CN104198893B - Adaptive failure electric current detecting method - Google Patents

Adaptive failure electric current detecting method Download PDF

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CN104198893B
CN104198893B CN201410496062.6A CN201410496062A CN104198893B CN 104198893 B CN104198893 B CN 104198893B CN 201410496062 A CN201410496062 A CN 201410496062A CN 104198893 B CN104198893 B CN 104198893B
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current
value
output valve
sef
current transformer
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CN104198893A (en
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马韬
张京业
戴少涛
赵连岐
薛弛
滕玉平
朱志芹
许熙
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Institute of Electrical Engineering of CAS
Jiangsu Zhongtian Technology Co Ltd
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Institute of Electrical Engineering of CAS
Jiangsu Zhongtian Technology Co Ltd
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Abstract

A kind of adaptive failure electric current detecting method, it is characterised in that described fault current detection method is predicted to current signal using sef-adapting filter, using predicted value as reference frame, and sets threshold value.The predicted value of the current signal that the current signal value that current transformer is detected is exported with sef-adapting filter compares, if the deviation between the current signal value and predicted value of the reality that current transformer is detected exceedes threshold value set in advance, then it is assumed that produce failure.The present invention is applied to the current failure diagnosis of power system and the devices such as power equipment.

Description

Adaptive failure electric current detecting method
Technical field
The present invention relates to a kind of electric network fault electric current detecting method.
Background technology
With the continuous increase of electrical network scale, electric network fault electric current is also increasing, and some places have begun to exceed breaks The maximum of road device can cut-off the limit.And the state-detection of fault current is the direct basis of breaker actuation, fast and effectively event Barrier electric current judges for the action as breaker to save valuable time.
The certain threshold value of traditional fault current basis for estimation, i.e., think event when electric current exceedes a certain preset value Barrier occurs, it should cut-off breaker.There is problems with the method:First, being usually reduces erroneous judgement, can arrange threshold value Higher, it is contemplated that from fault detect to the regular hour is needed between breaker actuation, event when so resulting in breaker actuation Barrier current peak has been produced;2nd, sensor output is easily disturbed by external environment condition, and disturbing pulse may cause electric current to be believed Number exceed set threshold value, cause breaker misoperation.
For reducing the harm of fault current to the full extent, quick, reliable fault current detection method just becomes existing For the important content that electrical network and protective-relay device for power equipment are researched and developed.Using digital technology, believed by the electric current to detecting Number it is analyzed, the shortcoming of direct hardware circuit threshold detection can be prevented effectively from.For AC network sine wave failure electricity The detection of stream, proposes multiple methods both at home and abroad:First, two dot product integration method, the method need to detect that current waveform is stable Sine wave, and more multiplication and division will be carried out, operand is larger;2nd, three dot product area method, the method are approximate with two dot product area method, Its response speed is slightly fast, but also requires that detection electric current is to stablize sine wave;3rd, the differential method, the method carry out differential to signal, Easily it is interfered, and amount of calculation larger (ABB Is- current limiter technical manuals, http://www.abb.com.cn/ product/db0003db004279/c125739900636470c125698c00553a43.aspx);4th, half cycle absolute value product Algorithm, the method is divided to need the signal for gathering half sine wave, therefore time delay is larger;5th, fourier algorithm, the method is by half-and-half The signal of an individual or cycle carries out Fourier transform, and so as to realize the differentiation of signal, its time delay is larger, the not high (Guo of rapidity Glory, relay protection of power system (second edition), Higher Education Publishing House, 2011).
It is relatively stable sine wave that above method is required to measured signal, and actually power network current is always comprising repeatedly Harmonic wave, in fluctuation, therefore the scope of application of said method is by a definite limitation, limited reliability for its amplitude, phase place.
Additionally, there is part research to realize fault current detection using neutral net, which is by wavelet transformation and neutral net Grader combines, using Wavelet transformation extract fault current feature, then input to neural network recognization failure (Zhaoyang etc., For the neural network failure electric current detecting method of hybrid circuit breaker, Harbin University of Science and Technology's journal, 2011,16 (1):53- 56).But such method needs substantial amounts of fault sample to be trained neutral net, and the form thousand of actually failure differs from ten thousand Not, neutral net is trained it is difficult to the sample of all fault categories is all brought.Also, the amount of calculation of neutral net compared with Greatly, real-time is not high, and the simulation result surface of such as above-mentioned document needs 3ms just to can recognize that failure.
Therefore, how using the minimum current signal sample for detecting, the most accurate event is made with the most short time Barrier differentiates that just becoming relay protection of power system needs key problems-solving.
Content of the invention
Present invention aim at solving quick, the reliable test problems of power system fault current, there is provided a kind of reliable Adaptive failure electric current detecting method.Fault current inspection of the method suitable for electrical network, power equipment AC and DC power system Survey.
The adaptive failure electric current detecting method of the present invention is based on following principle:
The present invention is based in current power system and commonly uses microcomputer protective relay device.Described microcomputer protective relay dress The electric current and voltage data of on the one hand collection electrical network is put, wave filter is on the other hand provided with and in real time the data for gathering is resolved, Whether failure judgement occurs.The present invention replaces the filter in existing power system microcomputer protective relay device using sef-adapting filter Ripple device, according to history data, is predicted to the current value of subsequent time.Fluctuation range is normally run in power system Deviation between interior current actual value and the predicted value is smaller, if power system is broken down, microcomputer protective relay is filled Deviation between the actually detected current value for arriving of the current transformer put and predicted value will be larger.Using this feature, can be with Distinguish normal current fluctuation and failure.The present invention is predicted to current signal using sef-adapting filter, and predicted value is made For reference frame, and set threshold value.The current signal value that current transformer is detected is pre- with what sef-adapting filter was exported Measured value compares, if the deviation between the current signal value of reality that detects of current transformer and predicted value exceedes preset Threshold value, then it is assumed that produce failure.Additionally, may there is detected value and prediction because being interfered in the output of current transformer The larger situation of value deviation, when disturbing the deviation for causing be much larger than the normal operation of system and failure operation in systems in practice Deviation, therefore can be made a distinction by different threshold settings.
The adaptive failure electric current detecting method of the present invention is comprised the following steps:
(1) the current transformer output signal value x for current t current transformer being collectedtWith sef-adapting filter Output valveIt is compared,
Wherein, t be the data acquisition moment, xtFor t collection current transformer output valve,Filter for t self adaptation The output valve of ripple device;δl、δhConstant respectively set in advance, and meet δlh;Symbol | | represent and take absolute value.Above formula table Bright three kinds of situations:
A, t current transformer output valve xtWith sef-adapting filter output valveBetween difference be less than setting value δlWhen, it is believed that power network current is normal;
B, t current transformer output valve xtWith sef-adapting filter output valveBetween difference be not less than setting value δlAnd it is less than setting value δh, it is believed that grid collapses, need to make breaker actuation immediately;
C, t current transformer output valve xtWith sef-adapting filter output valveBetween difference be more than setting value δh, Think that current transformer output is subject to external disturbance, the signal is spurious signal, can ignore.
(2) if judging to belong to situation b, failure is provided by microcomputer protective relay device immediately signal occurs to relay protection The relay of system;If judging to belong to situation a or c, then it is assumed that do not break down, according to the current transformer output number for collecting Export according to now sef-adapting filter is calculated:
Wherein,
In formula, symbolRepresent the transposition for asking for matrix or vector, symbolRepresent and ask for the inverse of matrix or vector, " t ", " t-1 ", " t+1 " the moment symbolic variable corresponding value are represented respectively.λ for be close to 1 but Positive number less than 1, can take λ=0.99 again;For the noise variance of current transformer output signal, by the spy of current transformer Property parameter can be obtained;I is that d ties up unit square formation;Initial value is arranged as unit square formation;Wt=[wtwt-1… wt-d-1]TIt is certainly The d dimension weight vectors of adaptive filter, its initial value are chosen as null vector, and d is filter order;Input vector is tieed up for sef-adapting filter d, as sampling instant t<During d, its value elects 0 as, and Have:
(3) current transformer data x at t+1 moment are gatheredt+1, by xt+1Output with sef-adapting filter in step (2)Subtract each other, and differentiated according to the formula in step (1).Thus iterate calculating, judgement, until detect failure sending out Raw.Now according to the processing mode in step (2), failure is provided by microcomputer protective relay device signal occurs to relay protection system The relay of system.
Described microcomputer protective relay device is the vitals of power system, is known in professional and technical personnel in the field. Microcomputer protective relay device includes the parts such as data collecting system, CPU main systems and output switch parameter system;Data collecting system It is made up of current transformer, voltage transformer and analog quantity converting unit, current transformer and voltage transformer primary side are direct It is connected to by protection power circuit, measurement in real time is by the current value and magnitude of voltage, current transformer and voltage of protection power circuit The secondary side of transformer is connected with analog quantity converting unit, is converted to corresponding digital quantity by analog quantity converting unit;Data are adopted The output bus of collecting system is directly connected with CPU main systems, and the digital quantity that analog quantity converting unit is converted into is sent to CPU Main system, carries out Treatment Analysis by CPU main systems to the current value that gathers and magnitude of voltage etc., provides corresponding operational order;Open Pass amount output system is made up of isolation circuit, relay etc., and the output of CPU main systems is directly isolated with output switch parameter system Circuit connects, and after the operational order be given by CPU main systems is through the isolation circuit of output switch parameter system, sends defeated to switching value Go out the relay of system;The relay of output switch parameter system is directly connected with the executing agency of breaker in power circuit, The executing agency of breaker is caused to carry out corresponding action by the switch of relay.
Described relay protection system is the requisite part of Operation of Electric Systems, main including microcomputer protective relay dress Put and breaker.Microcomputer protective relay device is responsible for the state that real-time monitoring is protected power circuit, once detect protected There is exception in power circuit, then provide corresponding action command value to breaker;Breaker directly connects access by protection electric power Circuit, when normally being run by protection power circuit, breaker is in the conduction state, when being occurred abnormal by protection power circuit, by Microcomputer protective relay device control breaker disconnects.
Described relay is the part for driving power system switchgear adopt.Due to power equipments such as breakers Startup and stopping be required for high-power, and the control system of microcomputer protective relay device itself can only export weak electric signal, should The underpower of weak electric signal is driving the power equipments such as breaker, it is therefore desirable to using relay by low power weak electric signal Instruction is converted to the high-power signal that can drive the power equipments such as breaker.
The characteristics of adaptive failure electric current detecting method of the present invention is current signal to be carried out using sef-adapting filter Prediction, using predicted value as reference frame, if between the actually detected current signal value for arriving of current transformer and predicted value Deviation exceedes threshold value set in advance, then it is assumed that produce failure.The sef-adapting filter of the method and conventional adaptive-filtering Device is different, and its calculating only needs using historical data and do not rely on reference signal.The calculating process of conventional sef-adapting filter There must be a reference signal, and more difficult acquisition reference signal in systems in practice.The method is the quick, accurate of solution fault current Detection provides a kind of new effective technology means, it is adaptable to which power system is diagnosed with the current failure of the devices such as power equipment.
Description of the drawings
Fig. 1 is adaptive failure electric current detecting method block diagram;
Map of current when Fig. 2 is a short circuit malfunction;
Fig. 3 is prognostic chart of the sef-adapting filter to power network current;
Fig. 4 is the deviation map between sef-adapting filter predicted value and actually detected value;
Fig. 5 is that power network current is normal but sensor exports detected value figure when being interfered;
Fig. 6 is deviation map when sensor output is interfered between predicted value and detected value.
Specific embodiment
The present invention is further illustrated with reference to the accompanying drawings and detailed description.
Fig. 1 show the FB(flow block) of adaptive failure electric current detecting method.When detecting system brings into operation, to method In parameters initialized, including forgetting factor λ=0.99, according to current transformer handbook parameter to noise side DifferenceAssignment, arranges filter length d=5, and setting I is d rows, the unit square formation of d row, arranges intermediate variableArrange Sef-adapting filter initial weight vector W0For d rows, the null vector of 1 row, sef-adapting filter initial input vector X is set0For d Row, the null vector of 1 row, arrange sef-adapting filter and initially exportThreshold delta is arranged according to power system featurelAnd δh, Such as δl=100, δh=1000.
After initial parameter value is provided with, judgement flow process is proceeded by.
First, the output valve of current t current transformer is gathered, x is assigned tot
Then, by xtOutput with t-1 moment wave filtersIt is compared, if the deviation between the two is less than δl, then it is assumed that electricity , within normal range (NR), Operation of Electric Systems is normal, and the output x by current transformer for streamtIt is assigned to intermediate parametersIf Deviation between the two is not less than δl, then proceed to judge, see whether deviation exceedes another threshold deltahIf deviation does not surpass Cross δh, it is considered as power system and breaks down, now exports fault-signal, and the output x by current transformertIt is assigned to centre ParameterIf deviation is more than δh, just think that current transformer output is interfered, now by t-1 moment sef-adapting filters OutputIt is assigned to intermediate parameters
Further, sef-adapting filter is using historical data and t intermediate parametersValue, according to below equation calculate Predicted value to t+1 moment electric currents:
Wherein,
In formula, λ=0.99;For the noise variance of current transformer output signal, d=5, I are 5 × 5 dimension unit square formations,The 5 dimension input vectors for sef-adapting filter.
Finally, the output valve of sef-adapting filter is returned, for comparing next time.Resurvey the sensing at t+1 moment Device is exported, and is carried out the multilevel iudge of a new round, is so gone round and begun again.
Fig. 2 show a map of current during short circuit malfunction.Current value meeting when the grid collapses can be seen It is increased dramatically, but the fundamental frequency characteristic of power system remains as 50Hz, the increase of electric current is primarily due to network system during short circuit Impedance reduces.
Fig. 3 show prognostic chart of the sef-adapting filter to power network current.Compared with Fig. 2, it can be seen that the electricity of prediction Flow valuve is basically identical with actual current value under normal circumstances.
Fig. 4 show the deviation map between sef-adapting filter predicted value and actually detected value.Can see, normal condition Under, the deviation of the two is substantially less than 5A.When the grid collapses, first sampled point that predicted current can be after a failure Place's deviation is increased dramatically.Current sample frequency is 100kHz, arranges δl=100, can after a failure after 0.02ms at just Fault pre-alarming signal is given immediately;According to conventional threshold value detection method, using 5kA as threshold value, then 0.46ms is needed.
Detected value figure when Fig. 5 show power network current normally but sensor output is interfered.Current transformer is exported The interference being subject to is mainly induced voltage, and the feature of rising shows as that peak value is big but the duration is short.
Fig. 6 show deviation map when current transformer output is interfered between predicted value and detected value.With shown in Fig. 4 Fault current prediction deviation value compare, deviation during interference is bigger, and it is mutation that its reason is to disturb the detected value for causing. But, as electrical network includes certain inductive component in normal and failure, cause real power network current go out Now it is mutated.Mutation causes the exporting change of sef-adapting filter big, more than threshold deltal=1000, can be distinguished according to the feature Interference and normal fault current.

Claims (1)

1. a kind of adaptive failure electric current detecting method, it is characterised in that described fault current detection method adopts self adaptation Wave filter is predicted to current signal, using predicted value as reference frame, and sets threshold value;Current transformer is detected The predicted value of current signal that exports with sef-adapting filter of current signal value compare, if current transformer detects reality Current signal value and the predicted value between deviation exceed threshold value set in advance, then it is assumed that produce failure;Concrete step Rapid as follows:
(1) current transformer output valve x for current t being collectedtOutput valve with sef-adapting filterIt is compared:
Wherein, t be the data acquisition moment, xtFor t collection current transformer output valve,For t sef-adapting filter Output valve;δl、δhConstant respectively set in advance, and meet δlh;Symbol | | represent and take absolute value;Above formula shows three The situation of kind:
A, t current transformer output valve xtWith sef-adapting filter output valveBetween difference be less than setting value δlWhen, recognize Normal for power network current;
B, t current transformer output valve xtWith sef-adapting filter output valveBetween difference be not less than setting value δlAnd it is little In setting value δh, it is believed that grid collapses, need to make breaker actuation immediately;
C, t current transformer output valve xtWith sef-adapting filter output valveBetween difference be more than or equal to setting value δh, Think that current transformer output is subject to external disturbance, the signal is spurious signal, can ignore;
(2) if judging to belong to situation b, failure is provided immediately by microcomputer protective relay device signal occurs to relay protection system Relay;If judging to belong to situation a or c, then it is assumed that do not break down, calculated according to the current transformer output valve for collecting Now sef-adapting filter output valve:
x ^ t + 1 = W t T X t
Wherein,
W t = W t - 1 + &Phi; t - 1 &lsqb; ( x t - W t - 1 T X t ) X t - C &rsqb;
&Phi; t - 1 = &lambda; - 1 ( I - K t X t T ) &Phi; t - 1 - 1
K t = &Phi; t - 1 - 1 X t &lambda; + X t T &Phi; t - 1 - 1 X t
C = &sigma; b 2 0 ... 0 T
In formula, symbolRepresent the transposition for asking for matrix or vector, symbolRepresent and ask for the inverse of matrix or vector, " t ", " t-1 ", " t+1 " the moment symbolic variable corresponding value are represented respectively;λ for being close to 1 but is less than 1 Positive number, take λ=0.99;For the noise variance of sensor output signal, can be obtained by the characterisitic parameter of sensor;I is d Dimension unit square formation;Initial value is arranged as unit square formation;Wt=[wtwt-1… wt-d-1]TD right-safeguarding values for sef-adapting filter Vector, its initial value elect null vector as, and d is filter order;Tie up for sef-adapting filter d defeated Incoming vector, as sampling instant t<During d, its value elects 0 as, and has:
(3) current transformer output valve x at t+1 moment is gatheredt+1, by current transformer output valve xt+1Adaptive with step (2) Answer the output valve of wave filterSubtract each other, and differentiated according to the formula in step (1);Thus iterate calculating, judgement, Until detecting failure generation.
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Publication number Priority date Publication date Assignee Title
CN104915777B (en) * 2015-06-12 2018-11-02 北京交通大学 Relay protection criterion method based on the analysis of dynamic trend degree
CN107525969A (en) * 2016-06-21 2017-12-29 中电普瑞科技有限公司 A kind of self-adapting type electric harmonic analysis method for merging many algorithms
CN107294049B (en) * 2017-06-19 2019-02-26 华中科技大学 A kind of short circuit electric current quick predict and guard method and system
CN112034387B (en) * 2020-09-08 2021-09-21 武汉大学 Power transmission line short-circuit fault diagnosis method and device based on prediction sequence

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101533058A (en) * 2009-04-24 2009-09-16 东北大学 Power abnormal failure data analyzing device and diagnosing method
CN102279341A (en) * 2011-07-23 2011-12-14 华北电力大学(保定) Cage asynchronous motor rotor broken-bar fault detection method based on electronic stability program rotation invariant technology (ESPRIT) and pattern search algorithm (PSA)
CN202230172U (en) * 2011-10-13 2012-05-23 李怡 Electric power system fault detection device
CN103091606A (en) * 2013-02-28 2013-05-08 绥化电业局 Grounding fault detecting method for direct current system with high anti-interference capacity
CN103176128A (en) * 2013-03-28 2013-06-26 华南理工大学 Method and system for forcasting state of wind generating set and diagnosing intelligent fault
CN103336173A (en) * 2013-01-29 2013-10-02 上海海维工业控制有限公司 Genetic algorithm based self-adaption harmonic detection method
CN103929150A (en) * 2014-03-27 2014-07-16 苏州大学 Weight vector updating method for sub-band adaptive filter
CN103971163A (en) * 2014-05-09 2014-08-06 哈尔滨工程大学 Adaptive learning rate wavelet neural network control method based on normalization lowest mean square adaptive filtering

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8336352B2 (en) * 2010-01-25 2012-12-25 Aclara Power-Line Systems, Inc. Transient detector and fault classifier for a power distribution system
KR101118375B1 (en) * 2010-09-07 2012-03-09 엘에스산전 주식회사 Apparatus for swift determination of fault in electric power system

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101533058A (en) * 2009-04-24 2009-09-16 东北大学 Power abnormal failure data analyzing device and diagnosing method
CN102279341A (en) * 2011-07-23 2011-12-14 华北电力大学(保定) Cage asynchronous motor rotor broken-bar fault detection method based on electronic stability program rotation invariant technology (ESPRIT) and pattern search algorithm (PSA)
CN202230172U (en) * 2011-10-13 2012-05-23 李怡 Electric power system fault detection device
CN103336173A (en) * 2013-01-29 2013-10-02 上海海维工业控制有限公司 Genetic algorithm based self-adaption harmonic detection method
CN103091606A (en) * 2013-02-28 2013-05-08 绥化电业局 Grounding fault detecting method for direct current system with high anti-interference capacity
CN103176128A (en) * 2013-03-28 2013-06-26 华南理工大学 Method and system for forcasting state of wind generating set and diagnosing intelligent fault
CN103929150A (en) * 2014-03-27 2014-07-16 苏州大学 Weight vector updating method for sub-band adaptive filter
CN103971163A (en) * 2014-05-09 2014-08-06 哈尔滨工程大学 Adaptive learning rate wavelet neural network control method based on normalization lowest mean square adaptive filtering

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