CN107844863B - Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme - Google Patents
Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme Download PDFInfo
- Publication number
- CN107844863B CN107844863B CN201711127658.9A CN201711127658A CN107844863B CN 107844863 B CN107844863 B CN 107844863B CN 201711127658 A CN201711127658 A CN 201711127658A CN 107844863 B CN107844863 B CN 107844863B
- Authority
- CN
- China
- Prior art keywords
- superheater
- pipeline
- time
- determining
- tube
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000004140 cleaning Methods 0.000 title claims abstract description 25
- 239000000126 substance Substances 0.000 title claims abstract description 20
- 238000013461 design Methods 0.000 title claims abstract description 8
- 238000004880 explosion Methods 0.000 claims abstract description 64
- 238000006243 chemical reaction Methods 0.000 claims abstract description 58
- 238000005554 pickling Methods 0.000 claims abstract description 56
- 239000002253 acid Substances 0.000 claims abstract description 41
- 230000036632 reaction speed Effects 0.000 claims abstract description 24
- 230000012010 growth Effects 0.000 claims abstract description 23
- 238000013178 mathematical model Methods 0.000 claims abstract description 14
- 230000003068 static effect Effects 0.000 claims abstract description 8
- 238000012360 testing method Methods 0.000 claims abstract description 8
- VEXZGXHMUGYJMC-UHFFFAOYSA-N Hydrochloric acid Chemical compound Cl VEXZGXHMUGYJMC-UHFFFAOYSA-N 0.000 claims description 98
- 238000013058 risk prediction model Methods 0.000 claims description 18
- 239000010410 layer Substances 0.000 claims description 17
- 238000005406 washing Methods 0.000 claims description 12
- 229910052751 metal Inorganic materials 0.000 claims description 10
- 239000002184 metal Substances 0.000 claims description 10
- 239000007788 liquid Substances 0.000 claims description 7
- 239000011159 matrix material Substances 0.000 claims description 7
- 239000000758 substrate Substances 0.000 claims description 6
- 238000005520 cutting process Methods 0.000 claims description 5
- 238000009826 distribution Methods 0.000 claims description 5
- UQSXHKLRYXJYBZ-UHFFFAOYSA-N iron oxide Inorganic materials [Fe]=O UQSXHKLRYXJYBZ-UHFFFAOYSA-N 0.000 claims description 5
- 239000013598 vector Substances 0.000 claims description 5
- 239000002356 single layer Substances 0.000 claims description 4
- 238000007476 Maximum Likelihood Methods 0.000 claims description 3
- JEIPFZHSYJVQDO-UHFFFAOYSA-N iron(III) oxide Inorganic materials O=[Fe]O[Fe]=O JEIPFZHSYJVQDO-UHFFFAOYSA-N 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 19
- LPXPTNMVRIOKMN-UHFFFAOYSA-M sodium nitrite Chemical compound [Na+].[O-]N=O LPXPTNMVRIOKMN-UHFFFAOYSA-M 0.000 description 10
- 238000002161 passivation Methods 0.000 description 7
- VHUUQVKOLVNVRT-UHFFFAOYSA-N Ammonium hydroxide Chemical compound [NH4+].[OH-] VHUUQVKOLVNVRT-UHFFFAOYSA-N 0.000 description 6
- 235000011114 ammonium hydroxide Nutrition 0.000 description 6
- 235000010288 sodium nitrite Nutrition 0.000 description 5
- 230000003647 oxidation Effects 0.000 description 4
- 238000007254 oxidation reaction Methods 0.000 description 4
- 239000002245 particle Substances 0.000 description 4
- 238000002360 preparation method Methods 0.000 description 4
- 239000002932 luster Substances 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- VKYKSIONXSXAKP-UHFFFAOYSA-N hexamethylenetetramine Chemical compound C1N(C2)CN3CN1CN2C3 VKYKSIONXSXAKP-UHFFFAOYSA-N 0.000 description 2
- 239000002699 waste material Substances 0.000 description 2
- 238000009825 accumulation Methods 0.000 description 1
- QGZKDVFQNNGYKY-UHFFFAOYSA-N ammonia Natural products N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 description 1
- QVGXLLKOCUKJST-UHFFFAOYSA-N atomic oxygen Chemical compound [O] QVGXLLKOCUKJST-UHFFFAOYSA-N 0.000 description 1
- 230000009172 bursting Effects 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005474 detonation Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005315 distribution function Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- SZVJSHCCFOBDDC-UHFFFAOYSA-N ferrosoferric oxide Chemical compound O=[Fe]O[Fe]O[Fe]=O SZVJSHCCFOBDDC-UHFFFAOYSA-N 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 238000010438 heat treatment Methods 0.000 description 1
- 239000003112 inhibitor Substances 0.000 description 1
- 238000009413 insulation Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 229910052760 oxygen Inorganic materials 0.000 description 1
- 239000001301 oxygen Substances 0.000 description 1
- 239000012466 permeate Substances 0.000 description 1
- 238000004886 process control Methods 0.000 description 1
- 229920006395 saturated elastomer Polymers 0.000 description 1
- 230000008470 skin growth Effects 0.000 description 1
- 238000003756 stirring Methods 0.000 description 1
- 230000008646 thermal stress Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/067—Enterprise or organisation modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
- Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Development Economics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Cleaning And De-Greasing Of Metallic Materials By Chemical Methods (AREA)
Abstract
The invention provides a design method of a supercritical power station boiler superheater pipeline chemical cleaning scheme, which comprises the following steps: determining a mathematical model of the growth of the oxide skin; performing static tests at different temperatures and concentrations, determining the time required for complete reaction of the oxide skin and the acid liquor, the reaction amount of the acid liquor in unit time and unit area, and determining the chemical reaction speed of the acid liquor at different temperatures and concentrations; predicting the tube explosion probability of the superheater tube aiming at the running condition of the superheater tube, and determining the time when the superheater tube starts pickling based on the tube explosion probability of the superheater tube; determining the theoretical time of oxide skin pickling under the condition of constant chemical reaction speed; and (4) configuring acid liquor, and determining a chemical cleaning scheme of the supercritical power station boiler superheater pipeline. The method provides a new idea for cleaning the superheater pipeline of the power plant, selects the optimal time for starting pickling of the pipeline, enhances the running time of the superheater pipeline, and reduces the economic loss caused by pipe explosion of the pipeline.
Description
Technical Field
The invention belongs to the technical field of process control, and particularly relates to a design method of a supercritical power station boiler superheater pipeline chemical cleaning scheme.
Background
The working medium of the thermal power plant is water, under the conventional condition, when the water reaches the saturation temperature under the given pressure through the heating temperature, the phase change is generated, the water is changed from a liquid state to a gaseous state, when the steam pressure reaches 22.129MPa, the water is completely vaporized when being heated to 374.15 ℃ under the pressure, the superheater mainly plays a role in taking out the moisture in the saturated steam in the working link of the power plant, a steam turbine is protected, and the steam is dried mainly through a superheating method. In the process, due to the high-temperature and high-pressure steam environment in the superheater pipeline, the metal inner wall can be in contact oxidation with steam, the operating temperature of the superheater steam is 571 ℃, at the temperature, oxygen in the air is combined with the metal inner wall of the superheater to generate an oxidation film, the oxidation film is divided into three layers along with the time, and FeO-Fe is sequentially formed from the metal matrix of the superheater pipeline inwards all the time3O4-Fe2O3The ferroferric oxide and the ferriferrous oxide on the outer layer have compact structures and stable chemical properties, the ferrous oxide on the inner layer has loose structures, when the temperature of a superheater pipeline is changed violently, an oxidation film can be cracked due to different thermal stresses of a pipeline matrix and the ferriferrous oxide, and steam permeates into a metal matrix through oxide skin cracks to be further oxidized to forceThe integral stability of the oxide skin is damaged, the oxide film is easy to fall off and accumulates in the pipeline, so that the pipeline is blocked, and the problem of pipe explosion of the pipeline is further caused.
At present, the means for treating the oxide skin of a power plant is mainly to shut down after the pipe explosion happens to the pipeline, and the pipeline of a part of the pipe explosion is cut and replaced, so that the intuitive economic loss of a power station boiler caused by the pipe explosion, the shutdown and the maintenance can not be estimated, the problem of accumulation of the oxide skin of the pipe explosion pipeline is actually solved, measures are not taken for other pipelines, the cutting and the replacement are carried out again only when the next pipe explosion happens, and the treatment method is rough.
Disclosure of Invention
Aiming at the defects of the existing oxide skin treatment technology, the invention provides a design method of a supercritical power station boiler superheater pipeline chemical cleaning scheme.
The technical scheme of the invention is as follows:
a design method of a supercritical power station boiler superheater pipeline chemical cleaning scheme comprises the following steps:
determining a relation curve of the running time of the superheater pipeline and the corresponding oxide scale thickness under the working condition of the rated working condition of the superheater pipeline, namely a mathematical model of oxide scale growth;
performing static tests at different temperatures and concentrations, determining the time required for complete reaction of the oxide skin and the acid liquor, the reaction amount of the acid liquor in unit time and unit area, and determining the chemical reaction speed of the acid liquor at different temperatures and concentrations;
predicting the tube explosion probability of the superheater tube aiming at the running condition of the superheater tube, and determining the time when the superheater tube starts pickling based on the tube explosion probability of the superheater tube;
determining the theoretical time of oxide skin pickling under the condition of constant chemical reaction speed;
and (3) configuring acid liquor based on the theoretical time of oxide skin pickling, and determining a chemical cleaning scheme of the supercritical power station boiler superheater pipeline.
The method for establishing the mathematical model of the oxide skin growth comprises the following steps:
acquiring historical data of the superheater pipeline under the working condition of a rated working condition, wherein the historical data comprises steam temperature, pressure, t-time scale thickness and running time of the superheater pipeline during running;
and performing regression processing on the historical data, and fitting a relation curve between the running time of the superheater pipeline and the corresponding oxide scale thickness under the condition of certain steam temperature and pressure to obtain a mathematical model of oxide scale growth.
The mathematical model of the growth of the oxide skin is as follows:wherein, delta is the thickness of oxide skin at t time, A is undetermined coefficient, and n is [1, 2 ]]And (3) taking a median value, wherein when n is 1, the growth curve of the oxide scale is linear, and when n is 2, the growth curve of the oxide scale is parabolic, and estimating the undetermined coefficient A according to the historical data of the superheater pipeline.
The specific method for determining the chemical reaction speed of the hydrochloric acid at different temperatures and concentrations comprises the following steps:
respectively preparing acid liquids with different concentrations, setting different temperatures, respectively cutting oxide skins with the same area to perform a static test, and recording the time required for complete reaction of the oxide skins and the acid liquids;
and determining the reaction amount of the acid liquor in unit time and unit area according to the time required by the complete reaction of the oxide skin and the acid liquor, and further determining the chemical reaction speed of the acid liquor at different temperatures and concentrations.
The method for predicting the tube explosion probability of the superheater tubes according to the running conditions of the superheater tubes comprises the following specific steps:
extracting historical data related to pipe explosion faults in the historical data of the superheater pipeline;
training a risk prediction model of superheater pipeline pipe explosion probability based on historical data related to pipe explosion faults in the superheater pipeline historical data;
and after the state characteristic vector of the superheater pipeline running to a certain moment is given, calculating a pipe explosion probability function value of the superheater pipeline.
The method comprises the steps of determining the time when the superheater pipeline starts pickling based on the pipe explosion probability of the superheater pipeline, and specifically, taking the time when a pipe explosion probability function value reaches a set upper limit as the time when pickling starts.
The method for establishing the risk prediction model of the superheater pipeline pipe explosion probability comprises the following steps:
defining a risk prediction model of the pipe explosion probability of the superheater pipeline; selecting Weibull distribution as a substrate tube explosion risk function to obtain a risk prediction model of the tube explosion probability of the final superheater pipeline; performing parameter estimation on a risk prediction model of the superheater pipeline tube explosion probability by adopting a maximum likelihood function method, and determining a likelihood function of the risk prediction model of the superheater pipeline tube explosion probability for historical data of N superheater pipelines related to tube explosion faults; and solving the maximum value of the likelihood function based on a DFP method.
The method for determining the theoretical time of scale pickling under the condition of constant chemical reaction speed comprises the following steps:
determining the chemical reaction speed of the acid liquor according to the concentration of the acid liquor prepared by acid washing and the temperature of an acid washing environment;
calculating the time required by the complete reaction of the single-layer oxide skin on the unit area of the pipeline;
calculating the time required by the complete reaction of the three layers of oxide skins on the unit area of the pipeline;
calculating the hydrochloric acid consumption of three oxides contained in the three-layer oxide skin;
calculating the hydrochloric acid consumption of the unit area of the inner wall of the pipeline;
the theoretical time of the scale pickling is determined under the condition that the chemical reaction speed is not changed, namely the sum of the hydrochloric acid consumption of three oxides contained in the three-layer scale is divided by the hydrochloric acid consumption per unit area of the inner wall of the pipeline.
Has the advantages that:
predicting the tube explosion probability of the superheater tube aiming at the running condition of the superheater tube, and determining the time when the superheater tube starts pickling based on the tube explosion probability of the superheater tube; determining the chemical reaction speed of hydrochloric acid according to the concentration of hydrochloric acid configured in pickling and the temperature of pickling environment, determining the thickness of the oxide scale at the moment of starting pickling based on a mathematical model of oxide scale growth, calculating the weight of the oxide scale, and determining the theoretical time of pickling the oxide scale under the condition that the chemical reaction speed is not changed. And (3) configuring acid liquor based on the theoretical time of oxide skin pickling, and determining a chemical cleaning scheme of the supercritical power station boiler superheater pipeline. The method provides a new idea for cleaning the superheater pipeline of the power plant, selects the optimal time for starting pickling of the pipeline, and applies for shutdown for chemical cleaning of the oxide skin of the pipeline by selecting the appropriate time of the power plant. The probability of tube explosion of the superheater is reduced, the running time of the superheater pipeline is enhanced, the economic loss caused by tube explosion of the pipeline is reduced, and the economic benefit of a power plant is improved.
Drawings
FIG. 1 is a schematic diagram of a pickling plant, wherein 1 is a pickling tank, 2 is a constant-temperature water bath, 3 is a rinsing tank, 4 is a magnetic pump, 5 is an electromagnetic flow meter, 6 is a pipeline to be pickled, and 7 is a waste liquid tank;
FIG. 2 is a graph of the chemical reaction rate of hydrochloric acid at room temperature as a function of concentration in an embodiment of the present invention;
FIG. 3 is a graph of absolute temperature versus chemical reaction rate of hydrochloric acid in an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the invention refers to the accompanying drawings.
In the present embodiment, a pickling apparatus shown in fig. 1, which is directed to a recyclable pickling platform, mainly includes: the pickling tank 1, the constant temperature water bath 2, the rinsing tank 3, the magnetic pump 4, the electromagnetic flowmeter 5, the pipeline 6 to be pickled and the waste liquid tank 7 are mainly used for controlling the flow through controlling the opening degree of a valve, the constant temperature water bath 2 is used for setting the reaction temperature, the acid solution adopted by the embodiment is hydrochloric acid, and the reaction temperature is controlled at 30 ℃ at room temperature.
The embodiment provides a design method of a supercritical power station boiler superheater pipeline chemical cleaning scheme, which comprises the following steps:
step 1: and determining a relation curve of the running time of the superheater pipeline under the working condition of the rated working condition and the corresponding oxide scale thickness, namely a mathematical model of oxide scale growth.
Step 1.1: acquiring historical data X of the superheater pipeline under the working condition of the rated working condition as [ T, P, delta, T ], wherein the historical data comprises steam temperature T, pressure P, T time scale thickness delta and running time T when the superheater pipeline runs.
Step 1.2: and performing regression processing on the historical data, and fitting a relation curve between the running time of the superheater pipeline and the corresponding oxide scale thickness under the condition of certain steam temperature T and pressure P to obtain a mathematical model of oxide scale growth.
The growth of the oxide skin in the superheater tubes is divided into two phases: the growth curve of the oxide skin in the first stage is linear; in the second stage, due to the heat insulation effect of the oxide scale, the growth curve of the oxide scale tends to be flat and is in a parabolic shape. Therefore, under the working conditions of the superheater tubes at nominal conditions, the mathematical model of the growth of the scale is:wherein, delta is the thickness of oxide skin at t time, A is undetermined coefficient, and n is [1, 2 ]]And if n is 1, the growth curve of the oxide scale is linear, and if n is 2, the growth curve of the oxide scale is parabolic, and the undetermined coefficient A is estimated according to the historical data of the superheater pipeline during selection, wherein in the embodiment, n is 1.62, and A is 136.2.
Step 2: and (3) carrying out static tests at different temperatures and concentrations, determining the time required by the complete reaction of the oxide skin and the hydrochloric acid, the reaction amount of the hydrochloric acid in unit time and unit area, and determining the chemical reaction speed of the hydrochloric acid at different temperatures and concentrations.
Step 2.1: hydrochloric acid with different concentrations is prepared respectively, different temperatures are set in a constant-temperature water bath, oxide skins with the same area are cut respectively for static test, and the time required for complete reaction of the oxide skins and the hydrochloric acid is recorded.
In the embodiment, 10g/L, 20g/L, 50g/L, 100g/L and 150g/L of dilute hydrochloric acid solution are respectively used, the temperature is set in a constant-temperature water bath kettle from 20 to 40 ℃, oxide scales with the cutting areas of 1 square centimeter are respectively used for static test, and the time required by complete reaction of the oxide scales and the hydrochloric acid is recorded.
Step 2.2: according to the time required by the complete reaction of the oxide skin and the hydrochloric acid, the reaction amount of the hydrochloric acid in unit time and unit area is determined, and further the chemical reaction speed of the hydrochloric acid at different temperatures and concentrations is determined. The chemical reaction rate of hydrochloric acid at room temperature is shown in FIG. 2 as a function of concentration. The relationship between absolute temperature and chemical reaction rate of hydrochloric acid is shown in FIG. 3.
And step 3: and predicting the tube explosion probability of the superheater tube aiming at the running condition of the superheater tube, and determining the pickling starting time of the superheater tube based on the tube explosion probability of the superheater tube.
Step 3.1: extracting historical data related to pipe explosion faults in the historical data of the superheater pipeline, and establishing a data set as follows:
DataSet(i)＝(ti，Xi，δi)i＝1，2，...，N；
wherein the operation state data X of the ith pipelinei＝(xi，1，xi，2…xi，p-1，xi，p)，xi，pThe ith state feature vector of the superheater is represented, and p in the present embodiment is 4, that is, the operating state data of the ith line includes four state feature vectors of the steam temperature, the line wall temperature, the operating time, and the temperature change rate. DeltaiThe indication is random right deletion data, δ ═ 1 indicates that a pipe explosion event occurs in the superheater pipe during the observation time, δ ═ 0 indicates that a pipe explosion event does not occur during the observation time, and the indication is right deletion data. t is tiIndicating the time of the pipe bursting event in the ith pipeline. And N is the number of superheater pipelines in the data set.
Step 3.2: training a risk prediction model of superheater pipeline pipe explosion probability based on historical data related to pipe explosion faults in the superheater pipeline historical data;
step 3.2.1: defining a risk prediction model of the pipe explosion probability of the superheater pipeline:
h(ti，Xi)＝h0(ti)exp(xi，1β1+xi，2β2+…+xi，pβp)
wherein, h (t)i，Xi) Is an operating condition of XiAt time ti(onset time t)i0) probability of tube burst, β1，β2…βp-1，βpThe parameters of the impact on the pipe explosion of the superheater pipeline under different operating conditions are called regression coefficients, the impact on the pipe explosion probability is obtained by estimating historical data related to pipe explosion faults in the historical data of the superheater pipeline. h is0(ti) Is a function of substrate detonation risk.
Step 3.2.2: selecting Weibull distribution as a substrate tube explosion risk function to obtain a risk prediction model of the tube explosion probability of the final superheater pipeline;
substrate burst risk function:
wherein: eta > 0 is a proportional parameter, gamma > 0 is a shape parameter, h0(ti) Carry-in h (t)i，Xi)；
Obtaining a risk prediction model of the final superheater pipeline pipe explosion probability:
step 3.2.3: and (2) performing parameter estimation on a risk prediction model of the superheater pipeline tube explosion probability by adopting a maximum likelihood function method, and determining the likelihood function of the risk prediction model of the superheater pipeline tube explosion probability for the historical data of the N superheater pipelines related to the tube explosion fault as follows:
wherein S isi(ti，Xi) Is a reliability function derived from the cumulative distribution function:
taking logarithms to both sides of the reliability function at the same time can obtain:
thus, the parameter estimation is converted into a problem of maximization of the function lnL (γ, η, β).
Step 3.2.4: lnL (gamma, eta, beta) are solved for the maximum value based on the DFP method.
The DFP method is an optimization algorithm named Davidon, Fletcher, Powell.
Step 3.2.4.1: the objective function f (γ, η, β) is determined to be lnL (γ, η, β), and the gradient of the objective function f (γ, η, β) is g (γ, η, β).
Step 3.2.4.2: randomly selecting a group of gamma, eta, beta as a selected iteration initial point I0Is (γ, η, β) and calculates an initial objective function f0＝f(I0) Initial gradient g0＝g(I0) (ii) a Setting a termination limit and a maximum iteration number n';
step 3.2.4.3: set up HoIs a unit matrix, and an initial search direction is set to be p0＝-g0The number of iterations k is 0.
Step 3.2.4.4: performing linear search along the initial search direction to obtain k +1 iteration points Ik+1＝ls(Ik，pk) Obtaining a new iteration initial value, and calculating f on the basis of the new iteration initial valuek+1＝f(Ik+1)，gk+1＝g(Ik+1)，pkIs the search direction of the kth iteration point, IkAre k iteration points.
Step 3.2.4.5: judging whether the current iteration meets the termination limit, if so, stopping the iteration to obtain the parameter estimation value corresponding to the current iteration pointStep 3.3 is executed; otherwise continue with step 3.2.4.6;
step 3.2.4.6: if k is n', then I is set0＝Ik+1，f0＝fk+1，g0＝gk+1Go to step 3.2.4.4 above, otherwise go to step 3.2.4.7;
step 3.2.4.7: calculating gradient differences y between k +1 iteration points and k iteration pointskThe difference s between k +1 iteration points and k iteration pointskEstimation H of the inverse of the second-order Hessian matrix for k +1 iteration pointsk+1：
yk＝gk+1-gk sk＝Ik+1-Ik
pk+1＝-Hk+1gk+1
Set k to k +1, go to step 3.2.4.4 and continue the straight line search.
Step 3.3: run at given superheater line to tiState feature vector X (t) at time instanti) And then, calculating a tube explosion probability function value of the superheater pipeline:
therefore, the probability of pipe explosion at a certain moment is known based on real-time data of each superheater pipe in the power plant.
Step 3.4: determining the pickling start time of the superheater pipeline based on the pipe explosion probability of the superheater pipeline: the moment when the pipe explosion probability function value reaches the set upper limit (90%) is the moment when pickling starts, and field personnel apply for shutdown for pickling at the moment.
And 4, step 4: determining the chemical reaction speed of hydrochloric acid according to the concentration of hydrochloric acid configured in pickling and the temperature of pickling environment, determining the thickness of the oxide scale at the moment of starting pickling based on a mathematical model of oxide scale growth, calculating the weight of the oxide scale, and determining the theoretical time of pickling the oxide scale under the condition that the chemical reaction speed is not changed.
Step 4.1: determining the chemical reaction speed of the hydrochloric acid according to the concentration of the hydrochloric acid prepared by pickling and the temperature of pickling environment;
taking hydrochloric acid with the preparation concentration of 300g/L as an example, the chemical reaction speed of the hydrochloric acid is determined at room temperatureWherein C isHCLThe concentration of hydrochloric acid is shown, and T represents the temperature of the pickling environment.
Step 4.2: theoretically calculating the time required by the complete reaction of the single-layer oxide skin on the unit area of the pipeline;
assuming that a pipeline with the length of one meter and the specification of 55 x 4.5 mm is taken, the thickness of an oxide scale on the inner wall of the pipeline determined according to an oxide scale growth model is 300 microns, and the weight m of the oxide scale in the pipeline is calculated on the premise that the oxide scale is uniformly distributedFeoComprises the following steps:
where ρ is the ferrous oxide density, r is the inner diameter of the pipe, δ is the thickness of the scale representing time t, and l is the length of the pipe
Consumption m of hydrochloric acid at this timeHClComprises the following steps:
the reaction speed of the hydrochloric acid per unit area of the inner wall of the pipeline is as follows:
ΔmHCl＝k·2·π·rn·Δl＝0.867g/s
theoretically, the time required for complete reaction of the single-layer oxide skin on the unit area of the pipeline is as follows:
step 4.3: calculating the time required by the complete reaction of the three layers of oxide skins on the unit area of the pipeline;
the oxide skin is divided into three layers from the metal matrix outwards in turn, and the three layers are respectively: FeO-Fe2O4-Fe2O3And under the condition that the thickness ratio is recorded as 100: 10: 1, respectively calculating the time required by the complete reaction of the three layers of oxide skins again:
step 4.4: calculating the hydrochloric acid consumption of three oxides contained in the three-layer oxide skin;
under the dissolving action of hydrochloric acid, the consumption hydrochloric acid amounts of three oxides contained in the three-layer oxide skin are calculated as follows:
step 4.5: calculating the hydrochloric acid consumption on the unit area of the inner wall of the pipeline:
wherein k is the chemical reaction rate of hydrochloric acid, rnIs the inner diameter of the pipe.
Step 4.6: determining the theoretical time of the scale pickling under the condition that the chemical reaction speed is not changed, namely dividing the sum of the hydrochloric acid consumption of three oxides contained in the three-layer scale by the hydrochloric acid consumption per unit area of the inner wall of the pipeline:
and 5: and based on the theoretical time of scale pickling, configuring hydrochloric acid, and determining a chemical cleaning scheme of the supercritical power station boiler superheater pipeline, wherein the chemical cleaning scheme comprises the moment of starting pickling, the theoretical time of scale pickling, and the concentration and consumption of hydrochloric acid.
Performing chemical cleaning according to the determined chemical cleaning scheme of the superheater pipeline of the supercritical power station boiler, and preparing by adopting commercially available 20% 60g/L hydrochloric acid, wherein the density of the 20% hydrochloric acid is 1.098g/cm at normal temperature3When acid washing is carried out, 20L of acid washing solution is prepared, 5.46L of 20% diluted hydrochloric acid and 14.56L of clear water are needed, and 0.2kg of urotropine serving as a corrosion inhibitor is added to prepare the acid washing solution.
| 20% hydrochloric acid | Clean water | Urotropine |
| 5.46L | 14.56L | 0.2kg |
At this time, the theoretical time for scale pickling was calculated to be 84.48 minutes, with the temperature of the pickling environment being 30 ℃.
And (2) connecting the pipeline to be pickled into an acid liquor outlet, setting the temperature of a constant-temperature water bath kettle, opening a valve, and circularly washing the acid liquor, wherein 20% of time is reserved on the basis of the theoretical time of oxide skin pickling, namely the pickling condition of the pipeline is checked in 67.584 minutes, and when the inner surface of the pipeline is smooth and rustless, the pipeline is qualified when the metal luster is presented.
Check the effect of chemical cleaning:
firstly, washing with water: cleaning the residual acid liquor in the pipeline to prevent the residual acid liquor from further corroding the metal substrate;
secondly, passivating: protecting the pipeline after acid washing, wherein the specific configuration of the passivation solution is as follows:
the preparation of the passivation solution selects sodium nitrite and ammonia water, the percentage of the sodium nitrite is required to be more than 1 during the preparation, the sodium nitrite is in a slightly alkaline environment, the preparation of the alkaline environment is carried out by using 25% ammonia water, 0.5kg of sodium nitrite is selected, 20L of clear water is added, the stirring is uniform, the ammonia water is added on the basis, the pH value of the passivation solution is measured while the ammonia water is added, and the pH value of the passivation solution is determined to be between 9 and 10 through the adjustment of the ammonia water.
| Sodium nitrite | Clean water | Aqueous ammonia | PH |
| 0.5kg | 20L | 25％ | 9 |
Then, water washing is performed again: and removing the passivation solution in the pipeline, connecting the pipeline into a clean water pipeline, and cleaning the residual passivation solution for half an hour.
Specifically, after the pickling pipeline is checked to be qualified, clean water is added for cleaning. The time is half an hour.
And finally, drying: after a series of procedures such as pickling passivation water washing and the like, the pipeline is immediately dried, and the gas is dried by dry compressed air.
The examples of chemical cleaning using the method of the present invention are as follows:
example 1:
the cutting of a certain pipeline sample is observed, the oxide skin condition of the inner wall of the pipeline is observed, the inner wall of the pipeline is corroded, the surface is rough, particles with different sizes are distributed, the blackening belt is dark red, and the oxide skin is distributed uniformly. The pickling is carried out by adopting 6% hydrochloric acid solution, the theoretical pickling time is 84 minutes, the pickling time is 60 minutes in actual control, after cleaning, the inner surface and the outer surface are smooth, irregularly distributed particles do not exist, the inner surface presents clear metal luster, the over-pickling condition does not appear, and the control of the hydrochloric acid time is just right.
Example 2:
the sample of a certain pipeline is cut and observed, the oxide skin condition of the inner wall of the pipeline is observed, the inner surface wall is dark black and slightly corroded, the surface wall has no particle distribution and uniform oxide skin distribution, the pickling time is controlled for 60 minutes, after the pipeline is cleaned, the inner surface wall is smooth and has no irregularly distributed particles, the inner surface presents clear metal luster, and the over-pickling condition is avoided.
Claims (8)
1. A design method for a supercritical power station boiler superheater pipeline chemical cleaning scheme is characterized by comprising the following steps:
determining a relation curve of the running time of the superheater pipeline and the corresponding oxide scale thickness under the working condition of the rated working condition of the superheater pipeline, namely a mathematical model of oxide scale growth;
performing static tests at different temperatures and concentrations, determining the time required for complete reaction of the oxide skin and the acid liquor, the reaction amount of the acid liquor in unit time and unit area, and determining the chemical reaction speed of the acid liquor at different temperatures and concentrations;
predicting the tube explosion probability of the superheater tube aiming at the running condition of the superheater tube, and determining the time when the superheater tube starts pickling based on the tube explosion probability of the superheater tube;
determining the theoretical time of oxide skin pickling under the condition of constant chemical reaction speed;
and (3) configuring acid liquor based on the theoretical time of oxide skin pickling, and determining a chemical cleaning scheme of the supercritical power station boiler superheater pipeline.
2. The method according to claim 1, characterized in that the mathematical model of the scale growth is established as follows:
acquiring historical data of the superheater pipeline under the working condition of a rated working condition, wherein the historical data comprises steam temperature, pressure, t-time scale thickness and running time of the superheater pipeline during running;
and performing regression processing on the historical data, and fitting a relation curve between the running time of the superheater pipeline and the corresponding oxide scale thickness under the condition of certain steam temperature and pressure to obtain a mathematical model of oxide scale growth.
3. Method according to claim 1 or 2, characterized in that the oxide scale is appliedThe mathematical model of growth of (a) is:wherein, in the step (A),is the thickness of the oxide skin at time t,An is [1, 2 ] for the undetermined coefficient]The average value is that when n =1, the growth curve of the oxide scale is linear, when n =2, the growth curve of the oxide scale is parabolic, and the undetermined coefficient is carried out according to the historical data of the superheater pipelineAIs estimated.
4. The method as claimed in claim 1, wherein the chemical reaction rate of the acid solution at different temperatures and concentrations is determined by:
respectively preparing acid liquids with different concentrations, setting different temperatures, respectively cutting oxide skins with the same area to perform a static test, and recording the time required for complete reaction of the oxide skins and the acid liquids;
and determining the reaction amount of the acid liquor in unit time and unit area according to the time required by the complete reaction of the oxide skin and the acid liquor, and further determining the chemical reaction speed of the acid liquor at different temperatures and concentrations.
5. The method of claim 1, wherein the prediction of the probability of knock-out of the superheater tubing is made for the operating conditions of the superheater tubing by:
extracting historical data related to pipe explosion faults in the historical data of the superheater pipeline;
training a risk prediction model of superheater pipeline pipe explosion probability based on historical data related to pipe explosion faults in the superheater pipeline historical data;
and after the state characteristic vector of the superheater pipeline running to a certain moment is given, calculating a pipe explosion probability function value of the superheater pipeline.
6. The method according to claim 1, characterized in that the time when the superheater pipeline starts pickling is determined based on the pipe explosion probability of the superheater pipeline, and specifically, the time when the pipe explosion probability function value reaches a set upper limit is used as the time when pickling starts.
7. The method of claim 5, wherein the risk prediction model of superheater tube knock probability is established as follows:
defining a risk prediction model of the pipe explosion probability of the superheater pipeline; selecting Weibull distribution as a substrate tube explosion risk function to obtain a risk prediction model of the tube explosion probability of the final superheater pipeline; performing parameter estimation on a risk prediction model of superheater pipeline tube explosion probability by adopting a maximum likelihood function method, wherein i =1, 2, …, N represents the ith superheater tube, and for historical data of N superheater tubes related to tube explosion faults, a likelihood function of the risk prediction model of the superheater tube explosion probability is determined; and solving the maximum value of the likelihood function based on a DFP method.
8. The method of claim 1, wherein the method for determining the theoretical time for scale pickling with a constant chemical reaction rate is:
determining the chemical reaction speed of the acid liquor according to the concentration of the acid liquor prepared by acid washing and the temperature of an acid washing environment;
calculating the time required by the complete reaction of the single-layer oxide skin on the unit area of the pipeline;
the oxide skin is divided into three layers from the metal matrix to the outside in sequence, and the three layers are respectively FeO and Fe2O4、Fe2O3Calculating the time required by the complete reaction of the three oxide skins on the unit area of the pipeline;
calculating the hydrochloric acid consumption of three oxides contained in the three-layer oxide skin;
calculating the hydrochloric acid consumption of the unit area of the inner wall of the pipeline;
the theoretical time of the scale pickling is determined under the condition that the chemical reaction speed is not changed, namely the sum of the hydrochloric acid consumption of three oxides contained in the three-layer scale is divided by the hydrochloric acid consumption per unit area of the inner wall of the pipeline.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711127658.9A CN107844863B (en) | 2017-11-15 | 2017-11-15 | Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme |
| PCT/CN2018/087695 WO2019095658A1 (en) | 2017-11-15 | 2018-05-21 | Design method of chemical cleaning scheme for superheater pipe of supercritical power station boiler |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711127658.9A CN107844863B (en) | 2017-11-15 | 2017-11-15 | Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107844863A CN107844863A (en) | 2018-03-27 |
| CN107844863B true CN107844863B (en) | 2019-12-31 |
Family
ID=61679517
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711127658.9A Active CN107844863B (en) | 2017-11-15 | 2017-11-15 | Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme |
Country Status (2)
| Country | Link |
|---|---|
| CN (1) | CN107844863B (en) |
| WO (1) | WO2019095658A1 (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107844863B (en) * | 2017-11-15 | 2019-12-31 | 东北大学 | Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme |
| CN111893424B (en) * | 2020-06-29 | 2022-07-01 | 武汉钢铁有限公司 | Plate blank surface iron scale heating control method based on hot-conveying and hot-charging process |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102444885A (en) * | 2011-12-19 | 2012-05-09 | 上海望特能源科技有限公司 | Method for avoiding overheat tube burst in tubular boiler of power station boiler |
| CN107059030A (en) * | 2017-05-02 | 2017-08-18 | 西安热工研究院有限公司 | A kind of power station superheater or reheater oxide skin chemical cleaning system and method |
Family Cites Families (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5108771B2 (en) * | 2006-08-23 | 2012-12-26 | エヌケーケーシームレス鋼管株式会社 | Austenitic stainless steel pipe for boilers with excellent high-temperature steam oxidation resistance |
| CN102749038B (en) * | 2011-04-20 | 2016-02-03 | 华东电力试验研究院有限公司 | The detection method of austenitic steel steam oxidation skin growth conditions |
| CN102588940A (en) * | 2011-12-16 | 2012-07-18 | 上海发电设备成套设计研究院 | Method for comprehensively evaluating state of scale cinder of heated surface of boiler |
| JP5681843B1 (en) * | 2013-07-30 | 2015-03-11 | パナソニックＩｐマネジメント株式会社 | Thermoelectric generator unit and thermoelectric generator system |
| CN106442661A (en) * | 2016-10-27 | 2017-02-22 | 中国神华能源股份有限公司 | Online measurement device for chemical boiler cleaning system |
| CN107844863B (en) * | 2017-11-15 | 2019-12-31 | 东北大学 | Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme |
-
2017
- 2017-11-15 CN CN201711127658.9A patent/CN107844863B/en active Active
-
2018
- 2018-05-21 WO PCT/CN2018/087695 patent/WO2019095658A1/en active Application Filing
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102444885A (en) * | 2011-12-19 | 2012-05-09 | 上海望特能源科技有限公司 | Method for avoiding overheat tube burst in tubular boiler of power station boiler |
| CN107059030A (en) * | 2017-05-02 | 2017-08-18 | 西安热工研究院有限公司 | A kind of power station superheater or reheater oxide skin chemical cleaning system and method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107844863A (en) | 2018-03-27 |
| WO2019095658A1 (en) | 2019-05-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107844863B (en) | Design method of supercritical power station boiler superheater pipeline chemical cleaning scheme | |
| US10315234B2 (en) | Method for conditioning a power-generating circulatory system of a power plant | |
| CN109242370B (en) | Optimal scale cleaning period calculation and determination method for water-cooled motor | |
| CN107059030A (en) | A kind of power station superheater or reheater oxide skin chemical cleaning system and method | |
| CN106442293A (en) | Method for testing carbon dioxide corrosion resistance of low-Cr pipeline steel | |
| CN112063987A (en) | Circulating water cooling system for PVD coating furnace and cleaning method thereof | |
| CN105973061B (en) | A kind of descaling method of condenser of power plant | |
| JP7271205B2 (en) | POWER PLANT WATER QUALITY MONITORING SYSTEM, WATER QUALITY MONITORING METHOD AND WATER QUALITY MONITORING PROGRAM, POWER PLANT | |
| CN110699696A (en) | Acid pickling passivation method for stainless steel pipe fitting | |
| CN112858155A (en) | Dynamic simulation test device and test method for corrosion of hollow copper conductor of generator | |
| CN112344314A (en) | Sodium-cooled fast reactor steam generator and chemical cleaning system for steam-water side of heat transfer pipe of superheater | |
| JP4288018B2 (en) | Water quality evaluation method and water quality management system | |
| CN206736364U (en) | A kind of power station superheater or reheater oxide skin chemical cleaning system | |
| CN110132827A (en) | A kind of high-temperature steam oxidation test device | |
| CN114036756A (en) | Method and device for evaluating furnace shutdown protection anti-corrosion effect of thermal power generating unit | |
| WO2015047131A1 (en) | Method for the in situ passivation of the steel surfaces of a nuclear reactor | |
| EP3093369B1 (en) | Method for inner-contour passivation of steel surfaces of nuclear reactor | |
| CN102534624A (en) | Protection method of super-long-period shut-down thermal generator set | |
| CN113433056A (en) | System for evaluating aging state of non-metallic material under ETA + NH3 condition | |
| CN110629235A (en) | Cleaning agent for scale containing apatite or/and calcium phosphate scale and system containing austenitic steel and application thereof | |
| CN106967886B (en) | A kind of method of on-line cleaning recycling noble metal in nitric acid plant | |
| CN115069683B (en) | Method for removing oxide skin of generator set | |
| RU2767674C1 (en) | Method of cleaning and passivating steam turbine condenser tubes inner surfaces from deposits | |
| CN215061998U (en) | Energy-saving deoxidizing device for steam turbine | |
| CN111121295B (en) | Vacuum phase-change boiler exhaust system and exhaust method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |