CN104360192A - Electromagnetic disturbance waveform feature extracting method for transformer substation gas insulation switch - Google Patents
Electromagnetic disturbance waveform feature extracting method for transformer substation gas insulation switch Download PDFInfo
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Abstract
The invention relates to an electromagnetic disturbance waveform feature extracting method for a transformer substation gas insulation switch and belongs to the field of the electromagnetic compatibility technology for secondary equipment of transformer substations. The electromagnetic disturbance waveform feature extracting method for the transformer substation gas insulation switch specially comprises the steps that when on-off operation is conducted on an GIS transformation substation under different voltage classes, electromagnetic disturbance waveform data of the port of a sensor on a GIS pipeline or the port of an intelligent component in a GIS collection control cabinet are measured and recorded; the obtained electromagnetic disturbance waveform data are calculated according to a formula for the common-mode voltage and difference-mode voltage in electromagnetic compatibility conducted interference, so that a common-mode interference waveform and a difference-mode interference waveform are obtained; macroscopic feature parameters and microscopic feature parameters are extracted respectively. By the adoption of the electromagnetic disturbance waveform feature extracting method for the transformer substation gas insulation switch, all macroscopic feature parameters and all microscopic feature parameters of disturbance waveforms can be obtained reliably and accurately, and quantitative analysis of the waveforms of electromagnetic disturbance caused by on-off operation of the GIS transformation substation is achieved.
Description
Technical field
The invention belongs to substation secondary device technical field of electromagnetic compatibility, in particular to the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch, be the extracting method of the waveform character of the electromagnetic disturbance that a kind of GIS switching operation in substation causes specifically.
Background technology
It is little that gas-insulated switchgear (GIS) transformer station has floor area, good airproof performance, and affected by environment little, operational reliability is high, and the time between overhauls(TBO) is long, and maintenance workload is few, and operating cost is low waits remarkable advantage, and in China, electrical network is widely applied.During isolator operation in GIS, produce the row ripple that wave head is very steep, after catadioptric occurs repeatedly these row ripples in GIS, form very fast transient overvoltage.When it arrives sleeve pipe, a transient electromagnetic wave part is coupled on pole line, propagates along pole line, and then forms coup injury to the insulation of the electrical equipments such as the transformer be connected with GIS, overhead transmission line; Another part is then coupled between shell and ground, forms GIS shell transient state earth potential and raises, and then be coupled to secondary device port formation electromagnetic disturbance, threaten to the safe and reliable operation of secondary device.
The completely different electromagnetic disturbance waveform caused in lightning impulse and short trouble of waveform character of the electromagnetic disturbance that GIS switching operation in substation causes, to the threat of secondary device also comparatively after both are larger.And the electric fast transient pulse train electromagnetic compatibility test set up to check secondary device to resist the ability of this harassing and wrecking, its electromagnetic disturbance waveform caused for the GIS switching operation in substation of the reference waveform checked and actual measurement has a lot of difference fundamentally; And quantize these differences, with regard to needing, feature extraction is carried out to a large amount of measured waveform data.At present, still lack the extracting method of the waveform character of the electromagnetic disturbance that a kind of reliable GIS switching operation in substation causes, this is meaning of the present invention just.
Summary of the invention
The electromagnetic disturbance waveform feature extracting method that the object of the invention is to provide a kind of transformer station gas-insulated switch is characterized in that, specifically comprises following steps:
Step 1: during GIS switching operation in substation under different electric pressure, surveys the electromagnetic disturbance Wave data of intelligent assembly port a in the simulation convergence control cabinet of analog sensor port A or GIS on record GIS pipeline;
Step 2: by the formulae discovery of common mode voltage and differential mode voltage in electromagnetic compatibility conduction interference, common mode interference waveform and differential mode interference waveform are obtained to the electromagnetic disturbance Wave data obtained in step 1;
Step 3: macrofeature parameter is extracted respectively to the common mode interference waveform obtained in step 2 and differential mode interference waveform;
Step 4: microscopic feature parameter is extracted respectively to the common mode interference waveform obtained in step 2 and differential mode interference waveform.
In described step 1, the measuring system surveying record electromagnetic disturbance waveform will have good electromagnet shield effect to ensure to survey the effectively reliable of record data.
In described step 2, common mode interference waveform and differential mode interference waveform will carry out equivalent obtaining in strict accordance with the three-port network of tested Two-port netwerk and port device earth terminal composition.
In described step 3, the macrofeature parameter of single interference waveform comprises:
Grand pulse peak peak value: the difference of interference waveform maxima and minima;
Grand pulse peak-peak: in interference waveform, maxima and minima compares larger that of absolute value;
The grand duration of pulse: first scarcely perceptible pulse is flushed to the time of last micropulse from interference waveform;
Micropulse number: the number of whole micropulse in interference waveform;
Micropulse interval time: the mistiming between every two micropulses.
In described step 3, specifically comprise following steps:
Step 31: the data obtaining common mode interference waveform and differential mode interference waveform in step 2 are discrete-time series, carry out global search to it, obtain the maximal value Max in waveform and minimum M in, both subtract each other to obtain grand pulse peak peak value Vpp;
Step 32: maximal value Max will be obtained in step 31 and minimum M in takes absolute value, then compare, get larger value as grand pulse peak-peak;
Step 33: according to pre-determined amplitude threshold values Th1, extract all absolute time Twm being greater than the micropulse peak-peak place of threshold values Th1 in interference waveform, in one-dimension array Twm, the number of data is micropulse number;
Step 34: sorted from small to large by the one-dimension array Twm obtained in step 33, then calculates the mistiming of adjacent 2, obtains one digit number group Td, is micropulse interval time.
In described step 33, specifically comprise following steps:
Step 331: carry out global search by obtaining interference waveform data in step 2, obtains position Ind and the absolute time Twm1 at peak-peak place;
Step 332: according to pre-determined distance threshold values Th2, by Th2 the Wave data zero setting of putting of the position Ind and neighbouring symmetry that obtain peak-peak place in step 331;
Step 333: the interference waveform data after process in step 332 are carried out global search, obtains position Ind1 and the absolute time Twm2 at peak-peak place;
Step 334: repeat step 332 and step 333, until peak value not large than amplitude threshold values Th1 in Wave data.
In described step 4, the microscopic feature parameter of micropulse in interference waveform comprises:
The micropulse duration: the time from pulse waveform rises to being substantially submerged in neighbourhood noise;
The micropulse rise time: the time of micropulse peak-peak place peak value from 10% to 90%;
Micropulse dominant frequency distributes: the frequency of main frequency in micropulse amplitude versus frequency characte.
In described step 4, specifically comprise following steps:
Step 41: carry out global search by obtaining interference waveform data in step 2, obtain the position Ind at peak-peak place, the Wave data of Th2 of Ind and neighbouring symmetry point is extracted in two-dimensional array Pulse, and by Th2 Wave data zero setting in former array of putting of Ind and neighbouring symmetry;
Step 42: repeat step 41 until all extract in two-dimensional array Pulse by the micropulse waveform at the peak value place being greater than amplitude threshold values Th1, each provisional capital of two-dimensional array Pulse is one group of micropulse Wave data;
Step 43: utilize wavelet transformation to carry out noise reduction process the every data line in the two-dimensional array Pulse obtained in step 42, obtains new 2-D data Pulse1;
Step 44: according to pre-determined rate of change threshold values Th3, its rate of change is all calculated by obtaining every data line in two-dimensional array Pulse1 in step 43, each row of data rate of change first is greater than Th3 absolute time and is designated as Pstart, often going last absolute time being greater than Th3 is designated as Pend, and the micropulse duration, Pd just equaled the difference of Pstart and Pend;
Step 45: according to pre-determined amplitude threshold values Th4, the whole zero setting of data that absolute value in the two-dimensional array Pulse obtained in step 42 is less than Th4 is obtained Pulse2, then extract in two-dimensional array Pulse2 every a line all meet 2, left and right different time be that the position at the zero point of 00 forms two-dimensional array Zero;
Step 46: carrying out global search by obtaining two-dimensional array Pulse2 in step 45, obtaining the position Tmax of the maximal value of every a line.It is compared with the null position of corresponding row in Zero, Zm at zero point nearest apart from Tm before obtaining Tm, get the Zm-2 at 2 places before Zm in Zero again, in Pulse2, find the position Tmin of the minimum value between Zm-2 and Zm, then the difference that is approximately equal to Tmax and Tmin is multiplied by 0.8 the micropulse rise time;
Step 47: each row of the two-dimensional array Pulse obtained in step 42 is carried out Fourier transform, gets to the matrix obtained the amplitude versus frequency characte Zfft that amplitude obtains micropulse, and Zfft gets several frequencies that amplitude is larger, namely obtains the dominant frequency distribution of micropulse.
The invention has the beneficial effects as follows that this extracting method can obtain harassing whole macrofeature parameters and the microscopic feature parameter of waveform reliably, accurately, to realize the quantitative analysis of the waveform to the electromagnetic disturbance that GIS switching operation in substation causes.
Accompanying drawing explanation
Fig. 1 is system under test (SUT) schematic diagram.
Fig. 2 is the waveshape feature abstraction process flow diagram of the electromagnetic disturbance that GIS switching operation in substation causes.
Fig. 3 is testing apparatus schematic diagram.
Fig. 4 is microscopic feature parameter extracting method process flow diagram.
Fig. 5 is typical interference waveform, (a) typical common mode interference waveform; (b) typical differential mode interference waveform.
Fig. 6 is the distribution of typical micropulse dominant frequency.
Embodiment
The invention provides the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch, below according to Fig. 1 ~ 6, illustrate preferred embodiment of the present invention.
The waveshape feature abstraction process flow diagram of the electromagnetic disturbance that the test macro schematic diagram according to Fig. 1 and the GIS switching operation in substation shown in Fig. 2 cause.The extracting method of the waveform character of the electromagnetic disturbance that described GIS switching operation in substation causes specifically comprises following steps:
Step 1: during GIS switching operation in substation under different electric pressure, surveys the electromagnetic disturbance Wave data of intelligent assembly port a in analog sensor port A on record GIS pipeline or GIS convergence control cabinet; The measuring system surveying record electromagnetic disturbance waveform will have good electromagnet shield effect to ensure to survey the effectively reliable of record data.
Step 2: by the formulae discovery of common mode voltage and differential mode voltage in electromagnetic compatibility conduction interference, the common mode interference waveform Uc as shown in formula (1) the below and differential mode interference waveform Ud Ru shown in formula (2) is below obtained to the electromagnetic disturbance Wave data obtained in above-mentioned steps 1; Common mode interference waveform and differential mode interference waveform will carry out equivalent obtaining (as shown in Figure 3) in strict accordance with the three-port network of tested port and port device earth terminal composition.
Step 3: extract macrofeature parameter.To the common mode interference waveform obtained in above-mentioned steps 2 and differential mode interference waveform [common mode interference waveform as typical in Fig. 5 (a); The typical differential mode interference waveform of Fig. 5 (b)] extract macrofeature parameter respectively, specifically comprise:
Grand pulse peak peak value: the difference of interference waveform maxima and minima;
Grand pulse peak-peak: in interference waveform, maxima and minima compares larger that of absolute value;
The grand duration of pulse: first scarcely perceptible pulse is flushed to the time of last micropulse from interference waveform;
Micropulse number: the number of whole micropulse in interference waveform;
Micropulse interval time: the mistiming between every two micropulses.
Step 3: extract macrofeature parameter, macrofeature parameter is extracted respectively to the common mode interference waveform obtained in above-mentioned steps 2 and differential mode interference waveform, specifically comprises the following steps:
Step 31: the data obtaining common mode interference waveform and differential mode interference waveform in step 2 are discrete-time series, carry out global search to it, obtain the maximal value Max in waveform and minimum M in, both subtract each other to obtain grand pulse peak peak value Vpp;
Step 32: maximal value Max will be obtained in step 31 and minimum M in takes absolute value, then compare, get larger value as grand pulse peak-peak;
Step 33: according to pre-determined amplitude threshold values Th1, extract all absolute time Twm being greater than the micropulse peak-peak place of threshold values Th1 in interference waveform, in one-dimension array Twm, the number of data is micropulse number; , specifically comprise the following steps:
Step 331: carry out global search by obtaining interference waveform data in step 2, obtains position Ind and the absolute time Twm1 at peak-peak place;
Step 332: according to pre-determined distance threshold values Th2, by Th2 the Wave data zero setting of putting of the position Ind and neighbouring symmetry that obtain peak-peak place in step 331;
Step 333: the interference waveform data after process in step 332 are carried out global search, obtains position Ind1 and the absolute time Twm2 at peak-peak place;
Step 334: repeat step 332 and step 333, until peak value not large than amplitude threshold values Th1 in Wave data.
Step 34: sorted from small to large by the one-dimension array Twm obtained in step 33, then calculates the mistiming of adjacent 2, obtains one digit number group Td, is micropulse interval time.
Step 4: extract microscopic feature parameter.Microscopic feature parameter is extracted respectively to the common mode interference waveform obtained in above-mentioned steps 2 and differential mode interference waveform; Specifically comprise:
The micropulse duration: the time from pulse waveform rises to being substantially submerged in neighbourhood noise;
The micropulse rise time: the time of micropulse peak-peak place peak value from 10% to 90%;
Micropulse dominant frequency distributes: the frequency of main frequency in micropulse amplitude versus frequency characte.
Microscopic feature parameter is extracted: microscopic feature parameter is extracted respectively to the common mode interference waveform obtained in above-mentioned steps 2 and differential mode interference waveform, specifically comprises the following steps: according to the microscopic feature parameter extracting method process flow diagram shown in Fig. 4
Step 41: carry out global search by obtaining interference waveform data in step 2, obtain the position Ind at peak-peak place, the Wave data of Th2 of Ind and neighbouring symmetry point is extracted in two-dimensional array Pulse, and by Th2 Wave data zero setting in former array of putting of Ind and neighbouring symmetry;
Step 42: repeat step 41 until all extract in two-dimensional array Pulse by the micropulse waveform at the peak value place being greater than amplitude threshold values Th1, each provisional capital of two-dimensional array Pulse is one group of micropulse Wave data;
Step 43: utilize wavelet transformation to carry out noise reduction process the every data line in the two-dimensional array Pulse obtained in step 42, obtains new 2-D data Pulse1;
Step 44: according to pre-determined rate of change threshold values Th3, its rate of change is all calculated by obtaining every data line in two-dimensional array Pulse1 in step 43, each row of data rate of change first is greater than Th3 absolute time and is designated as Pstart, often going last absolute time being greater than Th3 is designated as Pend, and the micropulse duration, Pd just equaled the difference of Pstart and Pend;
Step 45: according to pre-determined amplitude threshold values Th4, the whole zero setting of data that absolute value in the two-dimensional array Pulse obtained in step 42 is less than Th4 is obtained Pulse2, then extract in two-dimensional array Pulse2 every a line all meet 2, left and right different time be that the position at the zero point of zero condition forms two-dimensional array Zero;
Step 46: carrying out global search by obtaining two-dimensional array Pulse2 in step 45, obtaining the position Tmax of the maximal value of every a line.It is compared with the null position of corresponding row in Zero, Zm at zero point nearest apart from Tm before obtaining Tm, get the Zm-2 at 2 places before Zm in Zero again, in Pulse2, find the position Tmin of the minimum value between Zm-2 and Zm, then the difference that is approximately equal to Tmax and Tmin is multiplied by 0.8 the micropulse rise time;
Step 47: each row of the two-dimensional array Pulse obtained in step 42 is carried out Fourier transform, the amplitude versus frequency characte Zfft that amplitude obtains micropulse is got to the matrix obtained, Zfft gets several frequencies that amplitude is larger, namely obtains the dominant frequency of micropulse: 0.75MHz, 1.125MHz, 17MHz, 38.25MHz distribute (as shown in Figure 6).
Claims (8)
1. an electromagnetic disturbance waveform feature extracting method for transformer station's gas-insulated switch, is characterized in that, specifically comprise following steps:
Step 1: during GIS switching operation in substation under different electric pressure, surveys the electromagnetic disturbance Wave data of intelligent assembly port in sensor port on record GIS pipeline or GIS convergence control cabinet;
Step 2: by the formulae discovery of common mode voltage and differential mode voltage in electromagnetic compatibility conduction interference, common mode interference waveform and differential mode interference waveform are obtained to the electromagnetic disturbance Wave data obtained in step 1;
Step 3: macrofeature parameter is extracted respectively to the common mode interference waveform obtained in step 2 and differential mode interference waveform;
Step 4: microscopic feature parameter is extracted respectively to the common mode interference waveform obtained in step 2 and differential mode interference waveform.
2. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 1, it is characterized in that, in described step 1, the measuring system surveying record electromagnetic disturbance waveform will have good electromagnet shield effect to ensure to survey the effectively reliable of record data.
3. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 1, it is characterized in that, in described step 2, common mode interference waveform and differential mode interference waveform will carry out equivalent obtaining in strict accordance with the three-port network of tested Two-port netwerk and port device earth terminal composition.
4. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 1, it is characterized in that, in described step 3, the macrofeature parameter of single interference waveform comprises:
Grand pulse peak peak value: the difference of interference waveform maxima and minima;
Grand pulse peak-peak: in interference waveform, maxima and minima compares larger that of absolute value;
The grand duration of pulse: first scarcely perceptible pulse is flushed to the time of last micropulse from interference waveform;
Micropulse number: the number of whole micropulse in interference waveform;
Micropulse interval time: the mistiming between every two micropulses.
5. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 1, is characterized in that, in described step 3, specifically comprise following steps:
Step 31: the data obtaining common mode interference waveform and differential mode interference waveform in step 2 are discrete-time series, carry out global search to it, obtain the maximal value Max in waveform and minimum M in, both subtract each other to obtain grand pulse peak peak value Vpp;
Step 32: maximal value Max will be obtained in step 31 and minimum M in takes absolute value, then compare, get larger value as grand pulse peak-peak;
Step 33: according to pre-determined amplitude threshold values Th1, extract all absolute time Twm being greater than the micropulse peak-peak place of threshold values Th1 in interference waveform, in one-dimension array Twm, the number of data is micropulse number;
Step 34: sorted from small to large by the one-dimension array Twm obtained in step 33, then calculates the mistiming of adjacent 2, obtains one digit number group Td, is micropulse interval time.
6. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 5, is characterized in that, in described step 33, specifically comprise following steps:
Step 331: carry out global search by obtaining interference waveform data in step 2, obtains position Ind and the absolute time Twm1 at peak-peak place;
Step 332: according to pre-determined distance threshold values Th2, by Th2 the Wave data zero setting of putting of the position Ind and neighbouring symmetry that obtain peak-peak place in step 331;
Step 333: the interference waveform data after process in step 332 are carried out global search, obtains position Ind1 and the absolute time Twm2 at peak-peak place;
Step 334: repeat step 332 and step 333, until peak value not large than amplitude threshold values Th1 in Wave data.
7. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 1, it is characterized in that, in described step 4, the microscopic feature parameter of micropulse in interference waveform comprises:
The micropulse duration: the time from pulse waveform rises to being substantially submerged in neighbourhood noise;
The micropulse rise time: the time of micropulse peak-peak place peak value from 10% to 90%;
Micropulse dominant frequency distributes: the frequency of main frequency in micropulse amplitude versus frequency characte.
8. the electromagnetic disturbance waveform feature extracting method of a kind of transformer station gas-insulated switch according to claim 1, is characterized in that, in described step 4, specifically comprise following steps:
Step 41: carry out global search by obtaining interference waveform data in step 2, obtain the position Ind at peak-peak place, the Wave data of Th2 of Ind and neighbouring symmetry point is extracted in two-dimensional array Pulse, and by Th2 Wave data zero setting in former array of putting of Ind and neighbouring symmetry;
Step 42: repeat step 41 until all extract in two-dimensional array Pulse by the micropulse waveform at the peak value place being greater than amplitude threshold values Th1, each provisional capital of two-dimensional array Pulse is one group of micropulse Wave data;
Step 43: utilize wavelet transformation to carry out noise reduction process the every data line in the two-dimensional array Pulse obtained in step 42, obtains new 2-D data Pulse1;
Step 44: according to pre-determined rate of change threshold values Th3, its rate of change is all calculated by obtaining every data line in two-dimensional array Pulse1 in step 43, each row of data rate of change first is greater than Th3 absolute time and is designated as Pstart, often going last absolute time being greater than Th3 is designated as Pend, and the micropulse duration, Pd just equaled the difference of Pstart and Pend;
Step 45: according to pre-determined amplitude threshold values Th4, the whole zero setting of data that absolute value in the two-dimensional array Pulse obtained in step 42 is less than Th4 is obtained Pulse2, then extract in two-dimensional array Pulse2 every a line all meet 2, left and right different time be that the position at the zero point of 00 forms two-dimensional array Zero;
Step 46: carrying out global search by obtaining two-dimensional array Pulse2 in step 45, obtaining the position Tmax of the maximal value of every a line; It is compared with the null position of corresponding row in Zero, Zm at zero point nearest apart from Tm before obtaining Tm, get the Zm-2 at 2 places before Zm in Zero again, in Pulse2, find the position Tmin of the minimum value between Zm-2 and Zm, then the difference that is approximately equal to Tmax and Tmin is multiplied by 0.8 the micropulse rise time;
Step 47: each row of the two-dimensional array Pulse obtained in step 42 is carried out Fourier transform, gets to the matrix obtained the amplitude versus frequency characte Zfft that amplitude obtains micropulse, and Zfft gets several frequencies that amplitude is larger, namely obtains the dominant frequency distribution of micropulse.
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| CN105186491A (en) * | 2015-08-27 | 2015-12-23 | 国家电网公司 | Assessment method for overvoltage on primary side of electric power system caused by switching operation |
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| CN105825037A (en) * | 2016-06-13 | 2016-08-03 | 华北电力大学 | Equivalent circuit modeling method of pipeline support of transformer substation gas insulation switching equipment |
| CN105825037B (en) * | 2016-06-13 | 2019-02-05 | 华北电力大学 | The equivalent circuit modeling method of substation's gas-insulated switchgear support of pipelines |
| CN108152622A (en) * | 2017-12-18 | 2018-06-12 | 中国北方车辆研究所 | For inhaling the disturbed degree quantitative estimation method of Vehicular communication system in wave darkroom |
| CN110488085A (en) * | 2019-04-30 | 2019-11-22 | 广东石油化工学院 | A kind of detection method and device of the load switch event based on Mode Decomposition |
| CN110647908A (en) * | 2019-08-05 | 2020-01-03 | 湖北工业大学 | Automatic transformer substation feature fingerprint extraction method |
| CN110749787A (en) * | 2019-09-24 | 2020-02-04 | 清华大学 | Electromagnetic disturbance testing method for direct-current power distribution transformation system |
| CN110749787B (en) * | 2019-09-24 | 2021-01-05 | 清华大学 | Electromagnetic disturbance testing method for direct-current power distribution transformation system |
| CN113866532A (en) * | 2021-08-23 | 2021-12-31 | 中国电力科学研究院有限公司 | Method and device for quantizing maximum amplitude of disturbance voltage of in-situ intelligent measuring equipment |
| CN113866532B (en) * | 2021-08-23 | 2023-12-08 | 中国电力科学研究院有限公司 | Method and device for quantifying maximum amplitude of disturbance voltage of on-site intelligent measurement equipment |
| CN116840600A (en) * | 2023-07-05 | 2023-10-03 | 河北久维电子科技有限公司 | Equipment abnormality alarming method and transformer substation auxiliary system comprehensive monitoring linkage platform |
| CN116840600B (en) * | 2023-07-05 | 2024-01-16 | 河北久维电子科技有限公司 | Equipment abnormality alarming method and transformer substation auxiliary system comprehensive monitoring linkage platform |
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