CN106646068A - Method for diagnosing defects of intelligent substation secondary system based on multi-parameter information fusion - Google Patents
Method for diagnosing defects of intelligent substation secondary system based on multi-parameter information fusion Download PDFInfo
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- CN106646068A CN106646068A CN201710054177.3A CN201710054177A CN106646068A CN 106646068 A CN106646068 A CN 106646068A CN 201710054177 A CN201710054177 A CN 201710054177A CN 106646068 A CN106646068 A CN 106646068A
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- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
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Abstract
The invention discloses a method for diagnosing defects of an intelligent substation secondary system based on multi-parameter information fusion. The method comprises the following steps of: 1) establishing an information fusion model for diagnosing the defects of the secondary equipment; 2) establishing an expert database for diagnosing and analyzing the defects of the secondary equipment; 3) collecting original data information of the secondary equipment; 4) performing information fusion; and 5) outputting a diagnosing result. According to the method disclosed by the invention, on the basis of reference to the existing information fusion method, according to the collected reference data and electric power test data, a self-adaptive algorithm is utilized to optimize a network and information induction-deduction technique; the defects of the electric secondary equipment are comprehensively diagnosed; the relation network is constructed by dividing the defect characteristic parameters according to the logic relation between different defect characteristic information; the defect reasons of the secondary equipment can be reflected from different sides; the elementary probability distribution assignment for an evidence is improved according to the output of uncertain reasoning of the evidence; the reliability of the evidence for recognizing single disabled mode is fully reflected.
Description
Technical field
The present invention relates to a kind of Substation fault diagnosis, specifically a kind of intelligence based on Multi-parameter information fusion
Energy transformer station secondary system defect diagnostic method, belongs to substation fault analysis technical field.
Background technology
Intelligent transformer station electrical secondary system be power system measuring, protection, monitoring important composition, operational excellence it is secondary
Impact of the system to whole electrical network is most important.The reliability requirement of power system electrical secondary system is not only embodied in and ensure that user
Normal electricity consumption, the service life of extension device, additionally it is possible to ensure power grid security effectively economical operation, improve operating efficiency.
Because electrical secondary system adopts hardwire in traditional transformer station, there is respective logic reality loop, physics wiring and change
There is one-to-one relation in the functional configuration in power station, therefore by detecting that the wiring of electrical secondary system just can analyze determination power transformation
Electrical secondary system of standing failure.But with the development of technology, intelligent substation becomes future substation development with its distinctive advantage
Trend.And hardwire is then changed into communication network by secondary system of intelligent substation, i.e., real loop is changed into empty loop, stand in adopt
Sample information, control information, locking information, status information and relay protection tripping operation is closed a floodgate to be realized by communication network, net
Network topological structure is no longer corresponded with the input and output of function information and signal.Based on these changes, intelligent substation two
The fault diagnosis of subsystem is very different with traditional transformer station.
Because secondary system of intelligent substation defect has diversity and uncertainty, exist between various defects multiple
Miscellaneous contact so that defect diagonsis process is complex, single diagnostic method is difficult to meet demand.In order to more accurate
Judge defect type, need the secondary system of intelligent substation defect analysis that a kind of comprehensive many-side defect information makes inferences to examine
Disconnected method.
The content of the invention
To solve the deficiency that prior art is present, the invention provides a kind of intelligent power transformation based on Multi-parameter information fusion
Electrical secondary system of standing defect diagnostic method, it can carry out comprehensive diagnos to secondary equipment in power system defect.
The present invention solves its technical problem and adopts the technical scheme that：Intelligent substation two based on Multi-parameter information fusion
Subsystem defect diagnostic method, is characterized in that, comprise the following steps：
1) information fusion model of secondary device defect diagonsis, the information fusion mould of the secondary device defect diagonsis are set up
Information fusion is divided into data Layer fusion, Feature-level fusion and Decision-level fusion by type according to the level of different fusion objects；
2) experts database of secondary device defect diagonsis analysis, the expert stock of the secondary device defect diagonsis analysis are set up
Contain the inference rule diagnosed to secondary device defect；
3) primary data information (pdi) of secondary device is gathered, the primary data information (pdi) includes electrical secondary system configuration information, sets
Standby on-line monitoring information, comprehensive monitor information on-line from warning information (from transformer station's integrated system) and communication network；
4) information fusion is carried out, using the information fusion model of secondary device defect diagonsis to secondary device with confidence
Breath, equipment on-line monitoring information, comprehensive classified from warning information, communication network on-line monitoring information, collect process and extract special
Reference ceases, and according to different classes of defect characteristic information the matching of different diagnostic rules is carried out, and is entered according to defect characteristic information
Row secondary device defect location；
5) diagnostic result output is exported, secondary device defect diagonsis result is exported and is provided dependent diagnostic explanation.
Further, the experts database diagnosis object of the secondary device defect diagonsis analysis includes combining unit, protection dress
Put, intelligent switch, measure and control device, communication network and communicator.
Further, in information fusion process, to gather secondary device data message carry out respectively data Layer fusion,
Feature-level fusion and Decision-level fusion.
Further, the data Layer fusion is exactly that the primary data information (pdi) to collection is classified, collected and comprehensive, when
When defect occurs, there is a large amount of message informations, monitoring alarm information and accident information in interior will concentration of standing, by the original number for collecting
Carry out characteristic information extraction according to analysis is merged.
Further, the Feature-level fusion is exactly that sifting sort process is carried out to warning information, and original alarm is believed
Breath is processed, and is stated with certain world knowledge structure, is carried out not according to different classes of defect characteristic information
With the matching of diagnostic rule.
Further, the Decision-level fusion is exactly to carry out secondary device working condition respectively according to defect characteristic information to examine
It is disconnected, and progressively analyze concrete reason and the minimum zone that secondary device defect occurs.
Further, in step 4) in, using DS information fusion algorithms according to DS evidence theories and the group of DS evidence theories
Information fusion is normally carried out, the DS evidence theories include basic probability assignment, belief function and likelihood function.
Further, during secondary system of intelligent substation defect diagonsis is carried out,
When first voltage combining unit SV that secondary device defect is certain 500kV line segregation Intelligent component cabinet is always alerted
During information, the primary data information (pdi) include measure and control device SV receive warning information, protection and combining unit self-check of device message,
Sv/goose group-net communication facility informations；
During defect occurs, relay protection and fault information system is reported " first voltage combining unit SV is always alerted "
As the input data of data Layer, SCD file is parsed first, whether the issue device for judging the alarm is measure and control device, if not
It is to judge the warning information to send out by mistake, then characteristic layer is analyzed according to experts database and lists triggering measure and control device and sends the alarm
The reason for, such as measure and control device, combining unit installation's power source power down, GOOSE chain ruptures, packet parsing exception or exchange fault are former
Cause, judge above reason logical value (1,0), lock the reason, last decision-making level provides corresponding solution according to the input of reason
Certainly scheme is (such as verifying power supply power down light word, inspection goose chain rupture light words, inspection respective physical optical fiber circuit or artificial experience are done
In advance).
Further, the reason for triggering measure and control device sends the alarm includes measure and control device, combining unit device electricity
Source power down, GOOSE chain ruptures, packet parsing exception or exchange fault reason.
Further, corresponding solution includes verifying power supply power down light word, inspection goose chain rupture light words, inspection
Look into respective physical optical fiber circuit or artificial experience intervention.
The invention has the beneficial effects as follows：
The present invention proposes a kind of second power equipment defect synthesis diagnosis model based on many reference amounts, with reference to existing letter
Breath fusion method, with reference to the reference data and power test data that have gathered, optimizes network and information is returned using adaptive algorithm
Receive rendering technique, comprehensive diagnos is carried out to second power equipment defect, it is closed according to the logic between different defect characteristic information
System, by dividing defect characteristic parameter relational network is built, and never ipsilateral reflects the defect cause of secondary device, while knot
The output for closing evidence uncertain reasoning improves the basic probability assignment assignment of evidence body, fully demonstrates evidence body to single barrier pattern
The confidence level of identification.
For prior art ambiguity and uncertain problem present in defect diagonsis process, the present invention proposes base
In the equipment deficiency diagnostic techniques of many reference amounts, what it was more suitable for problem solves the problems, such as and overcomes multiple shot array.Due to defect with
The causality of various degrees between sign, considers to judge that equipment may be sent out on the basis of all indications parameter at comprehensive
Raw defect, it is possible to effectively improve the accuracy of defect diagonsis, reduces the possibility failed to judge, and eliminates measurement in on-line monitoring and misses
Poor impact.Each equipment and communication network are not ensured that and absolutely detect whole defects in transformer station, and will alarm
Information carries out indifference upload, therefore, the infull situation of defect characteristic information or warning information is occurred in some cases, this
It is bright to carry out auxiliary diagnosis by other related warning information defects, and infer the lack part of defect warning information, aid in school
Test diagnostic result accuracy.
Description of the drawings
Fig. 1 is method of the present invention flow chart；
Fig. 2 is the basic framework figure of the information fusion model of secondary device defect diagonsis of the present invention；
Fig. 3 is the concrete structure schematic diagram of information fusion model shown in Fig. 2；
Fig. 4 is the structural representation of the experts database of secondary device defect diagonsis analysis of the present invention；
Fig. 5 is the particular flow sheet that the present invention carries out secondary system of intelligent substation defect diagonsis；
Fig. 6 is the schematic diagram of DS evidence theories shown in the present invention.
Specific embodiment
Clearly to illustrate the technical characterstic of this programme, below by specific embodiment, and with reference to its accompanying drawing, to this
It is bright to be described in detail.Following disclosure provides many different embodiments or example is used for realizing the different knots of the present invention
Structure.In order to simplify disclosure of the invention, hereinafter the part and setting of specific examples are described.Additionally, the present invention can be with
Repeat reference numerals and/or letter in different examples.This repetition is that for purposes of simplicity and clarity, itself is not indicated
Relation between various embodiments being discussed and/or being arranged.It should be noted that part illustrated in the accompanying drawings is not necessarily to scale
Draw.Present invention omits to the description of known assemblies and treatment technology and process avoiding being unnecessarily limiting the present invention.
As shown in figure 1, a kind of secondary system of intelligent substation defect diagonsis based on Multi-parameter information fusion of the present invention
Method, it is comprised the following steps：
1) information fusion model of secondary device defect diagonsis, the information fusion mould of the secondary device defect diagonsis are set up
Information fusion is divided into data Layer fusion, Feature-level fusion and Decision-level fusion by type according to the level of different fusion objects；
2) experts database of secondary device defect diagonsis analysis, the expert stock of the secondary device defect diagonsis analysis are set up
Contain the inference rule diagnosed to secondary device defect；
3) primary data information (pdi) of secondary device is gathered, the primary data information (pdi) includes electrical secondary system configuration information, sets
Standby on-line monitoring information, comprehensive monitor information on-line from warning information (from transformer station's integrated system) and communication network；
4) information fusion is carried out, using the information fusion model of secondary device defect diagonsis to secondary device with confidence
Breath, equipment on-line monitoring information, comprehensive classified from warning information, communication network on-line monitoring information, collect process and extract special
Reference ceases, and according to different classes of defect characteristic information the matching of different diagnostic rules is carried out, and is entered according to defect characteristic information
Row secondary device defect location；
5) diagnostic result output is exported, secondary device defect diagonsis result is exported and is provided dependent diagnostic explanation.
As shown in Figures 2 and 3, the information fusion model of secondary device defect diagonsis is different according to the level of fusion object,
Information fusion is divided into low layer (data level or Pixel-level), middle level (feature level) and high-rise (decision level):(1) data Layer (as
Plain layer) fusion be exactly directly merge the initial data collected by detection terminal, and combined analysis；(2) Feature-level fusion is believed
The intermediate layer of breath fusion, it carries out comprehensive analysis to characteristic information and processes；(3) Decision-level fusion is level fusion, its knot
Fruit provides foundation for control decision, and in the case where one or several information sources fail, Decision-level fusion also can continue to work,
With fault-tolerance.
Data Layer fusion, Feature-level fusion and Decision-level fusion are described in detail separately below：
(1) data Layer fusion.The characteristic information for generally being extracted should be the abundant expression amount or statistic of data message, according to
This is classified to primary data information (pdi), is collected and comprehensive.When defect occurs, stand in will concentrate occur a large amount of message informations,
Monitoring alarm information and accident information, this method believes electrical secondary system configuration information, equipment on-line monitoring information, comprehensive alarm certainly
The information such as breath, communication network on-line monitoring information are referred to as initial data.System is utilized from multiple intelligent substation Intelligent Measurements
The initial data that analyzer terminal is collected carrys out characteristic information extraction.
(2) Feature-level fusion.In comprehensive analysis and the intermediate level process for processing, defect diagonsis should first to warning information
Sifting sort process is carried out, and original alarm information is processed, stated with certain world knowledge structure, pressed
The matching of different diagnostic rules is carried out according to different classes of defect characteristic information.Here comprising primary equipment working condition, two
Secondary intelligent apparatus working condition, COMMUNICATION NETWORK PERFORMANCES, communication device works state.Resolution logic link, live integrated system point
Table, specifies the corresponding relation that light word is alerted with specific MMS, understands association message as auxiliary judgment foundation.Such as protection connects
The information such as whether the process layer SMV messages of receipts, the related station level MMS messages alarm for sending, secondary circuit configuration correct, can be with
As defect dipoles checking.
(3) Decision-level fusion.During comprehensive diagnos, secondary intelligent apparatus work will respectively be carried out according to defect characteristic information
Make state, input/output loop integrality, COMMUNICATION NETWORK PERFORMANCES, communication device works condition diagnosing.Then in the middle of comprehensive analysis
The reasoning results, according to the incidence relation between logical circuit, the secondary device of SCD descriptions, the secondary device physics of configuration typing
Communication network topology relation, progressively analysis occurs in the concrete reason and minimum zone of this light word.Finally comprehensive diagnos is tied
Fruit exports, and provides dependent diagnostic explanation.
Further, the experts database diagnosis object of the secondary device defect diagonsis analysis includes combining unit, protection dress
Put, intelligent switch (including intelligent assembly and switch operating mechanism), measure and control device, communication network and communicator.Such as Fig. 4 institutes
Show, the present invention classifies according to defect diagonsis object to knowledge base.Because expert system obtains the fullest extent of defect information,
The scope of application of its inference rule is determined, meanwhile, when there is new defect case to occur, need the study by expert system
Mechanism is updated perfect to rule base.
As shown in figure 5, during secondary system of intelligent substation defect diagonsis is carried out, here protecting letter system (relay
Protection and failure information system) report first voltage combining unit SV of certain 500kV line segregation Intelligent component cabinet always to alert
As a example by.
When first voltage combining unit SV that secondary device defect is certain 500kV line segregation Intelligent component cabinet is always alerted
During information, the primary data information (pdi) include measure and control device SV receive warning information, protection and combining unit self-check of device message,
Sv/goose group-net communication facility informations etc.；
During defect occurs, relay protection and fault information system is reported " first voltage combining unit SV is always alerted "
As the input data of data Layer, SCD file is parsed first, judge that (issue device is for normal for the issue device of the alarm
Measure and control device) whether it is measure and control device, as not being to judge the warning information to send out by mistake, measure and control device in this way, then characteristic layer
The reason for triggering measure and control device analyzed and listed according to experts database sending the alarm, such as measure and control device, combining unit installation's power source
Power down, GOOSE chain ruptures, packet parsing exception or exchange fault reason, judge above reason logical value (1,0), locking should
Reason, last decision-making level provides corresponding solution (such as verifying power supply power down light word, inspection goose according to the input of reason
Chain rupture light word, inspection respective physical optical fiber circuit or artificial experience intervention etc.).
Further, in step 4) in, using DS (Dempster_Shafer) information fusion algorithms according to DS evidence theories
And the rule of combination of DS evidence theories carries out information fusion.DS information fusion algorithms are described in detail below.
DS evidence theories
As shown in fig. 6, the theory information that collects different channels is in addition comprehensive, eliminates and be there may be between multi-source information
Redundancy and contradictory information, it is and in addition complementary to it, reduce uncertain, formed to the relatively complete uniformity of system environments
The process of description.Result (evidence) after occurring mainly for event, seeks the main cause (hypothesis) of event generation, for tool
There is many attributes diagnosis problem that subjective uncertainty judges, DS evidence theories are one and merge the effective of subjective uncertainty information
, there are various possibility, or the combination of many factors the reason for means, such as one failure generation, induction, and the theory is by luring
Because probability of happening is allocated, associative function is calculated, and probability highest inducement is derived in combination.
If Θ is an identification framework or assumes space.
(1) basic probability assignment
Basic probability assignment：Basic Probability Assignment, abbreviation BPA.BPA on identification framework Θ
It is the function m of 2 Θ → [0,1], referred to as mass functions.And meetAnd
Wherein so that m (A)>0 A is referred to as burnt unit (Focal elements).
(2) belief function
Belief function is also referred to as belief function (Belief function).Trust letter on identification framework Θ based on BPA m
Number is defined as：
Represent to A propositions to be genuine trusting degree.
(3) likelihood function
Likelihood function is also referred to as likelihood score function (Plausibility function).BPA m are based on identification framework Θ
Likelihood function be defined as：
Represent to A to be non-false trusting degree, the uncertainty measure that may be set up also is seemed to A.
Belief function Bel (A) and likelihood function Pl (A) compositions trust interval [Bel (A), Pl (A)], to represent to certain
The confirmation degree of individual hypothesis.
2nd, the rule of combination of DS evidence theories
1) combinatorial formula
ForTwo mass function m1 on Θ, the Dempster composition rules of m2 are：
Wherein, K is normaliztion constant
ForLimited mass function m1, m2 on identification framework Θ ..., the Dempster composition rules of mn
For：
Wherein,
2) combination is trusted at interval (the evidence interval after combination)The trust interval of A and B is respectively：
El1(A)=[Bel1(A), pl1(A)], El2(B)=[Bel2(B), pl2(B)]
For ambiguity and uncertainty present in defect diagonsis process, the present invention is proposed based on the equipment of many reference amounts
Defect diagonsis technology, it is more suitable for the solution of problem, and overcomes multiple shot array problem.Due to existing between defect and sign
Different degrees of causality, considers to judge the defect that equipment may occur on the basis of all indications parameter at comprehensive, so that it may
To effectively improve the accuracy of defect diagonsis, the possibility failed to judge is reduced, eliminate the impact of measure error in on-line monitoring.Power transformation
Each equipment and communication network are not ensured that and absolutely detect whole defects in standing, and warning information is carried out in indifference
Pass, therefore, the infull situation of defect characteristic information or warning information is occurred in some cases, the present invention is related by other
Warning information defect carries out auxiliary diagnosis, and infers the lack part of defect warning information, and auxiliary examination diagnostic result is accurate
Property.
The above is the preferred embodiment of the present invention, for those skilled in the art,
Without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications are also regarded as this
Bright protection domain.
Claims (10)
1. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion, is characterized in that, including following step
Suddenly：
1) information fusion model of secondary device defect diagonsis is set up, the information fusion model of the secondary device defect diagonsis is pressed
Information fusion is divided into data Layer fusion, Feature-level fusion and Decision-level fusion according to the level of different fusion objects；
2) experts database of secondary device defect diagonsis analysis is set up, the experts database of the secondary device defect diagonsis analysis is stored with
The inference rule that secondary device defect is diagnosed；
3) primary data information (pdi) of secondary device is gathered, the primary data information (pdi) includes that electrical secondary system configuration information, equipment exist
Line monitoring information, it is comprehensive from warning information and communication network on-line monitoring information；
4) carry out information fusion, using the information fusion model of secondary device defect diagonsis to the configuration information of secondary device, set
Standby on-line monitoring information, comprehensive classified from warning information, communication network on-line monitoring information, collect process and extract feature letter
Breath, according to different classes of defect characteristic information the matching of different diagnostic rules is carried out, and carries out two according to defect characteristic information
Secondary device defect location；
5) diagnostic result output is exported, secondary device defect diagonsis result is exported and is provided dependent diagnostic explanation.
2. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 1,
It is characterized in that, the experts database diagnosis object of the secondary device defect diagonsis analysis includes that combining unit, protection device, intelligence are opened
Pass, measure and control device, communication network and communicator.
3. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 1,
It is characterized in that, in information fusion process, the secondary device data message to gathering carries out respectively data Layer fusion, characteristic layer and melts
Close and Decision-level fusion.
4. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 3,
It is characterized in that, the data Layer fusion is exactly that the primary data information (pdi) to gathering is classified, collected and comprehensive, when defect occurs
When, there is a large amount of message informations, monitoring alarm information and accident information in interior will concentration of standing, and the initial data for collecting is closed
And analysis carrys out characteristic information extraction.
5. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 3,
It is characterized in that, the Feature-level fusion is exactly to carry out sifting sort process to warning information, and to original alarm information at
Reason, is stated with certain world knowledge structure, and according to different classes of defect characteristic information different diagnosis rule are carried out
Matching then.
6. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 3,
It is characterized in that, the Decision-level fusion is exactly to carry out secondary device working condition diagnosis respectively according to defect characteristic information, and by
Concrete reason and minimum zone that step analysis secondary device defect occurs.
7. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 1,
It is characterized in that, in step 4) in, entered according to the rule of combination of DS evidence theories and DS evidence theories using DS information fusion algorithms
Row information merges, and the DS evidence theories include basic probability assignment, belief function and likelihood function.
8. the secondary system of intelligent substation based on Multi-parameter information fusion according to claim 1 to 7 any one lacks
Sunken diagnostic method, is characterized in that, during secondary system of intelligent substation defect diagonsis is carried out,
When the total warning information of first voltage combining unit SV that secondary device defect is certain 500kV line segregation Intelligent component cabinet
When, the primary data information (pdi) includes that measure and control device SV receives warning information, protection and combining unit self-check of device message, sv/
Goose group-net communication facility informations；
During defect occurs, relay protection and fault information system reports " first voltage combining unit SV is always alerted " conduct
The input data of data Layer, parses first SCD file, and whether the issue device for judging the alarm is measure and control device, if not being
The warning information is judged to send out by mistake, then the original that triggering measure and control device sends the alarm is analyzed and listed to characteristic layer according to experts database
Cause, judge above reason logical value (1,0), lock the reason, last decision-making level provides corresponding solution according to the input of reason
Certainly scheme.
9. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 8,
It is characterized in that, the triggering measure and control device include the reason for send the alarm measure and control device, combining unit installation's power source power down,
GOOSE chain ruptures, packet parsing exception or exchange fault reason.
10. the secondary system of intelligent substation defect diagnostic method based on Multi-parameter information fusion according to claim 9,
It is characterized in that, corresponding solution includes verifying power supply power down light word, inspection goose chain rupture light words, checks homologue
Reason optical fiber circuit or artificial experience intervention.
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| CN110837866A (en) * | 2019-11-08 | 2020-02-25 | 国网新疆电力有限公司电力科学研究院 | XGboost-based electric power secondary equipment defect degree evaluation method |
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