CN2641472Y - On-line optimization control device for boiler combustion based on computation intelligence - Google Patents
On-line optimization control device for boiler combustion based on computation intelligence Download PDFInfo
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- CN2641472Y CN2641472Y CN 03231306 CN03231306U CN2641472Y CN 2641472 Y CN2641472 Y CN 2641472Y CN 03231306 CN03231306 CN 03231306 CN 03231306 U CN03231306 U CN 03231306U CN 2641472 Y CN2641472 Y CN 2641472Y
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Abstract
The utility model discloses a boiler burning online optimization control device which is based on the computational intelligence. The utility model downloads the operational parameter of the boiler from the distributed control system through the download interface of the boiler distributed control system, and obtains the smoke evacuation component of the boiler from the boiler trailer gas component online monitoring system, and obtains the flying ash carbon content of the boiler from the flying ash carbon content monitor fixed in the tail of the boiler, the operational parameter, the smoke evacuation component and the e flying ash carbon content data of the boiler is stored in the database of the central processing computer of the burning online optimization control system to study, and built a non-linear model and a global optimization computation. The utility model is capable for obtaining the boiler optimizing operation plan of the smallest boiler when releasing the pollutants, or obtaining the biggest boiler efficiency under the releasing limit of the certain boiler pollutants, and the utility model is capable for realizing the operation plan with optimal multiple goals.
Description
Technical field
The utility model relates to computer control system, relates in particular to a kind of boiler combustion on-line optimization control device based on computational intelligence.
Background technology
Along with to the improving constantly of station boiler performance driving economy and environmental requirement, efficient, the low pollution optimization running technology of large-scale power station coal-burning boiler improves day by day.Along with continuous progress in science and technology, the operation automaticity of the coal-fired unit of big capacity improves constantly, but the burning optimization On-line Control of boiler fails to be well solved all the time.
The burning optimization of boiler mainly relies on the commissioning staff to carry out the multi-state test at present, obtains best air distribution mode at coal test commonly used, and the operations staff is with reference to operation.This method wastes time and energy, and coal changes and operating condition changes frequently because boiler uses, and actual operating mode often departs from operating condition of test.This burning method of adjustment can't realize online optimization simultaneously, can not implement corresponding adjustment scheme automatically according to the variation of service condition, makes boiler be in the optimum operation situation.
As everyone knows, the discharged nitrous oxides characteristic of boiler and boiler efficiency are subjected to having a strong impact on of combustion control level.The characteristic complexity of the discharged nitrous oxides of boiler and unburned carbon in flue dust, the influence of the factors such as control parameter such as oxygen amount, air distribution mode, load, wind powder distributing uniformity of not only being burnt, and be subjected to parameter influences such as coal, boiler and burner structure, also there is stronger coupled relation between each factor.Boiler often causes that unburned carbon in flue dust raises after adopting the low NOx combustion mode simultaneously.The complexity of boiler combustion causes the foundation of boiler combustion characteristic model very difficult, can't set up suitable combustion characteristics model, also just can't be optimized control to boiler combustion.
Summary of the invention
The utility model purpose provides a kind of boiler combustion on-line optimization control device based on computational intelligence.
It is an operational factor of downloading boiler by the download interface of Boiler Distributed Control System from Distributed Control System, obtain the smoke evacuation component of boiler from boiler tail flue gas component on-line monitoring system, and obtain the unburned carbon in flue dust of boiler from the unburned carbon in flue dust monitor that boiler tail is installed, the operational factor of boiler, smoke evacuation component and unburned carbon in flue dust data-storing learn and set up nonlinear model and global optimization computation in the database of the central processing computer of combustion on-line optimization control system.
Boiler optimization operating scheme when the utility model can obtain the discharging of minimum boiler pollutant, the maximum boiler efficiency that perhaps obtains under certain boiler pollutant discharging limit is the optimizing target, also can realize the operating scheme of multiple-objection optimization.After central processing computer obtains the optimal value of each boiler operatiopn, except instructing the operations staff to optimize the operation, operating parameter setting value after also these can being optimized uploads to DCS by the interface of uploading of DCS, the directly burning of closed-loop control boiler, thus realized the online adaptive optimal control of boiler combustion.
Description of drawings
Accompanying drawing is based on the boiler combustion on-line optimization control device block diagram of computational intelligence.
The specific embodiment
Boiler combustion on-line optimization control device based on computational intelligence is an operational factor of downloading boiler by the download interface 3 of boiler 1 Distributed Control System 2 from Distributed Control System 2, obtain the smoke evacuation component of boiler from boiler tail flue gas component on-line monitoring system 4, and obtain the unburned carbon in flue dust of boilers from the unburned carbon in flue dust monitor 5 that boiler tail is installed, the operational factor of boiler, nonlinear model and global optimization computation are learnt and set up to smoke evacuation component and unburned carbon in flue dust data-storing in the database of the central processing computer 6 of combustion on-line optimization control system.
The utility model utilizes the data download interface of station boiler Distributed Control System (DCS), the relevant operational factor of boiler is downloaded to the central processing computer of combustion on-line optimization control system from Distributed Control System, the data-interface of the online flue gas composition analytical equipment of installing by the station boiler afterbody (CEMS) and the data-interface of boiler flyash carbon content on-line measurement device, with boiler operatiopn flue gas composition and the boiler flyash carbon content central processing computer that downloads to combustion on-line optimization control system constantly, and be stored in the database.
Although the operational factor of boiler is complicated to the influence of boiler discharged nitrous oxides level and boiler efficiency, but be not that irregular can be followed yet, the non-linear relation that has more complicated between operational factor and discharged nitrous oxides level and the boiler efficiency, because the adjustable parameter of boiler is many, and have stronger coupled relation between each adjustable parameter, therefore this relation is difficult to be expressed with the simple mathematical expression formula.
A large amount of boiler operating parameters of storing in the database are to the historical data of boiler efficiency and pollutant emission, and these historical datas can adopt the mathematical method based on computational intelligence to make up relation between boiler operating parameter and boiler efficiency and the pollutant emission level.The available method based on computational intelligence mainly contains: neural net method, bayes method and support vector machine method etc.
In conjunction with the mathematical modeling method based on computational intelligence, the central processing computer of combustion on-line optimization control system can obtain the operational factor of boiler and the relation between boiler discharged nitrous oxides level and the boiler efficiency.
On the basis of realizing boiler pollutant discharging and boiler efficiency modeling, the central processing computer of combustion on-line optimization control system can adopt global optimization method such as genetic algorithm, simulated annealing, TABU search, methods such as statistical learning are found the solution the maximum boiler efficiency of the pursuit boiler operatiopn scheme in following time that obtains, comprise the oxygen value, each throttle opening value, the coal pulverizer mode that puts into operation, the concrete optimization numerical value of various boiler operating parameters such as burner hearth and bellows differential pressure, the operations staff adopts the boiler operating parameter of optimization to adjust boiler combustion, just can obtain maximum boiler efficiency, thereby improve the economy of power plant's operation.
Equally, as change the target of global optimizing, boiler optimization operating scheme in the time of also can obtaining the discharging of minimum boiler pollutant is the optimizing target with the maximum boiler efficiency under certain boiler pollutant discharging limit also perhaps, also can realize the operating scheme of multiple-objection optimization.
After central processing computer obtains the optimal value of each boiler operatiopn, except instructing the operations staff to optimize the operation, operating parameter setting value after also these can being optimized uploads to DCS by the interface of uploading of DCS, the directly burning of closed-loop control boiler, thus realized the online adaptive optimal control of boiler combustion.
System downloads the operational factor of boiler from DCS by the download interface of the Distributed Control System (DCS) of boiler, the flue gas composition on-line monitoring system of installing from boiler tail (CEMS) obtains the smoke evacuation component of boiler, and obtains the unburned carbon in flue dust of boiler from the unburned carbon in flue dust monitor that boiler tail is installed.
Gather real time data and mainly contain following several method from DCS: the MIS network interface card that (1) utilizes DCS to provide, some DCS allow PC to link to each other with the DCS communications loop by MIS network interface card, and DCS links to each other with the harvester serial ports by serial ports simultaneously.(2) serial ports by each printing server of DCS transmits real time data, and harvester transmits real time data from the printer server serial ports.Existing system does not need to increase any equipment, and Installation and Debugging do not constitute influence to system.But when breaking down, transfer of data can go wrong as the order management system (MCS) of DCS.(3) utilize multifunctional processor (MFC) module among some DCS, this module allows the user that the output data point is carried out configuration, module after the configuration can periodically receive and the output real time data from the data high-speed highway, is connected with interface message processor (IMP) by standard output interface such as RS-232 etc.This method work quantity is less, and interface message processor (IMP) is passive monitoring to module simultaneously, can not exert an influence to production control.
The operational factor of boiler, smoke evacuation component and unburned carbon in flue dust data-storing are in the database of the central processing computer of combustion on-line optimization control system, central processing computer carries out study based on computational intelligence to these data, utilize neutral net, Bayesian network, SVMs equal samples learning method, operational factor is learnt, thereby set up the boiler exhaust gas component, the nonlinear model between parameter such as unburned carbon in flue dust and the boiler operating parameter.Central processing computer utilizes this nonlinear model to carry out global optimization computation subsequently, calculate to obtain minimum smoke-discharging pollution thing concentration of emission or (with) boiler operating parameter under the maximum boiler efficiency, these operational factors can be used for the operation that the boiler operatiopn personnel are instructed in open loop, also can be directly the interface 7 of uploading by DCS enter the on-line optimization closed-loop control that Boiler Distributed Control System realizes boiler combustion.
Claims (1)
1. boiler combustion on-line optimization control device based on computational intelligence, it is characterized in that it has boiler (1), boiler and Distributed Control System (2) are joined, Distributed Control System (2) successively with download interface (3), the central processing computer of on-line optimization control system (6) joins, Distributed Control System (2) successively with DCS upload interface (7), the central processing computer of on-line optimization control system (6) joins, boiler respectively with on-line monitoring system (4), unburned carbon in flue dust monitor (5) joins, the central processing computer of on-line optimization control system (6) respectively with on-line monitoring system (4), unburned carbon in flue dust monitor (5) joins.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 03231306 CN2641472Y (en) | 2003-05-16 | 2003-05-16 | On-line optimization control device for boiler combustion based on computation intelligence |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN 03231306 CN2641472Y (en) | 2003-05-16 | 2003-05-16 | On-line optimization control device for boiler combustion based on computation intelligence |
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| Publication Number | Publication Date |
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| CN2641472Y true CN2641472Y (en) | 2004-09-15 |
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| CN 03231306 Expired - Lifetime CN2641472Y (en) | 2003-05-16 | 2003-05-16 | On-line optimization control device for boiler combustion based on computation intelligence |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100535512C (en) * | 2007-12-27 | 2009-09-02 | 上海交通大学 | Optimizing and guiding system for coal-burned industrial boiler operation |
| CN101634459A (en) * | 2009-08-24 | 2010-01-27 | 陶晓鹏 | Thermal power generation boiler intelligent combustion optimizing system and realizing method thereof |
| CN101561148B (en) * | 2009-05-08 | 2011-07-13 | 上海颖科计算机科技有限公司 | Boiler combustion control system and method |
| CN101684944B (en) * | 2008-09-28 | 2011-07-20 | 宝山钢铁股份有限公司 | Self-optimizing combustion control method of blast-furnace hot blast stove |
| CN103576655A (en) * | 2013-11-06 | 2014-02-12 | 华北电力大学（保定） | Method and system for utility boiler combustion subspace modeling and multi-objective optimization |
| CN103577681A (en) * | 2013-06-26 | 2014-02-12 | 长沙理工大学 | Factor analysis-based quantitative evaluation method on of boiler efficiency influence indexes |
| CN104763999A (en) * | 2015-03-04 | 2015-07-08 | 内蒙古瑞特优化科技股份有限公司 | Power plant pulverized coal boiler combustion performance online optimizing method and system |
-
2003
- 2003-05-16 CN CN 03231306 patent/CN2641472Y/en not_active Expired - Lifetime
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100535512C (en) * | 2007-12-27 | 2009-09-02 | 上海交通大学 | Optimizing and guiding system for coal-burned industrial boiler operation |
| CN101684944B (en) * | 2008-09-28 | 2011-07-20 | 宝山钢铁股份有限公司 | Self-optimizing combustion control method of blast-furnace hot blast stove |
| CN101561148B (en) * | 2009-05-08 | 2011-07-13 | 上海颖科计算机科技有限公司 | Boiler combustion control system and method |
| CN101634459A (en) * | 2009-08-24 | 2010-01-27 | 陶晓鹏 | Thermal power generation boiler intelligent combustion optimizing system and realizing method thereof |
| CN103577681A (en) * | 2013-06-26 | 2014-02-12 | 长沙理工大学 | Factor analysis-based quantitative evaluation method on of boiler efficiency influence indexes |
| CN103576655A (en) * | 2013-11-06 | 2014-02-12 | 华北电力大学（保定） | Method and system for utility boiler combustion subspace modeling and multi-objective optimization |
| CN103576655B (en) * | 2013-11-06 | 2016-03-02 | 华北电力大学（保定） | A kind of power boiler burning subspace modeling and Multipurpose Optimal Method and system |
| CN104763999A (en) * | 2015-03-04 | 2015-07-08 | 内蒙古瑞特优化科技股份有限公司 | Power plant pulverized coal boiler combustion performance online optimizing method and system |
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| Date | Code | Title | Description |
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| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C17 | Cessation of patent right | ||
| CX01 | Expiry of patent term |
Expiration termination date: 20130516 Granted publication date: 20040915 |