CN113610250B - Method for online calculation of number of wind field fault stops exceeding 24 hours based on defect list - Google Patents
Method for online calculation of number of wind field fault stops exceeding 24 hours based on defect list Download PDFInfo
- Publication number
- CN113610250B CN113610250B CN202110929155.3A CN202110929155A CN113610250B CN 113610250 B CN113610250 B CN 113610250B CN 202110929155 A CN202110929155 A CN 202110929155A CN 113610250 B CN113610250 B CN 113610250B
- Authority
- CN
- China
- Prior art keywords
- defect
- defect list
- wind field
- day
- fan
- 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.)
- Active
Links
- 230000007547 defect Effects 0.000 title claims abstract description 80
- 238000000034 method Methods 0.000 title claims abstract description 16
- 238000004364 calculation method Methods 0.000 title description 6
- 238000004519 manufacturing process Methods 0.000 claims abstract description 15
- 238000003860 storage Methods 0.000 claims abstract description 4
- 238000001914 filtration Methods 0.000 claims description 3
- 238000012423 maintenance Methods 0.000 description 10
- 230000002354 daily effect Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000001737 promoting effect Effects 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 230000003203 everyday effect Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 238000005728 strengthening Methods 0.000 description 1
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
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2462—Approximate or statistical queries
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy 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
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Probability & Statistics with Applications (AREA)
- Marketing (AREA)
- Health & Medical Sciences (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Fuzzy Systems (AREA)
- Mathematical Physics (AREA)
- Primary Health Care (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a method for online calculating the number of wind field fault shutdown exceeding 24 hours based on a defect list, which comprises the following steps: 1) Collecting defect lists with statistics days T 0 in an unopened state and defect list creation time earlier than that of T 0 from a wind field production management system to form a set A 0; 2) Removing defect list with temporary storage, cancellation and revocation status from the set A 0 to form a set A; 3) Collecting defect lists which are closed on the same day as T 0 and have the defect list creation time of T create from a wind field production management system to form a set B, wherein T create is 24 hours earlier than the closing time; 4) Combining the set A and the set B to form a defect list set C 0; 5) Removing defect list with reduced output and removed defect from the set C 0 to form a set C; 6) Inquiring in the defect set C according to the fan ID, if the same fan has a plurality of defect lists, only reserving 1 defect list, and finally obtaining a defect set M; 7) The number n of defects in the set M is the number of the faults of the wind field which are stopped for more than 24 hours on the statistical day T 0. The invention provides a scientific and rapid index acquisition method for production management departments.
Description
Technical Field
The invention belongs to the technical field of wind power operation and maintenance, and particularly relates to a method for calculating the number of wind field fault shutdown exceeding 24 hours based on a defect single online.
Background
The number of wind field failure stops exceeding 24 hours refers to the number of fans which start failure stops before the statistical day and have the duration of failure stops longer than 24 hours until 24 points on the statistical day. The method is an important index for supervision and evaluation of the long-stop condition of the wind field fan fault by a management department, is an important content of the long-stop fan management, and is characterized in that wind field operators manually judge by consulting wind field fan operation and maintenance history data, but because of the large number of fans and large time span, the analysis workload is heavy, the operators can hardly accurately judge, and the whole process can not be effectively supervised and controlled, so that the management department can not grasp the real long-stop information of the wind field fault, and the production decision is affected. In addition, the index cannot be calculated based on the real-time data of the fan, the fan fault state from the fan PLC only represents the state of the period of time when the fan reports the fault and is stopped, during the fault stopping period, the fan state can be switched among the states of fault, maintenance, standby, off-line and the like, and a judging logic capable of effectively identifying the starting time and the recovering time of the fault stopping can not be found, so that the application of the method is influenced.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method for online calculation of the number of wind field failure stops for more than 24 hours based on a defect list.
In order to achieve the above purpose, the invention adopts the following technical scheme:
A method for online calculating wind field fault shutdown exceeding 24 hours based on a defect list comprises the following steps:
1) Collecting defect lists which are in an unopened state on the day of the statistical day T 0 and have the defect list creation time earlier than the day of the statistical day T 0 from a wind field production management system to form a set A 0;
2) Removing defect list with temporary storage, cancellation and revocation status from the set A 0 to form a set A;
3) Collecting defect lists which are closed on the day of statistics T 0 and have the defect list creation time of T create from a wind field production management system to form a set B, wherein T create is earlier than the closing time T close hours;
4) Combining the set A and the set B to form a defect list set C 0;
5) Removing defect list with reduced output eliminating defect from the collection C 0, namely filtering defect list with reduced output as defect phenomenon to form a collection C;
6) Inquiring in the defect set C according to the fan ID, if the same fan has a plurality of defect lists, only reserving 1 fan to ensure that each fan is counted only once in a counting day, and finally obtaining a defect set M;
7) The number n of defects in the set M is the number of the faults of the wind field which are stopped for more than 24 hours on the statistical day T 0.
Compared with the prior art, the invention has the following advantages:
The method can integrate parameters such as the state of a defect list, the ID of a defect fan, the defect phenomenon, the defect creation time and the like, calculate the number of wind field fault shutdown for more than 24 hours on line, and automatically time to provide fault long-stop fan information of a subordinate wind field for production management staff of an enterprise, thereby promoting spare part purchase and strengthening overhaul supervision and indicating a definite direction for the enterprise. The method has clear logic, scientific and accurate calculation, can flexibly calculate the number of more than 24 hours, more than 168 hours and more than 720 hours according to the needs, and can effectively promote the 'zero' concept of the long-stop fan when releasing human resources, thereby promoting defect prevention control, ensuring sufficient spare parts and eliminating defects in time. Meanwhile, under the large background of new energy localization management, the alignment between wind fields and the alignment between time dimensions can be realized, the influence of human factors in the calculation process is reduced, the operation and maintenance analysis and decision level of enterprises are improved, and the scientific and normative efficient operation and maintenance is realized.
Drawings
FIG. 1 shows the number of times of failure to stop for more than 24 hours (daily report).
FIG. 2 shows comparison (daily report) of indexes such as the number of times of fan failure and shutdown exceeding 24 hours.
Detailed Description
The invention is described in further detail below with reference to the drawings and the detailed description.
The method for online calculating the number of wind field faults and stopping for more than 24 hours based on the defect list has been tested on a wind power intelligent operation and maintenance project, realizes automatic calculation on an intelligent operation and maintenance platform, and becomes an important means for production management departments to monitor wind field operation and maintenance and develop wind field performance assessment. Taking a headquarter of a wind power company as an example, an embodiment of the method is described as follows:
1) And collecting and arranging field information of a certain wind field defect list in the wind field production management system, and extracting fields such as the state of the defect list, the ID of a defect fan, the defect phenomenon, the defect creation time and the like.
2) The statistics program collects defect list information of the previous day (statistics day) on line every zero morning to form an original defect list table.
3) And screening out the defect list which is in an unoccluded state on the day of statistics and has the defect list creation time before the day of statistics from the original defect list table, and eliminating the defect list which is in a temporary storage, cancellation, revocation and other states.
4) And screening out defect lists which are closed on the day of statistics and have the defect list duration time of more than 24 hours from the original defect list table.
5) And (3) merging the defect list obtained in the steps 3) and 4) and removing the defect list with reduced output and eliminating the defect, namely filtering the defect list with the defect phenomenon of reduced output to form an effective defect list table.
6) And inquiring in an effective defect list table according to the fan ID, if the same fan has a plurality of defect lists, only reserving 1 fan to ensure that each fan is counted only once in a counting day.
7) And finally obtaining the defect list number which is the number of the fault stops of the wind field on the day of statistics for more than 24 hours.
FIG. 1 is a chart showing the number of times of failure stop exceeding 24 hours (daily report), wind field data of the previous day is automatically counted and calculated every day in zero morning, and the wind field data are displayed in the production daily report of a production management department, so that a user can flexibly inquire the number of times of failure stop exceeding 24 hours among subordinate wind fields on any date.
Fig. 2 is a comparison (daily report) of indexes such as the number of times of fan failure and shutdown exceeding 24 hours, and the calibration between wind fields and between different indexes is realized.
In fig. 1 and fig. 2, a user can randomly select a date, inquire the number of fault stops of each wind farm more than 24 hours, and display the number of fault stops, the number of periodical maintenance stops, the number of planned stops, the number of descending output operation stops and other indexes, so that a basis is provided for the user to master the production overall of each wind farm, and an objective and effective means is provided for the production management department to carry out wind farm operation and maintenance level evaluation and calibration.
Claims (1)
1. The method for online calculating the number of wind field fault shutdown exceeding 24 hours based on the defect list is characterized by comprising the following steps of: the method comprises the following steps:
1) Collecting defect lists which are in an unopened state on the day of the statistical day T 0 and have the defect list creation time earlier than the day of the statistical day T 0 from a wind field production management system to form a set A 0;
2) Removing defect list with temporary storage, cancellation and revocation status from original defect list set A 0 to form set A;
3) Collecting defect lists which are closed on the day of statistics T 0 and have the defect list creation time of T create from a wind field production management system to form a set B, wherein T create is earlier than the closing time T close hours;
4) Combining the set A and the set B to form a defect list set C 0;
5) Removing defect list with reduced output eliminating defect from the collection C 0, namely filtering defect list with reduced output as defect phenomenon to form a collection C;
6) Inquiring in the defect set C according to the fan ID, if the same fan has a plurality of defect lists, only reserving 1 fan to ensure that each fan is counted only once in a counting day, and finally obtaining a defect set M;
7) The number n of defects in the set M is the number of the faults of the wind field which are stopped for more than 24 hours on the statistical day T 0.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110929155.3A CN113610250B (en) | 2021-08-13 | 2021-08-13 | Method for online calculation of number of wind field fault stops exceeding 24 hours based on defect list |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110929155.3A CN113610250B (en) | 2021-08-13 | 2021-08-13 | Method for online calculation of number of wind field fault stops exceeding 24 hours based on defect list |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113610250A CN113610250A (en) | 2021-11-05 |
| CN113610250B true CN113610250B (en) | 2024-06-14 |
Family
ID=78340633
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110929155.3A Active CN113610250B (en) | 2021-08-13 | 2021-08-13 | Method for online calculation of number of wind field fault stops exceeding 24 hours based on defect list |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113610250B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105117830A (en) * | 2015-08-11 | 2015-12-02 | 中节能港建（甘肃）风力发电有限公司 | Wind farm production operation and maintenance information collection application system and method |
| CN108074197A (en) * | 2016-11-11 | 2018-05-25 | 河北新天科创新能源技术有限公司 | The control method of fan trouble data analysis system |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0918979A (en) * | 1995-06-28 | 1997-01-17 | Canon Inc | Operating state management system |
| CN101770612A (en) * | 2009-09-17 | 2010-07-07 | 宁波北电源兴电力工程有限公司 | Device defect management module of EAM (Enterprise Asset Management) system in power plant |
| CN104361419B (en) * | 2014-09-10 | 2018-01-23 | 国家电网公司 | Power transmission and transformation equipment state monitoring fault management system and method based on regulation and control unification |
| CN106874525B (en) * | 2017-04-18 | 2020-05-19 | 重庆工商大学 | Method and device for screening and counting equipment faults of wind turbine generator |
| CN109472459B (en) * | 2018-10-17 | 2022-03-22 | 贵州电网有限责任公司 | Power grid operation task optimization method considering change overhaul risk and waiting time |
| CN109658006B (en) * | 2018-12-30 | 2022-02-15 | 广东电网有限责任公司 | Large-scale wind power plant group auxiliary scheduling method and device |
| CN111311133B (en) * | 2020-04-24 | 2021-08-20 | 广东卓维网络有限公司 | Monitoring system applied to power grid production equipment |
| CN112633531A (en) * | 2020-12-26 | 2021-04-09 | 北京中恒博瑞数字电力科技有限公司 | Wind power plant operation maintenance system |
-
2021
- 2021-08-13 CN CN202110929155.3A patent/CN113610250B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105117830A (en) * | 2015-08-11 | 2015-12-02 | 中节能港建（甘肃）风力发电有限公司 | Wind farm production operation and maintenance information collection application system and method |
| CN108074197A (en) * | 2016-11-11 | 2018-05-25 | 河北新天科创新能源技术有限公司 | The control method of fan trouble data analysis system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113610250A (en) | 2021-11-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104638764A (en) | Intelligent state diagnosis and overhauling system for power distribution network equipment | |
| CN111191878A (en) | Abnormal analysis based station area and electric energy meter state evaluation method and system | |
| CN106655522A (en) | Master station system suitable for operation and maintenance management of secondary equipment of power grid | |
| CN107798395A (en) | A kind of power grid accident signal automatic diagnosis method and system | |
| CN110879327B (en) | 10KV line monitoring method by multi-data fusion | |
| CN107302264B (en) | Control method for stable operation of secondary automation equipment of transformer substation | |
| CN112666885A (en) | Environmental protection equipment monitoring management platform based on industrial internet | |
| CN110852624A (en) | Intelligent manufacturing management system facing enterprise execution layer and operation method thereof | |
| CN110247474B (en) | Statistical summary method and system based on D5000 system power grid operation state | |
| CN112633531A (en) | Wind power plant operation maintenance system | |
| CN107545519B (en) | Power grid enterprise operation and inspection management and control method | |
| CN115965266A (en) | Intelligent analysis system based on big data | |
| CN115130905A (en) | Dispatching duty management system for central control center of drainage basin cascade power plant and use method | |
| CN113610250B (en) | Method for online calculation of number of wind field fault stops exceeding 24 hours based on defect list | |
| CN112418548B (en) | Intelligent workshop management method and system based on artificial intelligence technology | |
| CN106199251A (en) | A kind of distribution network failure early warning system analyzed based on adaptive modeling and method | |
| CN113346622A (en) | Power grid operation risk intelligent warning system based on big data analysis | |
| CN111652500B (en) | Automatic on-duty auxiliary system based on scheduling | |
| CN113627802B (en) | Method for online calculating number of wind field fault eliminating machine stops based on defect list | |
| CN116231757A (en) | Power generation energy efficiency analysis management system of water-wind-solar power station group | |
| CN113642746B (en) | Method for calculating wind field fixed inspection maintenance number or planned shutdown number based on work ticket | |
| CN111008787B (en) | Active power outage planning monitoring and scheduling method based on metering terminal alarm technology | |
| CN114167342A (en) | Evaluation method for running health state of relay protection device | |
| CN113627628B (en) | Method for online calculating repeated overhaul times of same fan based on working ticket | |
| CN113656455A (en) | Method for calculating number of operating units of wind field output reduction force on line based on defect list |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |