Книга - English Original Reader for Technical Students. Power transformers: short-circuit testing, monitoring systems (Smart Grid)

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English Original Reader for Technical Students. Power transformers: short-circuit testing, monitoring systems (Smart Grid)
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English Original Reader for Technical Students. Power transformers: short-circuit testing, monitoring systems (Smart Grid)





This book is dedicated to the memory of my father Khrennikov Yurij Alexandrovich


This book is dedicated to the memory of my father Khrennikov Yurij Alexandrovich.

He was an Electrical Engineer and took part in the building of seven hydroelectric power stations.




Abbreviations


IMS-Information-measuring systems;

LVI�Low Voltage Impulse;

FRA-Frequency Response Analysis;

T-controlled power transformer;

TV-voltage transformer;

CT-current transformer;

B-high-voltage circuit breaker;

L-inductance;

ANR-accidental and non-regime;

RW-regulation winding;

DGA-Dissolved Gas Analysis;

ADC-analog-to-digital converters;

RMSD-root-mean-square deviation;

AFC-amplitude-frequency characteristic;

HV-high voltage (winding);

LV1-first low voltage (winding);

LV2-second low voltage (winding);

MV-medium voltage (winding);

HEPS-Heat Electric Power Station;

�sec-microsecond;

JSC �FGC UES�-Joint Stock Company �Federal Grid Company of

Unified Energy System�;

STL-Short-current Testing Laboratory;

SREPS-State Regional Electric Power Station;

IR-control-infra-red control;

PD-partial discharges;

TG-turbo-generator;

DC-direct current

DO-digital oscillograph;

GIS-gas insulated switchgear;

SAWP-specialized automated working place;

TCS-technical condition state;

IEPS AAN-Intellectual electric power system with the active-

adaptive network;

M&R-maintenance and repair;

EMF-electromotive force;

OA-operational amplifier;

EDS-expert- diagnostic system;

TREE-transformer and reactor electrical equipment;

ETCS-electrotechnical complexes and systems;

DM-diagnostic models;

DF-diagnostic feature;

ED- electrical device;

OFA-operational physical actions;

EMC-electromagnetic compatibility;




Chapter 1. Monitoring Systems (Smart Grid) and Diagnostics Electrical Equipment Faults





Abstract


The most important elements of �intellectual networks� (Smart Grid) are the systems of monitoring the parameters of electrical equipment. Information-measuring systems (IMS), which are described in this paper, were proposed to be used together with rapid digital protection against short-circuit regimes in transformer windings. This paper presents the experience of LVI-testing application, some results of using Frequency Response Analysis (FRA) to check conditions of transformer windings and infra-red control results of the electrical equipment. The LVI method and short-circuit inductive reactance measurements are quite sensitive to be able to detect such faults as radial and axial winding deformations, twisting of low-voltage or regulating winding, losing of winding pressing, and others.

Keywords: Intellectual Networks; Smart Grid; Monitoring System; Electrical Equipment; Information-Measuring System; Frequency Response Analysis; Transformer Winding Fault Diagnostic; Low Voltage Impulse Method; Short-Circuit Inductive Reactance Measurement




1.1. Introduction


Joint Stock Company �Federal Grid Company of Unified Energy System� is the operator of the United National Electrical Network of Russia. The total extent of electrical power transmission lines is 121.7 thousand km, the number of substations is 805, and the class of voltage is 220�750 kV. The five-year investment program includes the construction of 73 new substations.

The switch to �clever power engineering� (Smart Grid) realized by Federal Grid Company, will make it possible not only substantially change today�s energy landscape, but also further develop the electrotechnical industry, mastering new technologies and creating new electrical equipment. Novel methods are to be incorporated both in plants and in scientific design institutes, stimulating the professional growth of Russian scientists.

In Saint-Petersburg International Economic Forum that took place some years ago, it was declared that one of the results of the conversions, conducted today by Federal Grid Company, must be the creation of the components of �intellectual networks� (Smart Grid), which will solve the existing tasks of the power electrical engineering providing for increase of effectiveness of its work and creating conditions for increasing the competitive ability of the economy of Russia on the basis of new innovation solutions and technologies.




1.2. Smart Grid Information-Measuring System for Control of Inductance Value Transformer�s Winding


The most important elements of �intellectual networks� (Smart Grid) are the systems of monitoring of the parameters of the electrical equipment. The residual winding�s deformations of power transformers during short circuits appear practically instantly, not leaving time to analysis of the results of diagnostic measurements, demanding to switch off the transformer as fast as possible in order to avert or, at least, reduce the necessary consequent repair of the electrical equipment.

Information-measuring systems (IMS), which are described in this paper, were proposed to transformer winding control. Rapid digital protection against short-circuit regimes in transformer windings is used with IMS. The instantaneous and average values of inductance have been calculated. This calculation showed that using IMS for inductance control allows to decrease the number of failures and expenditures for repair.

Scheme of using IMS for the control of transformer�s winding state avoiding disconnecting from the network is depicted in Figure 1 [by 1�4].








Figure 1. Information-measuring system for control of transformer�s windings state in service.




1.3. Algorithm of Smart Grid Information-Measuring System (IMS)


The algorithm of IMS�s work is the following. The continuous control of the winding�s state of the controlled power transformer is ensured by a constant monitoring of deviation of inductance value from the base value of inductance, which is obtained from the block of the base inductance.

During the work of the three-phase controlled power transformer (T) for the three-phase resistive load (Load) the value of primary voltage U1 is obtained by measuring converters primary voltage (high-voltage transformers TV1).

Signal from the converters was input to the entrance of the block which brings the primary voltage to the second one. In this block the value of the primary voltage, which is corrected to the second, is calculated:

Signal from the converters was entered to the entrance of the block of bringing the primary voltage to the second. In this block the value of the primary voltage, which is corrected to the second, is calculated:




(1.1)

where: Kt is the known given value of the transformation ratio of the power transformer.

Signals from the measuring converters of second voltage (voltage transformers TV2) and signals from the output of the previous block are input to the entrance.

In the block of calculation of voltage difference, which is corrected to the second side, we determine




,(1.2)

where: U2 is the value of second voltage, measured by converters TV2.

The calculations are performed in the assigned time interval in the block of calculation of voltage�s average value:




(1.3)

where: uj is the difference between corrected to the second side voltages on the transformer;

t1 and t2 are the temporary boundaries of the partition interval.

In the block of calculation of the current derivation the increase of the current in the assigned time interval is calculated:




(1.4)

Here ij is the value of current in the secondary winding of the controlled transformer, measured by current converters (current transformers CT).

In the block of calculation of inductance, the instantaneous value of inductance is determined in the assigned time interval:




(1.5)

where: uaverage is the average value of voltage,

dij/dt is the value of current derivation.

Expression (1.5) can be obtained from Ohm's law for the magnetic circuit:




(1.6)

Further using the expressions below




(1.7)

we obtain


.

Disregarding the second term (assuming L = const), and assuming the linear characteristic of the medium, we have




(1.8)

which is analogous to (1.5).

In the block of bringing the value of inductance to the nominal frequency the instantaneous value of inductance corrected to the nominal frequency is calculated:




(1.9)

where: fmeas is the value of the frequency (Hz) measured by frequency converter,

fnom. is the nominal value of the frequency.

Lj meas. is the instantaneous value of inductance.

In the following block the average value of inductance during each period is calculated:




(1.10)

In the block of calculation of deviation, Laverage value during the period is compared with the base L0 value, and their difference is calculated:




(1.11)

where: L average is the average value of inductance during the period;

L0 is the base value of transformer inductance, determined from the preliminary experiment.

When winding deformations begin or in the case of winding turn-to-turn internal short-circuit, the value of inductance L tends to increase, or to decrease from one time period to the next period in case of irreversible destruction of the controlled power transformer windings.

Then, the signal from the control block enters the protection block (rapid digital protection), where a signal to switch off is formed in the high-voltage circuit breaker (B). After that Information-measuring system and the connected with it protection block stop the process of winding destruction [by 1�4].

This Smart Grid monitoring system is a perspective direction of diagnostics under operating voltage.




1.4. Inductance Calculations of 167 MVA/ 500/220 kV Autotransformer


Basing on the foregoing, the algorithm (1.1�1.11) was developed and now constitutes a special program for calculating instantaneous inductance L during electrodynamic test of the power transformer by short-circuit currents. The program allows determining the average value of the inductance during each period. This value is more significant in the case of damage to the coil (primary deformation, coil circuit). To evaluate the potential effectiveness of the monitoring system, the calculations of instantaneous and average values of inductance (L) were performed for the case of accidental and non-regime (ANR) due to damage during short-circuit testing at Power Testing Laboratory (Togliatti) of 167 MVA/ 500/220 kV autotransformer.

During short-circuit testing of 167 MVA/ 500/220 kV autotransformer at the second short-circuit shot, i.e., experience with 100�% value of the short-circuit current 0.2 sec duration according to the test program (time set by the conditions of experience � 10 periods of current, and regulated by high voltage thyristor valves), there has been actuation of transformer gas protection.

Audit and inspection with the lifting of transformer tank and inspection of the active part of autotransformer have revealed the presence of electrical damage to the regulation winding (RW) � turn-to-turn short circuit. Figure 2 shows the real oscillograms of short-circuit current (Figure 2a), voltage (Figure 2b), estimated the average curve of inductance for 10 periods (Figure 2c), the calculated curve instantaneous inductance (Figure 2d) in the second short-circuit shot. Change of the value of the inductance of the curves in Figure 2 shows that the electric damage of RW winding happened at the 4th period and continued to develop in the remaining periods of short-circuit shot.

Calculations of inductance values show that the application of Smart Grid monitoring system and quick-working protection would submit a command to turn off the high-voltage circuit breaker in the fourth period of current that is, taking into account the work of protection and circuit breaker (at least three periods, i.e., 0.06 seconds), cease the emergency process at the 7-th period of current. Thus one could reduce the damage of RW windings and the cost of its repair at the transformer manufacturer.








a)








b)








c)�and d) Figure 2. Oscillograms of short-circuit current (Figure 2a), voltage (Figure 2b), estimated the average curve of inductance for 10 periods (Figure 2c), the calculated curve instantaneous inductance (Figure 2d) in the second short-circuit shot of 167 MVA/ 500/220 kV autotransformer.




1.5. Smart Grid Monitoring System for Short-Circuit Testing


Smart Grid Monitoring System for control of parameters of the transformer when tested for withstands to short-circuit currents, part of the quick-working protection, is discussed in [by 1�3].








Figure 3. Smart Grid Monitoring System for control of transformer parameters during short-circuit testing, which is a part of the quick-working protection. 1-power supply (network), 2-safety high-voltage circuit breaker, 3-test transformer, 4-synchronous short-circuiter, 5�7-capacitive voltage dividers, 8�9, the control block, 9 � voltage transformer, 10�12-current-measurement shunts, 14�22-the functional blocks of the inductance average value�s calculation of the deviation from the original value, 23-testing transformer in the secondary winding short-circuit mode.

Control of the average value of inductance Laverage for the period during the test allows fixing moment of the beginning of the emergency regime and reducing the scale of the accident if the tested transformer is timely disconnected. The Monitoring System provides a more accurate measurement of inductance and increases the reliability of the power transformer in case of dangerous deformations.

Quick-working protection prevents accidental destruction of the test object and increases the crash safety of the test (Figure 3) [by 1�5].

In Figure 3 the following details of the equipment are shown: 1-power supply (network), 2-safety high-voltage circuit breaker, 3-test transformer, 4-synchronous short-circuiter, 5�7-capacitive voltage dividers, 8�9, the control block, 9 � voltage transformer, 10�12-current-measurement shunts, 14�22-the functional blocks of the inductance average value�s calculation of the deviation from the original value, 23-testing transformer in the secondary winding short-circuit mode [1�5].

Consider the work of the monitoring system in Figure 3 with an example of the 400 MVA/220 kV transformer testing. Current and voltage oscillograms at the second short-circuit shot on the phase �C� of the 400 MVA/220 kV transformer are shown in Figure 4.








Figure 4. Current oscillogram (1) and voltage oscillogram (2) in the second short-circuit shot on the phase �C� of the 400 MVA/220 kV transformer.

Current oscillogram analysis shows that the value of aperiodical (shock) component of short-circuit current at the beginning of the short-circuit shot amounted to 12.8 kA, and through 10 periods after attenuation of aperiodical (shock) component at the end of the shot, then periodic component is only 10.2 kA.

The calculated curve derivative from current and calculated inductance Ls-c curve of 400 MVA/220 kV transformer in the short-circuit shot on the phase �C� with 100�% of the value of the aperiodical (shock) short-circuit current are shown in Figure 5. Deviation of Ls-c amounted to +1.3�% in the short-circuit shot.




a)




b)

Figure 5. The calculated curve in the short-circuit shot on the phase �C� with 100�% of the value of the aperiodical (shock) short-circuit current of 400 MVA/220 kV transformer: a) derivative from current; b) calculated inductance Ls-c curve.

During the tests for withstands to short-circuit currents of 400 MVA/220 kV transformer, the following data were obtained:

values of voltage and current in short circuit shots,

the short-circuit inductance measurement results,

level of vibration in the short circuit shot,

LVI-testing data,

the results of chromatographic analysis of transformer oil dissolved gas (DGA).

Diagnostic data parameters allowed to complete the objective picture of the condition stste of 400 MVA/220 kV transformer during the tests for withstands to short-circuit currents [by 1�4].




1.6. An Accuracy of Diagnostic Parameter of Smart Grid Monitoring System


When Smart Grid Monitoring System is working, an important issue is the accuracy of main diagnostic parameter which characterizing the normal operation of power transformer � the short-circuit inductance of the windings. Large error during the measurement of this parameter can lead to malfunctions of the device: false outages or, on the contrary, the protection isn�t working when the inductance changed after the transformer or the reactor had been damaged. Therefore, it is proposed to introduce to the scheme of this device the block of the mathematical treatment of ?L measurement.

The confidence interval of a random measurement error of transformer inductance was determined in the block of mathematical treatment of


L measurements results by a specific algorithm.

Measured parameters I, U, P, F from the measured voltage transformers, capacitive voltage dividers, current-measurement shunts and frequency counter are input to the entrance of mathematical treatment block of measurement results, where at the entrance there are analog-to-digital converters (ADC), within which the following operations are performed by a special algorithm:

1)�The value of short-circuit transformer inductance which is converted to a frequency 50 Hz, is calculated




(1.12)

Where Ii, Ui, Pi, Fi are the values of current, voltage, power and frequency which are measured by ADC during i- count.

2)�The average value of short-circuit transformer inductance at the 50 Hertz frequency is calculated




(1.13)

together with the total average value, including the parameters of the I, U, P, F:




(1.14)

where: Xi � values of the I, U, P, F, measured by ADC during i-counting,

n is the number of measurements.

3)�The deviation of short-circuit inductance is calculated




(1.15)

where:X0 � base value of short-circuit transformer inductance, determined by calculations according to the results of preliminary tests.

4)�The root-mean-square deviation (RMSD) of the measurement results for each of the primary parameters of I, U, P, F is calculated;

5)�The RMSD for the resultant of short-circuit inductance is calculated:




(1.16)

where:


are the corresponding RMSD of the means of the measurement (ADC converters of current, voltage, power and frequency);




are the specific weights of errors in a general error in the result X50:




(1.17)

where: I, U, P, F are the primary measured parameters of the current, voltage, power and frequency.

6)�The value of the fourth central moment of distributing the random error of measurement of inductance X50 is calculated:




(1.18)

where n is number of measurements;








Xi50 is the value of short-circuit inductance;

Xaverage50 is the average value of short-circuit inductance;

7)�The value of antikurtosis


and kurtosis


of the distribution of a random error of measurement (the coefficient of kurtosis measures the �peakedness� of a distribution) is calculated




(1.19)

where:


is the RMSD value from expression (1.16);

M4 is the value of the fourth central moment of distribution from (1.18).

8)�The value of an entropy error of measurement is calculated:




(1.20)

where: n is the number of measurements;

d is the width of the interval of the histogram of distribution definition as:




(1.21)

where: Xi50 and Xaverage50 are the values from (1.12�1.14), moreover the maximum significance of a deviation between them is taken;

m is the optimum number of class intervals of columns for constructing the histogram of distribution law of the random error:




(1.22)

where


is the antikurtosis of distribution from (1.19);

n is the number of measurements;

nj is the number of counting in j column of the histogram (j = 1�., m).

9)�Determined by d � width of the interval of the histogram of distribution by (1.21);

10)�Determined by m � optimum number of class intervals of columns for constructing the histogram of distribution law of the random error on (1.22);

11)�Calculated value of the entropy coefficient of random error�s distribution of measurement:




(1.23)

where: ?� � entropy error from (20);




is the root-mean-square deviation (RMSD) from (1.16).




1.7. Determination of the Distribution Law of Measurement Random Error


12)�The form of distribution law of measurement random error, the diagram of the topographic classification of the laws of distribution, values of antikurtosis


and entropy coefficient � are determined.

13)�The value of quantile coefficient for the concrete identified distribution is calculated:

Table 1.1.













14)�The error in the determination of root-mean-square deviation (RMSD) of random error distribution is calculated:




(1.24)

where:


is the kurtosis of distribution;

n is the number of measurements.

15)�The value of the confidence interval of a random error of measurement of short-circuit transformer inductance is determined:




(1.25)

where: t is the quantile coefficient;




is the measurement�s root-mean-square deviation (RMSD) of X50 value.

16)�Obtained result of measuring the deviation of short-circuit transformer inductance is derived to the printing in the following form:




(1.26)

where: ?X50 is the deviation of X50 value from base value of short-circuit transformer inductance �0;

?conf is the value of the confidence interval of a random error of measurement of short-circuit transformer inductance from (1.25).




1.8. �alculation of Confidence of Interval of Measurement Random Error during Short-Circuit Transformer Testing


In the case of the appearance of residual deformations in the windings of transformer-reactor electrical equipment (TREE) comes a gradual increase in the value of short-circuit transformer inductance.

The criterion of the evaluation of the threshold quantity of the deviation of short-circuit inductance, which corresponds to the beginning of the appearance of deformation, is value (?�s-c = +0,2�0,3�% with the confidence interval (accuracy) of the measurements (?conf = 0,1�%). Value ?�s-c = +1�% corresponds to the sufficiently serious deformations of the transformer windings [by 1�4].

The given procedure of the determination of the confidence interval ?conf (1.12�1.25) for the measurements of �s-c can be used also in the case of calculation ?conf for the deviations ?�s-c in the course of transformer testing for withstand to short-circuit current. The value of ?conf for the deviations ?�s-c, determined on (1.26), does not exceed the value of ?conf for ?�s-c, since utilized in (1.13�1.15) Xaverageand X0 are calculated from the samples n of the uniform the equal-point values xi, which have one and the same law of random error distribution in the type �Chapeau�.

Let us illustrate this based on the example of a change in the significance of a deviation of short-circuit inductance ?�s-c from one shot to the next during the 25MVA/220 kV transformer testing for withstand to short-circuit currents (Figure 6).








Figure 6. Example of a change in short-circuit inductance and the estimation of the significance of deviations �s-c with the aid of the confidence interval of measurements ?conf during the 25MVA/220 kV transformer testing.

Advantage of the proposed in this chapter method one can see well in the case of changing �s-c in the third, and then in the fourth final shot from +0,22�% to 0,34�%, when the value of confidence interval with the normal distribution ?conf =


(no shaded rectangles in Figure 6) the significance of the obtained deviations does not give to estimate, since confidence intervals ?conf of third and fourth shots are overlapped. This can lead to the false conclusion that change ?�s-c = +0,12�% from the third to the fourth shot insignificant and is connected only with the influence of measurement error.

The procedure of determination of ?conf, which presented in (1.13�1.26), allows to obtain the significant deviation of ?�s-c with its change from the third short-circuit shot to the fourth short-circuit shot, having ?conf = 0,05�% for �Chapeau� distribution.

The obtained result is confirmed by the 25MVA/220 kV transformer dismantling at the manufacturing plant, when untwisting the regulating winding (RW) of transformer was discovered. Therefore, the proposed method is more reliable and can be recommending for the introduction on other short-circuit testing laboratories and in the operation in the power systems during the measurement of short-circuit inductance or impedance [by 3�4].

In addition to examined method, which makes it possible to obtain significant deviations of ?�s-c with the aid of the correct calculation of ?conf, it follows to add that in the case of obtaining the insignificant deviations (as in Figure 6) from the first short-circuit shot to the second short-circuit shot and from second to the third short-circuit shot it is possible to consider significant deviation ?�s-c = +0,17�% (0,22�% � 0,05�% = 0,17�%) from first to the third final short-circuit shot.

In addition to this, in the case of the intersection of the zones of confidence intervals ?conf between the first (?�s-c = +0,05�%) and the second short-circuit shot (?�s-c = +0,16�%) at point +0,11�% it is possible to consider this as one significant deviation ?�s-c = +0,11�% with the confidence interval ?conf =


, since between the second and the third short-circuit shot also occurs insignificant deviation (Figure 6) [by 10�14].

From Figure 5 follow that zones of confidence interval ?conf of measurement short-circuit inductance �s-c of the adjacent on the time short-circuit shot (for example, 2-nd short-circuit shot and 3-d short-circuit shot) can intersect between themselves: ?�s-c2 = +0,16�% (?conf2 =


) and ?�s-c3 = +0,22�% (?conf2 =


).

This �imposition� of measurement confidence interval is inadmissible, since in certain cases this hampers the estimation of winding condition state of transformer: if this deviation ?�s-c insignificantly, i.e. it is connected with a measurement error, then of changes in the windings does not occur; but if it significantly, i.e. it corresponds to the development of residual deformations in the windings, then it must be considered for evaluating the winding condition state in order not to bring it to the destruction [5�14].

Example. During the short-circuit testing of two accordingly switch reactors of the type ROST-700 in the course of measurements by ADC of short-circuit inductance there was identified �Chapeau� type distribution.

The value of resulting of measurement root-mean-square deviation comprised:


= 0,02693�%; the value of the quantile coefficient t = 1,8143; the confidence interval of a measurement random error comprised ?conf = 0,052�% with the number of measurements of n = 572.

The obtained value ?conf = 0,052�% is lower than stipulated level of error +-0,1�%, which confirms the high accuracy of the determination of short-circuit inductance deviation in the proposed device � Smart Grid Monitoring System [by 1�9, 15�26].




1.9. Conclusion


The most important element of �intellectual of networks� (Smart Grid) are the systems of monitoring the parameters of electrical of equipment.

Smart Grid Monitoring System, which described in this chapter, were proposed to use together with quick-working protection against short-circuit regimes in transformer windings.

At the beginning of winding deformations, and also in the case of winding turn-to-turn internal short-circuit the value of inductance L is developed to increase, or to decrease.

Smart Grid Monitoring System and connected with it protection block were stopped the process of winding destruction.

Short-circuit inductance measurements by ADC there was identified �Chapeau� type distribution of random error.

The determination of confidence interval of measurement random error of short-circuit inductance deviation ?�s-c by algorithm (1.12�1.26) makes to increase the accuracy of the conducted measurements and the reliability of Smart Grid Monitoring System�s work for the control of short-circuit inductance of power transformers and the reactors.

Smart Grid Monitoring System makes it possible to continuously control the state of power transformer windings without their turning off from the network, to achieve their protection in the case of the appearance of the winding deformations or their damage, and it ensures the high accuracy of the inductance measurement with the confidence interval value of the random error less than +0,1�%. This increases the reliability of operation and the continuity of the power supply of the electrical energy users.




Active Vocabulary of electrotechnical terms and verbs:


Information-measuring system � �������������-������������� �������,

monitoring system � ������� �����������,

Smart Grid � ���������������� (�������) ����,

inductance � �������������,

autotransformer � �����������������,

short-circuit � �������� ���������,

short-circuit testing � ��������� �� ��������� ��� �������� ���������,

accuracy � ��������,

accuracy of diagnostic parameters � �������� (���������) ��������������� ����������,

confidence interval of measurement � ������������� �������� ���������,

Frequency Response Analysis � (�����) ���������� �������,

transformer winding fault diagnostic � ����������� ����������� ������� ��������������,

Low Voltage Impulse method � ����� ������������� ���������,

short-circuit inductive reactance measurement � ��������� ������������ ������������� ��������� ���������,

voltage transformer (TV)�� ������������� ����������,

current transformer (CT)�� ������������� ����;

high-voltage circuit breaker (HVCB)�� ������������ �����������,

dissolved gas analysis (DGA)�� ������ ����������� (� �����) �����,

analog-to-digital converters (ADC)�� �������-�������� ���������������,

Short-current Testing Laboratory (STL)�� ����������� (�����) ��������� �� ��������� ��� �������� ���������,

to enter- �������,

to include � �������� (� ����),

to determine � ����������,

to show � ����������,

to prevent � �������������.

Exercise 1. Match the English words and word-combinations given below with Russian evuivalents:

equipment a) ��������,

application b) ���������,

check c) �����������,

transformer d) ����������,

windings e) ������������,

Scheme f) ������� (��������),

to decrease g) �������������,

continuous h) �����������,

measuring i) �������������,

converter j) ������������������ ����������,

primary k) �������� (��������),

voltage o) ��������,

calculation p) ���������������,

Average q) ��������� ������,

root-mean-square deviation r) ���������,

distribution s) �����,

short-circuit regime t) ���������,

determination u) ����������,

appearance v) ���������� (������)

random error x) ����� ��������� ���������,

to obtain y) �������,

significant z) ����������,

Exercise 2. Find the antonyms and translate them:

Appearance, increase, scientific, slow digital protection, high-voltage, necessary, automated working place, unscientific, rapid digital protection, nonautomated working place, unnecessary, decrease, low-voltage, disappearance.

Exercise 3. Study the Active vocabulary. Insert the missing verbs from the list into the sentence and translate them:

The five-year investment program __________ the construction of 73 new substations.

The signal from the control block __________ the protection block (rapid digital protection).

The instantaneous value of inductance is ___________ in the assigned time interval.

The most important elements of �intellectual networks� (Smart Grid) ______ the systems of monitoring the parameters of electrical equipment.

The program allows ________ the average value of the inductance during each period.

Figure 2 _______ the real oscillograms of short-circuit current (Figure 2a), voltage (Figure 2b).

Quick-working protection _______ accidental destruction of the test object and increases the crash safety of the test.

List of verbs: to enter, are, to include, to determine, to show, to prevent, to calculate.

Exercise 4. Answer the following questions to the text.

1.�What is the advantage of power transformer monitoring?

2.�What is the purpose of digitalization of substations and switchgear of electric power stations, the construction of a digital electrical network?

3.�On what principle does the information-measuring system work?

4.�Describe the algorithm of the device for continuous monitoring of the state of power transformer windings.

5.�What elements and signal converters are included in the block diagram of the device for assessing the state of the windings of power transformers by the value of short-circuit resistance?

6.�What are the advantages of the device? Does it provide sufficient speed to process the measured parameters?

7.�Why is the value of short-circuit inductive reactance of the transformer reduced to a frequency of 50 Hertz?

8.�How are the primary and secondary currents and voltages of the power transformer measured for the further operation of the device?

9.�What are the metrological parameters of this device?

Exercise 5. Make � plan of the text and retell the text looking in your plan.

Exercise 6. Discuss the following topics.

1.�Smart Grid Monitoring System.

2.�Short-circuit inductance measurements.

3.�Measurements of short-circuit inductance deviation.

4.�Digitization of substations and switchgear of electric power stations, building a digital electrical network.

3.�Algorithm of the operation of the information-measuring system for continuous monitoring of the state of the windings of power transformers.

4.�Metrological parameters of the device for continuous monitoring of the state of windings of power transformers.

5.�Quick-working protection during the operation of the device for continuous monitoring of the state of the windings of power transformers.

6.�Registration of primary and secondary currents and voltages of a power transformer during operation of the device for continuous monitoring of the state of power transformer windings.




References


[1] ������� �. �. ���������� ���� ��� ����������� ��������������. English for Technical Colleges: ������� ��� ����. ���������� ���/ �. �. �������, �. �. ��������, �. �. ��������.�� �.: ������������ ����������, 2014.�� 208 �.

[2] Khrennikov, A. Yu., Shlegel, O. A., Lurie, S. I., (1996). Control and protection device of transformer windings against deformation at short-circuits in service. Patent of Russian Federation, ��2063050. Bulletin ��18.

[3] �. �., ���������� (https://www.litres.ru/author/serafima-zayceva-5994195/) �. �., �������� �. �., �������� (https://www.litres.ru/author/elena-smirnova-7471553/) �. �., ���������� ����. ����������. ������-������������ ������ (https://www.litres.ru/genre/uchebno-metodicheskie_posobiya-5314/)�,�� �.: ������, 2018, �. 65.

[4]Khrennikov, A. Yu. Control and protection device of transformer windings against deformation at short circuits�, Patent of Russian Federation, ��2136099. 1999,Bulletin ��24.

[5] �. �., ������� (https://www.litres.ru/author/serafima-zayceva-5994195/) �. �., �������� (https://www.litres.ru/author/elena-smirnova-7471553/) �. �., �������� (https://www.litres.ru/author/ludmila-tinigina/) �. �., English reader for technical students ���������� ���� (https://www.litres.ru/genre/anglijskij_yazyk-6361/), ������-������������ ������ (https://www.litres.ru/genre/uchebno-metodicheskie_posobiya-5314/)�,�� �.: ������, 2018, �. 66.

[6] Khrennikov, A. Yu., (1998). Measuring device of the inductive transformer short-circuit impedance�, Patent of Russian Federation, ��96110718 �.

������� �. �. ���������� ���� ��� ��������� �������������� ��������������: ������� �������/�. �. �������.�� �.: ����. ��., 2009.�� 150 �.

[7] Fogelberg, T., Girgis, R. S., (1994). ABB power transformers � a result of merging different technologies with prospects for significant future advancements�, International Simposium "Electrotechnics � 2010", Moscow, vol. 1, 56�59.

[8] Balakrishnan, V. A study of short-circuits in large power transformers, Electrical India, 1989, Vol. XXIX, ��4, 87�91.

[9] �������� �. �. ����������� ������ ��� �����������: ������������ ������� �� ����������� ����� ��� ��������� 1, 2 ������ �������������� �������������� ������� � ������� ���� �������� / ����. �. �. ��������.�� ���������: �����, 2004�112 �.

[10] Lech, W., Tyminski, L. Detecting transformer winding damage � the low voltage impulse method, Electrical Review, 1966, ��18, 23�27.

[11]������������ �. �., ���������� �. �. English for energy industry. ���������� ���� ��� �������������� ��������������: ������� ������� /, �. �. ������������, �. �. ����������.�� �����. ���. �����. ��-�, 2014�152 �.

[12] Malewski, R., Khrennikov, A. Yu., Shlegel, O. A., Dolgopolov, A. G. (1995). Monitoring of Winding Displacements in HV Transformers in Service, Reports of CIGRE Working Group 33.03. Italy, Padua.

[13] Khrennikov, A. Yu., (1999). Short-circuit performance of power transformers. Test experience at Samaraenergo Co and at Power Testing Station in Togliatti, including fault diagnostics, Reports of CIGRE Study Commitee 12 Transformers. Hungary, Budapest.

[14] ������, �. �. ���������� ���� ��� �����������: ����. ������� /�. �. ������, �. �. �����. �����: ���. ��., 2011�191 �.

[15] Khrennikov, A. Yu., (2000). Power transformer's fault diagnostics at Samaraenergo Co, including FRA/LVI method, Reports from School of Math. and System Engineering, Vaxjo University, Sweden, ��43, ISSN 1400�1942.

[16] Khrennikov, A. Yu., (2005). Short-circuit performance of power transformers. Transformer testing experience for reliability�s increase of electric power supply, Reports of CIGRE Colloquium, Comitee A2., Moscow.

[17] Khrennikov, A. Yu., Goldshtein, V. G., Skladchikov, A. A., (2010). The analysis of a condition of overhead lines of power transmission 6�500 �V, Power plants, ��5.

[18] Khrennikov, A. Yu. (2012). New �intellectual networks� (Smart Grid) for detecting electrical equipment faults, defects and weaknesses. Smart Grid and Renewable Energy, February, Volume 3, Issue 1, 159�164. http://www.scirp.org/journal/sgre/ (http://www.scirp.org/journal/sgre/)

[19] Khrennikov, A. Yu., (2013). Smart Grid technologies for Detecting Electrical Equipment Faults, Defects and Weaknesses. Workshop on Mathematical Modelling of Wave Phenomena with applications in the power industry, Linnaeus University, V?xj?.

[20] Khrennikov, A.Yu., Mazhurin, R. V., Radin P. S., (2014). Infra-red and ultraviolet control, LVI-testing, partial discharges and another diagnostic methods for detection of electrical equipment�s faults, defects. Journal of Multidisciplinary Engineering Science and Technology (JMEST) (ISSN: 3159�0040), Volume 1, Issue 4, 184�189. http://www.jmest.org/vol-1-issue-4-november-2014/ (http://www.jmest.org/vol-1-issue-4-november-2014/)




Chapter 2. Diagnostics and Transformer Testing Experience by LVI/FRA Methods





Abstract


LVI-testing, FRA and short-circuit inductive reactance measurements are sensitive to detecting such typical transformers winding faults as buckling, axial shift and other. It is given an algorithm of the frequency spectral analysis. The examples of diagnostics by LVI-testing, frequency spectral analysis of capacity range from 20 to 400 MVA and voltage range from 35 to 220 kV transformers and autotransformers are showed in service and during short-circuit testing. The studies are carried out for dependency of LVI oscillograms and signal spectra of power transformer winding of one type manufacturing.

Keywords: Short-circuit, Testing Laboratory, Winding fault, Electrodynamic deformation, Low voltage impulse method




2.1. Introduction


Power transformers are one of the basic parts in the circuitry of power transmission and delivery. Therefore, the interest to perfection of the power transformers' fault diagnostic methods is increased. The repairs of power transformers and other electrical equipment are carried out, using diagnostic measurement results.

LVI-testing, FRA and short-circuit inductive reactance measurements are sensitive to detecting such typical transformers winding faults as buckling, axial shift and other. The 70 units of 25�240 MVA 110�500 kV power transformers have been checked by low voltage impulse (LVI) method. A few power transformers were detected with winding deformations after short-circuit with aperiodical short-circuit current.

The idea of the application of an apparatus of frequency spectral analysis (FRA) for diagnostics of defects and damages of transformer-reactor electrical equipment belongs to R. Malewski, which proposed to use frequency spectra or transfer function of winding on the oscillograms of current and voltage for the analysis of the state of the transformer.




2.2. LVI-Testing and FRA Method for 250 MVA/220 kV Transformer Diagnostic


Significant amplitude-frequency changes with value to 1,5 Volts in the LVI- oscillograms, corresponding to radial deformations in LV winding of phase A, were occurred during the short-circuit tests of phase A of 250 MVA/220 kV transformer after short-circuit shot with 85�% value of transient (aperiodic) current. Conclusion was made about the impossibility of conducting further transformer testing (Figure 7) [by 1�4].








a)�for LVI-testing of phases ��-ѻ of LV winding;








b)�for LVI-testing of phases ��-B� of LV winding;








c)�for LVI-testing of phases �B-C� of LV winding.

Figure 7. LVI-oscillograms of LV winding of 250 MVA/220 kV transformer after short-circuit shot with 85�% value of transient (aperiodic) current in the phase �A�, illustrating the appearance of significant amplitude-frequency changes with value to 1,5 Volts, short-circuit impedance ?Z s-c = +1�% (radial deformations).

The changes in the spectra of windings, which occurred as a result of radial deformations, bear in essence amplitude nature, while changes in the frequency are less significant. One of the fundamental resonance frequencies (Figure 8) appears frequently in the period of 3 microseconds, i.e., 330 kHz.













Figure 8. Calculated FRA-spectrum of LV winding of 250 MVA/220 kV transformer after short-circuit shot with 85�% value of transient (aperiodic) current in the phase �A�, built on the basis of LVI-oscillograms.

It is confirmed by the calculations of spectra that the frequency of 320 kHz is one of the fundamental resonance frequencies. Resonances are also the frequencies of 110 kHz and 510 divided by 550 kHz. It is possible to establish an increase in the amplitudes after the appearance of the deformations of at frequencies 320 kHz and 550 kHz (Figure 8).




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