CN108933480A - A kind of power supply reliability monitoring method based on big data - Google Patents
A kind of power supply reliability monitoring method based on big data Download PDFInfo
- Publication number
- CN108933480A CN108933480A CN201810727587.4A CN201810727587A CN108933480A CN 108933480 A CN108933480 A CN 108933480A CN 201810727587 A CN201810727587 A CN 201810727587A CN 108933480 A CN108933480 A CN 108933480A
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- power
- grid
- monitoring method
- power supply
- big data
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- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012544 monitoring process Methods 0.000 title claims abstract description 30
- 230000009471 action Effects 0.000 claims abstract description 18
- 230000005611 electricity Effects 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 abstract description 10
- 238000013459 approach Methods 0.000 abstract description 2
- 238000007405 data analysis Methods 0.000 abstract description 2
- 230000008901 benefit Effects 0.000 description 2
- 230000007717 exclusion Effects 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000006641 stabilisation Effects 0.000 description 1
- 238000011105 stabilization Methods 0.000 description 1
Classifications
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- H02J13/0017—
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
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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
- 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
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Abstract
The present invention relates to grid monitoring approach more particularly to a kind of power supply reliability monitoring methods based on big data.A kind of power supply reliability monitoring method based on big data provided by the invention, it is intended to which electric network reliability monitoring method is unreasonable in the prior art for solution, causes the technical problem of subsequent data analysis difficulty.A kind of power supply reliability monitoring method based on big data provided by the invention, acquire the action record of each distribution components when grid power blackout number and grid power blackout, and classified to the reason of grid power blackout, to the type of grid power blackout carry out classify and the power off time of power grid is acquired, acquire power system restoration power when whether livewire work, the monitoring method carries out classification to data and is conducive to technical staff's subsequent analysis data, and, the data of monitoring method acquisition are more comprehensive, are conducive to the subsequent analysis of technical staff.
Description
Technical field
The present invention relates to grid monitoring approach more particularly to a kind of power supply reliability monitoring methods based on big data.
Background technique
Power grid is the infrastructure for conveying electric energy, and power grid generally requires power grid reliably, steadily to convey in the process of running
Electric energy, to improve the power supply quality of power grid.
In the prior art to guarantee the stabilization of power grids, reliable operation, generally requires and power grid is effectively monitored, with benefit
In power grid is analyzed, early warning etc..Such as when being monitored to the reliability of operation of power networks, acquisition power grid is generally required one
Frequency of power cut, power off time etc. in the section time.But the data acquired when monitoring in the prior art to electric network reliability do not conform to
Reason is unfavorable for carrying out subsequent analysis to power grid.
Summary of the invention
A kind of power supply reliability monitoring method based on big data provided by the invention, it is intended to solve power grid in the prior art
Reliability monitoring method is unreasonable, causes the technical problem of subsequent data analysis difficulty.
In order to solve the above-mentioned technical problem, the present invention adopts the following technical scheme:
A kind of power supply reliability monitoring method based on big data, comprising the following steps:
Step 1: acquiring the power failure data of power grid, which includes power grid 24 hours frequencies of power cut and grid power failure
The action record of each distribution components when electric；
Step 2: the safety at power cut of power grid in acquisition step one, the safety at power cut include scheduled outage and fault outage；
Step 3: the power failure type of power grid in acquisition step one, the power failure type include that rural power grids have a power failure and city electricity
Net has a power failure；
Step 4: acquisition grid power blackout time, power off time, that is, grid power blackout time used between restoring electricity；
Step 5: acquisition restore power grid power supply when whether livewire work；
Step 6: the data that storing step one to step 5 acquires.
A kind of power supply reliability monitoring method based on big data provided by the invention acquires grid power blackout number and power grid
The action record of each distribution components when power failure, and classified to the reason of grid power blackout, the type of grid power blackout is carried out
Classification and the power off time of power grid is acquired, acquire power system restoration power when whether livewire work, the monitoring method pair
Data carry out classification and are conducive to technical staff's subsequent analysis data, also, the data of monitoring method acquisition are more comprehensive, have
Conducive to the subsequent analysis of technical staff.
A kind of optional scheme records each distribution components when grid power blackout in the step 1 in the form of video file
Action record.
The action record that each distribution components are recorded using video file, improves the accuracy of action record, and is conducive to
The generation of action record reduces the labor intensity of related personnel.
A kind of optional scheme acquires fault type when safety at power cut is fault outage in the step 2.
The record of fault type is conducive to the subsequent depth analysis to safety at power cut of technical staff, and then is conducive to similar event
The exclusion of barrier.
A kind of optional scheme is somebody's turn to do the power supply reliability monitoring method based on big data further include:
Step 7: the data that step 6 stores are converted into chart, the action record wherein acquired in step 1 is with hyperlink
The form of connecing is associated with to chart.
Convert data to chart, data show more intuitive, are conducive to the subsequent analysis of technical staff.
A kind of optional scheme, the data acquired using Cloud Server storing step one to step 5 in the step 6.
Be conducive to the storage of data.
Compared with prior art, a kind of power supply reliability monitoring method based on big data provided by the invention has such as
Lower advantage:
This method classifies to data when acquiring data, also, records the movement of each distribution components when grid power blackout
Record, can effectively be monitored the stability of operation of power networks using this method, also, the data of this method record are advantageous
In technical staff's subsequent analysis, and then be conducive to improve the stability of operation of power networks.
Specific embodiment
A kind of power supply reliability monitoring method based on big data of the invention is described further below.Implement below
Example is only used for helping skilled in the art to understand the present invention, is not limitation of the present invention.
A kind of power supply reliability monitoring method based on big data, comprising the following steps:
Step 1: acquiring the power failure data of power grid, which includes power grid 24 hours frequencies of power cut and grid power failure
The action record of each distribution components when electric.
Frequency of power cut refers to that the frequency of power cut in a period of time, frequency of power cut can recorde 24 hours frequencies of power cut, can also
It, can for time interval those skilled in the art of frequency of power cut to record one week frequency of power cut or one month frequency of power cut
With rationally setting as needed.
The action record of each distribution components can be recorded in the form of video file, in favor of the generation of action record, and
And action record accuracy is high.Action record can be the video file of shooting distribution components erecting bed, and action record can also
Think the animation file in grid monitoring system.The content of action record is the video file at scene or the animation text in system
Part those skilled in the art can be with unrestricted choice.
Step 2: the safety at power cut of power grid in acquisition step one, the safety at power cut include scheduled outage and fault outage.
Scheduled outage, that is, planned certain a part to power grid carries out power failure operation.The purpose of scheduled outage is generally electricity
The maintenance of net or the maintenance of power grid.
Fault outage refer to distribution components failure or it is other due to caused by power failure, since fault outage is abnormal thing
Part, therefore fault type should be acquired when fault outage, in favor of the exclusion of failure.
Step 3: the power failure type of power grid in acquisition step one, the power failure type include that rural power grids have a power failure and city electricity
Net has a power failure.
Rural power grids have different structures from urban distribution network, therefore, after acquisition power failure type is beneficial to technical staff
Continuous analysis data, reduce the labor intensity of technical staff.
Step 4: acquisition grid power blackout time, power off time, that is, grid power blackout time used between restoring electricity；
Step 5: acquisition restore power grid power supply when whether livewire work；
Step 6: the data that storing step one to step 5 acquires, this step can use Cloud Server storing step one
The data acquired to step 5；
Step 7: the data that step 6 stores are converted into chart, it is the prior art that data, which are converted to chart, i.e., using soft
Part converts data to chart, which is the prior art, is no longer described herein, the movement note wherein acquired in step 1
Record is associated with hyperlink form to chart.
Technical solution disclosed by the invention can effectively monitor the reliability of power grid power supply, also, acquire in monitoring
Data be conducive to technical staff's subsequent analysis.
Section Example of the invention is described in detail above.After those skilled in the art read this specification,
It based on technical solution of the present invention, can modify to above-described embodiment, these modifications still fall within protection scope of the present invention.
Claims (5)
1. a kind of power supply reliability monitoring method based on big data, which comprises the following steps:
Step 1: acquiring the power failure data of power grid, when which includes power grid 24 hours frequencies of power cut and grid power blackout
The action record of each distribution components；
Step 2: the safety at power cut of power grid in acquisition step one, the safety at power cut include scheduled outage and fault outage；
Step 3: the power failure type of power grid in acquisition step one, the power failure type include that rural power grids power failure and urban distribution network stop
Electricity；
Step 4: acquisition grid power blackout time, power off time, that is, grid power blackout time used between restoring electricity；
Step 5: acquisition restore power grid power supply when whether livewire work；
Step 6: the data that storing step one to step 5 acquires.
2. a kind of power supply reliability monitoring method based on big data according to claim 1, it is characterised in that: the step
The action record of each distribution components when grid power blackout is recorded in rapid one in the form of video file.
3. a kind of power supply reliability monitoring method based on big data according to claim 1, it is characterised in that: the step
Fault type is acquired when safety at power cut is fault outage in rapid two.
4. a kind of power supply reliability monitoring method based on big data according to claim 1, it is characterised in that: this is based on
The power supply reliability monitoring method of big data further include:
Step 7: the data that step 6 stores are converted into chart, the action record wherein acquired in step 1 is with hyperlink shape
Formula is associated with to chart.
5. a kind of power supply reliability monitoring method based on big data according to claim 1, it is characterised in that: the step
The data acquired using Cloud Server storing step one to step 5 in rapid six.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810727587.4A CN108933480A (en) | 2018-07-05 | 2018-07-05 | A kind of power supply reliability monitoring method based on big data |
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| CN201810727587.4A CN108933480A (en) | 2018-07-05 | 2018-07-05 | A kind of power supply reliability monitoring method based on big data |
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2016185004A (en) * | 2015-03-26 | 2016-10-20 | 東芝ライテック株式会社 | Communication system and distribution board |
| CN107909295A (en) * | 2017-12-08 | 2018-04-13 | 国网山东省电力公司电力科学研究院 | A kind of outage information monitor and analysis system |
-
2018
- 2018-07-05 CN CN201810727587.4A patent/CN108933480A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2016185004A (en) * | 2015-03-26 | 2016-10-20 | 東芝ライテック株式会社 | Communication system and distribution board |
| CN107909295A (en) * | 2017-12-08 | 2018-04-13 | 国网山东省电力公司电力科学研究院 | A kind of outage information monitor and analysis system |
Non-Patent Citations (3)
| Title |
|---|
| 《铁路营业线施工安全管理知识》编委会: "《铁路营业线施工安全管理知识》", 31 December 2017, 中国铁道出版社 * |
| 曹永新: "《农村供电可靠性培训教材》", 31 October 2006, 中国电力出版社 * |
| 段传宗: "《无人值班变电所及农网综合自动化》", 30 April 1998, 中国电力出版社 * |
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Application publication date: 20181204 |