CN103986238B - Intelligent substation fault diagnosis method based on probability weighting bipartite graph method - Google Patents

Intelligent substation fault diagnosis method based on probability weighting bipartite graph method Download PDF

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CN103986238B
CN103986238B CN201410230444.4A CN201410230444A CN103986238B CN 103986238 B CN103986238 B CN 103986238B CN 201410230444 A CN201410230444 A CN 201410230444A CN 103986238 B CN103986238 B CN 103986238B
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information
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probability
intelligent substation
prognostic
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CN103986238A (en
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高湛军
高诺
王俊山
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Shandong University
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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
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • 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
    • Y04S10/16—Electric power substations
    • 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
    • Y04S10/20—Systems supporting electrical power generation, transmission or distribution using protection elements, arrangements or systems

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Abstract

The invention discloses an intelligent substation fault diagnosis method based on a probability weighting bipartite graph method. The method comprises the steps that intelligent substation symptom information is obtained, and interrogation information is obtained according to practical needs of fault analysis; all the information obtained in the first step is subjected to priority classifying, the symptom information and the interrogation information are subjected to probability assignment, and a probability weighting bipartite cause-and-effect graph of a practical system is obtained; and according to the probability weighting bipartite graph obtained in the second step, a fault locating algorithm based on the Bayes formula is used for computing the probability of each fault which may happen, final fault locating is carried out, a fault element is determined, and diagnosis results are output. According to the method, the fault of a primary system of an intelligent substation can be diagnosed, meanwhile the fault of a secondary system can be diagnosed, a diagnosis process is deliberate and reliable, the diagnosis results are accurate, and the great novel fault diagnosis method is provided for intelligent substation secondary system fault diagnosis.

Description

Based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph
Technical field
The present invention relates to a kind of intelligent substation method for diagnosing faults based on probability weight Bipartition graph.
Background technology
Because electrical secondary system adopts hardwire in traditional transformer station, there is the real loop of respective logic, there is relation one to one in the functional configuration of physics wiring and transformer station, the wiring therefore by detecting electrical secondary system just can be analyzed and determine transformer station secondary system fault.But along with the development of technology, intelligent substation becomes the trend of future substation development with its distinctive advantage.Hardwire is then become communication network by secondary system of intelligent substation; namely real loop becomes empty loop; it is all realized by communication network that sample information in standing, control information, locking information, state information and relaying protection tripping operation are closed a floodgate, the input and output no longer one_to_one corresponding of network topology structure and function information and signal.Based on these changes, failure diagnosis and traditional transformer station of secondary system of intelligent substation are very different.
Because traditional Fault Diagnosis for Substation algorithm model is generally be based upon on the topological structure basis of switching information, protection act information and primary system; therefore these algorithms only relate to the failure diagnosis of transforming plant primary system, and the failure diagnosis for electrical secondary system then seldom has and relates to.Such diagnosis is very incomplete, is unfavorable for quick excision and the service restoration of fault.Simultaneously for intelligent substation, because its electrical secondary system achieves networking, the fault diagnosis model of tradition transformer station cannot be applicable to the failure diagnosis of its electrical secondary system more, and can find by consulting corresponding data, intelligent substation primary system and electrical secondary system prognostic information is relied on to carry out the research of primary system and electrical secondary system failure diagnosis, still deficienter so far.
Summary of the invention
For solving the deficiency that prior art exists, the invention discloses the intelligent substation method for diagnosing faults based on probability weight Bipartition graph, utilize intelligent substation prognostic information and call measurement information together, set up the probability weight bipartite graph of system, this method clear logic is understandable, no matter how complicated system is, all available bipartite graph represents its internal relation, the method process is simple simultaneously, very practical.Intelligent substation failure diagnosis is carried out based on the method, can the fault of intelligent diagnosis transforming plant primary system and electrical secondary system accurately.
For achieving the above object, concrete scheme of the present invention is as follows:
Step one: obtain intelligent substation prognostic information and obtain according to the actual needs of accident analysis and call measurement information together;
Step 2: priority classification is carried out to all information that step one obtains, to each prognostic information with call measurement information together and carry out probability assignment, obtain probability weight two points of cause-and-effect diagrams of real system;
Step 3: the probability weight bipartite graph obtained according to step 2, adopts the fault location algorithm based on Bayesian formula to calculate the probability of often kind of possible breakdown generation, carries out fault and finally locate, determine fault element, export diagnostic result;
Step 4: according to the fault diagnosis result exported, analyzes the reason causing this fault further, if there is same fault next time, diagnoses fast.
In described step one, intelligent substation prognostic information comprises all relaying protection action messages, switching information, electrical secondary system prognostic information, and wherein electrical secondary system prognostic information comprises network service break-make information, exchange fault information and flow information;
But described measurement information of calling together is do not upload relaying protection action message, circuit breaker information, the static configuration information of secondary communication network, dynamic monitoring information and the network delay etc. analyzing and need in prognostic information;
The static configuration information of described secondary communication network comprises the secondary system of intelligent substation network configuration information and intelligent electronic device configuration information that are obtained by the CONFIG.SYS SCD that entirely stands;
Described dynamic monitoring information comprises the dynamic monitoring information that the electrical secondary system obtained by data acquisition analysis system SCADA calls measurement information and communication network together;
Described electrical secondary system is called measurement information together and is comprised power failure, message exception and network delay.
Also comprise in described step one, according to prognostic information, failure diagnosis is carried out to intelligent substation primary system, the information belonged in primary system when prognostic information is then judged as primary system fault, and go out corresponding fault element according to the type diagnostic of information, if not primary system, then should the electrical secondary system of intelligent diagnosis transformer station further, the prognostic information according to obtaining electrical secondary system determines whether electrical secondary system equipment fault further.
In described step 2, priority classification is carried out to all information that step one obtains, to determine its priority orders;
At the prognostic information obtained and call together in measurement information, first judge whether it is primary system fault according to relaying protection action message and switching information, if be judged as primary system fault, then only with the first precedence information; If judge that primary system is normal according to circuit breaker information and protection act information, then judged to determine that secondary device fault by secondary device information and LAN Information.
According to priority determination primary system fault, next determines electrical secondary system equipment fault, and finally determine the rule of the principle determination priority of electrical secondary system network failure, described priority is established rules then really:
First priority: relaying protection action message and switching information;
Second priority: secondary device information;
3rd priority: LAN Information, specifically comprises: network break-make, exchange fault and flow and the error rate.
Probability weight two points of cause-and-effect diagrams of real system are obtained in described step 2, be specially: the fault set of certainty annuity, the prognostic information obtained and call measurement information collection together, sets up corresponding probability weight bipartite graph according to the fault set of system to prognostic information and the topological relation of calling together between measurement information collection.
The embody rule of probability weight Bipartition graph is described: suppose that the fault set of a system is for F:(L for a simple electric power system s, B s), wherein L sfor line fault, its probability occurred is 0.1629, B sfor substation bus fault, its probability occurred is 0.0058; Obtain prognostic information and call measurement information collection S together 0: (J w, R w, C w, L w, B w), wherein J wfor circuit breaker trip signal, R wto attach most importance to switching signal, C wfor current differential protection signal, L wfor mother's difference pilot protection signal, B wfor bus failure protection signal.According to the relation between possible fault and prognostic information, can this system probability weight bipartite graph as shown in Figure 4.
Fault location algorithm formula based on Bayesian formula in described step 3 is specially:
P ( f | S N ) = Σ S i ∈ S N P ( f | S i ) Σ S j ∈ symtom ( f ) P ( f | S j )
In formula, S nfor prognostic information with call measurement information collection together; s ifor S nin i-th information; S jfor the prognostic information relevant to fault with call measurement information together and concentrate a jth information; Symtom (f) for all indications information that is associated with fault f with call measurement information collection together;
Described step 3 detailed process for: based on obtained probability bipartite graph, calculate the probability that often kind of possible breakdown occurs, namely each fault is corresponded to, the probability that it occurs can both be tried to achieve under acquired prognostic information and the condition of calling measurement information together, by gained probability of malfunction stored in suspicious component library H, the descending arrangement of probable value each fault occurred in H, what probable value was maximum is the most possible fault occurred, and then determines fault element.
Described step 4 is specially: according to the result of final failure diagnosis exported, and analyzes and causes the reason of this fault and used prognostic information and call measurement information together, if similar fault occurs carries out failure diagnosis fast later in this failure diagnosis; Apply other fault diagnosis model to recalculate simultaneously, compare the similarities and differences of the result of this model and other model and respective pluses and minuses, for intelligent substation failure diagnosis finds more outstanding model algorithm.
Beneficial effect of the present invention:
(1) the present invention utilizes the prognostic information that obtains and calls measurement information together, and utilize the topological structure relation of system to set up probability weight bipartite graph, and then utilize the fault location algorithm based on Bayesian formula to carry out fault location, not only can Accurate Diagnosis primary system fault, also can Accurate Diagnosis electrical secondary system fault, determine faulty equipment, find out abort situation.
(2) the present invention is to prognostic information and call measurement information together and carried out the division of priority, can improve diagnosis efficiency greatly like this, improve the practicality of the method in the process of failure diagnosis.
(3) what the present invention adopted is probability weight bipartite graph based on system topology, failure diagnosis is carried out based on this bipartite graph, logical relation between prognostic information and fault is very clear and definite, no matter how complicated system, can the very clear internal relation found out between fault and prognostic information, obtain probability weight bipartite graph, and then carry out corresponding failure diagnosis.
(4) the present invention not only can the fault of intelligent diagnosis transforming plant primary system, also can diagnose the fault of electrical secondary system simultaneously, diagnostic procedure is very reliably careful, and diagnostic result is accurate, and this provides a good New Fault Diagnosis Method for secondary system of intelligent substation failure diagnosis.
Accompanying drawing explanation
Fig. 1: intelligent substation primary system bus operating structure figure;
Fig. 2: secondary system of intelligent substation fault diagnosis model figure;
Fig. 3: secondary system of intelligent substation Troubleshooting Flowchart;
The bipartite graph of Fig. 4: one simple electric power system;
Fig. 5: the probability weight bipartite graph of primary system;
Fig. 6: the probability weight bipartite graph of electrical secondary system.
Embodiment:
Below in conjunction with accompanying drawing, the present invention is described in detail:
Step one: obtain intelligent substation prognostic information, comprise protection information, switching information, electrical secondary system corresponding information.
Based on these prognostic information such as obtained relaying protection action message and switching informations, failure diagnosis is once carried out to intelligent substation; whether can diagnose out is accurately primary system fault; if primary system fault then diagnoses out corresponding fault element; if not primary system; then should the electrical secondary system of intelligent diagnosis transformer station further; the prognostic information obtaining electrical secondary system, as network break-make information, exchanger information, flow information etc., determines whether electrical secondary system equipment fault further.As shown in Figure 2, Troubleshooting Flowchart as shown in Figure 3 for its fault diagnosis model figure.At this; for intelligent substation primary system bus operating structure figure Fig. 1; if the switch of secondary system of intelligent substation port failure, now will obtain a large amount of prognostic information, this is comprising protection information; the relevant information of circuit breaker information and electrical secondary system equipment; simultaneously for this fault, this belongs to electrical secondary system fault, and protection and circuit breaker should not occur; if there is action, be misoperation, can embody to some extent in the fault location below.These information above that obtain also are not enough to complete reaction fault signature, now enter next step.
Step 2: according to the actual needs of accident analysis, obtains and calls measurement information together, and carry out priority classification to obtained all information.
If primary system fault, call the switching information required for survey and protection information together, if electrical secondary system fault, call the static configuration information and dynamic monitoring information and the information needed for some other failure diagnosis of surveying secondary communication network together.The static configuration information of secondary communication network comprises secondary system of intelligent substation network configuration information and intelligent electronic device configuration information etc., these information is obtained by SCD (Substation Configuration Description, CONFIG.SYS of entirely standing).And dynamic monitoring information comprises the dynamic monitoring information etc. of SCADA (Supervisory Control And Data Acquisition data acquisition analysis system) system prognostic information and communication network.These prognostic information mainly comprise communication disruption, exchange fault, power failure, message exception, network delay etc.
Call measurement information together by what obtain the prognostic information of step one and step 2, now obtained for failure diagnosis than more comprehensive information, failure diagnosis is below according to these prognostic information and calls measurement information together.But before failure diagnosis, also need the division these information obtained being carried out to priority, to determine its priority orders.
Priority is established rules then really:
First priority: circuit breaker information and protection act information;
Second priority: secondary device information;
3rd priority: LAN Information (network break-make, exchange fault, flow and the error rate etc.);
For this example, owing to being the some port failure of switch, so according to calling measurement information together and prognostic information can first determine whether as primary system fault, it is not primary system fault that diagnostic result shows this, then electrical secondary system is diagnosed, proceed corresponding failure diagnosis by Troubleshooting Flowchart.It should be noted is that; Owing to there is protection and circuit breaker misoperation in this example; so can not determine it is not primary system fault according to protection and circuit breaker information; first must carry out failure diagnosis to primary system, determine whether primary system fault, and then again failure diagnosis be carried out to electrical secondary system.
Step 3: the probability weight bipartite graph setting up real system, to fault each in bipartite graph and prognostic information corresponding with it with call measurement information together and carry out probability assignment, obtains probability weight two points of cause-and-effect diagrams of real system.
Run topological diagram by the intelligent substation primary system of reality, set up the probability weight bipartite graph of primary system.The prognostic information that we obtain at this and to call measurement information together be that circuit breaker CB5 disconnects; circuit breaker CB1; circuit breaker CB2; circuit breaker CB3; circuit breaker CB4 is normal, and bus protection is not operating, the action of circuit L1 current protection; electrical secondary system sign and call together measurement information be network disconnect, switch ports themselves fault GOOSE message and SV message disappearance etc.Based on this, possible fault set F:(bus B1 fault can be inferred, bus B2 fault; circuit L1 fault, switch ports themselves fault, merge cells fault; protecting control fault; intelligent terminal fault), according to the priority of prognostic information, first failure diagnosis is carried out to primary system; draw its probability weight bipartite graph; if diagnostic result is not primary system fault, continue to diagnose electrical secondary system, draw its probability weight bipartite graph.First based on the internal relation of fault and prognostic information, the probability weight bipartite graph of primary system can be obtained, as shown in Figure 5.Then according to electrical secondary system prognostic information and call measurement information together and obtain electrical secondary system probability weight bipartite graph, as shown in Figure 6.
Step 4: adopt the fault location algorithm based on Bayesian formula to carry out fault and finally locate, determine fault element, exports diagnostic result.
After obtaining probability weight bipartite graph above, utilize the fault location algorithm based on Bayesian formula, calculate at obtained prognostic information and the condition line L1 calling measurement information together respectively, bus B1, the probability that B2 breaks down, stored in suspicious component library H, and arrange from high to low, and then utilize the fault location algorithm based on Bayesian formula to calculate the suspicious element fault probability of electrical secondary system, stored in suspicious component library, arrange from high to low according to the size of probability of happening, the equipment broken down for most probable that probable value is the highest, and then determine faulty equipment, export fault diagnosis result.For this example, the maximum probability that switch ports themselves fault breaks down, break down so diagnostic result is switch ports themselves, result is accurate.
Step 5: according to the fault diagnosis result exported, analyzes the reason causing this fault further, if there is same fault next time, can diagnose fast.
According to the result of final failure diagnosis exported, analyze and cause the reason of this fault and used prognostic information and call measurement information together, if similar fault occurs can carry out failure diagnosis fast later in this failure diagnosis.For this example, this time useful prognostic information that obtains of fault and to call measurement information together be circuit breaker, protection act information and electrical secondary system information, if obtain similar carrying out later, then can failure judgement element fast and accurately.
Although be described in detail specific embodiment of the invention scheme by reference to the accompanying drawings above; but this is not limitation of the scope of the invention; on the basis of technical scheme of the present invention; those skilled in the art can utilize technical solution of the present invention to revise accordingly very easily, and the various amendment made for this programme or distortion are still within protection scope of the present invention.

Claims (6)

1., based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph, it is characterized in that, comprise the following steps:
Step one: obtain intelligent substation prognostic information and obtain according to the actual needs of accident analysis and call measurement information together;
Step 2: priority classification is carried out to all information that step one obtains, to each prognostic information with call measurement information together and carry out probability assignment, obtain probability weight two points of cause-and-effect diagrams of real system;
Step 3: the probability weight bipartite graph obtained according to step 2, adopts the fault location algorithm based on Bayesian formula to calculate the probability of often kind of possible breakdown generation, carries out fault and finally locate, determine fault element, export diagnostic result;
Step 4: according to the fault diagnosis result exported, analyzes the reason causing this fault further, if there is same fault next time, diagnoses fast;
Also comprise in described step one, according to prognostic information, failure diagnosis is carried out to intelligent substation primary system, the information belonged in primary system when prognostic information is then judged as primary system fault, and go out corresponding fault element according to the type diagnostic of information, if not primary system, then should the electrical secondary system of intelligent diagnosis transformer station further, the prognostic information according to obtaining electrical secondary system determines whether electrical secondary system equipment fault further;
In described step 2, priority classification is carried out to all information that step one obtains, to determine its priority orders;
At the prognostic information obtained and call together in measurement information, first judge whether it is primary system fault according to relaying protection action message and switching information, if be judged as primary system fault, then only with the first precedence information; If judge that primary system is normal according to circuit breaker information and protection act information, then judge to determine which secondary device fault by secondary device information and LAN Information;
Probability weight two points of cause-and-effect diagrams of real system are obtained in described step 2, be specially: the fault set of certainty annuity, the prognostic information obtained and call measurement information collection together, sets up corresponding probability weight bipartite graph according to the fault set of system to prognostic information and the topological relation of calling together between measurement information collection;
Described step 3 detailed process for: based on obtained probability bipartite graph, calculate the probability that often kind of possible breakdown occurs, namely each fault is corresponded to, the probability that it occurs can both be tried to achieve under acquired prognostic information and the condition of calling measurement information together, by gained probability of malfunction stored in suspicious component library H, the descending arrangement of probable value each fault occurred in suspicious component library H, what probable value was maximum is the most possible fault occurred, and then determines fault element.
2. as claimed in claim 1 based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph, it is characterized in that, in described step one, intelligent substation prognostic information comprises all relaying protection action messages, switching information, electrical secondary system prognostic information, and wherein electrical secondary system prognostic information comprises network service break-make information, exchange fault information and flow information;
But described measurement information of calling together is do not upload relaying protection action message, circuit breaker information, the static configuration information of secondary communication network, dynamic monitoring information and the network delay analyzing and need in prognostic information.
3. as claimed in claim 2 based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph, it is characterized in that, the static configuration information of described secondary communication network comprises the secondary system of intelligent substation network configuration information and intelligent electronic device configuration information that are obtained by the CONFIG.SYS SCD that entirely stands;
Described dynamic monitoring information comprises the dynamic monitoring information that the electrical secondary system obtained by data acquisition analysis system SCADA calls measurement information and communication network together;
Described electrical secondary system is called measurement information together and is comprised power failure, message exception and network delay.
4., as claimed in claim 1 based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph, it is characterized in that, described priority is established rules then really:
First priority: relaying protection action message and switching information;
Second priority: secondary device information;
3rd priority: LAN Information, specifically comprises: network break-make, exchange fault, flow and the error rate.
5., as claimed in claim 1 based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph, it is characterized in that, the fault location algorithm formula based on Bayesian formula in described step 3 is specially:
P ( f | S N ) = Σ S i ∈ S N P ( f | s i ) Σ S j ∈ symtom ( f ) P ( f | S j )
In formula, S nfor prognostic information with call measurement information collection together; s ifor S nin i-th information; S jfor the prognostic information relevant to fault with call measurement information together and concentrate a jth information; Symtom (f) for all indications information that is associated with fault f with call measurement information collection together.
6. as claimed in claim 1 based on the intelligent substation method for diagnosing faults of probability weight Bipartition graph, it is characterized in that, described step 4 is specially: according to the result of the final failure diagnosis exported, analyze and cause the reason of this fault and used prognostic information and call measurement information together, if similar fault occurs carries out failure diagnosis fast later in this failure diagnosis; Apply other fault diagnosis model to recalculate simultaneously, compare the similarities and differences of the result of this model and other model and respective pluses and minuses, for intelligent substation failure diagnosis finds more outstanding model algorithm.
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