CN104217261A - Operating state risk early-warning method for main transformer system - Google Patents
Operating state risk early-warning method for main transformer system Download PDFInfo
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- CN104217261A CN104217261A CN201410486583.3A CN201410486583A CN104217261A CN 104217261 A CN104217261 A CN 104217261A CN 201410486583 A CN201410486583 A CN 201410486583A CN 104217261 A CN104217261 A CN 104217261A
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000004458 analytical method Methods 0.000 claims abstract description 14
- 238000007418 data mining Methods 0.000 claims abstract description 12
- 230000002159 abnormal effect Effects 0.000 claims abstract description 8
- 238000004140 cleaning Methods 0.000 claims abstract description 4
- 238000005516 engineering process Methods 0.000 claims description 6
- 238000012113 quantitative test Methods 0.000 claims description 6
- 238000011156 evaluation Methods 0.000 claims description 4
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000013480 data collection Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
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- 238000005259 measurement Methods 0.000 claims description 3
- 238000004445 quantitative analysis Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 238000009825 accumulation Methods 0.000 claims description 2
- 238000012423 maintenance Methods 0.000 abstract 2
- 238000012098 association analyses Methods 0.000 abstract 1
- 238000012544 monitoring process Methods 0.000 abstract 1
- 238000011084 recovery Methods 0.000 description 3
- 238000009412 basement excavation Methods 0.000 description 2
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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
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Abstract
The invention relates to an operating state risk early-warning method for a main transformer system under data mining. The method comprises the following steps: collecting and storing operating information on line according to the operating state indicator system of a main transformer; performing data cleaning, cutting and integrating for mass operating information on the basis of an indicator analyzing model so as to realize association analysis of various indictors; summarizing the operating state of the main transformer system based on the data mining, analyzing the varying rule, and creating a trend analysis report; pushing to early-warn the possible abnormal condition of a knowledge base and providing handling suggestions. According to the method, useful information is extracted from mass data produced by the operating of the main transformer system, and the system operating rule is mined, so as to realize the comprehensive sensing of the system operating system and advanced early-warning for the potential risk in operating; therefore, the problem that the operating maintenance of the main transformer system depends on the passive monitoring after an event occurs can be solved, the emergency treatment level of an operating maintenance people is improved, the risk preventing capacity of the main transformer system is improved, and as a result, the safety of a power grid in operating can be further ensured.
Description
Technical field
The present invention relates to a kind of method in power network schedule automation field, specifically relate to a kind of main station system running status method for prewarning risk.
Background technology
Along with the development of electrical network, especially the development of self-healing intelligent grid, require continuously online self-assessment, to predict electrical network possibility produced problem, find to have existed or the problem that developing take immediate steps and controlled or correct, to guarantee the reliability of electrical network, security, the quality of power supply and efficiency, scheduling station system importance improves gradually.Main station system runs and supervenes a large amount of data comprising management and running and management, and the profile data that existing supervisory system only lays particular emphasis on real-time analysis, warning system runs, lack the effective analysis and evaluation to a large amount of historical information, the potential safety hazard that the data resource Timeliness coverage system that cannot make full use of electric system magnanimity exists.
A new branch of science data mining technology of showing up prominently can utilize accumulative mass data for research object, finds out and is hidden in the useful knowledge of these data behind, thus provides strong foundation for science decision.
Therefore, need to provide a kind of main station system that data mining technology is used for run the mass historical data excavation main station system operation potential rule produced, strengthen trend analysis and the pre-alerting ability of scheduling station system running state, height enters and promotes main station system Risk-recovery level.
Summary of the invention
For the deficiencies in the prior art, the object of this invention is to provide a kind of main station system running status method for prewarning risk, this method solve main station system running status rely on PASSIVE SURVEILLANCE afterwards, can not the problem of Timeliness coverage security of system hidden danger, improve main station system Risk-recovery level.
The object of the invention is to adopt following technical proposals to realize:
The invention provides a kind of main station system running status method for prewarning risk, its improvements are, described method, based on data mining, comprises the steps:
(1) online acquisition store main website operation information;
(2) arrangement is gathered to main website operation information;
(3) trend analysis and assessment are carried out to main station system running status;
(4) Risk-warning is carried out to main station system running status.
Further, in described step (1), store main website operation information according to main website running status index system online acquisition; The main website operation information gathered comprises leading information, system asset information, application state information and system conformance information, and the main website operation information of storage comprises real-time data collection and history alarm, and sampling frequency is 5 minutes/time.
Further, described step (2) comprising: carry out Data classification, cleaning, cutting and fusion based on main website running status index analysis model to main website operation information, realize the association quantitative test of many indexes, comprise following sub-step:
(2-1) the main website operation information gathered is classified as follows: preposition operating mode, Bit Error Ratio Measurement, preposition switching statistics, preposition control, multi-source data consistance, data do not refresh statistics, resource utilization statistics, devoting rate statistics, network operating mode, network statistics, message accumulation statistics, zombie process statistics, data base consistency(-tance), clock consistency, delta data transmission time and statistics of database, and threshold value threshold is arranged respectively to the index gathered;
(2-2) from history library, extract historical data according to year, month, day time dimension, invalid data is cleared up and cuts out;
(2-3) carry out time period calculating according to classifying described in step (2-1) to each acquisition index, statistics main station system meets situation to this index;
(2-4) use statistics to carry out association quantitative test to transportation load, calculate the related coefficient between transportation load and influence factor representing correlation degree.
Further, described step (3) comprises the steps:
(3-1) from association quantitative analysis results, conclude main website running status index variation tendency rule based on data mining technology, form knowledge base;
(3-2) main station system running status trend is analyzed, form analysis and evaluation report.
Further, described step (4) comprises the steps:
(4-1) knowledge base is utilized to sum up the abnormal conditions of main station system running status generation and push early warning;
(4-2) handling suggestion comprising following information is provided for abnormal conditions: check system associated process handle release conditions, check system messaging bus ruuning situation, checks that associated process writes consistance and synchronism, the preposition port connection of inspection in storehouse.
Compared with the prior art, the beneficial effect that the present invention reaches is:
1. the main station system running status method for prewarning risk based on data mining provided by the invention, effectively utilizes main station system magnanimity service data, realizes the statistics to main station system moving law and trend analysis, achieves main station system and runs giving warning in advance of hidden danger;
2. method provided by the invention, solves main website operation and relies on PASSIVE SURVEILLANCE problem afterwards, enhance main station system Risk-recovery ability, ensured safe operation of electric network further.
3. method provided by the invention, make use of main station system and run the mass historical data excavation main station system operation potential rule produced, further enhancing scheduling station system for the problem existed or developing takes immediate steps and is controlled or correct, and greatly improves the reliability of electrical network, security, the quality of power supply and efficiency.
Accompanying drawing explanation
Fig. 1 is main station system running status method for prewarning risk schematic diagram provided by the invention.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.
Main station system running status method for prewarning risk schematic diagram based on data mining provided by the invention as shown in Figure 1, comprises the steps:
(1) online acquisition and the storage of operation information is realized according to main website running status index system:
The data gathered comprise leading information, system asset information, application state information and system conformance information, and the data of storage comprise real-time data collection and history alarm, and sampling frequency is 5 minutes/time.
(2) main website running state information gathers arrangement: carry out Data classification, cleaning, cutting and fusion based on index analysis model to magnanimity operation information, realizes the association quantitative test of many indexes, comprises following sub-step:
(2-1) index gathered is classified, comprise preposition operating mode, Bit Error Ratio Measurement, preposition switching statistics, preposition control, multi-source data consistance, data do not refresh statistics, resource utilization statistics, devoting rate statistics, network operating mode, network statistics, message piles up statistics, zombie process statistics, data base consistency(-tance), clock consistency, delta data transmission time, statistics of database, arrange threshold value threshold respectively;
(2-2) from history library, extract historical data according to year, month, day time dimension, invalid data is cleared up, cut out; ;
(2-3) carry out time period calculating according to classifying described in step (2-1) to each acquisition index, statistics main station system meets situation to this index.
(2-4) use statistical method to carry out association quantitative test to any two and above index, calculate the related coefficient between transportation load and influence factor, be used for describing its degree that is associated.
(3) trend analysis and assessment are carried out to main station system running status: sum up main station system running status based on data mining, analyze Changing Pattern, form trend analysis report, comprise following sub-step:
(3-1) from association quantitative analysis results, conclude main website running status index variation tendency rule based on data mining technology, form knowledge base;
(3-2) main station system operation trend is analyzed, form analysis and evaluation report.
(4) utilize knowledge base push early warning to contingent abnormal conditions and provide handling suggestion, comprise following sub-step:
(4-1) knowledge base is utilized to sum up the contingent abnormal conditions of main station system running status and push early warning;
(4-2) handling suggestion is provided for abnormal conditions, described handling suggestion comprises check system associated process handle release conditions, check system messaging bus ruuning situation, checks that associated process writes consistance and synchronism, the preposition port connection of inspection in storehouse.
Finally should be noted that: above embodiment is only in order to illustrate that technical scheme of the present invention is not intended to limit; although with reference to above-described embodiment to invention has been detailed description; those of ordinary skill in the field still can modify to the specific embodiment of the present invention or equivalent replacement; these do not depart from any amendment of spirit and scope of the invention or equivalent replacement, are all applying within the claims of the present invention awaited the reply.
Claims (5)
1. a main station system running status method for prewarning risk, is characterized in that, described method, based on data mining, comprises the steps:
(1) online acquisition store main website operation information;
(2) arrangement is gathered to main website operation information;
(3) trend analysis and assessment are carried out to main station system running status;
(4) Risk-warning is carried out to main station system running status.
2. main station system running status method for prewarning risk as claimed in claim 1, is characterized in that, in described step (1), stores main website operation information according to main website running status index system online acquisition; The main website operation information gathered comprises leading information, system asset information, application state information and system conformance information, and the main website operation information of storage comprises real-time data collection and history alarm, and sampling frequency is 5 minutes/time.
3. main station system running status method for prewarning risk as claimed in claim 1, it is characterized in that, described step (2) comprising: carry out Data classification, cleaning, cutting and fusion based on main website running status index analysis model to main website operation information, realize the association quantitative test of many indexes, comprise following sub-step:
(2-1) the main website operation information gathered is classified as follows: preposition operating mode, Bit Error Ratio Measurement, preposition switching statistics, preposition control, multi-source data consistance, data do not refresh statistics, resource utilization statistics, devoting rate statistics, network operating mode, network statistics, message accumulation statistics, zombie process statistics, data base consistency(-tance), clock consistency, delta data transmission time and statistics of database, and threshold value threshold is arranged respectively to the index gathered;
(2-2) from history library, extract historical data according to year, month, day time dimension, invalid data is cleared up and cuts out;
(2-3) carry out time period calculating according to classifying described in step (2-1) to each acquisition index, statistics main station system meets situation to this index;
(2-4) use statistics to carry out association quantitative test to transportation load, calculate the related coefficient between transportation load and influence factor representing correlation degree.
4. main station system running status method for prewarning risk as claimed in claim 1, it is characterized in that, described step (3) comprises the steps:
(3-1) from association quantitative analysis results, conclude main website running status index variation tendency rule based on data mining technology, form knowledge base;
(3-2) main station system running status trend is analyzed, form analysis and evaluation report.
5. main station system running status method for prewarning risk as claimed in claim 1, it is characterized in that, described step (4) comprises the steps:
(4-1) knowledge base is utilized to sum up the abnormal conditions of main station system running status generation and push early warning;
(4-2) handling suggestion comprising following information is provided for abnormal conditions: check system associated process handle release conditions, check system messaging bus ruuning situation, checks that associated process writes consistance and synchronism, the preposition port connection of inspection in storehouse.
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| CN201410486583.3A CN104217261A (en) | 2014-09-22 | 2014-09-22 | Operating state risk early-warning method for main transformer system |
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| CN201410486583.3A CN104217261A (en) | 2014-09-22 | 2014-09-22 | Operating state risk early-warning method for main transformer system |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104820907A (en) * | 2015-05-22 | 2015-08-05 | 中国石油化工股份有限公司 | Working site safety check improvement method and system based on data mining |
| CN105825314A (en) * | 2015-01-08 | 2016-08-03 | 国家电网公司 | Monitoring information analysis method and system based on centralized operation and maintenance mode |
| CN105913126A (en) * | 2016-03-25 | 2016-08-31 | 北京用尚科技股份有限公司 | Transformer station intelligent alarm model method for big data and cloud environment |
| CN106483947A (en) * | 2016-09-21 | 2017-03-08 | 国网江苏省电力公司南通供电公司 | Distribution Running State assessment based on big data and method for early warning |
| CN106789412A (en) * | 2016-12-08 | 2017-05-31 | 国网北京市电力公司 | Method, the apparatus and system of monitoring information collection main website performance |
| CN107561383A (en) * | 2017-08-25 | 2018-01-09 | 国网山东省电力公司潍坊供电公司 | A kind of static automatic testing method of telemetry concluded based on the time and system |
| CN108074021A (en) * | 2016-11-10 | 2018-05-25 | 中国电力科学研究院 | A kind of power distribution network Risk Identification system and method |
| CN108594070A (en) * | 2018-04-17 | 2018-09-28 | 国网上海市电力公司 | Transmission line malfunction based on the analysis of various dimensions network public information predicts construction method |
| CN109684310A (en) * | 2018-11-22 | 2019-04-26 | 安徽继远软件有限公司 | A kind of information system performance Situation Awareness method based on big data analysis |
-
2014
- 2014-09-22 CN CN201410486583.3A patent/CN104217261A/en active Pending
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105825314A (en) * | 2015-01-08 | 2016-08-03 | 国家电网公司 | Monitoring information analysis method and system based on centralized operation and maintenance mode |
| CN104820907A (en) * | 2015-05-22 | 2015-08-05 | 中国石油化工股份有限公司 | Working site safety check improvement method and system based on data mining |
| CN105913126A (en) * | 2016-03-25 | 2016-08-31 | 北京用尚科技股份有限公司 | Transformer station intelligent alarm model method for big data and cloud environment |
| CN106483947A (en) * | 2016-09-21 | 2017-03-08 | 国网江苏省电力公司南通供电公司 | Distribution Running State assessment based on big data and method for early warning |
| CN108074021A (en) * | 2016-11-10 | 2018-05-25 | 中国电力科学研究院 | A kind of power distribution network Risk Identification system and method |
| US11289944B2 (en) | 2016-11-10 | 2022-03-29 | China Electric Power Research Institute Company Limited | Distribution network risk identification system and method and computer storage medium |
| CN106789412A (en) * | 2016-12-08 | 2017-05-31 | 国网北京市电力公司 | Method, the apparatus and system of monitoring information collection main website performance |
| CN107561383A (en) * | 2017-08-25 | 2018-01-09 | 国网山东省电力公司潍坊供电公司 | A kind of static automatic testing method of telemetry concluded based on the time and system |
| CN108594070A (en) * | 2018-04-17 | 2018-09-28 | 国网上海市电力公司 | Transmission line malfunction based on the analysis of various dimensions network public information predicts construction method |
| CN109684310A (en) * | 2018-11-22 | 2019-04-26 | 安徽继远软件有限公司 | A kind of information system performance Situation Awareness method based on big data analysis |
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Application publication date: 20141217 |