CN102638100B - District power network equipment abnormal alarm signal association analysis and diagnosis method - Google Patents
District power network equipment abnormal alarm signal association analysis and diagnosis method Download PDFInfo
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Abstract
The invention discloses a district power network equipment abnormal alarm signal association analysis and diagnosis method in the field of automation of scheduling of electric power systems. According to the method disclosed by the invention, the weather situation of a plant station region at which abnormal alarm information is located can be automatically identified so as to determine the information processing mode. The method disclosed by the invention has the beneficial effects that by realizing intelligent association analysis and auxiliary decision making of the equipment abnormal alarm information under the real-time state, and performing playback on historical alarm information and performing real-time treatment on manual set information under the research state, the abnormal treatment time is greatly reduced, the incidence of accidents is reduced, a real-time, rich and intelligent auxiliary decision-making support is provided for regulation and control staff, and the safe, high-quality, economical and stable operation of an electric fence is further ensured.
Description
Technical field
The invention belongs to dispatching automation of electric power systems field, relate in particular to the alarm signal association analysis of area power grid unit exception and diagnostic method.
Background technology
Unit exception alarm signal mainly refers to some alarm signals that first and second equipment of electrical network sends before electrical network breaks down prerequisite, as main transformer cooler fault, main transformer overload, the low warning of circuit breaker SF6 air pressure, protection alarm, ground connection alarm etc.While delivering to control centre in this type of alarm signal, indicating that electric power system is at present in dangerous running status, remind management and running personnel must take measures in time to eliminate the hidden danger that causes alarm, now power system operation does not occur obviously abnormal, early warning signal is often mixed in Normal Alarm signal, the operations staff that is not easy to be scheduled identification is also processed, thereby finally develops into the system failure.Simultaneously by electric power in the alarm signal enormous amount of equipment and of a great variety, the processing scheme of distinct device warning information is also not quite similar, so just collection control and management and running personnel's professional qualities have been proposed to high requirement, continuous increase along with network size, operations staff's operating pressure is increasing, omits or ignores instrument for equipment alarm signal and the risk that causes system to break down is also more and more higher.
At present, also rare to the research of grid equipment abnormality alarming signal intelligent treatment system both at home and abroad, mostly concentrate on the unit exception warning information processing aspect of transformer station, mostly to be optimized aspect information layered, classification, the correlation analysis that seldom has pair signal, more lack in special weather situation and adopt different disposal pattern technology, do not possess the ability of intellectual analysis and diagnosis, aid decision.Existing supervisory control of substation alarm expert system mainly comprises single incident reasoning and comprehensive reasoning to the reasoning of alarm signal, the inference mode adopting is respectively simple one-step inference and fuzzy reasoning method, although fuzzy reasoning method adaptability is good, can tackle the equipment of different model, structure, but be subject to the interference of mistake remote signalling, the low precision of reasoning, causes reasoning not accurate enough, can not effectively reduce dispatcher and process the abnormal time.
Because same interval or same unit alarm signal have logical associations, therefore correlation signal was defined as in one period of short time, a certain interval or a certain unit of transformer station recur a plurality of alarm signals, and these recur signal and are one and have associated organic whole.The comprehensive event scheduling person of this class is difficult to be judged to be at short notice certain unit exception and causes, and get rid of in time, stop it to develop into the system failure.Therefore, need to be by means of the intelligent association analysis and diagnosis method synthesis reasoning and judging of unit exception signal, diagnose out the reason of abnormality alarming and provide corresponding processing policy, this is to improving monitor staff's supervision quality, improve rapidity and the accuracy of monitor staff to abnormal conditions judgement and processing, have important practical significance.
Summary of the invention
The object of the invention is to overcome the above problems, a kind of area power grid unit exception alarm signal association analysis and diagnostic method are provided, with realize area power grid in different weather situation (typhoon weather and normal weather) to the association analysis of unit exception alarm signal and diagnosis, and aid decision support.
This method is embedded in the warning information treatment system at regulation and control center in the mode of software module, comprise real-time state and two kinds of running statuses of research state, in real time under state from warning information treatment system pretreated unit exception warning information and the fault message of Real-time Obtaining, effectively guaranteed integrality and the authenticity of information analysis; Under research state, obtain history alarm information or manually simulate and set abnormality alarming information and fault message, realize respectively the historical playback of information processing and enrich dispatcher's knowledge and experience.
The alarm signal association analysis of area power grid unit exception and diagnostic method comprise the following steps:
1) receive the fault message from warning information treatment system, according to transmission line switch trip quantity in monitor for faults information in the mode time of setting, judge under switch that plant stand is whether in typhoon situation, these plant stand abnormality alarming messaging models of mark are normal mode under these plant stand default situations;
2) receive the abnormality alarming information from warning information treatment system, according to the priority of extractive technique automatic Identification mark warning information according to keywords in the association analysis time of setting, with time-division interval or subdivision, deposit in the real-time storehouse with hierarchical model;
3) scanning step 1) in execution result, determine whether plant stand pattern has renewal, the plant stand warning information in typhoon model and normal mode is processed respectively;
4) prioritization of warning information being processed, the power plant and substation's information priority treatment under typhoon model is determined its interval, place or cell processing order by the priority of information itself simultaneously;
5) the information processing order obtaining according to step 4), is described as successively an example by it according to the example description scheme before processing in example storehouse, and adopts nearest neighbor search strategy to retrieve similar example in conjunction with example storehouse, judges whether similarity meets the requirements;
6) if do not met the similarity requirement of step 5), in conjunction with knowledge base expertise, according to the relevance of causality inference mechanism analytical information, and provide unit exception alarm cause and respective handling strategy, above send supervisory control system alarm window to show;
7) as met the similarity requirement of step 5), directly provide the reasoning results, and on send supervisory control system alarm window to show;
8) integrating step 6) result, it is described as to new example or original example is modified according to the example description scheme after processing in example storehouse, and deposit in example storehouse, generate analysis report simultaneously.
In described knowledge base, set up and have keyword priority mapping table, list structure to comprise under numbering, keyword, typhoon model priority under priority, normal mode.
The height of described priority determines according to the importance of information, if do not process can be accidents caused immediately abnormal information priority high, the information priority level that can not cause the accident is in a short time low.
Described real-time storehouse has hierarchical model, the intermediate object program that storehouse comprises electrical network model, secondary model, expertise and an association analysis in real time.
Realize the important information priority treatment that priority is high; Order is successively according to the priority arrangement of plant stand pattern, electric pressure, interval or unit, and the priority of interval or unit is definite to be referred to: the wherein limit priority of information of take is that mark forms information processing queue.
Adopt rule-based and mixed inference mode example to analyze the relevance of warning information;
RBR mode adopts the method based on graph theory, utilize production rule to describe expert system knowledge, according to anomaly relation, formation causality tree, according to causality topological diagram, through topological analysis, process associated alarm information, causality is stored in knowledge base, wherein in knowledge base, also comprises causal incidence relation rule, by device exception information type set information processing priority with carry out the necessary knowledge of association analysis;
Inference mode based on example adopts nearest neighbor strategy retrieval example storehouse, be about to abnormal signal numbering and convert Boolean type to calculate the similarity of target example and source example, according to the size of similarity, choose 1-3 example the most similar and list, provide the reasoning results and processing scheme.
All take commercial SQL storehouse and build as basis in described knowledge base and example storehouse, deposits respectively the case after the special knowledge in the required field of instrument for equipment alarm signal of sending in processing and warning information are processed; Except keyword priority mapping off-balancesheet, in knowledge base and example storehouse, include example description list, abnormal signal processing rule table, causality table and history alarm information table, in order to the association analysis of warning information and diagnosis.
Described the reasoning results and result are all presented in the individual page in the alarm window of supervisory control system, remind dispatcher to process in time abnormal, auxiliary on-line decision; The reasoning results and result are saved as to historical information, as the initial data of association analysis reasoning inverting; Record reasoning process simultaneously, generate analysis report, with document form, preserve, so that operations staff analyzes summing up experience.
The scope of the mode time of described setting is 5-15s.
The scope of the association analysis time of described setting is 3-10s.
Described method is applicable to real-time state and research state, in real time under state from warning information treatment system pretreated unit exception warning information and the fault message of Real-time Obtaining, under research state, obtain history alarm information or manually simulation set abnormality alarming information and fault message.
Beneficial effect of the present invention is: the present invention is by realizing intelligent association analysis and the aid decision of equipment abnormality alarming information under real-time state, and playback and the real-time processing to manual set information of history alarm information processing under research state, greatly shortened the abnormality processing time, reduced accident rate, more real-time, abundant and intelligentized aid decision support are provided to regulation and control personnel, have ensured safety, high-quality, economy and the stable operation of electrical network.
Accompanying drawing explanation
Fig. 1 is implementation structure figure of the present invention.
Fig. 2 is embodiment causality tree.
Fig. 3 is program flow diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing, the invention will be further described.Following examples are only for technical scheme of the present invention is more clearly described, and can not limit the scope of the invention with this.
As shown in Figure 1, Figure 3, abnormality alarming information correlation analysis and diagnostic module are embedded in the warning information treatment system at regulation and control center, comprise real-time state and two kinds of running statuses of research state, under state, obtain real-time abnormality alarming information and fault message in real time, under research state, read history alarm information.After receiving alarm information, through information pretreatment unit and reasoning element, process, provide association analysis result and respective handling measure, above send independent display interface, auxiliary dispatching person's decision-making.Wherein pretreatment unit comprise the identification of information priority level, minute interval or unit storage, according to the automatic identifying processing pattern of information plant stand of living in region weather, reasoning element comprises knowledge base and example storehouse and rule and example mixed inference machine.
The alarm signal association analysis of area power grid unit exception and diagnostic method comprise the following steps:
1) receive the fault message from warning information treatment system, according to transmission line switch trip quantity in monitor for faults information in the mode time of setting, judge under switch that plant stand is whether in typhoon situation, these plant stand abnormality alarming messaging models of mark are normal mode under these plant stand default situations;
2) receive the abnormality alarming information from warning information treatment system, according to the priority of extractive technique automatic Identification mark warning information according to keywords in the association analysis time of setting, with time-division interval or subdivision, deposit in the real-time storehouse with hierarchical model;
3) scanning step 1) in execution result, determine whether plant stand pattern has renewal, the plant stand warning information in typhoon model and normal mode is processed respectively;
4) prioritization of warning information being processed, the power plant and substation's information priority treatment under typhoon model is determined its interval, place or cell processing order by the priority of information itself simultaneously;
5) the information processing order obtaining according to step 4), is described as successively an example by it according to the example description scheme before processing in example storehouse, and adopts nearest neighbor search strategy to retrieve similar example in conjunction with example storehouse, judges whether similarity meets the requirements;
6) if do not met the similarity requirement of step 5), in conjunction with knowledge base expertise, according to the relevance of causality inference mechanism analytical information, and provide unit exception alarm cause and respective handling strategy, above send supervisory control system alarm window to show;
7) as met the similarity requirement of step 5), directly provide the reasoning results, and on send supervisory control system alarm window to show;
8) integrating step 6) result, it is described as to new example or original example is modified according to the example description scheme after processing in example storehouse, and deposit in example storehouse, generate analysis report simultaneously.
For the priority of automatic Identification warning information, in described knowledge base, set up and have keyword priority mapping table, list structure to comprise under numbering, keyword, typhoon model priority under priority, normal mode.
Warning information to different plant stand different interval, adopt keyword extraction technology, determine the priority of processing, the height of priority is determined according to the importance of information, if do not process can be accidents caused immediately abnormal information priority high, the information priority level that can not shine in a short time accident is low.
In real time storehouse has hierarchical model, and the intermediate object program that storehouse comprises electrical network model, secondary model, expertise and an association analysis in real time provides the exchanges data of each interprocedual.
Realize the important information priority treatment that priority is high; Order is successively according to the priority arrangement of plant stand pattern, electric pressure, interval or unit, and the priority of interval or unit is definite to be referred to: the wherein limit priority of information of take is that mark forms information processing queue.
Adopt the mixed inference mode of rule-based (RBR) and example (CBR) to analyze the relevance of warning information; Make the method there is self-learning capability, overcome the problem that expert system knowledge obtains " bottleneck ".
RBR mode is mainly used in there is the processing of causal equipment alarm information, the method of employing based on graph theory, utilize production rule to describe expert system knowledge, according to anomaly relation (being one-level causality), formation causality tree, according to causality topological diagram, through topological analysis, process associated alarm information, causality is stored in knowledge base, wherein in knowledge base, also comprises causal incidence relation rule, by device exception information type set information processing priority with carry out the necessary knowledge of association analysis;
Inference mode based on example is mainly used in certain or a plurality of abnormal information to be described as an example, adopt nearest neighbor strategy retrieval example storehouse, being about to abnormal signal numbering converts Boolean type to and (in example, exists this signal to be designated as 1, do not exist for 0) to calculate the similarity of target example and source example, according to the size of similarity, choose 1-3 example the most similar and list, provide the reasoning results and processing scheme.
All take commercial SQL storehouse and build as basis in knowledge base and example storehouse, deposits respectively the case after the special knowledge in the required field of instrument for equipment alarm signal of sending in processing and warning information are processed; Except keyword priority mapping off-balancesheet, in knowledge base and example storehouse, include the dependency relation tables such as example description list, abnormal signal processing rule table, causality table, history alarm information table, in order to the association analysis of warning information and diagnosis.
The reasoning results and result are all presented in the individual page in the alarm window of supervisory control system, remind dispatcher to process in time abnormal, auxiliary on-line decision; The reasoning results and result are saved as to historical information, as the initial data of association analysis reasoning inverting; Record reasoning process simultaneously, generate analysis report, with document form, preserve, so that operations staff analyzes summing up experience.
The scope of the mode time of setting is 5-15s, and the length of the mode time of setting need be set according to on-the-spot ruuning situation and historical analysis data flexibly by user.
The scope of the association analysis time of setting is 3-10s, and the association analysis time length of setting need be set according to on-the-spot ruuning situation and historical analysis data flexibly by user.
Described method is applicable to real-time state and research state, in real time under state from warning information treatment system pretreated unit exception warning information and the fault message of Real-time Obtaining, under research state, obtain history alarm information or manually simulation set abnormality alarming information and fault message.
A specific embodiment of the present invention below:
Be illustrated in figure 2 program realization flow figure of the present invention, the unit exception sequential alarm signal to collect in certain the 220kV transformer station a period of time shown in table 1, illustrates rational analysis process of the present invention.
The list of table 1 unit exception sequential alarm signal
| Sequence number | Date | Hour Minute Second millisecond | Unit exception alarm signal | Plant stand | Interval |
| 1 | 20080416 | 75416715 | #1 cooler fault | Certain transformer station | #1 becomes |
| 2 | 20080416 | 75418000 | #1 temperature raises extremely | Certain transformer station | #1 becomes |
| 3 | 20080416 | 75416600 | #1 becomes oil stream fault | Certain transformer station | #1 becomes |
| 4 | 20080416 | 75417460 | Lighten protection action of #1 | Certain transformer station | #1 becomes |
| 5 | 20080416 | 75417466 | It is abnormal that #1 becomes oil level | Certain transformer station | #1 becomes |
Receive after fault-signal time sequence information, monitor each line tripping number of times, the mode time of setting is 10s.
Receive after unit exception signal sequence information search key priority mapping relation table, the priority of mark warning information.Priority is that the signal classification based on warning information treatment system is set with standard, under normal weather condition, be divided into 3 grades, the priority class of traffic of all or part of disabler of equipment is high, and the priority class of traffic that the equipment general level of the health reduces is taken second place, and other alarm signal priority are low.Take transformer and circuit breaker as example, and abnormal information keyword has: fault, disappearance, broken string, locking, light gas, extremely, not energy storage, leakage, warning, corresponding priority is: 1,1,1,1,2,2,3,3,3, the larger priority of numeral is lower.When duplicating coupling, with priority maximum mark.Therefore the abnormality alarming information sequence notation receiving in the present embodiment is: 1,2,1,2,2.
The association analysis time of setting is 5s, and this abnormality alarming information is all in range of receiving, and information source belongs to same unit simultaneously, therefore they deposit in the #1 of this transformer station change in real-time storehouse.Whether the signal processing model that now scans all plant stands has renewal, and the mode time of setting does not also finish (it is front twice that this method circulation is carried out, and the not renewal of plant stand pattern, just has renewal afterwards), determines that this plant stand is in normal mode.
According to prioritization, require to determine that in this unit, abnormal signal processing priority is 1.Abnormal signal in unit is described as to a new example (source example), example description scheme is { 1,2 again, 3,4,5, a}, the numbering of signal in numeral unit (numbering of this signal is the unique period of marker in remote signalling definition list, and in the present embodiment, hypothesis numbering is sequence number in time-scale), the example type before letter representation under signal, as a indication transformer, b represents bus, and c represents generator, and d represents line-breaker.Then adopt nearest neighbor strategy retrieval example storehouse, according to example type and example length, find corresponding example storehouse example (target example), the length of example is searched by half that is greater than source example length, searches in example result as shown in table 2,
Then carry out similarity calculating.Convert abnormal signal numbering to Boolean type, in example, exist this signal to be designated as 1, do not exist and be designated as 0, according to binary variable value relation, calculate similarity, formula is
wherein Q represents that example intermediate value is all 1 attribute number; R represents in example Y that attribute value is 0 and the number of the attribute that in example X, attribute value is 1; S represents in example Y that attribute value is 1 and the number of the attribute that in example X, attribute value is 0; T represent attribute value in example Y be 0 and example X in attribute value be also the number of 0 attribute.
The present embodiment similarity value calculation is 0.9, (value is more than 0.9) meets the requirements, the reasoning results and processing scheme deposit in buffer memory, because do not mate completely, therefore remaining alarm signal is searched in knowledge base to the causality in real-time storehouse that is stored in that causality forms to be set, by topological analysis, see if there is causalnexus relation, wherein causality tree as shown in Figure 2, knowledge base one-level causality is as shown in table 3, again according to abnormal signal processing rule table, as shown in table 4, provide the reasoning results and processing scheme, the reasoning results is, transformer oil level causes light gas protecting action extremely.
Finally comprehensively provide the reasoning results and processing scheme, above send alarm window, and add new example by example database table structure, generate analysis report.If remain alarm signal in embodiment, there is not incidence relation, directly carry out causality reasoning, reach a conclusion and add example storehouse.
Table 2 example description list
Table 3 causality table
| Numbering | Because of abnormal numbering | The abnormal numbering of fruit |
| 1 | 3 | 1 |
| 2 | 1 | 2 |
| 3 | 5 | 2 |
| 4 | 5 | 4 |
Table 4 abnormal signal processing rule table
Reasoning process and this example real-time for other or history alarm signal are similar, are concrete decision logic difference.
The present invention adopts mode identification method to realize the weather condition in automatic Identification abnormality alarming information plant stand of living in region, to determine the pattern of information processing.Due in actual generation typhoon situation, transmission line is influenced the most serious, when therefore system is moved, carry out the monitoring to transmission line switch trip quantity, when in circuit, switch trip number of times is obviously more than the set point of normal condition within a certain period of time, by topological analysis, found the plant stand of corresponding region, these plant stands are set as to typhoon model, in unit exception warning information Intelligent treatment subsystem, the processing of abnormality alarming information is pressed typhoon model and is processed, when the switch trip number of times of system monitoring is in normal range (NR), each typhoon model is gone to the factory to stand and is transferred normal mode to.Certain hour is wherein the mode time of setting, and the length of the mode time of setting need be set flexibly according to the historical information in plant stand typhoon situation and on-the-spot ruuning situation, guarantees pattern recognition accuracy.
Want the incidence relation between accurate judgment device abnormality alarming information, provide diagnostic result and processing policy, the information in a period of time of need to intercepting in receiving abnormality alarming message buffer is as reasoning foundation, only the information in this time period is carried out to reasoning and judging, this time period is called the association analysis time of setting.Setting this association analysis time is to have certain deviation in sequential while receiving in main station system in the distance because of on-the-spot simultaneous several signals, mainly because automated system information processing causes.The association analysis time of setting will escape automated system message processing time exactly, but can not be oversize, otherwise does not have related signal also can be merged in this example.Time is set according to on-the-spot ruuning situation flexibly by user.
Anyly be familiar with those skilled in the art in the technical scope that the present invention discloses, the variation that can expect easily or replacement, within all should being encompassed in protection scope of the present invention.Therefore, protection scope of the present invention should be as the criterion with the protection range of claim.
Claims (10)
1. the association analysis of area power grid unit exception alarm signal and diagnostic method, is characterized in that, it comprises the following steps:
1) receive the fault message from warning information treatment system, according to transmission line switch trip quantity in monitor for faults information in the mode time of setting, judge under switch that plant stand is whether in typhoon situation, these plant stand abnormality alarming messaging models of mark are normal mode under these plant stand default situations;
2) receive the abnormality alarming information from warning information treatment system, according to the priority of extractive technique automatic Identification mark warning information according to keywords in the association analysis time of setting, with time-division interval or subdivision, deposit in the real-time storehouse with hierarchical model;
3) scanning step 1) in execution result, determine whether plant stand pattern has renewal, the plant stand warning information in typhoon model and normal mode is processed respectively;
4) prioritization of warning information being processed, the power plant and substation's information priority treatment under typhoon model is determined its interval, place or cell processing order by the priority of information itself simultaneously;
5) the information processing order obtaining according to step 4), is described as successively an example by it according to the example description scheme before processing in example storehouse, and adopts nearest neighbor search strategy to retrieve similar example in conjunction with example storehouse, judges whether similarity meets the requirements;
6) if do not met the similarity requirement of step 5), in conjunction with knowledge base expertise, according to the relevance of causality inference mechanism analytical information, and provide unit exception alarm cause and respective handling strategy, above send supervisory control system alarm window to show;
7) as met the similarity requirement of step 5), directly provide the reasoning results, and on send supervisory control system alarm window to show;
8) integrating step 6) result, it is described as to new example or original example is modified according to the example description scheme after processing in example storehouse, and deposit in example storehouse, generate analysis report simultaneously.
2. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, it is characterized in that, in described knowledge base, set up and have keyword priority mapping table, list structure to comprise under numbering, keyword, typhoon model priority under priority, normal mode.
3. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, it is characterized in that, the height of described priority is determined according to the importance of information, if do not process can be accidents caused immediately abnormal information priority high, the information priority level that can not cause the accident is in a short time low.
4. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, it is characterized in that, described real-time storehouse has hierarchical model, the intermediate object program that storehouse comprises electrical network model, secondary model, expertise and an association analysis in real time.
5. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, is characterized in that, realizes the important information priority treatment that priority is high; Order is successively according to the priority arrangement of plant stand pattern, electric pressure, interval or unit, and the priority of interval or unit is definite to be referred to: the wherein limit priority of information of take is that mark forms information processing queue.
6. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, is characterized in that, adopts rule-based and mixed inference mode example to analyze the relevance of warning information;
RBR mode adopts the method based on graph theory, utilize production rule to describe expert system knowledge, according to anomaly relation, formation causality tree, according to causality topological diagram, through topological analysis, process associated alarm information, causality is stored in knowledge base, wherein in knowledge base, also comprises causal incidence relation rule, by device exception information type set information processing priority with carry out the necessary knowledge of association analysis;
Inference mode based on example adopts nearest neighbor strategy retrieval example storehouse, be about to abnormal signal numbering and convert Boolean type to calculate the similarity of target example and source example, according to the size of similarity, choose 1-3 example the most similar and list, provide the reasoning results and processing scheme;
All take commercial SQL storehouse and build as basis in described knowledge base and example storehouse, deposits respectively the case after the special knowledge in the required field of instrument for equipment alarm signal of sending in processing and warning information are processed; Except keyword priority mapping off-balancesheet, in knowledge base and example storehouse, include example description list, abnormal signal processing rule table, causality table and history alarm information table, in order to the association analysis of warning information and diagnosis.
7. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, it is characterized in that, described the reasoning results and result are all presented in the individual page in the alarm window of supervisory control system, remind dispatcher to process in time abnormal, auxiliary on-line decision; The reasoning results and result are saved as to historical information, as the initial data of association analysis reasoning inverting; Record reasoning process simultaneously, generate analysis report, with document form, preserve, so that operations staff analyzes summing up experience.
8. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, is characterized in that, the scope of the mode time of described setting is 5-15s.
9. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, is characterized in that, the scope of the association analysis time of described setting is 3-10s.
10. area power grid unit exception alarm signal association analysis according to claim 1 and diagnostic method, it is characterized in that, described method is applicable to real-time state and research state, in real time under state from warning information treatment system pretreated unit exception warning information and the fault message of Real-time Obtaining, under research state, obtain history alarm information or manually simulation set abnormality alarming information and fault message.
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Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2714623B2 (en) * | 1989-03-03 | 1998-02-16 | 株式会社日立製作所 | Alarm control device |
| CN101958536B (en) * | 2010-09-20 | 2014-02-19 | 中国电力科学研究院 | Distribution network failure isolation and quick power service restoration decision support system |
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