CN113617216B - Integrated control method and system for wet desulfurization absorption tower system - Google Patents
Integrated control method and system for wet desulfurization absorption tower system Download PDFInfo
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- 238000006477 desulfuration reaction Methods 0.000 title claims abstract description 152
- 230000023556 desulfurization Effects 0.000 title claims abstract description 152
- 238000010521 absorption reaction Methods 0.000 title claims abstract description 63
- 238000000034 method Methods 0.000 title claims abstract description 37
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims abstract description 31
- 229910052717 sulfur Inorganic materials 0.000 claims abstract description 31
- 239000011593 sulfur Substances 0.000 claims abstract description 31
- 238000004519 manufacturing process Methods 0.000 claims abstract description 30
- 238000013145 classification model Methods 0.000 claims abstract description 17
- 238000005265 energy consumption Methods 0.000 claims abstract description 9
- 239000002002 slurry Substances 0.000 claims description 52
- 238000004891 communication Methods 0.000 claims description 30
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims description 25
- 239000003546 flue gas Substances 0.000 claims description 25
- 238000011217 control strategy Methods 0.000 claims description 16
- 238000004422 calculation algorithm Methods 0.000 claims description 13
- 239000006028 limestone Substances 0.000 claims description 12
- 238000013480 data collection Methods 0.000 claims description 11
- 230000003009 desulfurizing effect Effects 0.000 claims description 10
- 238000007635 classification algorithm Methods 0.000 claims description 9
- 238000007781 pre-processing Methods 0.000 claims description 9
- 238000013500 data storage Methods 0.000 claims description 8
- 239000003795 chemical substances by application Substances 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 6
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims description 5
- 239000003245 coal Substances 0.000 claims description 5
- 239000007788 liquid Substances 0.000 claims description 5
- 229910052760 oxygen Inorganic materials 0.000 claims description 5
- 239000001301 oxygen Substances 0.000 claims description 5
- 230000001502 supplementing effect Effects 0.000 claims description 5
- 239000006096 absorbing agent Substances 0.000 claims description 4
- 239000007789 gas Substances 0.000 claims description 4
- 238000003064 k means clustering Methods 0.000 claims description 4
- 238000011160 research Methods 0.000 claims description 4
- 238000013528 artificial neural network Methods 0.000 claims description 3
- 238000007405 data analysis Methods 0.000 claims description 2
- 238000012847 principal component analysis method Methods 0.000 claims 1
- 235000019738 Limestone Nutrition 0.000 description 6
- 238000013461 design Methods 0.000 description 2
- 239000003344 environmental pollutant Substances 0.000 description 2
- 239000000446 fuel Substances 0.000 description 2
- 231100000719 pollutant Toxicity 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 239000010440 gypsum Substances 0.000 description 1
- 229910052602 gypsum Inorganic materials 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 125000000962 organic group Chemical group 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/46—Removing components of defined structure
- B01D53/48—Sulfur compounds
- B01D53/50—Sulfur oxides
- B01D53/501—Sulfur oxides by treating the gases with a solution or a suspension of an alkali or earth-alkali or ammonium compound
- B01D53/502—Sulfur oxides by treating the gases with a solution or a suspension of an alkali or earth-alkali or ammonium compound characterised by a specific solution or suspension
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- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
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- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/346—Controlling the process
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/74—General processes for purification of waste gases; Apparatus or devices specially adapted therefor
- B01D53/80—Semi-solid phase processes, i.e. by using slurries
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/34—Chemical or biological purification of waste gases
- B01D53/96—Regeneration, reactivation or recycling of reactants
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D27/00—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00
- G05D27/02—Simultaneous control of variables covered by two or more of main groups G05D1/00 - G05D25/00 characterised by the use of electric means
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D2251/00—Reactants
- B01D2251/40—Alkaline earth metal or magnesium compounds
- B01D2251/404—Alkaline earth metal or magnesium compounds of calcium
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D2258/00—Sources of waste gases
- B01D2258/02—Other waste gases
- B01D2258/0283—Flue gases
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Abstract
The invention discloses an integrated control method of a wet desulfurization absorption tower system, which comprises the following steps: step S01: selecting working condition classification parameters; step S02: establishing a classification model; step S03: establishing a working condition classification knowledge base; step S04: collecting real-time working condition operation parameters of a desulfurization system; step S05: comparing the real-time working condition operation parameters acquired in the step S04 with the best operation parameter data in the working condition classification knowledge base established in the step S03, identifying and classifying the working condition types of the current desulfurization system, and determining the working condition types of the current desulfurization system; step S06: and matching the optimal working condition operation parameter data applicable to the working condition type of the current desulfurization system determined in the step S05. The invention also discloses an integrated control system of the wet desulfurization absorption tower system. The method and the system greatly reduce the energy consumption of the desulfurization absorption tower system, and more intelligently control the PH value and the outlet sulfur value so as to better meet and adapt to the production requirements.
Description
Technical Field
The invention relates to an integrated control method and system for a wet desulfurization absorption tower system, and belongs to the technical field of power plant desulfurization systems.
Background
The energy consumption of an absorption tower of a desulfurization system of a current power plant is high, the optimal collocation and selection of a slurry circulating pump are difficult, and the difficulties of discharging outlet sulfur and controlling the PH value of the absorption tower are high; the fuel of the power plant is frequently changed, so that the pollutant generation amount far exceeds the design value of the system.
The absorption of the desulfurization absorption tower is the most core system of the whole desulfurization system, and the energy consumption of a slurry circulating pump of key equipment of the desulfurization absorption tower accounts for about 60% of the whole desulfurization system. Generally, the energy consumption of the absorption tower is reduced by changing the liquid-gas ratio of the absorption tower, namely, changing the combination and collocation mode of the slurry circulating pump, but the combination and collocation mode of the slurry circulating pump is generally based on personal experience of operators, and because the operators are uneven in level, the combination is carried out only by the personal experience of the operators, so that the energy consumption of the system is very high.
In addition, the PH control and the outlet sulfur numerical control of the absorber system are the most important parameters of the absorber system, and the PH and the outlet sulfur numerical control account for about 50 to 70% of the total operations in the daily monitoring operation of the operators.
The control strategies for the PH and outlet sulfur of current desulfurization systems are presumably as follows:
1) The pH value is controlled by the manual operation of operators or the pH value control;
2) The control strategy is mainly controlled according to the combination of the concentration of SO2 at the inlet and the pH value;
3) Controlling mainly according to the PH value or the outlet SO 2;
In the wet limestone-gypsum desulfurization process, since the desulfurization absorber slurry contains a large amount of unreacted limestone, the pH of the slurry is retarded relatively much compared to the supply of limestone slurry. The reaction of PH to the limestone slurry feed rate is nonlinear. When the pH value is 5.2-5.5, the pH value change amplitude is larger due to the change of the limestone slurry; when the pH value is 6.0-6.2, even though the limestone slurry supplying speed is greatly increased, the pH value amplitude is very small, and when the absorption tower slurry is operated in the area, a small deviation of the pH value can bring about a great deal of limestone waste.
These control methods, although currently the mainstream control strategies, do not adapt well to the production requirements.
Disclosure of Invention
The invention aims to provide an integrated control method and an integrated control system for a wet desulfurization absorption tower system, which can ensure safe and efficient operation of the desulfurization absorption tower system, improve the level of automation and intellectualization of operation of the desulfurization system, and reduce the energy consumption of the desulfurization absorption tower system by about 10-25%.
In order to solve the technical problems, the invention adopts the following technical scheme: an integrated control method of a wet desulfurization absorption tower system comprises the following steps: step S01: selecting working condition classification parameters: determining 17 variables including unit load, main steam flow, total coal supply amount, total air quantity, raw flue gas sulfur concentration, raw flue gas temperature, clean flue gas sulfur concentration, absorption tower PH value, slurry circulation A pump current, slurry circulation B pump current, slurry circulation C pump current, slurry circulation D pump current, slurry circulation E pump current, absorption tower system resistance, absorption tower liquid level, clean flue gas oxygen content and slurry supplementing flow rate from historical production data of a desulfurization system by a mechanism method, a Pearson linear correlation algorithm and a PCA main component analysis method; step S02: establishing a classification model: selecting parameters of load, total sulfur content of an inlet, flue gas temperature and flue gas flow, classifying working conditions through a K-means clustering algorithm, and establishing a classification model by taking the characteristic variable selected in S01 as a research parameter of the classification model; step S03: establishing a working condition classification knowledge base: establishing a working condition classification knowledge base of the desulfurization system through the classification model established in the step S02, wherein the working condition classification knowledge base comprises N types of standard working condition data of the desulfurization system and also comprises optimal operation parameter data under the working conditions of each type of desulfurization system under the condition of secondarily calculated optimizing indexes (such as the lowest energy consumption, the safest operation of the system and the like); step S04: collecting real-time working condition operation parameters of a desulfurization system; step S05: comparing the real-time working condition operation parameters acquired in the step S04 with the best operation parameter data in the working condition classification knowledge base established in the step S03, identifying and classifying the working condition types of the current desulfurization system, and determining the working condition types of the current desulfurization system; step S06: matching the optimal working condition operation parameter data applicable to the working condition category of the current desulfurization system determined in the step S05; step S07: establishing a control strategy model of the desulfurization system according to the optimal working condition operation parameter data matched in the step S06; and providing an output value of the adjusting variable which reaches the optimum operation parameter and needs to be changed; step S08: and pushing the optimal operating parameter value matched with the current operating mode category of the desulfurization system to the DCS control system of the desulfurization system through MOBUS protocol.
The integrated control method of the wet desulfurization absorption tower system further comprises the step of mining optimal operation parameter data of the desulfurization system under different working conditions based on a data analysis algorithm, wherein the optimal operation parameter data comprise an optimal liquid-gas ratio, an optimal slurry circulating pump combination mode, an optimal PH value, an optimal resistance value and an outlet sulfur value.
In the foregoing method for controlling the wet desulfurization absorption tower system integrally, the establishing a control strategy model of the desulfurization system by the best working condition operation parameter data matched in the step S06 includes: establishing a PH value-limestone desulfurizing agent flow cascade control model by taking the optimal PH value in the matched optimal working condition operation parameter data in the step S06 as a set value and making deviation with the PH value under the working condition of the current desulfurizing system; the method further comprises the step of establishing an outlet sulfur-limestone desulfurizing agent flow cascade control model by taking the outlet sulfur value in the matched optimal working condition operation parameter data in the step S06 as a set value and making deviation with the outlet sulfur value of the current working condition; and the method further comprises the step of adjusting a non-most energy-saving slurry circulation pump combination mode under the working condition of the current desulfurization system by the optimal slurry circulation pump combination collocation mode in the operation parameter data of the matched optimal working condition in the step S06.
The integrated control system of the wet desulfurization absorption tower system adopts the integrated control method of the wet desulfurization absorption tower system, and comprises a production data storage module, wherein the production data storage module is connected with a data preprocessing module and is used for storing historical production data of a desulfurization system collected by a production data collection module; the data preprocessing module is used for selecting characteristic variables, determining the characteristic variables by utilizing a mechanism method, a Pearson linear correlation algorithm and a PCA main component analysis method through the data preprocessing module, wherein the characteristic variables comprise organic group load, main steam flow, total coal feeding amount, total air quantity, raw flue gas sulfur concentration, raw flue gas temperature, pure flue gas sulfur concentration, absorption tower PH value, slurry circulation A pump current, slurry circulation B pump current, slurry circulation C pump current, slurry circulation D pump current, slurry circulation E pump current, absorption tower system resistance, absorption tower liquid level, purified flue gas oxygen content and slurry supplementing flow;
The working condition classification algorithm module is used for classifying each operation working condition of the desulfurization system through the classification algorithm model and calculating the optimal operation parameters of the desulfurization system under each working condition; the optimal operation parameter data under various working conditions are used as a benchmark, an optimal operation parameter prediction model is established through an RBF neural network, and partial parameter values (such as PH value and absorption tower resistance value) are locally optimized;
the working condition classification knowledge base is used for storing the optimal operation parameter data under various working conditions provided by the working condition classification algorithm module;
the working condition classification module is used for identifying the working condition type of the current desulfurization system and selecting the best operation parameter data matched with the working condition type of the current desulfurization system from the working condition classification knowledge base;
The optimal parameter pushing module is used for pushing optimal operation parameter data matched with the working condition type of the current desulfurization system to the data communication subsystem; the data communication subsystem comprises a communication sub-module, and the communication sub-module is used for sending the optimal operation parameter data matched with the working condition type of the current desulfurization system to the parameter receiving module; the parameter receiving module is used for receiving the optimal operation parameter data sent by the communication sub-module; the first acquisition data module is connected with the working condition classification module and is used for sending the acquired real-time working condition operation parameters to the working condition classification module; the second data acquisition module is connected with the standard alignment module, the second data acquisition module is used for transmitting the acquired real-time working condition operation parameters to the standard alignment module, the standard alignment module is used for identifying and classifying the working condition types of the current desulfurization system, a standard working condition type corresponding to the working condition types of the current desulfurization system is matched from the working condition classification knowledge base, and the matched standard working condition is used for giving out the optimal operation parameter data under the working condition of the current desulfurization system; the control strategy module is used for establishing a control strategy model of the desulfurization system; the first data communication module is used for pushing the best working condition operation parameter data matched with the working condition type of the current desulfurization system to the DCS control system of the desulfurization absorption tower.
In the integrated control system of the wet desulfurization absorption tower system, the DCS control system of the desulfurization absorption tower comprises a production data collection module, wherein the production data collection module is connected with a production data storage module, and the production data collection module is used for collecting and storing historical production data of the desulfurization system for many years.
In the integrated control system of the wet desulfurization absorption tower system, the DCS control system of the desulfurization absorption tower further comprises a real-time data acquisition module for acquiring real-time working condition operation parameters of the current desulfurization system, wherein the real-time data acquisition module is respectively connected with the first acquisition data module and the second acquisition data module.
In the integrated control system of the wet desulfurization absorption tower system, the DCS control system of the desulfurization absorption tower further comprises a second data communication module connected to the first data communication module, for receiving the optimal operating parameter data pushed by the first data communication module and sending the optimal operating parameter data to the command control module.
In the integrated control system of the wet desulfurization absorption tower system, the DCS control system of the desulfurization absorption tower further comprises an instruction control module for controlling the operation state of each device of the desulfurization system, and adjusting and controlling the operation state of each device of the desulfurization system according to the optimal operating condition operating parameter data sent by the second data communication module.
Compared with the prior art, the desulfurization system is not dependent on experience of operators any more by the method and the system, and the optimal slurry circulating pump combination mode can be automatically selected for the desulfurization system by the method and the system, so that energy consumption of the desulfurization absorption tower system is greatly reduced; the PH value and the outlet sulfur value can be controlled more intelligently, and the corresponding PH value and outlet sulfur value can be adjusted in time under different working conditions of the desulfurization system, so that production requirements can be better met and adapted. The method and the system greatly reduce the control difficulty of the outlet sulfur and the PH value of the desulfurization system, and can be timely adjusted along with the change of the fuel of the power plant so as to prevent the pollutant generation amount from exceeding the system design value.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flow chart of a control method of the present invention;
fig. 2 is a schematic structural view of the control system of the present invention.
The invention is further described below with reference to the drawings and the detailed description.
Detailed Description
In order to enable those skilled in the art to better understand the present invention, the following description is made clearly and completely with reference to the accompanying drawings in the embodiments of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Example 1 of the present invention: an integrated control method of a wet desulfurization absorption tower system comprises the following steps: step S01: selecting working condition classification parameters: 17 variables including unit load, main steam flow, total coal supply amount, total air quantity, raw flue gas sulfur concentration, raw flue gas temperature, purified flue gas sulfur concentration, absorption tower PH value, slurry circulation A pump current, slurry circulation B pump current, slurry circulation C pump current, slurry circulation D pump current, slurry circulation E pump current, absorption tower system resistance, absorption tower liquid level, purified flue gas oxygen content and slurry supplementing flow are determined as characteristic variables of a model through a mechanism method, a Pearson linear correlation algorithm and a PCA main component analysis method; step S02: establishing a classification model: classifying working conditions through a K-means clustering algorithm, and establishing a classification model by taking characteristic variables as research parameters of the classification model; step S03: establishing a working condition classification knowledge base: establishing a working condition classification knowledge base of the desulfurization system through the classification model established in the step S02, wherein the working condition classification knowledge base comprises N types of standard working condition data of the desulfurization system and optimal operation parameter data of each type of working condition of the desulfurization system; step S04: collecting real-time working condition operation parameters of a desulfurization system; step S05: comparing the real-time working condition operation parameters acquired in the step S04 with the best operation parameter data in the working condition classification knowledge base established in the step S03, identifying and classifying the working condition types of the current desulfurization system, and determining the working condition types of the current desulfurization system; step S06: matching the optimal working condition operation parameter data applicable to the working condition category of the current desulfurization system determined in the step S05; step S07: establishing a control strategy model of the desulfurization system according to the optimal working condition operation parameter data matched in the step S06; step S08: and pushing the optimal working condition operation parameter data matched with the working condition type of the current desulfurization system to the DCS control system of the desulfurization system through MOBUS protocol.
Example 2 of the present invention: an integrated control method of a wet desulfurization absorption tower system comprises the following steps: step S01: selecting working condition classification parameters: 17 variables including unit load, main steam flow, total coal supply amount, total air quantity, raw flue gas sulfur concentration, raw flue gas temperature, purified flue gas sulfur concentration, absorption tower PH value, slurry circulation A pump current, slurry circulation B pump current, slurry circulation C pump current, slurry circulation D pump current, slurry circulation E pump current, absorption tower system resistance, absorption tower liquid level, purified flue gas oxygen content and slurry supplementing flow are determined as characteristic variables of a model through a mechanism method, a Pearson linear correlation algorithm and a PCA main component analysis method; step S02: establishing a classification model: classifying working conditions through a K-means clustering algorithm, and establishing a classification model by taking characteristic variables as research parameters of the classification model; step S03: establishing a working condition classification knowledge base: establishing a working condition classification knowledge base of the desulfurization system through the classification model established in the step S02, wherein the working condition classification knowledge base comprises N types of standard working condition data of the desulfurization system and optimal operation parameter data of each type of working condition of the desulfurization system; step S04: collecting real-time working condition operation parameters of a desulfurization system; step S05: comparing the real-time working condition operation parameters acquired in the step S04 with the best operation parameter data in the working condition classification knowledge base established in the step S03, identifying and classifying the working condition types of the current desulfurization system, and determining the working condition types of the current desulfurization system; step S06: matching the optimal working condition operation parameter data applicable to the working condition category of the current desulfurization system determined in the step S05; step S07: establishing a control strategy model of the desulfurization system according to the optimal working condition operation parameter data matched in the step S06; step S08: and pushing the optimal working condition operation parameter data matched with the working condition type of the current desulfurization system to the DCS control system of the desulfurization system through MOBUS protocol. Wherein, the optimal operation parameter data comprises an optimal liquid-gas ratio, an optimal slurry circulating pump combination mode, an optimal PH value, an optimal resistance value and an outlet sulfur value.
In addition, establishing the control strategy model of the desulfurization system through the matched optimal working condition operation parameter data in the step S06 comprises the following steps: establishing a PH value-limestone desulfurizing agent flow cascade control model by taking the optimal PH value in the matched optimal working condition operation parameter data in the step S06 as a set value and making deviation with the PH value under the working condition of the current desulfurizing system; the method further comprises the step of establishing an outlet sulfur-limestone desulfurizing agent flow cascade control model by taking the outlet sulfur value in the matched optimal working condition operation parameter data in the step S06 as a set value and making deviation with the outlet sulfur value of the current working condition; and the method further comprises the step of adjusting a non-most energy-saving slurry circulation pump combination mode under the working condition of the current desulfurization system by the optimal slurry circulation pump combination collocation mode in the operation parameter data of the matched optimal working condition in the step S06.
Example 3 of the present invention: the integrated control system of the wet desulfurization absorption tower system comprises a production data storage module, wherein the production data storage module is connected with the data preprocessing module and is used for storing historical production data of the desulfurization system collected by the production data collection module;
The data preprocessing module is used for selecting characteristic variables, and determining the characteristic variables such as unit load, inlet sulfur content, flue gas temperature outlet sulfur content, PH value, slurry circulating pump current and the like by a mechanism method, a Pearson linear correlation algorithm and a PCA main component analysis method through the data preprocessing module;
The working condition classification algorithm module is used for classifying each operation working condition of the desulfurization system through the classification algorithm model and calculating the optimal operation parameters of the desulfurization system under each working condition; the optimal operation parameter data under various working conditions are used as a benchmark, an optimal operation parameter prediction model is established through an RBF neural network, and partial parameter values are locally optimized;
The working condition classification knowledge base is used for storing the optimal operation parameter data under various working conditions provided by the working condition classification algorithm module; the working condition classification module is used for identifying the working condition type of the current desulfurization system and selecting the best operation parameter data matched with the working condition type of the current desulfurization system from the working condition classification knowledge base; the optimal parameter pushing module is used for pushing optimal operation parameter data matched with the working condition type of the current desulfurization system to the data communication subsystem; the data communication subsystem comprises a communication sub-module, and the communication sub-module is used for sending the optimal operation parameter data matched with the working condition type of the current desulfurization system to the parameter receiving module; the parameter receiving module is used for receiving the optimal operation parameter data sent by the communication sub-module; the first acquisition data module is connected with the working condition classification module and is used for sending the acquired real-time working condition operation parameters to the working condition classification module; the second data acquisition module is connected with the standard alignment module, the second data acquisition module is used for transmitting the acquired real-time working condition operation parameters to the standard alignment module, the standard alignment module is used for identifying and classifying the working condition types of the current desulfurization system, a standard working condition type corresponding to the working condition types of the current desulfurization system is matched from the working condition classification knowledge base, and the matched standard working condition is used for giving out the optimal operation parameter data under the working condition of the current desulfurization system; the control strategy module is used for establishing a control strategy model of the desulfurization system; the first data communication module is used for pushing the best working condition operation parameter data matched with the working condition type of the current desulfurization system to the DCS control system of the desulfurization absorption tower. The desulfurization absorption tower DCS control system comprises a production data collection module, wherein the production data collection module is connected with a production data storage module, and the production data collection module is used for collecting and storing historical production data of the desulfurization system for many years. The DCS control system of the desulfurization absorption tower further comprises a real-time data acquisition module which is used for acquiring real-time working condition operation parameters of the current desulfurization system and is respectively connected with the first acquisition data module and the second acquisition data module. The DCS control system of the desulfurization absorption tower further comprises a second data communication module which is connected with the first data communication module and used for receiving the best working condition operation parameter data pushed by the first data communication module and sending the best working condition operation parameter data to the instruction control module. The DCS control system of the desulfurization absorption tower also comprises an instruction control module which is used for controlling the operation state of each device of the desulfurization system, and adjusting and controlling the operation state of each device (such as a pump, a valve and the like) of the desulfurization system according to the optimal working condition operation parameter data sent by the second data communication module.
Claims (2)
1. The integrated control method of the wet desulfurization absorption tower system is characterized by comprising the following steps of:
Step S01: selecting working condition classification parameters: 17 variables including unit load, main steam flow, total coal supply, total air quantity, raw flue gas sulfur concentration, raw flue gas temperature, purified flue gas sulfur concentration, absorption tower PH value, slurry circulation A pump current, slurry circulation B pump current, slurry circulation C pump current, slurry circulation D pump current, slurry circulation E pump current, absorption tower system resistance, absorption tower liquid level, purified flue gas oxygen content and slurry supplementing flow are determined as characteristic variables of a model through a mechanism method, a Pearson linear correlation algorithm and a PCA main component analysis method;
Step S02: establishing a classification model: selecting parameters of load, total sulfur content of an inlet, flue gas temperature and flue gas flow, classifying working conditions through a K-means clustering algorithm, and establishing a classification model by taking the characteristic variable selected in S01 as a research parameter of the classification model;
Step S03: establishing a working condition classification knowledge base: establishing a working condition classification knowledge base of the desulfurization system through the classification model established in the step S02, wherein the working condition classification knowledge base comprises N types of standard working condition data of the desulfurization system and also comprises optimal operation parameter data under the twice-calculated optimizing index and under the working condition of each type of desulfurization system;
Step S04: collecting real-time working condition operation parameters of a desulfurization system;
Step S05: comparing the real-time working condition operation parameters acquired in the step S04 with the best operation parameter data in the working condition classification knowledge base of the desulfurization system established in the step S03, and carrying out category identification and classification on the working condition of the current desulfurization system to determine the category of the working condition of the current desulfurization system;
Step S06: matching the optimal working condition operation parameter data applicable to the working condition category of the current desulfurization system determined in the step S05;
Step S07: establishing a control strategy model of the desulfurization system according to the optimal working condition operation parameter data matched in the step S06; and providing an output value of the adjusting variable which reaches the optimum operation parameter and needs to be changed;
step S08: pushing the optimal working condition operation parameter value matched with the working condition type of the current desulfurization system to a DCS control system of the desulfurization system through MOBUS protocol, and achieving the aim of optimizing production through the DCS system;
The system also comprises data analysis algorithm based, and the data of the optimal operation parameters of the desulfurization system under different working conditions are mined, wherein the optimal operation parameter data comprise an optimal liquid-gas ratio, an optimal slurry circulating pump combination mode, an optimal PH value, an optimal resistance value, an optimal desulfurizing agent supply amount and an outlet sulfur value;
The step of establishing the control strategy model of the desulfurization system through the optimal working condition operation parameter data matched in the step S06 comprises the following steps: establishing a PH value-limestone desulfurizing agent flow cascade control model by taking the optimal PH value in the matched optimal working condition operation parameter data in the step S06 as a set value and making deviation with the PH value under the working condition of the current desulfurizing system;
the method further comprises the step of establishing an outlet sulfur-limestone desulfurizing agent flow cascade control model by taking the outlet sulfur emission value in the matched optimal working condition operation parameter data in the step S06 as a set value and making deviation with the outlet sulfur emission value of the current working condition;
And the method also comprises the step of adjusting the slurry circulating pump combination mode with the lowest non-energy consumption under the working condition of the current desulfurization system by the optimal slurry circulating pump combination collocation mode in the operation parameter data of the matched optimal working condition in the step S06.
2. An integrated control system for a wet desulfurization absorber system for carrying out the method of claim 1, comprising
The production data storage module is connected with the data preprocessing module and is used for storing historical production data of the desulfurization system collected by the production data collection module;
the data preprocessing module is used for selecting characteristic variables, and determining the characteristic variables by using a mechanism method, a pearson linear correlation algorithm and a PCA principal component analysis method through the data preprocessing module;
The working condition classification algorithm module is used for classifying each operation working condition of the desulfurization system through the classification algorithm model and calculating the optimal operation parameters of the desulfurization system under each working condition; the optimal operation parameter data under various working conditions are used as a benchmark, an optimal operation parameter prediction model is established through an RBF neural network, and partial parameter values are locally optimized;
the working condition classification knowledge base is used for storing the optimal operation parameter data under various working conditions provided by the working condition classification algorithm module;
the working condition classification module is used for identifying the working condition type of the current desulfurization system and selecting the best operation parameter data matched with the working condition type of the current desulfurization system from the working condition classification knowledge base;
the optimal parameter pushing module is used for pushing optimal operation parameter data matched with the working condition type of the current desulfurization system to the data communication subsystem;
the data communication subsystem comprises a communication sub-module, and the communication sub-module is used for sending the optimal operation parameter data matched with the working condition type of the current desulfurization system to the parameter receiving module;
The parameter receiving module is used for receiving the optimal operation parameter data sent by the communication sub-module;
The first acquisition data module is connected with the working condition classifying module, and the first acquisition data module is used for sending the acquired real-time working condition operation parameters to the working condition classifying module so as to find out the historical optimal working condition corresponding to the current working condition;
The second data acquisition module is connected with the calibration module, the acquired real-time working condition operation parameters are sent to the calibration module through the second data acquisition module, calibration is carried out on the optimal working conditions corresponding to the current working conditions pushed by the optimal parameter recommendation module of the absorption tower through the calibration module, and the optimal operation values of all control parameters under the current working conditions are provided according to the calibration result;
the control strategy module is used for establishing a control strategy model of the desulfurization system according to the provided optimal operation value, and calculating each control parameter to adjust the variable;
The first data communication module is used for pushing the control quantity of each parameter to be changed to the DCS control system of the desulfurization absorption tower when the working condition of the current desulfurization system reaches the optimal working condition under the working condition;
The DCS control system of the desulfurization absorption tower comprises a production data collection module, wherein the production data collection module is connected with a production data storage module and is used for collecting and storing historical production data of the desulfurization system for many years;
the DCS control system of the desulfurization absorption tower further comprises a real-time data acquisition module which is used for acquiring real-time working condition operation parameters of the current desulfurization system and is respectively connected with the first acquisition data module and the second acquisition data module;
the DCS control system of the desulfurization absorption tower further comprises a second data communication module which is connected with the first data communication module and is used for receiving the optimal working condition operation parameter data pushed by the first data communication module and sending the optimal working condition operation parameter data to the instruction control module;
the DCS control system of the desulfurization absorption tower further comprises an instruction control module which is used for controlling the operation state of each device of the desulfurization system and adjusting and controlling the operation parameters of each device of the desulfurization system according to the optimal working condition operation parameter data sent by the second data communication module.
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