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

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 К 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: ΔX50 is the deviation of X50 value from base value of short-circuit transformer inductance Х0;

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

1.8. Сalculation 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 (ΔХs-c = +0,2–0,3 % with the confidence interval (accuracy) of the measurements (Δconf = 0,1 %). Value ΔХs-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 Δconf (1.12–1.25) for the measurements of Хs-c can be used also in the case of calculation Δconf for the deviations ΔХs-c in the course of transformer testing for withstand to short-circuit current. The value of Δconf for the deviations ΔХs-c, determined on (1.26), does not exceed the value of Δconf for ΔХs-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 ΔХs-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 Хs-c with the aid of the confidence interval of measurements Δconf during the 25MVA/220 kV transformer testing.

Advantage of the proposed in this chapter method one can see well in the case of changing Хs-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 Δconf =

(no shaded rectangles in Figure 6) the significance of the obtained deviations does not give to estimate, since confidence intervals Δconf of third and fourth shots are overlapped. This can lead to the false conclusion that change ΔХs-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 Δconf, which presented in (1.13–1.26), allows to obtain the significant deviation of ΔХs-c with its change from the third short-circuit shot to the fourth short-circuit shot, having Δconf = 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 ΔХs-c with the aid of the correct calculation of Δconf, 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 ΔХs-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 Δconf between the first (ΔХs-c = +0,05 %) and the second short-circuit shot (ΔХs-c = +0,16 %) at point +0,11 % it is possible to consider this as one significant deviation ΔХs-c = +0,11 % with the confidence interval Δconf =

, 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 Δconf of measurement short-circuit inductance Хs-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: ΔХs-c2 = +0,16 % (Δconf2 =

) and ΔХs-c3 = +0,22 % (Δconf2 =
).

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 ΔХs-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 Δconf = 0,052 % with the number of measurements of n = 572.

The obtained value Δconf = 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 ΔХs-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 – информационно-измерительная система,

monitoring system – система мониторинга,

Smart Grid – интеллектуальная («умная») сеть,

inductance – индуктивность,

autotransformer – автотрансформатор,

short-circuit – короткое замыкание,

short-circuit testing – испытание на стойкость при коротком замыкании,

accuracy – точность,

accuracy of diagnostic parameters – точность (измерений) диагностических параметров,

confidence interval of measurement – доверительный интервал измерений,

Frequency Response Analysis – (метод) частотного анализа,

transformer winding fault diagnostic – диагностика повреждений обмоток трансформатора,

Low Voltage Impulse method – метод низковольтных импульсов,

short-circuit inductive reactance measurement – измерение индуктивного сопротивления короткого замыкания,

voltage transformer (TV) – трансформатор напряжения,

current transformer (CT) – трансформатор тока;

high-voltage circuit breaker (HVCB) – высокольтный выключатель,

dissolved gas analysis (DGA) – анализ растворённых (в масле) газов,

analog-to-digital converters (ADC) – аналого-цифровой преобразователь,

Short-current Testing Laboratory (STL) – лаборатория (стенд) испытаний на стойкость при коротком замыкании,

to enter- входить,

to include – включать (в себя),

to determine – определять,

to show – показывать,

to prevent – предотвращать.

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

equipment a) получать,

application b) появление,

check c) непрерывный,

transformer d) применение,

windings e) оборудование,

Scheme f) среднее (значение),

to decrease g) трансформатор,

continuous h) определение,

measuring i) распределение,

converter j) среднеквадратичное отклонение,

primary k) значимая (величина),

voltage o) проверка,

calculation p) преобразователь,

Average q) случайная ошибка,

root-mean-square deviation r) первичный,

distribution s) схема,

short-circuit regime t) уменьшать,

determination u) напряжение,

appearance v) вычисление (расчёт)

random error x) режим короткого замыкания,

to obtain y) обмотка,

significant z) измеренный,

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 а 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

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[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] Т. Н., Гращенкова Г. Н., Зудилова Е. Н., Смирнова Л. И., Английский язык. Менеджмент. Учебно-методическое пособие, – М.: ЛИТРЕС, 2018, с. 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] Т. Н., Зайцева С. Е., Смирнова Е. В., Тинигина Л. А., English reader for technical students Английский язык, Учебно-методическое пособие, – М.: ЛИТРЕС, 2018, с. 66.

[6] Khrennikov, A. Yu., (1998). Measuring device of the inductive transformer short-circuit impedance”, Patent of Russian Federation, № 96110718 А.

Луговая А. Л. Английский язык для студентов энергетических специальностей: Учебное пособие/А. Л. Луговая. – М.: Высш. шк., 2009. – 150 с.

[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] Бухарова Г. П. Техническое чтение для энергетиков: Методическое пособие по английскому языку для студентов 1, 2 курсов энергетических специальностей дневной и заочной форм обучения / сост. Г. П. Бухарова. – Ульяновск: УлГТУ, 2004–112 с.

[10] Lech, W., Tyminski, L. Detecting transformer winding damage – the low voltage impulse method, Electrical Review, 1966, № 18, 23–27.

[11]Галиахметова А. Т., Лутфуллина Г. Ф. English for energy industry. Английский язык для энергетических специальностей: Учебное пособие /, А. Т. Галиахметова, Г. Ф. Лутфуллина. – Казан. гос. энерг. ун-т, 2014–152 с.

[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] Трухан, Е. В. Английский язык для энергетиков: учеб. пособие /Е. В. Трухан, О. Н. Кобяк. Минск: Выш. шк., 2011–191 с.

[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 кV, 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/

[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, Växjö.

[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/

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 «А-С» of LV winding;



b) for LVI-testing of phases «А-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 ΔZ 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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