitoring equipment are determined, and the denitrification process data and air preheater operation data are collected based on the data collection requirements and the preset monitoring equipment.

[0073] In this embodiment, monitoring demand information: user's demand information for monitoring data, including monitoring parameters, frequency, accuracy, etc.;

[0074] In this embodiment, demand change information: comparative analysis results of monitoring demand information at different time points, used to indicate whether the monitoring demand has changed;

[0075] In this embodiment, data collection requirements: data collection requirements determined based on monitoring demand information and demand change information, including which data need to be collected, how to collect, when to collect, etc., for example, parameters that need to be monitored, such as nitrogen oxide concentration, temperature, pressure, etc.; frequency of data collection, such as every minute, every hour or in real time; accuracy requirements for data collection, such as the accuracy of several decimal places.

[0076] The implementation principle and beneficial effects of this embodiment: After determining the monitoring demand information and data collection requirements, the present invention can more accurately configure the monitoring equipment and obtain the denitrification process data and air preheater operation data in real time. The present invention can adjust the data collection method according to actual needs through the analysis of the monitoring demand information and demand change information to ensure that the data obtained meets the actual monitoring requirements. Such an optimization method can improve the efficiency and accuracy of data collection, provide more reliable data support for subsequent simulation analysis and optimization, and then optimize the operation of denitrification and air preheater, improve system performance and reduce energy consumption.

[0077] The operation optimization method of a denitration and air preheater provided by an embodiment of the present invention further includes, before step 2:

[0078] Feature extraction is performed on the monitoring demand information, and a demand feature set is constructed based on the extracted features. In addition, a preset software system that is compatible with the demand feature set is selected from the software database in combination with a preset demand feature-software mapping table.

[0079] In this embodiment, demand feature set: a feature set extracted from monitoring demand information, used to describe the characteristics and attributes of the monitoring demand;

[0080] In this embodiment, the requirement feature-software mapping table: a table containing the mapping relationship between the requirement features and the preset software systems, so as to select an adaptive software system;

[0081] In this embodiment, the software database is a database that stores various preset software systems and their characteristics, functions, scope of application and other information. For example, software system A used to establish simulation models and perform optimization analysis has high flexibility and customization; software system B used for data processing and simulation optimization has fast calculation and visual analysis capabilities.

[0082] The implementation principle and beneficial effects of this embodiment: After feature extraction and demand feature set construction, the present invention can select an adaptive preset software system in combination with the demand feature-software mapping table. The present invention can select the most suitable software system for data processing, modeling and optimization analysis according to the characteristics and requirements of the monitoring needs. By selecting a suitable software system, the present invention can improve work efficiency, reduce human errors, and ensure the stability and reliability of the system.

[0083] An operation optimization method for denitration and air preheater provided by an embodiment of the present invention comprises, in step 2:

[0084] The initial data is divided to obtain first initial data corresponding to the cyclone separator, second initial data corresponding to the denitration equipment, and third initial data corresponding to the air preheater;

[0085] Through the preset software system, and based on the first initial data, the second initial data and the third initial data, a cyclone separator simulation model, a denitrification equipment simulation model and an air preheater simulation model are constructed respectively.

[0086] In this embodiment, the first initial data: initial data corresponding to the cyclone separator, including design parameters, operating conditions and operating parameters of the cyclone separator;

[0087] In this embodiment, the second initial data: initial data corresponding to the denitration equipment, including information such as the reactor design and catalyst properties of the denitration equipment;

[0088] In this embodiment, the third initial data: initial data corresponding to the air preheater, including structural parameters and combustion conditions of the air preheater;

[0089] In this embodiment, the cyclone separator simulation model: a mathematical model for simulating and optimizing the performance of the cyclone separator constructed based on the first initial data;

[0090] In this embodiment, the denitration equipment simulation model: a mathematical model constructed based on the second initial data for simulating and optimizing the performance of the denitration equipment;

[0091] In this embodiment, the air preheater simulation model: a mathematical model constructed based on the third initial data for simulating and optimizing the performance of the air preheater, for example, the input data is the combustion temperature, fuel composition and other parameters of the air preheater, and the output data is the simulation data under performance indicators such as the thermal efficiency and NOx emission concentration of the air preheater.

[0092] Implementation principle and beneficial effects of this embodiment: The present invention can simulate and optimize the performance of cyclone separators, denitrification equipment and air preheaters by dividing initial data and constructing corresponding simulation models. Each simulation model can adjust and optimize parameters according to its corresponding initial data to achieve more efficient denitrification and air preheater operation. The present invention can help system operators better understand system behavior, predict possible problems, and take corresponding measures for optimization, thereby improving system efficiency, reducing energy consumption, and optimizing system performance.

[0093] An operation optimization method for a denitrification and air preheater provided in an embodiment of the present invention performs simulation analysis on initial data based on a simulation model and outputs simulation analysis results, including:

[0094] Acquire the simulation analysis requirements of the user, and extract the data to be analyzed from the first initial data, the second initial data, and the third initial data based on the simulation analysis requirements, and at the same time, acquire the target historical data matching the data to be analyzed from the historical database;

[0095] The cyclone separator simulation model, the denitrification equipment simulation model and the air preheater simulation model are used to perform simulation analysis on the data to be analyzed and the target historical data, and the first simulation result, the second simulation result and the third simulation result are obtained respectively, and the simulation analysis results are summarized.

[0096] In this embodiment, simulation analysis requirements: requirements on system performance, efficiency, etc. proposed by users, which are used to guide the goals and directions of simulation analysis;

[0097] In this embodiment, the data to be analyzed is the data extracted from the first, second, and third initial data for simulation analysis.

[0098] In this embodiment, historical database: a database storing historical operation data of the system, used for comparison and analysis with the data to be analyzed;

[0099] In this embodiment, target historical data: data obtained from the historical database that matches the data to be analyzed and is used as a comparison and reference;

[0100] In this embodiment, the first simulation result: the simulation analysis result obtained by the cyclone separator simulation model, including simulation data under the indicators such as separation efficiency and pressure drop;

[0101] In this embodiment, the second simulation result: the simulation analysis result obtained by the denitration equipment simulation model, including simulation data under indicators such as denitration efficiency and catalyst activity;

[0102] In this embodiment, the third simulation result: the simulation analysis result obtained by the air preheater simulation model, including simulation data under indicators such as thermal efficiency and NOx emission concentration.

[0103] The implementation principle and beneficial effects of this embodiment: The present invention can extract the data to be analyzed from the initial data according to the simulation analysis requirements of the user, and compare and analyze the target historical data in the historical database. The present invention can use various simulation models to simulate and analyze the corresponding data, obtain respective simulation results, and finally summarize the overall simulation analysis results, so as to help users better understand the operation of the system, optimize system performance, improve the efficiency of denitration and air preheater, and reduce energy consumption.

[0104] An operation optimization method for a denitrification and air preheater provided in an embodiment of the present invention optimizes and analyzes simulation analysis results in combination with preset optimization indicators, and outputs optimization analysis results, including:

[0105] Feedback the simulation analysis results to the system and the user, and obtain the self-selected optimization indicators generated by the system and the manual optimization indicators input by the user in real time, and output the preset optimization indicator set according to the execution priority corresponding to the self-selected optimization indicators and the manual optimization indicators;

[0106] Based on the preset optimization indicator set and using the preset optimization algorithm, the simulation analysis results are optimized and analyzed, and the optimization analysis results are output.

[0107] In this embodiment, the system end refers to the denitration and air preheater system itself, which is used to monitor and control the system operation in real time;

[0108] In this embodiment, the user terminal refers to a user such as a system operator or engineer, who can interact with the system and set parameters through the user terminal;

[0109] In this embodiment, the optimization index is selected automatically: the optimization index automatically generated by the system according to a preset algorithm is used to evaluate the system performance and optimize it;

[0110] In this embodiment, manual optimization index: an optimization index manually set by a user, an optimization target determined according to user needs and experience;

[0111] In this embodiment, execution priority: the priority order of execution of optimization indicators to determine which optimization indicators should be considered first;

[0112] In this embodiment, the preset optimization index set is a set of optimization indexes determined according to the self-selected optimization indexes and the manual optimization indexes and their execution priorities, and is used to guide the execution of the optimization algorithm;

[0113] In this embodiment, the preset optimization algorithm is an algorithm for performing optimization analysis according to a preset optimization index set, which is used to adjust system parameters to achieve performance optimization, for example, using a genetic algorithm or a simulated annealing algorithm to optimize system parameters.

[0114] The implementation principle and beneficial effects of this embodiment: The present invention works together through the system end and the user end. The system end provides real-time data feedback, and the user end sets manual optimization indicators. The system executes the optimization algorithm according to the self-selected optimization indicators and the manual optimization indicators, and outputs the optimization results. The present invention can realize dynamic optimization of system performance, adjust system parameters according to real-time data and user needs, and improve the operating efficiency and performance of denitrification and air preheater. Through the preset optimization algorithm, the system can automatically adjust parameters to achieve continuous optimization of the system, improve energy efficiency, reduce emissions, and meet user needs.

[0115] An operation optimization method for a denitrification and air preheater provided in an embodiment of the present invention comprises: after outputting a simulation analysis result, optimizing the simulation analysis result in combination with a preset optimization index, and before outputting the optimization analysis result, comprising:

[0116] The simulation analysis results are analyzed to obtain first analytical data corresponding to the cyclone separator, second analytical data corresponding to the denitration equipment, and third analytical data corresponding to the air preheater;

[0117] At the same time, first measured data corresponding to the first analyzed data, second measured data corresponding to the second analyzed data, and third measured data corresponding to the third analyzed data are acquired in real time;

[0118] Comparing and verifying the first analytical data with the first measured data, the second analytical data with the second measured data, and the third analytical data with the third measured data, respectively, to obtain a model verification result, and based on the model verification result, selecting a denitrification numerical analysis model and an air preheater numerical analysis model that meet preset performance conditions from a plurality of numerical analysis models constructed by a preset software system;

[0119] Among them, the denitrification numerical analysis model includes chemical reaction rate model, SNCR reaction model and drag model;

[0120] The chemical reaction rate model includes a urea droplet evaporation sub-model based on a preset urea droplet evaporation algorithm and a urea thermal decomposition sub-model;

[0121] The urea droplet evaporation submodel is as follows:

[0122] ;

[0123] in, Indicates the change rate of the urea droplet diameter corresponding to the process from the beginning of boiling to complete evaporation of the urea droplet in the preset urea droplet evaporation algorithm; represents the droplet density of urea; represents the gas phase thermal conductivity of urea; represents the latent heat of vaporization of urea; represents the droplet diameter of urea; It represents the Reynolds number defined by the diameter of urea droplet as the qualitative size and the relative velocity between urea droplet and urea solution fluid; represents the ambient temperature, i.e. the temperature away from the surface of the urea droplet; represents the temperature of the urea droplet surface; represents the surface thermal radiation emissivity of the urea droplet; represents the Stefan-Boltzmann constant used to describe thermal radiation; represents the urea vapor temperature on the surface of urea droplets;

[0124] A denitration process under a first preset operating condition is numerically simulated by a denitration numerical analysis model to obtain a denitration simulation result, wherein the first preset operating condition includes a first preset reference operating condition and a first preset optimized operating condition;

[0125] Combining the first measured data and the second measured data, the denitrification simulation results under the first preset working condition are compared and analyzed to obtain the inlet and outlet NO mass concentration, denitrification efficiency and ammonia escape data of the cyclone separator under the first preset working condition, and output the denitrification analysis results;

[0126] The air preheater numerical analysis model is used to perform numerical simulation on the flue gas temperature, SO3 concentration and NH3 concentration data in the air preheater under the second preset working condition to obtain the air preheater simulation result;

[0127] The air preheater simulation results are analyzed in combination with the third measured data to obtain the smoke temperature distribution, SO3 concentration distribution and NH3 concentration distribution results of the air preheater under the second preset working condition;

[0128] Based on the temperature distribution, SO3 concentration distribution and NH3 concentration distribution results, the temperature change diagram, SO3 concentration change diagram and NH3 concentration change diagram under the second preset working condition are constructed to analyze the temperature change of the flue gas temperature, SO3 concentration change, NH3 concentration change and the generation of ammonium bisulfate in the air preheater under different unit load conditions, and output the air preheater analysis results;

[0129] Based on the denitrification analysis results and the air preheater analysis results, the results to be optimized are summarized and output.

[0130] In this embodiment, the first analytical data: analytical data corresponding to the cyclone separator, used to analyze the simulation performance and effect of the cyclone separator simulation model;

[0131] In this embodiment, the second analytical data: analytical data corresponding to the denitration equipment, used to analyze the simulation performance and effect of the denitration equipment simulation model;

[0132] In this embodiment, the third analytical data: analytical data corresponding to the air preheater, used to analyze the simulation performance and effect of the air preheater simulation model;

[0133] In this embodiment, the first measured data: measured data corresponding to the first analytical data, used to verify the accuracy of the model;

[0134] In this embodiment, the second measured data: measured data corresponding to the second analytical data, used to verify the accuracy of the model;

[0135] In this embodiment, the third measured data: measured data corresponding to the third analytical data, used to verify the accuracy of the model;

[0136] In this embodiment, the model verification result: the verification result obtained by comparing the analytical data and the measured data is used to evaluate the accuracy of the simulation data obtained by the simulation model;

[0137] In this embodiment, the numerical analysis model: a model used to perform numerical simulation and analysis on the system;

[0138] In this embodiment, the preset performance conditions are performance requirements and conditions that are preset and used to screen the numerical analysis model;

[0139] In this embodiment, the denitration numerical analysis model: a model used to numerically simulate and analyze the denitration process;

[0140] In this embodiment, the air preheater numerical analysis model: a model used to perform numerical simulation and analysis on the internal parameters of the air preheater;

[0141] In this embodiment, chemical reaction rate model: a model describing the chemical reaction rate, used to simulate the chemical reaction rate in the denitration process;

[0142] In this embodiment, SNCR reaction model: a model used to describe the selective non-catalytic reduction (SNCR) reaction to help understand and optimize the denitrification process;

[0143] In this embodiment, drag model: a model that describes the airflow force on particles or droplets during the denitration process;

[0144] In this embodiment, the urea droplet evaporation sub-model: a model of the urea droplet evaporation process, used to describe the behavior of the urea droplets from boiling to complete evaporation during the denitration process;

[0145] In this embodiment, urea pyrolysis sub-model: a model describing the urea pyrolysis process, which helps analyze the pyrolysis behavior of urea in the denitrification process;

[0146] In this embodiment, the first preset working condition: a specific working condition set in advance, used for numerical simulation and analysis of the denitration process, for example, the T01 benchmark working condition in which the urea solution injection flow rate in the cyclone separator is 0.44 kg / s, the T01 benchmark working condition in which the jet flow rate is 0.41 kg / s, and multiple optimized working conditions obtained by optimizing the position and number of spray guns based on the T01 benchmark working condition and the T02 benchmark working condition, for example, the five nozzles at the inlet of the cyclone separator are changed to four nozzles, and the other parameters remain unchanged. T03 working condition;

[0147] In this embodiment, the denitration simulation result: the result of the denitration process obtained by numerical simulation under the first preset working condition;

[0148] In this embodiment, the first preset reference operating condition: is a reference state in the first preset operating condition, which is used to compare and analyze the denitration effect;

[0149] In this embodiment, the first preset optimized operating condition: the operating condition after optimization adjustment under the first preset operating condition is used to evaluate the improvement of the denitration effect;

[0150] In this embodiment, denitration analysis results: denitration effect analysis results obtained by comparing simulation data with measured data;

[0151] In this embodiment, the second preset working condition is used to evaluate the performance of the air preheater system under different operating conditions, for example, including: BMCR (Boiler maximum continuous rating) working condition, BRL rated working condition, full cut high processing condition, 100% THA working condition, 75% THA working condition, 50% THA working condition, 30% BMCR working condition;

[0152] In this embodiment, the air preheater simulation results are: data results such as the flue gas temperature, SO3 concentration and NH3 concentration in the air preheater under the second preset working condition obtained by numerical simulation;

[0153] In this embodiment, the air preheater analysis results: the performance and characteristics of the air preheater system under the second preset operating condition obtained by comparing and analyzing the simulation results and the measured data.

[0154] The implementation principle and beneficial effects of this embodiment: The present invention ensures the accuracy of the numerical analysis model by comparing and verifying the analytical data and the measured data. According to the verification results, the denitrification and air preheater numerical analysis model that meets the performance conditions is selected from the numerical analysis model constructed by the preset software system. The present invention numerically simulates the denitrification and air preheater processes under different unit load conditions to obtain the simulation results of the denitrification and air preheater, and compares and analyzes them with the measured data, and outputs the analysis results of the denitrification and air preheater, which can help optimize the system operation, improve the efficiency of the denitrification and air preheater, reduce energy consumption and emissions, and guide the further optimization and improvement of the system.

[0155] An operation optimization method for denitration and air preheater provided by an embodiment of the present invention comprises, in step 4:

[0156] Analyze the optimization analysis results and obtain optimization analysis data based on the analysis content;

[0157] Identify and extract keywords from the optimized parsing data, and construct a keyword set based on the extracted keywords;

[0158] Matching the keyword set with preset keywords in a preset vocabulary, and outputting the matched keywords as keyword matching results;

[0159] Combined with the preset keyword-factor comparison table, obtain the matching factor corresponding to each keyword in the keyword matching result, and output the matching factor set;

[0160] In combination with the preset matching factor-strategy-method comparison table, an optimization strategy and an optimization method corresponding to each matching factor in the matching factor set are selected from the strategy-method database;

[0161] Based on the optimization strategy and optimization method, the denitrification reaction process in the cyclone separator, the SO3 removal process in the air preheater and the ammonium bisulfate generation process are optimized;

[0162] Obtain parameter change data in the optimized cyclone separator and air preheater, output feedback data, and adjust the optimization strategy and optimization method based on the feedback data.

[0163] In this embodiment, the optimization analysis data: data extracted based on the optimization analysis results, used to identify and extract key information for subsequent optimization analysis;

[0164] In this embodiment, keyword identification and extraction: identifying keywords in the parsed data and extracting them for subsequent analysis and processing;

[0165] In this embodiment, keyword set: a set of keywords extracted from the text, for example, keywords such as "denitrification efficiency" and "ammonia escape";

[0166] In this embodiment, the preset word library: a predefined word library containing specific keywords;

[0167] In this embodiment, preset keywords: predefined keywords for matching and analysis, such as "NOx emission", "ammonia slip";

[0168] In this embodiment, the keyword matching result: the result obtained after matching the extracted keyword with the preset keyword library;

[0169] In this embodiment, the keyword-factor comparison table: a comparison table including mapping relationships between keywords and matching factors;

[0170] In this embodiment, matching factor: a factor or feature associated with a keyword;

[0171] In this embodiment, the matching factor set is a set of matching factors extracted from the matching results;

[0172] In this embodiment, the matching factor-strategy-method comparison table: a comparison table including mapping relationships between matching factors and optimization strategies and optimization methods;

[0173] In this embodiment, parameter change data: after optimization, the parameter change data in the cyclone separator and the air preheater, for example, after optimization, the temperature distribution inside the cyclone separator changes and the SO3 concentration decreases;

[0174] In this embodiment, feedback data: result data obtained after adjusting the optimization strategy and method according to the parameter change data, is used to feed back to the system, for example, the denitrification efficiency of the denitrification system is improved and the ammonia escape is reduced through the optimization strategy and optimization method.

[0175] Implementation principle and beneficial effects of this embodiment: The present invention can more accurately understand the needs and directions of system optimization through keyword recognition and matching, factor extraction, strategy selection and parameter change data analysis. At the same time, the optimized feedback data can help adjust the optimization strategy and method, further improve system performance and efficiency, and reduce energy consumption and emissions. The present invention can effectively guide the optimization of the denitration and desulfurization system, improve the operating efficiency and stability of the denitration and air preheater system, and thus achieve the goal of energy conservation and emission reduction.

[0176] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the operation of a denitrification and air preheater, characterized in that: include: Step 1: Obtain denitrification process data and air preheater operation data in real time through preset monitoring equipment, and output initial data; Step 2: Combine the initial data and use the preset software system to construct simulation models of the cyclone separator, the denitrification equipment and the air preheater respectively; Step 3: performing simulation analysis on the initial data based on the simulation model, outputting simulation analysis results, and performing optimization analysis on the simulation analysis results in combination with preset optimization indicators, and outputting optimization analysis results; Step 4: In combination with the preset result-strategy-method comparison table, an optimization strategy and an optimization method matching the optimization analysis result are selected from the strategy-method database, and the denitrification process and the air preheater operation process are optimized based on the optimization strategy and the optimization method; Among them, in step 3, after outputting the simulation analysis results, the simulation analysis results are optimized and analyzed in combination with preset optimization indicators, and before outputting the optimization analysis results, the steps include: Analyze the simulation analysis results to obtain first analytical data corresponding to the cyclone separator, second analytical data corresponding to the denitration equipment, and third analytical data corresponding to the air preheater; At the same time, first measured data corresponding to the first parsed data, second measured data corresponding to the second parsed data, and third measured data corresponding to the third parsed data are acquired in real time; Comparing and verifying the first analytical data with the first measured data, the second analytical data with the second measured data, and the third analytical data with the third measured data, respectively, to obtain a model verification result, and selecting a denitrification numerical analysis model and an air preheater numerical analysis model that meet preset performance conditions from a plurality of numerical analysis models constructed by the preset software system based on the model verification result; Wherein, the denitrification numerical analysis model includes a chemical reaction rate model, a SNCR reaction model and a drag model; Wherein, the chemical reaction rate model includes a urea droplet evaporation sub-model and a urea thermal decomposition sub-model based on a preset urea droplet evaporation algorithm; The urea droplet evaporation submodel is as follows: ； in, represents the change rate of the urea droplet diameter corresponding to the process from the beginning of boiling to complete evaporation of the urea droplet in the preset urea droplet evaporation algorithm; represents the droplet density of urea; represents the gas phase thermal conductivity of urea; represents the latent heat of vaporization of urea; represents the droplet diameter of urea; It represents the Reynolds number defined by the diameter of urea droplet as the qualitative size and the relative velocity between urea droplet and urea solution fluid; represents the ambient temperature, i.e. the temperature away from the surface of the urea droplet; represents the temperature of the urea droplet surface; represents the surface thermal radiation emissivity of the urea droplet; represents the Stefan-Boltzmann constant used to describe thermal radiation; represents the urea vapor temperature on the surface of urea droplets; Performing numerical simulation on the denitration process under the first preset working condition by using the denitration numerical analysis model to obtain a denitration simulation result, wherein the first preset working condition includes a first preset reference working condition and a first preset optimized working condition; Combining the first measured data and the second measured data, performing data comparison and analysis on the denitration simulation results under the first preset working condition, obtaining the inlet and outlet NO mass concentration, denitration efficiency and ammonia slip data of the cyclone separator under the first preset working condition, and outputting the denitration analysis results; The air preheater numerical analysis model is used to perform numerical simulation on the flue gas temperature, SO3 concentration and NH3 concentration data in the air preheater under the second preset working condition to obtain an air preheater simulation result; Analyze the air preheater simulation results in combination with the third measured data to obtain the smoke temperature distribution, SO3 concentration distribution and NH3 concentration distribution results of the air preheater under the second preset operating condition; Based on the temperature distribution, SO3 concentration distribution and NH3 concentration distribution results, a temperature change diagram, a SO3 concentration change diagram and an NH3 concentration change diagram under the second preset operating condition are constructed to analyze the temperature change of the flue gas temperature, the SO3 concentration change, the NH3 concentration change and the generation of ammonium bisulfate in the air preheater under different unit load conditions, and output the air preheater analysis results; Based on the denitrification analysis results and the air preheater analysis results, the results to be optimized are summarized and output.

2. The method for optimizing the operation of a denitrification and air preheater according to claim 1, characterized in that: Before obtaining the denitration process data and air preheater operation data in real time through the preset monitoring equipment, it includes: Obtain users' monitoring demand information in real time, conduct comparative analysis on monitoring demand information at different times, and output demand change information; Based on the monitoring demand information and demand change information, data collection requirements and preset monitoring equipment are determined, and based on the data collection requirements and preset monitoring equipment, denitrification process data and air preheater operation data are collected.

3. The method for optimizing the operation of a denitrification and air preheater according to claim 2, characterized in that: Before step 2, also include: Feature extraction is performed on the monitoring demand information, and a demand feature set is constructed based on the extracted features. In combination with a preset demand feature-software mapping table, a preset software system adapted to the demand feature set is selected from a software database.

4. The method for optimizing the operation of a denitrification and air preheater according to claim 1, characterized in that: Step 2 includes: The initial data is divided to obtain first initial data corresponding to the cyclone separator, second initial data corresponding to the denitration equipment, and third initial data corresponding to the air preheater; Through the preset software system, and based on the first initial data, the second initial data and the third initial data, a cyclone separator simulation model, a denitrification equipment simulation model and an air preheater simulation model are constructed respectively.

5. The method for optimizing the operation of a denitrification and air preheater according to claim 4, characterized in that: The performing simulation analysis on the initial data based on the simulation model and outputting simulation analysis results includes: Acquire the simulation analysis requirements of the user, and extract the data to be analyzed from the first initial data, the second initial data, and the third initial data based on the simulation analysis requirements, and at the same time, acquire the target historical data matching the data to be analyzed from the historical database; The cyclone separator simulation model, the denitrification equipment simulation model and the air preheater simulation model are used to perform simulation analysis on the data to be analyzed and the target historical data, and a first simulation result, a second simulation result and a third simulation result are obtained respectively, and the simulation analysis results are summarized.

6. The method for optimizing the operation of a denitrification and air preheater according to claim 1, characterized in that: The optimizing analysis of the simulation analysis results in combination with preset optimization indicators and outputting the optimization analysis results includes: Feedback the simulation analysis results to the system end and the user end, and obtain the self-selected optimization indicators generated by the system and the manual optimization indicators input by the user in real time, and output the preset optimization indicator set according to the execution priorities corresponding to the self-selected optimization indicators and the manual optimization indicators; Based on the preset optimization index set, the simulation analysis result is optimized and analyzed using a preset optimization algorithm, and the optimization analysis result is output.

7. The method for optimizing the operation of a denitrification and air preheater according to claim 1, characterized in that: Step 4 includes: Analyze the optimization analysis results and obtain optimization analysis data based on the analysis content; Performing keyword recognition and extraction on the optimized parsed data, and constructing a keyword set based on the extracted keywords; Matching the keyword set with preset keywords in a preset word library, and outputting the matched keywords as keyword matching results; Combined with a preset keyword-factor comparison table, the matching factor corresponding to each keyword in the keyword matching result is obtained, and a matching factor set is output; In combination with a preset matching factor-strategy-method comparison table, an optimization strategy and an optimization method corresponding to each matching factor in the matching factor set are selected from a strategy-method database; Based on the optimization strategy and optimization method, the denitration reaction process in the cyclone separator, the SO3 removal process in the air preheater and the ammonium bisulfate generation process are optimized; Obtain parameter change data in the optimized cyclone separator and air preheater, output feedback data, and adjust the optimization strategy and optimization method based on the feedback data.

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