CN108594156A - A kind of improved CT saturation characteristics recognizing method - Google Patents
A kind of improved CT saturation characteristics recognizing method Download PDFInfo
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- CN108594156A CN108594156A CN201810447036.2A CN201810447036A CN108594156A CN 108594156 A CN108594156 A CN 108594156A CN 201810447036 A CN201810447036 A CN 201810447036A CN 108594156 A CN108594156 A CN 108594156A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R35/00—Testing or calibrating of apparatus covered by the other groups of this subclass
- G01R35/02—Testing or calibrating of apparatus covered by the other groups of this subclass of auxiliary devices, e.g. of instrument transformers according to prescribed transformation ratio, phase angle, or wattage rating
Abstract
The invention discloses a kind of improved CT saturation characteristics recognizing methods.First, all current transformers for being connected to same busbar are divided into same group, acquire current signal；Secondly, differential protection calculating is carried out using Kalman filtering algorithm extraction fundametal compoment, detects protection signal；Finally, data window is chosen, respective abrupt climatic change is obtained as a result, determining all catastrophe point positions after being modified wavelet transformation, power function optimization to same group of all current transformers, identifies CT saturation characteristic.The present invention can promote the real-time of differential protection calculating；Traditional wavelet transformation is modified, Singularity detection can be made more accurate；The deficiency for the method that can get over jet lag identifies different failures and saturation moment, correctly judges fault type, has higher correctness and applicability under various scenes.
Description
Technical field
The present invention relates to CT saturation specificity analysis, special more particularly, to a kind of improved CT saturation
Property recognition methods.
Technical background
In the power system, current transformer and protective relaying device, electric current metering device etc. are used cooperatively, and provide power grid
Current information, decisive role is played to the normal operation of the secondary devices such as relay equipment, current monitoring device.When electric current is mutual
After sensor saturation, due to the nonlinear characteristic of itself, it will cause to acquire current data output distortion, influence normal use.Especially
It is when current transformer crosses ambassador's current transformer supersaturation more than its maximum protection ability because of electric current, it will leads to secondary electricity
Stream waveform is distorted, and in the process, the operative condition of quick-break overcurrent protective device will be influenced by distortion current, due to
Its current effective value is lowered, which will be difficult to play a role, at the same differential protection but can because of electric current not just
Often variation makes differential protection send out error signal, it is also possible to which the misaction for causing current protection causes important damage to power grid
It loses.
At this stage, scholars propose various CT saturation identifying schemes, however still have some shortcomings,
Such as：The various schemes based on time difference method still rely on failure with saturation there are the regular hour is poor, are obtained if detected
The time difference be less than the threshold value, then it is assumed that the time difference is not present.It is seriously rapidly saturated or occurs the case where strong pulse interference if encountering,
Detection method based on time difference criterion will be mistaken for the time difference and be not present and lead to false protection, and if external area error leads to electricity
After current transformer saturation and when changing property failure, protection may long-time tripping.Current harmonics method is believed according only to electric current
Harmonic component in number determines whether to be saturated, and can not inherently identify the generation moment of failure and saturation.And differential guarantor
When mutual inductor degree of saturation is deeper, difference current may be still located at tripping area and lead to false protection shield.Based on small echo mould pole
The wave character at moment occurs for the mutation in the signal disturbance detection identification current transformer being worth greatly, is relatively effective at present prominent
Detection of change-point method, however this method relies only on the current information of single current transformer, more the amount of can refer to does not carry out pair
Than screening, anti-interference ability is poor, and criterion may fail under certain extreme cases.
Invention content
Goal of the invention：The object of the present invention is to provide a kind of improved CT saturation characteristics recognizing methods, can
Promote the real-time that differential protection calculates；Keep Singularity detection more accurate；The saturated characteristic identification of various extreme cases is coped with,
Ensure the correct action of differential protection.
Technical solution：To reach this purpose, the present invention uses following technical scheme：
Improved CT saturation characteristics recognizing method of the present invention, includes the following steps：
S1：All current transformers for being connected to same busbar are divided into same group, acquisition current signal f (t)；
S2：Differential protection calculating is carried out using Kalman filtering algorithm extraction fundametal compoment, detects protection signal；
S3：Data window is chosen, wavelet transformation is modified to same group of all current transformers, power function optimizes；
S4：Catastrophe point is detected, determines all catastrophe point positions, identifies CT saturation characteristic.
Further, the step S2 includes the following steps：
S2.1：The selection of Kalman filtering algorithm parameter
Wherein g1,j、g2,jTo represent the combination signal of jth layer harmonic wave；ΔuiFor the amplitude of ith harmonic wave；θiIth harmonic wave
Phase；Q (k) is the observation at k moment, and P (k) is the observing matrix at k moment,For system noise matrix, ρ (k) is to see
Noise matrix is surveyed, y (k) is the systematic observation matrix at k moment；Y (k+1) is the systematic observation matrix at k+1 moment；f1、...、fNPoint
Not Wei each harmonic frequency；The value range of i is (1~N), and the value range of j is (1~N)；
S2.2：The extraction of fundametal compoment
Wherein, Δ w1It is the amplitude of fundametal compoment, θ1It is the phase of fundametal compoment, g1,1、g2,1Believe for the combination of fundametal compoment
Number；
S2.3：Protection signal is detected using kirchhoff electric current theorem.
Further, the step S3 includes the following steps：
S3.1：The selection of data window；
Take data window [t0-T,t0] current transformer detects in totally one cycle data are object, t0It is protected to detect
At the time of protecting actuating signal；
S3.2：In the data window, wavelet decomposition is modified to same group of all current transformers, specifically includes following step
Suddenly：
S3.2.1：The amendment of hierarchy parameters；
The amendment of hierarchy parameters is carried out by formula (3)：
Wherein H is revised hierarchy parameters, and fs is sample frequency, and f0 is fundamental frequency, and CEIL is the function that rounds up；
S3.2.2：The determination of threshold value；
Pass through threshold method preprocessed data shown in formula (4)：
Wherein, Ds is treated data, and D be the data of acquisition, and β is to correct flexible strategy, and ε is the threshold value of selection；
Using linear interpolation function, (4) formula is smoothed；
S3.2.3：Correct wavelet transformation
Wherein, f (t) be acquisition current signal, f'(t) be wavelet reconstruction jump signal；J, j+1 are wavelet decomposition
Decomposition order；T is time parameter；D is the power series of Scale Discreteness；aj,dFor the scale parameter of jth layer harmonic wave；aj,zIt is j layers
The approximating parameter of harmonic wave, aj+1,zFor the approximating parameter of j+1 layers of harmonic wave, bj,zFor the local feature parameter of j layers of harmonic wave, bj+1,zFor j+
The local feature parameter of 1 layer of harmonic wave；Z is the level of each harmonic；For scale space function；ψ (*) is wavelet mother function；h
(*) is low-pass filter function, realizes decomposition of the signal to low frequency part；G (*) is high-pass filtering function, realizes signal to high frequency
Partial decomposition；H is the number of plies where jump signal, aj,HFor wavelet reconstruction when jump signal where level approximating parameter,
bj,HFor wavelet reconstruction when jump signal where level local feature parameter；
S3.3：Power function optimizes；
To the jump signal f'(t of wavelet reconstruction) carry out sliding time integral；
Wherein, Ie(S) it is the power function after optimization, S is the beginning collection point of energy integral, and S+n is energy integral
Terminate collection point, n is the points of power integral；S adds 1 automatically after integral every time, carries out integrated power function optimization next time.
Further, the step S4 includes the following steps：
S4.1：Catastrophe point judges；
As power function Ie(S) when meeting formula (7), the rising edge end moment of power function is corresponded to this moment, i.e. mutation hair
The raw moment, while the initial time of peak value is also corresponded to, sampled point this moment is catastrophe point；σ is the threshold value that can be adjusted；
S4.2：The identification of CT saturation characteristic, follows the steps below：
S4.2.1：It analyses and compares to all respective catastrophe points of current transformer in same group：For a certain electric current
Mutual inductor, it is assumed that sampled point O is its catastrophe point, if other all current transformers occur to dash forward in the point simultaneously in same group
Become, then failure has occurred in the point moment, and all current transformers detect out of order generation simultaneously in the point；If in same group
Other current transformers all do not mutate in the point, illustrate that only there are one current transformers to occur to satisfy at this point in the group
With, and remaining current transformer is unsaturated in the point；
S4.2.2：After finding out the faulty and saturation point of institute, valid data section is extracted；For what is be not saturated
The data information of current transformer, the progress of disease is effective；For the current transformer being saturated, extraction fault point to thereafter the
Data segment between one saturation point is current transformer valid data section.
Advantageous effect：The present invention carries out differential protection calculating using Kalman filtering algorithm, can promote fundametal compoment and carry
The accuracy that the real-time and differential protection taken calculates；Traditional wavelet transformation is modified, and carries out power function optimization,
Singularity detection can be made more accurate；It can recognize that different failures and saturation moment, reply are rapidly saturated and interfere, and
And it being capable of timely open and protection when changing property failure；Correctness under various scenes and applicability, compared to time difference method
There is apparent advantage.
Description of the drawings
Fig. 1 is flow chart of the method for the present invention.
Specific implementation mode
Technical scheme of the present invention is further introduced With reference to embodiment.
Present embodiment discloses a kind of improved CT saturation characteristics recognizing method, as shown in Figure 1, packet
Include following steps：
S1：All current transformers for being connected to same busbar are divided into same group, acquisition current signal f (t)；
S2：Differential protection calculating is carried out using Kalman filtering algorithm extraction fundametal compoment, detects protection signal；
S2.1：The selection of Kalman filtering algorithm parameter
Wherein g1,j、g2,jTo represent the combination signal of jth layer harmonic wave；ΔuiFor the amplitude of ith harmonic wave；θiIth harmonic wave
Phase；Q (k) is the observation at k moment, and P (k) is the observing matrix at k moment,For system noise matrix, ρ (k) is to see
Noise matrix is surveyed, y (k) is the systematic observation matrix at k moment；Y (k+1) is the systematic observation matrix at k+1 moment；f1、...、fNPoint
Not Wei each harmonic frequency；The value range of i is (1~N), and the value range of j is (1~N)；
S2.2：The extraction of fundametal compoment
Wherein, Δ w1It is the amplitude of fundametal compoment, θ1It is the phase of fundametal compoment, g1,1、g2,1Believe for the combination of fundametal compoment
Number；
S2.3：Protection signal is detected using kirchhoff electric current theorem；
S3：Data window is chosen, wavelet transformation is modified to same group of all current transformers, power function optimizes；
S3.1：The selection of data window；
Take data window [t0-T,t0] current transformer detects in totally one cycle data are object, t0It is protected to detect
At the time of protecting actuating signal；
S3.2：In the data window, wavelet decomposition is modified to same group of all current transformers, specifically includes following step
Suddenly：
S3.2.1：The amendment of hierarchy parameters；
The amendment of hierarchy parameters is carried out by formula (3)：
Wherein H is revised hierarchy parameters, and fs is sample frequency, and f0 is fundamental frequency, and CEIL is the function that rounds up；
S3.2.2：The determination of threshold value；
Pass through threshold method preprocessed data shown in formula (4)：
Wherein, Ds is treated data, and D be the data of acquisition, and β is to correct flexible strategy, and ε is the threshold value of selection；
Using linear interpolation function, (4) formula is smoothed；
S3.2.3：Correct wavelet transformation
Wherein, f (t) be acquisition current signal, f'(t) be wavelet reconstruction jump signal；J, j+1 are wavelet decomposition
Decomposition order；T is time parameter；D is the power series of Scale Discreteness；aj,dFor the scale parameter of jth layer harmonic wave；aj,zIt is j layers
The approximating parameter of harmonic wave, aj+1,zFor the approximating parameter of j+1 layers of harmonic wave, bj,zFor the local feature parameter of j layers of harmonic wave, bj+1,zFor j+
The local feature parameter of 1 layer of harmonic wave；Z is the level of each harmonic；For scale space function；ψ (*) is wavelet mother function；h
(*) is low-pass filter function, realizes decomposition of the signal to low frequency part；G (*) is high-pass filtering function, realizes signal to high frequency
Partial decomposition；H is the number of plies where jump signal, aj,HFor wavelet reconstruction when jump signal where level approximating parameter,
bj,HFor wavelet reconstruction when jump signal where level local feature parameter；
S3.3：Power function optimizes；
To the jump signal f'(t of wavelet reconstruction) carry out sliding time integral；
Wherein, Ie(S) it is the power function after optimization, S is the beginning collection point of energy integral, and S+n is energy integral
Terminate collection point, n is the points of power integral；S adds 1 automatically after integral every time, carries out integrated power function optimization next time；
S4：Catastrophe point is detected, determines all catastrophe point positions, identifies CT saturation characteristic；
S4.1：Catastrophe point judges；
As power function Ie(S) when meeting formula (7), the rising edge end moment of power function is corresponded to this moment, i.e. mutation hair
The raw moment, while the initial time of peak value is also corresponded to, sampled point this moment is catastrophe point；σ is the threshold value that can be adjusted；
S4.2：The identification of CT saturation characteristic, follows the steps below：
S4.2.1：It analyses and compares to all respective catastrophe points of current transformer in same group：For a certain electric current
Mutual inductor, it is assumed that sampled point O is its catastrophe point, if other all current transformers occur to dash forward in the point simultaneously in same group
Become, then failure has occurred in the point moment, and all current transformers detect out of order generation simultaneously in the point；If in same group
Other current transformers all do not mutate in the point, illustrate that only there are one current transformers to occur to satisfy at this point in the group
With, and remaining current transformer is unsaturated in the point；
S4.2.2：After finding out the faulty and saturation point of institute, valid data section is extracted；For what is be not saturated
The data information of current transformer, the progress of disease is effective；For the current transformer being saturated, extraction fault point to thereafter the
Data segment between one saturation point is current transformer valid data section.
Claims (4)
1. a kind of improved CT saturation characteristics recognizing method, which is characterized in that include the following steps：
S1：All current transformers for being connected to same busbar are divided into same group, acquisition current signal f (t)；
S2：Differential protection calculating is carried out using Kalman filtering algorithm extraction fundametal compoment, detects protection signal；
S3：Data window is chosen, wavelet transformation is modified to same group of all current transformers, power function optimizes；
S4：Catastrophe point is detected, determines all catastrophe point positions, identifies CT saturation characteristic.
2. improved CT saturation characteristics recognizing method according to claim 1, it is characterised in that：The step
S2 includes the following steps：
S2.1：The selection of Kalman filtering algorithm parameter
Wherein g1,j、g2,jTo represent the combination signal of jth layer harmonic wave；ΔuiFor the amplitude of ith harmonic wave；θiThe phase of ith harmonic wave
Position；Q (k) is the observation at k moment, and P (k) is the observing matrix at k moment,For system noise matrix, ρ (k) is that observation is made an uproar
Sound matrix, y (k) are the systematic observation matrix at k moment；Y (k+1) is the systematic observation matrix at k+1 moment；f1、...、fNRespectively
The frequency of each harmonic；The value range of i is (1~N), and the value range of j is (1~N)；
S2.2：The extraction of fundametal compoment
Wherein, Δ w1It is the amplitude of fundametal compoment, θ1It is the phase of fundametal compoment, g1,1、g2,1For the combination signal of fundametal compoment；
S2.3：Protection signal is detected using kirchhoff electric current theorem.
3. improved CT saturation characteristics recognizing method according to claim 1, it is characterised in that：The step
S3 includes the following steps：
S3.1：The selection of data window；
Take data window [t0-T,t0] current transformer detects in totally one cycle data are object, t0To detect that protection is dynamic
At the time of making signal；
S3.2：In the data window, wavelet decomposition is modified to same group of all current transformers, specifically includes following steps：
S3.2.1：The amendment of hierarchy parameters；
The amendment of hierarchy parameters is carried out by formula (3)：
Wherein H is revised hierarchy parameters, and fs is sample frequency, and f0 is fundamental frequency, and CEIL is the function that rounds up；
S3.2.2：The determination of threshold value；
Pass through threshold method preprocessed data shown in formula (4)：
Wherein, Ds is treated data, and D be the data of acquisition, and β is to correct flexible strategy, and ε is the threshold value of selection；
Using linear interpolation function, (4) formula is smoothed；
S3.2.3：Correct wavelet transformation
Wherein, f (t) be acquisition current signal, f'(t) be wavelet reconstruction jump signal；J, j+1 are the decomposition of wavelet decomposition
The number of plies；T is time parameter；D is the power series of Scale Discreteness；aj,dFor the scale parameter of jth layer harmonic wave；aj,zFor j layers of harmonic wave
Approximating parameter, aj+1,zFor the approximating parameter of j+1 layers of harmonic wave, bj,zFor the local feature parameter of j layers of harmonic wave, bj+1,zIt is j+1 layers
The local feature parameter of harmonic wave；Z is the level of each harmonic；For scale space function；ψ (*) is wavelet mother function；h(*)
For low-pass filter function, decomposition of the signal to low frequency part is realized；G (*) is high-pass filtering function, realizes signal to high frequency section
Decomposition；H is the number of plies where jump signal, aj,HFor wavelet reconstruction when jump signal where level approximating parameter, bj,HFor
The local feature parameter of level where jump signal when wavelet reconstruction；
S3.3：Power function optimizes；
To the jump signal f'(t of wavelet reconstruction) carry out sliding time integral；
Wherein, Ie(S) it is the power function after optimization, S is the beginning collection point of energy integral, and S+n is that the end of energy integral is adopted
Collect point, n is the points of power integral；S adds 1 automatically after integral every time, carries out integrated power function optimization next time.
4. improved CT saturation characteristics recognizing method according to claim 1, it is characterised in that：The step
S4 includes the following steps：
S4.1：Catastrophe point judges；
As power function Ie(S) when meeting formula (7), the rising edge end moment of power function is corresponded to this moment, i.e., when mutation occurs
It carves, while also corresponding to the initial time of peak value, sampled point this moment is catastrophe point；σ is the threshold value that can be adjusted；
S4.2：The identification of CT saturation characteristic, follows the steps below：
S4.2.1：It analyses and compares to all respective catastrophe points of current transformer in same group：For a certain Current Mutual Inductance
Device, it is assumed that sampled point O is its catastrophe point, if other all current transformers mutate in the point simultaneously in same group,
Failure has occurred in the point moment, and all current transformers detect out of order generation simultaneously in the point；If other in same group
Current transformer does not all mutate in the point, illustrates only to be saturated at this point there are one current transformer in the group,
And remaining current transformer is unsaturated in the point；
S4.2.2：After finding out the faulty and saturation point of institute, valid data section is extracted；For the electric current not being saturated
The data information of mutual inductor, the progress of disease is effective；For the current transformer being saturated, extraction fault point is to first thereafter
Data segment between saturation point is current transformer valid data section.
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| CN112180315A (en) * | 2020-09-27 | 2021-01-05 | 国网江苏省电力有限公司电力科学研究院 | Fault feature extraction method, device and system for optical fiber current transformer |
| CN113315104A (en) * | 2021-07-14 | 2021-08-27 | 保定钰鑫电气科技有限公司 | Method for reducing differential protection misoperation |
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