CN105259758A - Thermal power unit operating parameter intelligent online optimization method based on massive historical data - Google Patents
Thermal power unit operating parameter intelligent online optimization method based on massive historical data Download PDFInfo
- Publication number
- CN105259758A CN105259758A CN201510695780.0A CN201510695780A CN105259758A CN 105259758 A CN105259758 A CN 105259758A CN 201510695780 A CN201510695780 A CN 201510695780A CN 105259758 A CN105259758 A CN 105259758A
- Authority
- CN
- China
- Prior art keywords
- parameter
- uncontrollable
- temperature
- case library
- historical data
- 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.)
- Pending
Links
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a thermal power unit operating parameter intelligent online optimization method based on massive historical data. The method comprises the steps of 1) setting optimization parameters, consisting of uncontrollable parameters which are the unit load, circulating water inlet temperature, ash content as received basis, moisture as received basis and the like, and controllable parameters which are the main steam temperature, main steam pressure, reheat steam temperature, vacuum, feed-water temperature, overheating attemperating water amount and the like; 2) extracting six uncontrollable parameters in 15 minutes, searching a case library for similar operation conditions according to a matching algorithm, if similar operation conditions can be found in the case library, going a step 4), and otherwise going to a step 3); 3) searching historical data for one operation condition with the lowest rate of coal consumption in a year according to the six uncontrollable parameter based on the matching algorithm; 4) finding out or nine controllable parameter optimization values in the corresponding case under a timestamp; and 5) storing the optimized result in the case library if the result is not in the case library.
Description
Technical field:
The invention belongs to thermal power generating technology field, be specifically related to a kind of based on mass historical data thermal power unit operation parameter intelligent online optimizing method.
Background technology:
At present, the adoptable optimization target values of fired power generating unit has design load, calculated value, trial value and empirical value, these methods are all also existing drawback in varying degrees, because some unit thermodynamic system sets up accurate mathematical model, obtain economical operation calculating desired value and also have difficulties; Get design parameter is generally applicable to be with basic load unit as desired value, for the unit of long-term variable load operation, uncomfortable conjunction design load is as desired value; Test method is then tested by set optimization, and by carrying out repetition test and adjustment to multiple typical load operating mode, the problem of test method is that experimentation cost is high, and the target operating condition point obtained is limited.
Summary of the invention:
Desired value is basis and the key problem of diagnosis of energy saving optimization, due to the drawback of prior art, the object of the invention is to determine unit optimal objective value accurately in real time, provide based on mass historical data thermal power unit operation parameter intelligent online optimizing method, the method passes through history steady state data optimizing value as Calculation Basis and basis for estimation, the operation characteristic change of the unit of tracking in time own, determines unit optimal objective value online.
For achieving the above object, the present invention adopts following technical scheme to realize:
Based on mass historical data thermal power unit operation parameter intelligent online optimizing method, comprise the steps:
1) set the parameter of optimizing, comprise uncontrollable parameter and controllable parameter, wherein, uncontrollable parameter is: unit load, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter and as received basis low heat value; Controllable parameter is: main steam temperature, main steam pressure, reheat steam temperature, vacuum, feed temperature, overheated spray water flux, reheating spray water flux, flue gas oxygen content and exhaust gas temperature;
2) unit load value, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter and as received basis low heat value 6 the uncontrollable parameters extracted in 15 minutes are pressed matching algorithm and are found operating condition close in case library, if this operating mode can be found in case library, then enter step 4), if can not find in case library, enter step 3);
3) 1 minimum operating mode of coa consumption rate in a year is found according to unit load value, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter and as received basis low heat value 6 uncontrollable parameters by matching algorithm in the historical data;
4) find out the main steam temperature under corresponding case or time stamp, main steam pressure, reheat steam temperature, vacuum, feed temperature, cross diminishing flow, again diminishing flow, flue gas oxygen content and exhaust gas temperature 9 controllable parameter optimizing values;
5) if the result that this time optimizing obtains does not have in case library, be then saved in case library.
The present invention further improves and is, step 2) and 3) in, matching algorithm is as follows:
The similarity utilizing the geometric model method based on Distance geometry directional information to carry out unit operation operating mode case describes, current steady state operating condition data x
qwith case x in unit case library
isimilarity function can be expressed as:
In formula, i=1 to 6, j=1 to 6, x
qjbe respectively the value of lower 6 the real-time measuring points of uncontrollable parameter of current steady state operating condition, x
ijrepresent the case value of 6 uncontrollable parameters in unit case library respectively, w
1, w
2for weight factor, be taken as 0.75 and 0.25 respectively; D (x
q, x
i) represent range information, γ
jrepresent the weighting coefficient of 6 uncontrollable parameters respectively, be taken as 0.3,0.2,0.1,0.1,0.1,0.2, cos (δ respectively
i) represent case directional information;
Formula (1) is utilized to calculate current steady state operating condition data and unit history operating mode similarity S
i, be greater than similarity threshold S by all
vhistory operating mode all as coupling operating mode.
The present invention further improves and is, similarity threshold S
vvalue is 0.8.
Relative to prior art, the present invention has following beneficial effect:
The present invention adopts based on history steady state data optimizing value as the Calculation Basis of the functional modules such as Optimized Diagnosis and basis for estimation, and the operation characteristic change of the unit of tracking in time own, determines unit target operating condition online.The present invention can meet the demand of producing the functional modules such as Examination of Small Indicators, power consumption analysis, running optimizatin, diagnosis of energy saving in real-time live, and then improves and improve unit performance.
Accompanying drawing illustrates:
Fig. 1 is the process flow diagram that the present invention is based on mass historical data thermal power unit operation parameter intelligent online optimizing method.
Fig. 2 is Present Thermal Power unit operation parameter intelligent online optimizing figure.
Embodiment:
Below in conjunction with concrete enforcement, the present invention will be further described.
Based on mass historical data thermal power unit operation parameter intelligent online optimizing method, as shown in Figure 1, detailed step comprises following content to its calculation process:
1) set the parameter of optimizing, uncontrollable parameter is: unit load, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter, as received basis low heat value; Controllable parameter is: main steam temperature, main steam pressure, reheat steam temperature, vacuum, feed temperature, overheated spray water flux, reheating spray water flux, flue gas oxygen content, exhaust gas temperature;
In actual motion, as shown in table 1 by the data gathering the above-mentioned uncontrollable parameter drawn:
Table 1:
Parameter name | Unit | Steady-state operation value |
Unit load | MW | 310.19 |
Inlet Temperature of Circulating Water | ℃ | 22.6 |
As received basis ash content | % | 18.06 |
Moisture as received coal | % | 9.5 |
Dry ash-free basis volatile matter | % | 34.12 |
As received basis low heat value | kJ/kg | 22640 |
2) 1 minimum operating mode of coa consumption rate in a year is found according to controllable parameters such as unit load value, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter, as received basis low heat values by matching algorithm in the historical data, the controllable parameter optimizing values such as main steam temperature corresponding under finding out this operating mode, main steam pressure, reheat steam temperature, vacuum, feed temperature, excessively diminishing flow, again diminishing flow, flue gas oxygen content, exhaust gas temperature, the optimizing result obtained is as shown in Figure 2;
Each optimizing parameter value corresponding to the operating mode that the coal consumption calculated under all coupling operating modes by matching algorithm is minimum is as follows:
Table 2:
Power plant operations staff can be instructed to adjust current operating parameter in time by above-mentioned optimizing parameter value, under making the unit moment be in optimized operation condition, and meet the function needs such as Examination of Small Indicators, power consumption analysis, running optimizatin, diagnosis of energy saving of production scene further, improve and improve unit performance.
Claims (3)
1., based on mass historical data thermal power unit operation parameter intelligent online optimizing method, it is characterized in that, comprise the steps:
1) set the parameter of optimizing, comprise uncontrollable parameter and controllable parameter, wherein, uncontrollable parameter is: unit load, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter and as received basis low heat value; Controllable parameter is: main steam temperature, main steam pressure, reheat steam temperature, vacuum, feed temperature, overheated spray water flux, reheating spray water flux, flue gas oxygen content and exhaust gas temperature;
2) unit load value, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter and as received basis low heat value 6 the uncontrollable parameters extracted in 15 minutes are pressed matching algorithm and are found operating condition close in case library, if this operating mode can be found in case library, then enter step 4), if can not find in case library, enter step 3);
3) 1 minimum operating mode of coa consumption rate in a year is found according to unit load value, Inlet Temperature of Circulating Water, as received basis ash content, moisture as received coal, dry ash-free basis volatile matter and as received basis low heat value 6 uncontrollable parameters by matching algorithm in the historical data;
4) find out the main steam temperature under corresponding case or time stamp, main steam pressure, reheat steam temperature, vacuum, feed temperature, cross diminishing flow, again diminishing flow, flue gas oxygen content and exhaust gas temperature 9 controllable parameter optimizing values;
5) if the result that this time optimizing obtains does not have in case library, be then saved in case library.
2. according to claim 1 based on mass historical data thermal power unit operation parameter intelligent online optimizing method, it is characterized in that, step 2) and 3) in, matching algorithm is as follows:
The similarity utilizing the geometric model method based on Distance geometry directional information to carry out unit operation operating mode case describes, current steady state operating condition data x
qwith case x in unit case library
isimilarity function can be expressed as:
In formula, i=1 to 6, j=1 to 6, x
qjbe respectively the value of lower 6 the real-time measuring points of uncontrollable parameter of current steady state operating condition, x
ijrepresent the case value of 6 uncontrollable parameters in unit case library respectively, w
1, w
2for weight factor, be taken as 0.75 and 0.25 respectively; D (x
q, x
i) represent range information, γ
jrepresent the weighting coefficient of 6 uncontrollable parameters respectively, be taken as 0.3,0.2,0.1,0.1,0.1,0.2, cos (δ respectively
i) represent case directional information;
Formula (1) is utilized to calculate current steady state operating condition data and unit history operating mode similarity S
i, be greater than similarity threshold S by all
vhistory operating mode all as coupling operating mode.
3. according to claim 2 based on mass historical data thermal power unit operation parameter intelligent online optimizing method, it is characterized in that, similarity threshold S
vvalue is 0.8.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510695780.0A CN105259758A (en) | 2015-10-22 | 2015-10-22 | Thermal power unit operating parameter intelligent online optimization method based on massive historical data |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201510695780.0A CN105259758A (en) | 2015-10-22 | 2015-10-22 | Thermal power unit operating parameter intelligent online optimization method based on massive historical data |
Publications (1)
Publication Number | Publication Date |
---|---|
CN105259758A true CN105259758A (en) | 2016-01-20 |
Family
ID=55099503
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201510695780.0A Pending CN105259758A (en) | 2015-10-22 | 2015-10-22 | Thermal power unit operating parameter intelligent online optimization method based on massive historical data |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN105259758A (en) |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110556033A (en) * | 2019-07-30 | 2019-12-10 | 华电青岛发电有限公司 | Operation guiding system based on typical and accident case base of thermal power plant |
CN110837226A (en) * | 2019-12-26 | 2020-02-25 | 华润电力技术研究院有限公司 | Thermal power generating unit operation optimization method based on intelligent optimization algorithm and related device |
CN110989360A (en) * | 2019-12-23 | 2020-04-10 | 武汉博晟信息科技有限公司 | Thermal power generating unit steady-state history optimizing method based on full data |
CN111061148A (en) * | 2018-10-17 | 2020-04-24 | 帆宣***科技股份有限公司 | Intelligent pre-diagnosis and health management system and method |
CN111178576A (en) * | 2019-11-19 | 2020-05-19 | 浙江中控技术股份有限公司 | Operation optimization method based on refining device operation data |
CN111399382A (en) * | 2020-04-07 | 2020-07-10 | 无锡信捷电气股份有限公司 | Control method based on full-automatic down filling machine |
CN111539546A (en) * | 2019-02-01 | 2020-08-14 | 帆宣***科技股份有限公司 | Modeling method of intelligent pre-diagnosis and health management system and computer program product thereof |
CN111639802A (en) * | 2020-05-28 | 2020-09-08 | 中电投珠海横琴热电有限公司 | Combustion engine unit operation optimization guidance method |
CN112488380A (en) * | 2020-11-26 | 2021-03-12 | 西安西热电站信息技术有限公司 | Unit steady-state working condition matching method and system based on similarity dynamic model |
CN113095591A (en) * | 2021-04-29 | 2021-07-09 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Consumption difference analysis method for self-optimization of operation parameters of thermal power generating unit |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101187804A (en) * | 2006-11-15 | 2008-05-28 | 北京华电天仁电力控制技术有限公司 | Thermal power unit operation optimization rule extraction method based on data excavation |
CN102708180A (en) * | 2012-05-09 | 2012-10-03 | 北京华电天仁电力控制技术有限公司 | Data mining method in unit operation mode based on real-time historical library |
CN103279658A (en) * | 2013-05-21 | 2013-09-04 | 广东电网公司电力科学研究院 | Thermal generator set working condition optimizing method |
CN103838216A (en) * | 2014-03-07 | 2014-06-04 | 华北电力大学(保定) | Power station boiler combustion optimization method based on data driven case matching |
CN104035331A (en) * | 2014-01-10 | 2014-09-10 | 上海白丁电子科技有限公司 | Machine group operation optimization guidance system and equipment thereof |
CN104712378A (en) * | 2015-02-06 | 2015-06-17 | 广东电网有限责任公司电力科学研究院 | Main steam pressure closed loop energy-saving control method and system for thermal power generating unit |
-
2015
- 2015-10-22 CN CN201510695780.0A patent/CN105259758A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101187804A (en) * | 2006-11-15 | 2008-05-28 | 北京华电天仁电力控制技术有限公司 | Thermal power unit operation optimization rule extraction method based on data excavation |
CN102708180A (en) * | 2012-05-09 | 2012-10-03 | 北京华电天仁电力控制技术有限公司 | Data mining method in unit operation mode based on real-time historical library |
CN103279658A (en) * | 2013-05-21 | 2013-09-04 | 广东电网公司电力科学研究院 | Thermal generator set working condition optimizing method |
CN104035331A (en) * | 2014-01-10 | 2014-09-10 | 上海白丁电子科技有限公司 | Machine group operation optimization guidance system and equipment thereof |
CN103838216A (en) * | 2014-03-07 | 2014-06-04 | 华北电力大学(保定) | Power station boiler combustion optimization method based on data driven case matching |
CN104712378A (en) * | 2015-02-06 | 2015-06-17 | 广东电网有限责任公司电力科学研究院 | Main steam pressure closed loop energy-saving control method and system for thermal power generating unit |
Non-Patent Citations (1)
Title |
---|
王伟等: "基于运行性能评价的发电过程可控参数优化方法", 《热力发电》 * |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111061148A (en) * | 2018-10-17 | 2020-04-24 | 帆宣***科技股份有限公司 | Intelligent pre-diagnosis and health management system and method |
CN111539546A (en) * | 2019-02-01 | 2020-08-14 | 帆宣***科技股份有限公司 | Modeling method of intelligent pre-diagnosis and health management system and computer program product thereof |
CN110556033A (en) * | 2019-07-30 | 2019-12-10 | 华电青岛发电有限公司 | Operation guiding system based on typical and accident case base of thermal power plant |
CN111178576A (en) * | 2019-11-19 | 2020-05-19 | 浙江中控技术股份有限公司 | Operation optimization method based on refining device operation data |
CN111178576B (en) * | 2019-11-19 | 2023-09-05 | 浙江中控技术股份有限公司 | Operation optimization method based on refining device operation data |
CN110989360A (en) * | 2019-12-23 | 2020-04-10 | 武汉博晟信息科技有限公司 | Thermal power generating unit steady-state history optimizing method based on full data |
CN110837226A (en) * | 2019-12-26 | 2020-02-25 | 华润电力技术研究院有限公司 | Thermal power generating unit operation optimization method based on intelligent optimization algorithm and related device |
CN111399382A (en) * | 2020-04-07 | 2020-07-10 | 无锡信捷电气股份有限公司 | Control method based on full-automatic down filling machine |
CN111639802A (en) * | 2020-05-28 | 2020-09-08 | 中电投珠海横琴热电有限公司 | Combustion engine unit operation optimization guidance method |
CN112488380A (en) * | 2020-11-26 | 2021-03-12 | 西安西热电站信息技术有限公司 | Unit steady-state working condition matching method and system based on similarity dynamic model |
CN112488380B (en) * | 2020-11-26 | 2024-04-12 | 西安西热电站信息技术有限公司 | Unit steady-state working condition matching method and system based on similarity dynamic model |
CN113095591A (en) * | 2021-04-29 | 2021-07-09 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Consumption difference analysis method for self-optimization of operation parameters of thermal power generating unit |
CN113095591B (en) * | 2021-04-29 | 2023-03-21 | 中国大唐集团科学技术研究院有限公司中南电力试验研究院 | Consumption difference analysis method for self-optimization of operation parameters of thermal power generating unit |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN105259758A (en) | Thermal power unit operating parameter intelligent online optimization method based on massive historical data | |
CN107796851B (en) | Online monitoring method for heat value of blast furnace gas entering furnace and heat efficiency of furnace | |
CN113822496B (en) | Multi-unit thermal power plant heat supply mode and parameter online optimizing method | |
WO2017050207A1 (en) | Method for analyzing energy efficiency of generator set | |
CN105787211B (en) | For the Combined Cycle Heat Recovery Boiler pressure method of adjustment of combustion gas turbine deterioration | |
CN110288135B (en) | Drainage water level energy-saving optimization method for high-pressure heating system | |
CN105787271B (en) | The adjustable output Interval evaluation method of thermal power plant unit based on big data analytical technology | |
CN111754030B (en) | Thermal power generating unit power supply coal consumption optimization method based on HAC and RF-GA | |
CN103679549B (en) | Energy-saving for Thermal Power Units Potentials method | |
CN105275508A (en) | Steam turbine flow curve identification and optimization method based on power value calculation | |
CN111639802A (en) | Combustion engine unit operation optimization guidance method | |
CN104088771B (en) | The accurate determination method of circulating cooling water of power plant system water pump assembly optimum combination operating scheme | |
CN103512768A (en) | System and method for monitoring performance of thermal power generating unit | |
CN105046064A (en) | Calculation method for electric load adjustable range of heat and power cogeneration unit in heating period | |
CN113343490B (en) | Industrial steam supply power station operation optimization method and system coupled with molten salt heat storage | |
CN103678915A (en) | Thermal power plant generator set varying duty energy consumption analysis method based on approach method | |
CN111159624A (en) | Method for calculating heat supply coal consumption rate of new steam and extracted steam combined heat supply unit | |
CN112000012B (en) | Unit sliding pressure control optimization method and system based on thermoelectric load condition | |
CN103576553A (en) | Fractional-order self-adjusting control method for steam temperature of coal-fired boiler | |
CN105512800A (en) | Method for determining peak adjustment scheduling of heat supply unit according to mode of ordering power by heat | |
CN102661820A (en) | Method for determining actual heat consumption of steam extraction heat supply machine | |
CN103309314A (en) | Metal wall temperature early warning optimization control method of high-temperature super-heater of supercritical coal-fired unit | |
CN103699786B (en) | Energy consumption difference analysis method for load varying of ultra-supercritical generating unit of thermal power plant | |
CN103235512B (en) | A kind of method that genset runs | |
CN113283121A (en) | Flow and capacity design method and system for molten salt heat storage industrial steam supply system |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WD01 | Invention patent application deemed withdrawn after publication | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20160120 |