CN109711642A - Desulphurization system running optimizatin method and system based on big data - Google Patents
Desulphurization system running optimizatin method and system based on big data Download PDFInfo
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- CN109711642A CN109711642A CN201910104366.6A CN201910104366A CN109711642A CN 109711642 A CN109711642 A CN 109711642A CN 201910104366 A CN201910104366 A CN 201910104366A CN 109711642 A CN109711642 A CN 109711642A
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- 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
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- 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
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Abstract
The desulphurization system running optimizatin method based on big data that the invention discloses a kind of, this method is based on desulphurization system theoretical model, regression analysis, big data analysis are carried out to power station actual operating data, it builds mathematical model and finds model part, globally optimal solution, then spoke proposes running optimizatin method with theoretical model.The present invention is to rely on theoretical model, provides running optimizatin improvement project for desulphurization system, and it is unreasonable to solve the problems, such as that energy resources present in previous desulphurization system utilize.
Description
Technical field
The present invention relates to coal-burning boiler atmosphere pollution control technology fields, in particular to one kind based on big data point
It analyses and provides the method for strategy for desulphurization system running optimizatin.
Background technique
Now, coal fired power plant improves power station money by drawing close to the direction of fine-grained management as traditional blowdown rich and influential family
Source utilization efficiency reduces energy consumption.
However in actual moving process, since power station equipment is various, manually how to be formulated to reach in face of equipment room
To optimal working efficiency and adequately protect asset of equipments problem when, it tends to be difficult to accurate decision, it is extra that this often will cause
Energy consumption, the wasting of resources.Meanwhile with the development of hardware device, more and more coal fired power plants start using variable frequency pump etc.
How the equipment for needing accurately to adjust realizes accurate adjusting, and reducing resources and energy consumption has been that the another reality that power station faces is difficult
Topic.In addition, for many years, in actual moving process, the actual operating data that power station stores a large amount of preciousnesses is not filled but
Divide and utilize, the waste to network, physical space is not only, even more to the waste of data resource.
The development of big data, artificial intelligence technology solves problem above for power station and provides thinking and direction.Big data skill
Art is because of its powerful data analysis capabilities, by the concern of more and more coal fired power plants, research and application.Utilize big data skill
Art carries out depth analysis to the operation data of electric power station system, it has also become the important content that coal fired power plant reduces blowdown, improves efficiency
One of.
By above-mentioned it is found that external factor and internal environment all press coal fired power plant adjusts to accurate, improve efficiency
Advance in direction.Unreasonable, pollutant removing higher cost that there are usings energy source to overcome the problems, such as desulphurization system, the present invention mention
Go out one kind based on big data analysis technology, provides the method for strategy protocol for desulfurizing system optimization operation, it is intended to improve coal-fired
The efficiency of energy utilization of power station desulphurization system reduces pollutant removing cost, energy saving.
Summary of the invention
It is an object of that present invention to provide a kind of desulphurization system running optimizatin method and system based on big data, this method with
Desulphurization for Coal-fired Power Plant system is research object, by carrying out the method for big data analysis to power station operation data to power station desulfurization
System carries out profound analysis and proposes running optimizatin scheme.By means of big data analysis method to the reality of substantial amounts
Operation data is analyzed, and the correlation degree between different factors and efficiency is obtained, and is chosen the factor of wherein suitable number, is built
Mathematical forecasting model, and using the part of appropriate algorithm searching model, globally optimal solution.The present invention is to rely on theoretical model,
Running optimizatin improvement project is provided for desulphurization system, energy resources present in previous desulphurization system is solved and is asked using unreasonable
Topic.
To reach above-mentioned purpose, in conjunction with Fig. 1, the present invention proposes a kind of desulphurization system running optimizatin side based on big data
Method, which comprises
S1: it is theoretical based on energy balance and conservation of matter, desulphurization system reason is created according to coal fired power plant physical device component
By model, desulfuration efficiency evaluation index is set, extracts operation data of the coal fired power plant in the first set period of time as modeling
Data.
Preferably, the desulfuration efficiency evaluation index includes the energy usage and material amounts of desulfurization process consumption.One
In a little examples, it can choose larger loss or the higher several materials of value or the energy refer to as desulfuration efficiency evaluation
Mark, with reduced model.
More preferred, the desulfuration efficiency evaluation index includes the goods equivalent with the energy of desulfurization process consumption and material
Value of money.By desulfurization process consumption energy usage and material amounts it is equivalent at currency, desulfuration efficiency evaluation index can be done into
One step is simplified, and subsequent modeling and data processing are convenient for；Material loss as much as possible can also be added, energy loss is made
For evaluation points, without deleting material or the energy；Meanwhile having even if the energy occur and transformation or material price occurring
Situations such as variation etc., by this equivalent way, desulfuration efficiency evaluation index can be quickly adjusted, model is repaired in reduction
Positive quantity.
S2: pre-processing modeling data, and based on desulphurization system theoretical model, it is right under different working conditions to analyze
The several factor that desulfuration efficiency has an impact.
It is described that modeling data is pre-processed in step S2 in further embodiment, with desulphurization system theoretical model
Based on, analyze the method for the several factor having an impact under different working conditions to desulfuration efficiency the following steps are included:
S201: modeling data is pre-processed, comprising:
Confidence level audit, to reject unreasonable data therein；Supplement missing data；It is more than setpoint frequency to vibration frequency
The supplemental characteristic of threshold value carries out the biggish parameters of vibration frequencies such as denoising, such as operating voltage, after doing denoising to it
It utilizes again.
S202: using load as foundation, different working conditions are divided.
S203: based on different working conditions, recurrence calculating is carried out to pretreated modeling data, to obtain difference
The several factor that desulfuration efficiency is had an impact under working condition.
S3: carrying out big data analysis to pretreated modeling data, to obtain the key factor under different working conditions,
Mathematical forecasting model is created, globally optimal solution of the mathematical forecasting model under different working conditions is found, exists as desulphurization system
Running optimizatin strategy under different working conditions.
In further embodiment, in step S3, big data analysis is carried out to pretreated modeling data, to obtain not
With the key factor under working condition, mathematical forecasting model is created, it is complete under different working conditions to find mathematical forecasting model
Office optimal solution, as running optimizatin strategy of the desulphurization system under different working conditions method the following steps are included:
S301: to pretreated modeling data carry out big data analysis, with obtain under different working conditions it is crucial because
Element, using the key factor under different working conditions to create mathematical forecasting model.
S302: operation data of the coal fired power plant in the second set period of time is extracted as audit data, to mathematical prediction
Model is audited, step-up error threshold value, if audit by entering step S303, otherwise return step S301.
S303: optimal solution of the mathematical forecasting model under different working conditions is calculated, to obtain desulphurization system in different works
Running optimizatin strategy under the conditions of condition.
In further embodiment, the method also includes:
In step S302, if auditing unacceptable number reaches setting frequency threshold value, warning is issued.
Queueing problem is gone by issuing the step of warning is to remind user to return to earlier, such as returns to step S1 to examine again
Looking into theoretical model, whether correct or modeling data is with the presence or absence of missing etc..
Obtaining the method for corresponding to the key factor under working condition includes:
Grey relevance analysis is used to obtain the key factor under corresponding working condition, or is obtained described under different working conditions
For several factor to the influence value of desulfuration efficiency, will affect value is more than that setting influences the factor definition of threshold value into corresponding operating condition item
Key factor under part.
S4: being analyzed based on desulphurization system theoretical model, the correctness of the running optimizatin strategy is verified, if just
Really, the running optimizatin strategy is exported, otherwise, finds global optimum of the mathematical forecasting model under different working conditions again
Solution.
In further embodiment, the method also includes:
Genetic algorithm is used to calculate optimal solution of the mathematical forecasting model under different working conditions.
In further embodiment, in step S4, using the key factor under different working conditions, using neural network
And/or vector machine method is to create corresponding mathematical forecasting model.
Based on preceding method, the present invention further mentions a kind of desulphurization system operation optimizing system based on big data, the system
System includes following module:
1) for theoretical based on energy balance and conservation of matter, according to coal fired power plant physical device component creation desulphurization system
The module of theoretical model.
2) for setting the module of desulfuration efficiency evaluation index.
3) for extracting module of operation data of the coal fired power plant in the first set period of time as modeling data.
4) for carrying out pretreated module to modeling data.
5) it for based on desulphurization system theoretical model, analyzes and desulfuration efficiency is had an impact under different working conditions
The module of several factor.
6) for pretreated modeling data carry out big data analysis, with obtain under different working conditions it is crucial because
The module of element.
7) for creating the module of mathematical forecasting model.
8) for finding globally optimal solution of the mathematical forecasting model under different working conditions, as desulphurization system in difference
The module of running optimizatin strategy under working condition.
9) for analyzing based on desulphurization system theoretical model, the mould of the correctness of the running optimizatin strategy is verified
Otherwise block, finds mathematical forecasting model under different working conditions if correctly, exporting the running optimizatin strategy again
Globally optimal solution.
The above technical solution of the present invention, compared with existing, significant beneficial effect is:
1) CCS regulating system inevitably adulterates manual decision in the practical application of power station, and manual decision is often difficult
To realize accuracy, thus the case where often lead to the energy, the wasting of resources, and the analysis method based on big data have it is accurate
The characteristics of adjusting, this feature is to reduce energy consumption, energy saving to provide safeguard.
2) in traditional power station adjustment process, manual decision has often played important function, and manually not in decision
It can accomplish accurate resolution in real time, due to the excessive dependence to manual decision, so traditional power station regulating system may not necessarily accomplish
Accurately, best decision.And power station actual operating data basis is built upon based on the decision that big data analysis technology generates
On, it is the dependence for having the accuracy of mathematics powerful as its, and Theories on Decision Making Process model is introduced as the effective of decision
Property provides further guarantee.
3) matching between equipment may not be fully considered in the operational process of power station, in traditional CCS regulating system
Property, and due to the longtime running and maintenance maintenance of equipment, equipment room matching may have already appeared variation.It is basic based on this,
Big data analysis provides possibility for new matching process.
It should be appreciated that as long as aforementioned concepts and all combinations additionally conceived described in greater detail below are at this
It can be viewed as a part of the subject matter of the disclosure in the case that the design of sample is not conflicting.In addition, required guarantor
All combinations of the theme of shield are considered as a part of the subject matter of the disclosure.
Can be more fully appreciated from the following description in conjunction with attached drawing present invention teach that the foregoing and other aspects, reality
Apply example and feature.The features and/or benefits of other additional aspects such as illustrative embodiments of the invention will be below
Description in it is obvious, or learnt in practice by the specific embodiment instructed according to the present invention.
Detailed description of the invention
Attached drawing is not intended to drawn to scale.In the accompanying drawings, identical or nearly identical group each of is shown in each figure
It can be indicated by the same numeral at part.For clarity, in each figure, not each component part is labeled.
Now, example will be passed through and the embodiments of various aspects of the invention is described in reference to the drawings, in which:
Fig. 1 is the flow chart of the desulphurization system running optimizatin method of the invention based on big data.
Specific embodiment
In order to better understand the technical content of the present invention, special to lift specific embodiment and institute's accompanying drawings is cooperated to be described as follows.
In conjunction with Fig. 1, the present invention proposes a kind of desulphurization system running optimizatin method based on big data, the method includes with
Lower step:
1) data needed for establishing coal fired power plant desulphurization system theoretical model and obtaining: according to power station physical device component and tool
Body construction builds theoretical model, establishes conservation of matter.To remove unit mass SO2Consumed currency is efficiency evaluation index, point
Data needed for analysis project simultaneously are cooperated to obtain certain period of time operation data with power station.
2) obtained data are pre-processed: and carrying out confidence level audit: reject wherein unreasonable data, using suitable
Method supplements missing data, carries out denoising to the frequent supplemental characteristic (such as pressure) of fluctuation.
3) regression analysis is carried out to data after pretreatment: recurrence calculating is carried out to data according to above-mentioned efficiency index, is compared
The factor of efficiency variance under analyzing influence different situations.
4) big data artificial intelligence analysis is carried out to data: is analyzed and is obtained to effect using appropriate methods such as grey correlation analysis
Rate influences the most key many factors, then sets up threshold values and chooses the progress next step analysis of certain amount factor.
5) it builds mathematical forecasting model: using key factor, establishing mathematical prediction by the methods of neural network, vector machine
Model.
6) it audits prediction model: prediction model being audited using another period actual operating data in power station, be arranged
Suitable error line, if audit by entering the 8) step, otherwise returns the 5) step.
7) prediction model locally optimal solution is found using the methods of genetic algorithm, proposition system optimizes under different operating conditions and changes
Into strategy.
8) it is basic analytical procedure 7 with theoretical model) big data processing obtains running optimizatin improvement strategy.
Various aspects with reference to the accompanying drawings to describe the present invention in the disclosure, shown in the drawings of the embodiment of many explanations.
Embodiment of the disclosure need not be defined on including all aspects of the invention.It should be appreciated that a variety of designs and reality presented hereinbefore
Those of apply example, and describe in more detail below design and embodiment can in many ways in any one come it is real
It applies, this is because conception and embodiment disclosed in this invention are not limited to any embodiment.In addition, disclosed by the invention
Some aspects can be used alone, or otherwise any appropriately combined use with disclosed by the invention.
Although the present invention has been disclosed as a preferred embodiment, however, it is not to limit the invention.Skill belonging to the present invention
Has usually intellectual in art field, without departing from the spirit and scope of the present invention, when can be used for a variety of modifications and variations.
Therefore, the scope of protection of the present invention is defined by those of the claims.
Claims (10)
1. a kind of desulphurization system running optimizatin method based on big data, which is characterized in that the described method includes:
S1: it is theoretical based on energy balance and conservation of matter, desulphurization system theory mould is created according to coal fired power plant physical device component
Type sets desulfuration efficiency evaluation index, extracts operation data of the coal fired power plant in the first set period of time as modeling data；
S2: pre-processing modeling data, based on desulphurization system theoretical model, analyzes under different working conditions to desulfurization
The several factor that efficiency has an impact；
S3: carrying out big data analysis to pretreated modeling data, to obtain the key factor under different working conditions, creation
Mathematical forecasting model finds globally optimal solution of the mathematical forecasting model under different working conditions, as desulphurization system in difference
Running optimizatin strategy under working condition；
S4: being analyzed based on desulphurization system theoretical model, verifies the correctness of the running optimizatin strategy, if correctly, led
Otherwise the running optimizatin strategy out finds globally optimal solution of the mathematical forecasting model under different working conditions again.
2. the desulphurization system running optimizatin method according to claim 1 based on big data, which is characterized in that the desulfurization
Efficiency evaluation index includes the energy usage and material amounts of desulfurization process consumption.
3. the desulphurization system running optimizatin method according to claim 2 based on big data, which is characterized in that the desulfurization
Efficiency evaluation index includes the currency values equivalent with the energy of desulfurization process consumption and material.
4. the desulphurization system running optimizatin method according to claim 1 based on big data, which is characterized in that step S2
In, it is described that modeling data is pre-processed, based on desulphurization system theoretical model, analyze under different working conditions to desulfurization
The method of the several factor that efficiency has an impact the following steps are included:
S201: modeling data is pre-processed, comprising:
Confidence level audit, to reject unreasonable data therein；Supplement missing data；It is more than setpoint frequency threshold value to vibration frequency
Supplemental characteristic carry out denoising；
S202: using load as foundation, different working conditions are divided；
S203: based on different working conditions, recurrence calculating is carried out to pretreated modeling data, to obtain different operating conditions
Under the conditions of several factor that desulfuration efficiency is had an impact.
5. the desulphurization system running optimizatin method according to claim 1 based on big data, which is characterized in that step S3
In, big data analysis is carried out to pretreated modeling data, to obtain the key factor under different working conditions, creates mathematics
Prediction model finds globally optimal solution of the mathematical forecasting model under different working conditions, as desulphurization system in different operating conditions
Under the conditions of running optimizatin strategy method the following steps are included:
S301: carrying out big data analysis to pretreated modeling data, to obtain the key factor under different working conditions, benefit
With the key factor under different working conditions to create mathematical forecasting model；
S302: operation data of the coal fired power plant in the second set period of time is extracted as audit data, to mathematical forecasting model
Audited, step-up error threshold value, if audit by entering step S303, otherwise return step S301；
S303: optimal solution of the mathematical forecasting model under different working conditions is calculated, to obtain desulphurization system in different operating condition items
Running optimizatin strategy under part.
6. the desulphurization system running optimizatin method according to claim 5 based on big data, which is characterized in that the method
Further include:
Genetic algorithm is used to calculate optimal solution of the mathematical forecasting model under different working conditions.
7. the desulphurization system running optimizatin method according to claim 5 based on big data, which is characterized in that the method
Further include:
In step S302, if auditing unacceptable number reaches setting frequency threshold value, warning is issued.
8. the desulphurization system running optimizatin method according to claim 5 based on big data, which is characterized in that the method
Further include:
Grey relevance analysis is used to obtain the key factor under corresponding working condition.
9. the desulphurization system running optimizatin method according to claim 5 based on big data, which is characterized in that step S4
In, using the key factor under different working conditions, it is pre- to create corresponding mathematics to use neural network and/or vector machine method
Survey model.
10. a kind of desulphurization system operation optimizing system based on big data, which is characterized in that the system comprises:
For theoretical based on energy balance and conservation of matter, according to coal fired power plant physical device component creation desulphurization system theory mould
The module of type；
For setting the module of desulfuration efficiency evaluation index；
For extracting module of operation data of the coal fired power plant in the first set period of time as modeling data；
For carrying out pretreated module to modeling data；
For based on desulphurization system theoretical model, analyze desulfuration efficiency is had an impact under different working conditions it is several
The module of factor；
For carrying out big data analysis to pretreated modeling data, to obtain the mould of the key factor under different working conditions
Block；
For creating the module of mathematical forecasting model；
For finding globally optimal solution of the mathematical forecasting model under different working conditions, as desulphurization system in different operating condition items
The module of running optimizatin strategy under part；
For analyzing based on desulphurization system theoretical model, the module of the correctness of the running optimizatin strategy is verified, if
Correctly, the running optimizatin strategy is exported, otherwise, finds global optimum of the mathematical forecasting model under different working conditions again
Solution.
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