CN110045207A - A kind of complex fault diagnostic method based on power grid architecture and multisource data fusion - Google Patents
A kind of complex fault diagnostic method based on power grid architecture and multisource data fusion Download PDFInfo
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- CN110045207A CN110045207A CN201910344354.0A CN201910344354A CN110045207A CN 110045207 A CN110045207 A CN 110045207A CN 201910344354 A CN201910344354 A CN 201910344354A CN 110045207 A CN110045207 A CN 110045207A
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- G—PHYSICS
- G01—MEASURING; TESTING
- 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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- G—PHYSICS
- G01—MEASURING; TESTING
- 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 present invention relates to a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion, comprising the following steps: step 1: establishing faulty grids equipment connection topological relation, passes through power supply interrupted district and searches for and determines cascading failure type；Step 2: if cascading failure type is judged as transmission line of electricity, using amplitude of short circuit Suspected Degree and harmonic energy Suspected Degree as the extraction characteristic quantity of failure wave-recording file；Step 3: if cascading failure type is judged as transformer and bus, using the ratio of difference current and stalling current as the extraction characteristic quantity of failure wave-recording file；Step 4: step 2 and step 3 are established electric network failure diagnosis frame and diagnosed with complex fault real-time for power grid for transmission line of electricity and the respective extraction characteristic quantity combination of transformer and bus.Compared with prior art, the present invention has many advantages, such as that diagnosis is accurate, covering fault type is more.
Description
Technical field
The present invention relates to electric network fault Intelligent Diagnosis Technology fields, are based on power grid architecture and multi-source number more particularly, to one kind
According to the complex fault diagnostic method of fusion.
Background technique
With going deep into for power grid big data platform construction, the data that can be used in electric network failure diagnosis are more and more abundant, packet
The remote signalling amount of only " 0 " and one state is included, the fault recorder data of consecutive variations electrical quantity waveform is recorded, passes through failure wave-recording
Data can be calculated such as electric current, voltage magnitude, measure resistance, the grid faults characteristics amount such as harmonic amplitude, scheduling end data can
It is divided into analog data only comprising " 1 " and " 0 " status switch amount data and consecutive variations.
When electric network fault, the variation of power grid primary equipment topological connection relation, the collected various switching values of monitoring system
The analog data arrived with system acquisitions such as faulty recordings has certain correlation, during reflecting electric network fault
Certain fault signature.The different faults feature for comprehensively utilizing different types of data reflection, examines the complex fault in power grid
It is disconnected, there is important application value.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to be based on power grid architecture
With the complex fault diagnostic method of multisource data fusion.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of complex fault diagnostic method based on power grid architecture and multisource data fusion, comprising the following steps:
Step 1: establishing faulty grids equipment connection topological relation, searched for by power supply interrupted district and determine cascading failure type；
Step 2: doubtful with amplitude of short circuit Suspected Degree and harmonic energy if cascading failure type is judged as transmission line of electricity
Spend the extraction characteristic quantity as failure wave-recording file；
Step 3: if cascading failure type is judged as transformer and bus, using the ratio of difference current and stalling current as
The extraction characteristic quantity of failure wave-recording file；
Step 4: combining step 2 and step 3 for transmission line of electricity and the respective extraction characteristic quantity of transformer and bus
Electric network failure diagnosis frame is established to diagnose with complex fault real-time for power grid.
Further, the recognition methods of power supply interrupted district is retouched using the adjacency matrix method of non-directed graph in the step 1
State formula are as follows:
In formula, cijIndicate that the element in adjacency matrix, A indicate the side in non-directed graph.
Further, the calculation formula of the amplitude of short circuit Suspected Degree in the step 2 are as follows:
In formula, xkThe amplitude of short circuit degree of approximation of kth route, I after expression failurekIndicate line current signal in event
The amplitude variation degree of barrier front and back electric current, I1,I2…InIndicate the respective short circuit current of n route.
Further, the calculation formula of line current signal amplitude variation degree of electric current before and after failure are as follows:
In formula, IkIndicate the amplitude variation degree of line current signal electric current before and after failure, Fkf、FkbRespectively failure is sent out
Current amplitude in the latter period before death.
Further, the calculation formula of the harmonic energy Suspected Degree in the step 2 are as follows:
In formula, wk indicates harmonic energy Suspected Degree,WkFor intermediate calculations, WkhFor the high frequency of signal k
Energy characterization, WklIt is characterized for the low frequency energy of signal k, W1,W2…WnIndicate the respective energy characterization of n route.
Further, the calculation formula of the high-frequency energy characterization of the signal k are as follows:
In formula, t is wavelet decomposition scales, DkjIndicate detail coefficients of the signal k under j-th of decomposition scale.
Further, the calculation formula of the low frequency energy characterization of the signal k are as follows:
In formula, AktIndicate similarity factor of the signal k under t-th of decomposition scale.
Further, in the step 3 difference current and stalling current ratio, formula is described are as follows:
In formula, peIndicate the ratio of difference current and stalling current, Icd=| i1-i2-...-in|, IcdIndicate difference current,
i1,i2...inIndicate each transformer or the respective electric current of bus, Izd=| i1|+|i2|+...+|in|, IzdIndicate stalling current.
Compared with prior art, the invention has the following advantages that
(1) precisely, the present invention utilizes training after the topological connection relation and power supply interrupted district for determining electric network fault for diagnosis
Neural network recognition afterwards goes out cascading failure type, is based respectively on transmission line of electricity and transformer and bus later, extracts
Failure wave-recording file characteristic amount: being directed to transmission line of electricity, the amplitude of short circuit Suspected Degree and harmonic energy changed with current amplitude
Suspected Degree indicates the feature of faulty line；For transformer and bus, indicated with the ratio of difference current and stalling current
The feature of faulty line.The detailed diagnosis for finally carrying out cascading failure model establishes fault diagnosis frame to use, and diagnosis is smart
Exactness is high.
(2) it is more to cover fault type, the present invention is covered for power grid feature including route, transformer and all bases of bus
The fault type of this power grid composition,
Detailed description of the invention
Fig. 1 is route provided by the invention-transformer fault type schematic diagram；
Fig. 2 is route provided by the invention-bus-bar fault type schematic diagram；
Fig. 3 is switch failure fault type schematic diagram in bus scheme with one and half breaker side provided by the invention；
Fig. 4 is switch failure fault type schematic diagram in a half breaker provided by the invention；
Fig. 5 is route provided by the invention-bus-bar fault type analysis model schematic；
Fig. 6 is East China electric network wiring scheme provided by the invention；
Fig. 7 is primary equipment topology connections maps after failure provided by the invention；
Fig. 8 is method flow schematic diagram of the invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiment is a part of the embodiments of the present invention, rather than whole embodiments.Based on this hair
Embodiment in bright, those of ordinary skill in the art's every other reality obtained without making creative work
Example is applied, all should belong to the scope of protection of the invention.
Embodiment
One: the topological connection relation of electric network fault
For scheming G=(V (G), E (G)), if certain two element v in V (G)i,vjIt is then non-directed graph for unordered pair.Scheme G=
(V (G), E (G)), if certain two element v in V (G)i,vjIt is then non-directed graph for ordered pair.
After element failure in power grid, relevant protective relaying device can be acted and the corresponding breaker of tripping is cut
Except fault zone, one or more power supply interrupted district is ultimately formed, so that fault element and isolated from power.And if in entire electricity
Trouble-shooting element is very time-consuming in web area, and does not have practical significance.But it if can to the identification of suspected fault element
It is limited to some or several regions, i.e. power supply interrupted district, then the diagnosis efficiency of diagnostic system can be greatly improved.
Identification for power supply interrupted district is to realize on computers, and there are commonly 2 kinds of methods: Adjacent Matrix Method be associated with square
The tactical deployment of troops.The adjacency matrix method of non-directed graph is used herein.
Shown in adjacency matrix such as formula (1).
C is the 0-1 matrix of a n × n, i.e. C=(cij)n×n∈{0,1}n×n, wherein
Two: power supply interrupted district inquiry
If breaker warning information can be uploaded correctly completely, the identification of power supply interrupted district will be very simple, however
Situations such as loss of learning easily occurs in upload procedure for scheduling information, variation.Therefore this section defines following algorithm.
The principle of passive connected subgraph inquiry is as follows:
The state of breaker changes, after figure G state is updated, using the other elements node in addition to power supply point as searching
Suo Qidian obtains the set of all connected subgraphs of figure G (V (G), E (G)) by depth-first search (DFS) inquiryIfThen claimFor inactive regions or power supply interrupted district.Wherein Ge=
{G1,G2,G3, the power supply node being expressed as in system.
Three: the cascading failure type identification based on topological connection relation
Utilize the failure classes of the cascading failure identification of the breaker failure of primary equipment topological connection relation after electric network fault
Type is mainly divided into 4 classes in FIG. 1 to FIG. 4.The topological connection relation sample for constructing 4 kinds of fault types carries out neural network
Training, forms the disaggregated model of 4 kinds of fault types.
Four: transmission line malfunction recording characteristic quantity
Shown in the amplitude variation degree such as formula (2) of line current electric current before and after failure:
In formula, IkFor the amplitude variation degree of signal electric current before and after failure, Fkf, FkbRespectively preceding the latter occurs for failure
Current amplitude in period.Shown in amplitude of short circuit Suspected Degree such as formula (3):
In formula, xkFor the amplitude of short circuit degree of approximation of kth route after failure.
Shown in harmonic energy Suspected Degree such as formula (4):
Wherein:
WkhIt is characterized for the high-frequency energy of signal k, WklFor low frequency energy characterization, t is wavelet decomposition scales.DkjExist for signal k
Detail coefficients under jth (j=1 ..., t) a decomposition scale, AktFor similarity factor of the signal k under t-th of decomposition scale.
Five: transformer or bus-bar fault recording characteristic quantity
According to the principle of transformer or bus differential protecting, when troubles inside the sample space, difference current is very big but stalling current very little,
Difference current very little but stalling current is very big when external area error, so a possibility that difference current is bigger, and equipment occurs is bigger.Structure
The difference current and stalling current for making transformer or bus current vector value are shown below:
In formula, peIndicate the ratio of difference current and stalling current, value is between 0 to 1, Icd=| i1-i2-...-in|,
IcdIndicate difference current, i1,i2...inIndicate each transformer or the respective electric current of bus, Izd=| i1|+|i2|+...+|in|,
IzdIndicate stalling current.
Do not consider CT progress of disease error, when equipment external area error, peIt is 0, so, pe=0, illustrate that equipment can not be faulty.
When equipment two sides equivalent system impedance angle is identical, when troubles inside the sample space occurs, i1,i2...inPhase angle is identical, so IcdFor each electricity
The algebraical sum of flow amplitude, IcdObtain maximum value and IzdIt is equal, peIt is 1, centainly breaks down in battery limits.So peValue
Size reflects a possibility that device fails.
Six, the detailed diagnosis of cascading failure model
The detailed diagnostic model for establishing 4 kinds of cascading failure models respectively makes identification to cascading failure and breaker failure.
By taking route-bus fault type as an example, analysis model is as shown in Figure 5.
In route-bus-bar fault type, it is possible to which failure occurs on the line, such as K1 point in figure, route both ends breaker
B1 movement excision failure, B2 breaker failure, all breakers being connected by the tripping of bus failure protection with bus, failure are cut
It removes.It is possible to break down (such as K2 point) on bus again, bus differential protecting movement due to B2 breaker failure, there is B2 tripping
Finally cut off failure.The type that breaks down on route may be single-phase fault, one breaker of tripping or multiphase event
Barrier, tripping three-phase breaker.During tripping is single-phase or three-phase breaker, it may occur however that breaker failure, by adjacent elements
Breaker fail protection movement, finally cuts off failure.
Fault diagnosis frame Θ={ route A directional element, route B directional element, phase selection element, amplitude Suspected Degree, harmonic wave
Energy Suspected Degree, bus-bar fault Suspected Degree }.Fault diagnosis frame classification results are as shown in table 1.
1 route of table-bus-bar fault type diagnostic result
Seven: simulation analysis
By taking the power grid of East China as an example, considers influencing each other between power transmission network and power distribution network, build grid simulation wiring diagram
As shown in Figure 6.It breaks down on transmission line of electricity L2, the A phase tripping of B10 breaker, by the breaker being connected with bus M3
Movement, finally cuts off failure.
The connection matrix of primary equipment comprising breaker connection relationship is as shown in table 2.
2 primary equipment connection matrix of table
After receiving scheduling system remote signalling information, after refreshing primary equipment connection matrix according to circuit breaker position remote signalling, equipment
Connection relationship topological diagram is as shown in Figure 7.Available 4 passive subgraphs are searched for by the scope of power outage to Fig. 7, are respectively: L2-
M3, M4-L8, L6, L7.Coincidence circuit-bus connection relationship subgraph has L2-M3 and M4-L8.But one in M4-L8 subgraph
Secondary device does not receive relay protection movement remote signalling, does not analyze so giving up.L2-M3 has relay protection to act remote signalling, full
Foot analysis requires.
It is as shown in table 3 to the analysis of transmission line malfunction Suspected Degree.
3 transmission line malfunction Suspected Degree of table
The diagnosis frame of cascading failure can be calculated by the above analytical calculation.Wherein the positive direction of directional element is 1,
Opposite direction is 0, and it be that 1, B phase numbers be that 2, C phase numbers is 3 that the output result A phase of phase selection element, which is numbered,.The doubtful angle value of bus-bar fault
It is 1 greater than 0.5, is 0 less than 0.5.So diagnosis frame numerical value is as follows:
Diagnose frame={ positive direction, opposite direction, A phase fault, route L2 amplitude failure Suspected Degree, route L2 energy failure
Suspected Degree, bus-bar fault Suspected Degree }, numerical value is as follows:
Θ={ 1,0,1,0.4937,0.4547,0 }.
Pass through the lookup of failure modes table 1, it can be deduced that transmission line of electricity L2 failure B10 breaker A phase failure.
In conclusion method flow of the invention is as shown in Figure 8, comprising the following steps:
Step 1: establishing faulty grids equipment connection topological relation, searched for by power supply interrupted district and determine cascading failure type；
Step 2: doubtful with amplitude of short circuit Suspected Degree and harmonic energy if cascading failure type is judged as transmission line of electricity
Spend the extraction characteristic quantity as failure wave-recording file；
Step 3: if cascading failure type is judged as transformer and bus, using the ratio of difference current and stalling current as
The extraction characteristic quantity of failure wave-recording file；
Step 4: combining step 2 and step 3 for transmission line of electricity and the respective extraction characteristic quantity of transformer and bus
Electric network failure diagnosis frame is established to diagnose with complex fault real-time for power grid.
The above description is merely a specific embodiment, but scope of protection of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or replace
It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with right
It is required that protection scope subject to.
Claims (8)
1. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion, which is characterized in that including following step
It is rapid:
Step 1: establishing faulty grids equipment connection topological relation, searched for by power supply interrupted district and determine cascading failure type；
Step 2: if cascading failure type is judged as transmission line of electricity, being made with amplitude of short circuit Suspected Degree and harmonic energy Suspected Degree
For the extraction characteristic quantity of failure wave-recording file；
Step 3: if cascading failure type is judged as transformer and bus, using the ratio of difference current and stalling current as failure
The extraction characteristic quantity of recorded wave file；
Step 4: step 2 and step 3 establish transmission line of electricity and the respective extraction characteristic quantity combination of transformer and bus
Electric network failure diagnosis frame is diagnosed with complex fault real-time for power grid.
2. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 1,
It is characterized in that, the recognition methods of power supply interrupted district uses the adjacency matrix method of non-directed graph in the step 1, describes formula
Are as follows:
In formula, cijIndicate that the element in adjacency matrix, A indicate the side in non-directed graph.
3. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 1,
It is characterized in that, the calculation formula of the amplitude of short circuit Suspected Degree in the step 2 are as follows:
In formula, xkThe amplitude of short circuit degree of approximation of kth route, I after expression failurekIndicate line current signal before failure
The amplitude variation degree of electric current afterwards, I1,I2…InIndicate the respective short circuit current of n route.
4. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 3,
It is characterized in that, the calculation formula of line current signal amplitude variation degree of electric current before and after failure are as follows:
In formula, IkIndicate the amplitude variation degree of line current signal electric current before and after failure, Fkf、FkbBefore respectively failure occurs
Current amplitude in the latter period.
5. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 1,
It is characterized in that, the calculation formula of the harmonic energy Suspected Degree in the step 2 are as follows:
In formula, wkIndicate harmonic energy Suspected Degree,WkFor intermediate calculations, WkhFor the high-frequency energy scale of signal k
Sign, WklIt is characterized for the low frequency energy of signal k, W1,W2…WnIndicate the respective energy characterization of n route.
6. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 5,
It is characterized in that, the calculation formula of the high-frequency energy characterization of the signal k are as follows:
In formula, t is wavelet decomposition scales, DkjIndicate detail coefficients of the signal k under j-th of decomposition scale.
7. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 6,
It is characterized in that, the calculation formula of the low frequency energy characterization of the signal k are as follows:
In formula, AktIndicate similarity factor of the signal k under t-th of decomposition scale.
8. a kind of complex fault diagnostic method based on power grid architecture and multisource data fusion according to claim 1,
It is characterized in that, the ratio of difference current and stalling current, describes formula in the step 3 are as follows:
In formula, peIndicate the ratio of difference current and stalling current, Icd=| i1-i2-...-in|, IcdIndicate difference current, i1,
i2...inIndicate each transformer or the respective electric current of bus, Izd=| i1|+|i2|+...+|in|, IzdIndicate stalling current.
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| CN110988520A (en) * | 2019-11-13 | 2020-04-10 | 广西电网有限责任公司 | Waveform analysis method without error in time scale |
| CN111638427A (en) * | 2020-06-03 | 2020-09-08 | 西南交通大学 | Transformer fault detection method based on nuclear capsule neuron coverage |
| CN112763846A (en) * | 2020-12-23 | 2021-05-07 | 国网河南省电力公司电力科学研究院 | Multi-data source information fusion-based intelligent power failure judgment method for distribution line |
| CN112858902A (en) * | 2021-02-02 | 2021-05-28 | 南方电网数字电网研究院有限公司 | Miniature circuit breaker monitoring method and device, computer equipment and storage medium |
| CN113570345A (en) * | 2021-08-13 | 2021-10-29 | 国网江苏省电力有限公司南通供电分公司 | Power failure range automatic identification system based on construction project circuit diagram |
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| CN111638427A (en) * | 2020-06-03 | 2020-09-08 | 西南交通大学 | Transformer fault detection method based on nuclear capsule neuron coverage |
| CN111638427B (en) * | 2020-06-03 | 2021-05-28 | 西南交通大学 | Transformer fault detection method based on nuclear capsule neuron coverage |
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| CN112858902A (en) * | 2021-02-02 | 2021-05-28 | 南方电网数字电网研究院有限公司 | Miniature circuit breaker monitoring method and device, computer equipment and storage medium |
| CN113570345A (en) * | 2021-08-13 | 2021-10-29 | 国网江苏省电力有限公司南通供电分公司 | Power failure range automatic identification system based on construction project circuit diagram |
| CN113570345B (en) * | 2021-08-13 | 2024-01-19 | 国网江苏省电力有限公司南通供电分公司 | Automatic power failure range identification system based on construction project circuit diagram |
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Application publication date: 20190723 |