20 IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 24, NO. 1, JANUARY 2009
RF-Based Partial Discharge Early WarningSystem for Air-Insulated Substations
Iliana E. Portugués, Member, IEEE, Philip J. Moore, Senior Member, IEEE, Ian A. Glover, Member, IEEE,Carl Johnstone, Ralph H. McKosky, Member, IEEE, Mark B. Goff, and Luke van der Zel, Member, IEEE
Abstract—Partial discharges (PDs) generate widebandradio-frequency interference which can be used for noninva-sive monitoring of discharges. This paper presents a novel methodbased on this principle for PD monitoring of substations. Thesignificant advantage of this method lies in the ability to detect PDsources in energized equipment anywhere within a substation com-pound during normal operating conditions. The results obtainedfrom the prototypes installed in the U.K. and U.S. substations arereported. Results include correlation with apparent charge anddaily recordings obtained before, during, and after the failure of a132-kV current transformer and 69-kV voltage transformer.
H IGH-VOLTAGE equipment insulation deteriorates withtime. Many mechanisms exist to explain this phenom-
enon, but in nearly all cases, the presence of partial discharge(PD) acts as an indicator of insulation integrity degeneration.Under normal operating conditions, PD activity is rarely con-stant; discharge sites have been inactive for periods of hours ordays. Small changes in operating or environmental conditions,however, can trigger PD episodes which may extend over sev-eral minutes. This form of discharge activity is notoriously dif-ficult to detect during site inspection and consequently contin-uous monitoring becomes the only viable solution. Although ex-pensive, continuous equipment monitoring forms the basis forcondition-based maintenance and the secure operation of un-manned substations. The importance of being able to selectivelyidentify and replace those items of equipment that have deteri-orated significantly is, therefore, of great importance from aneconomic and safety perspective.
The main motivation for continuous PD monitoring is to re-alize the condition assessment quality normally associated withroutine servicing but with reduced inspection and maintenance
Manuscript received April 15, 2008; revised July 15, 2008. Current versionpublished December 24, 2008. This work was supported in part by the U.K.Engineering and Physical Sciences Research Council under Grant GR/R17799and in part by EPRI. Paper no. TPWRD-00255-2008.
I. E. Portugues is with Elimpus Ltd., Bellshill ML4 3NQ, U.K. (e-mail: [email protected]).
P. J. Moore and I. A. Glover are with the Department of Electronic and Elec-trical Engineering, University of Strathclyde, Strathclyde, G1 1XW, U.K.
C. Johnstone is with National Grid, Warwick CV34 6DA, U.K.R. H. McKosky and M. Goff are with the Tennessee Valley Authority, Chat-
tanooga, TN 37402-2801 USA.L. van der Zel is with EPRI, Charlotte, NC 28262 USA.Color versions of one or more of the figures in this paper are available at
costs [1]. Due to high capital cost, the transformer is the most at-tractive of all substation equipment for continuous monitoring.Various instruments have been developed to act as early warningdevices based on dissolved gas analysis [2] and electrical mea-surements [3], [4]. However, retrofitting of such equipment canbe expensive and studies have presently shown that utilities maynot be willing to pay the extra cost for sensors in new trans-formers [5]. A study of other substation equipment reveals thatcontinuous monitoring equipment has also been developed forcircuit breakers (CBs) [6], bushings, and current transformers(CTs) [7].
In general, the majority of continuous monitoring schemesare designed for individual equipment items. For economic via-bility, the cost of PD monitoring must be significantly lower thanthe outage and capital replacement costs of failed equipment [8].Economic justification may be easily made for high capital sub-station equipment items, such as transformers and CBs. Thereare many items, however, which are not so readily justified, suchas insulators, capacitor banks, and surge arresters.
The most cost-effective approach to this problem is the de-velopment of a system capable of monitoring an entire sub-station. A significant obstacle to this goal—since the majorityof PD monitoring is based on electrical measurement—is therequirement for multiple connections to substation equipment.This disadvantage can be overcome by the use of a noncontact,remote-sensing technology, such as the detection of radio-fre-quency (RF), acoustic, or visible/UV/IR emissions from PD.A continuous monitoring system, based on RF sensing in therange 10–1000 MHz, that can cost-effectively monitor an entireair-insulated substation is described here. Compared to acousticor light emissions, RF sensing is chosen due to the favorablylong distances over which the effect may be measured. Resultsare presented for two trials of this system conducted over a pe-riod of 12 months in which the incipient signs of a catastrophicequipment failure were detected.
II. RF RADIATION AS A PD DIAGNOSTIC TOOL
While not the most commonly used method for diagnosis, RFmeasurement is a well-established method to detect insulationfaults. It is easily applied to energized equipment regardless ofwhether suitable electrical transducers are present. The first RFmonitor was used by Westinghouse more than 40 years ago todetect arcing subconductors in the stator windings of a large tur-bine generator [9]. In the last decade, several publications (e.g.,[10]–[12]) have demonstrated the success of RF technology asa means for remotely detecting PD-related insulation defects.Recent work based on new developments in ultra-high-speeddigital sampling technology [13] has shown that PD-related RF
PORTUGUÉS et al.: RF-BASED PARTIAL DISCHARGE EARLY WARNING SYSTEM 21
Fig. 1. System components.
emissions have impulsive waveforms. Since steep wavefronts inimpulsive signals can be easily and accurately identified in time,it is now possible to identify the 3-D position of PD sources onenergized equipment [14], [15] using an array of simultaneouslysampled antennas.
III. HV SOURCES OF RF RADIATION
The substation environment is particularly onerous for RF im-pulsive noise which can be generated from breakdown and PD.PDs are generated by a wide range of energized equipment con-taining stressed insulation. The risetime of PD impulses is suf-ficiently fast to extend into the RF spectrum causing electricallyattached supporting structures—busbars, bushings, etc.—to im-pulsively radiate. The resulting impulses are localized and, de-pending on impulse magnitude, can be readily measured withintypically 100–200 m. Impulses due to breakdown are caused bythe switching operations of disconnectors and CBs [16]–[20].Switchgear-generated impulses are generally very large in mag-nitude compared to PD impulses although the wave shape canvary greatly depending on the voltage level, and the type ofswitch being operated. Other sources of RF impulses arise fromhigh-voltage equipment, including power-electronic equipment,arc welding equipment [21]; electric railways [22], [23]; andthermostatically controlled heating equipment [24]. There areconsequently many sources of RF impulsive radiation in addi-tion to the PD originating from degraded insulation.
IV. SYSTEM OVERVIEW
The PD early warning system is being developed for substa-tion-wide applications and gives a degree of protection for allstressed insulation within 100–200 m of the installation. The pro-totype hardware of the system, a further development of earlierwork [15], is shown in Fig. 1 and consists of a four-antenna array,sampling oscilloscope, hard-disk storage, and uninterruptiblepower supply (UPS). The antennas are based on a disk-cone de-sign [10], [11], [15] that has a relatively flat frequency responseover the range 10–1000 MHz. RF impulses are sensed by theantenna array which is elevated within the substation—usually
Fig. 2. (a) Nonimpulsive waveform due to mobile-phone emission. (b) Impul-sive PD waveform recorded from the 132-kV capacitor bank.
on top of a building. The oscilloscope has an analog bandwidth of1 GHz, and samples each antenna simultaneously at 2.5 GSam-ples/s. The high sampling speed allows the impulse sourcelocation to be calculated due to the measured time delays acrossthe array. The system is consequently able to identify degradinginsulation from the impulse source and the pattern of impulseemissions.
The system is noninvasive and monitors substation emissionscontinuously. It is expected that a fully developed online ver-sion of this prototype equipment will be able to automaticallyreport (e.g., through the supervisory control and data acquisition(SCADA) or Internet) the occurrence and location of potentialinsulation defects.
The system records an impulse when the signal received onone of the antennas exceeds a preset trigger level, typically setat 10–25 mV. The oscilloscope records two separate items ofinformation.
1) Timestamp data—a record of when the trigger occurred asrecorded by the internal equipment clock (resolution 1 ps).
2) Waveform data—four blocks of time-series data relatingto the signals recorded on each of the four antennas. Eachblock consists of 5000 points of data sampled at 2.5 GSam-ples/s, which corresponds to a time window of 2 s.
A high capacity hard disk is used to store recorded data forfuture offline analysis; the system can be left unattended formonths. All of the equipment is connected to the mains supplyvia a uninterruptible power supply (UPS) to prevent interrup-tions during site LV switching.
A. Determining the Impulsive Nature of the Triggered Signal
Experience in the operation of the system has shown that twodifferent types of signals are recorded: nonimpulsive and im-pulsive. Typical examples of these are shown in Fig. 2. In gen-eral, setting lower trigger levels tends to increase the number ofrecorded nonimpulsive signals. The frequency analysis of thewaveform of Fig. 2(a) reveals a major frequency component in
22 IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 24, NO. 1, JANUARY 2009
Fig. 3. Effect of incorrect time delay estimation on the bearing and range errors�� sampling interval � 0.4 ns).
the region of 900 MHz which corresponds to the mobile-phonecarrier used by the substation site staff. Recordings of this typeare clearly not related to PDs and so can be discarded withoutfurther processing. The algorithm developed to distinguish be-tween impulsive and nonimpulsive records by detecting the in-crease in signal energy in the proximity of the wavefront is de-scribed in detail in Appendix B. In the following sections, onlythe processing of impulsive signals is considered.
V. 2-D SUBSTATION SOURCE LOCATION
Since the antenna array is mounted at roof level, and due tothe relatively large space occupied by air-insulated substations,the angle of arrival of a PD impulse is in the region of fromthe plane of the array. For this reason, the height of the impulsesource may be neglected and the substation may be defined as a2-D space.
Conventional 2-D time-difference-of arrival (TDOA) loca-tion techniques are based on solutions of quadratic equationsof the form
(1)
where is the speed of light, are the coordinates of thedischarge source, are the coordinates of antenna ,is the arrival time of the impulse at antenna , and is the timeat which the signal leaves the source.
In the above equation, it is more convenient to express thedischarge location as a range and bearing from the array.Equation (1) can therefore be rewritten as
(2)
For a 2-D case with four antennas, this allows for some redun-dancy since there are four equations with only three unknowns.This redundancy is important since there is always error associ-ated with the estimation of impulse arrival times. In general, thebearing can be calculated with relatively high accuracy, even ifthe arrival time estimates are in error. In contrast, the range ishighly sensitive to time error and demands highly accurate timeof arrival. An illustration of this effect is shown in Fig. 3 for a
TABLE IBEARING VALUES FOR ALL POSSIBLE ANTENNA-PAIR COMBINATIONS OF A
4-ANTENNA ARRAY (CORRECT BEARING SHOWN IN BOLD)
discharge source located 100 m from the array: an error of 1/2sample in the arrival time estimation yields only 0.3 inaccu-racy in the bearing, whereas the range can be more than 50 m inerror.
VI. LOCATION ALGORITHM
The impulse source location is found by first estimating thebearing and second by finding the range , using (2). In gen-eral, high accuracy of the arrival time of an impulse at the arraycan only be obtained by calculating the arrival difference, ortime delay, apparent between two antennas. Thus, (2) is used inmodified form allowing the use of antenna-pair time delays, forexample, for antennas 1 and 2
(3)
where . The time-delay estimation (TDE) tech-nique used to find uses the cross-correlation of interpolatedsections of the two impulse wavefronts; interpolation being usedto improve the time-delay accuracy. Further details of the TDEalgorithm can be found in [25]. The accuracy of the TDE is re-lated to the ratio of the impulse wavefront to the backgroundnoise signals.
A. Bearing Calculation
To find the bearing, it is necessary to calculate the time delaybetween all pairs of antennas in the array. From the time delay,the angle of arrival of the impulse with respect to the antennapair can be found. Appendix A details the mathematical for-mulation employed. Note that an antenna pair cannot find theunique angle of arrival; there are always two results. The bearingis found by adding the angle of arrival to the orientation angleof the antenna pair within the array. For example, in the array ofFig. 9, the orientation angle of antenna pair 1-4 is 0 , whereasfor 1-2, it is 90 . For a four-antenna array, 12 bearings are there-fore calculated. A sample set of bearings is shown in Table Iwhere the true bearing is 210 . The correct bearings, shown inbold in Table I, are identified through a simple algorithm. Thereported result is the mean of the six correct bearings.
B. Range
The range is calculated following the calculation of thebearing. As shown in Fig. 3, small errors in the TDE cause
PORTUGUÉS et al.: RF-BASED PARTIAL DISCHARGE EARLY WARNING SYSTEM 23
Fig. 4. TDE uncertainty versus signal strength.
significant errors in the source-range estimation. Since TDE er-rors are inevitable, the range is estimated as a spread of values.Inherent in this process is an estimation of the signal strengthof the impulse: the TDE for large impulses can be found withlittle error and so the spread of range values will be small. Bycomparison, the TDE for smaller impulses will be subject togreater errors and so, a larger spread of ranges can be expected.
The signal-strength metric is calculated from the ratio of theabsolute amplitude of the first peak of the impulse to the max-imum absolute signal amplitude in the preimpulse section ofthe record. For example, for the impulse of Fig. 2(b), the signalstrength is calculated as 24, whereas the impulse of Fig. 20 hasa value of 10. A relationship between signal strength and TDEuncertainty has been found experimentally. This is shown inFig. 4. Thus, for a given impulse, the analysis of the signalstrength allows a range of uncertainty of the TDE to be found(i.e., ).
Once the uncertainty of all TDEs for the array has been estab-lished, the corresponding spread of range values is calculated.Once this is achieved for a given , by finding the values offor which the following inequality is true:
(4)
and similarly, and simultaneously, for all other antenna pairs.Two applications of this technique are shown in Figs. 5 and 6.These results are calculated from data recorded during site trialA described in Section VII. In Fig. 5, a small amplitude impulseis shown to yield a large spread of range values. In Fig. 6, a largeimpulse is seen to yield virtually no spread at all, with the uniqueposition of the impulsive source being found.
VII. CORRELATION WITH APPARENT CHARGE
The correlation between impulse characteristics measured byRF-based PD monitoring systems and the apparent charge froma conventional electrical measurement system is currently thesubject of wider research interest [26] since there is presentlyno general relationship between these two physical quantities.
Fig. 5. Bearing and range obtained for a small amplitude signal������ �������� � 150 m).
Fig. 6. Results of locating sources of three impulses originating from a capac-itor bank CB operation. The distances relate to a coordinate system centred onthe antenna array shown in Fig. 9.
Fig. 7. Experimental setup.
However, tests performed within a screened high-voltage lab-oratory using the PD monitoring equipment described in Sec-tion IV can give an idea of the typical sensitivity of PD thatcan be measured in a substation. Fig. 7 shows the experimentalsetup. A point-to-plane discharge source (11-mm gap) was im-mersed in oil (type L10B). The apparent charge was measuredusing a Lemke LDS-6 system calibrated according to IEC60270by injecting current pulses of a known charge across the termi-nals of the test object. The cell was energized using a PD-freevariable HV supply operating at 50-Hz ac.
24 IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 24, NO. 1, JANUARY 2009
Fig. 8. Impulse magnitude versus apparent charge.
Fig. 8 shows the relationship between the absolute peak im-pulse voltage magnitude measured by the PD monitoring systemcompared to the IEC apparent charge measured. It is impor-tant to note that this relationship is only valid for the aforemen-tioned experimental configuration. It is, therefore, not possibleto extrapolate these results to generally relate the PD moni-toring system waveforms to apparent charge values, althoughFig. 8 demonstrates that relatively sensitive measurements arepossible.
VIII. CASE STUDIES
Two case studies are described which demonstrate the abilityof the system to detect equipment failure.
A. Case Study: National Grid 400-kV Substation
This case study describes the first ever trial of the earlywarning system and documents recordings leading up to thefailure of a 132-kV CT. The results of this trial, conductedbetween January and December 2003, were the first tangibleevidence that the system could detect impending equipmentfailure. In addition, the trial demonstrated, following the failure,that the system could cope with the impulsive noise environ-ment of a large transmission substation. The failure occurredduring a period when the system was autonomously recording;the results presented here were analyzed offline following thefailure and, hence, no warning was possible.
1) Installation: The system hardware was installed at a 400/275/132-kV substation in Southern England. The antenna arraywas installed at a height of 6.5 m on the roof of the controlroom building located almost centrally within the substation.The oscilloscope, UPS, and hard disk were located inside thecontrol room.
To minimize signal distortion, the antennas were remotely po-sitioned from any metalwork on the roof and incorporated di-electric plinths and weathershields. Connections to the oscillo-scope were provided with matched, low-loss coaxial wiring. Theantennas were located at the corners of the building and formeda rectangular shape of approximate dimensions 7.5 m 14.7 mas shown in Fig. 9.
The system recorded all results to hard disk which was col-lected at the end of every month. The results were analyzed of-
Fig. 9. Positioning of the antennas on the roof of the control room.
Fig. 10. Percentage distribution of impulsive triggers throughout the month ofFebruary 2003.
fline. Initially, care was taken to prevent the equipment fromrecording large quantities of data which can complicate the of-fline analysis. Thus, when the equipment began recording onJanuary 3, 2003, the trigger sensitivity was set to the relativelyhigh level of 25 mV. By comparison, the background noise level(i.e., the level of signals not originating from within the substa-tion) rarely exceeded 4 mV.
2) Typical Results: Typical results from the system wereobtained during the months of February to December 2003during a period following the CT failure when the substationwas free from PD. Ignoring nonimpulsive signals, which arediscarded using the methodology described in Appendix B, thesystem recorded between 300 to 500 impulsive signals everymonth—an exact breakdown is given in Table II. The majorityof these impulses relate to the normal, but variable, operationof reactive switchgear within the substation, in particular, threeCB-controlled 132-kV capacitor banks, and a CB and discon-nector associated with a 400-kV reactor. These operations canbe easily identified by reference to the substation log.
In terms of diagnosing failing equipment, it is, therefore, im-pulsive signals that are recorded by the system that do not cor-relate with the substation log that are of interest—these will bereferred to as unaccounted impulses. Fig. 10 shows a breakdownof impulses recorded for the month of February 2003 for which3% (ten in total) of the records are unaccounted impulses. Ex-perience with the operation of the system in the months fol-lowing the CT failure have shown that unaccounted impulsesare frequently recorded due to switching operations in nearbydistribution substations, overhead line faults, unspecified con-tactor operations, etc. An investigation of unaccounted impulsesrecorded for the months of February to December 2003 showed
PORTUGUÉS et al.: RF-BASED PARTIAL DISCHARGE EARLY WARNING SYSTEM 25
Fig. 11. Number of recorded “significant” unaccounted impulses in relation toall unaccounted impulses.
that they are usually isolated (i.e. they do not occur in sequentialtrains). It is therefore possible to distinguish between “non-sig-nificant” and “significant” unaccounted impulses based on theirtime history: significant impulses are repetitive trains of im-pulses consisting of four or more impulses where consecutiveimpulses are separated by less than 1 s. This approach allowsmost three-phase switching events to be classified as “nonsignif-icant.” Applying this procedure to the unaccounted impulsesrecorded between February and December 2003 yields everyimpulse to be classified as “nonsignificant.”
3) Fault Diagnosis: The trial of the prototype equipment wasscheduled for 2003; the equipment was installed during De-cember 2002 and began recording on January 3, 2003. Fortu-itously for the project, though not the utility, a 132-kV CT failedduring the evening of January 26, 2003. It is speculated that theRF evidence of defective insulation within the CT was presentbefore the system began recording. The CT experienced insula-tion failure leading to an internal flashover that caused damageto the metal base tank. This defect was detected by the systemwhich, up to the point of failure, recorded 420 unaccounted im-pulses, 390 of which were classified as “significant.” A dailybreakdown of the unaccounted impulses is shown in Fig. 11. Atypical impulse recorded on January 25 is shown in Fig. 20.
4) Source Location: The location algorithm can be used tocheck the position of unaccounted impulses. A typical resultof this calculation for records corresponding to the CT failure(waveform of Fig. 20) is shown in Fig. 12, superimposed on aprojection-corrected aerial photograph of the substation. Thelocation result is shown as a line representing the spread of rangepositions along the bearing. The bay containing the failed CT iscircled in Fig. 12. The midpoint of the location result coincideswith the position of the failed CT. The uncertainty in this positionis approximately 10 m. For this failure, the system was thereforecapable of identifying the bay containing the faulty component,but not the individual phase on which the CT was connected.
5) Discussion: This case study demonstrated the capabilitiesof the RF system to detect and locate PDs originating from a132-kV CT several weeks before catastrophic failure. Due tothe early failure soon after the installation of the system, it isnot possible to determine the extent of the early warning thatthe system is capable of providing.
B. Case Study: TVA 69-kV Substation
The Tennessee Valley Authority (TVA) installed an earlywarning system in a 69-kV substation adjacent to a coal-fired
Fig. 12. Position of the failed CT with respect to the antenna array.
Fig. 13. TVA early warning system installation.
power station. This site was chosen due to insulator pollutionproblems related to the particulates from the power station’scombustion stacks. This trial began in December 2005 and iscontinuing to date (July 2008).
1) Installation: The system was installed in a relocatabletrailer (Fig. 13), which was positioned within the 69-kV substa-tion. The antennas were fixed to the corners of the trailer whichgave an array size of 2 m by 4 m. The recording equipment waslocated within the trailer which was air-conditioned. Unlike theNational Grid trial, where the hard disks were physically re-moved from the substation for analysis, the TVA installation in-cludes a 1-Mb/s Internet connection which allows recorded datato be electronically downloaded to the University of Strathclydefor weekly analysis.
2) Fault Diagnosis: The results presented here relate only to“nonsignificant” impulses, the raw data having been processedusing the preceding methods. In common with the National Gridtrial, the defects detected by the system were present at commis-sioning. Two separate areas of discharge activity have been de-tected by the system (Fig. 14). Fig. 14 shows two separate areaswhich enclose the range of locations calculated by the systemsuperimposed onto the substation plan drawing. One of thesesources, source 2, which coincides with one of the VTs in theforeground of Fig. 13, showed a more or less continuous emis-sion of impulses, resulting in the system recording in excess of2000 impulses per day. Fig. 15 shows the number of dischargesrecorded daily by the system for source 2 between April andJune 2007.
26 IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 24, NO. 1, JANUARY 2009
Fig. 14. Positioning of the two areas of discharge detected by the system.
Fig. 15. Graphs of the number of discharges obtained from source 2.
Fig. 16. Moisture in windings.
Fig. 17. PD source.
A follow-up power factor retest on the voltage transformer(VT) showed a sharp increase and it was replaced during anoutage. After the outage, when the 69-kV bus was returned toservice, source 2 disappeared. The transformer was then dis-mantled to find the cause of the PD. Moisture was found underthe cotton linen tape on the outside of the windings (Fig. 16).After removing the cotton linen tape and removing the firstwinding (wide copper strip), the PD site was found at the high-voltage top terminal connection to the first winding (Fig. 17).Notice the burn marks on the cotton linen tape.
3) Discussion: This case study demonstrated the capabilityof the system to detect discharges and provide early warningindications over a period of several months for 69-kV equipmentlocated at a distance of approximately 30 m.
IX. CONCLUSION
An experimental RF-based monitoring system for detectingsubstation-wide partial discharge sources has been developed.Through the use of ultra-high-speed sampling, the system is ca-pable of locating the position of impulsive radiation within thesubstation. The relationship between impulse magnitude andapparent charge has been discussed. The system additionallyrecords several types of RF signal, both impulsive and nonim-pulsive, which do not relate to PD effects. These signals can bediscounted for further processing through the use of signal anal-ysis, and by reference to known switching operations recordedin the substation log.
During a 12-month trial, in a major transmission substa-tion—case study A—the system recorded significant evidenceof PD radiating from a 132-kV CT which eventually failed.This evidence was present at least three weeks prior to failure.The system did not recorded any other evidence of significantPD activity within the substation during the trial, demonstratinga robust prediction metric in, what is otherwise, an extremelyharsh electromagnetic environment.
The most significant issue arising from this trial relates to thedegree of advance warning that the system can provide. Withrespect to the failed CT, could more than three weeks be pro-vided? It is difficult to answer this point definitively withoutfurther experimental trials. The system began recording evi-dence of the demise of the CT from startup; it is thereforepossible that this pattern of PD emission had been establishedfor considerably longer than three weeks before the failure. Ex-perimentation with the system trigger levels, which was con-ducted following the CT failure, showed little variation in thenumber of recorded impulses. These impulses originated pre-dominantly, however, from reactive switchgear which tends toproduce large, but constant magnitude impulses. PD impulsesare more likely to be of variable magnitude and so loweringthe trigger threshold results in more triggers. Assuming the PDemissions of the type related to the failed CT build up gradu-ally with time, it is likely that a lower trigger threshold wouldprovide greater advance warning.
The second case study (B) has demonstrated the capability ofthe system to act as an early warning system for several monthsin the presence of a failing VT, demonstrating that the systemhas high potential for practical implementation in substationsfor monitoring purposes.
Further development of this prototype is anticipated to re-alize a fully developed, online system. In particular, a signif-icant effort will be directed to removing the dependency onsubstation switching records. The current algorithm for classi-fying “significant” impulses will need further development toenable automatic recognition of disconnector operations. Withthese developments, the system will be noncontact and standalone, capable of providing cost-effective substation-wide PDmonitoring.
PORTUGUÉS et al.: RF-BASED PARTIAL DISCHARGE EARLY WARNING SYSTEM 27
Fig. 18. Schematic for derivation of bearing.
APPENDIX AANGLE-OF-ARRIVAL CALCULATION
In Fig. 18, an impulsive signal from a source at S is receivedby a pair of antennas A and B. Let the time delay of the impulsearriving at each antennas A and B be measured as . Thus, thepath difference of the impulse is given by
(A1)
where is the speed of light .The angle of arrival of the impulse relative to the antenna
array can be found from
(A2)
and so
(A3)
Note that it is not possible to distinguish between sourcespresent at positions S and T in Fig. 18.
APPENDIX BDETECTING NONIMPULSIVE SIGNALS
Impulsive signals include fast rising edges as shown, for ex-ample, in Fig. 2(b). The detection of this edge can be used todistinguish between impulsive and nonimpulsive signals. Usinga sliding window of ten samples across the waveform, the signalenergy can be found using the expression
(A4)
where is the window number and is a signal variable con-taining 5000 samples.
The central difference gradient is then evaluated for . If theincrease in signal energy from one window to the next exceeds500%, the dataset is deemed to contain an impulsive waveform.Typical results obtained using this procedure for impulsive andnonimpulsive signals are shown in Fig. 19.
Fig. 19. Rate of change of amplitude against the window number for (a) non-impulsive waveform in Fig. 2 and (b) impulsive waveform in Fig. 2(a).
Fig. 20. Impulsive waveform recorded at 07:10 on January 25, 2003. The wave-form was classified by the system as “significant, nonaccounted.” Application ofthe location algorithm placed the origin of this waveform at the position shownin Fig. 12.
TABLE IINUMBER OF IMPULSES RECORDED THROUGHOUT A YEAR
A typical waveform from a failed CT is shown in Fig. 20, anda breakdown of impulses recorded in case study A is shown inTable II.
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Iliana E. Portugués (M’03) was born in Madrid,Spain, in 1979. She received the M.Eng. degree inelectronic and communication engineering and thePh.D. degree in radiometric equipment diagnosticsfrom the University of Bath, Bath, U.K., in 2001 and2004, respectively.
From 2001 to 2005, she was a Research Officerwith the University of Bath. From 2005 to 2007, shewas a Research Fellow in the Institute for Energy andEnvironment with the University of Strathclyde, in-vestigating characteristic RF emissions from defec-
tive substation insulation. She is a Founder and Director of Elimpus Ltd., Bell-shill, U.K.
Philip J. Moore (SM’96) was born in Liverpool,U.K., in 1960. He received the B.Eng. degree in elec-trical engineering from Imperial College, London,U.K., in 1984 and the Ph.D. degree in power systemprotection from City University, London, in 1989.
From 1984 to 1987, he was a DevelopmentEngineer with GEC Measurements. He began hisacademic career at City University in 1987, and waswith the University of Bath, Bath, U.K., from 1991to 2005. Currently, he is a Professor of ElectricalPlant and Diagnostics in the Institute for Energy
and Environment, University of Strathclyde, Strathclyde, U.K. His researchinterests include radio-frequency emissions from power system equipment,harmonics, numeric protection, high-voltage discharges, power system simu-lation, and fault location.
Prof Moore is a Chartered Engineer in the U.K. He is a Founder and Directorof Elimpus Ltd., Bellshill, U.K.
Ian A. Glover (M’98) received the B.Eng. degree inelectrical and electronic engineering and the Ph.D.degree in microwave cross-polarization from theUniversity of Bradford, Bradford, U.K., in 1981 and1987, respectively.
From 1975 to 1981, he was a Power Engineer withthe Yorkshire Electricity Board, Scarcroft, U.K. Hewas a Reader in Radio Science and Wireless Com-munications at the University of Strathclyde, wherehe held academic posts at the University of Bradfordand the University of Bath, Bath, U.K. His principal
research interests are in the areas of radio science and radio systems, includingchannel modeling, channel measurements, and the impulsive noise environment.
Carl Johnstone joined the Central Electricity Gener-ating Board (CEGB) in 1987, delivering the mainte-nance program for the Transmission System and theHVDC link between the U.K. and France until 1997,while studying Higher National Certificate (HNC) atCanterbury College, Kent, U.K.
In 1997, he moved to research and develop-ment for all equipment types across National Gridbecoming the Deputy Head of the High VoltageLaboratory at Leatherhead within the Engineeringand Technology Department. Since 2002, he has
worked within Asset Management for National Grid, delivering primary andsecondary technical support on main equipment issues. The technical areascovered are GIS, SF6, switchgear, partial-discharge detection, and failuresmodes.
Currently, he is the Technical Lead for the Condition Monitoring Strategy atNational Grid, Warwick, U.K.
PORTUGUÉS et al.: RF-BASED PARTIAL DISCHARGE EARLY WARNING SYSTEM 29
Ralph H. McKosky (M’00) received the B.S.E.E.degree from Mississippi State University, MississippiState, in 1987.
He joined the Tennessee Valley Authority, Chat-tanooga, after having worked in the Nuclear PowerDepartment. Currently, he is a Project Engineer in theResearch and Technology Applications Department,Transmission Technologies Group. As Project Engi-neer, he is responsible for the research, development,and demonstration of new technologies that improveTVA’s transmission system.
Mark B. Goff received the B.S.E.E. degree from theUniversity of Kentucky, Lexington, in 1983.
He is a Staff System Engineer in the Transmis-sion Operations and Maintenance Department, Sub-station/Power Equipment Group, for the TennesseeValley Authority (TVA) and went to work for TVA asa Field Test Engineer. He joined TVA’s TransmissionStaff in 1990 as a Lead Engineer for large power sub-station equipment. Since being on the staff, he has de-veloped TVA’s predictive maintenance program forTVA’s substation and is currently working on the de-
velopment of an online transformer monitoring program for TVA’s 500-kV grid.He is a registered professional engineer in Kentucky.
Luke van der Zel (M’96) received the Ph.D. degreein electrical engineering with a focus on high-voltageresearch from the University of the Witwatersrand,Johannesburg, South Africa.
His doctorate research was on the prebreakdownbehavior of SF . He was a Research Engineer for theelectric utility ESKOM for 11 years. His research wason utility-related SF issues and gas-insulated-sub-station (GIS) diagnostics. Currently, he is a ProjectManager with the Electric Power Research Institute(EPRI), where he has been for six years. His chief
responsibilities are in the areas of transformers and SF and GIS research. Hehas been published in the Proceedings of the Institute of Electrical Engineers ofScience, Measurement, and Technology.
Dr. van der Zel was the South African member of the CIGRE Working Groupon insulating gases.
