CN110848733A - Combustion optimization method based on coal quality on-line monitoring - Google Patents
Combustion optimization method based on coal quality on-line monitoring Download PDFInfo
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Abstract
The invention discloses a combustion optimization method based on coal quality on-line monitoring, which comprises a coal quality on-line monitoring method; a coal pulverizing system operation optimization method based on coal quality on-line monitoring; a refined air distribution optimization method based on coal quality on-line monitoring; an exhaust gas oxygen amount optimization method based on coal quality on-line monitoring. The coal pulverizing system optimizes to realize the real-time optimization of the air-coal ratio of the coal mill; the refined air distribution optimization realizes the proportioning optimization of the secondary air volume and the burning air volume of all the burners; and the total air volume is optimized by the oxygen content of the discharged smoke. The combustion optimization method can adapt to the change of coal quality and load to carry out dynamic real-time optimization, effectively improves the boiler efficiency and reduces the emission of pollutants NOx.
Description
The technical field is as follows:
the invention relates to a combustion optimization method based on coal quality on-line monitoring, in particular to the technical field of boiler combustion optimization control of a coal-fired power generating unit.
Background art:
the coal-fired thermal power generating set causes the boiler combustion to deviate from the designed coal types due to the reasons of variable load, variable coal types and the like, and the traditional boiler coordination control optimization is not suitable for the change of the coal quality, so that the primary air rate, the secondary air rate, the burnout air rate, the oxygen amount control and the like of the boiler operation deviate from the optimal operation working condition. At present, the primary air rate, the secondary air rate and the burn-out air volume rate are mainly adjusted manually by operators according to experience. When coal quality deviation is large, frequent overtemperature of a water-cooled wall, slag bonding and burning of a nozzle of a combustor, increase of carbon content in fly ash and the like often occur. It is difficult to simultaneously ensure the improvement of the boiler efficiency and the control of the exhaust gas NOx. Therefore, an effective intelligent combustion optimization method is found to replace a manual operation mode with experience, real-time optimization under variable load and variable coal quality is realized, and the method has important significance for long-term energy conservation, emission reduction and safe operation of the coal-fired boiler.
The combustion fluctuation and load oscillation of the coal-fired boiler are the root causes, mainly because of the fluctuation of coal quality parameters. The change of the coal quality is difficult to be quickly judged only by manual operation, and correct combustion optimization adjustment is made; the traditional coordination control only judges the change of the coal quality heat value according to the main steam temperature/main steam pressure and other parameters after combustion, has combustion heat transfer delay and is one of the main reasons of large fluctuation of the main steam temperature/main steam pressure and large consumption of desuperheating water. Furthermore, conventional coordinated control has not optimized and controlled the small secondary dampers for each burner.
In order to solve the above problems, some intelligent combustion optimization methods using big data analysis, such as an intelligent combustion optimization method based on neural network modeling and optimizing using a genetic algorithm, have been developed. The method is mainly based on modeling training of boiler operation historical parameter samples, and an air distribution optimization model under adaptive load is established. The main problem of the model is that the input parameters of the model do not have accurate coal quality parameter information, and when the coal quality changes greatly, the correctness of the model cannot be guaranteed.
In order to solve the problem of measuring the coal quality parameters, some air distribution optimization methods based on coal quality soft measurement are provided, namely: and calculating the average heat value of the coal according to the enthalpy increase of steam generated after the quantitative coal is burnt, and calculating other industrial or element analysis components of the coal according to the ash content of the discharged smoke and gas analysis. And then simply adjusting the secondary air distribution of the boiler according to the coal quality of the soft side, such as taking a coal-fired power generating unit of a boiler with four tangential corners and four tangential walls as an example, and adopting the traditional balanced, waisted, regular pagoda and inverted pagoda air distribution modes. Firstly, the accuracy of coal quality soft measurement of the method is poorer than that of an actual measurement test result, and a second and simple air distribution guiding mode does not accurately measure the air quantity of a secondary air door, a perimeter air door, an OFA air door and a SOFA air door of each combustor, and only roughly adjusts the opening degree of each secondary small air door according to experience.
In order to solve the problem of refined air distribution, a functional relation G (G, k) between the secondary air volume G of the layer combustor, the pressure P of an air box and the opening k of an air door is obtained by fitting based on a cold aerodynamic field test. The method only performs fitting of the flow characteristics of the air door baffle in the cold state of the boiler, and cannot accurately meet measurement of secondary air volume of each nozzle in the hot state.
The methods for solving the problems have certain limitations, and the problems of boiler efficiency reduction and pollutant NOx emission increase caused by frequent amplitude modulation and variable coal quality of the conventional coal-fired power plant are difficult to systematically solve, so that a more scientific and reasonable improvement and optimization scheme for boiler combustion control is urgently needed to be developed.
The invention content is as follows:
the invention provides a combustion optimization method based on coal quality on-line monitoring, solves the problems of boiler efficiency reduction and pollutant NOx emission increase caused by frequent amplitude modulation and variable coal quality of the conventional coal-fired power plant, and comprehensively improves the economic benefit of the power plant.
The technical scheme adopted by the invention is as follows:
a combustion optimization method based on coal quality on-line monitoring comprises an intelligent combustion optimization system, a coal quality parameter acquisition system and coal quality on-line testing equipment, and is characterized in that: the intelligent combustion optimization system comprises a coal quality online monitoring module, a coal pulverizing system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen optimization module, the coal quality online monitoring module acquires coal quality parameter acquisition system information in real time, and correspondingly transmits the acquired information to the coal pulverizing system operation optimization module, the refined air distribution optimization module and the smoke exhaust oxygen optimization module, the coal pulverizing system operation optimization module is connected with coal mills controlled by a DCS control system of a power plant, the refined air distribution optimization module is connected with combustors controlled by the DCS control system of the power plant, the smoke exhaust oxygen optimization module is connected with a blower controlled by the DCS control system of the power plant, and the intelligent combustion optimization system realizes the intelligent combustion optimization method steps comprising:
1) the coal quality on-line monitoring module acquires coal quality parameter information through coal quality on-line chemical examination equipment, is connected with a coal conveying program control system of a power plant, acquires equipment operation state information, monitors and judges coal quality parameters conveyed to each coal mill, and conveys the judged coal quality parameters of each coal mill to a coal pulverizing system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen quantity optimization module;
2) the coal pulverizing system operation optimizing module is connected with a power plant DCS control system, the coal feeding amount, the primary total wind temperature of a mill inlet, the primary total wind rate of the mill inlet, the current of the coal mill and the primary wind temperature of a mill outlet of each coal mill are obtained in real time, the primary total wind rate of the coal mill inlet is sequentially optimized and calculated by using the coal quality parameters provided in the step 1), and the coal quality parameters are fed back to the DCS control system to control the opening degree of a primary air door of the coal mill inlet;
3) the refined air distribution optimization module is connected with a power plant DCS control system, acquires information of negative pressure of a hearth, total air volume of a secondary air main pipe at the side of A and B, total air pressure of the secondary air main pipe at the side of A and B, opening degree of each burner secondary air door, opening degree of a perimeter air door, opening degree of an OFA air door and opening degree of a SOFA air door in real time, performs optimization calculation on the opening degrees of each burner secondary air door, each perimeter air door, each OFA air door and each SOFA air door by using the coal quality parameters provided in the step 1), and feeds back the calculation results to the DCS to control;
4) the exhaust oxygen amount optimization module is connected with a power plant DCS control system, the main steam flow and exhaust oxygen amount information of the boiler are obtained in real time, the coal quality parameters provided in the step 1) are used for carrying out optimization calculation on the secondary total air amount of the boiler, and the secondary total air amount is fed back to the DCS to control the output of the blower.
Further, the coal quality parameters of the coal mills refer to a coal quality parameter data set of all the coal mills, and each coal mill corresponds to one group of coal quality parameters, including receiving a base volatile component Var, receiving a base fixed carbon Car, receiving a base ash Aar, receiving a base moisture Mar, receiving a base Sar, receiving a base Nar, and receiving a base low calorific value Qar.
Further, according to the method, the coal quality online monitoring module, the coal pulverizing system operation optimization module, the refined air distribution optimization module and the smoke exhaust oxygen amount optimization module are realized in the following modes:
1. coal quality on-line monitoring module
The coal quality industrial analysis data measured by the coal quality on-line testing equipment during coal feeding is collected in real time, the operation information of the main equipment is collected in real time from the coal conveying program control system, and the whole-process monitoring of coal feeding, belt conveying, process weighing, process crushing and coal plowing warehousing is carried out. The main collection equipment comprises: bucket wheel machine, coal conveying belt, metering scale, coal plough; the state information is: start/stop of the plant, real-time tonnage of the weigher, cumulative tonnage of the weigher, start/stop of the coal plough, start/stop of the coal belt. The coal quality on-line monitoring method utilizes the real-time acquisition of coal quality information, the real-time whole-process monitoring of the coal heading, and the calculation and analysis of the coal quality parameters in each coal mill before the coal is discharged out of the furnace.
2. Operation optimizing module of powder process system
The module is based on coal quality parameters, and the operation optimization module of the coal pulverizing system optimizes the primary total air volume of the inlet of each coal mill. The input parameters of the optimization algorithm are: the method comprises the following steps of (1) industrial analysis data of coal quality, coal feeding quantity, mill outlet air temperature and current of a coal mill; the output parameter is the optimal primary total air quantity of the grinding inlet. The optimization formula is as follows:
in the formula:
grinding the primary total air quantity at the inlet, wherein the metering unit is t/h;
coal feeding quantity, and the metering unit is t/h;
the coal quality moisture parameter is provided by a coal quality on-line monitoring module according to percentage values;
and the working current of the coal mill is measured in A.
Description of the formula:
formula (1): when the coal feeding amount is less than 10, judging that the grinding is stopped, and only keeping the cooling air amount for 20 t/h;
formula (2): the mill normally runs, and the total air quantity = coal supply quantity + 45;
formula (3): when the moisture of the processed coal is more than 18%, primary air quantity needs to be increased, and the risk of blockage and abrasion caused by insufficient drying output is prevented;
formula (4): when the mill running current is higher than 54A, the primary air quantity needs to be increased, and the pre-abrasion-proof disc stores too much coal to cause the risk of abrasion blockage.
3. Refined air distribution optimization module
Based on the coal quality parameters, the refined air distribution optimization module optimizes the opening degrees of air doors of the burner nozzles, the OFA air nozzles and the SOFA air nozzles. The method comprises the following steps and formulas in sequence:
step a): calculating theoretical air quantity through coal quality industrial analysis; the general calculation formula is as follows:
description of the parameters:
k: the following table can be looked up according to the type of the fuel and the value of the ashless dry-based volatile component of the fuel;
description of the formula:
the formulas (11) and (12) are derived from the technical and economic index calculation method of the DLT 904-2015 thermal power plant.
Step b): determining the actual air quantity of each burner nozzle, OFA air nozzle and SOFA air nozzle, performing numerical modeling on a boiler hot air duct, a large air box, each burner nozzle, OFA air nozzle, SOFA air nozzle and each small air door baffle by using a numerical simulation method, and simulating the air quantity of each burner nozzle, OFA air nozzle and SOFA air nozzle under different furnace air box differential pressures and different opening degrees of each small air door:
in the formula:
to
Generalizing coefficients for formulas, from a large numberFitting CFD numerical simulation data;
the air quantity of each secondary air nozzle, each peripheral air nozzle, each OFA air nozzle and each SOFA air nozzle is measured in t/h;
the pressure of a secondary hot air duct main pipe at the outlet of the air preheater on the first side and the second side is measured in Pa;
actually measuring pressure in a hearth with the measurement unit of Pa;
the difference value between the numerical simulation air duct inlet pressure and the hearth negative pressure; x is the opening degree of the valve and is expressed in percentage;calculating the sum of air quantity by all secondary air injection;
actually measuring the secondary total air volume, wherein the measuring unit is t/h;
a total air volume correction coefficient;
description of the formula:
the formula (13) is a flow characteristic formula of each air door baffle under different opening degrees and different pressure differences through fitting of a large amount of numerical simulation data. The fitting method is polynomial fitting.
Equation (14) is the total air volume correction. And (3) comparing the total air volume calculated by the formula (13) with the actually measured total air volume to obtain a correction coefficient K, and correcting the air volume of each nozzle by using the correction coefficient K.
Step c): the excess air ratio of each burner was calculated:
description of the formula:
equation (15) comes from boiler principle.
Step d): determining the optimal air excess coefficient of each combustor:
the optimal excess air coefficients of all the burners are confirmed by using a method of a field combustion adjustment test, and when the moisture of the coal for combustion is lower than 25%, the optimal excess air coefficients of the burners A, B, C, D, E, F are respectively 0.85, 0.68, 0.71 and 0.95; when the water content of the coal for combustion of the combustor is higher than 25%, the optimal excess air coefficient is 1; and the rest air quantity enters the hearth from the OFA air nozzle and the SOFA air nozzle.
Step e): determining the optimal opening of each burner secondary air door, each peripheral air door, each OFA air door and each SOFA air door:
determining the optimal opening of each combustor secondary air door and each peripheral air door: when the actual excess air coefficient of the combustor is lower than the optimal excess air coefficient, opening the corresponding secondary small air door, and when the actual excess air coefficient of the combustor is higher than the optimal excess air coefficient, closing the corresponding secondary small air door;
determining the optimal opening of the OFA air door and the SOFA air door: when the secondary air door and the perimeter air door are fully opened and still do not reach the optimal excess air coefficient, the OFA air door and the SOFA air door need to be closed down; when the opening degree of the secondary air door and the peripheral air door is 10 percent and is still higher than the optimal excess air coefficient, the OFA air door and the SOFA air door need to be opened greatly.
4. Smoke exhaust oxygen amount optimization module
Based on coal quality parameters, the secondary total air volume is optimized by the smoke exhaust oxygen optimization module, and the secondary total air volume is optimized according to the following steps and formulas: step A): an oxygen optimization adjustment test is carried out on three coal qualities of low, medium and high low calorific values by utilizing a field combustion adjustment test, and according to a load-optimal oxygen data change curve, the exhaust gas oxygen optimization formulas of the three coal qualities of low, medium and high low calorific values are summarized as follows:
in the formula:
the boiler load rate is 100 percent of full load;optimizing the exhaust oxygen amount; k1, k2 and k3 are respectively formula fitting coefficients, wherein the value range of k1 is 17.0 to 18.0; k2 ranges from 33.0 to 40.0; k3 ranges from 17.0 to 24.0;
according to the generalized exhaust gas oxygen optimization formulas of three coal qualities of low, medium and high low calorific values, a linear difference value correction method is utilized to deduce the exhaust gas oxygen optimization formula corrected by the low calorific value of the coal quality as follows:
in the formula:the boiler load rate is 100 percent of full load;
optimizing the exhaust oxygen amount;
the coal quality receiving base low-level heating value is provided by a coal quality on-line monitoring module; 5000. 7000 is a set constant, and an empirical value is obtained by fitting an optimized curve of the exhaust oxygen amount of the low, medium and high-low calorific values; k1, k2 and k3 are formula fitting coefficients respectively, wherein k1 ranges from 17.0 to 18.0, k2 ranges from 33.0 to 40.0, k3 ranges from 17.0 to 24.0, k4 ranges from 3.0 to 4.0, and k5 ranges from 3.0 to 4.0; .
Description of the formula:
in the formula (16)
Fitting a direct change relation between the optimal exhaust smoke oxygen amount and the load rate by using a polynomial;
in the formula (16)
And correcting the influence of the change of the coal value heat value on the optimal oxygen amount by adopting a linear interpolation correction method.
Step B): the secondary total air volume is optimized, and the output of the air feeder is connected and controlled:
when the actually measured smoke exhaust oxygen value is lower than the optimal smoke exhaust oxygen value, the secondary total air quantity needs to be increased, and the output of the air feeder is improved by connecting and controlling the air feeder; when the actually measured smoke exhaust oxygen value is higher than the optimal smoke exhaust oxygen value, the secondary total air quantity needs to be reduced, and the output of the air feeder is reduced by connecting and controlling the air feeder.
According to the scheme, the method comprises the steps of firstly providing a real-time coal quality parameter acquisition method for each coal mill, and providing a real-time air volume calculation method for the air volume of each burner nozzle, OFA air nozzle and SOFA air nozzle; based on the coal quality parameters, the operation optimization module of the coal pulverizing system optimizes the primary total air volume of the inlet of each coal mill; based on the coal quality parameters, a refined air distribution optimization module optimizes the opening degrees of air doors of each combustor nozzle, OFA air nozzles and SOFA air nozzles; based on the coal quality parameters, the smoke exhaust oxygen quantity optimization module optimizes the secondary total air quantity. The invention optimizes and controls the air distribution of the coal mill, the burner and the boiler main pipe through the intelligent circulation of the system, thereby achieving the comprehensive optimization of the boiler combustion.
The invention has the following beneficial effects:
1. the coal quality on-line monitoring module: at present, the real-time coal quality parameter measuring equipment and the method are not popularized in coal-fired power plants, and the safety hazard exists mainly because the existing hardware measuring equipment is expensive, and part of on-line measuring instruments have radioactive sources. However, the demand of coal quality on-line measurement exists all the time, and the demand is stronger and stronger as the blending burning intensity of the coal blending of the power plant is increased. In recent years, with the continuous improvement of the digitalization and informatization construction of power plants, the coal quality online monitoring module judges coal parameters corresponding to coal mills by utilizing the real-time analysis of coal quality testing parameters and equipment operation information, thereby effectively solving the problem of difficult real-time measurement of the coal quality of the coal-fired power plants and providing key coal quality parameters for the optimized operation of a coal pulverizing system and a coal-fired boiler.
2. The operation optimization module of the powder process system: the operation optimization module of the coal pulverizing system is optimized based on the primary total air volume of the coal quality parameters, and has the innovation point that the Mar parameters of the coal quality received base water are added into the optimized input parameters. The primary total air volume of the existing coal pulverizing system is optimized only according to the safe and healthy state of a coal mill, the influence of the change of coal quality and moisture on the total air volume is not considered, and the situations that the primary total air volume is insufficient when the coal with high moisture content is used and the primary total air volume is too much when the coal with low moisture content is used often occur. The primary total air volume of each coal mill is reasonably corrected according to the change of the coal quality, and the primary total air volume can be controlled in real time while the safe operation of the coal mill is ensured. The temperature rise of the exhaust gas and the efficiency reduction of the boiler under the condition of changing the coal quality are effectively controlled.
3. Refined air distribution optimization module: the invention has the innovation point that the excess air coefficient of each combustor can be calculated in real time according to the coal quality parameters of each coal mill and the secondary air volume data of each combustor nozzle. The excess air coefficient can measure accurately whether the secondary air supplement amount is reasonable or not when each burner is used for burning different coal quality, so that fine adjustment of the opening degree of each secondary small air door can be judged. At present, aiming at the optimization of secondary air distribution of a coal-fired boiler, a plurality of preset coal qualities are tested mainly according to an adjustment test, and finally a relatively good opening degree combination guidance optimization is obtained. The method can only be operated by manual experience, but is not suitable for various coal quality change conditions, and the air distribution adjustment is usually lagged due to the fact that the change of the coal quality cannot be predicted. The invention is based on the air distribution optimization of coal quality and air quantity real-time measurement, and can adjust each secondary small air door in time according to the change of the coal quality. The secondary air door air distribution optimization can effectively inhibit pollutant NOx generation, timely adjust the NOx standard exceeding risk and reduce the operation cost of environmental protection and emission reduction.
4. An exhaust oxygen amount optimization module: the traditional optimization control of the exhaust smoke oxygen amount is to carry out corresponding optimization adjustment according to the change of load, and the change of coal quality is not considered, so that the conditions that the exhaust smoke oxygen amount is higher when high-quality coal is combusted and the exhaust smoke oxygen amount is lower when low-quality coal is combusted often occur. According to the invention, because the coal quality parameter information is acquired in real time and the coal quality parameter correction term is added into the smoke exhaust oxygen optimization calculation formula, the problem of coal quality imbalance of the traditional smoke exhaust oxygen optimization control is effectively solved. The reasonable optimization of the oxygen content of the discharged smoke can effectively reduce the loss of the discharged smoke and improve the boiler efficiency.
Description of the drawings:
FIG. 1 is a schematic structural diagram of a combustion optimization system for on-line monitoring of coal quality.
FIG. 2 is a simulation modeling diagram of soft side measurement of the air quantity of the refined air distribution optimization module according to the present invention.
FIG. 3 is a graph and formula of the optimum flue gas oxygen content for the present invention.
The specific implementation mode is as follows:
the invention will be further described with reference to the accompanying drawings.
The invention relates to a combustion optimization method based on coal quality on-line monitoring, which comprises an intelligent combustion optimization system and a coal quality parameter acquisition system, the intelligent combustion optimization system comprises a coal quality online monitoring module, a coal pulverizing system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen quantity optimization module, wherein the coal quality online monitoring module acquires the information of a coal quality parameter acquisition system in real time, and correspondingly transmitting the acquired information to a powder making system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen quantity optimization module, the coal pulverizer of powder process system operation optimization module connection power plant DCS control system control each, each combustor of power plant DCS control system control is connected to the air distribution optimization module that becomes more meticulous, and the forced draught blower of the control of power plant DCS control system is connected to the oxygen content of discharging fume optimization module, intelligent combustion optimization system realizes that intelligent combustion optimization method step includes:
1) the coal quality on-line monitoring module acquires coal quality parameter information through coal quality on-line chemical examination equipment, is connected with a coal conveying program control system of a power plant, acquires equipment operation state information, monitors and judges coal quality parameters conveyed to each coal mill, and conveys the judged coal quality parameters of each coal mill to a coal pulverizing system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen quantity optimization module;
2) the coal pulverizing system operation optimizing module is connected with a power plant DCS control system, the coal feeding amount, the primary total wind temperature of a mill inlet, the primary total wind rate of the mill inlet, the current of the coal mill and the primary wind temperature of a mill outlet of each coal mill are obtained in real time, the primary total wind rate of the coal mill inlet is sequentially optimized and calculated by using the coal quality parameters provided in the step 1), and the coal quality parameters are fed back to the DCS control system to control the opening degree of a primary air door of the coal mill inlet;
3) the refined air distribution optimization module is connected with a power plant DCS control system, acquires information of negative pressure of a hearth, total air volume of a secondary air main pipe at the side of A and B, total air pressure of the secondary air main pipe at the side of A and B, opening degree of each burner secondary air door, opening degree of a perimeter air door, opening degree of an OFA air door and opening degree of a SOFA air door in real time, performs optimization calculation on the opening degrees of each burner secondary air door, each perimeter air door, each OFA air door and each SOFA air door by using the coal quality parameters provided in the step 1), and feeds back the calculation results to the DCS to control;
4) the exhaust oxygen amount optimization module is connected with a power plant DCS control system, the main steam flow and exhaust oxygen amount information of the boiler are obtained in real time, the coal quality parameters provided in the step 1) are used for carrying out optimization calculation on the secondary total air amount of the boiler, and the secondary total air amount is fed back to the DCS to control the output of the blower.
Further, the coal quality parameters of the coal mills refer to a coal quality parameter data set of all the coal mills, and each coal mill corresponds to one coal quality parameter, and the coal quality parameters include a data set of received base volatile components Var, received base fixed carbon Car, received base ash Aar, received base moisture Mar, received base Sar, received base Nar and received base low calorific value Qar.
Further, according to the method, the coal quality online monitoring module, the coal pulverizing system operation optimization module, the refined air distribution optimization module and the smoke exhaust oxygen amount optimization module are realized in the following modes:
1. coal quality on-line monitoring module
The coal quality industrial analysis data measured by the coal quality on-line testing equipment during coal feeding is collected in real time, the operation information of the main equipment is collected in real time from the coal conveying program control system, and the whole-process monitoring of coal feeding, belt conveying, process weighing, process crushing and coal plowing warehousing is carried out. The main collection equipment comprises: bucket wheel machine, coal conveying belt, metering scale, coal plough; the state information is: start/stop of the plant, real-time tonnage of the weigher, cumulative tonnage of the weigher, start/stop of the coal plough, start/stop of the coal belt. The coal quality on-line monitoring method utilizes the real-time acquisition of coal quality information, the real-time whole-process monitoring of the coal heading, and the calculation and analysis of the coal quality parameters in each coal mill before the coal is discharged out of the furnace.
2. Operation optimizing module of powder process system
The module is based on coal quality parameters, and the operation optimization module of the coal pulverizing system optimizes the primary total air volume of the inlet of each coal mill. The input parameters of the optimization algorithm are: the method comprises the following steps of (1) industrial analysis data of coal quality, coal feeding quantity, mill outlet air temperature and current of a coal mill; the output parameter is the optimal primary total air quantity of the grinding inlet. The optimization formula is as follows:
in the formula:
grinding the primary total air quantity at the inlet, wherein the metering unit is t/h;
coal feeding quantity, and the metering unit is t/h;
the coal quality moisture parameter is provided by a coal quality on-line monitoring module according to percentage values;
and the working current of the coal mill is measured in A.
Description of the formula:
formula (1): when the coal feeding amount is less than 10, judging that the grinding is stopped, and only keeping the cooling air amount for 20 t/h;
formula (2): the mill normally runs, and the total air quantity = coal supply quantity + 45;
formula (3): when the moisture of the processed coal is more than 18%, primary air quantity needs to be increased, and the risk of blockage and abrasion caused by insufficient drying output is prevented;
formula (4): when the mill running current is higher than 54A, the primary air quantity needs to be increased, and the pre-abrasion-proof disc stores too much coal to cause the risk of abrasion blockage.
3. Refined air distribution optimization module
Based on the coal quality parameters, the refined air distribution optimization module optimizes the opening degrees of air doors of the burner nozzles, the OFA air nozzles and the SOFA air nozzles. The method comprises the following steps and formulas in sequence:
step a): calculating theoretical air quantity through coal quality industrial analysis;
description of the parameters:
k: the following table can be looked up according to the type of the fuel and the value of the ashless dry-based volatile component of the fuel;
description of the formula:
the formulas (11) and (12) are derived from the technical and economic index calculation method of the DLT 904-2015 thermal power plant.
Step b): determining the actual air quantity of each burner nozzle, OFA air nozzle and SOFA air nozzle, performing numerical modeling on a boiler hot air duct, a large air box, each burner nozzle, OFA air nozzle, SOFA air nozzle and each small air door baffle by using a numerical simulation method, and simulating the air quantity of each burner nozzle, OFA air nozzle and SOFA air nozzle under different furnace air box differential pressures and different opening degrees of each small air door:
in the formula:
to formula induction coefficient, fitting from a large amount of CFD numerical simulation data;
the air quantity of each secondary air nozzle, each peripheral air nozzle, each OFA air nozzle and each SOFA air nozzle is measured in t/h;
the pressure of a secondary hot air duct main pipe at the outlet of the air preheater on the first side and the second side is measured in Pa;
actually measuring pressure in a hearth with the measurement unit of Pa;the difference value between the numerical simulation air duct inlet pressure and the hearth negative pressure; x is the opening degree of the valve and is expressed in percentage;
calculating the sum of air quantity by all secondary air injection;
actually measuring the secondary total air volume, wherein the measuring unit is t/h;: a total air volume correction coefficient;
description of the formula:
the formula (13) is a flow characteristic formula of each air door baffle under different opening degrees and different pressure differences through fitting of a large amount of numerical simulation data. The fitting method is polynomial fitting.
Equation (14) is the total air volume correction. And (3) comparing the total air volume calculated by the formula (13) with the actually measured total air volume to obtain a correction coefficient K, and correcting the air volume of each nozzle by using the correction coefficient K.
Step c): the excess air ratio of each burner was calculated:
description of the formula:
equation (15) comes from boiler principle.
Step d): determining the optimal air excess coefficient of each combustor:
the optimal excess air coefficients of all the burners are confirmed by using a method of a field combustion adjustment test, and when the moisture of the coal for combustion is lower than 25%, the optimal excess air coefficients of the burners A, B, C, D, E, F are respectively 0.85, 0.68, 0.71 and 0.95; when the water content of the coal for combustion of the combustor is higher than 25%, the optimal excess air coefficient is 1; and the rest air quantity enters the hearth from the OFA air nozzle and the SOFA air nozzle.
Step e): determining the optimal opening of each burner secondary air door, each peripheral air door, each OFA air door and each SOFA air door:
determining the optimal opening of each combustor secondary air door and each peripheral air door: when the actual excess air coefficient of the combustor is lower than the optimal excess air coefficient, opening the corresponding secondary small air door, and when the actual excess air coefficient of the combustor is higher than the optimal excess air coefficient, closing the corresponding secondary small air door;
determining the optimal opening of the OFA air door and the SOFA air door: when the secondary air door and the perimeter air door are fully opened and still do not reach the optimal excess air coefficient, the OFA air door and the SOFA air door need to be closed down; when the opening degree of the secondary air door and the peripheral air door is 10 percent and is still higher than the optimal excess air coefficient, the OFA air door and the SOFA air door need to be opened greatly.
4. Smoke exhaust oxygen amount optimization module
Based on coal quality parameters, the secondary total air volume is optimized by the smoke exhaust oxygen optimization module, and the secondary total air volume is optimized according to the following steps and formulas:
step A): when the average low calorific value for combustion is 4500kcal/kg coal quality, performing oxygen adjustment test under the load of 50%, 60%, 70%, 80%, 90% and 100% of the boiler, and determining an optimal smoke exhaust oxygen curve and formula; when the average low calorific value for combustion is 5000kcal/kg of coal quality, performing oxygen adjustment tests under the loads of 50%, 60%, 70%, 80%, 90% and 100% of boilers to determine an optimal smoke exhaust oxygen curve and formula; when the average lower calorific value for combustion is 5500kcal/kg of coal quality, oxygen adjustment tests are carried out under the load of 50%, 60%, 70%, 80%, 90% and 100% of the boiler, an optimal flue gas oxygen quantity curve and formula are determined, the optimal flue gas oxygen quantity curve and formula are shown in figure 3, and the optimization formulas of the flue gas oxygen quantities of three coal qualities of 4500kcal/kg, 5000kcal/kg and 5500kcal/kg of lower calorific value are summarized as follows:
in the formula:
the boiler load rate is 100 percent of full load;
optimizing the exhaust oxygen amount;
the coal quality receiving base low-level heating value is provided by a coal quality on-line monitoring module;
the invention is used as a correction term of a linear interpolation correction method to correct the influence of the change of the coal value heat value on the optimal oxygen amount, the low, middle and low heat values adopted by the formula derived by the invention are 4500, 5000 and 5500 respectively, the unit is kcal/kg, the correction term is based on the middle and low heat value, and when the low heat value Qar of the actual coal is 5000kcal/kg, the correction term is used as a reference
0, when the lower calorific value Qar of the coal is higher than 5000kcal/kg, this correction term
Negative, when the lower calorific value Qar of coal is less than 5000kcal/kg, this correction term
For positive values, 7000 in this correction term is a fixed scaling factor; 17.857 is the preferred value of k1 in the formula, 36.729 is the preferred value of k2 in the formula, 20.914 is the preferred value of k3 in the formula, 3.6 is the preferred value of k4 in the formula, and 3.8 is the preferred value of k5 in the formula.
Description of the formula:
in the formula (16)
Polynomial fitting for optimal exhaust smoke oxygen content and loadDirect rate change relationship;
in the formula (16)
And correcting the influence of the change of the coal value heat value on the optimal oxygen amount by adopting a linear interpolation correction method.
In fig. 3, point A, B, C shows three cases where the formula is applied, where A, B, C shows the results of calculation using the formula when the load factor is 65% and the low-grade calorific values are 5000kcal/kg, 3000kcal/kg, and 6000kcal/kg, respectively, and: the recommended exhaust gas oxygen amount of the point A is 4.58%, the recommended exhaust gas oxygen amount of the point B is 5.0%, and the recommended exhaust gas oxygen amount of the point C is 4.37%, wherein the correction term of the exhaust gas oxygen amount of the point A is 0, the correction term of the exhaust gas oxygen amount of the point B is 0.417, and the correction term of the exhaust gas oxygen amount of the point C is-0.209.
Step B): the secondary total air volume is optimized, and the output of the air feeder is connected and controlled:
when the actually measured smoke exhaust oxygen value is lower than the optimal smoke exhaust oxygen value, the secondary total air quantity needs to be increased, and the output of the air feeder is improved by connecting and controlling the air feeder; when the actually measured smoke exhaust oxygen value is higher than the optimal smoke exhaust oxygen value, the secondary total air quantity needs to be reduced, and the output of the air feeder is reduced by connecting and controlling the air feeder.
According to the scheme, the method comprises the steps of firstly providing a real-time coal quality parameter acquisition method for each coal mill, and providing a real-time air volume calculation method for the air volume of each burner nozzle, OFA air nozzle and SOFA air nozzle; based on the coal quality parameters, the operation optimization module of the coal pulverizing system optimizes the primary total air volume of the inlet of each coal mill; based on the coal quality parameters, a refined air distribution optimization module optimizes the opening degrees of air doors of each combustor nozzle, OFA air nozzles and SOFA air nozzles; based on the coal quality parameters, the smoke exhaust oxygen quantity optimization module optimizes the secondary total air quantity. The invention optimizes and controls the air distribution of the coal mill, the burner and the boiler main pipe through the intelligent circulation of the system, thereby achieving the comprehensive optimization of the boiler combustion.
The intelligent combustion optimization method based on the coal quality on-line monitoring is explained in detail below.
1. Coal quality on-line monitoring module
The attached figure 1 illustrates the coal quality on-line monitoring process, namely: the digital fuel server acquires the running signal of the coal conveying program control equipment in real time, acquires the industrial analysis data information of coal quality test in real time, and acquires the industrial analysis data of the coal quality entering the coal mill in real time through calculation.
2. Operation optimizing module of powder process system
And determining the optimal primary total air volume of the coal mill inlet through a large number of operation optimization tests of the coal pulverizing system. Note that the test method is as follows:
test one: the air-coal ratio adjustment test was performed on bituminous coal with 12% moisture in the industrial analysis:
experiments confirm that when the total moisture of the coal is lower than 18%, the drying output of the coal mill cannot be reduced, namely the air temperature at the outlet of the coal mill can be maintained to be higher than 75 ℃.
In the first test, the coal type is used with 12% of total water, and the drying output of the coal mill can be ensured.
The test contents are as follows: the tests were carried out at total air volumes of 80t/h, 85t/h, 90t/h and 95t/h, respectively, at coal feeding volumes of 40t/h and 45t/h, respectively.
Test data:
according to the judgment of test data, when the coal feeding amount is 45t/h and the total air volume is 80t/h, the current of the coal mill continuously rises, the primary air speed continuously falls, and the risk of blocking the coal mill exists, so that the current of the coal mill which safely operates is 54A. And (3) determining the optimal primary total air quantity to be 90t/h when the coal feeding quantity is 45t/h through comprehensive test data. The optimal primary total air volume is 85t/h when the coal amount is 40 t/h.
And (2) test II: the air-coal ratio adjustment test is carried out on lignite with 40% moisture in industrial analysis:
when the total water content of the coal exceeds 18%, the drying output of the coal mill begins to be reduced. The mill exit temperature was initially below 75 ℃. In order to ensure the outlet of the coal mill, the primary air quantity is increased.
Test data:
according to the judgment of test data, the coal feeding amount of 40t/h and the total air volume of 95t/h are carried out on coal types with 40% of total water, the air temperature at the outlet of the coal mill is continuously reduced, and the risk of pipe blocking and grinding is caused. And (3) determining the optimal primary total air quantity to be 105t/h when the coal feeding quantity is 40t/h through comprehensive test data. The optimal primary total air volume is 100t/h when the coal amount is 35 t/h.
And finally determining a key formula of an optimization module of the coal pulverizing system and a primary total air volume optimization formula of an inlet of the coal mill.
3. Refined air distribution optimization module
The boiler hot secondary air duct, the large air box, the burner and the secondary small air door are subjected to numerical modeling, a three-dimensional modeling diagram of the hot secondary air duct, the large air box, the burner and the secondary small air door of a certain power plant is shown in figure 2, P1 is model inlet pressure, P2 is hearth negative pressure, and secondary air quantities of burner nozzles and burnout air nozzles under different air duct-hearth differential pressures and different opening degrees of the small air doors are simulated. And fitting a secondary air volume calculation formula of each air door by utilizing a polynomial after a large amount of simulation sample data is formed.
Description of the parameters:
a total air volume correction coefficient;
the correction coefficient can eliminate the soft measurement absolute air quantity deviation caused by the change of the internal structure of the air duct, partial blockage and the like, and ensure that the soft measurement total air quantity is equal to the actual measurement total air quantity.
On the basis of the soft measurement of the air quantity, the theoretical air quantity is calculated according to the coal quality parameters of the nozzles of each burner, and the excess air coefficient around the nozzles of each pulverized coal burner can be calculated and displayed in real time. And determining the optimal excess air coefficient of each combustor nozzle under different loads by utilizing a combustion adjustment performance test.
And finally, adjusting the opening degree of each secondary small air door by utilizing the deviation of the actual excess air coefficient and the optimal excess air coefficient.
4. Smoke exhaust oxygen amount optimization module
Through a field combustion adjustment test, the boiler performance test is carried out by respectively using the calorific values of 4500kcal/kg, 5000kcal/kg and 5500kal/kg and adjusting the oxygen content of the exhaust smoke under different loads to determine the boiler efficiency. And fitting an optimal oxygen amount calculation formula under the conditions of variable coal quality and variable load by utilizing the efficiency of the boiler.
5. Intelligent combustion optimization implementation method
And the intelligent combustion optimization industrial personal computer acquires boiler combustion operation parameters from the DCS/SIS and coal quality data from the coal quality on-line measurement system.
The intelligent combustion optimization server integrates a powder preparation system operation optimization algorithm, a refined air distribution optimization algorithm and a smoke and oxygen content optimization algorithm, carries out real-time calculation processing on the obtained boiler combustion operation parameters and the obtained coal quality parameters, and provides optimization guidance suggestions
The foregoing is only a preferred embodiment of this invention and it should be noted that modifications can be made by those skilled in the art without departing from the principle of the invention and these modifications should also be considered as the protection scope of the invention.
Claims (8)
1. A combustion optimization method based on coal quality on-line monitoring is based on an intelligent combustion optimization system with a coal quality on-line monitoring module, a coal pulverizing system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen quantity optimization module, and is characterized in that:
1) the coal quality on-line monitoring module acquires coal quality parameter information through coal quality on-line chemical examination equipment, is connected with a coal conveying program control system of a power plant, acquires equipment operation state information, monitors and judges coal quality parameters conveyed to each coal mill, and conveys the judged coal quality parameters of each coal mill to a coal pulverizing system operation optimization module, a refined air distribution optimization module and a smoke exhaust oxygen quantity optimization module;
2) the coal pulverizing system operation optimizing module is connected with a power plant DCS control system, the coal feeding amount, the primary total wind temperature of a mill inlet, the primary total wind rate of the mill inlet, the current of the coal mill and the primary wind temperature of a mill outlet of each coal mill are obtained in real time, the primary total wind rate of the coal mill inlet is sequentially optimized and calculated by using the coal quality parameters provided in the step 1), and the coal quality parameters are fed back to the DCS control system to control the opening degree of a primary air door of the coal mill inlet;
3) the refined air distribution optimization module is connected with a power plant DCS control system, acquires information of negative pressure of a hearth, total air volume of a secondary air main pipe at the side of A and B, total air pressure of the secondary air main pipe at the side of A and B, opening degree of each burner secondary air door, opening degree of a perimeter air door, opening degree of an OFA air door and opening degree of a SOFA air door in real time, performs optimization calculation on the opening degrees of each burner secondary air door, each perimeter air door, each OFA air door and each SOFA air door by using the coal quality parameters provided in the step 1), and feeds back the calculation results to the DCS to control;
4) the exhaust oxygen amount optimization module is connected with a power plant DCS control system, the main steam flow and exhaust oxygen amount information of the boiler are obtained in real time, the coal quality parameters provided in the step 1) are used for carrying out optimization calculation on the secondary total air amount of the boiler, and the secondary total air amount is fed back to the DCS to control the output of the blower.
2. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: the coal quality parameters of the coal mills refer to a coal quality parameter data set of all the coal mills, and each coal mill corresponds to one group of coal quality parameters, including receiving base volatile components Var, receiving base fixed carbon Car, receiving base ash Aar, receiving base moisture Mar, receiving base Sar, receiving base Nar and receiving base low-grade calorific value Qar.
3. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: the coal quality on-line monitoring module adopts a method of monitoring running information of coal quality chemical examination equipment and coal conveying program control equipment in real time to judge the corresponding coal quality parameters reaching each coal mill.
4. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: optimizing the primary total air volume of the coal mill inlet in the step 2) according to the following formula in sequence:
in the formula:grinding the primary total air quantity at the inlet, wherein the metering unit is t/h;
coal feeding quantity, and the metering unit is t/h;
: the coal quality moisture parameter is provided by a coal quality on-line monitoring module according to percentage values;and the working current of the coal mill is measured in A.
5. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: the fine air distribution optimization in the step 3) is sequentially optimized by the following steps:
step a): calculating theoretical air quantity through coal quality industrial analysis;
step b): determining the actual air quantity of each burner nozzle, OFA air nozzle and SOFA air nozzle, performing numerical modeling on a boiler hot air duct, a large air box, each burner nozzle, OFA air nozzle, SOFA air nozzle and each small air door baffle by using a numerical simulation method, and simulating the air quantity of each burner nozzle, OFA air nozzle and SOFA air nozzle under different furnace air box differential pressures and different opening degrees of each small air door:
in the formula:
to
A formula induction coefficient, fitted from a large amount of CFD numerical simulation data;
the air quantity of each secondary air nozzle, each peripheral air nozzle, each OFA air nozzle and each SOFA air nozzle is measured in t/h;
: the pressure of a secondary hot air duct main pipe at the outlet of the air preheater on the first side and the second side is measured in Pa;
actually measuring pressure in a hearth with the measurement unit of Pa;the difference value between the numerical simulation air duct inlet pressure and the hearth negative pressure; x is the opening degree of the valve and is expressed in percentage;calculating the sum of air quantity by all secondary air injection;
actually measuring the secondary total air volume, wherein the measuring unit is t/h;: a total air volume correction coefficient;
step c): the excess air ratio of each burner was calculated:
step d): determining the optimal air excess coefficient of each combustor:
carrying out a combustion adjustment test under the condition of changing the excess air coefficient by using the calculated excess air coefficient of each combustor, and determining the optimal excess air coefficient of each combustor under the condition of combusting different coals by using a field test method;
step e): determining the optimal opening of each burner secondary air door, each peripheral air door, each OFA air door and each SOFA air door:
determining the optimal opening of each combustor secondary air door and each peripheral air door: when the actual excess air coefficient of the combustor is lower than the optimal excess air coefficient, opening the corresponding secondary small air door, and when the actual excess air coefficient of the combustor is higher than the optimal excess air coefficient, closing the corresponding secondary small air door;
determining the optimal opening of the OFA air door and the SOFA air door: when the secondary air door and the perimeter air door are fully opened and still do not reach the optimal excess air coefficient, the OFA air door and the SOFA air door need to be closed down; when the opening degree of the secondary air door and the peripheral air door is 10 percent and is still higher than the optimal excess air coefficient, the OFA air door and the SOFA air door need to be opened greatly.
6. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: optimizing the exhaust oxygen amount in the step 4) by sequentially optimizing the following steps and formulas:
step A): an oxygen optimization adjustment test is carried out on three coal qualities of low, medium and high low calorific values by utilizing a field combustion adjustment test, and according to a load-optimal oxygen data change curve, the exhaust gas oxygen optimization formulas of the three coal qualities of low, medium and high low calorific values are summarized as follows:
in the formula:
: the boiler load rate is 100 percent of full load;optimizing the exhaust oxygen amount; k1, k2 and k3 are respectively formula fitting systemsNumber, wherein k1 ranges from 17.0 to 18.0; k2 ranges from 33.0 to 40.0; k3 ranges from 17.0 to 24.0;
according to the generalized exhaust gas oxygen optimization formulas of three coal qualities of low, medium and high low calorific values, a linear difference value correction method is utilized to deduce the exhaust gas oxygen optimization formula corrected by the low calorific value of the coal quality as follows:
in the formula:
the boiler load rate is 100 percent of full load;
optimizing the exhaust oxygen amount;
the coal quality received basic low-level calorific value is provided by a coal quality on-line monitoring module, 5000 and 7000 are set constants, and experimental values are obtained by fitting an optimized curve of the exhaust gas oxygen amount of the low, medium and high low-level calorific values; k1, k2 and k3 respectively form fitting coefficients, wherein the value range of k1 is 17.0 to 18.0, the value range of k2 is 33.0 to 40.0, the value range of k3 is 17.0 to 24.0, the value range of k4 is 3.0 to 4.0, and the value range of k5 is 3.0 to 4.0;
step B): the secondary total air volume is optimized, and the output of the air feeder is connected and controlled:
when the actually measured smoke exhaust oxygen value is lower than the optimal smoke exhaust oxygen value, the secondary total air quantity needs to be increased, and the output of the air feeder is improved by connecting and controlling the air feeder; when the actually measured smoke exhaust oxygen value is higher than the optimal smoke exhaust oxygen value, the secondary total air quantity needs to be reduced, and the output of the air feeder is reduced by connecting and controlling the air feeder.
7. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: the intelligent combustion optimization system is arranged on an industrial personal computer, and the industrial personal computer is connected with the coal quality online testing equipment and is used for acquiring coal quality parameter information; the industrial personal computer is connected with the coal conveying program control system and is used for acquiring the running state information of the equipment; the industrial personal computer is connected with the power plant DCS control system and is used for acquiring boiler combustion operation parameter information; the industrial personal computer is connected with the DCS control system of the power plant, the optimal primary total air volume of the inlet of the coal mill, the optimal opening degree of each burner secondary air door, each perimeter air door, each OFA air door and each SOFA air door and the optimal exhaust oxygen volume value of the boiler are sent to the DCS control system, and the DCS control system carries out boiler combustion real-time optimization control by utilizing the optimization parameters.
8. The combustion optimization method based on the coal quality online monitoring as claimed in claim 1, characterized in that: coal quality on-line monitoring module among the intelligent combustion optimization system acquires coal quality parameter acquisition system information in real time to correspond the information of acquireing and carry for powder process system operation optimization module, the air distribution optimization module that becomes more meticulous and the oxygen volume optimization module of discharging fume, each coal pulverizer of power plant DCS control system control is connected to powder process system operation optimization module, and each combustor of power plant DCS control system control is connected to the air distribution optimization module that becomes more meticulous, and the forced draught blower of power plant DCS control system control is connected to the oxygen volume optimization module of discharging fume.
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