CN112650167A - Thermal power plant operation parameter optimization analysis method based on data mining - Google Patents
Thermal power plant operation parameter optimization analysis method based on data mining Download PDFInfo
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- CN112650167A CN112650167A CN202011484718.4A CN202011484718A CN112650167A CN 112650167 A CN112650167 A CN 112650167A CN 202011484718 A CN202011484718 A CN 202011484718A CN 112650167 A CN112650167 A CN 112650167A
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- 238000007418 data mining Methods 0.000 title claims abstract description 12
- 238000000034 method Methods 0.000 title claims abstract description 12
- 238000013433 optimization analysis Methods 0.000 title claims abstract description 12
- 238000005265 energy consumption Methods 0.000 claims abstract description 58
- 239000003245 coal Substances 0.000 claims abstract description 6
- 238000004140 cleaning Methods 0.000 claims description 3
- 230000007613 environmental effect Effects 0.000 claims description 3
- 230000000717 retained effect Effects 0.000 claims description 3
- 239000000446 fuel Substances 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000010248 power generation Methods 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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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
- 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
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
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Abstract
The invention discloses a thermal power plant operation parameter optimization analysis method based on data mining, which comprises the following steps of: s1: acquiring running power information and condition parameters of the generator set in a preset time period, wherein the condition parameters comprise load, coal quality, equipment technical improvement, ambient temperature and time of the generator set; s2: acquiring operation parameters of the generator set in a preset time period, wherein the operation parameters comprise start-stop information and working environment information of the generator set; s3: and acquiring the operating characteristics of the generator set. According to the invention, not only can the energy consumption characteristics of the generator set be obtained, but also the energy consumption of the generator set can be analyzed or predicted according to the energy consumption model, and at least one of the starting energy consumption, the stable operation energy consumption of the generator set and the starting and stopping change information of the generator set when the operation power information changes can be determined, so that the energy consumption configuration of the generator set is optimized, and the operation cost of the generator set is reduced.
Description
Technical Field
The invention relates to the technical field of thermal power generation, in particular to a thermal power plant operation parameter optimization analysis method based on data mining.
Background
A thermal power plant, referred to as a thermal power plant, is a plant that produces electric energy using a combustible (e.g., coal) as a fuel. The basic production process is as follows: when the fuel is burnt, water is heated to generate steam, chemical energy of the fuel is converted into heat energy, the steam pressure pushes a steam turbine to rotate, the heat energy is converted into mechanical energy, and then the steam turbine drives a generator to rotate, so that the mechanical energy is converted into electric energy.
The boundary conditions of the actual operation of the thermal power plant unit are constantly changing, and the problems of variable coal quality, variable load, variable climate and variable equipment (hereinafter referred to as 'four-variable') generally exist in the operation of the domestic thermal power plant unit. How to effectively solve the optimization and control problems of the thermal power plant unit under the 'four-variable' condition, reduce the energy consumption of the thermal power plant unit, and meet the mandatory constraint conditions of the national energy saving and emission reduction policy is a problem to be solved urgently at present.
Therefore, the invention provides a thermal power plant operation parameter optimization analysis method based on data mining.
Disclosure of Invention
The invention aims to: in order to solve the problems, the thermal power plant operation parameter optimization analysis method based on data mining is provided.
In order to achieve the purpose, the invention adopts the following technical scheme:
a thermal power plant operation parameter optimization analysis method based on data mining comprises the following steps:
s1: acquiring running power information and condition parameters of the generator set in a preset time period, wherein the condition parameters comprise load, coal quality, equipment technical improvement, ambient temperature and time of the generator set;
s2: acquiring operation parameters of the generator set in a preset time period, wherein the operation parameters comprise start-stop information and working environment information of the generator set;
s3: acquiring the operation characteristics of the generator set, wherein the operation characteristics represent the operation changes of the generator set when the working environment information changes, removing non-steady-state data from the acquired operation historical data to obtain steady-state data, and performing data cleaning on the steady-state data, which exceeds the temperature and the limit and is an environmental protection index;
s4: selecting specific environment information related to the operation characteristics from the working environment information according to the operation characteristics;
s5: constructing an energy consumption model according to the corresponding relation between at least one of the start-stop information and the specific environment information and the operation power information;
s6: and determining at least one of start-up energy consumption, stable operation energy consumption and start-up change information of the generator set when the operation power information changes according to the energy consumption model.
As a further description of the above technical solution:
the working environment information in step S2 includes one or more of air pressure information, geographical information, temperature information, and humidity information of the operating environment.
As a further description of the above technical solution:
in step S3, according to the upper and lower limits of the warning value of the over-temperature over-limit, data is acquired from the historical data through the SIS point corresponding to or bound to the over-temperature over-limit to match the upper and lower limits of the given warning value, so that data meeting the condition is retained, and data not meeting the condition is removed.
As a further description of the above technical solution:
the step S6 where the energy consumption model determines the starting energy consumption of the generator set includes:
determining first change information of the operation power information when the generator set is started according to the energy consumption model; determining the starting energy consumption of the generator set according to the first change information; determining the stable operation energy consumption of the generator set according to the energy consumption model comprises: according to the energy consumption model generator set stopping operation, second change information of the operation power information is obtained; and determining the stable operation energy consumption of the generator set according to the second change information.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
according to the invention, not only can the energy consumption characteristics of the generator set be obtained, but also the energy consumption of the generator set can be analyzed or predicted according to the energy consumption model, and at least one of the starting energy consumption, the stable operation energy consumption of the generator set and the starting and stopping change information of the generator set when the operation power information changes can be determined, so that the energy consumption configuration of the generator set is optimized, and the operation cost of the generator set is reduced.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a technical scheme that: a thermal power plant operation parameter optimization analysis method based on data mining comprises the following steps:
s1: acquiring running power information and condition parameters of the generator set in a preset time period, wherein the condition parameters comprise load, coal quality, equipment technical improvement, ambient temperature and time of the generator set;
s2: acquiring operation parameters of the generator set in a preset time period, wherein the operation parameters comprise start-stop information and working environment information of the generator set;
s3: acquiring the operation characteristics of the generator set, wherein the operation characteristics represent the operation changes of the generator set when the working environment information changes, removing non-steady-state data from the acquired operation historical data to obtain steady-state data, and performing data cleaning on the steady-state data, which exceeds the temperature and the limit and is an environmental protection index;
s4: selecting specific environment information related to the operation characteristics from the working environment information according to the operation characteristics;
s5: constructing an energy consumption model according to the corresponding relation between at least one of the start-stop information and the specific environment information and the operation power information;
s6: and determining at least one of start-up energy consumption, stable operation energy consumption and start-up change information of the generator set when the operation power information changes according to the energy consumption model.
The working environment information in step S2 includes one or more of air pressure information, geographical information, temperature information, and humidity information of the operating environment.
In step S3, according to the upper and lower limits of the warning value of the over-temperature over-limit, data is acquired from the historical data through the SIS point corresponding to or bound to the over-temperature over-limit to match the upper and lower limits of the given warning value, so that data meeting the condition is retained, and data not meeting the condition is removed.
The step S6 where the energy consumption model determines the starting energy consumption of the generator set includes:
determining first change information of the operation power information when the generator set is started according to the energy consumption model; determining the starting energy consumption of the generator set according to the first change information; determining the stable operation energy consumption of the generator set according to the energy consumption model comprises: according to the energy consumption model generator set stopping operation, second change information of the operation power information is obtained; and determining the stable operation energy consumption of the generator set according to the second change information.
In the energy consumption analysis method for the generator set, the operation power information and the operation parameters of the generator set in a preset time period are respectively obtained, and an energy consumption model is constructed according to the operation power information and the operation parameters. The relation between the operation power information and the operation parameters can be determined according to the energy consumption model, and the energy consumption characteristics of the detected component are obtained, so that when the operation parameters of the generator set are changed, the operation power information can be analyzed or predicted, at least one of the start-up energy consumption, the stable operation energy consumption and the start-stop change information of the generator set when the operation power information is changed can be analyzed according to the energy consumption model, and the energy consumption of the generator set can be configured according to the operation parameters and the energy consumption characteristics.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (4)
1. A thermal power plant operation parameter optimization analysis method based on data mining is characterized by comprising the following steps:
s1: acquiring running power information and condition parameters of the generator set in a preset time period, wherein the condition parameters comprise load, coal quality, equipment technical improvement, ambient temperature and time of the generator set;
s2: acquiring operation parameters of the generator set in a preset time period, wherein the operation parameters comprise start-stop information and working environment information of the generator set;
s3: acquiring the operation characteristics of the generator set, wherein the operation characteristics represent the operation changes of the generator set when the working environment information changes, removing non-steady-state data from the acquired operation historical data to obtain steady-state data, and performing data cleaning on the steady-state data, which exceeds the temperature and the limit and is an environmental protection index;
s4: selecting specific environment information related to the operation characteristics from the working environment information according to the operation characteristics;
s5: constructing an energy consumption model according to the corresponding relation between at least one of the start-stop information and the specific environment information and the operation power information;
s6: and determining at least one of start-up energy consumption, stable operation energy consumption and start-up change information of the generator set when the operation power information changes according to the energy consumption model.
2. The thermal power plant operation parameter optimization analysis method based on data mining as claimed in claim 1, wherein the working environment information in step S2 includes one or more of air pressure information, geographical information, temperature information and humidity information of the operating environment.
3. The thermal power plant operation parameter optimization analysis method based on data mining as claimed in claim 1, wherein in step S3, according to the upper and lower early warning values of the over-temperature and over-limit, data is obtained from historical data through SIS points corresponding to or bound to the over-temperature and over-limit to match the upper and lower early warning values, the data meeting the conditions is retained, and the data not meeting the conditions is removed.
4. The thermal power plant operating parameter optimization analysis method based on data mining as claimed in claim 1, wherein the step S6 of determining the starting energy consumption of the generator set by the energy consumption model comprises:
determining first change information of the operation power information when the generator set is started according to the energy consumption model; determining the starting energy consumption of the generator set according to the first change information; determining the stable operation energy consumption of the generator set according to the energy consumption model comprises: according to the energy consumption model generator set stopping operation, second change information of the operation power information is obtained; and determining the stable operation energy consumption of the generator set according to the second change information.
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| CN102566551A (en) * | 2012-02-03 | 2012-07-11 | 北京华电天仁电力控制技术有限公司 | Data mining-based method for analyzing thermal power plant operation index optimal target value |
| CN102809928A (en) * | 2012-08-10 | 2012-12-05 | 南京南瑞继保电气有限公司 | Control optimizing method for energy consumption of thermal equipment of industrial enterprise |
| CN109407506A (en) * | 2018-11-28 | 2019-03-01 | 深圳圣缘节能科技有限公司 | A kind of acquisition methods of the power plant units dynamic optimal value based on data mining |
| CN111664553A (en) * | 2020-06-08 | 2020-09-15 | 中国工商银行股份有限公司 | Water chilling unit operation control method and system, electronic equipment and storage medium |
-
2020
- 2020-12-15 CN CN202011484718.4A patent/CN112650167A/en active Pending
Patent Citations (5)
| 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 |
| CN102566551A (en) * | 2012-02-03 | 2012-07-11 | 北京华电天仁电力控制技术有限公司 | Data mining-based method for analyzing thermal power plant operation index optimal target value |
| CN102809928A (en) * | 2012-08-10 | 2012-12-05 | 南京南瑞继保电气有限公司 | Control optimizing method for energy consumption of thermal equipment of industrial enterprise |
| CN109407506A (en) * | 2018-11-28 | 2019-03-01 | 深圳圣缘节能科技有限公司 | A kind of acquisition methods of the power plant units dynamic optimal value based on data mining |
| CN111664553A (en) * | 2020-06-08 | 2020-09-15 | 中国工商银行股份有限公司 | Water chilling unit operation control method and system, electronic equipment and storage medium |
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Application publication date: 20210413 |