CN104504509A - Dynamic reference value-adopting thermal power plant consumption analyzing system and method - Google Patents
Dynamic reference value-adopting thermal power plant consumption analyzing system and method Download PDFInfo
- Publication number
- CN104504509A CN104504509A CN201410776788.5A CN201410776788A CN104504509A CN 104504509 A CN104504509 A CN 104504509A CN 201410776788 A CN201410776788 A CN 201410776788A CN 104504509 A CN104504509 A CN 104504509A
- Authority
- CN
- China
- Prior art keywords
- power plant
- thermal power
- controllable factor
- data
- factor
- 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.)
- Granted
Links
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
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- 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—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas 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
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
- Y02P90/82—Energy audits or management systems therefor
Abstract
The invention discloses a dynamic reference value-adopting thermal power plant consumption analyzing system and a dynamic reference value-adopting thermal power plant consumption analyzing method and relates to the technology of thermal power generation unit operation. The system comprises a thermal power generation unit, an electric power plant operation monitor, a data statistic processor, an optimizing operation score calculator and a data publishing device which are sequentially connected. The method comprises the following steps of 1, determining a boundary condition; 2, determining an optimal working condition; 3, creating an optimal working condition database. A new reference value is changed with the change of operation conditions; when a consumption function is calculated, operator controllable factors which can be controlled and are more closely related to the actual operation of an operator are selected to perform calculation; the relation between an evaluation index and each operation factor is established, the optimal operation under various working conditions is established, and the system and the method have guiding significance to the operation of the operator; the interference of external uncontrollable environmental conditions to an evaluation system is eliminated to a certain degree by selecting a convenient condition.
Description
Technical field
The present invention relates to thermal power unit operation control technology, especially relate to a kind of the thermal power plant's Consumption Difference Analysing System and the method thereof that adopt dynamic benchmark value.
Background technology
Thermal power plant's power consumption analysis, as the basic research work of unit running optimization, is optimal power plant operation, energy-saving and cost-reducing basis.Abroad start in the 60's of 20th century, China then just starts to walk in the 70's of 20th century and is developed rapidly.The accuracy of power consumption analysis theory depends on determining whether accurately of optimization target values.Theoretical research at present about thermal power plant's power consumption analysis mainly concentrates on: the research of optimization target values problem identificatioin, optimization target values is operation instruction science, believable support accurately.
At present, the optimization target values in domestic Consumption Difference Analysing System mainly also adopts non real-time reference value, do not consider the change of environmental parameter and working conditions change larger time unit performance change; And external monitoring and optimization system dynamically can provide the controlling value reducing energy loss in real time to operations staff.Visible, still there is a certain distance in China with optimizing operation technical elements in Fossil-fired Unit Performance monitoring compared with abroad.By investigating domestic five large electricity power enterprises, obtaining China and mainly containing following several for the defining method of power consumption analysis optimization target values at present:
1. the design load that manufacturing plant provides is adopted;
2. the result of unit thermal test is adopted;
3. variable working condition thermodynamic computing result is adopted;
4. the statistical value of historical data is adopted;
5. automatic optimal is determined;
6. data mining technology;
7. full index system.
During fixed pressure operation, for the optimization target values of class parameters such as main steam pressure, main steam temperature and reheat steam temperature, each power plant design load that all manufacturing plant of the side of employing provides is determined; When unit sliding pressure operation, the general optimization target values adopting the method for thermal test or variable working condition thermodynamic computing to obtain main vapour pressure under different load (or main steam flow).Other is as the determination of exhaust gas temperature, flying marking rate, loss of steam and water, steam turbine vacuum, feed temperature, main spray water flux, station service power consumption rate and boiler efficiency parameter, each employing diverse ways, in the power plant of investigation, You Liangjia power plant employing method 1. and 2., method 3. 4. and 5. Ge Youyijia power plant adopt.
Employing method 1., the designing for manufacturing data of unit equipment are the firsthand information about machine unit characteristic that manufacturing plant is supplied to power plant, apply it simple and easy to do as reference value, but the thermodynamic property that the change of the equipment matching problem that unit equipment exists in installation process and operational process conditional causes change is easily left in the basket, therefore applies merely design load and do not conform to reality.
Employing method is 2., better at system cloud gray model initial performances, but along with the prolongation of working time, the state of unit changes, and optimization target values also should change to some extent, but, generating plant often can not carry out a large amount of thermal tests, and optimization target values and unit actual motion state are not met.
3., result of calculation is subject to the impact of variable working condition Thermodynamic calculating model to employing method on the one hand, and on the other hand, the optimization target values calculated is theoretical value, more difficult realization in actual motion, have impact on the directive function to running.
4., on the one hand, statistics is loaded down with trivial details time-consuming for employing method, on the other hand, raw data through checking, just need have credibility, therefore, statistics will be selected through typical data, data verification, boundary condition analysis, finally draw optimization target values, because this process is loaded down with trivial details, the system of adopting in this way does not generally also carry out regular renewal to optimization target values, and optimization target values and set state are not met.
Employing method, 5. because boundary condition is numerous, causes the curve of optimization target values to be difficult to statistics in the short period of time and completes.Therefore, determine that the optimization target values of operating index should consider its accuracy, real-time and feasibility.If the optimization target values drawn is in operation the equipment that do not meet virtual condition or can not reach in actual motion, just can not play good directive function to operation.
7. employing method, proposes to set up the full index system of thermal power plant's power consumption analysis.To reflect that thermal power plant's energy consumption is for cardinal principle comprehensively, objectively, on the basis that qualitative and quantitative is comprehensively analyzed, follow the science and operability principle of setting up index system, avoid the overlap between index, consider data easily getting property, establish the full index system of power consumption analysis, but the index row in the method does not get rid of extraneous uncontrollable environmental baseline to the interference of appraisement system, and the weight coefficient of each index does not consider the impact of unit consumption difference and variation range, the result of calculating is comparatively coarse.
Summary of the invention
The present invention seeks to, for technical matters existing in prior art, to provide a kind of the thermal power plant's Consumption Difference Analysing System and the method thereof that adopt dynamic benchmark value.
New consumption difference function account form is chosen and is contacted with actual motion human users the controllable factor that operations staff is controlled more closely and calculate, instead of three grades of in the past selected examination Small Indicators; Dynamic benchmark value changes along with the change of operating condition, and is no longer the unique value determined.
For achieving the above object, the present invention takes following technical scheme:
One, thermal power plant's Consumption Difference Analysing System (abbreviation system) of dynamic benchmark value is adopted
Native system carries out power plant's service data collection with DCS, SIS system, by MINITAB software, statistics and analysis is carried out to data, be optimized running score on this basis to calculate, and then distributing data, evaluation and operational management are carried out to operations staff, realize the authentic assessment to the operation behavior of operations staff, finally realize the continuous advancement of thermal power plant's running optimizatin.
Preposition collection, the statistics and analysis comprising data of system, collecting part is made up of DCS, SIS system.Carry out adding up on backstage by MINITANB software after data acquisition and analyze.
After the collection of data, statistics and analysis complete, optimizing operation score calculates by the optimizing operation score computing system software simulating on backstage, and distributing data.
Specifically, native system comprises target---fired power generating unit; Be provided with power plant's service data monitor, data statistics processing device, evaluation index counter and data publication device;
Its annexation is: fired power generating unit, power plant's operational monitoring device, data statistics processing device, evaluation index counter is connected successively with data publication.
Two, the method (abbreviation method) of thermal power plant's power consumption analysis of dynamic benchmark value is adopted
This method comprises the following steps:
1. boundary condition is determined
Adopt new controllable factor, determine again the variation range of crucial controllable factor, then under determining each arbitrary boundary conditions, utilize Minitab software to solve out to the regression equation of each crucial controllable factor to optimizing evaluation, namely the expression formula under each boundary condition is set up: Y=f(x1, x2, x3 ...)
Y: dynamic benchmark value, x1, x2, x3 ...: various dissimilar controllable factor;
2. optimum operating condition is determined
By Minitab software analysis optimum operating condition point, determine the crucial controllable factor definite value under optimum operating condition point, be just to locate a kind of combination of each controllable factor, to make Y minimum;
3. optimum operating condition database is set up
Obtain under each boundary condition optimum controllable factor combination x1, x2, x3 ...
optimum, as the reference parameter data storehouse under each arbitrary boundary conditions.
Tool of the present invention has the following advantages and good effect:
1. new reference value changes along with the change of operating condition, unlike being all the same value determined under different operating conditions in computing method in the past, and not too science;
2. when calculating consumption difference function, what chose is three grades of examination Small Indicators in the past, and what choose here is contact with actual motion human users the controllable factor that operations staff is controlled more closely to calculate;
3. establish the relation between evaluation index and each operations factor, establish Optimum Operation under various operating mode, have directive significance to the operation of operations staff;
4. extraneous uncontrollable environmental baseline is eliminated to a certain extent to the interference of appraisement system by being chosen at of convenient condition.
Accompanying drawing explanation
Fig. 1 is the block diagram of native system, in figure:
100-fired power generating unit; 101-power plant service data monitor; 102-data statistics processing device
103-evaluation index counter, 104-data publication device;
Fig. 2 is that this method chooses the sub-process figure calculating consumption difference function controllable factor;
Fig. 3 is the sub-process figure that this method finds dynamic benchmark parameter.
english to Chinese:
1, DCS:Distributed Control System, dcs;
2, SIS:Supervisory Information System in Plant Level, SIS in Thermal Power PlantQ.
Embodiment
Describe in detail below in conjunction with drawings and Examples.
One, system
1, overall
As Fig. 1, the present invention includes target---fired power generating unit 100; Be provided with power plant's service data monitor 101, data statistics processing device 102, evaluation index counter 103 and data publication device 104;
Its annexation is: fired power generating unit 100, power plant's operational monitoring device 101, and data statistics processing device 102, optimizing operation score counter 103 is connected successively with data publication 104.
2, functional part
Following function parts are common apparatus.
0) fired power generating unit 100
Fired power generating unit 100 refers to thermal power generation unit.
1) power plant's operational monitoring device 101
Power plant's operational monitoring device 101 is a kind of equipment every service data of thermal power plant being carried out to Real-Time Monitoring and collection, wherein includes general working software DCS and SIS.
2) data statistics processing device 102
Data statistics processing device 102 is the equipment that a kind of data to collecting are added up and processed, and wherein includes general working software MINITANB(commercially available).
3) evaluation index counter 103
Evaluation index counter 103 refers to general counter, calculates the index score of operations staff;
Its software is designed, designed, relates to method step and sub-process thereof.
4) data publication device 104
The current parameters value of data publication device 104 pairs of systems and index score value carry out data publication.
The working mechanism of native system:
For fired power generating unit 100, gather power plant's service data by power plant's operational monitoring device 101, by data statistics processing device 102 pairs of data statistic analysis, and carry out Calculation Estimation index by evaluation index counter 103, eventually through data publication device 104 distributing data, realize optimizing operation evaluation.
Two, method
1, the sub-process calculating consumption difference function controllable factor is chosen
As Fig. 2, choose the sub-process calculating consumption difference function controllable factor as follows:
Index 201 is set up on A, definition border
Determine the operating mode border of unit, namely determine which extraneous factor comprises as coal, rate of load condensate, environment temperature and unit situation can have an impact to the evaluation result that final optimization pass is run; Carry out test combinations between each border simultaneously, form science catalogue, formulate optimal control policy, thus get rid of extraneous factor to the interference evaluated;
B, define crucial controllable factor 202
Controllable factor is the adjustment behavior that operations staff can control, which be determined by experiment these factors by adjustment parameter or equipment to be determined, judge that whether the control of adjustment parameter or the equipment state operations staff determined is consistent again, thus set up the principle of the crucial controllable factor of a set of selection;
C, set up crucial controllable factor Figure 20 3
First the crucial controllable factor determined by step B, adds up the variation range of controllable factor, determines its scope changed;
By data statistics, utilize Minitab software to calculate the application of key factor change to evaluation index, set up regression equation;
Set up crucial controllable factor inventory;
The index list set up by steps A, design experiment operating mode, organizes specific operation to test;
Record, add up, analyze each operating condition of test under crucial controllable factor data, by Minitab software analysis optimum operating condition point, under determining optimum operating condition point, crucial controllable factor definite value.
2, the sub-process of dynamic benchmark parameter is found
As Fig. 3, the sub-process finding dynamic benchmark parameter is as follows:
A, screening intermediate variable 301
According to the index list that steps A in Fig. 2 is set up, design experiment, organizes specific operation to test;
Record, add up, analyze each operating condition of test under crucial controllable factor data, by Minitab software analysis optimum operating condition point, determine the crucial controllable factor definite value under optimum operating condition point;
Crucial controllable factor under screening index list, determines selected controllable factor;
Supplement and improve crucial controllable factor inventory, set up optimum operating condition database.
B, set up controllable factor x and intermediate variable y graph of a relation 302
Following problem may be run into: when testing some variable xn to the affecting of Y in this process, this variable possible is very little on the impact of Y in its whole range of adjustment, such as make δ Yn, and due to the impact of the inevitable noise of environment and measuring error, the error of measuring error itself just has δ Ym, if the magnitude of δ Ym and δ Yn relatively, so be just difficult to accurately determine the impact of this variable on result Y according to actual tests; Directly do not set up the relation between Variable Factors x and Y;
Be exemplified below:
First, find an intermediate variable y, first determine the relation y=f1(x of y and x), selected intermediate variable is that variation range is large, affects large performance calculation level;
Next, then determine the relation Y=f2 (y) of Y and y, the indirect like this relation finding x and Y;
Here the intermediate variable chosen is exactly some performance assessment criteria artificially controlled in the three grades of performance assessment criteria in the past examined, and the relation between these performance assessment criteria and x can the method for statistical study by experiment obtain, and the relation of itself and evaluation index can have been determined;
C, searching optimum condition establish factor reference value 303
Determine most economical operating mode according to the minimum value of δ Y, thus establish optimum condition factor reference value.
Claims (4)
1. adopt thermal power plant's Consumption Difference Analysing System of dynamic benchmark value, comprise fired power generating unit (100);
It is characterized in that:
Be provided with power plant's service data monitor (101), data statistics processing device (102), evaluation index counter (103) and data publication device (104);
Its annexation is: fired power generating unit (100), power plant's operational monitoring device (101), and data statistics processing device (102), optimizing operation score counter (103) is connected successively with data publication (104).
2., by thermal power plant's power consumption analysis method of the employing dynamic benchmark value of system described in claim 1, it is characterized in that comprising the following steps:
1. boundary condition is determined
Adopt new controllable factor, determine again the variation range of crucial controllable factor, then under determining each arbitrary boundary conditions, utilize Minitab software to solve out to the regression equation of each crucial controllable factor to optimizing evaluation, namely the expression formula under each boundary condition is set up: Y=f(x1, x2, x3 ...)
Y: dynamic benchmark value, x1, x2, x3 ...: various dissimilar controllable factor;
2. optimum operating condition is determined
By Minitab software analysis optimum operating condition point, determine the crucial controllable factor definite value under optimum operating condition point, be just to locate a kind of combination of each controllable factor, to make Y minimum;
3. optimum operating condition database is set up
Obtain under each boundary condition optimum controllable factor combination x1, x2, x3 ...
optimum, as the reference parameter data storehouse under each arbitrary boundary conditions.
3., by thermal power plant's power consumption analysis method of employing dynamic benchmark value according to claim 2, it is characterized in that choosing the sub-process calculating consumption difference function controllable factor as follows:
Index (201) is set up on A, definition border;
B, define crucial controllable factor (202);
C, set up crucial controllable factor figure (203).
4., by thermal power plant's power consumption analysis method of employing dynamic benchmark value according to claim 2, it is characterized in that the sub-process finding dynamic benchmark parameter is as follows:
A, screening intermediate variable (301);
B, set up controllable factor x and intermediate variable y graph of a relation (302);
C, searching optimum condition establish factor reference value (303).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410776788.5A CN104504509B (en) | 2014-12-16 | 2014-12-16 | A kind of thermal power plant's Consumption Difference Analysing System and its method using dynamic benchmark value |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410776788.5A CN104504509B (en) | 2014-12-16 | 2014-12-16 | A kind of thermal power plant's Consumption Difference Analysing System and its method using dynamic benchmark value |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN104504509A true CN104504509A (en) | 2015-04-08 |
| CN104504509B CN104504509B (en) | 2018-12-18 |
Family
ID=52945904
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410776788.5A Active CN104504509B (en) | 2014-12-16 | 2014-12-16 | A kind of thermal power plant's Consumption Difference Analysing System and its method using dynamic benchmark value |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104504509B (en) |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105844400A (en) * | 2016-03-22 | 2016-08-10 | 大唐贵州野马寨发电有限公司 | Thermal power plant consumption difference analysis and management method and system |
| CN107315852A (en) * | 2017-05-22 | 2017-11-03 | 大唐宝鸡热电厂 | Unit running optimization management and performance appraisal system based on power consumption analysis |
| CN108021694A (en) * | 2017-12-18 | 2018-05-11 | 华润电力湖北有限公司 | A kind of method and apparatus of definite thermoelectricity plant border index structure |
| CN110161996A (en) * | 2019-06-12 | 2019-08-23 | 中国大唐集团科学技术研究院有限公司华东电力试验研究院 | Method and system for the analysis of power plant units consumption |
| 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 |
| CN111027744A (en) * | 2019-11-06 | 2020-04-17 | 上海长庚信息技术股份有限公司 | Real-time benchmarking optimization method for multi-level power plant |
| CN112257278A (en) * | 2020-10-28 | 2021-01-22 | 华润电力技术研究院有限公司 | Unit difference consumption calculation model obtaining method, difference consumption obtaining method and system |
| CN113052717A (en) * | 2020-07-31 | 2021-06-29 | 国电内蒙古东胜热电有限公司 | Energy efficiency management method and system in thermal power generation system |
| 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 |
| CN113639256A (en) * | 2021-06-21 | 2021-11-12 | 华能国际电力股份有限公司大连电厂 | Power plant combustion optimization method and equipment |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021878A (en) * | 2006-02-14 | 2007-08-22 | 中国交通建设集团有限公司 | Automatic computerized selecting optimized dredging method for cutter suction dredger |
| CN201274013Y (en) * | 2008-09-22 | 2009-07-15 | 中国国电集团公司九江发电厂 | Economic index real-time monitoring analyzing system for power generation plant |
| CN101893877A (en) * | 2009-05-20 | 2010-11-24 | 中国国电集团公司九江发电厂 | Optimization operational method based on energy consumption analysis for power plant and system thereof |
| CN104199290A (en) * | 2014-08-08 | 2014-12-10 | 华南理工大学 | Circulating fluidized bed boiler operation optimizing method based on consumption difference analysis |
-
2014
- 2014-12-16 CN CN201410776788.5A patent/CN104504509B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101021878A (en) * | 2006-02-14 | 2007-08-22 | 中国交通建设集团有限公司 | Automatic computerized selecting optimized dredging method for cutter suction dredger |
| CN201274013Y (en) * | 2008-09-22 | 2009-07-15 | 中国国电集团公司九江发电厂 | Economic index real-time monitoring analyzing system for power generation plant |
| CN101893877A (en) * | 2009-05-20 | 2010-11-24 | 中国国电集团公司九江发电厂 | Optimization operational method based on energy consumption analysis for power plant and system thereof |
| CN104199290A (en) * | 2014-08-08 | 2014-12-10 | 华南理工大学 | Circulating fluidized bed boiler operation optimizing method based on consumption difference analysis |
Non-Patent Citations (2)
| Title |
|---|
| 崇培安: "基于锅炉安全运行的耗差优化研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 胡思科 等: "耗差分析法在电站机组能耗分析中的应用", 《东北电力技术》 * |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105844400A (en) * | 2016-03-22 | 2016-08-10 | 大唐贵州野马寨发电有限公司 | Thermal power plant consumption difference analysis and management method and system |
| CN107315852A (en) * | 2017-05-22 | 2017-11-03 | 大唐宝鸡热电厂 | Unit running optimization management and performance appraisal system based on power consumption analysis |
| CN108021694A (en) * | 2017-12-18 | 2018-05-11 | 华润电力湖北有限公司 | A kind of method and apparatus of definite thermoelectricity plant border index structure |
| CN108021694B (en) * | 2017-12-18 | 2020-04-10 | 华润电力湖北有限公司 | Method and device for determining boundary index structure of thermal power plant |
| CN110161996A (en) * | 2019-06-12 | 2019-08-23 | 中国大唐集团科学技术研究院有限公司华东电力试验研究院 | Method and system for the analysis of power plant units consumption |
| CN111027744A (en) * | 2019-11-06 | 2020-04-17 | 上海长庚信息技术股份有限公司 | Real-time benchmarking optimization method for multi-level 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 |
| CN113052717A (en) * | 2020-07-31 | 2021-06-29 | 国电内蒙古东胜热电有限公司 | Energy efficiency management method and system in thermal power generation system |
| CN112257278A (en) * | 2020-10-28 | 2021-01-22 | 华润电力技术研究院有限公司 | Unit difference consumption calculation model obtaining method, difference consumption obtaining method and system |
| 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 |
| CN113639256A (en) * | 2021-06-21 | 2021-11-12 | 华能国际电力股份有限公司大连电厂 | Power plant combustion optimization method and equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN104504509B (en) | 2018-12-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104504509A (en) | Dynamic reference value-adopting thermal power plant consumption analyzing system and method | |
| EP3221579B1 (en) | Wind turbine condition monitoring method and system | |
| CN102663232A (en) | Multi-dimensional simulation analysis system and method thereof for user energy efficiency evaluation | |
| CN105044499A (en) | Method for detecting transformer state of electric power system equipment | |
| KR20180131246A (en) | Method for production control system through processing mining | |
| CN103226664A (en) | External surface temperature pre-testing method and device for high pressure rotor of throttle adjusting type steam turbine | |
| CN104536290A (en) | Soft measuring method and system based on kernel principal component analysis and radial basis function neural network | |
| CN104407688A (en) | Virtualized cloud platform energy consumption measurement method and system based on tree regression | |
| CN103390211A (en) | Thermal generator set overall process energy management and cost analysis system | |
| CN106018730A (en) | Coal water content measurement device and method based on coal mill inlet primary air correction | |
| CN101604287A (en) | A kind of method of obtaining performance data realization dynamic optimization server performance based on hardware counter | |
| Wang et al. | Determination of the minimum sample size for the transmission load of a wheel loader based on multi-criteria decision-making technology | |
| KR101622523B1 (en) | System and driving method for performance measurement and verification of building energy | |
| CN104503406A (en) | Optimized operation evaluation system and method for thermal power plant | |
| CN204423416U (en) | A kind of thermal power plant's power consumption analysis device adopting dynamic benchmark value | |
| JP7053141B2 (en) | Systems and methods for controlling and monitoring power assets | |
| CN109063863B (en) | Distribution network maintenance plan optimization method considering area equipment life cycle cost-efficiency ratio | |
| CN109521001A (en) | A kind of flying marking measuring method based on PSO and ε-SVR | |
| WO2016015637A1 (en) | Photovoltaic air conditioning system, and performance detection method and performance detection device therefor | |
| RU2013104504A (en) | SYSTEM AND METHOD FOR TESTING THE STEAM TURBINE OPERATING INDICATOR | |
| CN110142803B (en) | Method and device for detecting working state of mobile welding robot system | |
| Liu et al. | FESeR: A data-driven framework to enhance sensor reliability for the system condition monitoring | |
| Geiss | The MISTRALWIND project–towards a remaining useful lifetime analysis and holistic asset management approach for more sustainability of wind turbine structures | |
| CN102419593A (en) | Sensor fault diagnosis method based on data mining | |
| CN115936663A (en) | Maintenance method and device for power 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 | ||
| C41 | Transfer of patent application or patent right or utility model | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20160728 Address after: 518052 Guangdong city of Shenzhen province Qianhai Shenzhen Hong Kong cooperation zone before Bay Road No. 1 building 201 room A (located in Shenzhen Qianhai business secretary Co. Ltd.) Applicant after: Shenzhen New Intellectual Property Management Co., Ltd. Address before: 437300 No. 99 Huarun Road, Xianning, Hubei, Chibi Applicant before: CHINA RESOURCES POWER HUBEI CO., LTD. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |