CN109254225A - A kind of detection of electric network fault and faulty line recognition methods - Google Patents
A kind of detection of electric network fault and faulty line recognition methods Download PDFInfo
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- CN109254225A CN109254225A CN201810917311.2A CN201810917311A CN109254225A CN 109254225 A CN109254225 A CN 109254225A CN 201810917311 A CN201810917311 A CN 201810917311A CN 109254225 A CN109254225 A CN 109254225A
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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
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/085—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution lines, e.g. overhead
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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
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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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
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
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Abstract
The present invention provides electric network fault detection and faulty line recognition methods, comprising the following steps: obtains the topological structure and line parameter circuit value with the network system of n node, m route, and confirmation is mounted with vector measurement equipment on each node；Acquire and obtain in real time the measurement vector z and error in measurement vector v of all vector measurement equipments in power grid；It calculates and measures matrix H；According to the estimated state vector of linear weighted function the least square estimation and all nodes of the power gridThe module of every route real-time status estimation is calculated, that is, weights the mean value WMR of measurement residuals WMR and all WMRmean；Compare the weighting measurement residuals mean value WMR of two continuous time step-lengthsmean, detect whether failure occurs；If detecting failure, the smallest route of WMR is identified as faulty line, and calculates fault current according to the real-time status estimated result of this route, identifies fault type.This method can satisfy the time requirement and required precision of fault identification, have very strong applicability.
Description
Technical field
The present invention relates to smart grid securities to ensure field, and in particular to a kind of detection of electric network fault and faulty line identification
Method.
Background technique
The large-scale integrated of distributed power generation (DG) is causing operation of power networks that great change occurs.In this case,
Power grid security safeguard work is also in experience great change.In general, fault detection (including its matched relay protective plan)
And fault location is to separate research.This is because fault location needs certain calculating time, and fault detection is to the time
The requirement of delay is again harsher.In recent years, domestic and foreign scholars propose various faults detection and fault location for power grid
Method, wherein most is all based on the measurement of impedance traveling wave or vector measures realization, but rarely has scholar by fault detection and event
Barrier positioning function, which merges, to be considered and studies.And vector measurement equipment (phasor-measurement-unit, PMU) is as a kind of
The device for realizing low time delay and efficient real-time system state estimation, largely uses in power grid in recent years.Utilize electricity
Demand of the network operation business to real time monitoring can use this measurement basis facility and carry out to fault detection and fault location function
Research.
Summary of the invention
It is an object of the invention to overcome above-mentioned the deficiencies in the prior art, a kind of detection of electric network fault and faulty line are provided
Recognition methods, so that the safety guarantee of smart grid works.
To achieve the above object, the technical scheme is that
The present invention relates to a kind of detection of electric network fault and faulty line recognition methods, comprising the following steps:
1, a kind of electric network fault detection and faulty line recognition methods, which is characterized in that the described method includes:
Step 1, the topological structure and line parameter circuit value with the network system of n node, m route are obtained, and is confirmed
It is mounted with vector measurement equipment on each node；
Step 2, the measurement vector z and error in measurement vector of all vector measurement equipments in power grid are acquired and obtained in real time
v；
Step 3, it according to the relationship of state vector x and measurement vector z, calculates and measures matrix H；
Step 4, according to linear weighted function the least square estimation, the estimated state vector of all nodes of the power grid is calculated
Step 5, the module of every route real-time status SE estimation is calculated, that is, weight measurement residuals WMR and is owned
Weight the mean value WMR of measurement residuals WMRmean；
Step 6, compare the weighting measurement residuals mean value WMR of two continuous time step-lengthsmean, detect whether failure occurs；
Step 7, if detecting failure, the weighting the smallest route of measurement residuals WMR is identified as faulty line, and root
Fault current is calculated according to the state estimation result of this faulty line and identifies fault type.
In the step 2, the measurement vector z of all vector measurement equipments in power grid is acquired and obtained in real time and measures mistake
Difference vector v is specifically included:
Each node installation vector measurement equipment power grid in, measure vector z by 3m phase-to-ground voltage vector with
And 3m input current vector is constituted,
It measures vector and is expressed as z=[zV,zI]T, wherein (i=1,2 ..., m):
Assuming that error in measurement vector v is a white Gaussian noise, indicate are as follows:
P (v)~N (0, R) * MERGEFORMAT (3)
Wherein, R represents the measurement noise covariance matrix of measurement equipment accuracy.Assuming that not phase between each error in measurement
It closes, then R can be indicated are as follows:
Wherein,It is the variance of j-th of measurement.
In the step 3, according to the relationship of state vector x and measurement vector z, calculates measurement matrix H and specifically includes:
The state vector of n node three phase network under rectangular coordinate systemIt can indicate are as follows:
Wherein,
State vector x and the relationship measured between vector z can indicate are as follows:
Z=Hx+v * MERGEFORMAT (6)
Wherein, H is measurement matrix, by two subitem HVAnd HIComposition:
HVVoltage measurement is associated with state vector, and matrix interior element is 0 or 1, is derived by formula (6)
It arrives；HICurrent measurement result is related to state vector and related with the admittance matrix of power grid, calculating process is as follows:
The real and imaginary parts of power grid three-phase Injection Current can indicate are as follows:
Wherein, i and h respectively represents node, and p and l respectively represent phase, and G and B respectively represent the real part of power grid admittance matrix
And imaginary part；Therefore, H is derivedIAre as follows:
In the step 4, according to linear weighted function the least square estimation, the estimated state of all nodes of the power grid is calculated
VectorIt specifically includes:
In the case where known measurement matrix H and measurement noise covariance matrix R, gain matrix G is indicated are as follows:
G=HTR-1H \*MERGEFORMAT (11)
At this point, the estimated state vector of all nodes of the power gridIt indicates are as follows:
In the step 5, using the weighting measurement residuals WMR of every route real-time status SE estimation as module, and
Calculate the mean value WMR of all WMRmeanIt specifically includes:
The module of every route real-time status SE estimation is weighting measurement residuals WMR:
Wherein, j is any one route in power grid, and
At this point it is possible to calculate the mean value WMR of all WMRmeanAre as follows:
In the step 6, compare the weighting measurement residuals mean value WMR of two continuous time step-lengthsmean, whether detection failure
It specifically includes:
By comparing the weighting measurement residuals mean value WMR between two continuous time step-lengthsmean|k-1With WMRmean|kBetween
Relationship judge whether failure occurs；If not having failure in power grid, the WMR of all routes is very close in continuous time
WMR in step-lengthmeanToo big change will not occur；If there are line fault in power grid, its in power grid in addition to faulty line
The real-time status estimation (SEs) of his m-1 route can converge in the solution far from time of day, and have high WMR characteristic, can lead
Cause WMRmeanUnexpected increase.
In the step 7, fault current is calculated according to the state estimation result of this faulty line and identifies fault type
Specifically:
Electric network fault is in analysis with an increased dummy node simulation suddenly, it is believed that the node is located at true in power grid
Solid line road and absorption fault current；If detecting j-th strip line failure, (j=1,2 ... m), it is believed that the increased virtual section
Point is located among j-th strip route, utilizes the real-time status estimated result and network admittance matrix of j-th strip route at this time, calculates
The Injection Current I of each node of power grid when failurejIt is as follows:
Ij=YjEj \*MERGEFORMAT (15)
Wherein, YfTo increase the admittance matrix after dummy node；EjKnot is estimated for the real-time status that j-th strip route returns
Fruit, at this time, it is believed that the Injection Current at dummy nodeFor fault current, phase is fault phase, to analyze failure
Type
Compared with prior art, the present invention the beneficial effect is that:
This method senses infrastructure using the PMU being equipped at each node, by process fault detection and fault location mistake
Journey combines, under the premise of guaranteeing fault localization accuracy, the strict control time of fault identification, and this method is to different nets
Situations such as network type, fault type, fault impedance, all has very strong applicability.Electric network fault detection and event proposed by the present invention
Hinder identification of lines method, provides strong support for the safety guarantee work of smart grid.
Detailed description of the invention
It is as shown in Figure 1 a kind of flow chart of electric network fault detection and faulty line recognition methods provided by the invention；
It is illustrated in figure 2 emulation 18 node 10kV network system network topological structures used.
Specific embodiment
In order to deepen the understanding of the present invention, present invention will be further explained below with reference to the attached drawings and examples, the implementation
Example for explaining only the invention, does not constitute protection scope of the present invention and limits.
As shown in Figure 1, the present invention provides a kind of detection of electric network fault and faulty line recognition methods, following step is specifically included
It is rapid:
Step 1, the topological structure and line parameter circuit value with the network system of n node, m route are obtained, and is confirmed
It is mounted with vector measurement equipment (phasor-measurement-unit, PMU) on each node.
This is sentenced for 10kV three-phase electricity network that is Dutch and being runed by Alliander, European Union project C-DAX's
Under background, which is being equipped with PMU.The topological structure of the network is as shown in Fig. 2, share 18 nodes, the zero sequence of route
It is as shown in table 1 with positive sequence electric parameter.
1 18 node 10kV three-phase electricity network line parameter of table
The electric network models in SimPowerSystem, and uses Opal-RTRTS operation emulation.All routes are equal
Using equivalent PI circuit modeling, upstream power grid has the short-circuit power of 1000MVA, and uses short-circuit impedance ZSC(assuming that resistance ratio
RSC/ZSC=1/10) it models.The mode of connection of transformer can be Yg-Yg or Yg-Y according to the specific requirement of different scenes, bear
Lotus is impedance star-like connection.
In order to verify the validity and universality of the method for the invention, the group of following several fault conditions is directed in emulation
Conjunction is verified:
1) fault impedance lower (1 Ω), fault impedance higher (100 Ω) and fault impedance are very high (1000 Ω)；
2) symmetric fault situation (three-phase fault) and unbalanced fault situation (phase or phase to phase fault)；
3) position occurs for failure in route L4,5、L9,10、L13,161/2 at the case where；
4) power grid ground state and earth-free state.
Step 2: acquiring and obtain the measurement vector z of all vector measurement equipments (PMUs) in power grid in real time and measure mistake
Difference vector v.
In the power grid of each node installation vector measurement equipment (PUMs), vector z is measured by 3m phase-to-ground voltage
Vector and 3m input current vector are constituted,Assuming that the sample frequency of all PMU is 10kHz, report
Announcement rate is 50 frame per second.
It measures vector and is expressed as z=[zV,zI]T, wherein (i=1,2 ..., m):
Assuming that error in measurement vector v is a white Gaussian noise, indicate are as follows:
P (v)~N (0, R) * MERGEFORMAT (3)
Wherein, R represents the measurement noise covariance matrix of measurement equipment accuracy.Assuming that not phase between each error in measurement
It closes, then R can be indicated are as follows:
Wherein,It is the variance of j-th of measurement.
Assume that the error in measurement vector of all PMU is all the same in emulation, the node voltage/Injection Current width measured
The standard deviation of value and phase is provided that
Step 3: according to the relationship of state vector x and measurement vector z, calculating and measure matrix H.
The state vector of n node three phase network under rectangular coordinate systemIt can indicate are as follows:
Wherein,
State vector x and the relationship measured between vector z can indicate are as follows:
Z=Hx+v * MERGEFORMAT (6)
Wherein, H is measurement matrix, by two subitem HVAnd HIComposition:
HVVoltage measurement is associated with state vector, and matrix interior element is 0 or 1, can be derived by formula (6)
It obtains；HICurrent measurement result is related to state vector and related with the admittance matrix of power grid, calculating process is as follows.
The real and imaginary parts of power grid three-phase Injection Current can indicate are as follows:
Wherein, i and h respectively represents node, and p and l respectively represent phase, and G and B respectively represent the real part of power grid admittance matrix
And imaginary part.Therefore, H is derivedIAre as follows:
Step 4: according to linear weighted function the least square estimation, calculating the estimated state vector of all nodes of the power grid
In the case where known measurement matrix H and measurement noise covariance matrix R, gain matrix G is indicated are as follows:
G=HTR-1H\*MERGEFORMAT (11)
At this point, the estimated state vector of all nodes of the power gridIt indicates are as follows:
Step 5: being measured with the weighting of every route real-time status estimation (real-time state estimator, SE)
Residual error (weighted measurement residuals, WMR) is used as module, and calculates the mean value of all WMR
WMRmean。
The module of every route real-time status estimation (SE) is weighting measurement residuals (WMR):
Wherein, j is any one route in power grid, and
At this point it is possible to calculate the mean value WMR of all WMRmeanAre as follows:
Step 6: comparing the weighting measurement residuals mean value WMR of two continuous time step-lengthsmean, detect whether failure occurs.
By comparing the weighting measurement residuals mean value WMR between two continuous time step-lengthsmean|k-1With WMRmean|kBetween
Relationship judges whether failure occurs.If not having failure in power grid, the WMR of all routes is very close in consecutive hours spacer step
WMR in longmeanToo big change will not occur；If there are line fault in power grid, other in power grid in addition to faulty line
The real-time status estimation (SEs) of m-1 route can converge in the solution far from time of day, and have high WMR characteristic, will lead to
WMRmeanUnexpected increase.
Step 7: if detecting failure, i.e. WMRmean|k> > WMRmean|k-1, then it is by the smallest identification of lines of WMR
Faulty line.Electric network fault can use an increased dummy node simulation suddenly in analysis, it is believed that the node is located at power grid
In interior real line and absorb fault current.Therefore, if (j=1,2 ... m), it is believed that should for detection j-th strip line failure
Increased dummy node is located among j-th strip route.It is led at this time using the real-time status estimated result and network of j-th strip route
Receive matrix, the Injection Current I of each node of power grid when calculating failurejIt is as follows:
Ij=YjEj \*MERGEFORMAT (15)
Wherein, YfTo increase the admittance matrix after dummy node；EjKnot is estimated for the real-time status that j-th strip route returns
Fruit.At this time, it is believed that the Injection Current at dummy nodeFor fault current, phase is fault phase, consequently facilitating point
Analyse fault type.
So far, electric network fault detection and faulty line recognition methods are completed.
Different fault condition example combinations the result shows that, this method is estimated by comparing all route real-time status
(SE) weighting measurement residuals can monitor the presence of failure and identify faulty line, and time-consuming is about 102~112ms.Cause
This, the mentioned method of the present invention can correctly identify faulty line, connect but regardless of line neutral, fault type, fault impedance
With abort situation how.
Claims (7)
1. a kind of electric network fault detection and faulty line recognition methods, which is characterized in that the described method includes:
Step 1, the topological structure and line parameter circuit value with the network system of n node, m route are obtained, and confirmation is every
Vector measurement equipment is mounted on a node；
Step 2, the measurement vector z and error in measurement vector v of all vector measurement equipments in power grid are acquired and obtained in real time；
Step 3, it according to the relationship of state vector x and measurement vector z, calculates and measures matrix H；
Step 4, according to linear weighted function the least square estimation, the estimated state vector of all nodes of the power grid is calculated
Step 5, the module of every route real-time status SE estimation is calculated, i.e. weighting measurement residuals WMR and all weightings
The mean value WMR of measurement residuals WMRmean；
Step 6, compare the weighting measurement residuals mean value WMR of two continuous time step-lengthsmean, detect whether failure occurs；
Step 7, if detecting failure, the weighting the smallest route of measurement residuals WMR is identified as faulty line, and according to this
The state estimation result of faulty line calculates fault current and identifies fault type.
2. such as the detection of claim 1 electric network fault and faulty line recognition methods, which is characterized in that in the step 2, adopt in real time
Collect and obtain the measurement vector z of all vector measurement equipments and error in measurement vector v in power grid and specifically includes:
In the power grid of each node installation vector measurement equipment, vector z is measured by 3m phase-to-ground voltage vector and 3m
A input current vector is constituted,
It measures vector and is expressed as z=[zV,zI]T, wherein (i=1,2 ..., m):
Assuming that error in measurement vector v is a white Gaussian noise, indicate are as follows:
P (v)~N (0, R) * MERGEFORMAT (3)
Wherein, R represents the measurement noise covariance matrix of measurement equipment accuracy；Assuming that uncorrelated between each error in measurement, then R
It can indicate are as follows:
Wherein,It is the variance of j-th of measurement.
3. such as the detection of claim 1 electric network fault and faulty line recognition methods, which is characterized in that in the step 3, according to shape
State vector x and the relationship for measuring vector z calculate measurement matrix H and specifically include:
The state vector of n node three phase network under rectangular coordinate systemIt can indicate are as follows:
Wherein,
State vector x and the relationship measured between vector z are expressed as:
Z=Hx+v * MERGEFORMAT (6)
Wherein, H is measurement matrix, by two subitem HVAnd HIComposition:
HVVoltage measurement is associated with state vector, and matrix interior element is 0 or 1, is derived by by formula (6)；HI
Current measurement result is related to state vector and related with the admittance matrix of power grid, calculating process is as follows:
The real and imaginary parts of power grid three-phase Injection Current can indicate are as follows:
Wherein, i and h respectively represents node, and p and l respectively represent phase, and G and B respectively represent the real part and void of power grid admittance matrix
Portion；Therefore, H is derivedIAre as follows:
4. such as the detection of claim 1 electric network fault and faulty line recognition methods, which is characterized in that in the step 4, according to line
Property weighted least-squares state estimation, calculates the estimated state vector of all nodes of the power gridIt specifically includes:
In the case where known measurement matrix H and measurement noise covariance matrix R, gain matrix G is indicated are as follows:
G=HTR-1H\*MERGEFORMAT(11)
At this point, the estimated state vector of all nodes of the power gridIt indicates are as follows:
5. such as the detection of claim 1 electric network fault and faulty line recognition methods, which is characterized in that in the step 5, with every
The weighting measurement residuals WMR of route real-time status SE estimation calculates the mean value WMR of all WMR as modulemeanSpecifically
Include:
The module of every route real-time status SE estimation is weighting measurement residuals WMR:
Wherein, j is any one route in power grid, and
At this point, calculating the mean value WMR of all WMRmeanAre as follows:
6. such as the detection of claim 1 electric network fault and faulty line recognition methods, which is characterized in that in the step 6, compare two
The weighting measurement residuals mean value WMR of a continuous time step-lengthmean, detect whether failure specifically includes:
By comparing the weighting measurement residuals mean value WMR between two continuous time step-lengthsmean|k-1With WMRmean|kBetween pass
System is to judge whether failure occurs；If not having failure in power grid, the WMR of all routes is very close in continuous time step-length
Interior WMRmeanToo big change will not occur；If other m-1 there are line fault in power grid, in power grid in addition to faulty line
The real-time status estimation SEs of route can be converged in the solution far from time of day, and have high WMR characteristic, will lead to
WMRmeanUnexpected increase.
7. such as the detection of claim 1 electric network fault and faulty line recognition methods, which is characterized in that in the step 7, according to this
The state estimation result of faulty line calculates fault current and identifies fault type specifically:
Electric network fault is in analysis with an increased dummy node simulation suddenly, it is believed that the node is located at the true line in power grid
Road and absorption fault current；If detecting j-th strip line failure, (j=1,2 ... m), it is believed that the increased dummy node position
Among j-th strip route, the real-time status estimated result and network admittance matrix of j-th strip route are utilized at this time, calculate failure
When each node of power grid Injection Current IjIt is as follows:
Ij=YjEj\*MERGEFORMAT(15)
Wherein, YfTo increase the admittance matrix after dummy node；EjFor j-th strip route return real-time status estimated result, this
When, it is believed that the Injection Current at dummy nodeFor fault current, phase is fault phase, to analyze fault type.
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Application publication date: 20190122 |