Partial Discharge Fault Decision and Location of 12kV ...€¦ · Transformer. 1.1. PD Models and Experimental Devices According to the internal insulation PD in por-celain insulators

547Metallurgical and Mining IndustryNo. 9 — 2015

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Partial Discharge Fault Decision and Location of 12kV Power Transformers based on Optical Fiber Sensor and Power Spectrum

Density Algorithm

ShaoZhenhua1, Zheng Mei-rong 2, Chen Tianxiang 1, Chen Li-an 1, Zhao jing1

1Fujian Province Key Laboratory of High Voltage Engineering, Xiamen University of Technology, Xiamen Fujian, 361024, China

2Fujian Province Electric Power Maintenance Company, Xiamen Fujian, 361000, China

Corresponding author is ShaoZhenhua

AbstractPartial discharge in polymeric insulation of medium voltage equipment causes cumulative damage that increas-ingly deteiorates the insulation, leading to eventual failure.With the consideration of electromagnetic interference from the envionment, the detection results may be unreliable.In such situations the detection of optical emission from partial discharge can greatly enhance its detectability, especially when the optical fiber sensor s are used. With the help of JFD251 partial discharge detection system and optical sensor, the partial discharge detection for different electrode model and the test methods are studied in the paper. Moreover, we present and discuss experi-mential results that show power spectrum density method is a good way for the fault decision and location of 12kV power transformer based on optical fiber sensor. Keywords: OPTICAL FIBER SENSORS(OFS), PARTIAL DISCHARGE(PD), OPTICAL EMISSION SOURCE(OES) , FAULT DECISION AND LOCATION, 12KV POWER TRANSFORMERS

Metallurgical and Mining Industry548 No. 9 — 2015

Electrometallurgy1. IntroductionThe emission of optical pluses caused by inter-

nal PD can be used as an alternative, non-electrical observable for their detection [1].Insulation fault in power transformer is a potential threat to flight safety of the 12kV power grid stable operation [2-4]. There is no doubt that power transformers play important roles in power transmission. Auto-recognition to dis-charge types in on-line PD monitoring system could be used to find out internal partial defects and the relevant discharge development degree in time, and then prevents equipment from the coming faults. On the other hand, on-site or on-line PD detection using the conventional instrumentation is a challenge, in that the PD signals are weak output signals which are easily buried in electrical noise and electromagnetic interference from the environment [5-7]. Both elec-trical and optical detection of PD rely on the pres-ence of a pulsed discharge of sufficient magnitude, Electric methods and non-electric methods are to di-agnose and correct problem situations for large power transformer.

In the first part of this paper, the PD models and PSD methods are introduced. In the second part of this paper, the optical phenomena can be observed by fluorescence optical fiber that is sensitive to the well-known optical emission by internal PD. In order to deal with the measurement error in OES arrival time calculation ,the PD source location method is dis-cussed in Section 2. And the optical emission source detection and sensors position on transformers are shown .Moreover the two different measurement type details are given in Section 3. Based on these results,

the last part deals with the interpretation of the obser-vations in terms of power spectrum density method.This interpretation implies that optical emission may offer a way to detect PD-free defects in 12kV Power Transformer.

1.1. PD Models and Experimental DevicesAccording to the internal insulation PD in por-

celain insulators and the PD propagation charac-teristics, there are three PD models are designed in this paper, which are shown in Fig.1. That is point discharge in transformer oil (P1) Solid Insulation of Power Transformer (P2), and surface discharge in transformer oil (P3) . The PD signals are measured by PCM. Test PD detection schematic diagram and experimental devices are shown in Fig.1 and Fig.2.Moreover the Optical Fiber Sensors are shown in Fig.3.

1.2. Power Spectrum Density AnalysisPSD analysis is the method which indicate the re-

lation between the power change and the frequency variation. The most part of the PSD is the calculation of spectral density function. With the help of PAD analysis, statistical operator, pulse waveform charac-teristics, and fractal characteristics in 2 dimensions or 3 dimensions can be considered. As can be shown in equation 1, the frequency of PD and the maximum PD value can be calculated by the different windows spectral density functions (such as Boxcar data sam-pling, Hamming data sampling and Blackman data sampling etc.).

2 2( ) ( )s t dt S f df+∞ +∞

−∞ −∞

=∫ ∫ (1)

Figure 2. Detection Circuit on PD of 12kV Power Transformer

Figure 1. PD models of artificial defects


Electrometallurgy

2. Experimental Procedure2.1. PD Source Location Method If the PD source is located at P0(x,y,z) and the five

sensors are located at P1(x1,y1,z1) , P2(x2,y2,z2), P3(x3,y3,z3), P4(x4,y4,z4) and P5(x5,y5,z5) .And the OF is selected at the bottom centers of the tank .And the schematic depicting PD source and sensors position on tank is shown in Fig. 4.And the equations governing the position of optical source and sensors are:

2 2 2 2( 1) ( 1) ( 1) ( 1)x x y y z z Tν− + − + − = ∗ (2)2 2 2 2( 2) ( 2) ( 2) ( 2)x x y y z z Tν− + − + − = ∗ (3)2 2 2 2( 3) ( 3) ( 3) ( 3)x x y y z z Tν− + − + − = ∗ (4)2 2 2 2( 4) ( 4) ( 4) ( 4)x x y y z z Tν− + − + − = ∗ (5)2 2 2 2( 5) ( 5) ( 5) ( 5)x x y y z z Tν− + − + − = ∗ (6)

Where T1, T2, T3, T4 and T5 are the optic wave propagation time from source to the nearest sensor.

Figure 3. Optical Fiber Sensors

Figure 4. Schematic Depicting PD Source and Position on Tank

And the PD source location theory is shown in Fig.5. As shown in Fig.5, OF(Optical Fiber) is the nega-tive receiving terminal, so the phase spectra is oppo-site to the other sensor terminals. As the maximum amplitudes(MA) of the five sensors decreased in turn, the gradient of ( )d MA

dt is called the PSD Value.

Figure 5. PD Source Location Theory


ElectrometallurgyWhile the optic wave propagation time from

source to the five sensors is different from each other, arrival time calculation should be discussed. As a contrast ,a group of pulse current method samples are also prepared with the same voltage and the same 12 KV Power Transformer.

3. Results and DiscussionsIn order to get the PSD value of OES arrival time

of the five sensors, a variable 'V' is defined as fol-low[8]:

2

1( )

nNd

dti

VV x i n

N=

= −

∑ (7)

where N=1,2,3,4,5, and n is the sampled number, VN is OES arrival time of each sensor.

In the proposed comprehensive method, arrival of signal is calculated using cumulative energy and vari-able S method. The minimum arrival time among the

two methods is determined as arrival time of signal and used for the source location.

Table 1 shows the PD value of Tip VS. Tip signal calculated using pulse current method, and the PD value is the mean value of five times. As a contrast, Table 2 shows the PSD value of Tip VS. Tip signal calculated using OPS, and the PSD value of OES cal-culated using variable V method.

In the same way, Table 3 shows the PD value of Tip VS. Ground signal calculated using pulse current method, and the PD value is the mean value of five times. As a contrast , Table 4 shows the PSD value of Tip VS. Ground signal calculated using OPS, and the PSD value of OES calculated using variable V method.

Some cases, depending on location of PD source, its propagation path and reflection, V gives a down-ward trend value which is not the signal arrival time. From Fig. 6 to Fig.13, are showing cumulative energy

Table 1. Experimental Data Tip VS. Tip based on Pulse Current Method

Voltage (kv) Mean Discharge Magnitude (pc) Test of Discharge Magnitude (pc)0kV 24PC 25PC 23PC 24PC 25PC 23PC1kV 26PC 25PC 26PC 27PC 25PC 26PC2kV 28PC 29PC 27PC 28PC 29PC 27PC3kV 30PC 31PC 32PC 30PC 29PC 28PC4kV 75PC 74PC 75PC 75PC 74PC 76PC5kV 411PC 391PC 425PC 375PC 410PC 443PC6kV 695PC 704PC 689PC 694PC 714PC 689PC7kV 802PC 784PC 814PC 778PC 799PC 823PC

Table 2. PD Experimental Data Tip VS. Tip based on OPS

Voltage (kv) PSD VALUE (mV) Test of Discharge Magnitude (us)0kV 0.2443 234 267 256 276 2781kV 0.8667 894 857 867 903 9122kV 1.1912 1194 1120 1078 1244 10883kV 1.4227 1478 1572 1378 1470 15004kV 1.9685 2003 2345 1987 1988 20075kV 3.3969 3945 3857 4004 3851 39436kV 4.1008 4252 4381 4938 4205 43817kV 5.9403 6008 6107 6173 6083 6250

Table 3. PD Experimental Data Tip VS. Ground based on Pulse Current Method

Voltage (kv) Mean Discharge Magnitude (pc) Test of Discharge Magnitude (pc)0KV 23PC 20PC 25PC 22PC 23PC 24PC1KV 27PC 29PC 27PC 28PC 26PC 26PC2KV 32PC 29PC 33PC 32PC 36PC 30PC3KV 35PC 36PC 32PC 37PC 36PC 34PC4KV 171PC 160PC 183PC 166PC 172PC 172PC5KV 344PC 350PC 374PC 325PC 334PC 337PC6KV 504PC 517PC 524PC 492PC 485PC 502PC7KV 804PC 825PC 794PC 785PC 816PC 783PC


Electrometallurgyand variable V for a typical OES signal for a tip–tip electrode system with insulation.

In order to have a good comparison between the PC value and the PSD Value, all data from Table 1 to

Table 4. PD Experimental Data Tip VS. Ground based on OPS

Voltage (kv) Mean Discharge Magnitude (pc) Test of Discharge Magnitude (pc)

0KV 0.2043 214 217 216 216 2181KV 0.6438 794 757 767 803 7622KV 1.4673 1594 1620 1608 1604 15883KV 1.7522 1825 1843 1866 1837 19424KV 2.4788 2586 2681 2604 2594 26075KV 2.8745 2943 2957 3004 3075 29436KV 3.7642 3524 3834 3394 3204 33487KV 5.8403 6008 6107 6173 6083 6250

Figure 6. FFT Analysis on 0kV PD Voltage






Table 4 are in unitization which are shown in Fig.14. In order to have a good comparison between the PC value and the PSD Value, all data from Table 1 to Table 4 are in unitization which are shown in Fig.14.


Electrometallurgy

ConclusionsIn this paper, the comprehensive fault decision

based on PSD algorithm is studied. Furthermore ,the PD experiments on 12kV power transformer are in the implementation between Tip VS. Tip mode and Tip Vs. Ground mode and the PSD values are obtained by image recognition.With the help of Matlab 7, he simulation results show that the proposed method can improve the accuracy and the real time performance of fault diagnosis in 12kV power transformer.

AcknowledgementsThe Project Supported by Fujian Provincial Ma-

jor Scientific and Technological Projects under grant 2014H6028, Scientific Research Items of XMUT under grant XYK201401,XMUT Initializing Foun-dation under grant YKJ12010R,.and funding (fund-ing number: JA12253) from the Fujian Education Department. Xiamen Science and Technology Plan Project (3502Z20123043). Foreign scientific and technological cooperation and exchange Project of XMUT (E201401400), Natural Science Foundation of Fujian Province (2015J01275).

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Partial Discharge Fault Decision and Location of 12kV ...€¦ · Transformer. 1.1. PD Models and Experimental Devices According to the internal insulation PD in por-celain insulators