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IEEE Transactions on Power Delivery, Vol. 8. No. 3, July 1993 155 1

SUMMER THERMAL CAPABILITIES OF TRANSMISSION LINES IN NORTHERN CALIFORNIA BASED ON A COMPREHENSIVE STUDY OF WIND CONDITIONS

Tapani 0. Seppa, Edward Cromer Woodrow F. Whitlatch, Jr Senior Member, IEEE Member, IEEE Pacific Gas & Electric The Valley Group Pacific Gas & Electric Meteorology Services Ridgefield, Connecticut R&D Department San Francisco, California

San Ramon, California

Abstract

Prior thermal rating studies have considered wind unpredictable. This study indicates that local winds appear well behaved and statistically prdctable and that they are not independent from the ambient temperature and solar insolation. This means that appropri- ate probabilistic analysis of wind speeds can be used to potentially increase conductor ampacities.

The study is based on use of highquality weather measuring stations which have been located in the actual environment of transmission lines. The observations indicate a high probabihty that many transmission lines in Northem California could have their ampacity ratings increased.

I NTR 0 DUCTI 0 N

Wind is the most important and the least well understood of all the parameters which govem the thermal capabilities of transmission lines. In- in ambient tempeaht increases the conductor tempemture in approximately m e to one ratio (1). Compared to nighttime with no sun, maximum solar heating typically increases the temperature of a conductor by about 10 OC and reduces its thermal capability by 6-10% (2), (3). On the other hand, even a minor change in wind speed, e.g., f" 2 to 4 Wsec, increases the transmisson line capbdity by 20-30%(3). If the wind speed increases h m 2 Wsec to 10 Wsec, line capabilities increase about 50 7%. Such increase is seldom needed.

There exist numerous published reports on the thermal balance of conductors. The existing thermal models allow calculation of conductor temperature with an accuracy which is more than sufficient for any operational purposes. What is generally lacking is accurate data of the limiting wind conditions.

Because wind conditions are highly variable, it has been common to consider wind as a random variable which is assumed to be independent from temperature and solar radiation. Therefore, many utilities have developed separate summer and winter ratings and separate day versus night or "ambient adjusted" ratings. The

92 SM 567-8 PWRD A paper recommended and approved by the IEEE Transmission and Distribution Committee of the IEEE Power Engineering Society for presenta- tion at the IEEE/PES 1992 Summer Meeting, Seattle, WA, July 12-16, 1992. Manuscript submitted October 11, 1991; made available for printing June 7, 1992.

intent has been to separate the more predictable temperature and solar radiation from the less predictable wind. The practical con- sequence of this is that many utilities have lowest transmission capabilities dunng summer aftemoons, which commonly coincide with the maximum power demand.

With the advent of line mounted sensors during the past years, some utilities, PG&E included, have been able to observe that the limiting conductor temperatures can often occur at times other than summer aftemoons and that highest ambient temperatures appear not to correlate with highest conductor temperatures.

Studying prior data from field tests made it quite evident that the most critical missing data was that of low wind speed conditions in actual transmission line environment. Weather stations, e.g., NOAA sites, are generally located in open terrain, (e.g., airports). Wind sensors at these locations commonly have threshold speeds which are of the order of 5-8 Wsec Typical airport weather records consist of once per hour observation of wind speed, wind dwxtion and temperature. Because typical transmission conductors have thermal time constants in the order of 10-20 minutes and because the critical thermal conditions occur at wind speeds of 2 to 4 ft/sec, such data are not very useful for the assessment of conductor ampacities.

PG&E has a large service temtory and the weather conditions vary widely from one region to another. The company has two summer thermal rating zones for its transmission lines, the sole difference being different ambient temperature assumptions. The normal ratings are based on perpendicular wind of 2 ft/sec, full solar radiation and an emissivity of 0.5. The ambient temperature assumption is 109 O F (43OC) for the interior region and 99 O F (37 "C) for the coastal region. The design ratings are based on 80 "C normal temperature for ACSR and 75°C for AA conductors.

The data SupPcaQlg this repcat are a subset of a 15 s i a k " 1 o g i c a l and conductor monitoriDg network The slations were h d e d by various

data collection were performed by the Meteorology services of F " s Gas Conhl Department. Measurements and support for the two sites discussed below we^. provided by the Gas& Electric Transmission Department. A very large amount of data was collected during 1990 sumnrx(15si@ eachwith 15,cloOI.ec(xds~ofB30dab@b; i.e.,ahnost5 million datapoiilk). The various sites show majorM- in diurnal wind pattens Two sites were selected asexamples to be used i n t h i s r e p o l t a n e m t h e i n h i o r ~ ~ d a ~ i n t h e d r e g i o n . While the differences between the two sites are very substantial, the overall ccnclusim&hcanbebwnindicateimpcxtant similantiesregardmg the critical wind conditions.

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What makes the thermal rating decisions even more complex, is that each region has transmission lines of differing daily load characteristics. Typical feeder load cycles are shown in Figure 1. Curve 1 is a load in a feeder supplying combination of residential and commercial loads in the Bay Area. Curve 2 is a similar load combination in the Central Valley, while curve 3 is a commercial load in the Bay area. The residential loads have a sharp peak at 6- 7 p.m. local time (5-6 p.m. standard time). The commercial loads peak earlier and decline before the sunset. Load patterns of major network transmission lines are naturally much more variable.

- INSTRUMENTATION The instrumentation for PG&Es field weather stations was

specially selected to be both accurate and responsive for low wind speeds. Propeller-type anemometers were used for measurement of both horizontal and vertical wind speeds. The anemometers had a threshold wind speed of 1 Msec. Wind direction was measured using a wind vane with a threshold wind speed of 1 ftlsec. All sites were equipped with an ambient temperature sensor. Conductor temperature sensors were also used at 10 sites. The instruments were mounted at the height of 10-15 meters above ground, i.e., close to the height of the tranSmission conductors. Weather i " e n t s were routinely maintained and calibrated for maximum accuracy.

The data were collected with on-site data loggers, which recorded average weather conditions at 10 minute intervals. Addi- tionally, lowest one and five minute wind speeds during the 10 minute period were recorded, as well as the standard deviation of the wind direction fluctuations. The logged data were processed with a statistical data sorting program which allowed a broad range of analysis options.AU~~omareinpaCificstandardtime( lhourder than local summer time).

FIELD OBSERVATIONS

Mi-Wuk substation test site m-Wuk test site is in a fmsted region on the western slopes of the

Sierra Nevada mountains located near Mariposa, CA, (elevation @ 4OOO fi) . Thetraasmissonline at the site is a 115 kvlmeof 3975 kcmil ACSR conductor. According to pG&E's present ratings, the conductor has an ampacity of 49 1 A for 80 OC maximum tempemture.

There are several reasons which make this site interesting for thermal ram studies. Because the h e comes from a hydm plant, it isgenemllyopaatedateither380-440A oratlessthan1oOA; 50% of the time dunng 1990 summer the line was operated at 360-450 A. The site has very low summer winds, the median wind speed being only 2.4 Wsec. This is caused by the location of the site in a valley with the anemometers at the level of forest canopy. Furthermore, because of the hgh altitude, the combination of reduced convective cooling and increased solar radiation would indicate that t h s site should be one of the thermally critical locations.

The averages of all 1990 summer observations of ambient and conductor temperatures as well as horizontal and vertical winds are shown in Figure 2. Note that the horizontal wind dies down every moming and every evening during periods of wind flow reversal. Although the ambient temperature in the moming is generally lower than the evening temperature, the quiescent period

0 2 4 e e m P Y 1 1 2 0 P a 4 HOUR OF M Y (P8V

Fig. 7. Typical load cycles in PG&E's service area.

Fig. 2. Wind and temperature observations at Mi- Wuk substation. NUMBER OP OBSERVATIONS --

s2

28

24

20

16

12

8

4

0 " " "

10-MXN OBSERWTIOtiS

1 2 3 4 I 6 7 6 ~ 1 0 1 1 1 2 1 3 1 4 1 J 1 6 1 7 1 6 1 9 2 ~ 2 1 2 2 2 3 2 4 HOUR (PST)

Fig. 3. Diurnal distribution of condudor temperafures over 60 "C at MJ- Wuk substation.

is generally longer in the morning, causing a more pronounced tempera- maximum in the conductor in the moming than in the evening.

In spite of the very low wind speed conditions, conchactor tempemtures only occasionally ex& 60 "C at Mi-Wuk Figure 3 shows that the high temperature events occurred during morning and evening hours when lower wind speeds prevail. There were a total of 19 such events, the longest of whch was 130 minutes and the shortest 20 minutes. The total number of such 10 minute observations was 114. The conductor temperature never reached 60 *C dunng the aftemoon.

The reason for these observations can be found in the wind


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statistics. Figure 4 shows the dislribution of measuled wind speed for all days dunng the summer. It indicates that daytime winds exceed 2 ftJsec 95 % of the time. On the other hand the nighttime winds only average about 2 Wsec. There is a 5% probability (lowest 5% of observations) that the wind is m i n t h e "ing and in the evening. Note that the average vertical speed, as shown on Figure 2, is typically of the order of 2 Wsec during daytime but does not exist at night.

Another impatant observation at Mi-Wuk site was the variation of conductor temperatme which is caused by local wind variations. The two line temperature sensors at Mi-Wukare approximately 1500 ft. from each other. Statistically the two se~lsors seem equivalent as indicated by the quantile distribution shown in Table I1 below, but instantaneous tempera-s can be significantly different.

Table I. Temperature quantiles recorded at Mi-Wuk

Quantile Sensor 1 Sensor 2 50 % 38°C 37°C 90 % 52°C 51°C 95% 54°C 55°C 99 % 59°C 59°C

We sorted out all events during which either one of the conductor temperature sensors indicated a temperature of over 60 OC, and compared the two values. The total number of such 10 minute recordings was 140. An example of this series of readings is shown in Figure 5.

The hstogram in Figure 6 shows the temperature difference between the two sensors during the highest conductor temperatures. This indicates that local variation of wind causes significant temperature differences. Because the average temperature rise over the ambient for the 140 measurements was only 3OoC, the observed 3.5 OC mean difference between the two sensors is quite significant (over 10 % of temperature rise over ambient). More- over, as shown by Figure 6, there were six instances when the temperahwe difference was over 10 OC (i.e., of the order of 30% of the temperature rise).

Conductor temperature depends on wind speed and wind direction. Short term variations of wind speed and wind direction are cawed by the turbulence of the wind and therefore Iwnuledge of turbulence with a time scale of 1-10 minutes is very important. Figure 7 shows the standard deviation of wind direction during high and low ambient temperatures at Mi-Wuk. Note that the direction of low speed winds is highly variable, when ambient temperatwe is hgh.

The observations depict facts which are commonly acknowl- edged by micrometeorologists:

*Relative turbulence depends on Wind speed and temperature. Low speedwmds dunnghighdaythetemhaes ammorevariablethan higher wind speeds.

*When the ambient temperature is high, i.e., typically during after- noons, winds have high directional variability. Rolonged low speed daytime winds parallel to the conductor are extremely improbable,

1 2 a 4 6 a 7 I ) o 1 0 n o ~ ~ m 1 ~ w m 1 0 2 o a ~ z s ~ 4 HOUR OF M Y (PST)

Fig- 4. Diurnal distribution of wind at Mi-Wuk substation. WO wind means the lowest 5% of observations.

i z 1 4 I c i 8 9 io ii ia 13 14 IS 16 ii SI OBSERVATION NUMBER

Fig. 5. Series of observations at Mi- Wuk , 8-7-90 evening.

NUUEEER OF oB(KRmTI00 46, I I I I I I

40

S6

a0

26

20

16

10

6

0 0 - 1 2 - 8 4 - 6 6 - 7 0 - 0 1 0 - 1 1

TEMP WFERENCES W DE0 C

Fig. 6. Conductor temperature difference of two sensors at Mi-Wuk substation, when at least one sensor indicated over 60'C.

WINO ST0 DEV IN OEQREES

1 2 3 4 6 a

WINO ST0 DEV IN OEQREES

1 2 3 4 6 a especially as daytime verticai winds are also sipficant. WIND SPEED FllSEC

BY Comparing the lifr~-dimension Ofthe t"ce to the average Fig.7. Standard deviation of wind direction fluctuations at Mi- Wuk substation.

-~ . _- -


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wind speed, the average distance dimension of the turbulence can be i n f e d . Typical turbulence envelope of wind gusts at Mi-Wuk is of the order of several hundred feet and is larger during hot pen& than during cold periods. This important conclusion will be discussed later in detail under the “General Observations“ section.

‘ 1 2 1 e o n l y r a t i n g ~ c u s forthe M-wuklinemdesignsagsand cleamwx ‘Ihe sagsdependon the average tempatme of the conductor. Figure8 ~ t f r z p r o b a h l l t t y ofthe~reoordedavadgesofthetwo measured conductor tempemtures at Mi-Wuk. These are the lughest tempemtmsobeetvedwhentheumductor currentwasbetween370and 450k (l%r5704oftheob~m&aB ’ thelinecunentwas4COklO A). Nde tbat the probability for the extreme teqxmture ohmvations at this site appearsapppximatelylogan~c,dextzphan~lndicatethat tbpdabhtyoftheavemgetemp”exceechng 8ooc was O.ooOOl% for the e 1 0 A current level.

The cooductaratMi-Wukhasanomoalratingof491A f o r a m a x i “ temperature of 8OoC. From the collected data we can d e r that if the conductor current were 491 A, the Mi-Wuk site would exceed this temperaturelest€xm 0.001% oftimedunngthesurmner.’Ihtsdd~ a probability of one occmnce of a l@miuute penod of 80°C conductor temperatmeduring tensummas, ifthelineloadwereaccmtant491A

There is an interesting theoretical explanation for the approxi- mate logarithmic shape of the peak temperature distributions found at Mi-Wuk. Peak temperatures are clearly related to the length of near calm wind periods in the morning and evening. When wind speed lowers, the conductor warms in a manner dictated by the well known exponential time constant relationship. Thus, if the length of near calm periods is randomly distributed, probability distribution of peak temperatures would assume a logarithmic shape shown in Figure 8.

Kifer-Trimble substation test sites These test sites consists of two weather monifofing locations which

areonly 2rmlesapa1t,aboutl5rmlesfiromthePacificOcean, nearSan Jose. The sites are equipped with similar instrumentation as Mi-Wuk. The h e between the substations is 115 kV, 715 kcmil AA. There are two conductor sensors at each end of the line. Summer season wind flow is typically a sea breeze that develops in response to mesoscale surface pressure gradients. The gradients strengthen when the temperature differential between the cool Pacific Ocean waters and hot interior valleys is at maximum dunng the afternoon.

T h e l a a d v a r i a t o n a t K i f e r i s s i ~ f i ~ y d i ~ 6 o m M i - W u k a n d

~ t h e ~ c ~ c t e ~ v ~ ~ ~ a ~ i ~ d a y o f

of all observations at Kifex is shown in Figure 9.

theloadpeakstpcally chnmgthe day. Because of s&&”l Variations

obsematim i s n x n e c a n p h d t b m a t t h e M i - W u k s h e . A ~ on

The daily wind speed variation at Kifer is significantly different from Mi-Wuk. Even during the night, the average summer wind speed exceeds 5 ft/sec. The wind speed increases rapidly during the day and peaks m late afternoon. The load at %fer h e typically peaks in the early afternoon, when the wind speed is already quite high. Statistically, this means that at %fer the likellhood of a combination of hgh load and low wind conditions is unlikely. As shown by figure 9, the load has typically declined significantly before the onset of the quiescent wind period at night. The most likely

1

m.1

I I I I I I I I I I

0.01 . T 60 61 62 63 64 65 66 67 68 69

DEG C

Fig. 8. Probability of highest observed average temperatures at Mi- Wuk substation, summer 7990. AN currents over 370 A.

FTIOEC AUPBXlDOR DEPC

i s 6 7 m n m m n o n 2 a HOUR Of M Y (BT)

Fig. 9. Average daily conditions at Kifer substation, summer 7990.

NUUEER of OBSERUTIONS 10 -,

0 - IamWucrorrTEUP

I)--

7 -.

I ) ) ! , ! , : , ; , : 1

01 09 os 07 om n m I n m m 2s HOUR Of M Y (P8T)

Fig. 70. Diumd distribution of highest conductor temperatures at Kifer substation.

FTISEC

1

1

1

I s I 7 m n U 16 n a P( 9s

Fig. 7 7 . Average and the lowest 5% quantile of wind speed observations at Kifer substation.

HOUR Of M Y (-1)


~

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STD DEV IN DEBREES thermally critical time period is late morning. This is indicated by the highest recorded conductor temperatures shown in Figure 10.

The record of wind conditions shows clearly the prevalence of high summer wind speeds at this site. As shown by Figure 11, even the 5 % wind speed quantile exceeds 4 ftfsec during the aftemoon and evening, until approximately 8 p.m. local time.

The standard deviation of the wind direction fluctuations show a pattem of turbulence which decreases with wind speed and increases with temperatwe. This is shown in Figure 12, in which the observations are dlvided into groups based on ambient temperature. 1 3 6 7 0 11 ls M n

WIND SPEED FTlSEC

The highest Conduc~ tempaatureS quite law, which makas the fe8son is

Fig. 72. Standard deviation of mean wind direction at Kifer substation for high and low ambient temperatures. c o m ~ s o n less meaningful than that at m-w& %

obv&ly the high wind speeds at the Kifer site. "e were only 37 instanceswhenthelinetemperahm:exceeded5o"c,and~only

~was~s00and570ATheAAcoraductor i s1a teda t 699 A for a 75°C conductor temgerature. It is obvious that at this site the conductaropemtesmuchcoolerthanassumedbycoastaltatings,and its

18-25 "C temperam rise O V ~ the ambient. The Current chning t h m

ampacity couldmost likebe increased substantiall Y.

c o " s m & b t h e m ~ m a t m H -

~ w f i e n ~ ~ ~ b y s e r s o r 1 w a s a t l e a s t 5 o O c . Agammcan

c " ! d t o M i - w * t h e m e d i a n t e ~ v m o n ~ t h e m

Trimble. A s w t e d e a r h ~ , t k ~ ~ ~ o v e x l h e ~ m t k q u i t e l u w atKikr. ~13stKlwstf ietempadturedif f ixence~sawxs1and

notice that in spite of significantly dlfferent overall wind conditions

~ a m o u n t S to 2-3 "c, when tbe temperature k Of the orderof 20- 30 "C. The 10 % is consistent with the Mi-Wulc obmvatiom.

Trimble site is 2 miles distant from Kifer. As shown by Figure 14, the two sites are statistically equivalent. The wind speeds and conductor temperatures are statistically equivalent, within observation errors. Standard deviation of the wind direction fluctuations at Trimble is also similar to that of m e r , shown in Figure 12. Thus we can make the im-t observation that the two sites, separated by a distance equal to that of two deadends of a tsansmission line, show statisticallv equivalent cooling conditions.

Thu does not mean that the simultanm coo@ conditions are the same. While the ambienttempenlturesarethe same within the margin of observation error, the instantaneous wmd conditions are not equal. By sorting out the difference between simultaneously observed wind speeds at the two sites, we can derive Figure 15.

Note that the observations of Figure 15 indicate that:

If the wind speed at one of the sites is low (0-4 Wsec), the wind at the other site is likely to be about 0.5 ftfsec higher.

If the wind speed at one site is high, it is likely to be 0.5 ftfsec lower at the other site.

Thus, the comparison of the wind observations at the two sites indicates that low wind speeds are improbable to occur simultaneously at two sites two miles apart. As stated before, the same. observations could be made for shorter distances based on the observed temperature variation between two temperature sensors in adjacent spans.

NUMBER OP OISERWTIONS

- 0 1 2 3 4 SENSOR TEHPEPKWRE DIPPEPENCES (DE43 C)

Fig. 73. Observed tem rature variation between sensors at Kifer substation when c o n g t o r temperature was over 50 "C.

TEMP m DEQ c WIND OPEEO FTISEC

i a 6 7 s n l s i s n r o n z s HOUR OF DAY (-1)

Fig. 74. Diurnal variation of wind speed and conductor temperature rise over ambient at Kifer and lrimble substations.

DIFFERENCE IN FTISEC 0.8 I I

I KIFER - TRIYBLE

I 0.2

0

-0.2

-0.4

4 7 s 8 - , I 2 -0.8 N E WIND SPEED IN FTlSEC

Fig. 75. Difference in wind speed at lrimble compared to Kifer, and at Kifer compared to lrimble.


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GENERAL OBSERVATIONS

Within PG&E’s service area

’Ihe focus of thisreport is the examination of plumnary data analyses

detail spatial and temporal horizontal wind profiles at all sites. The m e ~ l ~ c a l p r o g r a m w a s s p e c i f i d y ~ g n e d t o ~ c o n d i t i o n s representative of the monitored conductors. Data presented here and ~ ~ y ~ o f ~ ~ ~ ~ o w u s ~ ~ t h e ~ ~ ~ g ~ a -

fmm two of the fifteen- sites. Furthastudies&waywill

tim reg- the Summertrme .

inthePG&Eservicetefri~.

conditions:

1 . C h a h o t s u ” e r d a y d P e e d i f f e r e n t t ~ ~ e x i s t attyplcal sites

*Winds increase during daytime as the surface tempemture rises and decrease during the evening hours after the ambient temperature has peakedIumanysectiolsof€G&Esservicearea,thaeisahighpmbab&y thataftemoonwimlswill sipficantly exceed the 2 ft/sec used in FG&E‘s normal ratings. Indaytimehouqwinddirectioavariance ishighdunng periods of low wind speeds, indicating that prolonsed low speed winds parallel to the conductor are very unlikely.

Nighttime winds are generally lower than daythe winds. Average

is low during nighttime low wind periods, meaning that udavorable parallelwindconditiommayexistatmght.

dspeedsvaryl i t t le~hourtohwratmght . winddirectionvariance

-During themominghoursthewind flowregime~itionsbetween mghthraeddaytime~vicevemintbeveninghoursThel-.n;cles2 average wind speeds of the day are measured during these quiescent

CondifioIlS in each region. p e r i o d s . ~ t i m e s o f t h e ~ ~ t p e n o d s m a y v a r y w i t h ~ l ~ c a l

2. Vertical wind speeds peak during the daytime. Combined with the autoccnvectiveflwge”kdbythebot&torthisindicates hatcalm C a n d i t i o n s a r e p O b a M y b r i e f a n d ~ ~ y ~ ~ ~ c h m n g d a y t i m e .

3. Typical daytime turbulence pattern have a wind gust dimension along-wind of several hundred feet. Gusts of those dimen- sions will have significant cooling effects on transmission conductors. Although it is possible to find a location where low wind speed persists for long enough to cause a h g h temperature at one point of the conductor, simultaneous calm conditions at a location only a short distance away m highly unlikely. a s means that the average temperature of any span is likely to vary much less than that of any single point of conductor.

3. Thermal line monitors used at PG&Es lines have proven reasonably reliable and accurate. The main problem in their application is the wide statistical variation of temperature along even a short section of transmission line. The sags of the line, which are the main concerns, depend on the average conditions of a ruling span section (between two deadends). As shown by the statistics at Mi-Wuk site, use of a single sensor set at 60 OC warning level would have been substantially in error- both low and high- in a high percentage of cases.

4. The significance of the wlnd studies is that they can be used to identify regions where weather and load conditions are substantially non-coincident, indicating times when there is a high probability that lines are under-utilized or when the line loads approach

the bounds of safe operations described by the static rating guide- lines. Wind studies can only indicate probability limits. This knowledge can be used by a utility to gain ampacity increases where feasible, keeping in mind the limitations imposed by utility rating standards, practices and applicable codes and indicating where instrumentation-intensive rating approaches (4) could be used profitably.

5. There are many interesting qualitative observations which cast some of the prior practices in doubt. For example, it has been generally considered that old, weathered conductors with h g h emissivity/absorptivity are more prone to h g h temperatures. But this assumption is valid only if the combined cooling conditions are worst during daytime. On the other hand, high emissivity will increase radiative cooling, which is of significance for nighttime conditions. The combined cooling conditions are, in the observed cases, worse during night than day. Thus new, shiny conductors could have a hgher thermal risk than old, weathered conductors.

6. The observations show that, because of the generally conserva- tive rating assumptions of PG& E, there is a very high probability that the studied transmission lines could be rated hgher. In case of Kifer -Trimble line, the probability amounts to certainty. In case of Mi-Wuk, there appears to be a possibility of uprating the line 15- 20% for 99.9% of time and 3040% higher 99% of time. Note that the primary reason is that the 2 #sec minimum wind speed used in PG&Es ratings has a very low probability of occurring during daytime (5). Note also that the results are highly sensitive to relatively minor changes in rating assumptions (6).

For conductors which are steadily loaded, the highest conductor t e m p e ” s appear generally to coincide with these quiescent periods during the morning and the evening. For conductors which are loaded with the typical dshbution feeder loads of PG&E, it appears unlikely that the peak temperatures will occur during the time of peak load.

The authors plan to continue the evaluation of the vast amount of collected information with the intent of a closer study of coincidence between load and cooling patterns and to identify where future wind monitoring sites are needed.

Applicability to other regions

The observations described above apply to two sets of weather conditions in the PG&E service area. Because the observed wind behavior exhibits gemally recoglllzed micrometeorological facts, the general nature of the observations is applicable to other locations.

Observed diurnal wind speed pattems have a statistical similar- ity regardless of environmental regime differences. For example, diurnal wind patterns measured in other countries (7),(8) are s M a r to the two discussed in this paper. The similar observations are true regardmg the statistical dependence of turbulence of wmd as a function of temperature, variation of wind speed as function of height and observations of tempemture variation along the conductor.

CONCLUSIONS

1. Wind measurements whch are made with highly sensitive instruments in actual t ” i s i o n line environment indicate that the studied transmission lines are mted consetvatively. They also indicate that wind


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(9) J.F. Hall, A.K. Deb, J. Savoullis, "Wind Tunnel Sudies of Trans- mission Line Conductor Temperatures", IEEE-PES T&D Confer- ence, Anaheim 1986 (86 T&D 500-3)

(10) WJ. Steeley, A.K. Deb, T.P. Mauldin, "Dynarmc Thermal Rating of TianmissiOn Lines Independent of Critical S a p Analysis"JASTED Conference, Phoenix 1988.

speed has a correlation with ambient temperature and time of day. The Illeasurementsindicatethatdaytimesummer a f l e m o o n c o o b d t i m in PG&Es service a m were generally better than nighttime or early momingconditim.

3.The c r i t i c a l ~ d t i o n s w h i c h r e s v l t i n thehgh&cm&b temperatures appear to be related to the pmbability of prolonged calm periods. l%is is of significant importance for the assessment of benefits of probabilistic line rating. We conclude that it seems likely that the

based on the g e n d observation that the time length and physical extent of the calm periods is most likely to be xandomly distributed.

ppobabtlity d l s t r l ~ o n o f h i ~ c o n d u c t o r te"islogarithmic,

4. Vertical wind @ adds a significant amount to the coohng of the

mmns why conductor ampacity models based on weather obmations ~ n ~ y o v e r e s t i m a t e t h e c o n d u c t o r t e ~ ~ ~ d a y t r m e .

conducbdurlngsu"erdaytime.omithingulisfibctormaybeoneofthe

5. F d y , the d s t u b s d a t e that the wind cooling conditions of the conductor are not likely to be deterministically Wctable, but appear to be statistically well predictable.

REFERENCES

(1) Glenn A. Davidson, "Considerations in the Application of Advanced Conductor Rating Concepts, " Proceedings of Seminars on Real Time Ratings of Overhead Conductors, Atlanta, GA., May 21,1986.

(2) W.Z. Black, R.A. Bush, "Dynamp- a Real-Time Ampacity Program for Overhead Conductors, "Proceedings of Seminars on Real Time Ratings of Overhead Conductors, Atlanta, GA., May 21, 1986.

(3) W.Z. Black, R.A. Bush, "Conductor Temperature Research," EPRI Final Report for Project 2546-1, EL 5707, May 1983.

(4) D A. Douglas, "Maximum conductor temperature-Effects on cost and thermal rating for new and old lines," Proceedings of Seminars on Real Time Ratings of Overhead Conductors, Atlanta, GA., May 21,1986.

(5) IEEE Standard for Calculation of Bare Overhead Conductor Temperature and Ampacity for Steady-State Conditions. IEEE/ PES, New York, 1986. (IEEE/ANSI Standard 738-1986.)

(6) Tapani 0. Seppa, Woodrow F. Whitlatch, "Wind studies show a low daytime thermal risk for transmission conductors." Trans- mission & Distribution, Vol. 44, No.5, May 1992.

(7) Seppo Huovila, "On the Structure ofWind Speed in Finland," Finnish Meteorological Ofice Contributions, 69, Helsinki 1967.

(8) G.M.L.M. van Der Wid" "A new probabilistic a p o a c h to thermal rating overhead line conductors in the Netherlands", IEE con$ on overhead line design and construction, London Nov. 1988.

AUTHORS

Tapani 0. Seppa (M '72-SM75) was born in Lapua, Finland on December 29,1938. He received his Diploma Engineering (MSEE) degree from Helsinki Technical University in 1962.

From 1960 to 1969 he was a research engineer at Imam Voima in Fdand. He held research and engineering management positions at Reynolds Metals in 1969-1970 and at Bumdy Corporation in 1971- 1975. In 1975-1981 he held several development and marketing management positions at Lapp Insulator. He was VP-Strategic Man- agement at Clevepak Corp. in 1982-1985 and VP-Marketing of Nitech, Inc. in 1985-1990. In 1990 he formed The Valley Group, a consulting company specialivng in advanced technologies for utility T&D systems. He has been active m a many IEEE task fixes and has authored a large number of papers for IEEE, CIGRE and other OrgaIliZatiOnS.

Edward G. Cromer (M '89) has 28 years of utility experience in engineering and operating positions with Montana Power and Pacific Gas & Electric. He is presently Director, Transmission and Distribu- tion Construction and Maintenance of Nevada Power. He received his BSEE from Montana State University in 1963. He is currently a Program Manager in PG&Es Research and Development Depart- ment. He is active in IEEE and EEI.

In EEI, he is the chairman of the T&D Committee's EMF Workmg Group, a member of EEI's EMF Technical Task Force, and an EEI repsentative to IEEE SCC28 Non-ionizing rahation. In IEEE, he is a member of the ESMOL Subcommittee and many of the ESMOL W o r m Groups and Task Forces, and ESMOL liaison with EPRI for M&O electrical testing. He is Vicechamam of ESMO-93.

Woodrow F. Whitlatch, Jr. was born in Tarentum, PA on January 8,1949. He received his BA h m Belmont Abbey College in 1970, his BS in Meteorology from San Jose State in 1980 and his MS in meteorology from San Jose State in 1990.

He has been employed as a meteorologist by Pacific Gas and Electric since 1980, where his main duties include o p t i o n a l weather forecasting, field project design and management, climatological analysis and air pollution modelling. He is a member of American Meteorological Society and the Air And Waste Management Associa- tion.


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Discussion

S. D. Foss (Underground Systems, Inc., Armonk, NY): The authors are to be commended for adding to the database of existing weather and overhead conductor temperature data by adding data from Northern California where the thermal capacity of overhead transmission lines was evaluated. Unfortunately, the author’s fail to cite prior weather and dynamic line rating research which also reflects the cyclic time of day dependence of overhead line ratings in other parts of the world. The time of day cyclic nature of dynamic line ratings has been investigated extensively by the Niagara Mohawk Power Corporation in recent y e a r s l ~ ~ . ~ .

The author’s over emphasize the significance of vertical wind speeds derived by natural convection forces perpetuating the flow of vertical air. Barrett cites that these forces perpetuate vertical wind speeds in the range of 0.82 ft per second. Natural convection heat transfer correlations presently account for vertical wind flow. The author’s conclusion that vertical wind speed adds a significant amount to the cooling conditions of conductors during hot summer days is grossly overstated. During hot summer days, by the authors own admission, horizontal wind speeds during the mid day average 4.5 f p s as opposed to an average mid day vertical wind speed of 2 fps. The vectorial sum of the two orthogonal wind directions is an effective wind speed of 4.9 fps not surprisingly different from the horizontal wind speed. A factor contributing to the overstatement of the effect of vertical wind is horizontal cup anemometer stall under low wind speed conditions.

The authors circumvent the issue of critical span by considering average line temperature, Figure 9, rather than average span temperatures. The issue of critical span remains a dominant issue to dynamic line rating. To date, no scientific data linking average conductor line temperatures with critical span conductor sag has been demonstrated.

The author’s make the general observation that the use of a single sensor set at a 60°C warning level would have been substantially in error, both low and high, in a high percentage of cases. We reiterate our position in our closing statement with regard to single point measurement made earlier ’.

“We circumvented the problem of single point measurement in regard to measuring average span temperature by time smoothing the single point measurements over a time period sufficient to capture the variability in weather conditions experienced by a span. _ _ . The dynamic and forecast rating algorithm further time smooth the temperature data for a period of one hour. Time smoothing enables one to acquire a distributive sample of conductor temperatures resulting from a variety of local weather conditions exposed to the span. Time smoothing makes it possible to obtain average span weather and conductor temperature conditions from a single point measurement.”

Single point conductor temperature measurements combined with arithmetic time averaging of acquired data has been demonstrated as an effective means of determining average span temperature. If the spot location of the conductor temperature monitor is at a critical span site, a powerful real-time monitoring technique develops for rating a power line.

References

Foss, S. D., H. S. Lin, R. A. Maraio and H. Schrayshuen, “Effect of Variability in Weather Conditions on Conductor Temperature and the Dynamic Rating of Transmission Lines,” IEEE Trans. PWRD, Vol. 3, No. 4, October 1988, pp. 1832-41. Foss, S. D. and R. A. Maraio, “Dynamic Line Rating in the Operating Environment,” ZEEE Trans. PWRD, Vol. 5, No. 2, April

Foss, S. D. and R. A. Maraio, “Evaluation of an Overhead Line Forecast Rating Algorithm,” ZEEE Trans. PWRD, Vol. 7, No. 3, July 1992, pp. 1618-27. Chisholm, W. A. and J. S. Barrett, “ilrnpacity Studies on 4YC Rated Transmission Line,” ZEEE Tra,i.c. I’WRD. Vol. 4, No. 2, April 1989, pp. 1476-85.

1990, pp. 1095-1105.

R. Bush (Georgia Power Company, Forest Park. (3.4): How do you incorporate vertical wind speed to obtain an effective perpendicular wind. Some account should be made either in the data collection mode or in software in the temperature calculation model to account for vertical wind speed. Also, arc thc effects oi the vertical wind speeds significant?

V.T. MORGAN (CSIRO Division of Applied Physics, Sydney, Australia): The authors have presented an interesting paper describing some of their results from field measurements of wind characteristics, air temperature and conductor temperature. Some further details about the instrumentation would be appreciated. What type of sensor is used for measuring conductor temperature, and is the surface temperature measured?. What was the sampling rate for the wind and temperature sensors?

Variable line current tends to confuse the effects of the atmospheric variables on the diurnal and statistical distributions of conductor temperature. We studied the heating of a flat triangular configuration of a 5W3.5 mm alumium plus 713.5 mm steel ACSR conductor carrying a constant 50 Hz current of 1500 A over a 32 month period [l]. Some of the statistical results are given in C2.31. We also found that the wind speed decreases during the night. We did not find calms at about 0700 and 1900. but found that the highest probability of low wind speed occurs between 0400 and 0700. The maximum wind speeds occurred at about 1400. in agreement with the results of other studies [4-61.

We have not observed an increase of the standard deviation of the wind direction with increasing ambient temperature at constant wind speed. Turbulence is usually expressed in terms of the intensity and the scale. The intensity Tu is equal to the standard deviation of the wind speed divided by the mean wind speed. We have observed that TU increases as the wind speed decreases.

Our results do not confirm that the probability of the highest temperatures follows a logarithmic law. It would be better to examine the probability of the highest temperature rises, which are almost independent of ambient temperature. We have found that the probability curve of temperature rise flattens out at the highest temperature rises, so that i t is inadvisable to extrapolate to even higher temperature rises (or temperatures).

The use of mean curves for the diurnal variation of wind speed and conductor temperature can be very misleading. We prefer to plot frequency contours. Could the authors please indicate where i t is demonstrated that “vertical wind speeds add a significant amount to the cooling of the conductor during summer daytime”?

References

c11

P I

c31

141

c51

Morgan, V.T., “Instrumentation and data handling on a model overhead power transmission line, Proc. Conf. on Measurement, Instrumentation and Digital Technology, Melbourne, Australia, October 31 - November 2, 1984 (Institution of Engineers. Australia), pp 14-18.

Morgan. V.T., Thermal Behaviour of Electrical Conductors, Research Studies Press (John Wiley), 1991. pp 567-591.

Morgan, V.T., “Statistical Distribution of the Temperature Rise of an Overhead Line Conductor Carrying Constant Current”, Electric Power Systems Research (in press).

Agbaka. A.C., “Experimental Investigation of the Possible Correlation of Wind Speed on Insolation”. Energy Conversion Management. Vol. 27, pp 45-48, 1987.

Chen. A.A., Daniel, A.R.. Daniel, S.T. and Gray.


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2 -

1 -

C.R.. “Wind Power in Jamaica”, Solar Energy, Vol. 44, pp 355-365. 1990.

Skidmore, E . L . and Tatarko, J . , “Stochastic Simulation for Erosion Modelling:, ASAE. Vol. 33. pp 1893-1899, 1990.

p i n

Manuscript received J u l y 31, 1992.

D. Douglass (Power Technologies, Inc., Schenectady, NY): I would like to compliment the authors upon writing a fine paper that is clearly written and of considerable worth to the power industry. I have the following comments and questions:

I am puzzled by the relatively small variation in conductor temperature shown in Figure 2. As near as I can read the data in that figure, the conductor temperature varies over the range of 40°C to 48°C during the 24 hour period shown while the temperature rise above ambient varies between 20°C and 26°C. Yet the plotted magnitude of the combined wind speed changes from about 2 ft/sec to nearly 5 ft/sec in the aftcrnoon. A change in wind speed of 2.5 to 1.0-all else being equal-should yicld a change in conductor temperature rise of nearly 1.6 to 1.0. In addition, solar heating during the daylight hours should add between 5°C and 10°C to the conductor temperature rise above ambient. Therefore, I would expect a considerably larger variation in measured conductor temperature if the plotted weathcr data is correct. Would the authors care to clarify what is going on in Fig. 2? System operators are typically interested in the thermal capacity of their transmission lines not the temperature of the conductors. Line thermal capacity may be calculated based on either measured line temperature and weather data or on weather data alone. As suggested by Foss [l], when the line temperature rise above ambient is small, the thermal capacity is bcst calculated using weather data alone.

Given the small line temperature rise above ambient shown in Figure 9, what is the usefulness of measuring line temperature. Would it not be better to simply calculate thermal capacity based on wcather data. Will the authors please comment on the matter of when the measurement of line temperature is of use operationally?

Many utilities have altered line ratings based on “typical” weather data for several sites within their operating area. Would the authors please comment on the degree to which they think such typical data is of use in thermal rating calculations? Also would the authors please dircuss the extent to which the very different wind conditions at the two locations-Kifer and Mi-Wuk-are due to terrain and foliage, that is to sheltering of the span versus differences in meteorological conditions related to altitude and the nearness of the ocean?

Reference

Foss, S . D., Line, S. H., Maraio, R. A., and Schrayshuen, H., “Effect of Variability in Weather Conditions on Conductor Tem- perature and the Dynamic Rating of Transmission Lincs,” ZEEE Transactions on Power Deliisery, Vol. 3, No. 4, October 1988, pp. 1832-1841.

Manuscript received August 4, 1992.

T.O. Seppa, W.F. Whitlatch & E. Cromer: Regarding DL Mormn’s questions on wind speed and conductor temperature observations, we can state the following: the wind speed was sampled once cvery second. Average 10 minute wind speeds wcre calculated from the data, as well as thc fastest and slowest 1 and 5 minute wind speeds. The temperature sensors sampled the data every 2-3 seconds. Conduc- tor temperature was averaged every 10 minutes.

The authors do not imply that high temperature causes a high Tu. It is well documented that Tu increases with increasing lapse rate.

Statistically, the lapse rate is a function of ambient temperature and insolation. See, e.g. (1). Because of this, there is a strong correlation between daytime temperature and Tu.

Dr. Morgan’s observation that the probability curve tends to flatten out for temperature is not unreasonable, especially in the open terrain conditions corresponding to Dr. Morgan’s test span. On the other hand, the authors’ observations relate to statistics on absolute conductor temperatures. Because the observed wind speeds have a positive correlation with temperatures, the probability curves ofabso- lute temperatures will not flatten out.

Regarding the effect of the vcrtical wind speed, the authors rercr to the conmcnts to Dr. Foss andMr. Bush below. The authors would like to point out thc correlation between vertical wind specds and daytime turbulence. An cxaniple is shown in Figure 1 below.

Field measurements, including Dr. Morgan’s (4), have shown that 3

ftlscc 1

0 0 15 30 45 60 75

Standard deviation of wind direction, degrees Figure 1. Correlation between std deviation of horizontal wind directiori (suninicr daytiriie, 10 min. avg.) a d veriical w i d speed at Mi- Wuk

4 1

I

I I I I

2 4 6 ft/sec 8

Figure 2. Correlatiori (equiprobability lutes) forsuiiiiiierdaytintc (IOAM- SPM) horizontal (x-an$) and vertical (paxi+) windspeeds ai Mi- Wuk

forced cooling increases with increasing standard deviation of wind speedand direction, i.e. increasingturbulence. Basedonvertical wind speed measurements, such as shown in Figure 1, it appears that the real causal relationship is between vertical wind (i.e. the vertical component of Tu) and forced cooling. At Mi-Wuk, it appears that the median daytime vertical component of Tu is about 50% of the horizontal median value (Fig.2)

Mr. Bush raises thc question rcgarding thc combining ofhorizontal and vertical wind speeds. The answer is quite complex, because it depends on selected rating assumptions, as illustratcd by the cxample calculated for Mi-Wuk below.

Figure 3 compares actual summcr daytlme wind speed against horizontal wind speed only. Note that the vertical wind speed effec- tively increases thc wind speed at a given probability level by approximately 15%, i.e. by 0.5 to 0.8 Wsec. The effect on the wind anglc is much more complex and depends on


1560

at 45" and hazy sun, we arrive at an average conductor temperature of 50.5"C, substantially higher value than the observed 43°C average. If

ctorial sum of the measured median horizontal and

temperature of 47°C is still significantly higher than the observed

ossible explanation for this difference is that the median vertical

.2 ft/sec. An alternative explanation is that the heat sink error

I I I I I I

rs agree with h4r. Douglass' comment that the line temperature appears to be accurate in thermal rating calculations only when the temperatureriseishigh. AsshownbyFigure9 ofthereport, such acalculation is also subjecttothe variation ofthe temperature along the line.

Effective wind ft/sec Figure 3. Cornparison bdtvren suninier daytinic (IOAM-6PM) effective witid speed and korizonlal wind speed at Mi- Wuk

rating assumptions. For example, at Mi-Wuk, it reasonable to rate the conductor at 2G"C anibienl for an 80°C conductor tempcrature by assuming that the wind speed is 2 Wsec perpendicular, or 3 Wsec at 30 degrccs. But if the vertical wind is taken into account, these assumptions would be modified (based on equal probabilities) to either 2.5 ft/ scc perpendicular wind or to 3.5 Wsec wind at 45 degrees. The effect on thc ampacity is shown in Table I below:

Table I Without vertical wind With vertical wind

2.0 fUsec at 90" : 550 A 2.5 ftlsec at !IOo : 580 A 3.0 fUsec at 30° : 525 A 3.5 ftlsec at 45O : 580 A

As Far as generalization of the observations to other sites is concerned, the data which is used in this report covcrs only two locations of fifteen studied in PG&E's service territory. There are some observations which are common to all sites:

( 1) Median vertical wind speeds during maximum insolation arc on the order of 2 Wsec or more at all sites.

(2) Median daytime horizontal wind speeds and daytime turbu- lcnces (as evidenced in the standard deviation of wind direction) were highcr than nighttime values.

(3) At the sites equipped with two conductor temperature sensors, the deviation between relative temperature rises of the sensors was on the same order of magnitude as shown at the'two sites.

common to Mi-Wukand KiferRrimble is likely to be true for the other observation sites in Northern California.

Regardmg Dr. Foss' comments, some of the observations of the

Thus, for Mi-Wuk, the effect of the vertical wind for summer daytime ratings could be approximated by either of the following SimDlified calculations:

effect of the vertical wind speeds have been stated above. The effects

spccds, arc vcry substantial. They ccrtainly are muchmore substantial (2) Keep all prior assumptions but discard solar radiation. than what would be explained by a 0.8 Wsec natural convection. The difference between the dfectiveand the horizontal wind speed It should also bc noled that thc mcasured mcdian horizontal wind

Statistics at Mi-Wuk is substantial, because the horizontal wind speeds speed is no1 perpendicular, ne median angle is 450. Instead of the at Mi-Wuk are low. Lesser changes could be expected at other sites coinparison suggested by Dr. Foss (that the effect would be compa- where horizontal speeds are higher. rable to 4.5 @s vs. 4.9 f p s perpendicular), the correct comparison is 4.2

M & - has noted the relatively small variation of the day/ Wscc at 45' vs. 4.7 Wsec at 5 1". The difference in convective cooling night temperatures at the Mi-Wuk site. The major cause appears to be is significant. At thc median daytime ambient temperature of 26°C and the vertical wind speeds, as explained above. for a conductor temperature of 80"C, the differencc in convcctivc

p E E Thermal Rating Model, The average effective current for he more critical low wind horizontal wind speed conditions, the differ- time the line was "on" is 425 A. Using cmissivity and absorptivity of cncc 's even larger, as shown in Figure 3. 0.5, and the median nighttime wind speed of 2.1 Wsec with a median Dr. Foss also suggests that the "overstatement" could be duc to thc wind direction of 45 degrees, we calculated that the nighttime conduc- stalling speeds ofcup ancmometers. We arc well aware ofthis problem tor temperaturc should be 45.5"C, at an average ambient teniperaturc and avoidcd it by using high sensitivity p-r anemomctcrs. of 20°C. This is in close agrecment with the observed 46°C average. itaverage line temperature" any-

When wc calculate the median daytime conductor temperature where in the report. We have correlated wind and other weather using an ambient temperature of 26"C, a horizontal wind of 4.2 Wsec obscrvations with observed local conductor temperatures. We have

( I ) Increase wind 'peed by 0'5 Wsec and keep Other ofvefiica] wind speed on ratillgs Mi-Wd, with low daytime wind prior assumptions.

T~ show the difference, we calculated the temperature rise using the COOlhg iS 10%. Its CffCCt On the ampacity would be about 5%. For t h C

lilt have not


1561

also obscrvcd variation ofconductor tcmperaturc along thc conductor. Such cases are exceptions to the more general turbulence conditions, Wc did not sce any nicrit in pursuing thc unproven critical span theory as shown by Figure 5, cited abovc and in references such as (2 ) and ( 3 ) . in this text.

Dr. Foss' rcfercricc (3 ) USCS 5 nlinutc time averaging. The authors uscd thc sanic type of sensors, with 10 nlinute averaging. In spite of this, thc temperature rises mcasured at two locations 1000 ft. apart diffcred by more than 10% for long periods. Also, as shown by (2), icmperaturcs avcraged 1 mile apart can vary by 15°C and as shown by (3) , tenipcraturcs in a single span can vary by 1O"C, cven when avcragcd.

The time averaging will only bc equivalent to spatial averaging under special circunistanccs. For cxample, the following critcria must be met:

(1) The averagc wind conditions are uniform. This means that thc terrain is uniform.

(2) The turbulencc is circular. This means that thc along-thc-wind and across-the-wind fluctuations of the wind spccd arc equal.

References: [l] H. M o n h & M. Armendariz, "Gust Factor Variations with

Height and Atmospheric Stability". ECOM -5320, Fort Monmouth , N J , August 1970.

[ 2 ] J.W. Jerrell, W.Z. Black & T.J. Parker, "Critical Span Analysis of Overhead Conductors", IEEE 87 SM 560-6, 1987.

[ 3 ] W.Z. Black & R. A. Bush, "Conductor Temperature Research," EPRI Final Report for Project 2546-1, EL 5707, May 1988.

[4] V.T. Morgan, "The Real-Time Heat Balance for Overhead Con- ductors," Proc. of Seminars on Real-Time Ratings of Overhead Condiictors, Atlanta, GA, May 21, 1986.


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