System and method for calculating and testing cleaning factor of convection heating surface of boiler

Abstract

The embodiment of the invention relates to the field of coal-fired power generation, and provides a boiler convection heating surface cleaning factor calculation and test system and method, and the system comprises the steps: employing a configuration function block of a production control system through employing the existing thermotechnical measurement point of a coal-fired power generation unit, and according to the design parameters and historical operation characteristic parameters of the coal-fired power generation unit, calculating a boiler convection heating surface cleaning factor; a real-time calculation loop is embedded in a production control system, working conditions are automatically screened when the coal-fired power generation unit continuously operates, typical test working condition signals of the coal-fired power generation unit and long-acting cleaning factor signals of a certain convection heating surface of a boiler are output, and the purpose that in the fully-closed production control system, the real-time calculation loop can be automatically calculated is achieved. On-line monitoring of the boiler convection heating surface cleaning factor can be realized without third-party auxiliary software, a good guiding effect on safe and stable operation and adjustment control of the boiler convection heating surface is achieved, and the investment cost of thermotechnical measuring points, third-party monitoring and other software and hardware is greatly reduced. And autonomous optimization and maintenance can be carried out in time according to working condition changes, so that the maintenance cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of coal-fired power generation, and in particular to a calculation and test system and method for a cleanliness factor of a boiler convection heating surface. Background Art

[0002] The ash and slagging phenomenon on the convection heating surface of the boiler will reduce the heat transfer capacity of the convection heating surface, induce local overheating, tube burst, uneven heat transfer and other problems on the convection heating surface, which will seriously affect the safe and economic operation of coal-fired power generation boilers. Especially in the context of variable fuel and flexible peak load regulation in power plants, the ash and slagging problem on the convection heating surface is more prominent, which makes the monitoring and control of the cleanliness of the convection heating surface particularly important.

[0003] At present, the degree of fouling and slagging of the convection heating surface of the boiler is usually characterized by the convection heating surface cleanliness factor. By monitoring and calculating the parameters such as the inlet and outlet smoke temperature and steam temperature of the convection heating surface, the corresponding intelligent algorithm is developed based on historical parameters and machine learning, and finally the online monitoring of the convection heating surface cleanliness is realized through third-party auxiliary software. However, this method not only has high software and hardware investment costs, but also has weak adaptability to changes in operating conditions, and its monitoring accuracy is highly dependent on the number of measurement points, and the maintenance cost is high.

[0004] In the prior art, parameter monitoring of boiler equipment is usually focused on safe and stable production, and the relevant thermal measurement points are not perfect. At the same time, in daily production, with the changes in fuel sources and power generation strategies, the operating conditions of coal-fired power generation units change frequently. Therefore, how to use the existing production control system measurement points and coal-fired conditions of coal-fired power generation unit boilers (hereinafter referred to as boilers) to develop an online monitoring method for the cleanliness of boiler-related convection heating surfaces, and to be able to adaptively adjust the monitoring model according to changes in the operating boundaries of boiler equipment, so as to better guide production operations and improve the safety and economy of power plant boiler operations, has become an urgent problem to be solved in this field. Summary of the invention

[0005] The present disclosure aims to solve at least one of the problems existing in the prior art and provides a calculation and test system and method for the cleanliness factor of a boiler convection heating surface.

[0006] In one aspect of the present disclosure, a calculation and test system for a cleanliness factor of a convection heating surface of a boiler is provided, the calculation and test system comprising: A fuel characteristic combination parameter module is used to activate a target fuel combination code and its corresponding fuel characteristic parameter data; An initial calculation loop, for generating an initial cleaning factor of a convective heating surface corresponding to the target fuel combination code based on the fuel characteristic parameter data and the combustion parameter data corresponding to the target fuel combination code; The secondary iterative calculation loop is used to generate secondary cleaning factor data of different operating condition intervals corresponding to the target fuel combination code based on different electric power thresholds and soot blowing system states of the coal-fired power generation unit and according to the initial cleaning factor of the convection heating surface, so that when the coal-fired power generation unit is running in real time, only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated, and the branch data of other operating condition intervals are kept statically latched; The test identification module is used to generate multi-fuel test cleaning factor data according to the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within a preset test time period and the secondary cleaning factor data in different operating condition intervals, and determine the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the convective heating surface under the typical operating condition based on the multi-fuel test cleaning factor data.

[0007] Optionally, the fuel characteristic combination parameter module is further used for: Based on the fuel characteristic parameters and the fuel combination code, multiplying the fuel characteristic parameter data set of different fuel combination codes in the production control system within a first preset time period; and, The fuel characteristic parameter data of the production control system that exceeds the first preset time period is cleared.

[0008] Optionally, the computing and testing system further comprises: The combustion characteristic combination function module is used to introduce the real-time measurement data of the head end, tail end and middle of the whole convection heating surface of the boiler according to the physical characteristics of the series convection heating surface of the boiler, and generate verification data through the differential fitting verification loop corresponding to each convection heating surface in series, so as to correct the real-time measurement data error corresponding to the corresponding convection heating surface through the verification data, and supplement or replace the missing or faulty measurement point data corresponding to the corresponding convection heating surface.

[0009] Optionally, the combustion characteristic combined function module is further used to generate the verification data according to the following formula: ; in, x Indicates the verification data corresponding to the missing or faulty measuring point data corresponding to a certain convection heating surface; They respectively represent the convection heating surface parameters corresponding to the head end, tail end and middle of the boiler's overall convection heating surface with real-time measurement data selected according to the physical characteristics of the boiler's convection heating surface in series; A represents an empirical constant selected according to the arrangement of the convection heating surface between the head end, tail end and middle of the boiler's overall convection heating surface; f express x The differential fitting verification function corresponding to the corresponding convection heating surface.

[0010] Optionally, the secondary iterative calculation loop includes a load segment division module; The load segment division module is used to divide the real-time coal-fired generator set electric power threshold into several load condition branches according to the preset coal-fired generator set electric power threshold interval, and obtain each load condition branch module. The initial cleaning factor of the convection heating surface is copied according to the number of load segments and sent to each load condition branch module in parallel. The real-time coal-fired generator set electric power threshold activates a certain load condition branch module according to the trigger condition, and transcribes and iterates the initial cleaning factor of the convection heating surface in real time into the secondary cleaning factor data of the load segment where the convection heating surface is located. When the fluctuation amplitude in its load segment is greater than the preset fluctuation amplitude, the iteration of the secondary cleaning factor data of the load segment is suspended, and the branch data remains statically latched; when the load change rate of the coal-fired generator set is greater than the preset load change rate, all the load condition branches suspend the iteration of the secondary cleaning factor data of the load segment, and the branch data remains statically latched.

[0011] Optionally, the secondary iterative calculation loop further includes a sootblowing system state division module; The sootblowing system state division module is used to set a sootblowing interval of a preset duration according to the falling edge of the high level disappearance of the sootblowing system operation signal as the reference starting point, the first percentage threshold duration of the preset duration iteratively corresponds to the secondary cleaning factor data after sootblowing of the load section where the co-current heating surface is located after sootblowing, and the second percentage threshold duration of the preset duration iteratively corresponds to the secondary cleaning factor data before sootblowing of the load section where the co-current heating surface is located before sootblowing; when the sootblowing system operation signal is triggered at a high level, the iteration of the cleaning factor is paused and the branch data remains statically latched.

[0012] Optionally, the test identification module is used to generate multi-fuel test cleaning factor data according to the initial cleaning factor of the convection heating surface corresponding to the target fuel combination code activated again within a preset test time period and the secondary cleaning factor data of different operating conditions, including: The test identification module is used to: When the target fuel combination code is activated again, the corresponding initial cleanliness factor of the convection heating surface and the secondary cleanliness factor data of different operating conditions are sampled simultaneously to generate multi-fuel test cleanliness factor data.

[0013] Optionally, the test identification module is used to determine the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the convection heating surface under the typical operating condition based on the multi-fuel test cleaning factor data, including: The test identification module is used to: All the multi-fuel test cleaning factor data generated within a preset test time period are compared with the preset theoretical fitting growth threshold, and the operating condition corresponding to the test cleaning factor data with the smallest threshold deviation is selected as the typical operating condition. At the same time, the secondary cleaning factor data under the typical operating condition is used as the long-term cleaning factor signal of the convection heating surface.

[0014] Optionally, the computing and testing system further comprises a display module; the display module is used to: Based on the typical working condition, the multi-fuel test cleaning factor data is sorted according to a preset sorting rule to obtain a corresponding sorting result; the sorting rule includes that the multi-fuel test cleaning factor data under the same typical working condition is updated in descending order according to the numerical value and in a time series; Using a human-machine interface of a production control system, displaying the sorting results; and / or, The cleaning factor characteristic information of the convection heating surface is displayed, and an alarm is issued when the cleaning factor characteristic information exceeds a limit value; wherein the cleaning factor characteristic information includes an upper limit and a lower limit of the cleaning factor.

[0015] Another aspect of the present disclosure provides a method for calculating and testing a cleanliness factor of a convection heating surface of a boiler, the method comprising: Activate the target fuel combination code and its corresponding fuel characteristic parameter data; Based on the fuel characteristic parameter data and combustion parameter data corresponding to the target fuel combination code, generating an initial cleaning factor of the convection heating surface corresponding to the target fuel combination code; Based on different electric power thresholds and sootblowing system states of coal-fired power generation units, according to the initial cleaning factor of the convection heating surface, the secondary cleaning factor data of different operating condition intervals corresponding to the target fuel combination code are generated, so that when the coal-fired power generation unit is running in real time, only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated, and the branch data of other operating condition intervals are kept statically latched; According to the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within the preset test time period and the secondary cleaning factor data in different operating condition intervals, multi-fuel test cleaning factor data are generated, and based on the multi-fuel test cleaning factor data, the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the convective heating surface under the typical operating condition are determined.

[0016] Compared with the prior art, the present invention utilizes the existing thermal measuring points of the coal-fired power generation unit, adopts the configuration function block of the production control system, and embeds a real-time calculation loop in the production control system according to the design parameters and historical operating characteristic parameters of the coal-fired power generation unit. The operating conditions are automatically screened when the coal-fired power generation unit is in continuous operation, and the typical test operating condition signal of the coal-fired power generation unit and the long-term cleaning factor signal of a certain convection heating surface of the boiler are output. In this way, online monitoring of the cleaning factor of the convection heating surface of the boiler can be achieved without third-party auxiliary software in a fully closed production control system, which has a good guiding role in the safe and stable operation and adjustment control of the convection heating surface of the boiler. The present invention also utilizes the necessary production control system and parameters of the power plant for development and research, which greatly reduces the software and hardware investment costs of thermal measuring points and third-party monitoring, and can perform autonomous optimization and maintenance in a timely manner according to changes in operating conditions, thereby reducing maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings represent similar elements, and unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0018] Figure 1 A schematic diagram of the structure of a calculation and test system for the cleanliness factor of a boiler convection heating surface provided in one embodiment of the present disclosure; Figure 2 A flow chart of a method for calculating and testing a cleanliness factor of a boiler convection heating surface provided in accordance with another embodiment of the present disclosure. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical scheme and advantages of the embodiments of the present disclosure clearer, the embodiments of the present disclosure will be described in detail below in conjunction with the accompanying drawings. However, it can be understood by those skilled in the art that in each embodiment of the present disclosure, many technical details are proposed in order to enable readers to better understand the present disclosure. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed for protection in the present disclosure can also be implemented. The division of the following embodiments is for the convenience of description and should not constitute any limitation on the specific implementation of the present disclosure. The various embodiments can be combined and referenced with each other without contradiction.

[0020] One embodiment of the present disclosure relates to a calculation and test system for a cleaning factor of a boiler convection heating surface, such as Figure 1 As shown, it includes a fuel characteristic combination parameter module 110 , an initial calculation loop 120 , a secondary iterative calculation loop 130 , and a test identification module 140 .

[0021] The fuel characteristic combination parameter module 110 is used to activate the target fuel combination code and its corresponding fuel characteristic parameter data.

[0022] Specifically, different codes are used to refer to different fuels. Fuel combination codes are used to refer to different fuel combinations. The target fuel combination code refers to the pre-specified fuel combination code. The fuel characteristic combination parameter module 110 can obtain the fuel combination code specified by the user through the human-machine interface input interface of the production control system such as the distributed control system (DCS), use the fuel combination code as the target fuel combination code and activate it, and at the same time activate the fuel characteristic parameter data corresponding to the target fuel combination code.

[0023] Exemplarily, the fuel characteristic combination parameter module 110 is also used to: based on the fuel characteristic parameters and the fuel combination code, multiply the fuel characteristic parameter data set of different fuel combination codes in the production control system within a first preset time period; and clear the production control system fuel characteristic parameter data that exceeds the first preset time period.

[0024] Specifically, the fuel characteristic parameters may include, but are not limited to, the received basis lower calorific value of the fuel, the received basis mass percentage of carbon, the received basis mass percentage of hydrogen, the received basis mass percentage of oxygen, the received basis mass percentage of nitrogen, the received basis mass percentage of sulfur, the received basis mass percentage of ash, the received basis mass percentage of moisture, the dry ash-free mass percentage of volatile matter, etc. The fuel characteristic combination parameter module 110 may activate the overwrite loop of the corresponding fuel characteristic parameter based on the different fuel combination codes input by the user, thereby multiplying the fuel characteristic parameter data set of different fuel combination codes in the production control system such as the DCS system within the first preset time period, or may directly collect the fuel characteristic parameter data corresponding to different fuel combination codes using the production control system such as the DCS system, thereby generating the fuel characteristic parameter data set of different fuel combination codes. Among them, the length and start and end time of the first preset time period may be selected and set according to actual needs, and this embodiment does not limit this.

[0025] Exemplarily, the calculation and test system of the cleaning factor of the boiler convection heating surface also includes a combustion characteristic combination function module. The combustion characteristic combination function module is used to introduce the real-time measurement data of the head end, tail end and middle of the whole convection heating surface of the boiler according to the physical characteristics of the series connection of the convection heating surface of the boiler, and generate verification data through the differential fitting verification loop corresponding to each convection heating surface in series, so as to correct the real-time measurement data error corresponding to the corresponding convection heating surface through the verification data, and supplement or replace the missing or faulty measurement point data corresponding to the corresponding convection heating surface.

[0026] Specifically, the real-time measurement data may include but are not limited to the flue gas, working fluid temperature, pressure, etc. at both ends of the convection heating surface. Each convection heating surface of the boiler in physical series can correspond to a sub-function module independently, and each sub-function module includes a differential fitting verification loop. The differential fitting verification loop can introduce the real-time measurement data of the head end, tail end and middle of the overall convection heating surface of the boiler according to the physical characteristics of the convection heating surface of the boiler in series, and generate verification data through differential verification. The verification data can correct the errors of the real-time measurement data such as the flue gas, working fluid temperature, pressure, etc. at both ends of the relevant convection heating surface, and supplement or replace the corresponding partial missing and faulty measurement point data of the relevant convection heating surface. Among them, the differential verification may include but is not limited to the first-order backward difference verification, the first-order forward difference verification and the second-order central difference verification. Each differential fitting verification loop exists in parallel to generate verification data corresponding to the convection heating surface respectively.

[0027] The combustion characteristics combined function module effectively realizes the high-order data processing and long-cycle iterative calculation functions of the production control system, and solves the calculation deviation problem caused by insufficient thermal measurement points and changeable combustion characteristics.

[0028] Exemplarily, the combustion characteristic combination function module is also used to generate verification data according to the following formula: .

[0029] in, x Indicates the verification data corresponding to the missing or faulty measuring point data corresponding to a certain convection heating surface; , , They respectively represent the convection heating surface parameters corresponding to the head end, tail end and middle of the boiler's overall convection heating surface with real-time measurement data selected according to the physical characteristics of the boiler's convection heating surface in series; A represents an empirical constant selected according to the arrangement of the convection heating surface between the head end, tail end and middle of the boiler's overall convection heating surface; f express x The differential fitting verification function corresponding to the corresponding convection heating surface.

[0030] For example, assuming that there are no measuring points for the inlet and outlet pressures of the boiler's low-temperature superheater working fluid, the corresponding differential fitting verification loop can perform first-order backward difference and first-order forward difference verification based on the steam drum pressure and the high-pressure outlet pressure, respectively, to obtain the low-pressure working fluid inlet pressure and the low-pressure working fluid outlet pressure.

[0031] Among them, the low-pressure working fluid inlet pressure can be expressed as , the low working fluid outlet pressure can be expressed as In the formula, Indicates the low-temperature superheater inlet pressure in MPa. Indicates the low-temperature superheater outlet pressure in MPa. Indicates the drum outlet pressure in MPa. Indicates the high-temperature superheater outlet pressure in MPa. A and B are constant codes, which are empirical constants selected based on the layout of the convection heating surface between the steam drum and the high-temperature superheater.

[0032] The initial calculation circuit 120 is used to generate an initial cleaning factor of the convective heating surface corresponding to the target fuel combination code based on the fuel characteristic parameter data and the combustion parameter data corresponding to the target fuel combination code.

[0033] Specifically, the combustion parameter data may include but are not limited to data corresponding to combustion parameters such as the electric power of the coal-fired power generation unit, the amount of boiler fuel, air distribution parameters, the temperature and pressure of the flue gas and working fluid of the convective heating surface. The initial calculation loop 120 may form an independent loop based on a specific convective heating surface, introduce the fuel characteristic parameter data corresponding to the target fuel combination code activated by the fuel characteristic combination parameter module 110, and the combustion parameter data such as the amount of boiler fuel and air distribution parameters input by the user or measured in real time by the production control system, and use the production control system configuration software calculation engine to fit the thermodynamics, combustion kinetics theory and empirical formula to generate the convective heating surface initial cleaning factor corresponding to the target fuel combination code. Among them, the production control system configuration software calculation engine may include but are not limited to high and low limit judgement, integer, remainder, selector, adder, multiplier, divider, exponential logarithm operator, function, delay, timer, register, date and time setter and other functional blocks.

[0034] For a specific convective heating surface, its initial cleanliness factor under the target fuel combination code can be expressed as . Where CF represents the initial cleanliness factor of the convection heating surface. To calculate the fuel quantity, the unit is kg / s. It is the convective heat transfer of the convective heating surface, and its unit is kJ / kg. is the heat transfer temperature and pressure of the convection heating surface, in °C. It is the flue gas velocity of the convection heating surface, in m / s. is the flue gas kinematic viscosity of the convection heating surface, in m 2 / s. It is the smoke blackness of the convection heating surface. is the average temperature of flue gas on the convection heating surface, in °C. It is the metal temperature of the tube wall on the convection heating surface, in degrees Celsius. is the working fluid flow rate of the convection heating surface, in m / s. is the dynamic viscosity of the convective heating surface, in N·s / m 2 . is the average specific volume of the working fluid on the convection heating surface, in m 3 / kg. M is the design parameters such as convection heating area, tube bundle layout and size. N is the thermodynamic coefficients such as thermal effectiveness coefficient, thermal conductivity, Planck number, Stefan-Boltzmann constant, etc.

[0035] For example, when CF represents the initial cleaning factor of the convection heating surface corresponding to the low-temperature superheater of the boiler, it can be calculated according to CF= K sj / K lx Calculated.

[0036] Among them, the actual heat transfer coefficient of the boiler low temperature superheater is K sj Can be based on Calculated. Actual heat transfer coefficient of boiler low temperature superheater K sj The unit is W / (m 2 ·℃). To calculate the fuel quantity, the unit is kg / s. It is the convective heat transfer of the low-temperature superheater convective heating surface, in kJ / kg. is the heat transfer temperature and pressure of the low-temperature superheater convection heating surface, in °C. A is the heat transfer area of ​​the low-temperature superheater convection heating surface, in m 2 .

[0037] Ideal heat transfer coefficient of convection heating surface of boiler low temperature superheater K lx Can be based on Calculated. Among them, is the thermal effectiveness coefficient. is the heat release coefficient of the flue gas side of the low-temperature superheater, in W / (m·℃), which can be calculated based on Calculated. In the formula, Correction factor for the geometric arrangement of low-temperature superheater tube bundles. It is the correction coefficient of the tube row in the flue gas travel direction of the low-temperature superheater. is the thermal conductivity of low-temperature superheater flue gas, in W / (m·℃). is the flue gas flow velocity of the low-temperature superheater, in m / s. d It is the outer diameter of the low-temperature superheater tube, in meters. is the kinematic viscosity of the low-temperature superheater flue gas, in m 2 / s. Pr g is the Planck number of low-temperature superheater flue gas. is the low temperature superheater Stefan-Boltzmann constant, =5.67×10 -8 , the unit is W / (m2 ·K 4 ). a y It is the blackness of low-temperature superheater flue gas. is the average temperature of low-temperature superheater flue gas, in °C. t hb It is the metal temperature of the low-temperature superheater tube wall, in °C.

[0038] is the heat release coefficient of the low-temperature superheater working medium side, the unit is W / (m·℃), which can be calculated based on Calculated. In the formula, It is the thermal conductivity of the low-temperature superheater working fluid, and its unit is W / (m·℃). is the working fluid flow rate of the low-temperature superheater, in m / s. d i It is the inner diameter of the low-temperature superheater tube, in meters. is the low temperature superheater dynamic viscosity, in N·s / m 2 . is the average specific volume of the low temperature superheater working fluid, in m 3 / kg. Pr is the Prandtl number of the low temperature superheater.

[0039] The secondary iterative calculation loop 130 is used to generate secondary cleaning factor data for different operating condition intervals corresponding to the target fuel combination code based on different electric power thresholds and sootblowing system states of the coal-fired power generation unit and according to the initial cleaning factor of the convection heating surface, so that when the coal-fired power generation unit is running in real time, only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated, and the branch data of other operating condition intervals remain statically latched.

[0040] Specifically, the secondary iterative calculation loop 130 can form a multi-branch screening loop based on the electric power of the coal-fired power generation unit measured in real time by the production control system such as the DCS system and the soot blowing system signals of each convection heating surface. Based on different electric power thresholds of the coal-fired power generation unit and the soot blowing system status, the initial cleaning factor of the convection heating surface is introduced to generate secondary cleaning factor data for different operating condition intervals, so that only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated during the real-time operation of the coal-fired power generation unit, while the data of other operating condition interval branches are kept statically latched.

[0041] Exemplarily, the secondary iterative calculation loop 130 includes a load segment division module. The load segment division module is used to divide the real-time coal-fired generator set electric power threshold into a number of load condition branches according to the preset coal-fired generator set electric power threshold interval, obtain each load condition branch module, and the initial cleaning factor of the convection heating surface is copied according to the number of load segments and sent to each load condition branch module in parallel. The real-time coal-fired generator set electric power threshold activates a certain load condition branch module according to the trigger condition, and the initial cleaning factor of the convection heating surface is transcribed and iterated in real time into the secondary cleaning factor data of the load segment corresponding to the convection heating surface. When the fluctuation amplitude in the load segment is greater than the preset fluctuation amplitude, the iteration of the secondary cleaning factor data of the load segment is suspended, and the branch data remains statically latched; when the load change rate of the coal-fired generator set is greater than the preset load change rate, all load condition branches suspend the iteration of the secondary cleaning factor data of the load segment, and the branch data remains statically latched.

[0042] Specifically, the load segment division module can divide the load segments according to the following criteria, thereby effectively reducing the amount of iterative calculations and improving the efficiency of iterative calculations: 1) The real-time electric power threshold of coal-fired generator sets is divided according to the electric power threshold of 5% coal-fired generator sets. When the load condition fluctuation amplitude in each divided load segment is greater than 0.5%Pe / min, the iteration is suspended and the branch data is kept statically latched. Pe represents the rated load of the coal-fired generator set. 2) When the load change rate of the coal-fired generator set △P>5%Pe / min, all branch iterations are suspended and the branch data remains statically latched.

[0043] Exemplarily, the secondary iterative calculation loop 130 also includes a sootblowing system state division module. The sootblowing system state division module is used to set the sootblowing interval of a preset duration according to the falling edge of the high level disappearance of the sootblowing system operation signal as the reference starting point, and the first percentage threshold duration of the preset duration is used to iterate the secondary cleaning factor data after sootblowing of the load section where the cocurrent heating surface is located after sootblowing, and the second percentage threshold duration of the preset duration is used to iterate the secondary cleaning factor data before sootblowing of the load section where the cocurrent heating surface is located before sootblowing; when the sootblowing system operation signal is triggered at a high level, the iteration of the cleaning factor is suspended, and the branch data remains statically latched.

[0044] Specifically, the sum of the first percentile threshold and the second percentile threshold should be 1. The sootblowing system state division module can divide the sootblowing system state according to the following criteria, thereby further reducing the iterative calculation amount and improving the iterative calculation efficiency: 1) Taking the falling edge of the high level disappearance of the sootblowing system operation signal as the reference starting point, the initial sootblowing interval is set to 4 hours. In the first 2 hours, the secondary cleaning factor data of the load section where the cocurrent heating surface is located after sootblowing is iterated, and in the second 2 hours, the secondary cleaning factor data of the load section where the cocurrent heating surface is located before sootblowing is iterated; 2) When the sootblowing system operation signal is triggered at a high level, the iteration is paused and the branch data remains statically latched.

[0045] By setting up a load segment division module and a sootblowing system state division module in the secondary iterative calculation loop, the real-time screening of the boiler combustion conditions is effectively realized, and the basic data error problem between the daily operating conditions and the typical test conditions of the coal-fired power generation unit is solved. In addition, through the rational processing of boundary conditions such as the load of the coal-fired power generation unit and the quality of coal entering the furnace, the accuracy of online monitoring and the representativeness of the online calculation results are effectively guaranteed.

[0046] The test identification module 140 is used to generate multi-fuel test cleaning factor data based on the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within a preset test time period and the secondary cleaning factor data in different operating condition intervals, and based on the multi-fuel test cleaning factor data, determine the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the convective heating surface under the typical operating condition.

[0047] Exemplarily, the test identification module 140 is used to generate multi-fuel test cleaning factor data according to the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within the preset test time period and the secondary cleaning factor data of different operating conditions, including: The test identification module 140 is used to: when the target fuel combination code is activated again, simultaneously sample the corresponding initial cleanliness factor of the convection heating surface and the secondary cleanliness factor data of different operating conditions to generate multi-fuel test cleanliness factor data.

[0048] Exemplarily, the test identification module 140 is used to determine the typical operating conditions of the coal-fired power generation unit and the long-term cleaning factor signal of the convection heating surface under the typical operating conditions based on the multi-fuel test cleaning factor data, including: The test identification module 140 is used to compare all multi-fuel test cleaning factor data generated within a preset test time period with the preset theoretical fitting growth threshold, select the operating condition corresponding to the cleaning factor data of the cleaning test with the smallest threshold deviation as the typical operating condition, and use the secondary cleaning factor data under the typical operating condition as the long-term cleaning factor signal of the convective heating surface.

[0049] Specifically, any target fuel combination code that has been activated can be stored in the test identification module 140. When the target fuel combination code stored in the test identification module 140 is activated again, the test iteration loop of the test identification module 140 corresponding to the target fuel combination code is triggered at the same time. At this time, the test identification module 140 can simultaneously sample the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code and the secondary cleaning factor data of different operating conditions through the triggered test iteration loop to generate multi-fuel test cleaning factor data.

[0050] The preset test time period may be a preset longer time period. The test identification module 140 may also compare the test cleaning factor data corresponding to different target fuel combination codes within the preset test time period, and select the test cleaning factor data with the smallest deviation from the theoretical fitting growth threshold according to the preset theoretical fitting growth threshold, and use the corresponding secondary cleaning factor data as the corresponding convection heating surface long-term cleaning factor signal, and use the corresponding operating condition as the typical operating condition.

[0051] Exemplarily, the calculation and testing system for the cleaning factor of the boiler convection heating surface also includes a display module.

[0052] The display module is used to: sort the multi-fuel test clean factor data according to the preset sorting rules based on typical working conditions to obtain the corresponding sorting results; and display the sorting results using the human-machine interface of the production control system. Among them, the sorting rules include that the multi-fuel test clean factor data under the same typical working condition is updated in descending order according to the numerical value and in a time series.

[0053] By using the display module to sort and display the cleaning factor data of multiple fuel tests under typical working conditions, the cleaning performance of different fuel combinations under specific working conditions can be intuitively displayed, thereby providing users with quick decision support.

[0054] Exemplarily, the display module is also used to: display the cleaning factor characteristic information of the convection heating surface, and alarm when the cleaning factor characteristic information exceeds the limit; wherein the cleaning factor characteristic information includes the upper limit and the lower limit of the cleaning factor.

[0055] By displaying the clean factor characteristic information of the convection heating surface, the clean factor characteristic information of the convection heating surface can be displayed more intuitively, providing users with quick decision support. By alarming when the clean factor characteristic information exceeds the limit, users can also be reminded in time to discover problems related to the convection heating surface, avoiding consequences such as equipment damage caused by untimely problem discovery.

[0056] It should be noted that all types of data involved in the above implementation modes can be stored in the database of the production control system, especially the historical database, so as to realize the storage management of various types of data and provide higher data availability.

[0057] Compared with the prior art, the calculation and test system for the cleanliness factor of the convection heating surface of a boiler provided in the embodiment of the present disclosure utilizes the existing thermal measuring points of the coal-fired power generation unit and adopts the configuration function block of the production control system. According to the design parameters and historical operation characteristic parameters of the coal-fired power generation unit, a real-time calculation loop is embedded in the production control system. When the coal-fired power generation unit is in continuous operation, the operating conditions are automatically screened, and the typical test operating condition signal of the coal-fired power generation unit and the long-term cleanliness factor signal of a certain convection heating surface of the boiler are output. In this way, the online monitoring of the cleanliness factor of the convection heating surface of the boiler can be realized without any third-party auxiliary software in a fully closed production control system, which has a good guiding role in the safe and stable operation and adjustment control of the convection heating surface of the boiler. In addition, the necessary production control system and parameters of the power plant are used for development and research, which greatly reduces the investment costs of software and hardware such as thermal measuring points and third-party monitoring, and can perform autonomous optimization and maintenance in a timely manner according to changes in operating conditions, thereby reducing maintenance costs.

[0058] Another embodiment of the present disclosure relates to a method for calculating and testing the cleaning factor of a boiler convection heating surface, the process of which is as follows: Figure 2 As shown, including: Step S210, activating the target fuel combination code and its corresponding fuel characteristic parameter data.

[0059] Step S220, based on the fuel characteristic parameter data and the combustion parameter data corresponding to the target fuel combination code, an initial cleaning factor of the convection heating surface corresponding to the target fuel combination code is generated.

[0060] Step S230, based on different electric power thresholds and sootblowing system states of coal-fired power generation units, and according to the initial cleaning factor of the convection heating surface, generates secondary cleaning factor data for different operating condition intervals corresponding to the target fuel combination code, so that when the coal-fired power generation unit is running in real time, only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated, and the branch data of other operating condition intervals remain statically latched.

[0061] Step S240, generates multi-fuel test cleaning factor data according to the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within the preset test time period and the secondary cleaning factor data of different operating conditions, and determines the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the heating surface under the typical operating condition based on the multi-fuel test cleaning factor data.

[0062] Compared with the prior art, the calculation and test method of the cleanliness factor of the boiler convection heating surface provided in the embodiment of the present disclosure realizes online monitoring of the cleanliness factor of the boiler convection heating surface in a fully closed production control system without third-party auxiliary software, which has a good guiding role in the safe and stable operation and adjustment control of the boiler convection heating surface, and also greatly reduces the investment cost of software and hardware such as thermal measurement points and third-party monitoring, and can perform autonomous optimization and maintenance in time according to changes in operating conditions, thereby reducing maintenance costs.

[0063] Those skilled in the art will appreciate that the above-mentioned embodiments are specific embodiments for implementing the present disclosure, and in actual applications, various changes may be made thereto in form and detail without departing from the spirit and scope of the present disclosure.

Claims

1. A calculation and test system for the cleanliness factor of a boiler convection heating surface, characterized in that: The computing and testing system comprises: A fuel characteristic combination parameter module is used to activate a target fuel combination code and its corresponding fuel characteristic parameter data; An initial calculation loop, for generating an initial cleaning factor of a convective heating surface corresponding to the target fuel combination code based on the fuel characteristic parameter data and the combustion parameter data corresponding to the target fuel combination code; The secondary iterative calculation loop is used to generate secondary cleaning factor data of different operating condition intervals corresponding to the target fuel combination code based on different electric power thresholds and soot blowing system states of the coal-fired power generation unit and according to the initial cleaning factor of the convection heating surface, so that when the coal-fired power generation unit is running in real time, only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated, and the branch data of other operating condition intervals are kept statically latched; The test identification module is used to generate multi-fuel test cleaning factor data according to the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within a preset test time period and the secondary cleaning factor data in different operating condition intervals, and determine the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the convective heating surface under the typical operating condition based on the multi-fuel test cleaning factor data.

2. The calculation and testing system according to claim 1, characterized in that: The fuel characteristic combination parameter module is also used for: Based on the fuel characteristic parameters and the fuel combination code, multiplying the fuel characteristic parameter data set of different fuel combination codes in the production control system within a first preset time period; and, The fuel characteristic parameter data of the production control system that exceeds the first preset time period is cleared.

3. The calculation and testing system according to claim 1, characterized in that: The computing and testing system also includes: The combustion characteristic combination function module is used to introduce the real-time measurement data of the head end, tail end and middle of the whole convection heating surface of the boiler according to the physical characteristics of the series convection heating surface of the boiler, and generate verification data through the differential fitting verification loop corresponding to each convection heating surface in series, so as to correct the real-time measurement data error corresponding to the corresponding convection heating surface through the verification data, and supplement or replace the missing or faulty measurement point data corresponding to the corresponding convection heating surface.

4. The calculation and testing system according to claim 3, characterized in that: The combustion characteristic combined function module is also used to generate the verification data according to the following formula: ； in, x Indicates the verification data corresponding to the missing or faulty measuring point data corresponding to a certain convection heating surface; They respectively represent the convection heating surface parameters corresponding to the head end, tail end and middle of the boiler's overall convection heating surface with real-time measurement data selected according to the physical characteristics of the boiler's convection heating surface in series; A represents an empirical constant selected according to the arrangement of the convection heating surface between the head end, tail end and middle of the boiler's overall convection heating surface; f express x The differential fitting verification function corresponding to the corresponding convection heating surface.

5. The calculation and testing system according to claim 1, characterized in that: The secondary iterative calculation loop includes a load segment division module; The load segment division module is used to divide the real-time coal-fired generator set electric power threshold into several load condition branches according to the preset coal-fired generator set electric power threshold interval, and obtain each load condition branch module. The initial cleaning factor of the convection heating surface is copied according to the number of load segments and sent to each load condition branch module in parallel. The real-time coal-fired generator set electric power threshold activates a certain load condition branch module according to the trigger condition, and transcribes and iterates the initial cleaning factor of the convection heating surface in real time into the secondary cleaning factor data of the load segment where the convection heating surface is located. When the fluctuation amplitude in its load segment is greater than the preset fluctuation amplitude, the iteration of the secondary cleaning factor data of the load segment is suspended, and the branch data remains statically latched; when the load change rate of the coal-fired generator set is greater than the preset load change rate, all the load condition branches suspend the iteration of the secondary cleaning factor data of the load segment, and the branch data remains statically latched.

6. The computing and testing system according to claim 1, characterized in that: The secondary iterative calculation loop also includes a sootblowing system state division module; The sootblowing system state division module is used to set a sootblowing interval of a preset duration according to the falling edge of the high level disappearance of the sootblowing system operation signal as the reference starting point, the first percentage threshold duration of the preset duration iteratively corresponds to the secondary cleaning factor data after sootblowing of the load section where the co-current heating surface is located after sootblowing, and the second percentage threshold duration of the preset duration iteratively corresponds to the secondary cleaning factor data before sootblowing of the load section where the co-current heating surface is located before sootblowing; when the sootblowing system operation signal is triggered at a high level, the iteration of the cleaning factor is paused and the branch data remains statically latched.

7. The computing and testing system according to claim 1, characterized in that: The test identification module is used to generate multi-fuel test cleaning factor data according to the initial cleaning factor of the convection heating surface corresponding to the target fuel combination code activated again within a preset test time period and the secondary cleaning factor data of different operating conditions, including: The test identification module is used to: When the target fuel combination code is activated again, the corresponding initial cleanliness factor of the convection heating surface and the secondary cleanliness factor data of different operating conditions are sampled simultaneously to generate multi-fuel test cleanliness factor data.

8. The calculation and testing system according to claim 7, characterized in that: The test identification module is used to determine the typical operating conditions of the coal-fired power generation unit and the long-term cleaning factor signal of the convection heating surface under the typical operating conditions based on the multi-fuel test cleaning factor data, including: The test identification module is used to: All the multi-fuel test cleaning factor data generated within a preset test time period are compared with the preset theoretical fitting growth threshold, and the operating condition corresponding to the test cleaning factor data with the smallest threshold deviation is selected as the typical operating condition. At the same time, the secondary cleaning factor data under the typical operating condition is used as the long-term cleaning factor signal of the convection heating surface.

9. The computing and testing system according to claim 1, characterized in that: The computing and testing system further comprises a display module; the display module is used to: Based on the typical working condition, the multi-fuel test cleaning factor data is sorted according to a preset sorting rule to obtain a corresponding sorting result; the sorting rule includes that the multi-fuel test cleaning factor data under the same typical working condition is updated in descending order according to the numerical value and in a time series; Using a human-machine interface of a production control system, displaying the sorting results; and / or, The cleaning factor characteristic information of the convection heating surface is displayed, and an alarm is issued when the cleaning factor characteristic information exceeds a limit value; wherein the cleaning factor characteristic information includes an upper limit and a lower limit of the cleaning factor.

10. A method for calculating and testing the cleanliness factor of a boiler convection heating surface, characterized in that: The calculation and test methods include: Activate the target fuel combination code and its corresponding fuel characteristic parameter data; Based on the fuel characteristic parameter data and combustion parameter data corresponding to the target fuel combination code, generating an initial cleaning factor of the convection heating surface corresponding to the target fuel combination code; Based on different electric power thresholds and sootblowing system states of coal-fired power generation units, according to the initial cleaning factor of the convection heating surface, the secondary cleaning factor data of different operating condition intervals corresponding to the target fuel combination code are generated, so that when the coal-fired power generation unit is running in real time, only the cleaning factor data of the corresponding operating condition interval branch is transcribed and iterated, and the branch data of other operating condition intervals are kept statically latched; According to the initial cleaning factor of the convective heating surface corresponding to the target fuel combination code activated again within the preset test time period and the secondary cleaning factor data in different operating condition intervals, multi-fuel test cleaning factor data are generated, and based on the multi-fuel test cleaning factor data, the typical operating condition of the coal-fired power generation unit and the long-term cleaning factor signal of the convective heating surface under the typical operating condition are determined.

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