CN104655991B - Electric power system fault data matching method based on Singularity detection combinational algorithm - Google Patents
Electric power system fault data matching method based on Singularity detection combinational algorithm Download PDFInfo
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Abstract
The present invention provides a kind of electric power system fault data matching method based on Singularity detection combinational algorithm, it is included in each one group of the fault data protected and extract certain circuit two ends in the fault recorder data storehouse in letter system at random, the corresponding failure starting point in two ends is calculated respectively using Singularity detection combinational algorithm, two ends failure starting point according to being calculated in step 2 asks for related criteria parameter, and judge whether two ends fault data matches according to triple criterions of Data Matching, including carrying out Fault Phase Selection with Sudden Changing Rate electric current phase selection method respectively to two ends, judge whether the corresponding fault type of two end datas matches；Judge whether two ends load current matches according to load current criterion if matching, judge whether two end datas match using switching angle criterion if matching, matching then illustrates that triple criterion result of determination are matched, then final to judge two ends Data Matching, otherwise two end datas are mismatched.
Description
Technical field
It is more particularly to a kind of based on Singularity detection combinational algorithm the present invention relates to electric power system fault positioning field
Electric power system fault data matching method.
Background technology
Electric power system fault data contain abundant information resources, to make it be fully used, and current people are with original
Based on some fault information processing systems, maintenance data digging technology develops protection equipment fault information managing and is with analysis
System (referred to as " protects letter system ").Protect letter system and read fault massage substation protection device by GPS precision time service system synchronizations, record
The important informations such as wave apparatus, complete the functions such as calculating, analysis, drawing, information output, provide and determine with relay protection personnel for operation
Plan information.
Fault location is to protect a critical function of letter system.At present, in transmission open acess technology, both-end is surveyed
Away from due to making full use of fault message, have the advantages that range accuracy is high, simple to operate, practical, in power system
To extensive use.The fault data that the both-end distance measuring module protected in letter system is utilized is the electricity of faulty line two ends homogeneous failure
Amount is so-called matched data, and the data of magnanimity are stored in fault recorder data storehouse, therefore must be right before both-end distance measuring
Fault data is screened so that it is mutually matched.Generally, due to there is GPS precision time services system to ensure data syn-chronization
Property, markers identical fault data is matched data.But in practice, external interference may cause GPS precision time service systems
Produce error, although there is scholar to propose that gps clock is monitored on-line and corrected using High Precision Crystal Oscillator, but further consider
The error introduced to factors such as transformer phase shift, hardware delay and sample rate difference, the matched data markers protected in letter system
It is not exactly the same.Therefore, when continuity failure occurs in circuit, when each time fault data markers is close, enter only according to markers
Row Data Matching may cause range finder module to read corrupt data, then cause fault location to fail.Therefore, study a kind of new
Fault data matching process causes both-end distance measuring module no longer solely to rely on GPS precision time services system when carrying out data screening
System, tool is of great significance.
The content of the invention
The present invention mainly solves the technical problem that existing method is present, and designs a kind of combined based on Singularity detection and calculates
The electric power system fault data matching method of method.
The technical scheme that the present invention is provided is a kind of electric power system fault data based on Singularity detection combinational algorithm
Method of completing the square, comprises the following steps,
Step 1: obtaining fault data, it is included in protect in the fault recorder data storehouse in letter system and extracts certain line at random
Each one group of the fault data at road two ends, note circuit one end is m ends, and the other end is n ends；
Step 2: the corresponding failure starting point in two ends is calculated respectively using Singularity detection combinational algorithm, including to circuit
Two ends perform following sub-step respectively,
Step A1, the fault data group of certain the circuit one end extracted based on step one, generate baseband signal sequence, realize
Mode is to carry out phase-model transformation to three-phase current with K conversion：
Wherein, ia、ib、icFor three-phase current, i0、i1、i2For corresponding three kinds of mold components, choose a kind of mold component and be used as base
This signal, generates baseband signal sequence；
Step A2, with Bayesian Classification Arithmetic baseband signal sequence obtained by step A1 is classified, find out suspicious dash forward
Height；
Step A3, the Sudden Changing Rate electric current for obtaining baseband signal sequence obtained by step A1, are calculated with Sudden Changing Rate current algorithm
Go out current break point ns0；
Step A4, determine failure starting point with Singularity detection combinational algorithm, including with n obtained by step A3s0On the basis of structure
Make time window [ns0-Δn,ns0], wherein Δ n is default window width, using time window from by suspicious catastrophe point obtained by step A2
The starting point that is out of order is screened, screening mode is as follows,
1) when the suspicious catastrophe point of only one of which in time window, failure starting point nsFor this suspicious catastrophe point；
2) when having the suspicious catastrophe point of two and the above in time window, failure starting point nsIt is average for these suspicious catastrophe points
After round；
3) when there is no suspicious catastrophe point in time window, failure starting point nsThe current break point n obtained by step A3s0；
Step 3: related criteria parameter is asked for according to the two ends failure starting point calculated in step 2, and according to data
The triple criterions matched somebody with somebody judge whether two ends fault data matches, including following sub-step：
Step B1, with the corresponding failure starting point n in two endssOn the basis of, calculate two end datas respectively with fourier algorithm each
The normal and fault current and voltage phasor of phase；
Step B2, Fault Phase Selection is carried out with Sudden Changing Rate electric current phase selection method respectively to two ends, judge that two end datas are corresponding
Whether fault type matches；
If step B3, step B2 judged results mismatch for the fault type of two end datas, two end datas are directly judged
Mismatch, terminate flow；M ends electric current is calculated if matchingWithIt is as follows,
Two ends phase on the basis of A phases, calculates with fourier algorithm and pushes away one before the failure starting point at m ends obtained by step 2
The electric current phasor of cycle, obtains m ends electric currentCalculated with fourier algorithm and push away one before the failure starting point at n ends obtained by step 2
The electric current phasor and voltage phasor of individual cycle, respectively obtain n ends electric currentWith n terminal voltages
Again with circuit distributed parameter model by n ends electric currentWith n terminal voltagesCalculate corresponding m ends electric current
Wherein, γ and ZcThe respectively propagation constant of circuit and characteristic impedance, L is line length；
Step B4, according to load current criterion judge whether two ends load current matches, if including | ρ -1 |≤λ, load
Currents match；Otherwise, load current is mismatched, wherein, parameterλ is default threshold values；
If step B5, step B4 judged results mismatch for two ends load current, judge that two end datas are mismatched, terminate
Flow；If matching, judges whether two end datas match, if including parameter using switching angle criterion
Then switching angle is matched, and otherwise switching angle is mismatched, wherein,For default threshold values；
If step B6, step B5 judged results match for switching angle, illustrate that triple criterion result of determination are matched, then finally
Judge two ends Data Matching, otherwise two end datas are mismatched.
Moreover, the realization that step A3 finds current break point with Sudden Changing Rate current algorithm is as follows：
A) Sudden Changing Rate electric current Δ i (k) is calculated according to formula Δ i (k)=i (k)-i (k-N), wherein N is fault wave recording device
The sampling number of a cycle, i (k) is electric current at baseband signal i sampled point k；
B) current break point is determined according to detection criteria, criterion is as follows,
Wherein, parameterA=ψ (n) | | and ψ (n) | ＞ ξ, k≤n ＜ k+ α }, α is parameter preset with β, ξ, full
First k value of the above-mentioned criterion of foot is the corresponding catastrophe point of detected signal.
The present invention goes out a kind of Singularity detection combinational algorithm for electric power system fault design data, proposes on this basis
Triple criterions of Data Matching are carried out in fault recorder data storehouse, using triple criterions circuit two ends number of faults are effectively judged
According to whether belonging to whether homogeneous failure, i.e. data match, so as to provide base for effective progress of two ends of electric transmission line fault localization
This data ensure.Therefore, the invention has the advantages that：Event is carried out with the failure starting-tool point method based on jump-value of current
Hinder Data Matching, result of determination reliability is high, real-time, simple and practical, can be the both-end distance measuring module in guarantor's letter system
One kind is provided than simple by the more structurally sound electric power system fault data matching method of GPS precision time services progress markers matching.
Brief description of the drawings
Fig. 1 is the both end power supplying system circuit diagram that the embodiment of the present invention is used to emulate.
Fig. 2 is the electric power system fault Data Matching decision flowchart of the embodiment of the present invention.
Fig. 3 is the Fault Phase Selection flow chart of the embodiment of the present invention.
Embodiment
Below by embodiment and with reference to accompanying drawing, technical scheme is described in further detail.
Referring to Fig. 2, it is as follows that embodiments of the invention include step：
Step 1: the step of obtaining electric power system fault data：It is random in the fault recorder data storehouse in letter system is protected
Extract each one group of the fault data at certain circuit two ends.
Referring to Fig. 1, circuit one end (left end) is m ends, and the other end (right-hand member) is n ends, Em、EnAnd Zm、ZnM ends are represented respectively
Voltage and impedance with n ends power supply, L are line length, and d is the fault distance at m ends.Embodiment is divided in fault recorder data storehouse
Each one group of the fault data of faulty line m sides and n sides is not randomly selected.
Step 2: the step of detection failure starting point：Two end data phases are calculated respectively using Singularity detection combinational algorithm
The failure starting point answered, asks for related criteria parameter and makees corresponding prepare when carrying out fault data matching with triple criterions after being.
The step of embodiment two, which specifically includes, is based respectively on the following sub-step of corresponding failure data execution to circuit two ends：
Step A1, the fault data group of certain the circuit one end extracted based on step one, generate baseband signal sequence, as
Sequence to be detected, implementation is to carry out phase-model transformation to three-phase current with K conversion：
Wherein, ia、ib、icFor three-phase current, i0、i1、i2For corresponding three kinds of mold components, when it is implemented, can select
Any of which mold component carries out subsequent analysis.Embodiment chooses mold component i1=ia+2ib-3icAs baseband signal, base is generated
This signal sequence, carries out analysis and calculating hereinafter.
Step A2, with Bayesian Classification Arithmetic baseband signal sequence obtained by step A1 is classified, found out " suspicious to dash forward
Height ".
Step A3, the Sudden Changing Rate electric current for obtaining baseband signal sequence obtained by step A1, are calculated with Sudden Changing Rate current algorithm
Go out current break point ns0。
Step A4, with Singularity detection combinational algorithm determine failure starting point.
The step A4 of embodiment is with n obtained by step A3s0On the basis of build time window [ns0-Δn,ns0], wherein Δ n is pre-
If window width, those skilled in the art can voluntarily preset value during specific implementation.Using time window from by step A2 draw " can
The starting point that is out of order is screened in doubtful catastrophe point ".Screening scheme is：
1) when only one of which " suspicious catastrophe point " in time window,Failure starting point nsAs this " suspicious catastrophe point "；
2) when there is " the suspicious catastrophe point " of two and the above in time window,Failure starting point nsFor these " suspicious catastrophe points "
Rounded after average；
3) when there is no " suspicious catastrophe point " in time window, failure starting point nsThe current break point n obtained by step A3s0, ns
=ns0。
When it is implemented, the Bayesian Classification Arithmetic that step A2 is used is referred to：Liu Mige, the small refined of Lee is determined based on Bayes
Inflection point detection [J] computer applications of plan, 2013,01:230-232. there is provided in embodiment for the sake of ease of implementation
Step A2 finds being implemented as follows for " the suspicious catastrophe point " in baseband signal sequence with Bayesian Classification Arithmetic：
A) element in baseband signal sequence is divided into two classes：Definition mutation point set ω1, prior probability is P (ω1)；It is non-prominent
Become point set ω2, prior probability is P (ω2)；
B) baseband signal sequence pre-process obtaining sequence { z (k) }.
The derivative of current x (k) at each sampled point k of baseband signal sequence is obtained first：
Wherein, i1(k) it is baseband signal i1Sampled point k at electric current.
Sudden Changing Rate ys (k) of the x (k) at each sampled point k is obtained again：
Y (k)=[x (k)-x (k+1)]2
Finally y (k) is normalized and obtains z (k)：
Wherein, maxy (k), miny (k) are respectively the maximum and least member in sequence { y (k) }, and T is neighbouring sample point
Between sampling interval, parameter δ is the positive number of numerical value very little, and those skilled in the art can voluntarily parameter preset δ during specific implementation
Value.
C) to class conditional probability P (z (k) | ω1) and P (z (k) | ω2) make following estimation：
Wherein, Γ is the sum of the element number, i.e. sampled point of sequence { z (k) }, 1≤k≤Γ；Parameter χ is just, specifically
During implementation those skilled in the art can voluntarily parameter preset χ value；For class conditional probability P (z (k) | ω1)
Estimate,For class conditional probability P (z (k) | ω2) estimate.
D) principle of classification
Calculate classification error rate P (e)
Wherein, R1For the corresponding data area of catastrophe point, R in sequence { z (k) }2For not mutated point correspondence in sequence { z (k) }
Data area, P (x ∈ R1,x∈ω2) represent region R1In data judging be not mutated point probability, P (x ∈ R2,x∈
ω1) represent region R2In data judging be catastrophe point probability, P (ω2)P2(e) it by Singularity detection is not mutated point to be
The probability of (missing inspection), P (ω1)P1(e) it is that not mutated point is detected as to the probability of catastrophe point (flase drop), prior probability P (ω1) and P
(ω2) it is constant (unknown).Calculate inference process and can be found in Bayesian Classification Arithmetic pertinent literature.
In order in P2(e)=ε when cause P1(e) it is minimum, the Neyman-Pearson in Bayesian decision theory can be used accurate
Then classified.Parameter ε is the positive number of a very little, during specific implementation those skilled in the art can voluntarily parameter preset ε value.
E) " suspicious catastrophe point " is determined
According to Neyman-Pearson criterions, have：
WhereinFor region R1A certain subregion.
By element(1≤k≤N, N are the sampling number of a cycle) arranges according to order from small to large
Row obtain sequenceThen new sequence { S (k) }, order wherein element are constructedRoot
According to inequality S (k*)≤ε ＜ S (k*+ 1) the corresponding sequence number k of element for meeting inequality is obtained*, then obtain the value of parameter μ.
Finally according to criterionThenSignal sampling point classification is carried out, wherein gathering
ω1In element be referred to as " suspicious catastrophe point ".
For the sake of ease of implementation current break point is found there is provided step A3 in embodiment with Sudden Changing Rate current algorithm
Be implemented as follows：
A) Sudden Changing Rate electric current Δ i (k) is calculated according to formula Δ i (k)=i (k)-i (k-N)：
Wherein, i (k) is electric current at baseband signal i sampled point k.
Embodiment is according to formula Δ i1(k)=i1(k)-i1(k-N) Sudden Changing Rate electric current Δ i is calculated1(k), wherein N is failure
The sampling number of wave recording device a cycle；
B) current break point is determined according to detection criteria, criterion is as follows：
Wherein, parameterA=ψ (n) | | and ψ (n) | ＞ ξ, k≤n ＜ k+ α }, card (A) is represented in set A
Element number.Parameter alpha can be preset with β, and specific set can be relevant with the sampling number N of a cycle, general desirable(capping when N is larger, removed the limit when smaller).Meet first k value of above-mentioned criterion i.e.
For the corresponding catastrophe point of detected signal.During specific implementation those skilled in the art can voluntarily parameter preset ξ value.
The m ends and n ends of circuit are performed after step A1~A4 respectively, corresponding failure starting point is obtained.
Step 3: fault data matching judges：Two ends corresponding failure starting point according to being calculated in previous step asks for phase
Close criteria parameter and judge whether two ends fault data matches according to triple criterions of Data Matching.
The triple criterion designs of the present invention are as follows：
The step of embodiment three, specifically includes following sub-step：
Step B1, with the corresponding failure starting point n in two endssOn the basis of, calculate two end datas respectively with fourier algorithm each
The normal and fault current and voltage phasor of phase.
Step B2, Fault Phase Selection is carried out with Sudden Changing Rate electric current phase selection method respectively to two ends, judge that two end datas are corresponding
Whether fault type matches, during this is fault type criterion, i.e. subsequent step, if two ends Fault Phase Selection result is different, directly
Connect two end datas of judgement to mismatch, terminate flow；If two ends Fault Phase Selection result is identical, i.e., two ends fault type is matched, then must
Make further judgement with load current criterion and switching angle criterion.Referred to when it is implemented, Fault Phase Selection is realized：Yang Qi
Inferior micro computers relay protection basis [M] Beijing：China Electric Power Publishing House, 2004.
The phase selection flow that embodiment is carried out to circuit either end is as shown in Figure 3.In figure,Respectively three-phase
Sudden Changing Rate electric current.
The normal and fault current and voltage phasor of each phase of this end data, calculate three kinds of phases first according to obtained by step B1
The Sudden Changing Rate of difference between currentThen carry out correlation ratio compared with judgement：
WhenThen judgeWhether set up,
IfIt is invalid then to enter judgement operation X；
IfEstablishment is then determined whetherWhether set up, event is judged if setting up
Hinder and be grounded for A phases, enter if invalid and judge operation X.
It is described to judge operation X, including first determine whetherWhether set up, ifSet up,
Then determine whetherWhether set up, judge that failure, as AB line to line fault, is otherwise determined as AB two if setting up
Phase short circuit grounding；IfIt is invalid, equally determine whetherWhether set up, if setting up
Failure is judged as AC line to line fault, is otherwise determined as that AC line to line fault is grounded.
WhenOrWhen
Determination step withWhen it is similar, the present invention it will not go into details, in Fig. 3 omit.
If step B3, step B2 judged results mismatch for the fault type of two end datas, two end datas are directly judged
Mismatch, terminate flow；If two ends fault type is matched, calculated according to the m end data failures starting point detected in step 2
M ends electric currentThe m ends electric current calculated with the n end data failures starting point detected according to step 2Including using line
Road distributed parameter model calculates that offside (is set to m ends, with subscript m table by the electricity (being set to n ends, represent with subscript n) of circuit side
Show) electric current
Two ends phase on the basis of A phases, with fourier algorithm calculate by detection Lai failure starting point ns1(m ends are corresponding
Failure starting point ns)、ns2(the corresponding failure starting point n in n endss) before push away (the i.e. sampled point n of a cycles1- N and ns2- N is corresponding) electricity
Stream and voltage phasor, including the electric current that a cycle is pushed away before the failure starting point at m ends obtained by step 2 is calculated with fourier algorithm
Phasor, obtains m ends electric currentThe electricity that a cycle is pushed away before the failure starting point at n ends obtained by step 2 is calculated with fourier algorithm
Phasor and voltage phasor are flowed, n ends electric current is respectively obtainedWith n terminal voltagesAgain with circuit distributed parameter model by n ends number
It is estimated that corresponding m ends electric current
Wherein, γ and ZcThe respectively propagation constant of circuit and characteristic impedance, L is line length.
Step B4, according to load current criterion judge whether two ends load current matches.Load current criterion is：If | ρ -1
|≤λ, then load current match, otherwise load current mismatch.Wherein, parameterλ is threshold values, Im、I′mIt isWith
Virtual value.During specific implementation those skilled in the art can voluntarily pre-set threshold value λ value.
If step B5, step B4 judged results mismatch for two ends load current, judge that two end datas are mismatched, terminate
Flow；If two ends load current is matched, judge whether two end datas match using switching angle criterion.Switching angle criterion is：If
ParameterThen switching angle is matched, and otherwise switching angle is mismatched.Wherein,For threshold values, during specific implementation
Those skilled in the art can voluntarily pre-set threshold valueValue.
If step B6, step B5 judged results match for switching angle, illustrate that triple criterion result of determination are matched, then most
Two ends Data Matching is judged eventually, it is otherwise final still to judge that two end datas are mismatched.
Specific embodiment described herein is only to spirit explanation for example of the invention.Technology neck belonging to of the invention
The technical staff in domain can be made various modifications or supplement to described specific embodiment or be replaced using similar mode
Generation, but without departing from the spiritual of the present invention or surmount scope defined in appended claims.
Claims (2)
1. a kind of electric power system fault data matching method based on Singularity detection combinational algorithm, it is characterised in that：Including with
Lower step,
Step 1: obtaining fault data, it is included in protect in the fault recorder data storehouse in letter system and extracts certain circuit two at random
Each one group of the fault data at end, note circuit one end is m ends, and the other end is n ends；
Step 2: the corresponding failure starting point in two ends is calculated respectively using Singularity detection combinational algorithm, including to the two of circuit
End performs following sub-step respectively,
Step A1, the fault data group of certain the circuit one end extracted based on step one, generate baseband signal sequence, implementation
To carry out phase-model transformation to three-phase current with K conversion：
Wherein, ia、ib、icFor three-phase current, i0、i1、i2For corresponding three kinds of mold components, a kind of mold component is chosen as basic letter
Number, generate baseband signal sequence；
Step A2, with Bayesian Classification Arithmetic baseband signal sequence obtained by step A1 is classified, find out suspicious catastrophe point；
Step A3, the Sudden Changing Rate electric current for obtaining baseband signal sequence obtained by step A1, electricity is calculated with Sudden Changing Rate current algorithm
Flow catastrophe point ns0；
Step A4, determine failure starting point with Singularity detection combinational algorithm, including with n obtained by step A3s0On the basis of when constructing
Between window [ns0-Δn,ns0], wherein Δ n is default window width, is screened using time window from by suspicious catastrophe point obtained by step A2
Be out of order starting point, and screening mode is as follows,
1) when the suspicious catastrophe point of only one of which in time window, failure starting point nsFor this suspicious catastrophe point；
2) when having the suspicious catastrophe point of two and the above in time window, failure starting point nsTaken after being averaged for these suspicious catastrophe points
It is whole；
3) when there is no suspicious catastrophe point in time window, failure starting point nsThe current break point n obtained by step A3s0；
Step 3: related criteria parameter is asked for according to the two ends failure starting point calculated in step 2, and according to Data Matching
Triple criterions judge whether two ends fault data matches, including following sub-step：
Step B1, with the corresponding failure starting point n in two endssOn the basis of, calculating each phase of two end datas respectively with fourier algorithm just
Often with fault current and voltage phasor；
Step B2, according to step B1 acquired results, Fault Phase Selection is carried out with Sudden Changing Rate electric current phase selection method respectively to two ends, judged
Whether the corresponding fault type of two end datas matches；
If step B3, step B2 judged results mismatch for the fault type of two end datas, directly two end datas of judgement are not
Match somebody with somebody, terminate flow；M ends electric current is calculated if matchingWithIt is as follows,
Two ends phase on the basis of A phases, calculates with fourier algorithm and pushes away a cycle before the failure starting point at m ends obtained by step 2
Electric current phasor, obtain m ends electric currentCalculated with fourier algorithm and push away a week before the failure starting point at n ends obtained by step 2
The electric current phasor and voltage phasor of ripple, respectively obtain n ends electric currentWith n terminal voltages
Again with circuit distributed parameter model by n ends electric currentWith n terminal voltagesCalculate corresponding m ends electric current
Wherein, γ and ZcThe respectively propagation constant of circuit and characteristic impedance, L is line length；
Step B4, according to load current criterion judge whether two ends load current matches, if including | ρ -1 |≤λ, load current
Matching；Otherwise, load current is mismatched, wherein, parameterλ is default threshold values；
If step B5, step B4 judged results mismatch for two ends load current, judge that two end datas are mismatched, terminate stream
Journey；If matching, judges whether two end datas match, if including parameter using switching angle criterionThen
Switching angle is matched, and otherwise switching angle is mismatched, wherein,For default threshold values；
If step B6, step B5 judged results match for switching angle, illustrate that triple criterion result of determination are matched, then it is final to judge
Two ends Data Matching, otherwise two end datas mismatch.
2. the electric power system fault data matching method based on Singularity detection combinational algorithm according to claim 1, it is special
Levy and be：The realization that step A3 finds current break point with Sudden Changing Rate current algorithm is as follows：
A) Sudden Changing Rate electric current Δ i (k) is calculated according to formula Δ i (k)=i (k)-i (k-N), wherein N is fault wave recording device one
The sampling number in cycle, i (k) is electric current at baseband signal i sampled point k；
B) current break point is determined according to detection criteria, criterion is as follows,
Wherein, parameterA=ψ (n) | | and ψ (n) | ＞ ξ, k≤n ＜ k+ α }, α is in parameter preset, satisfaction with β, ξ
First k value for stating criterion is the corresponding catastrophe point of detected signal.
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| CN106646106B (en) * | 2016-10-11 | 2019-02-22 | 河海大学 | Electric network fault detection method based on outlier's detection technology |
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