CN106569517B - Coking exhuast gas desulfurization procedure optimization control method - Google Patents
Coking exhuast gas desulfurization procedure optimization control method Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 170
- 238000006477 desulfuration reaction Methods 0.000 title claims abstract description 84
- 230000023556 desulfurization Effects 0.000 title claims abstract description 83
- 238000005457 optimization Methods 0.000 title claims abstract description 25
- 238000004939 coking Methods 0.000 title claims abstract description 20
- 239000003546 flue gas Substances 0.000 claims abstract description 60
- UGFAIRIUMAVXCW-UHFFFAOYSA-N Carbon monoxide Chemical compound [O+]#[C-] UGFAIRIUMAVXCW-UHFFFAOYSA-N 0.000 claims abstract description 59
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 claims abstract description 58
- VHUUQVKOLVNVRT-UHFFFAOYSA-N Ammonium hydroxide Chemical compound [NH4+].[OH-] VHUUQVKOLVNVRT-UHFFFAOYSA-N 0.000 claims abstract description 39
- 239000000908 ammonium hydroxide Substances 0.000 claims abstract description 39
- 239000007788 liquid Substances 0.000 claims abstract description 38
- 239000007789 gas Substances 0.000 claims abstract description 23
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 claims abstract description 14
- 239000001301 oxygen Substances 0.000 claims abstract description 14
- 229910052760 oxygen Inorganic materials 0.000 claims abstract description 14
- 239000000779 smoke Substances 0.000 claims abstract description 11
- 230000003247 decreasing effect Effects 0.000 claims abstract description 8
- 238000003062 neural network model Methods 0.000 claims abstract description 8
- 230000005540 biological transmission Effects 0.000 claims description 20
- 238000013404 process transfer Methods 0.000 claims description 17
- 239000005864 Sulphur Substances 0.000 claims description 10
- 230000010355 oscillation Effects 0.000 claims description 9
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 8
- 238000013528 artificial neural network Methods 0.000 claims description 8
- 239000011159 matrix material Substances 0.000 claims description 8
- 238000012546 transfer Methods 0.000 claims description 5
- GWEVSGVZZGPLCZ-UHFFFAOYSA-N Titan oxide Chemical compound O=[Ti]=O GWEVSGVZZGPLCZ-UHFFFAOYSA-N 0.000 claims description 4
- 230000003467 diminishing effect Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 241000790917 Dioxys <bee> Species 0.000 claims description 2
- 239000004408 titanium dioxide Substances 0.000 claims description 2
- 238000012850 discrimination method Methods 0.000 claims 1
- 230000007613 environmental effect Effects 0.000 abstract description 4
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 18
- 229910021529 ammonia Inorganic materials 0.000 description 9
- 238000005259 measurement Methods 0.000 description 6
- MWUXSHHQAYIFBG-UHFFFAOYSA-N nitrogen oxide Inorganic materials O=[N] MWUXSHHQAYIFBG-UHFFFAOYSA-N 0.000 description 6
- CBENFWSGALASAD-UHFFFAOYSA-N Ozone Chemical compound [O-][O+]=O CBENFWSGALASAD-UHFFFAOYSA-N 0.000 description 5
- 230000003009 desulfurizing effect Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- XSQUKJJJFZCRTK-UHFFFAOYSA-N Urea Chemical compound NC(N)=O XSQUKJJJFZCRTK-UHFFFAOYSA-N 0.000 description 4
- 239000004202 carbamide Substances 0.000 description 4
- 238000001514 detection method Methods 0.000 description 4
- 230000032683 aging Effects 0.000 description 3
- TXKMVPPZCYKFAC-UHFFFAOYSA-N disulfur monoxide Inorganic materials O=S=S TXKMVPPZCYKFAC-UHFFFAOYSA-N 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 239000007921 spray Substances 0.000 description 3
- 239000000126 substance Substances 0.000 description 3
- XTQHKBHJIVJGKJ-UHFFFAOYSA-N sulfur monoxide Chemical compound S=O XTQHKBHJIVJGKJ-UHFFFAOYSA-N 0.000 description 3
- QAOWNCQODCNURD-UHFFFAOYSA-N Sulfuric acid Chemical compound OS(O)(=O)=O QAOWNCQODCNURD-UHFFFAOYSA-N 0.000 description 2
- 239000006096 absorbing agent Substances 0.000 description 2
- BFNBIHQBYMNNAN-UHFFFAOYSA-N ammonium sulfate Chemical compound N.N.OS(O)(=O)=O BFNBIHQBYMNNAN-UHFFFAOYSA-N 0.000 description 2
- 229910052921 ammonium sulfate Inorganic materials 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 2
- 235000019504 cigarettes Nutrition 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 230000001537 neural effect Effects 0.000 description 2
- 239000002245 particle Substances 0.000 description 2
- 238000011084 recovery Methods 0.000 description 2
- 230000001105 regulatory effect Effects 0.000 description 2
- 229910052717 sulfur Inorganic materials 0.000 description 2
- AOSFMYBATFLTAQ-UHFFFAOYSA-N 1-amino-3-(benzimidazol-1-yl)propan-2-ol Chemical compound C1=CC=C2N(CC(O)CN)C=NC2=C1 AOSFMYBATFLTAQ-UHFFFAOYSA-N 0.000 description 1
- QGZKDVFQNNGYKY-UHFFFAOYSA-O Ammonium Chemical compound [NH4+] QGZKDVFQNNGYKY-UHFFFAOYSA-O 0.000 description 1
- PQUCIEFHOVEZAU-UHFFFAOYSA-N Diammonium sulfite Chemical compound [NH4+].[NH4+].[O-]S([O-])=O PQUCIEFHOVEZAU-UHFFFAOYSA-N 0.000 description 1
- 239000002250 absorbent Substances 0.000 description 1
- 230000002745 absorbent Effects 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 235000011130 ammonium sulphate Nutrition 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 230000002068 genetic effect Effects 0.000 description 1
- 239000004615 ingredient Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000003064 k means clustering Methods 0.000 description 1
- 210000004218 nerve net Anatomy 0.000 description 1
- 230000007935 neutral effect Effects 0.000 description 1
- 230000003647 oxidation Effects 0.000 description 1
- 238000007254 oxidation reaction Methods 0.000 description 1
- 231100000719 pollutant Toxicity 0.000 description 1
- 238000000746 purification Methods 0.000 description 1
- 238000013139 quantization Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000006722 reduction reaction Methods 0.000 description 1
- 238000007670 refining Methods 0.000 description 1
- 238000010992 reflux Methods 0.000 description 1
- 238000005507 spraying Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D21/00—Control of chemical or physico-chemical variables, e.g. pH value
- G05D21/02—Control of chemical or physico-chemical variables, e.g. pH value characterised by the use of electric means
-
- 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
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D2251/00—Reactants
- B01D2251/20—Reductants
- B01D2251/206—Ammonium compounds
- B01D2251/2062—Ammonia
-
- 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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- Automation & Control Theory (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
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- Environmental & Geological Engineering (AREA)
- Computer Vision & Pattern Recognition (AREA)
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Abstract
The present invention relates to a kind of coking exhuast gas desulfurization procedure optimization control methods applied to desulfurization and denitrification integral process device.Wherein, this method includes：According to the flue-gas temperature of desulfurization and denitrification integral process device portal, flue gas flow, oxygen content of smoke gas and sulfur dioxide concentration, using fuzzy recognition algorithm, current working is determined；The method successively decreased using variable step determines the optimal pH value of the desulfurization absorbing liquid under current working；The ammonium hydroxide compensation rate under current working is determined using neural network model；Based on the sulfur dioxide concentration of desulfurization and denitrification integral process device outlet, the ammonium hydroxide controlled quentity controlled variable under current working is determined using inner membrance control method；Optimal pH value based on desulfurization absorbing liquid, with reference to ammonium hydroxide compensation rate and ammonium hydroxide controlled quentity controlled variable, to control the pH value of desulfurization absorbing liquid.The embodiment of the present invention improves the rapidity and accuracy of control, and desulfurization and denitrification integral process device is made to operate in the state of most economical environmental protection, reduces operating cost.
Description
Technical field
The present invention relates to technical field of industrial control more particularly to a kind of coking exhuast gas desulfurization procedure optimization control methods.
Background technology
Sulfur dioxide and nitrogen oxides are main atmosphere pollutions, are the principal elements for influencing air quality.China is
Maximum coking producing country in the world, due to history, for a long time, domestic coking industry coking flue gas is all without desulfurization
Denitration process and be directly discharged into air, become one of important source of atmosphere pollution.Formally implement from 1 day January in 2015《Refining
Coking pollutant emission standard》The discharge index of sulfur dioxide and nitrogen oxides to coking industry proposes stringent and clear and definite
Quantization requirement.
Certain coke-oven plant takes the lead in using the desulfurization of wet-type ammonia forced turbulent in the country and forces oxidation urea denitrification integral work
A kind of important means of the process and equipment (abbreviation desulfurization and denitrification integral process device) as processing coking industry flue gas.The technique fills
Putting the equipment included has air-introduced machine, heat recovery boiler, booster fan, desulfurizing tower, denitrating tower, ammonium sulfate circulating slot, solid-liquid point
From the relevant devices such as device, urea dissolving tank, pipeline and auxiliary pump, Detection of Process Parameters device, procedure parameter regulating device, DCS
(Distributed Control System, dcs or Distributed Control System are a kind of computer control to system
System) etc. (as shown in Figure 1).
The technical process of above-mentioned process unit is as follows：
Flue gas in process of coking is sent into heat recovery boiler through air-introduced machine, and flue-gas temperature is down to 160 DEG C of left sides by 300 DEG C
The right side by booster fan, is converged, the part NO and ozone in flue gas are quickly anti-before desulfurizing tower is entered with ozone input channel
NO should be generated2.Flue gas enters desulfurizing tower enriching section, by spraying, wash, is cooled to 60 DEG C or so, then enters through gas cap de-
The absorber portion of sulphur tower, the desulfurization absorbing liquid counter current contacting with top spray；SO in flue gas2It is anti-with the ammonium sulfite in absorbent
Ammonium bisulfite, SO should be generated2It is able to removing purification.The liquid reflux of absorber portion bottom is to the reservoir of desulfurization tower bottom.For
Restore the absorbability of absorbing liquid, need to supplement ammonium hydroxide.Desulfurizing tower top spray technique keeps the liquid level of reservoir in reasonable model
In enclosing.Liquid storage trench bottom blasts air, by the part (NH in reservoir4)2SO3It is oxidized to (NH4)2SO4, for sulfuric acid in enriching section
Spray-the evaporation-concentration and subsequent processing of ammonium.
Flue after desulfurization is connect with ozone input channel, the ozone mixed into 60 DEG C or so of flue gas after desulfurization,
Part NO in flue gas generates NO with ozone fast reaction2, denitrating tower lower part is subsequently entered, the urea with denitrating tower top spray
Solution counter current contacting, NO, NO2Reduction reaction generation N occurs with the urea in solution2、CO2And H2O completes denitration.Reach environmental protection
The flue gas of discharge standard is discharged into air at the top of denitrating tower, so as to complete whole processing procedures of flue gas.
The above process can be divided into two subprocess, i.e. sweetening process and denitrification process.For sweetening process, to obtain
Higher desulfuration efficiency, the most important pH value for seeking to absorbing liquid in control tower, because it is to SO in flue gas in tower2Absorption
There is most direct influence.And there are following Railway Projects for the control of its sweetening process at this stage：1st, controlled variable is directly net
SO in flue gas after change2Concentration, and (proportional integral differential control, P represent ratio, and I represents integration, D only with simple PID
Represent differential) control, overshoot is very big with lag, can not ensure the stability and accuracy of control completely；2nd, process of coking has
Sufficiently complex working condition, causes its multi-state characteristic, the index errors such as temperature, flow, concentration of flue gas under different operating modes
It is different very big；3rd, the requirement that pH value is only defined in technological requirement is 4.5-6.5, and range is excessive and does not account for different flue gas conditions
Under difference, cause a large amount of wastes even the escaping of ammonia of raw material, be unfavorable for economy, the rings of desulfurization and denitrification integral process device
Protect operation.
In view of this, it is special to propose the present invention.
Invention content
In order to solve the above problem of the prior art, in order to solve how to ensure sweetening process in most economical environmental protection
Under the conditions of the technical issues of steadily carrying out and a kind of coking exhuast gas desulfurization procedure optimization control method is provided.
To achieve these goals, following technical scheme is provided：
A kind of coking exhuast gas desulfurization procedure optimization control method, the optimal control method are applied to desulfurization and denitrification integral
Process unit, the control method include：
According to the flue-gas temperature of the desulfurization and denitrification integral process device portal, flue gas flow, oxygen content of smoke gas and two
Sulfur oxide concentration using fuzzy recognition algorithm, determines current working；
The method successively decreased using variable step determines the optimal pH value of the desulfurization absorbing liquid under the current working；
The ammonium hydroxide compensation rate under the current working is determined using neural network model；
Based on the sulfur dioxide concentration of desulfurization and denitrification integral process device outlet, determined using inner membrance control method
Ammonium hydroxide controlled quentity controlled variable under the current working；
Based on the optimal pH value of the desulfurization absorbing liquid, with reference to the ammonium hydroxide compensation rate and the ammonium hydroxide controlled quentity controlled variable, to control
Make the pH value of the desulfurization absorbing liquid.
Preferably, it is described according to the flue-gas temperature of the desulfurization and denitrification integral process device portal, flue gas flow, flue gas
Oxygen content and sulfur dioxide concentration using fuzzy recognition algorithm, determine current working, specifically include：
The flue-gas temperature, the flue gas flow, the oxygen content of smoke gas and the sulfur dioxide concentration are set as shape
State vector；
It is clustered based on the state vector, determines sorting criterion, and passed through the sorting criterion and obtain state set；
By weighted fuzzy identification algorithm, the fuzzy membership relationship square of the state vector and the state set is obtained
Battle array；
Based on the fuzzy membership relational matrix, the current working is determined by maximum membership grade principle.
Preferably, the method successively decreased using variable step determines the optimal of desulfurization absorbing liquid under the current working
PH value specifically includes：
Determine the optimal pH value of the desulfurization absorbing liquid under the current working according to the following formula using variable step diminishing method：
In formula, the n represents iterations, n>=2；The PHnRepresent pH value during nth iteration；The PHn-1Table
Show pH value during (n-1)th iteration；The WmaxWith the WminThe maximum and minimum value of step-length is represented respectively；The knIt represents to work as
Preceding iterations；The kmaxRepresent maximum iteration；After t0 represents the desulfurization and denitrification integral process device stable operation
Initial time；The P (t0) represents the desulfurization and denitrification integral process device exiting flue gas sulfur dioxide concentration value；It is described
PLimitRepresent the sulfur dioxide concentration value limited；The T represents the sampling period；The ε represents to terminate threshold value.
Preferably, the neural network model is the model of multiple radial basis function neural networks parallel connection.
Preferably, the sulfur dioxide concentration based on the outlet of desulfurization and denitrification integral process device, is controlled using inner membrance
Method determines the ammonium hydroxide controlled quentity controlled variable under current working, specifically includes：
Using closed loop two channel relay feedback frequency domain identification method, to establish desulphurization denitration process transfer function model；
Using the desulphurization denitration process transfer function model, based on desulfurization and denitrification integral process device outlet
Sulfur dioxide concentration using internal model control method, determines ammonium hydroxide controlled quentity controlled variable.
Preferably, it is described to use closed loop two channel relay feedback frequency domain identification method, it is transmitted to establish desulphurization denitration process
Function model specifically includes：
According to the ammonium hydroxide addition during the desulphurization denitration and the output of limit cycles oscillations, estimated using Fourier transform
Meter obtains the frequency response estimation of the desulphurization denitration process；
Estimated according to the frequency response of the sweetening process, using identification algorithm and nonlinear optimization algorithm, estimated de-
Sulphur denitrification process transfer function model.
Preferably, it is described to be estimated according to the frequency response of the sweetening process, it is calculated using identification algorithm and nonlinear optimization
Method estimates desulphurization denitration process transfer function model, specifically includes：
Estimated according to the frequency response of sweetening process, determine following object function：
Wherein, the ciRepresent weights；The m represents selected phase number；It is describedRepresent by binary channels after
Electrical characteristics test, in ωiUnder Multiple points frequency response estimation；G (the j ωi) represent frequency characteristic to be estimated；The J tables
Show the object function；
Based on object function, using identification algorithm, transmission function is obtained；
Using nonlinear optimization algorithm, the constant in the transmission function is solved, so that it is determined that the desulphurization denitration process
Transfer function model.
Preferably, the transmission function adds lag transmission function for one order inertia；
It is described to use nonlinear optimization algorithm, the constant in the transmission function is solved, so that it is determined that the desulphurization denitration
Process transfer function model, specifically includes：Using nonlinear optimization algorithm, solve the proportionality constant in the transmission function, be used to
Property constant and hysteresis constant, so that it is determined that the one order inertia of the desulphurization denitration process adds lag transfer function model.
It is excellent that the embodiment of the present invention provides a kind of coking exhuast gas desulfurization process applied to desulfurization and denitrification integral process device
Change control method.This method includes：According to the flue-gas temperature of desulfurization and denitrification integral process device portal, flue gas flow, flue gas
Oxygen content and sulfur dioxide concentration using fuzzy recognition algorithm, determine current working；The method successively decreased using variable step is determined
The optimal pH value of desulfurization absorbing liquid under current working；The ammonium hydroxide compensation rate under current working is determined using neural network model；
Based on the sulfur dioxide concentration of desulfurization and denitrification integral process device outlet, determined under current working using inner membrance control method
Ammonium hydroxide controlled quentity controlled variable；Optimal pH value based on desulfurization absorbing liquid, with reference to ammonium hydroxide compensation rate and ammonium hydroxide controlled quentity controlled variable, desulfurization to be controlled to absorb
The pH value of liquid.The embodiment of the present invention is using pH value as controlled variable, using the internal model control knot compensated with feedforward neural network
Structure substantially increases the rapidity and accuracy of control, ensures that the SO2 contents of flue gas are controlled in the case where limiting index；It is walked using becoming
The long strategy for successively decreasing change PH setting values optimizes sweetening process, can reach SO2 concentration of flue gas and limit under index, also
The phenomenon that ammonium hydroxide consumption can be minimized, avoid the escaping of ammonia, occurs, and desulfurization and denitrification integral process device is made to operate in most
In the state of economic and environment-friendly, the control and optimization of sweetening process are realized, reduces operating cost.
Description of the drawings
Fig. 1 is the schematic diagram of desulfurization and denitrification integral process device；
Fig. 2 is the flow diagram of the coking exhuast gas desulfurization procedure optimization control method according to the embodiment of the present invention；
Fig. 3 is the structure diagram of the closed loop two channel relay feedback according to the embodiment of the present invention；
Fig. 4 is the structure diagram of the two channel relay according to the embodiment of the present invention.
Specific embodiment
The preferred embodiment of the present invention described with reference to the accompanying drawings.It will be apparent to a skilled person that this
A little embodiments are used only for explaining the technical principle of the present invention, it is not intended that limit the scope of the invention.
The basic thought of the embodiment of the present invention is：Using desulfurization absorbing liquid pH value as controlled variable, ammonia spirit adds in stream
Amount is as variable is controlled, using the internal model control structure with feedforward compensation, meanwhile, by corresponding optimisation strategy, control is de-
The pH value of sulphur absorbing liquid finds optimal pH value under current working, so as to ensure desulfurization and denitrification integral process device most economical
It is steadily transported under the condition (sulfur dioxide concentration is in indication range and desulfurization absorbing liquid pH value is in neutral range for outlet) of environmental protection
Row.
The embodiment of the present invention proposes a kind of coking exhuast gas desulfurization procedure optimization control method.This method is applied to desulphurization denitration
Integral process device, as shown in Fig. 2, this method can include：
S100：According to the flue-gas temperature of desulfurization and denitrification integral process device portal, flue gas flow, oxygen content of smoke gas and two
Sulfur oxide concentration using fuzzy recognition algorithm, determines current working.
Sweetening process is divided into different operating modes, such as operating mode S1, operating mode S2, operating mode S3 by this step.Wherein, operating mode S1 can be with
It is dense including first entrance flue-gas temperature, first entrance flue gas flow, first entrance oxygen content of smoke gas and first entrance sulfur dioxide
Degree.Operating mode S2 can include second entrance flue-gas temperature, second entrance flue gas flow, second entrance oxygen content of smoke gas and second and enter
Mouth sulfur dioxide concentration.And so on, it may be determined that other operating modes.The embodiment of the present invention replaces operating mode with classification code name.
The flow velocity of flue gas, grey density characteristics are different under different operating modes, and specific category number is depending on actual conditions.
Above-mentioned fuzzy recognition algorithm is preferably weighted fuzzy identification algorithm.
By taking weighted fuzzy identification algorithm as an example, the step of determining current working, can include：
S101：By the flue-gas temperature of desulfurization and denitrification integral process device portal, flue gas flow, oxygen content of smoke gas and dioxy
Change sulphur concentration and be set as state vector.
S102：It carries out clustering determining sorting criterion based on state vector, state set is obtained by sorting criterion.
This step is clustered state vector as state sample collection.Clustering method can be the calculations such as K- mean values
Method.
Cluster process is described in detail by taking k- means clustering algorithms as an example below.
K (it takes positive integer) a object is first randomly selected as initial cluster centre.Then, calculate each object with it is each
The distance between a seed cluster centre distributes to each object the cluster centre nearest apart from it.It so constantly repeats, directly
To meeting end condition.
Using cluster result as sorting criterion namely the foundation of setting operating mode type.For example, if current historical data
4 classes are divided by clustering algorithm, then can determine total operating mode classification is S1, S2, S3, S4Class.Operating mode can will be divided into S by this step1,
S2... class obtains state set S, S={ S1, S2……Sn}.By operating mode division and recognition methods, according to cigarette under different operating modes
The difference of gas characteristic " divides and rule control problem ".
S103：By weighted fuzzy identification algorithm, the fuzzy membership relational matrix of state vector and state set is obtained.
As an example, fuzzy membership relational matrix can be as follows：
Wherein, in formula, rij=λR{ei, sj, 0≤rij≤ 1 (i, j=1,2,3 ... n) represent the state quilt in state vector
It is chosen as SjThe probability of operating mode；λRRepresent the probability function of state vector and state set.Define ri=w1×r1j+w2×r2j+...+wn
×rnj, wherein w1, w2 ... wn expression weights.
S104：Based on fuzzy membership relational matrix, current working is determined by maximum membership grade principle.
The process of determining operating mode is described in detail with a preferred embodiment below.
Set state vector E={ e1, e2, e3, e4, in formula, e1To e4Entrance flue gas temperature, inlet flue gas stream are represented respectively
Speed, entrance SO2Concentration and inlet flue gas oxygen content.
Sorting criterion is determined based on the cluster of state sample collection, state set S is obtained by sorting criterion；Operating mode is divided into
S1, S2, S3, S4Class.S={ S1, S2, S3, S4}。
By weighted fuzzy identification, the fuzzy membership relational matrix R of state vector and state set is obtained, i.e.,：
In formula, rij=λR{ei, sj, 0≤rij≤ 1 (i, j=1,2,3,4) represents the e in state vectoriDimension index quilt
It is chosen as SjThe probability of operating mode；λRRepresent the probability function of state vector and state set.Define ri=w1×r1j+w2×r2j+w3×r3j
+w4×r4j(wherein w represents weight, it is preferable that can take 0.15 respectively, 0.1,0.7,0.05) belong to S for the statejOperating mode it is general
Rate.
Fuzzy membership relational matrix R based on state vector and state set, can be determined by maximum membership grade principle
Current working.
For example, compare current state and the different degrees of membership of operating mode 1,2,3,4,5 be respectively 0.2,0.3,0.4,
0.5th, 0.6, wherein maximum membership degree is 0.6, it is determined that current state corresponds to operating mode 5, and operating mode 5 is determined as current working.
S110：The method successively decreased using variable step determines the optimal pH value of the desulfurization absorbing liquid under current working.
Specifically, this step can include：Determine that desulfurization is inhaled under current working according to the following formula using variable step diminishing method
Receive the optimal pH value of liquid：
In formula, n represents iterations (n>=2)；PHnRepresent pH value during nth iteration；PHn-1Represent (n-1)th time repeatedly
For when pH value；WmaxAnd WminThe maximum and minimum value of step-length is represented respectively；knRepresent current iteration number；kmaxRepresent maximum
Iterations preferably take 5.
Due to being required in technique, PH is typically chosen PH between 4.5 to 6.51=6；
Wherein,For stopping criterion for iteration.
In formula, t0 is represented after changing setting value, the initial time after desulfurization and denitrification integral process device stable operation；t0
It can be depending on actual conditions.Wherein, the condition of stable operation is：During desulphurization denitration, by extremely after regulated variable
It can just ensure that device enters the condition of even running phase within few 2 hours or more.P (t0) represents that desulfurization and denitrification integral process device goes out
Mouth flue gas SO2Concentration value；PLimitRepresent the SO limited2Concentration value, it is therefore preferable to be 50 (mg/m3)；N=60/T+1, wherein T is adopt
Sample period, i.e. n seek poor number for sampling in one hour；ε represents to terminate threshold value, preferably takes 10%, i.e., when lower hour of stable state
Interior mean error reaches within the 10% of limiting concentration.
When reaching stopping criterion for iteration, it is believed that pH value is optimal pH value at this time.
After optimal pH value is obtained, since presence can not survey disturbance factor, such as：Ammonia spirit concentration, detection error with
And since what the aging of desulfurization and denitrification integral process device, Changes in weather and other reasons generated can not measure uncontrollable disturbance
Deng minor change can occur for the optimal pH value.The embodiment of the present invention further takes indemnifying measure described below as a result,.
S120：The ammonium hydroxide compensation rate under current working is determined using neural network model.
Wherein, the structure of multiple neural network parallel connections may be used in neural network model.Preferably, neural network is radially
Basis function neural network (RBFNN).By using Parallel neural networks structure, the precision handled complex working condition can be improved,
The generalization ability of strength neural network (model).
By taking RBF neural as an example, in practical applications, three layers of RBF neural can be selected.Wherein it is possible to by defeated
Enter layer to be configured to comprising desulfurization absorbing liquid internal circulating load, flue-gas temperature, inlet flue gas flow velocity, inlet flue gas sulfur dioxide concentration, take off
Sulphur absorbing liquid pH value and the data acquisition system of inlet flue gas oxygen content and measurable disturbance；Gaussian function may be used as middle layer；
Then weights are multiplied by, you can exported, in embodiments of the present invention, exported as ammonium hydroxide compensation rate, i.e. ammonia spirit addition.
The number of ammonia spirit addition directly affects pH value.
The embodiment of the present invention is by obtaining ammonium hydroxide compensation rate, when thering is disturbance to occur or operating mode is changed, nerve net
Network is calculated ammonium hydroxide compensation rate rather than ammonium hydroxide controlled quentity controlled variable is calculated again after control system feedback at once.In this way
It can prevent control from lagging, ammonium hydroxide addition is made to play a role much sooner.
S130：It is true using inner membrance control method based on the sulfur dioxide concentration of desulfurization and denitrification integral process device outlet
Determine the ammonium hydroxide controlled quentity controlled variable under current working.
Specifically, this step can include：
S131：Using closed loop two channel relay feedback frequency domain identification method, to establish desulphurization denitration process transmission function mould
Type.
The adjusting process of pH value is a typical non-linear process, for example, in the implementation process of the present invention, PH can be with
For 4.5-6.5, in the range of this, according to the characteristic of pH value, it is approximately a linear process that can PH be adjusted process.Example
Such as：If pH value, 7 or so, adjusting process has apparent non-linear, and pH value is more remote from 7, the adjusting process of pH value
It is non-linear weaker.In actual industrial process, PH typically each in 4-5 or so, pH value from 7 farther out, so, the adjusting of pH value
Journey it is non-linear very weak.Therefore the adjusting process of pH value can be indicated with transmission function.
Again due to coking flue gas desulfurization and denitrification be one with strong disturbance big inertia and large time delay process, Open-loop Identification
Process model will inevitably be influenced by strong disturbance and the exceeded situation of flue gas emission occurs and occur.So present invention
Embodiment establishes desulphurization denitration process transfer function model using closed loop two channel relay feedback frequency domain identification method.
Fig. 3 schematically illustrates the structure diagram of closed loop two channel relay feedback.Wherein, TR represents binary channels relay
Characteristic；R represents desulfurization absorbing liquid target pH value；Ud represents ammonium hydroxide controlled quentity controlled variable；D represents that measurable disturbance is (not such as：Ammonia spirit is dense
What the reasons such as degree, detection error, the aging of desulfurization and denitrification integral process device, Changes in weather generated can not measure uncontrollable
Disturbance etc.)；Yp represents actual measurement pH value.Wherein, actual measurement pH value can be from being mounted on desulfurizing tower bottom to the pipeline of tower top transport absorbing liquid
In sensor measurement, and will be obtained in transmitting measured values to DCS system by the sensor.Two channel relay TR's
Structure is as shown in Figure 4.Wherein, the input of TR is e.Wherein, e=R-Yp, | e |≤ε.ε represents threshold value, for example it can be set as
0.1。
For desulphurization denitration process there are a stable operating point (namely steady operation point), which is current state,
It can make a series of value of variables that desulphurization denitration process is stablized.Such as：In industrial processes, each variable or parameter are inscribed when a certain
Setting value, such as current time, ammonium hydroxide addition is 50 cubes of meter per seconds, desulfurization absorbing liquid internal circulating load is 150 cubes of meter per seconds,
The operating point can be considered steady operation point.The meaning of setting steady operation point be when operating mode changes, can at once will be each
The required state value of operating mode after specification of variables to variation is conducive to the stability of desulfurization and denitrification integral process device operation.
Due to introducing nonlinear element in the structure of closed loop two channel relay feedback, so, TR structures can be near present operating point
There is limit cycles oscillations.Since the process of limit cycles oscillations is approximately linear process, so, the superposition of linear process can be utilized
Principle obtains the output of limit cycles oscillations, i.e.,Wherein,Represent the output of limit cycles oscillations；YpRepresent real
Survey pH value；R represents desulfurization absorbing liquid target pH value.Since limit cycles oscillations is a kind of controlled oscillation, so, frequency characteristic test
The not measurable disturbance occurred in the process can be controlled.
By adjusting the gain controllable pH value of TR, so discharge flue gas concentration is being required within limit value.The gain of TR is
For the hp and hi in above-mentioned Fig. 4, gain is different, and when being recognized, maximum-minimum value of PH is just different.For example, Ke Yishe
It is all 2 to put hp and hi, then the variation range of PH is 2-9, this range is unacceptable in practical applications.If hp is set
It is 0.5 with hi, then PH variation ranges are 4-5, this range is that can receive in practical applications.By adjusting the gain of TR
PH value is controlled, in this way when transfer function model is recognized, pH value amplitude will not be excessive.
S1311：According to the ammonium hydroxide addition during desulphurization denitration and the output of limit cycles oscillations, Fourier transform is utilized
Estimation obtains the frequency response estimation of desulphurization denitration process.
Denitration tower top is mounted on, and the measurement of the flue gas online chemical analysis instrument positioned at smoke outlet is made an uproar to overcome
Sound, improves the precision of estimation, and the embodiment of the present invention uses the frequency characteristic of the method calculating process of Fourier transform.Wherein, cigarette
Gas online chemical analysis instrument is used for measuring outlet flue gas concentration, i.e., for measurements of sulfur dioxide concentrations law.Flue gas online ingredient point
The sulfur dioxide concentration of measurement is uploaded to DCS system by analyzer table.
As an example, the Fourier transform of input/output signal is determined according to the following formula：
Wherein, u (t) represents input signal；Y (t) represents output signal；F represents Fourier transform；T0Represent time-domain signal
It is T in the period to be0Periodic signal；ω0Represent fundamental frequency, n round numbers.
Fundametal compoment, i.e. n=1, ω=ω can be taken0Situation, then can determine that the frequency response of sweetening process is estimated as：
G (j ω in above formula0) represent frequency characteristic to be estimated in transmission function.
For example, in practical applications, frequency characteristic estimation can be obtainedIts
In,Represent tested by two channel relay, in ωiUnder frequency characteristic estimation (preferably multiple spot frequency is special
Property estimation).
S1312：Estimated according to the frequency response of sweetening process, using identification algorithm and nonlinear optimization algorithm, estimated
Desulphurization denitration process transfer function model.
It is preferably carried out in mode at some, this step can specifically include：
S13121：Estimated according to the frequency response of sweetening process, determine following object function：
Wherein ciRepresent weights；M represents selected phase number；That expression is tested by two channel relay,
In ωiUnder Multiple points frequency response estimation；G(jωi) represent frequency characteristic to be estimated；J represents object function.
By above-mentioned object function, estimation becomes a nonlinear optimal problem.
S13122：Based on object function, using identification algorithm, transmission function is obtained.
S13123：Using nonlinear optimization algorithm, the constant in above-mentioned transmission function is solved, so that it is determined that transmission function mould
Type.
The process of determining transfer function model is described in detail with a preferred embodiment below.
Step A：Based on object function, using identification algorithm, obtain following one order inertia and add lag transmission function：
Wherein, Gp(s) Laplace transform of the ratio between output and input is represented；K represents proportionality constant；T represents that inertia is normal
Number；τ represents hysteresis constant.
Wherein, identification algorithm includes but not limited to least square method, particle swarm optimization algorithm.
Step B：Using nonlinear optimization algorithm, proportionality constant, inertia constant and lag in above-mentioned transmission function are solved
Constant, so that it is determined that the one order inertia of desulphurization denitration process adds lag transfer function model.
Above-mentioned nonlinear optimization algorithm includes but not limited to particle cluster algorithm, genetic algorithm.
By using closed loop two channel relay feedback (being abbreviated as TRF) frequency domain identification method, the embodiment of the present invention can be with
The controlled mode of closed loop obtains the Multiple points frequency response of sweetening process according to specified phase, and then estimates to obtain sweetening process
Transfer function model.
S132：Using desulphurization denitration process transfer function model, two exported based on desulfurization and denitrification integral process device
Sulfur oxide concentration using internal model control method, determines ammonium hydroxide controlled quentity controlled variable.
Wherein, inner membrance control method may refer to《Internal model control and its application》, Electronic Industry Press no longer goes to live in the household of one's in-laws on getting married herein
It states.
This step is based on desulphurization denitration process transfer function model, using internal model control method, structure feedback filter and
Internal mode controller.The titanium dioxide that desulfurization and denitrification integral process device can be exported using feedback filter and internal mode controller
Sulphur concentration is controlled in index.
Wherein, feedback filter uses single order form：α represents constant.Feedback filtering
Device is used for feedback filtering in internal model control, can improve robustness.
S140：Optimal pH value based on desulfurization absorbing liquid, with reference to ammonium hydroxide compensation rate and ammonium hydroxide controlled quentity controlled variable, desulfurization to be controlled to inhale
Receive the pH value of liquid.
Since presence can not survey disturbance factor, such as：Ammonia spirit concentration, detection error and due to desulphurization denitration one
What the aging of chemical industry process and equipment, Changes in weather and other reasons generated can not measure uncontrollable disturbance etc., this step is being taken off
On the basis of the optimal pH value of sulphur absorbing liquid, ammonium hydroxide compensation rate and ammonium hydroxide controlled quentity controlled variable are added in, so as to control desulfurization absorbing liquid
PH value, and then realize the optimal control to coking exhuast gas desulfurization process.
Although each step is described in the way of above-mentioned precedence in above-described embodiment, this field
Technical staff is appreciated that the effect in order to realize the present embodiment, is performed between different steps not necessarily in such order,
It (parallel) execution simultaneously or can be performed with reverse order, these simple variations all protection scope of the present invention it
It is interior.
So far, it has been combined preferred embodiment shown in the drawings and describes technical scheme of the present invention, still, this field
Technical staff is it is easily understood that protection scope of the present invention is expressly not limited to these specific embodiments.Without departing from this
Under the premise of the principle of invention, those skilled in the art can make the relevant technologies feature equivalent change or replacement, these
Technical solution after changing or replacing it is fallen within protection scope of the present invention.
Claims (8)
1. a kind of coking exhuast gas desulfurization procedure optimization control method, the optimal control method is applied to desulfurization and denitrification integral work
Process and equipment, which is characterized in that the control method includes：
According to flue-gas temperature, flue gas flow, oxygen content of smoke gas and the titanium dioxide of the desulfurization and denitrification integral process device portal
Sulphur concentration using fuzzy recognition algorithm, determines current working；
The method successively decreased using variable step determines the optimal pH value of the desulfurization absorbing liquid under the current working；
The ammonium hydroxide compensation rate under the current working is determined using neural network model；
Based on the sulfur dioxide concentration of desulfurization and denitrification integral process device outlet, determined using internal model control method described
Ammonium hydroxide controlled quentity controlled variable under current working；
Based on the optimal pH value of the desulfurization absorbing liquid, with reference to the ammonium hydroxide compensation rate and the ammonium hydroxide controlled quentity controlled variable, to control
State the pH value of desulfurization absorbing liquid.
2. optimal control method according to claim 1, which is characterized in that described according to the desulfurization and denitrification integral work
Flue-gas temperature, flue gas flow, oxygen content of smoke gas and the sulfur dioxide concentration of process and equipment entrance using fuzzy recognition algorithm, determine
Current working specifically includes：
By the flue-gas temperature, the flue gas flow, the oxygen content of smoke gas and the sulfur dioxide concentration be set as state to
Amount；
It is clustered based on the state vector, determines sorting criterion, and passed through the sorting criterion and obtain state set；
By weighted fuzzy identification algorithm, the fuzzy membership relational matrix of the state vector and the state set is obtained；
Based on the fuzzy membership relational matrix, the current working is determined by maximum membership grade principle.
3. optimal control method according to claim 1, which is characterized in that the method successively decreased using variable step, really
The optimal pH value of desulfurization absorbing liquid under the fixed current working, specifically includes：
Determine the optimal pH value of the desulfurization absorbing liquid under the current working according to the following formula using variable step diminishing method：
In formula, the n represents iterations, n>=2, n=60/T+1；The PHnRepresent pH value during nth iteration；It is described
PHn-1Represent pH value during (n-1)th iteration；The WmaxWith the WminThe maximum and minimum value of step-length is represented respectively；The kn
Represent current iteration number；The kmaxRepresent maximum iteration；T0 represents that the desulfurization and denitrification integral process device is stablized
Postrun initial time；The P (t0) represents the desulfurization and denitrification integral process device exiting flue gas sulfur dioxide concentration
Value；The PLimitRepresent the sulfur dioxide concentration value limited；The T represents the sampling period；The ε represents to terminate threshold value.
4. optimal control method according to claim 1, which is characterized in that the neural network model is multiple radial direction bases
The model of Function Neural Network parallel connection.
5. optimal control method according to claim 1, which is characterized in that described to be filled based on desulfurization and denitrification integral process
The sulfur dioxide concentration of outlet is put, the ammonium hydroxide controlled quentity controlled variable under current working is determined using internal model control method, is specifically included：
Using closed loop two channel relay feedback frequency domain identification method, to establish desulphurization denitration process transfer function model；
Using the desulphurization denitration process transfer function model, the dioxy based on desulfurization and denitrification integral process device outlet
Change sulphur concentration, using internal model control method, determine ammonium hydroxide controlled quentity controlled variable.
6. optimal control method according to claim 5, which is characterized in that described using closed loop two channel relay feedback frequency
Domain discrimination method to establish desulphurization denitration process transfer function model, specifically includes：
According to the ammonium hydroxide addition during the desulphurization denitration and the output of limit cycles oscillations, estimated using Fourier transform
Frequency response to the desulphurization denitration process is estimated；
Estimated according to the frequency response of the desulphurization denitration process, using identification algorithm and nonlinear optimization algorithm, estimated de-
Sulphur denitrification process transfer function model.
7. optimal control method according to claim 6, which is characterized in that the frequency according to the desulphurization denitration process
Rate response estimation, using identification algorithm and nonlinear optimization algorithm, estimates desulphurization denitration process transfer function model, specific to wrap
It includes：
Estimated according to the frequency response of sweetening process, determine following object function：
Wherein, the ciRepresent weights；The m represents selected phase number；It is describedRepresent special by binary channels relay
Property test, in ωiUnder Multiple points frequency response estimation；G(jωi) represent frequency characteristic to be estimated；The J represents the mesh
Scalar functions；
Based on object function, using identification algorithm, transmission function is obtained；
Using nonlinear optimization algorithm, the constant in the transmission function is solved, so that it is determined that the desulphurization denitration process is transmitted
Function model.
8. optimal control method according to claim 7, which is characterized in that the transmission function adds lag for one order inertia
Transmission function；
It is described to use nonlinear optimization algorithm, the constant in the transmission function is solved, so that it is determined that the desulphurization denitration process
Transfer function model specifically includes：Using nonlinear optimization algorithm, proportionality constant, the inertia solved in the transmission function is normal
Number and hysteresis constant, so that it is determined that the one order inertia of the desulphurization denitration process adds lag transfer function model.
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