CN109884465A - A kind of one-way earth fault localization method based on signal injection method - Google Patents
A kind of one-way earth fault localization method based on signal injection method Download PDFInfo
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Abstract
The invention discloses a kind of one-way earth fault localization method based on signal injection method, including the following steps carried out in order: 1) installing n fault detector on every power transmission line, be segmented transmission line of electricity, the size of n is determined by route length；2) transmission line malfunction section is determined than localization method using double frequency frequency；3) computing electric power line head end to fault point distance.The one-way earth fault localization method based on signal injection method may be implemented double frequency Injection Signal frequency and compare fault location, determine fault zone, it positions reliable and high-efficient, fault distance is corrected offline using artificial fish school optimization BP neural network model, effective compensation initial ranging result, range accuracy is improved, achievees the purpose that accurately to find abort situation.
Description
Technical field
The present invention relates to electric network failure diagnosis technical field, in particular to a kind of unidirectional ground connection event based on signal injection method
Hinder localization method.
Background technique
Nowadays, with the expansion of power grid scale, power load increases year by year, and the structure of power distribution network is also all the more complicated, matches
Net Electrical Safety has been to be concerned by more and more people.Low and medium voltage distribution network mostly uses small grounding current system, and mesolow distribution
Singlephase earth fault accounts for the largest percentage in net accident.Failure is always inevitable, to guarantee that stablizing for electric system is transported
Row, ensures people's Electrical Safety, and quick processing and the protection of failure are keys, therefore the determination of abort situation, fault distance
Measuring just is particularly important reliable, the safe operation of electric system.
It for the determination problem of power distribution network grounding point, solves when one's early years: first being looked for using gradually open line method in two steps
To faulty line, route then is maked an inspection tour by operating personnel, range estimation is out of order a little.Open line method needs a rule route experimental
It operates a switch, send lock, which line failure determined, have no selectivity, non-faulting area electric load must be caused unnecessary
Power failure；It becomes increasingly complex with planar network architecture with the extension of power grid, range estimation line walking positioning is legal to expend considerable manpower object
Power, power off time is longer after failure occurs, and automatization level is low, and it is automatic that both methods has not adapted to contemporary grid height
The production of change needs, more opposite with distribution development trend at this stage.
It is either domestic or external, singlephase earth fault positioning distance measuring device be mostly for long and simple high pressure is defeated
Electric line, for the positioning device of low and medium voltage distribution network, comparative maturity, range unit are not widely applied also line selection apparatus, and
And theoretical research is only limited mostly.
Summary of the invention
The object of the present invention is to provide a kind of one-way earth fault localization method based on signal injection method.
For this purpose, technical solution of the present invention is as follows:
A kind of one-way earth fault localization method based on signal injection method, including the following steps carried out in order:
1) n fault detector is installed on every power transmission line, is segmented transmission line of electricity, the size of n is true by route length
It is fixed；
2) transmission line malfunction section is determined than localization method using double frequency frequency；
3) computing electric power line head end to fault point distance.
Further, the step 2) includes the following steps:
2-1) applying frequency on the transmission line is f1Signal source, calculate at route head end electric current and each fault detector
Electric current；
2-2) applying frequency on the transmission line is f2Signal source, calculate at route head end electric current and each fault detector
Electric current；
Judge to apply frequency 2-3) for f1Signal source when head end electric current and apply frequency be f2Signal source head end electricity
Whether the ratio of stream is equal to the frequency ratio for applying signal source, if judging result is "Yes", nothing is unidirectionally connect on the transmission line of electricity
Earth fault enters in next step if judging result is "No"；
Judge to apply frequency successively 2-4) for f1Signal source when with apply frequency be f2Signal source each fault detector
The frequency ratio whether ratio of electric current is equal to application signal source continues next group of comparison if being judged as "No"；If sentencing
Disconnected result is "Yes", then on the transmission line of electricity one-way earth fault point and the fault detector and a upper fault detector it
Between.
Further, the step 2-4) find one-way earth fault point after, ground fault is eliminated, then repeat walk
It is rapid 2), until find out one-way earth fault point all on transmission line of electricity.
Further, the method for distance of computing electric power line head end to fault point includes following step in the step 3)
It is rapid:
3-1) acquire data；According to transmission line of electricity overall length and fault detector position and collected ungrounded section
Zero-sequence current obtains ground connection section capacity current over the ground, while acquiring that ungrounded section Earth Phase characteristic signal electric current is i.e. non-to be connect
The induction reactance of ground section shunts；
3-2) calculate the measurement impedance Z in access aream；
Wherein:For bus exit or ground path head end voltage；For bus exit or ground path head end electricity
Stream；For ground path capacity current over the ground；It is shunted for the ungrounded section induction reactance of ground path；|zm| for measurement impedance Zm's
Modulus value.
3-3) calculate the measurement induction reactance X in access aream；
Wherein: | zm| for measurement impedance ZmModulus value；L is faulty line inductance；L is every kilometer of inductance of route；dmfFor reason
By fault distance；
Theoretical fault distance d 3-4) is calculated according to the measurement induction reactance in access areamf, and theoretical fault distance is repaired
Just.
Further, the step 3-4) in when being modified to theoretical fault distance, using artificial fish school optimization BP
Neural network model is modified, and the output of artificial fish school optimization BP neural network model obtains after being superimposed with theoretical fault distance
To physical fault distance；The building method of artificial fish school optimization BP neural network model is as follows:
1. determine the topological structure of BP neural network: the number of plies of BP network, it is especially hidden in addition to input layer and output layer
Number containing layer needs to determine and every layer of neuron number；
2. initializing the shoal of fish: according to BP network structure, being randomly provided interneuronal initial weight and threshold value, and made
For Artificial Fish initial position, Artificial Fish number is determined, form the initial shoal of fish；
3. the parameter of AFSA is arranged: field range Visual, the exploration number Try-number in foraging behavior, step-length
Step, maximum number of iterations MAXGEN, crowding factor delta；
4. calculating food concentration in waters: network error of the BP network under initial weight and threshold condition is calculated, with it
Food concentration reciprocal as Artificial Fish in the shoal of fish；
5. executing Artificial Fish code of conduct: by the looking for food of Artificial Fish, bunch, behavior of knocking into the back, search of food, and in time more
Newly find the position of the Artificial Fish of highest food concentration；
6. determining best initial weights and threshold value: the Artificial Fish position for the highest food concentration that the shoal of fish is finally explored is as new
Initial weight and threshold value be assigned to BP network；
7. BP training and prediction: input training sample calculates positive network error according to BP network training step, according to
Error again inversely amendment power, continue after threshold value to calculate network positive error, it is constantly reciprocal, until error meets required precision,
Terminate training, obtains artificial fish school optimization BP neural network model；Training is completed, and does simulation and prediction with test sample.
Further, the input of the artificial fish school optimization BP neural network model is Injection Signal frequency, route point
Cloth capacitor, earth-return circuit induction reactance, ground resistance and theoretical fault distance.
Compared with prior art, being somebody's turn to do the one-way earth fault localization method based on signal injection method may be implemented double frequency injection
Signal frequency determines fault zone than fault location, and positioning is reliable and high-efficient, utilizes artificial fish school optimization BP neural network mould
Type corrects fault distance offline, and effective compensation initial ranging reaches as a result, raising range accuracy and accurately finds abort situation
Purpose.
Detailed description of the invention
Fig. 1 is that signal injects range measurement principle figure.
Fig. 2 is that monophasic pulses injection method tracks positioning principle simplified model figure.
Fig. 3 is AFSA-BP neural network algorithm flow chart.
Fig. 4 is AFSA-BP neural network model distance correction policy map.
Fig. 5 is AFSA-BP neural network prediction error and initial error comparison diagram.
Fig. 6 is that AFSA-BP neural network corrects front and back error comparison diagram.
Fig. 7 is that AFSA-BP neural network corrects front and back comparative result figure.
Specific embodiment
With reference to the accompanying drawing and specific embodiment the present invention is described further, but following embodiments are absolutely not to this hair
It is bright to have any restrictions.
The one-way earth fault localization method based on signal injection method, including the following steps carried out in order:
1) n fault detector is installed on every power transmission line, is segmented transmission line of electricity, the size of n is true by route length
It is fixed；
2) transmission line malfunction section is determined than localization method using double frequency frequency；
3) computing electric power line head end to fault point distance.
Fig. 1 is that signal injects range measurement principle figure, to obtain more fault messages, more accurately measurement impedance is obtained, every
It installs 3~4 fault detectors (in figure for 3, determining in actual conditions with route length) on power transmission line additional, makes route
Segmentation.In figure: ImFor the Earth Phase characteristic signal electric current separated from power frequency information；ICFor faulty line, capacitive is electric over the ground
Stream；ILIt is shunted for the ungrounded section induction reactance of ground path；I′mFor earth-return circuit earth current at bus to grounding point；D is route
Overall length.
Fig. 2 is that monophasic pulses injection method tracks positioning principle simplified model figure.
According to fig. 2, it is measuring node number each on power transmission line, takes from 0 to n, then route head end I0Electric current is each on route
Node current and:
In above formula:Electric current on power transmission line at-n node；- each node capacitive earth current；It is electric at-grounding point
Stream.
The direct-to-ground capacitance of transmission line of electricity all very littles, are all microfarad ranges, and capacitive reactance is just quite big, even for cable run,
Its capacitor will more greatly, but be also microfarad range, and capacitive reactance is also far longer than resistance and induction reactance.Therefore quite a few electric current is all on route
It is shunted by direct-to-ground capacitance.If ignoring impedance on route, and applying frequency is f1Signal source, have at this time:
Then its virtual value are as follows:
Electric current after at grounding point are as follows:
Virtual value:
If application frequency is f2Signal source then have:
According to (5) formula and (7) formula, the capacity current after grounding point is directly proportional to the frequency of Injection Signal；And (3) formula and
(6) formula illustrates, the capacity current of fault zone is then unsatisfactory for proportional relation because of the influence of ground resistance.Then the injection of non-faulting area is double
After frequency characteristic signal capacity current than be their frequencies ratio, and faulty section is then unsatisfactory for, as shown in formula (8), (9).
The step 2) includes the following steps:
2-1) applying frequency on the transmission line is f1Signal source, calculate at route head end electric current and each fault detector
Electric current；
2-2) applying frequency on the transmission line is f2Signal source, calculate at route head end electric current and each fault detector
Electric current；
Judge to apply frequency 2-3) for f1Signal source when head end electric current and apply frequency be f2Signal source head end electricity
Whether the ratio of stream is equal to the frequency ratio for applying signal source, if judging result is "Yes", nothing is unidirectionally connect on the transmission line of electricity
Earth fault enters in next step if judging result is "No"；
Judge to apply frequency successively 2-4) for f1Signal source when with apply frequency be f2Signal source each fault detector
The frequency ratio whether ratio of electric current is equal to application signal source continues next group of comparison if being judged as "No"；If sentencing
Disconnected result is "Yes", then on the transmission line of electricity one-way earth fault point and the fault detector and a upper fault detector it
Between.
Step 2-4) find one-way earth fault point after, ground fault is eliminated, then repeatedly step 2), until finding out defeated
All one-way earth faults point in electric line.
The method of distance of computing electric power line head end to fault point includes the following steps: in the step 3)
3-1) acquire data；According to transmission line of electricity overall length and fault detector position and collected ungrounded section
Zero-sequence current obtains ground connection section capacity current over the ground, while acquiring that ungrounded section Earth Phase characteristic signal electric current is i.e. non-to be connect
The induction reactance of ground section shunts；
3-2) calculate the measurement impedance Z in access aream；
Wherein:For bus exit or ground path head end voltage；For bus exit or ground path head end electricity
Stream；For ground path capacity current over the ground；It is shunted for the ungrounded section induction reactance of ground path；|zm| for measurement impedance Zm's
Modulus value.
3-3) calculate the measurement induction reactance X in access aream；
Wherein: | zm| for measurement impedance ZmModulus value；L is faulty line inductance；L is every kilometer of inductance of route；dmfFor reason
By fault distance；
Theoretical fault distance d 3-4) is calculated according to the measurement induction reactance in access areamf, and theoretical fault distance is repaired
Just.
The step 3-4) in when being modified to theoretical fault distance, using artificial fish school optimization BP neural network mould
Type is modified, and the output of artificial fish school optimization BP neural network model obtains physical fault after being superimposed with theoretical fault distance
Distance；As shown in figs. 34, the building method of artificial fish school optimization BP neural network model is as follows:
1. determine the topological structure of BP neural network: the number of plies of BP network, it is especially hidden in addition to input layer and output layer
Number containing layer needs to determine and every layer of neuron number；
2. initializing the shoal of fish: according to BP network structure, being randomly provided interneuronal initial weight and threshold value, and made
For Artificial Fish initial position, Artificial Fish number is determined, form the initial shoal of fish；
3. the parameter of AFSA is arranged: field range Visual, the exploration number Try-number in foraging behavior, step-length
Step, maximum number of iterations MAXGEN, crowding factor delta；
4. calculating food concentration in waters: network error of the BP network under initial weight and threshold condition is calculated, with it
Food concentration reciprocal as Artificial Fish in the shoal of fish；
5. executing Artificial Fish code of conduct: by the looking for food of Artificial Fish, bunch, behavior of knocking into the back, search of food, and in time more
Newly find the position of the Artificial Fish of highest food concentration；
6. determining best initial weights and threshold value: the Artificial Fish position for the highest food concentration that the shoal of fish is finally explored is as new
Initial weight and threshold value be assigned to BP network；
7. BP training and prediction: input training sample calculates positive network error according to BP network training step, according to
Error again inversely amendment power, continue after threshold value to calculate network positive error, it is constantly reciprocal, until error meets required precision,
Terminate training, obtains artificial fish school optimization BP neural network model；Training is completed, and does simulation and prediction with test sample.
The input of the artificial fish school optimization BP neural network model is Injection Signal frequency, line distribution capacitance, connects
Earth-return induction reactance, ground resistance and theoretical fault distance.
Establish three layers of BP neural network structural model of 1 input layer, 1 hidden layer and an output layer.Input layer nerve
First number is i=5, and hidden layer takes j=20.1 neuron of output layer.Weight between output layer and hidden neuron is wjm；Hidden layer with
Weight is wij between input layer；The input data of training sample, i.e. Injection Signal frequency, are grounded back line distribution capacitance
Road feel is anti-, ground resistance and theoretical fault distance；The desired output of sample, i.e. initial ranging error；The output of test sample,
That is the prediction result of ASFA-BP neural network.
Artificial Fish algorithm parameter is set as fish way fishnum=100, field range Visual=1.5, crowding
Factor delta=0.618, maximum step-length Step=0.1 sound out number Try-number=100, maximum number of iterations MAXGEN
=200.The initial weight of BP network and threshold value are set as Artificial Fish initial position, Artificial Fish finds the process of highest food concentration
The as process of BP network weight threshold optimization.
As seen from Figure 5, ASFA-BP Neural Network Based Nonlinear approximation capability is excellent, predicts error and initial error phase
Difference is very few.The error comparison of AFSA-BP neural network amendment front and back, illustrates after AFSA-BP neural network compensates, surveys in Fig. 6
It is substantially reduced away from error, levels off to 0 substantially.Fig. 7 corrects front and back by ASFA-BP neural network and surveys fault distance comparison, amendment
Curve afterwards is almost overlapped with physical fault distance, and precision is quite high.And by calculated result it is found that final ranging relative error
Within 1%, even if ground resistance is more than 1000 Ω, range accuracy is also quite high.
Claims (6)
1. a kind of one-way earth fault localization method based on signal injection method, which is characterized in that including carrying out down in order
Column step:
1) n fault detector is installed on every power transmission line, is segmented transmission line of electricity, the size of n is determined by route length；
2) transmission line malfunction section is determined than localization method using double frequency frequency；
3) computing electric power line head end to fault point distance.
2. the one-way earth fault localization method according to claim 1 based on signal injection method, which is characterized in that described
Step 2) include the following steps:
2-1) applying frequency on the transmission line is f1Signal source, calculate the electricity at route head end electric current and each fault detector
Stream；
2-2) applying frequency on the transmission line is f2Signal source, calculate the electricity at route head end electric current and each fault detector
Stream；
Judge to apply frequency 2-3) for f1Signal source when head end electric current and apply frequency be f2Signal source head end electric current
Whether ratio is equal to the frequency ratio of application signal source, if judging result is "Yes", the unidirectional ground connection event of nothing on the transmission line of electricity
Barrier enters in next step if judging result is "No"；
Judge to apply frequency successively 2-4) for f1Signal source when with apply frequency be f2Signal source each fault detector electric current
Ratio whether be equal to apply signal source frequency ratio continue next group of comparison if being judged as "No"；If judgement knot
Fruit is "Yes", then on the transmission line of electricity between one-way earth fault point and the fault detector and a upper fault detector.
3. the one-way earth fault localization method according to claim 2 based on signal injection method, which is characterized in that step
After 2-4) finding one-way earth fault point, ground fault is eliminated, then repeatedly step 2), is owned until finding out on transmission line of electricity
One-way earth fault point.
4. the one-way earth fault localization method according to claim 3 based on signal injection method, which is characterized in that described
Step 3) in the method for distance of computing electric power line head end to fault point include the following steps:
3-1) acquire data；According to transmission line of electricity overall length and fault detector position and the zero sequence of collected ungrounded section
Electric current obtains ground connection section capacity current over the ground, while acquiring the ungrounded i.e. ungrounded area of section Earth Phase characteristic signal electric current
The induction reactance of section shunts；
3-2) calculate the measurement impedance Z in access aream；
Wherein:For bus exit or ground path head end voltage；For bus exit or ground path head end electric current；For ground path capacity current over the ground；It is shunted for the ungrounded section induction reactance of ground path；|zm| for measurement impedance ZmMould
Value.
3-3) calculate the measurement induction reactance X in access aream；
Wherein: | zm| for measurement impedance ZmModulus value；L is faulty line inductance；L is every kilometer of inductance of route；dmfFor theoretical failure
Distance；
Theoretical fault distance d 3-4) is calculated according to the measurement induction reactance in access areamf, and theoretical fault distance is modified.
5. the one-way earth fault localization method according to claim 4 based on signal injection method, which is characterized in that described
Step 3-4) in when being modified to theoretical fault distance, be modified using artificial fish school optimization BP neural network model,
The output of artificial fish school optimization BP neural network model obtains physical fault distance after being superimposed with theoretical fault distance；Artificial Fish
The building method of group's Optimized BP Neural Network model is as follows:
1. determining the topological structure of BP neural network: the number of plies of BP network, the especially hidden layer in addition to input layer and output layer
Number need to determine and every layer of neuron number；
2. initializing the shoal of fish: according to BP network structure, being randomly provided interneuronal initial weight and threshold value, and as people
Work shoal of fish initial position, determines Artificial Fish number, forms the initial shoal of fish；
3. the parameter of AFSA is arranged: field range Visual, exploration number Try-number, step-length Step in foraging behavior,
Maximum number of iterations MAXGEN, crowding factor delta；
4. calculating food concentration in waters: network error of the BP network under initial weight and threshold condition is calculated, with its inverse
Food concentration as Artificial Fish in the shoal of fish；
5. executing Artificial Fish code of conduct: by the looking for food of Artificial Fish, bunch, behavior of knocking into the back, search of food, and timely update and look for
To the position of the Artificial Fish of highest food concentration；
6. determining best initial weights and threshold value: the Artificial Fish position for the highest food concentration that the shoal of fish is finally explored is as at the beginning of new
Beginning weight and threshold value are assigned to BP network；
7. BP training and prediction: input training sample calculates positive network error, according to error according to BP network training step
Continue to calculate network positive error after reverse amendment power, threshold value again, it is constantly reciprocal, until error meets required precision, terminate
Training, obtains artificial fish school optimization BP neural network model；Training is completed, and does simulation and prediction with test sample.
6. the one-way earth fault localization method according to claim 5 based on signal injection method, which is characterized in that described
Artificial fish school optimization BP neural network model input be Injection Signal frequency, line distribution capacitance, earth-return circuit induction reactance, connect
Ground resistance and theoretical fault distance.
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| CN113567808A (en) * | 2021-07-26 | 2021-10-29 | 华北电力大学 | Unified power flow controller access line fault positioning method and system |
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