New developed Insulator Selection Tool (IST) software: results of application using known Russian service experience

Igor Gutman 1* Kjell Halsan 2 Dan Hübinette 3 Evgenij Solomonik and Lev Vladimirsky 4

1 STRI AB, Box 707, 77180, Ludvika, Sweden 2 Statnett, Box 5182, Oslo, Norway

3 Svenska Kraftnät, Box 526, Vällingby, Sweden

4 HVDC Transmission Research Institute, St. Petersburg, 194223, Russia E-mail : igor.gutman@stri.se

Abstract: Insulator Selection Tool (IST) and Line Performance Estimator (LPE) programs have been recently developed at STRI. Norwegian power utility Statnett has already used the LPE program for the practical evaluation of insulation alternatives to upgrade 300 kV transmission lines to 400 kV. In this particular case different future insulation options were compared based on pollution/ice performance data obtained in the laboratory. To increase level of confidence of the statistical dimensioning provided by the programs, it was decided to use the IST program (which is a part of the LPE program) to calculate the reliability of the overhead lines with known service experience. Russian pollution flashover performance data obtained in the laboratory was used as an input in the IST program to “calibrate” Russian guide for insulator selection. This Guide prescribes the number of cap-and-pin insulators for different pollution levels and is based on the long-time service experience. The results of the statistical dimensioning using IST program show very good agreement with demands of the Russian guide for insulator selection. Generally, without any additional corrections, the deviation is less than 10%. INTRODUCTION Insulator Selection Tool (IST) and Line Performance Estimator (LPE) programs have been developed at STRI with the support of Norwegian power utility Statnett and Swedish power utility Svenska Kraftnät. Statnett has already used the LPE program for the evaluation of insulation alternatives to upgrade 300 kV transmission lines to 400 kV [1]. In this case different future insulation options were compared based on pollution/ice performance data obtained in the laboratory. To increase level of confidence of the statistical dimensioning provided by the programs, it was decided to use the IST program (which is a part of the LPE program) to calculate the reliability of the overhead lines with known service experience. It was then suggested to use Russian pollution flashover performance data obtained in the laboratory as an input in the IST program to “calibrate” Russian guide for insulator selection [2]. This Guide prescribes the number of cap-and-pin insulators for different pollution

levels and is based on the long-time service experience. The general statistical level of reliability behind the Guide is known as 1 outage/100 km/year. The required number of insulators in the string is calculated using IST program for the required reliability and compared with the demands of the Guide [2]. STATISTICAL DIMENSIONING OF INSULATORS WITH RESPECT TO POLLUTED CONDITIONS The IST program uses the so-called probabilistic approach for the insulation selection in respect to pollution conditions [3]-[5], where the main parameters are considered as statistical variables, defined by average values and dispersions. This is different to the commonly used deterministic approach, where the parameters are assumed to be constant. The statistical dimensioning of insulators entails the selection of the dielectric strength of an insulator, with respect to the voltage and environmental stresses, to fulfill a specific performance requirement [5]. This selection is performed by evaluating the risk of flashover of the candidate insulation options and selecting those with an acceptable performance. With reference to Figure 1, the risk for flashover can be calculated as follows [5]:

Figure 1 Illustration of the input data needed for the calculation of the risk for flashover with respect to pollution conditions.

• It is assumed that the insulators are energized at a voltage with constant amplitude, corresponding to the maximum continuous operating voltage.

Proceedings of the 12th Asian Conference on Electrical Discharge, Graduate School of Shenzhen, Tsinghua

University Shenzhen, China, November 19-22, 2004, p.p. 10-15

• The variation of the pollution environmental stress (Equivalent Salt Deposit Density ESDD in our case) at the site of interest is represented by the probability density function “f (ESDD)”. This data is normally provided by in-service measurements.

• A cumulative distribution function “P (ESDD)” describes the strength of the insulation, which is, the probability for flashover as a function of the same measure of pollution environmental stress ESDD. This data is normally provided by laboratory pollution flashover tests.

• The multiplication of the f (ESDD) and P (ESDD) functions gives the probability density for flashover of the insulator at the given site, and the area under this curve expresses the risk for flashover.

AVAILABILITY CALCULATIONS Geometrical parameters The geometrical parameters of Russian glass cap-and-pin insulators used for the calculations are shown in Table 1 and some typical profiles for the so-called “standard”, “anti-fog” and “double-ribbed” insulators are shown in Figure 2 and Figure 3.

Table 1 Geometrical parameters of Russian insulators used for the calculations.

Insulator type

Insulator profile

Mechanical load [kN]

Creepage [mm]

Axial length [mm]

PS 40 Standard 40 198 110 PSV 40 Anti-fog 40 326 110 PSD 70 Double-

ribbed 70 412 127

PSV 70 Anti-fog 70 440 146 PS 120 Standard 120 314 146

PSV 120 Anti-fog 120 440 146 PSV 160 Anti-fog 160 551 170 PSV 210 Anti-fog 210 570 195 PS 300 Standard 300 392 195

Figure 2 Example of “standard” profile (left) and “anti-fog” profile (right) for 120 kN insulator.

Figure 3 Example of “double-ribbed” profile for 70 kN insulator.

Pollution flashover data The pollution flashover data from [6] is presented in Table 9-2 as constants (A and α) of the approximation curves U50%=A•SDD-α, where U50% is 50%-flashover voltage per insulator and ESDD is the Salt Deposit Density. The test method was Solid Layer according IEC 60507; the only difference was NSDD close to 3 mg/cm2.

Table 2 Approximation constants for the pollution flashover laboratory data of Russian insulators.

Insulator type

Insulator profile A [kV/m] α

PS 40 Standard 17,4 0,271 PSV 40 Anti-fog 31,8 0,322 PSD 70 Double-ribbed 37,0 0,415 PSV 70 Anti-fog 39,2 0,391 PS 120 Standard 35,4 0,421

PSV 120 Anti-fog 39,2 0,390 PSV 160 Anti-fog 36,4 0,317 PSV 210 Anti-fog 38,9 0,358 PS 300 Standard 34,7 0,359

Input parameters for the calculations According to the latest edition of the Russian Guide materials the pollution level and the average pollution parameters (surface conductivity) are related as shown in Table 3. The ESDD is not a primarily used parameter in Russian Guide and therefore it was recalculated in Table 3 from surface conductivity (SC) as: ESDD=SCx150. This is derived from the results of measurements of both pollution parameters performed independently in Russia and in South Africa.

Table 3 Relation between pollution level and pollution parameters.

Pollution level Surface conductivity [µS]

ESDD [mg/cm2]

I-Light 5 0,033 II-Medium 10 0,067 III-Heavy 20 0,133

IV-Very heavy 30 0,20 The following input parameters were used for the calculation using IST program:

• Standard deviation: minimum 0,3 and

maximum 0,4. This data is derived from Russian long-time measurements in the areas with agricultural and industrial pollution

• Number of events: 100. This data is typically used in Russia for evaluation of “average” temperate European climate, for example [3]

• Maximum system operation voltage for Russian overhead lines is: 126 kV for 110 kV; 252 kV for 220 kV; 362 kV for 330 kV; 525 kV for 500 kV and 787 kV for 750 kV

• Mean time between failures (MTBF) is 1 year which corresponds to the 1 outage per 100 km per year

• Typical span length is 250 m for Russian overhead lines of 110-220 kV; 300-350 m for overhead lines of 330 kV and 420 m for overhead lines of 500-750 kV. Then 3x3x4x100(km) will give 1200 parallel insulators on 100 km of 110-220 kV line; 3x3x100(km) will give 900 insulators on 100 km of 330 kV line and 2,5x3x100(km) will give 750 insulators on 100 km of 500-750 kV line.

Results of availability calculations The standard version of the IST 2.0 program was used for the calculations. Example of the standard IST windows is shown in Figure 4 and Figure 5.

Figure 4 Example of start window in Insulator Selection Tool (IST) program.

Figure 5 Illustration of the calculation in IST program for the line equipped by standard insulators PS 120.

The calculations were performed for the voltage classes 110-220-330-500-750 kV, see Table 4. The results of the calculations are compared with the recommendations of the Russian Guide as they were presented in [6]. Not all the cells of are filled in Table 4; this is due to the fact that the Russian Guide recommends certain profiles depending on the level of pollution. For example, no anti-pollution profiles are recommended for relatively clean areas, because their effectiveness is small (partial arcs often bridges the air gaps between the ribs and the creepage distance is not use 100%). Also, not all types of the insulators are recommended for all voltage classes, the mechanical class of the insulators was taken into account according to the design practice. Table 4 Required numbers of cap-and-pin insulators according to the Russian Guide and calculated by IST program (Guide/IST).

Number of insulators Insulator type Pollution

level I Pollution level II

Pollution level III

Pollution level IV

110 kV overhead lines PS 40 10/10 13/12

PSV 40 9/8 9/10 11/10 PSD 70 9/10 11/12 13/14 PSV 70 8/8 9/10 11/12

220 kV overhead lines PS 40 20/20 24/23

PSV 40 16/16 18/19 22/21 PSD 70 16/18 21/23 26/26 PSV 70 14/15 18/20 22/22

330 kV overhead lines PSD 70 22/24 30/32 37/38 PSV 70 20/21 26/28 32/33 PS 120 18/19 24/26

PSV 120 20/22 26/28 32/33 500 kV overhead lines

PSD 70 32/36 43/47 53/54 PSV 70 29/32 38/41 46/47 PS 120 26/30 34/38

PSV 120 29/32 38/41 46/47 PSV 160 26/27 33/35 39/39 PSV 210 27/30 35/38 42/43

750 kV overhead lines PS 120 39/42 51/57

PSV 120 43/48 56/60 69/70 PSV 160 39/40 49/51 58/58 PSV 210 40/43 52/54 63/63 PS 300 45/48

DISCUSSION

The results of the calculation using IST program show very good agreement with demands of the Russian Guide. The average deviation from the demands indicated by solid line in Figure 6 is less than 10%. The deviation is calculated as the number of the required insulators obtained by the Insulator Selection Tool program divided by the number of the insulators demanded by the Guide. Thus, “1,00” means that the fit was perfect. It can be seen that the deviation for the pollution levels 1, 2 and 3 is slightly higher than for the pollution level 4. This can be explained by some inaccuracy in defined input ESDD values used for the calculations. The input ESDD levels for the pollution classes 1, 2 and 3 (see Table 3) calculated from the Russian data are still under consideration of the IEC working group and may be further corrected. Another observation is that the deviation is systematically positive, which means that the insulators are slightly over-dimensioned in comparison with the Guide and thus the selection may be further corrected by some constant.

Figure 6 Deviation in the selection of the number of the insulators depending on the pollution level. The result “1,00” means perfect fit with zero deviation.

EXAMPLES OF FUTURE APPLICATIONS OF THE INSULATOR SELECTION TOOL PROGRAM

The IST program can be applied for different practical cases of statistical dimensioning which are briefly described below. Selection of insulation in ice&snow environment The same basic approach is used. The main pollution parameter in this case will be conductivity of the dripping water from the ice, see Figure 7. This parameter can be obtained by service measurements of the melted ice samples. The flashover voltage over the conductivity of the dripping water can be obtained in the laboratory using e.g. Ice Progressive Stress test method [9]. Example for the calculations for the “freezing rain” case, i.e. flashover during ice accretion, is shown in Figure 8.

Figure 7 Illustration of the input parameters needed for the calculation of the risk for flashover with respect to ice&snow conditions.

Figure 8 Example of availability calculation: Risk for flashover over the insulator length for the “freezing rain” service case for composite and glass insulators.

Selection of insulation based on test station results Insulator test stations are normally equipped by leakage current measurement systems. Using leakage current data and geometrical parameters of the tested insulators, density function of pollution stress, e.g. surface conductivity can be obtained as shown in Figure 9. These are test results for a specially developed set of composite/porcelain apparatus insulators tested during 5-8 years. The results shown in Figure 9 are completely applicable for the statistical dimensioning if laboratory pollution flashover data is also available. Similar test data is at present investigated for the South African power utility ESKOM.

Figure 9 Illustration of the input data for the IST calculations obtained from test station: density functions of surface conductivity.

Selection of insulation with different pollution exposed time (e.g. breakers in open position) The survey of breaker energization times for different types of breakers, e.g. shunt reactor, generator, line and transformer showed that this time could be very

different. This data was used for statistical dimensioning of outdoor insulation of the breakers in Scandinavia using IST program, see example in Figure 10.

Figure 10 Example of the normalized required pollution test severity as a function of exposure time for a certain required performance. Observe the difference in requirements for line and shunt reactor breaker.

Part of the Line Performance Estimator (LPE) The IST program is the part of other STRI-developed software program called Line Performance Estimator (LPE). The LPE program calculates the total risk for flashover of the line or its section, which covers: lightning performance, pollution and ice flashover performance, switching performance. Examples of the standard LPE windows are shown in Figure 11 and Figure 12.

Figure 11 Example of start window in Line Performance Estimator (LPE) program.

Figure 12 Illustration of the calculation in LPE program for line equipped by standard insulators F12/146.

CONCLUSIONS

The results of the statistical dimensioning using Insulator Selection Tool program show very good agreement with demands of the Russian guide for insulator selection. The deviation is less than 10%. The difference in the dimensioning using the IST program and the Russian Guide is explained by the difficulties in defining the ESDD value corresponding to the pollution levels from one to four. This issue is at present under consideration of the IEC TC 36 working group. A few further applications of the IST program are suggested. ACKNOWLEDGMENT The authors wish to acknowledge the contributions and support from Statnett, Svenska Kraftnät and NIIPT that made this work possible. REFERENCES

[1] K. Halsan, D. Loudon, C. Engelbrecht and I. Gutman, “Ice and pollution testing of compact insulator strings in Statnett”, 2003 World Conference on Insulators, Arresters & Bushings, Marbela, Spain, November 16-19, 2003

[2] Guide 34.51.101-90: “A guide for selection of outdoor insulation of electrical installations”, Moscow, 1990 (in Russian)

[3] N.N. Tikhodeev; S.S. Shur: “Insulation of electrical network”, Leningrad, Energy, 1979 (in Russian)

[4] V.V. Ivanov, E.A. Solomonik: “Statistical flashover voltage studies of wet polluted high voltage insulators”, Proceedings of ISH-1995, Graz, Austria, Aug. 28 - Sept 1 1995, Paper 3227

[5] C.S. Engelbrecht, R. Hartings, J. Lundquist: “On the statistical dimensioning of insulators with respect to pollution conditions”, IEE Proceedings - Generation, Transmission and Distribution, Volume 151, Issue 03, May 2004, p.321-326

[6] D.S. Pechalin, O.V. Timofeeva, T.V. Yakovleva and V.N. Golovin, “Investigation of flashover performance and establishment of the optimal areas of the use of modern glass cap-and-pin and porcelain line post insulators at overhead lines”, Proceedings of TRAVEK Conference, Moscow, 2001 (in Russian)

[7] L.L. Vladimirsky and E.A. Solomonik, “Comparison of the specific surface conductivity and ESDD approaches to assessment of salt deposits on naturally polluted insulators”, IEC 36-WG 11/Nberg/158, 2003

[8] I. Gutman, R. Hartings and W.L. Vosloo, “Insulation selection in the coastal Kelso area in South Africa”, Proceedings of 12th ISH-2001, Bangalore, India, August 20-24, 2001, paper 5-4

[9] I. Gutman, K. Halsan and D. Hübinette: “Application of Ice Progressive Stress method for selection of different insulation options”, Proceedings of 13th ISH-2003, Netherlands 2003, Smit (ed.), 2003 Millpress, Rotterdam, ISBN 90-77017-79-8, p. 179

[10] K. Halsan, D. Loudon, C. Engelbrecht and I. Gutman, “Norwegian Utility Evaluates Insulation Alternatives to Upgrade 300 kV Transmission Network”, Insulator News and Marker Report Quarterly Review, Issue 64, Quarter Two-2004, Volume 12, Number 2, 2004