CN104808109B - Based on ultra-high-tension power transmission line fault recognition method and the system of recorder data - Google Patents
Based on ultra-high-tension power transmission line fault recognition method and the system of recorder data Download PDFInfo
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Abstract
The invention provides a kind of ultra-high-tension power transmission line fault recognition method based on recorder data and system, method comprises step: obtain the circuit two ends of front and back wave recording device record occur ultra-high-tension power transmission line fault voltage waveform data and current waveform data; Respectively Fourier decomposition is carried out to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, then carry out voltage delay data and current slow data that Fourier decomposition obtains correspondence; Data are done normalized respectively, obtains the measured data after normalization and delayed data; Calculating current, voltage normalization measured data and the General Correlation Coefficient size between corresponding electric current, voltage normalization delayed data, judge transmission line malfunction type according to described General Correlation Coefficient.Said method, accuracy is higher.
Description
Technical field
The present invention relates to electric power project engineering field, particularly relate to a kind of ultra-high-tension power transmission line fault recognition method based on recorder data and the ultra-high-tension power transmission line fault finding system based on recorder data.
Background technology
Ultra-high-tension power transmission line is distributed in wide region, and the impact by various disaster and other environmental factor is serious, easily various types of fault occurs.According to the operating experience of electric system, the fault of usual transmission line of electricity can be divided into two kinds: transient fault and permanent fault.Transient fault refers to the insulator surface flashover caused by thunder and lightning etc., also has large wind-induced short, and the object such as birds and branch falls the short circuit caused on the line, and the electric discharge that under line, branch causes over the ground etc.This type of fault is after the isolating switch tripping of faulty line both sides, fault electric arc will after the physicochemical change of series of complex self-extinguish, before reclosing action, the insulation of trouble spot is restored to normal level substantially, after breaker closing, whole system can drop into normal operation, keeps continuing power supply to user.And permanent fault refers to because circuit falls the fault that tower, broken string, insulator breakdown or damage etc. cause.After the isolating switch tripping of faulty line both sides; the insulation of this type of trouble spot can not recover; after breaker closing; trouble spot still exists; circuit also will by relay protection tripping again; this not only brings a lot of negative effect to the safety of whole electric system, the continuity of stable operation hybrid power supply and reliability, may have a strong impact on the life-span of electrical equipment simultaneously.According to statistics, be single-line to ground fault more than 90% in extra high voltage network fault, and more than 80% be wherein transient fault.After single-line to ground fault transient fault occurs, make fault phase breaker closing fast, recover fault phase and power, effectively can improve stability and the power supply continuity of electric system.Therefore, when breaking down in system, fault type can be determined fast and accurately the safe and stable operation of electric system is had great importance.For transient fault, start reclosing fast to recover line powering; For permanent fault, lock-reclosing lock loop, avoids secondary pulse on the impact of system.
After transmission line of electricity breaks down, be widely used auto recloser and carry out recovery system and power, but traditional automatic reclosing can not identify the type of fault, the constant time lag through adjusting in advance after circuit breaker trip overlaps.If the permanent fault of coinciding with, then the impact caused electric system will much larger than first time fault.The adverse effect after reclosing failure do not considered by tradition reclosing.Adaptive reclose differentiates transient fault and permanent fault, mainly contains based on transient fault recovery voltage and the method based on transient fault arc characteristic.Based on the method for transient fault recovery voltage, can erroneous judgement be caused when capacitance voltage is less than line mutual-inductance voltage, there is dead band.Although revise the scope of application that criterion can improve criterion, calculate too complicated.In addition, along with the raising of line voltage grade, corresponding overvoltage level is more and more lower, needs the shunt reactor restriction extra-high voltage grid superpotential of installing some.Install after shunt reactor, the recovery voltage of circuit will lower, measuring error will be larger, the method for discrimination based on recovery voltage will be no longer applicable.Method based on transient fault arc characteristic all utilizes the harmonic wave of electric arc, and just disposal route is different.Method based on harmonic content and frequency range analysis needs higher sample frequency undoubtedly, and the introducing of artificial intelligence and wavelet technique too increases the complicacy of use.Along with the raising of line voltage grade, the application of super high-speed route protection device and high-speed circuit breaker makes an arc duration greatly shorten, and limits the application of the method based on an arc voltage theory of spectrum analysis; The harmonic component of arc voltage and the contradiction of CVT progress of disease band limiting also can affect the diagnostic result of the method.
In sum, the problem that the accuracy of the ultra-high-tension power transmission line fault recognition method existence identification of application is at present lower.
Summary of the invention
Based on this, be necessary, for the lower problem of the accuracy of the ultra-high-tension power transmission line fault recognition method existence identification of application at present, to provide a kind of ultra-high-tension power transmission line fault recognition method based on recorder data and the ultra-high-tension power transmission line fault finding system based on recorder data.
Based on a ultra-high-tension power transmission line fault recognition method for recorder data, comprise the following steps:
Obtain the circuit two ends of front and back wave recording device record occur ultra-high-tension power transmission line fault voltage waveform data and current waveform data;
Respectively Fourier decomposition is carried out to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, and carry out Fourier decomposition respectively, obtain corresponding voltage delay data and current slow data;
Described voltage measured data, practical measurement of current data, voltage delay data and current slow data respectively with the maximal value of the voltage in measured data for voltage normalization reference value, with the maximal value of the electric current in measured data for electric current normalization reference value, do normalized respectively, obtain voltage normalization measured data, electric current normalization measured data, voltage normalization delayed data and electric current normalization delayed data;
General Correlation Coefficient size between calculating voltage normalization measured data and corresponding voltage normalization delayed data, General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data, judges transmission line malfunction type according to the size of described General Correlation Coefficient and the regularity of distribution.
Based on a ultra-high-tension power transmission line fault finding system for recorder data, comprising:
, there is voltage waveform data and the current waveform data at the circuit two ends of front and back wave recording device record for obtaining ultra-high-tension power transmission line fault in acquisition module;
Decomposing module, for carrying out Fourier decomposition respectively to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, and carry out Fourier decomposition respectively, obtain corresponding voltage delay data and current slow data;
Normalizing module, for described voltage measured data, practical measurement of current data, voltage delay data and current slow data respectively with the maximal value of the voltage in measured data for voltage normalization reference value, with the maximal value of the electric current in measured data for electric current normalization reference value, do normalized respectively, obtain voltage normalization measured data, electric current normalization measured data, voltage normalization delayed data and electric current normalization delayed data;
Judge module, for the General Correlation Coefficient size between calculating voltage normalization measured data and corresponding voltage normalization delayed data, General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data, judges transmission line malfunction type according to the size of described General Correlation Coefficient and the regularity of distribution.
The above-mentioned ultra-high-tension power transmission line fault recognition method based on recorder data and system, to break down voltage, the current waveform data at circuit two ends of front and back wave recording device record by obtaining high voltage transmission line, then Fourier decomposition is carried out to Wave data, obtain measured data, simultaneously, the time interval of measured data according to setting is postponed, decomposes, obtain delayed data; Based on measured data and corresponding delayed data, calculate correlationship between the two, by the principle that the General Correlation Coefficient size of the data that break down and normal data is less, judge transmission line malfunction type, accuracy is higher.
Accompanying drawing explanation
Fig. 1 is the ultra-high-tension power transmission line fault recognition method process flow diagram of an embodiment based on recorder data;
Fig. 2 is an embodiment simulation circuit model schematic diagram;
Fig. 3 is an embodiment single-phase earthing transient fault sending end voltage oscillogram;
Fig. 4 is an embodiment single-phase earthing transient fault sending end current waveform figure;
Fig. 5 is an embodiment single-phase earthing transient fault receiving end voltage oscillogram;
Fig. 6 is an embodiment single-phase earthing transient fault receiving end current waveform figure;
Fig. 7 is an embodiment single-phase earthing permanent fault sending end voltage oscillogram;
Fig. 8 is an embodiment single-phase earthing permanent fault sending end current waveform figure;
Fig. 9 is an embodiment single-phase earthing permanent fault receiving end voltage oscillogram;
Figure 10 is an embodiment single-phase earthing permanent fault receiving end current waveform figure;
Figure 11 is the voltage oscillogram of an embodiment transient fault sending end 0.03S-0.13S;
Figure 12 is the voltage oscillogram of an embodiment transient fault sending end 0.23S-0.33S;
Figure 13 is the voltage oscillogram of an embodiment transient fault sending end 0.53S-0.63S;
Figure 14 is the voltage oscillogram of an embodiment transient fault receiving end 0.03S-0.13S;
Figure 15 is the voltage oscillogram of an embodiment transient fault receiving end 0.23S-0.33S;
Figure 16 is the voltage oscillogram of an embodiment transient fault receiving end 0.53S-0.63S;
Figure 17 is the voltage oscillogram of an embodiment permanent fault sending end 0.03S-0.13S;
Figure 18 is the voltage oscillogram of an embodiment permanent fault sending end 0.23S-0.33S;
Figure 19 is the voltage oscillogram of an embodiment permanent fault sending end 0.53S-0.63S;
Figure 20 is the voltage oscillogram of an embodiment permanent fault receiving end 0.03S-0.13S;
Figure 21 is the voltage oscillogram of an embodiment permanent fault receiving end 0.23S-0.33S;
Figure 22 is the voltage oscillogram of an embodiment permanent fault receiving end 0.53S-0.63S;
Zys1 related coefficient oscillogram when Figure 23 is an embodiment transient fault;
Zys2 related coefficient oscillogram when Figure 24 is an embodiment transient fault;
Zys3 related coefficient oscillogram when Figure 25 is an embodiment transient fault;
Zys1 related coefficient oscillogram when Figure 26 is an embodiment permanent fault;
Zys2 related coefficient oscillogram when Figure 27 is an embodiment permanent fault;
Zys3 related coefficient oscillogram when Figure 28 is an embodiment permanent fault;
Figure 29 is the ultra-high-tension power transmission line fault finding system structural representation of an embodiment based on recorder data.
Embodiment
Be described in detail below in conjunction with the embodiment of accompanying drawing to the ultra-high-tension power transmission line fault recognition method based on recorder data of the present invention and the ultra-high-tension power transmission line fault finding system based on recorder data.
Refer to Fig. 1, Fig. 1 is the ultra-high-tension power transmission line fault recognition method process flow diagram of an embodiment based on recorder data.
Based on a ultra-high-tension power transmission line fault recognition method for recorder data, comprise the following steps:
Step S101: obtain the circuit two ends of front and back wave recording device record occur ultra-high-tension power transmission line fault voltage waveform data and current waveform data;
In step S101, wave recording device can be fault oscillograph;
In one embodiment, the time interval of described setting can be 1,2 or 3 Operation of Electric Systems cycle.
General within the cycle of operation of 1-3 electric system, transient fault will return to normal level after reclosing action, is set to the accuracy that 1,2 or 3 Operation of Electric Systems length cycle length can improve follow-up failure judgement the time interval of setting.
Step S103: carry out Fourier decomposition respectively to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, and carry out Fourier decomposition respectively, obtain corresponding voltage delay data and current slow data;
In step s 103, corresponding delayed data is that measured data has the harmonic data of delay relatively in time, is equivalent to the phase place changing measured data, thus obtains corresponding delayed data.
In one embodiment, describedly carry out Fourier decomposition respectively to described voltage waveform data and current waveform data, obtain in the step of corresponding voltage measured data and practical measurement of current data, the formula of calculating voltage measured data is:
wherein u represents voltage measured data, and k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, U
mkrepresent voltage max;
The formula of calculating current measured data is:
wherein i represents practical measurement of current data, and k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, I
mkrepresent current maxima.
Further, in one embodiment, the described time interval described voltage waveform data and current waveform data being postponed setting, and carry out Fourier decomposition respectively, obtain in the step of corresponding voltage delay data and current slow data, the formula of calculating voltage delayed data is:
wherein k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, U
mkrepresent voltage max, τ represents the time interval of setting;
The formula of calculating current delayed data is:
wherein k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, I
mkrepresent current maxima, τ represents the time interval of setting.
Step S105: described voltage measured data, practical measurement of current data, voltage delay data and current slow data respectively with the maximal value of voltage for voltage normalization reference value, with the maximal value of electric current for electric current normalization reference value, do normalized respectively, obtain voltage normalization measured data, electric current normalization measured data, voltage normalization delayed data and electric current normalization delayed data;
In step S105, with the maximal value of voltage and current in described measured data for after reference value is normalized the measured data of correspondence and delayed data, the numerical range of measured data and delayed data will between zero and one, basis can be provided for subsequent calculations generalized correlation relation between the two, and also can improve the efficiency calculating generalized correlation relation.
In one embodiment, the time interval of described setting is selected according to the voltage waveform data of record ripple gained and the length of current waveform data, is usually set as the integral multiple in Operation of Electric Systems cycle.
Step S107: the General Correlation Coefficient size between calculating voltage normalization measured data and corresponding voltage normalization delayed data, General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data, judges transmission line malfunction type according to the size of described General Correlation Coefficient and the regularity of distribution.
In step s 107, when the harmonic data that normalization measured data is between age at failure, and the normalization delayed data of correspondence is when recovering normal harmonic data, both General Correlation Coefficient sizes are general less, if the normalization delayed data of correspondence is also the harmonic data between age at failure, so both General Correlation Coefficient sizes are general larger; The General Correlation Coefficient size between each normalization measured data and corresponding normalization delayed data calculating different overtone order is the rule in order to General Correlation Coefficient size both reflecting more accurately.
In one embodiment, the described variation tendency according to described General Correlation Coefficient size judges that transmission line malfunction type can comprise:
If described General Correlation Coefficient size is undergone mutation, then transmission line malfunction type is transient fault; If described General Correlation Coefficient size tends towards stability, then transmission line malfunction type is permanent fault.
Become again large from large to small when General Correlation Coefficient size or change from small to big, when namely undergoing mutation, transmission line malfunction type is transient fault; And if General Correlation Coefficient size tends towards stability, such as always larger, so transmission line malfunction type is permanent fault.
In one embodiment, the described size according to described General Correlation Coefficient and the regularity of distribution judge that transmission line malfunction type can comprise:
When the General Correlation Coefficient of the voltage after each time domain delay, electric current is greater than the first setting threshold value, being less than the second setting threshold value with the General Correlation Coefficient of data before fault, is permanent fault; Obtain weather monitoring system monitoring result at that time, be diagnosed as external force downtree or wind dance fault further;
When the voltage of each time domain delay, electric current General Correlation Coefficient are less than the 3rd setting threshold value, with the General Correlation Coefficient of data before fault be greater than the 4th set threshold value time, be diagnosed as transient fault; Acquisition meteorology or filthy monitoring system data contrast, and are diagnosed as pollution flashover, lightning or ice arcing fault further.
In one embodiment, General Correlation Coefficient size between described calculating voltage normalization measured data and corresponding voltage normalization delayed data, the step of the General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data comprises:
Each normalization measured data of different overtone order is converted to plural form with corresponding normalization delayed data, calculate General Correlation Coefficient between the two, the size of getting the mould of General Correlation Coefficient is General Correlation Coefficient size, and wherein, described plural form is:
k is overtone order, U
actual measurementrepresent voltage normalization measured data, U
postponerepresent voltage normalization delayed data, I
actual measurementrepresent electric current normalization measured data, I
postponerepresent electric current normalization delayed data, when plural number goes to zero, its argument is arbitrary.
In one embodiment, the described size according to described General Correlation Coefficient and the regularity of distribution can also comprise after judging transmission line malfunction type:
According to the regularity of distribution diagnosis change stake resistance fault of General Correlation Coefficient with the setting-up time interval postponed, its step is specially:
The General Correlation Coefficient of the electric current and voltage data after postponing, setting-up time interval with delay is first big after small, the variation tendency tended towards stability, and with fault before the General Correlation Coefficient of electric current and voltage data be less than the 5th set threshold value time, diagnosable for becoming stake resistance permanent fault;
Obtain the data of meteorology or filthy monitoring system at that time, and be diagnosed as downtree, foreign matter short circuit or wind dance fault further.
In one embodiment, the described size according to described General Correlation Coefficient and the regularity of distribution also comprise after judging transmission line malfunction type:
Obtain the data of the comparatively large and change of General Correlation Coefficient compared with away minor segment, the fault localization of the fault localization carrying out transmission line of electricity according to the size of described General Correlation Coefficient particularly transient fault.
The above-mentioned ultra-high-tension power transmission line fault recognition method based on recorder data, to break down voltage, the current waveform data at circuit two ends of front and back wave recording device record by obtaining high voltage transmission line, then Fourier decomposition is carried out to Wave data, obtain measured data, simultaneously, the time interval of measured data according to setting is postponed, decomposes, obtain delayed data; Based on measured data and corresponding delayed data, calculate correlationship between the two, by the principle that the General Correlation Coefficient size of the data that break down and normal data is less, judge transmission line malfunction type, accuracy is higher.
In order to further describe the ultra-high-tension power transmission line fault recognition method based on recorder data of the present invention in detail, be described below in conjunction with embody rule example.
By the wave recording device that ultra-high-tension power transmission line two ends are installed, in real time ripple is recorded to the electric current and voltage of circuit.With the electric current and voltage recorder data at ultra-high-tension power transmission line two ends for signal source, the record waveform in record ripple duration is intercepted according to time interval τ, then voltage long for the equal time at circuit two ends, current waveform data are carried out Fourier decomposition respectively, obtain series of harmonic, voltage harmonic expression formula is:
current harmonics expression formula is:
Then, the voltage current waveform data that ultra-high-tension power transmission line two ends equal time is long are time domain delay τ, and the ultra-high-tension power transmission line both end voltage electric current after postponing τ is carried out Fourier decomposition respectively, and obtain into series of harmonic, voltage delay harmonic wave expression formula is:
current slow harmonic wave expression formula is:
next, with the maximal value of the voltage of ultra-high-tension power transmission line both end voltage harmonic data for voltage normalization reference value, with the maximal value of the electric current of ultra-high-tension power transmission line two ends current harmonics data for electric current normalization reference value, normalized is done to ultra-high-tension power transmission line both end voltage, current harmonics data and voltage, current slow data.This is the basis of more each General Correlation Coefficient relative size.Then to having carried out the ultra-high-tension power transmission line both end voltage of normalized, current harmonics data calculate with corresponding delay voltage, current harmonics data respectively, obtain General Correlation Coefficient between the two, calculate the numeric distribution of the delay factor τ in time of General Correlation Coefficient size in record ripple duration.Fault type diagnosis is carried out according to the size of General Correlation Coefficient modulus value and the regularity of distribution.
This embody rule example combines voltage, the amplitude of electric current and phase information, and General Correlation Coefficient is plural number.When plural number goes to zero, its argument is arbitrary.The mould getting multiple correlation coefficient is the size of General Correlation Coefficient.
This embody rule example can diagnose permanent and transient fault according to General Correlation Coefficient with the regularity of distribution of τ.Also can gather the electric current and voltage data before fault simultaneously, carry out comprehensive descision, breakdown judge can be made more accurate.The General Correlation Coefficient of the ultra-high-tension power transmission line both end voltage after being normalized, current harmonics data and corresponding voltage, current slow data is comparatively large, and with fault before the General Correlation Coefficient of data less time, line fault is permanent fault; The General Correlation Coefficient of the ultra-high-tension power transmission line both end voltage after being normalized, current harmonics data and corresponding voltage, current slow data is less, and with fault before the related coefficient of data larger time, diagnosable is transient fault.Permanent fault also can be combined with monitoring systems such as meteorologies and judge, whether further diagnosis is the line fault that the reason such as external force downtree, wind dance causes.Transient fault can with the monitoring system Data Comparison such as meteorological, filthy, the reason such as whether can diagnose further be pollution flashover, lightning, ice sudden strain of a muscle causes.
This embody rule example can also according to the regularity of distribution diagnosis change stake resistance fault of General Correlation Coefficient with τ.When the General Correlation Coefficient of the ultra-high-tension power transmission line both end voltage be normalized, current harmonics data and corresponding voltage, current slow data, with being time delay first big after small, and tend towards stability, and during with the regularity of distribution that the related coefficient before fault is less, diagnosable for becoming stake resistance permanent fault.The stake resistance of trouble spot is first big after small or first little greatly rear.Combine with the data of the monitoring system such as meteorological, filthy, the permanent fault that the reasons such as downtree, foreign matter short circuit and wind dance cause can be diagnosed as further.
The time delay factor τ of this embody rule example, suitably can select according to the feature of each segment data during record ripple.Usually first select larger, and then reduce gradually, also can adaptable search.
The Changing Pattern of this embody rule example General Correlation Coefficient of trying to achieve delay factor τ in time, except for except the identification of fault type, also can be applicable to the fault localization of transmission line of electricity, icing, filthyly to detect.The fault localization of the fault localization of such as transmission line of electricity particularly transient fault, the comparatively large and change of General Correlation Coefficient is compared with the data of away minor segment, just fault localization can be carried out, and the less and change of General Correlation Coefficient is compared with the data of away minor segment, show that fault is recovered, the data of this section are not suitable for for fault localization.And (icing, filthy detect etc.) is estimated for circuit running status, the less and change of related coefficient is compared with the data (transient fault disappears) of away minor segment.
Refer to Fig. 2, Fig. 2 is an embodiment simulation circuit model schematic diagram.
For single-phase earthing transient fault and permanent fault, the recognition methods of this embody rule Instance failure will be described below.
In figure, LINERL represents ultra-high-tension power transmission line, V
1represent sending end fault place voltage, V
2represent receiving end fault place voltage.We with A phase (using circle mark) as fault phase.Grounding switch is closed when 0.03s, disconnect when 0.13s, transient fault is simulated with this, simulation result as shown in Figures 3 to 6, when can find out generation transient fault from Fig. 3 to Fig. 6, voltage, the current waveform of A phase distinguish very large with B (with square markings) phase, C (marking with triangle), and the waveform comparison of A, B, C phase is close after fault recovery; Grounding switch is closed when 0.03s, disconnects, simulate permanent fault with this at the end of emulation, simulation result as shown in Figure 7 to 10, as can be seen from Fig. 7 to Figure 10, upon a fault, voltage, the current waveform of A phase distinguish very large with B phase, C, and can continue.
For the ease of carrying out the comparison of General Correlation Coefficient, factor τ time delay is set to 0.1 second by us, and choose 0.03s ~ 0.13s, 0.23s ~ 0.33s respectively, the voltage oscillogram at 0.53s ~ 0.63s tri-time period circuit ultra-high-tension power transmission line two ends analyzes.The intercepting waveform of three time periods of transient fault is as shown in Figure 11 to Figure 16, the change along with the time can be found out from Figure 11 to Figure 16, the waveform of A phase differs larger with the waveform of B, C phase at 0.03s ~ 0.13s, then 0.23s ~ 0.33s, under 0.53s ~ 0.63s time period, three's waveform is more and more close, the intercepting waveform of three time periods of permanent fault as shown in FIG. 17 to 22, the change along with the time can be found out from Figure 17 to Figure 22, the waveform of A phase differs larger with the waveform of B, C phase, and always more stable, change very little.
According to overtone order, Generalized correlation analysis is carried out to the data gathered, as shown in Table 1 and Table 2, wherein, table 1 is transient fault correlation analysis result to the analysis result obtained, table 2 is permanent fault correlation analysis result, and harmonic wave 1-10 represents that overtone order is 1-10:
| Harmonic wave | 1 | 2 | 3 | 4 | 5 |
| Zys1 | 0.7345E+00 | 0.1928E+01 | 0.2330E+01 | 0.2561E+01 | 0.2956E+01 |
| Zys2 | 0.7026E+00 | 0.1883E+01 | 0.2287E+01 | 0.2517E+01 | 0.2919E+01 |
| Zys3 | 0.2278E+03 | 0.3593E+02 | 0.4088E+02 | 0.5393E+02 | 0.9484E+02 |
| Harmonic wave | 6 | 7 | 8 | 9 | 10 |
| Zys1 | 0.2770E+02 | 0.4716E+01 | 0.4607E+01 | 0.4146E+01 | 0.3743E+01 |
| Zys2 | 0.2771E+02 | 0.3740E+01 | 0.3680E+01 | 0.3782E+01 | 0.3896E+01 |
| Zys3 | 0.1599E+06 | 0.1181E+03 | 0.7823E+02 | 0.6640E+02 | 0.6160E+02 |
Table 1
| Harmonic wave | 1 | 2 | 3 | 4 | 5 |
| Zys1 | 0.5447E+01 | 0.4893E+01 | 0.5718E+01 | 0.7526E+01 | 0.1074E+02 |
| Zys2 | 0.1018E+03 | 0.1507E+02 | 0.1250E+02 | 0.1057E+02 | 0.1001E+02 |
| Zys3 | 0.2779E+01 | 0.4146E+02 | 0.2822E+02 | 0.4707E+02 | 0.9362E+02 |
| Harmonic wave | 6 | 7 | 8 | 9 | 10 |
| Zys1 | 0.1390E+05 | 0.1976E+02 | 0.2945E+02 | 0.4915E+02 | 0.8122E+02 |
| Zys2 | 0.2037E+03 | 0.8229E+01 | 0.6748E+01 | 0.6026E+01 | 0.5540E+01 |
| Zys3 | 0.2770E+03 | 0.3214E+03 | 0.1659E+03 | 0.1246E+03 | 0.1067E+03 |
Table 2
Utilize MATLAB to carry out analyzing and processing to the relative coefficient obtained, result as shown in Figure 23 to Figure 28, wherein, Zys1 related coefficient oscillogram when Figure 23 is an embodiment transient fault; Zys2 related coefficient oscillogram when Figure 24 is an embodiment transient fault; Zys3 related coefficient oscillogram when Figure 25 is an embodiment transient fault; Zys1 related coefficient oscillogram when Figure 26 is an embodiment permanent fault; Zys2 related coefficient oscillogram when Figure 27 is an embodiment permanent fault; Zys3 related coefficient oscillogram when Figure 28 is an embodiment permanent fault:
Zys1 represents the correlativity of I loop line 0.03s ~ 0.13s running status and 0.23s ~ 0.33s running status;
Zys2 represents the correlativity of I loop line 0.03s ~ 0.13s running status and 0.53s ~ 0.63s running status;
Zys3 represents the correlativity of I loop line 0.23s ~ 0.33s running status and 0.53s ~ 0.63s running status;
When there is transient fault, circuit is in malfunction in 0.03s ~ 0.13s, and time at 0.23s ~ 0.33s and in 0.53s ~ 0.63s time period, due to the effect of reclosing, circuit is restored to normal running status, therefore the numerical value of Zys1 and Zys2 is less, and time at 0.23s ~ 0.33s and in 0.53s ~ 0.63s time period, under circuit is all in normal operating condition, correlativity is larger, Zys3 numerical value is comparatively large, and diagnosable is transient fault.
When there is permanent fault, circuit is all in malfunction in 0.03s ~ 0.13s, 0.23s ~ 0.33s, 0.53s ~ 0.63s, and under being in same state, its correlativity is larger, therefore Zys1, Zys2, Zys3 numerical value is all comparatively large, and diagnosable is permanent fault.Simulation Example result confirms the validity and reliability of diagnostic method.
This embody rule example does not need to change first and second equipment of transmission system, does not need concrete structure parameter and the line parameter circuit value of transmission line of electricity, only needs the recorder data of ultra-high-tension power transmission line both end voltage and electric current, can guarantor's letter data of shared system.This embody rule example propose according to the method for General Correlation Coefficient with the regularity of distribution determination fault type of τ, be dynamic self-adapting to a certain extent, thus, have very strong operability and versatility.The diagnostic method that this embody rule example proposes is simple and practical, has very strong operability and versatility.Both can offline inspection, also can on-line monitoring.
Refer to Figure 29, Figure 29 is the ultra-high-tension power transmission line fault finding system of an embodiment based on recorder data.
Based on a ultra-high-tension power transmission line fault finding system for recorder data, comprising:
, there is voltage waveform data and the current waveform data at the circuit two ends of front and back wave recording device record for obtaining ultra-high-tension power transmission line fault in acquisition module 310;
Decomposing module 330, for carrying out Fourier decomposition respectively to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, and carry out Fourier decomposition respectively, obtain corresponding voltage delay data and current slow data;
Normalizing module 350, for described voltage measured data, practical measurement of current data, voltage delay data and current slow data respectively with the maximal value of voltage for voltage normalization reference value, with the maximal value of electric current for electric current normalization reference value, do normalized respectively, obtain voltage normalization measured data, electric current normalization measured data, voltage normalization delayed data and electric current normalization delayed data;
Judge module 370, for the General Correlation Coefficient size between calculating voltage normalization measured data and corresponding voltage normalization delayed data, General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data, judges transmission line malfunction type according to the size of described General Correlation Coefficient and the regularity of distribution.
The above-mentioned ultra-high-tension power transmission line fault finding system based on recorder data, to break down voltage, the current waveform data at circuit two ends of front and back wave recording device record by obtaining high voltage transmission line, then Fourier decomposition is carried out to Wave data, obtain measured data, simultaneously, the time interval of measured data according to setting is postponed, decomposes, obtain delayed data; Based on measured data and corresponding delayed data, calculate correlationship between the two, by the principle that the General Correlation Coefficient size of the data that break down and normal data is less, judge transmission line malfunction type, accuracy is higher.
Gather in an embodiment, described judge module 370 can comprise:
Modular converter, for each normalization measured data of different overtone order is converted to plural form with corresponding normalization delayed data, calculate General Correlation Coefficient between the two, the size of getting the mould of General Correlation Coefficient is General Correlation Coefficient size, wherein, described plural form is:
k is overtone order, U
actual measurementrepresent voltage normalization measured data, U
postponerepresent voltage normalization delayed data, I
actual measurementrepresent electric current normalization measured data, I
postponerepresent electric current normalization delayed data, when plural number goes to zero, its argument is arbitrary.
Ultra-high-tension power transmission line fault finding system based on recorder data of the present invention and the ultra-high-tension power transmission line fault recognition method one_to_one corresponding based on recorder data of the present invention, the technical characteristic of setting forth in the embodiment of the above-mentioned ultra-high-tension power transmission line fault recognition method based on recorder data and beneficial effect thereof are all applicable to, in the embodiment based on the ultra-high-tension power transmission line fault finding system of recorder data, hereby state.
The above embodiment only have expressed several embodiment of the present invention, and it describes comparatively concrete and detailed, but therefore can not be interpreted as the restriction to the scope of the claims of the present invention.It should be pointed out that for the person of ordinary skill of the art, without departing from the inventive concept of the premise, can also make some distortion and improvement, these all belong to protection scope of the present invention.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (9)
1., based on a ultra-high-tension power transmission line fault recognition method for recorder data, it is characterized in that, comprise the following steps:
Obtain the circuit two ends of front and back wave recording device record occur ultra-high-tension power transmission line fault voltage waveform data and current waveform data;
Respectively Fourier decomposition is carried out to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, and carry out Fourier decomposition respectively, obtain corresponding voltage delay data and current slow data;
Described voltage measured data, practical measurement of current data, voltage delay data and current slow data respectively with the maximal value of the voltage in measured data for voltage normalization reference value, with the maximal value of the electric current in measured data for electric current normalization reference value, do normalized respectively, obtain voltage normalization measured data, electric current normalization measured data, voltage normalization delayed data and electric current normalization delayed data;
General Correlation Coefficient size between calculating voltage normalization measured data and corresponding voltage normalization delayed data, General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data, judges transmission line malfunction type according to the size of described General Correlation Coefficient and the regularity of distribution.
2. the ultra-high-tension power transmission line fault recognition method based on recorder data according to claim 1, it is characterized in that, respectively Fourier decomposition is carried out to described voltage waveform data and current waveform data, obtain in the step of corresponding voltage measured data and practical measurement of current data, the formula of calculating voltage measured data is:
wherein u represents voltage measured data, and k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, U
mkrepresent voltage max; The formula of calculating current measured data is:
wherein i represents practical measurement of current data, and k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, I
mkrepresent current maxima.
3. the ultra-high-tension power transmission line fault recognition method based on recorder data according to claim 1, it is characterized in that, the described time interval described voltage waveform data and current waveform data being postponed setting, and carry out Fourier decomposition respectively, obtain in the step of corresponding voltage delay data and current slow data, the formula of calculating voltage delayed data is:
wherein k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, U
mkrepresent voltage max, τ represents the time interval of setting; The formula of calculating current delayed data is:
wherein k represents overtone order, and ω represents frequency, ψ
ukrepresent phase place, I
mkrepresent current maxima, τ represents the time interval of setting.
4. the ultra-high-tension power transmission line fault recognition method based on recorder data according to claim 1, it is characterized in that, the time interval of described setting is selected according to the voltage waveform data of record ripple gained and the length of current waveform data, is usually set as the integral multiple in Operation of Electric Systems cycle.
5. the ultra-high-tension power transmission line fault recognition method based on recorder data according to claim 1, is characterized in that, the described size according to described General Correlation Coefficient and the regularity of distribution judge that transmission line malfunction type comprises:
When the General Correlation Coefficient of the voltage after each time domain delay, electric current is greater than the first setting threshold value, being less than the second setting threshold value with the General Correlation Coefficient of data before fault, is permanent fault; Obtain weather monitoring system monitoring result at that time, be diagnosed as external force downtree or wind dance fault further;
When the voltage of each time domain delay, electric current General Correlation Coefficient are less than the 3rd setting threshold value, with the General Correlation Coefficient of data before fault be greater than the 4th set threshold value time, be diagnosed as transient fault; Acquisition meteorology or filthy monitoring system data contrast, and are diagnosed as pollution flashover, lightning or ice arcing fault further.
6. the ultra-high-tension power transmission line fault recognition method based on recorder data according to claim 1, it is characterized in that, General Correlation Coefficient size between described calculating voltage normalization measured data and corresponding voltage normalization delayed data, the step of the General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data comprises:
Each normalization measured data of different overtone order is converted to plural form with corresponding normalization delayed data, calculate General Correlation Coefficient between the two, the size of getting the mould of General Correlation Coefficient is General Correlation Coefficient size, and wherein, described plural form is:
k is overtone order, U
actual measurementrepresent voltage normalization measured data, U
postponerepresent voltage normalization delayed data, I
actual measurementrepresent electric current normalization measured data, I
postponerepresent electric current normalization delayed data, when plural number goes to zero, its argument is arbitrary.
7. the ultra-high-tension power transmission line fault recognition method based on recorder data according to claim 1, it is characterized in that, the described size according to described General Correlation Coefficient and the regularity of distribution also comprise after judging transmission line malfunction type: according to the regularity of distribution diagnosis change stake resistance fault of General Correlation Coefficient with the setting-up time interval postponed, its step is specially:
The General Correlation Coefficient of the electric current and voltage data after postponing, setting-up time interval with delay is first big after small, the variation tendency tended towards stability, and with fault before the General Correlation Coefficient of electric current and voltage data be less than the 5th set threshold value time, diagnosable for becoming stake resistance permanent fault; Obtain the data of meteorology or filthy monitoring system at that time, and be diagnosed as downtree, foreign matter short circuit or wind dance fault further.
8., based on a ultra-high-tension power transmission line fault finding system for recorder data, it is characterized in that, comprising:
, there is voltage waveform data and the current waveform data at the circuit two ends of front and back wave recording device record for obtaining ultra-high-tension power transmission line fault in acquisition module;
Decomposing module, for carrying out Fourier decomposition respectively to described voltage waveform data and current waveform data, obtains corresponding voltage measured data and practical measurement of current data; Described voltage waveform data and current waveform data are postponed the time interval of setting, and carry out Fourier decomposition respectively, obtain corresponding voltage delay data and current slow data;
Normalizing module, for described voltage measured data, practical measurement of current data, voltage delay data and current slow data respectively with the maximal value of the voltage in measured data for voltage normalization reference value, with the maximal value of the electric current in measured data for electric current normalization reference value, do normalized respectively, obtain voltage normalization measured data, electric current normalization measured data, voltage normalization delayed data and electric current normalization delayed data;
Judge module, for the General Correlation Coefficient size between calculating voltage normalization measured data and corresponding voltage normalization delayed data, General Correlation Coefficient size between calculating current normalization measured data and corresponding electric current normalization delayed data, judges transmission line malfunction type according to the size of described General Correlation Coefficient and the regularity of distribution.
9. the ultra-high-tension power transmission line fault finding system based on recorder data according to claim 8, it is characterized in that, described judge module comprises:
Modular converter, for each normalization measured data of different overtone order is converted to plural form with corresponding normalization delayed data, calculate General Correlation Coefficient between the two, the size of getting the mould of General Correlation Coefficient is General Correlation Coefficient size, wherein, described plural form is:
k is overtone order, U
actual measurementrepresent voltage normalization measured data, U
postponerepresent voltage normalization delayed data, I
actual measurementrepresent electric current normalization measured data, I
postponerepresent electric current normalization delayed data, when plural number goes to zero, its argument is arbitrary.
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