CN108876138A - A kind of supervisory control of substation information leakage prison detection method based on big data analysis - Google Patents
A kind of supervisory control of substation information leakage prison detection method based on big data analysis Download PDFInfo
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- CN108876138A CN108876138A CN201810598473.4A CN201810598473A CN108876138A CN 108876138 A CN108876138 A CN 108876138A CN 201810598473 A CN201810598473 A CN 201810598473A CN 108876138 A CN108876138 A CN 108876138A
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- 238000012544 monitoring process Methods 0.000 claims abstract description 93
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Abstract
Detection method is supervised in the supervisory control of substation information leakage based on big data analysis that the invention discloses a kind of, including S1, building supervisory control of substation information history database, the attribute of monitoring information historical data base include：Substation, monitoring information title, monitoring information classification occur for monitoring information time of origin；Data cleansing is carried out to monitoring information historical data base；S2, calculating analysis is carried out to monitoring information historical data base with the Apriori algorithm in big data analysis method, search the Strong association rule between monitoring information, the monitoring information set sent in 10kV over current fault and ground fault is found out, monitoring information Association Rules are established；S3, maintenance data library searching method carry out the fact retrieval of " over current fault correlation rule ", " ground fault correlation rule " to the monitoring information occurred in real time, search the over current fault occurred under real-time status, ground fault；Fault condition is pushed to regulation operations staff by S4, failure pushing module.
Description
Technical field
The invention belongs to electric power network technical field more particularly to a kind of changes based on big data analysis based on big data
Monitoring power station information leakage prison detection method.
Background technique
With the continuous expansion of power grid scale, the continuous development of intelligent substation technology, grid equipment quantity is increasing,
Substation equipment monitoring information exponentially increases, and runs work for power grid regulation and proposes new challenge.At this stage, big data
Technology is like a raging fire, and the processing capacity for mass data and complex data is carrying out in a deep going way for power grid regulation management work
Provide new solution.It is necessary to by utilize big data analysis means, construct " event " attribute based on monitoring information,
The monitoring information set of typical " event " is reacted by building, maintenance data traversal method carries out " thing to the monitoring information above sent
Part retrieval ", and it is pushed to regulation operations staff, prevent the leakage of monitoring information from supervising.
Summary of the invention
For increasing for present grid equipment quantity, in order to guarantee the safe operation of power grid, the present invention provides one kind and is based on
The abnormal of big data algorithm measures monitoring method, which is intended to search supervisory control of substation by using big data analysis method
Strong association rule is built into monitor event set by the Strong association rule between information, and information aggregate is packaged and is believed real time monitoring
Breath scans for, and searches the monitoring information collection that such event occurs, to establish a kind of substation's prison based on big data analysis
Control information leakage prison detection method.This method can quickly position the grid event occurred in real time, and be pushed to regulation fortune in time
Administrative staff, for regulation, operations staff provides aid decision.
Specific technical solution of the present invention is：
A kind of supervisory control of substation information leakage prison detection method based on big data analysis, includes at least following steps：
S1, building supervisory control of substation information history database, the attribute of above-mentioned monitoring information historical data base include：Prison
It controls information time of origin, substation, monitoring information title, monitoring information classification occurs；Monitoring information historical data base is carried out
Data cleansing, specially：The name of the information specification of same unit exception will be reacted into unified title；
S2, calculating analysis is carried out to monitoring information historical data base with the Apriori algorithm in big data analysis method,
The Strong association rule between monitoring information is searched, the monitoring information set sent in 10kV over current fault and ground fault is found out, is established
Monitoring information Association Rules；Specially：
S2.1 constructs 10kV over current fault collection, and maintenance data library screening technique is by " II sections of protection acts of overcurrent " this monitoring
The monitoring information that synchronization occurs for information, same substation occurs constitutes an event sets, maintenance data library screening technique
Screen all event sets that " II sections of protection acts of overcurrent " this monitoring information has occurred since 1 year for whole substations；With
Apriori algorithm calculates the event sets, searches the Strong association rule between monitoring information, establishes over current fault association rule
Then gather；
S2.2 constructs 10kV ground fault collection, and maintenance data library screening technique will " zero stream protection act " this monitoring information
Synchronization occurs, the monitoring information that same substation occurs constitutes an event sets, the screening of maintenance data library screening technique
All event sets of " zero stream protection act " this monitoring information have occurred since 1 year for whole substations；It is calculated with Apriori
Method calculates the event sets, searches the Strong association rule between monitoring information, establishes ground fault correlation rule set；
S3, maintenance data library searching method carry out " over current fault correlation rule " to the monitoring information occurred in real time, " connect
The fact retrieval of earth fault correlation rule " searches the over current fault occurred under real-time status, ground fault；
Fault condition is pushed to regulation operations staff by S4, failure pushing module.
Advantages of the present invention and good effect are：
The supervisory control of substation information leakage prison detection method based on big data analysis that the present invention provides a kind of, when a large amount of prison
When control information is uploaded to regulation center, this method effectively can provide " fact retrieval " set for regulation operations staff, prevent
The leakage of monitoring information is supervised.Using the technical solution, by getting over the monitoring information data during the National Games of A power supply company
Part retrieval, retrieves ground fault 10 and rises, and over current fault 6 rises, consistent with the fault data that regulation operations staff monitors, method
Effectively.
Detailed description of the invention
Fig. 1 is the flow chart of the embodiment of the present invention.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
Please refer to Fig. 1：A kind of supervisory control of substation information leakage prison detection method based on big data analysis, including：
1. constructing supervisory control of substation information history database, Database Properties include：Monitoring information time of origin occurs
The contents such as substation, monitoring information title, monitoring information classification.Data cleansing is carried out to monitoring information historical data base first,
The name of the information specification of same unit exception will be reacted into unified title, be convenient for big data analysis and Mining Association Rules.
2. carrying out calculating analysis to monitoring information historical data base with big data analysis method Apriori algorithm, search
Strong association rule between monitoring information finds out the monitoring information set sent in 10kV over current fault, ground fault etc., establishes monitoring
Information association rule set.
2.1 building 10kV over current fault collection, maintenance data library screening technique is by " II sections of protection acts of overcurrent " this monitoring
The monitoring information that synchronization occurs for information, same substation occurs constitutes an event sets, screens with same method
All event sets of " II sections of protection acts of overcurrent " this monitoring information have occurred since 1 year for whole substations.With
Apriori algorithm calculates the event sets, searches the Strong association rule between monitoring information, establishes over current fault association rule
Then gather.
2.2 building 10kV ground fault collection, maintenance data library screening technique will " zero stream protection act " this monitoring informations
Synchronization occurs, monitoring information one event sets of composition that same substation occurs, is screened all with same method
All event sets of " zero stream protection act " this monitoring information have occurred since 1 year for substation.With Apriori algorithm pair
The event sets are calculated, and are searched the Strong association rule between monitoring information, are established ground fault correlation rule set.
3. maintenance data library searching method carries out " over current fault correlation rule ", " ground connection to the monitoring information occurred in real time
The fact retrieval of fault correlation rule ", searches the over current fault occurred under real-time status, ground fault.
4. fault condition is pushed to regulation operations staff, prevents the leakage of monitoring information from supervising by failure pushing module.
In order to verify the confidence level of above-mentioned technical proposal, therefore following specific experiment is carried out：
1. the monitoring information data of 33 base system substations on the 1st in A power supply company January -2018 years on the 1st January in 2017 are exported,
Supervisory control of substation information history database is constructed, Database Properties include：Substation, prison occur for monitoring information time of origin
Control the contents such as name of the information, monitoring information classification.Data cleansing is carried out to monitoring information historical data base first, i.e., will react same
The name of the information specification of one unit exception is convenient for big data analysis and Mining Association Rules at unified title.
2. to the building site A, that corporation monitoring information history database is counted with big data analysis method Apriori algorithm
Point counting analysis, searches the Strong association rule between monitoring information, finds out the monitoring information collection sent in 10kV over current fault, ground fault etc.
It closes, establishes monitoring information Association Rules.
2.1 building 10kV over current fault collection, maintenance data library screening technique is by " II sections of protection acts of overcurrent " this monitoring
The monitoring information that synchronization occurs for information, same substation occurs constitutes an event sets, screens with same method
All event sets of " II sections of protection acts of overcurrent " this monitoring information have occurred since 1 year for whole substations.With
Apriori algorithm calculates the event sets, searches the Strong association rule between monitoring information, establishes over current fault association rule
Then gather.
2.2 building 10kV ground fault collection, maintenance data library screening technique will " zero stream protection act " this monitoring informations
Synchronization occurs, monitoring information one event sets of composition that same substation occurs, is screened all with same method
All event sets of " zero stream protection act " this monitoring information have occurred since 1 year for substation.With Apriori algorithm pair
The event sets are calculated, and are searched the Strong association rule between monitoring information, are established ground fault correlation rule set.
3. maintenance data library searching method carries out " over current fault association rule to the monitoring information that A power supply company occurs in real time
Then ", the fact retrieval of " ground fault correlation rule " searches the over current fault occurred under real-time status, ground fault.
4. fault condition is pushed to regulation operations staff, compared with the practical failure found of monitoring personnel, effectively
Prevent the leakage of monitoring information from supervising.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (1)
1. a kind of supervisory control of substation information leakage prison detection method based on big data analysis, which is characterized in that include at least as follows
Step：
S1, building supervisory control of substation information history database, the attribute of above-mentioned monitoring information historical data base include：Monitoring letter
It ceases time of origin, substation, monitoring information title, monitoring information classification occurs；Data are carried out to monitoring information historical data base
Cleaning, specially：The name of the information specification of same unit exception will be reacted into unified title；
S2, calculating analysis is carried out to monitoring information historical data base with the Apriori algorithm in big data analysis method, searched
Strong association rule between monitoring information finds out the monitoring information set sent in 10kV over current fault and ground fault, establishes monitoring
Information association rule set；Specially：
S2.1, building 10kV over current fault collection, maintenance data library screening technique believe " II sections of protection acts of overcurrent " this monitoring
The monitoring information that synchronization occurs for breath, same substation occurs constitutes an event sets, maintenance data library screening technique sieve
Select whole substations that all event sets of " II sections of protection acts of overcurrent " this monitoring information have occurred since 1 year；With
Apriori algorithm calculates the event sets, searches the Strong association rule between monitoring information, establishes over current fault association rule
Then gather；
S2.2, building 10kV ground fault collection, maintenance data library screening technique will " zero stream protection act " this monitoring information hairs
The monitoring information that raw synchronization, same substation occur constitutes an event sets, and screening technique screening in maintenance data library is complete
All event sets of " zero stream protection act " this monitoring information have occurred since 1 year for substation of portion；With Apriori algorithm
The event sets are calculated, the Strong association rule between monitoring information is searched, establishes ground fault correlation rule set；
S3, maintenance data library searching method carry out " over current fault correlation rule ", " ground connection event to the monitoring information occurred in real time
The fact retrieval of barrier correlation rule ", searches the over current fault occurred under real-time status, ground fault；
Fault condition is pushed to regulation operations staff by S4, failure pushing module.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117132025A (en) * | 2023-10-26 | 2023-11-28 | 国网山东省电力公司泰安供电公司 | Power consumption monitoring and early warning system based on multisource data fusion |
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| CN103488802A (en) * | 2013-10-16 | 2014-01-01 | 国家电网公司 | EHV (Extra-High Voltage) power grid fault rule mining method based on rough set association rule |
| CN103489138A (en) * | 2013-10-16 | 2014-01-01 | 国家电网公司 | Method for analyzing relevancy between power transmission network fault information and line out-of-limit information |
| CN106600034A (en) * | 2016-11-08 | 2017-04-26 | 温州职业技术学院 | Three-phase unbalance governance device having in-situ temperature alarm function and realization method thereof |
| CN107247995A (en) * | 2016-09-29 | 2017-10-13 | 上海交通大学 | Transmission line of electricity running status association rule mining and Forecasting Methodology based on Bayesian model |
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2018
- 2018-06-12 CN CN201810598473.4A patent/CN108876138A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103488802A (en) * | 2013-10-16 | 2014-01-01 | 国家电网公司 | EHV (Extra-High Voltage) power grid fault rule mining method based on rough set association rule |
| CN103489138A (en) * | 2013-10-16 | 2014-01-01 | 国家电网公司 | Method for analyzing relevancy between power transmission network fault information and line out-of-limit information |
| CN107247995A (en) * | 2016-09-29 | 2017-10-13 | 上海交通大学 | Transmission line of electricity running status association rule mining and Forecasting Methodology based on Bayesian model |
| CN106600034A (en) * | 2016-11-08 | 2017-04-26 | 温州职业技术学院 | Three-phase unbalance governance device having in-situ temperature alarm function and realization method thereof |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117132025A (en) * | 2023-10-26 | 2023-11-28 | 国网山东省电力公司泰安供电公司 | Power consumption monitoring and early warning system based on multisource data fusion |
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Application publication date: 20181123 |