1

Index Terms—Instrument transformer, meter, model, optical,performance, power quality, protection, relay.

I. INTRODUCTION

Conventional instrument transformers deliver to theprotection and control system with replicas of current andvoltage signals present in a power network. The high voltageand current of the primary circuit supply the primary side ofthe instrument transformers. The secondary side suppliessignals to the protection relays, power quality meters, revenuemeters and other IED. Instrument transformers (IT) areexpected to accurately reproduce power system current andvoltage signals. Lab research and field experience show thatconventional instrument transformer characteristics may affectthe performance (causing misoperations in some cases) of

This work was supported by the Power Systems Engineering ResearchCenter (PSERC)

M. Kezunovic and L. Portillo are with the Department of ElectricalEngineering, Texas A&M University, College Station, TX 77843 USA (e-mail: kezunov@ee.tamu.edu; leviportillo@tamu.edu).

G. Karady and S. Kucuksari are with the Department of ElectricalEngineering, Arizona State University, Tempe, AZ 85287 USA.

relays, revenue metering systems, power quality meters andother IED. These characteristics originate from IT design andthey can be classified as follows:

• Transient response ([1] and [2])• Frequency response ([3])• Accuracy ([4] and [5])

Recently, optical voltage and current transducers (alsocalled non-conventional instrument transformers or NCIT)have been deployed, which produce digital signalsrepresenting the primary current and voltage. These signals aretransported to the control room through fiber optic cables. Inthe control room the digital signal may supply a number ofIED such as digital relay, a digital revenue metering system ora power quality meter. In the theory, NCIT supply theprotection and control system with distortion-free replicas ofthe primary signals. The new digital measurement system,using NCIT, promises the following advantages: improvedsafety, smaller size, immunity from electro magneticinterferences, better transient response, wider frequency band,larger dynamic range and higher accuracy than the traditionalanalog system.

Performance indices for protection functions have alreadybeen defined in [6], [7], [8] and [9]. A methodology forassessing the influence of instrument transformercharacteristics on the performance of power system protectiondevices has been presented in [10], this has been done byadapting some of the indices for protection functions to serveas indicators of the influence of instrument transformercharacteristics on the power system protection performance. Itis also shown in [10] (from simulation results) how currenttransformer saturation affects the performance of protectiverelays.

In the first part of the paper, a model of an optical currenttransformer has been presented and validated throughsimulation. This paper uses some of the aspects presented in[10] to evaluate and quantify the influence of optical currenttransducers characteristics on protective relay performance,and defines criteria and procedure for evaluating the influenceof OIT characteristics on power quality meter performance.

Impact of Optical Instrument TransformerCharacteristics on the Performance of Protective

Relays and Power Quality Meters

Mladen Kezunovic, Fellow, IEEE, Levi Portillo, George Karady, Fellow, IEEE,Sadik Kucuksari, Student Member, IEEE

1-4244-0288-3/06/$20.00 ©2006 IEEE

2006 IEEE PES Transmission and Distribution Conference and Exposition Latin America, Venezuela

and

2

II. OPTICAL CURRENT TRANSFORMER

A. Model Development

We tested a commercial Optical Current Transformer. Theinput of this unit is the primary current; and there are threepossible outputs: a low-energy analog, high-energy analog ordigital voltage signal. Only the low-energy analog output hasbeen tested.The OCT can be set up for protection mode, when theaccuracy is less than 5 % or metering mode when the accuracyis 0.15 %. To model the OCT for protection applications, theprotection mode has been used for testing.

Measurement of the OCT Frequency CharacteristicsOne of the advantages of the OCT is that it has a better

frequency response than the traditional CT. According to themanufacturer, the OCT analog output has a built in 40-microsecond delay and a low pass filter with a cutofffrequency at 6 kHz (selectable). The OCT output above 20kHz is almost zero. In order to verify the manufacturerspecifications, the frequency response of the OCT has beenmeasured. These measurement data are used for thedevelopment of the OCT model.

The OCT was supplied by a current that has a variablefrequency. The input current and the output voltage weremeasured and compared. Figure 1 shows the experimental setup.

Fig. 1. Frequency response experimental test setup

A signal generator, with 0 Hz to 1MHz frequency range,has been used as a signal source. The variable frequencyoutput voltage of the signal generator was amplified by a1000W stereo amplifier. The loop current was kept constantwhile the frequency was varied in steps of twelve. Thewaveforms of both signals were recorded simultaneously withthe rms value at each frequency. The phase differencecorresponding to the time difference between the zerocrossings of the signals were determined and converted todegrees. Digital oscilloscope noise filter has been used duringthis measurement to reduce the inherent output noise of theOCT signal. Table 1 shows the results of the measurementsand calculated phase differences.

Using the data in Table 1, the normalized amplitude-frequency and phase angle/frequency characteristics of theoptical CT have been plotted in Figure 2 and Figure 3respectively.

The observation of the amplitude-frequency characteristicssuggests that using a low-pass filter we can represent the OCTfrequency response.

The observation of the phase angle frequency characteristicssuggests that the OCT frequency response can be presented bya sixth order low-pass filter.

Fig. 2. Amplitude - frequency characteristics of OCT

Fig. 3. Phase angle - frequency characteristics of OCT

Electrical Circuit Model For OCTThe OCT input is the primary current and the output is a

voltage signal. The ratio is 1000A, which corresponds to 1V.This can be modeled by an ideal transformer and a terminatingresistance. The 1000A/1V transfer function can be realizedusing an ideal transformer with a turn ratio of 1000:1 and aterminating resistance of 1 ohm. The ideal transformer reducesthe 1000 A to 1A. The voltage across the resistor is 1 ohm x 1

Signal Generator

0.1 OhmCoaxialcable

Fiber opticcable

Electroniccircuit

Shunt resistor

Optical CT

Oscilloscope

25 Turns

Power Amplifier

Resistor

TABLE ITEST RESULTS

OCT CurrentResistorVoltage

LoopCurrent

Normalized Phase Diff Phase

(mV) (A) (mV) (A) Amplitude (μs) (deg)

60 92.1 3.684 438 4.38 1 40 OCT -0.86300 91.37 3.6548 437 4.37 0.992074 72 OCT -7.781000 89.64 3.5856 437 4.37 0.971343 70 OCT -25.22000 85.13 3.4052 437 4.37 0.924321 72.8 OCT -52.424000 70.47 2.8188 437 4.37 0.763616 72.6 OCT -104.546000 55.53 2.2212 437 4.37 0.601726 69.2 OCT -149.477670 43.44 1.7376 437 4.37 0.466982 65.6 Current -181.138200 40.17 1.6068 435 4.35 0.435284 55.2 Current -197.05

10000 30.92 1.2368 438 4.38 0.335722 38 Current -223.212000 22.48 0.8992 438 4.38 0.242624 23.2 Current -259.7814000 16.68 0.6672 437 4.37 0.181836 11.6 Current -301.5416800 11.51 0.4604 436 4.36 0.137844 1 NO diff -353.95

Freq(Hz) Lagging

3

A = 1 V. This voltage will supply a sixth order low pass filter.The 1-ohm resistor is selected to produce a low impedancesource for the filter. The filter input impedance will be in thekilo-ohm range. Figure 4 shows the filter circuit and thesupplying ideal transformer:

Fig. 4. Electrical Circuit Model for OCT

B. Model Validation

The performance of the model was analyzed usingstraightforward mathematical method and the results wereverified by PSPICE and ATP simulation programs. Figure 5presents the amplitude-frequency characteristics of the model.The performance of the model is compared with the measuredvalues. The results indicate that the error is less than 5%.Figure 6 presents the phase angle-frequency characteristics ofthe model.

Fig. 5. Comparisons of circuit model amplitude frequency characteristics withthe measured values

Fig. 6. Comparisons of circuit model phase-angle frequency characteristicswith the measured values.

The performance of the model is compared with the

measured values. The figure shows that the system movesfrom inductive to capacitive at 0, 180 and 360 degrees. Duringthe transition, the error is infinite because of division by zeroor a number close to zero. Disregarding the transition intervalsthe error is less than 10%. The results proved that thedeveloped model represents the optical current transformerwith sufficient accuracy.

III. EVALUATION CRITERIA AND METHODOLOGY

A. Criteria and methodology based on relay performance

Functional components of a protective relay are shown inFig. 7. Overall performance of the relay will be based on theperformance of its main components.

Fig. 7. Functional components of a protective relay.

Reference [10] defines a methodology for evaluation of theinfluence of instrument transformer characteristics on systemprotection performance. In reference [10], performanceindices of the relay’s measuring algorithm and decision-making algorithm are presented:

For the measuring algorithm, the following indicesare used:

• Settling time, t2%, is a time after which the measuredvalue remains within 2% difference with respect tothe actual steady-state value of the estimatedquantity.

• Time to the first extreme, t1ext, is the time in whichthe measured value reaches its extreme (maximum orminimum) for the first time after the start ofmeasurement

• Overshoot/undershoot, �y%, defined as:

∞

∞−=Δ

y

yyy ext

% ,

where ∞y is the steady state value of the estimated

quantity.• Normalized absolute error index, eabs.

For the decision-making algorithm, the following index isused:

• Selectivity, s, defined as:

N

NNs 01 +

=

where N1 is the number of correct assertions of the tripcommand, N0 is the number of correct trip commandrestraints and N is the total number of test cases. Ideally

01 NNN +=

Evaluation based on simulationOur goal is to evaluate the influence of instrument

transformer models on IED (protective relay or power meter)performance by simulating different power system events and

MeasuringAlgorithm

DecisionMaking

Algorithm

Voltage

Current

TripAlarmControlData

R2L2

C3

R3L3

C2 C1

R1L1

Ip

R4 VOCT_out

4

conditions (scenarios). Simulation environment automaticallyperforms the following sequence:

1. Creation of an exposures database. Events aresimulated according to selected scenarios.Simulations incorporate power network andinstrument transformer models. Output signals fromsimulations are taken from the secondary connectionsof instrument transformers.

2. Replaying current and voltage signals (exposures) atthe input of IED models. Replaying creates the sameconditions on the input of IED model, as if the modelwas connected directly to instrument transformersecondary output during a particular event.

3. Creation of a database of IED model responses. Onceexposures are replayed, IED produces certain outputsignal(s).

Three IED models were investigated: IED model Arepresents an overcurrent protection relay, IED model Brepresents a distance relay; model data can be found inreference [11]. The electromagnetic current transformermodel has been taken from reference [12]. The optical currenttransformer model has been presented in section II. In bothcases, transformer models were investigated using 2 differentburdens (low and high) resulting in 4 models beingconsidered. The power network was modeled according to themodel given in reference [13] (9-bus, 11 line, 345 kV Sky-STP section). Simulation scenarios for both protective relaymodels are summarized in Tables II and III.

B. Criteria based on power quality meter performance

Power quality meter model is denoted as IED model C.Features of the model are:

• Detection of Disturbances• Classification of disturbances as power quality events

Fig. 8. Functional components of a power quality meter.

Functional elements and flowchart of the model are shown inFigure 8. Elements and their functions are:

• Feature extraction element captures distinct,dominant patterns in the metered signals. Thecapturing of patterns is done using Fourier and

wavelet transforms. Patterns characterize typicalpower quality events.

• Detection and classification element decides on theevent type, based on its features. There are five eventtypes that will be recognized:

1. Sag2. Swell3. Flicker4. Swell5. Sag

Events are created differently depending on the type ofdisturbance to be simulated. Table IV – VII summarizescenario definitions for all simulated disturbances:

The main function of a power quality meter is to detect,classify and characterize power quality disturbances, i.e. todefine and obtain distinctive and pertinent parameters todescribe specific types of disturbance waveforms. Hence,Performance indices of a power quality meter should providean estimate of its ability to properly detect and characterizedifferent kinds of power quality events. Based on the ability ofthe power quality meter to correctly detect a disturbance thefollowing index can be defined:

• The performance index of power quality meter P

when fed by exposure E is denoted by EPPQPI . The

average performance index of power quality meter Pis defined as:

�∈

=EDBE

EPP PQPI

NPQPI

1

TABLE IISIMULATION SCENARIO FOR IED MODEL A

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TABLE IIISIMULATION SCENARIO FOR IED MODEL B

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TABLE IVSIMULATION SCENARIO – SAG/SWELL

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TABLE VSIMULATION SCENARIO – SAG/SWELL

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TABLE VISIMULATION SCENARIO – TRANSIENTS

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TABLE VIISIMULATION SCENARIO – HARMONICS

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FeatureExtraction

Detection,Classification

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Current signalsAlarm

5

There are two types of calculations for the power qualityperformance index; these are the detection method and thecharacterization method. For the detection method:

rtEP DDPQPI −=

Where:

���

=otherwise

edisturbancectsproperlymeterPQifDD rt

0

det1,

For the characterization method:

rtEP DDPQPI −=

Where Dt and Dr stand for the estimated value of thecharacterization feature (i.e. phase angle shift, duration,magnitude, modulation RMS, etc) of the tested and thereferent power quality monitoring system. In our case, thetested power quality monitoring system will be fed by signalscoming from models of optical CT and an ideal voltagetransducer (no frequency bandwidth limitations), and thereferent power quality monitoring system will be fed bysignals coming from conventional CT and VT models. Amodel of the optical VT was not available for our evaluation;consequently, we have used an ideal voltage transducer tosimulate the wide frequency bandwidth and high dynamicrange, which is expected from the optical VT.

IV. RESULTS

A. Results of Relay Performance

The results of the application of methodology on relayperformance evaluation are given in Tables VIII through X.Measuring algorithm is the same for both relays (Fourierbased algorithm) In all cases, results are presented for the AGfault type. Performance indices for the measuring algorithmare presented in Table VIII. Settling time t2%, DC gain FRDC

and aggregated index F are similar for all the CT models,however, the overshoot was considerably smaller for CTmodel 2, suggestion that the transient response of the CTmodel 2 experienced saturation (corroborated by inspection ofCT signals). Steady state error is considerably larger for CTmodel 2. Optical CT model and referent CT model have verysimilar indices (as stated in [10], the referent model can beregarded as CT with characteristics proven in practice as thebest possible, this is, high accuracy, wide frequencybandwidth and distortion-free transient response).

Performance indices for decision-making algorithm ofprotective relay model A are given in Table IX. The selectivityof both optical CT models was ideal at 100%. On the other

hand, selectivity of CT model 2 was 18.7% lower than theselectivity of other models. Performance of this model fallsinto unacceptable limits.

Performance indices for decision-making algorithm ofprotective relay model B are given in Table X. In Table 10,N1 denotes number of expected trips in zone 1, while N2 isassociated with the zone 2. F1 denotes total number ofprotective relay miss-operations (either failures to trip or tripas if the fault was in the zone 2 - delayed trip). F2 is the sameinformation for the zone 2. t1 denotes average tripping timefor faults detected in zone 1, while t2 is average tripping timefor zone 2. Both CT model 1 and 2 present a questionableperformance since selectivity is only 75 and 53.1%respectively for operation in zone 1. A considerable number offaults were detected in zone 1 as belonging to zone 2. OpticalCT models performed as expected, identifying all faults withinthe correct zone of operation.

B. Results of Power Quality Meter Performance

Results of evaluation of the influence of conventional andoptical instrument transformers characteristics on powerquality meter performance are presented in this section.Results are obtained using simulation. Evaluation results arepresented in the form of performance indices in Tables XIthrough XIV.

1) Regarding performance of the sag/swell detection andcharacterization algorithm, the following conclusion can bemade based on the results:

• There is no influence on the PQ meter’s ability toproperly detect power quality disturbances such asvoltage sags/swells.

• Influence on calculation of sag/swell’s duration andsignal’s average RMS value is negligible.

2) Regarding performance of the flicker detection andcharacterization algorithm, the following conclusion can bemade based on the results:

• There is no influence on the PQ meter’s ability toproperly detect voltage flicker.

• Influence on calculation of the peak value of the

TABLE VIIIMEASURING ALGORITHM INDICES

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%yΔ %eΔ

TABLE IXIED MODEL A: DECISION MAKING ALGORITHM INDICES

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[%]s

TABLE XIED MODEL B: DECISION MAKING ALGORITHM INDICES

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�-+�� &( � &( � ��� ��� &� %&�)�� (% ' &( � �� ��� &� %&�)�( �� �� &( � �&1� ��� &� %&6�)�� &( � &( � ��� ��� &. %&6�)�( &( � &( � ��� ��� &. %&

[%]1s [%]2s

6

signal and RMS is negligible.

3) Regarding performance of the harmonic detection andcharacterization algorithm, the following conclusion can bemade based on the results:

• Influence on the PQ meter’s ability to properly detectharmonics is negligible for low order harmonics.Higher order harmonics were not considered sinceCCVT do not provide accurate representation of anyhigher-frequency components.

• Influence on calculation of signal’s average RMSvalue is negligible.

• Considering an average tested THD of 0.12pu, thePQPI – THD shows a considerable difference on theability of the algorithm to properly characterize THD(22.5 percent difference), even for low orderharmonics.

4) Regarding performance of the transient detection andcharacterization algorithm, the following conclusion can bemade based on the results:

• Influence on the PQ meter’s ability to properly detectvoltage transients is considerable (from PQPI –Detection we see that in more than 10% of the casesdetection was not achieved). This is especially truefor transients with high frequency oscillatorycomponents.

• Influence on calculation of the transient’s peak valueis also considerable. Even if the transient could bedetected when exposing the algorithm to signalscoming from conventional IT, there is a percentdifference of 18.2% when compared to the referent

system (PQPI of 0.429 for an average 2.36 peakvalue)

• Influence on calculation of the transient’s duration isvery substantial. For an average simulated transientduration of 0.018sec the calculated PQPI is 0.026,which is equivalent to a percent difference of 144%.

V. CONCLUSION

The methodology presented in this paper is has been use tomeasure the influence of recently deployed optical instrumenttransformer characteristics on the performance of IED. Well-defined indices for protection functions have been presented in[6]-[9]. Power quality performance indices have been definedand used in this paper to evaluate the difference inperformance between the conventional metering system(conventional transformers) and the digital system (opticaltransducers). The use of simulation combined with statisticalanalysis proved to be valuable to quantify the influence ofinstrument transducer characteristics on IED performance.Results show that the use optical transducers is expected topositively influence the performance of protection and controlIED. Furthermore, it is possible to use the same set of opticaltransducers for protective relay, revenue metering and powerquality metering applications without degrading the overallperformance of the system.

VI. REFERENCES

[1] IEEE Power System Relaying Committee Report, “Transient Responseof Current Transformers”, The Institute of Electrical and ElectronicsEngineers, New York, 1994.

[2] IEEE Committee Report, “Transient Response of Coupling CapacitorVoltage Transformers”, Working Group of the Relay Input SourcesSubcommittee of the Power System Relay Committee, IEEETransactions on Power Apparatus and Systems, Vol. PAS-100, No. 12,December 1981.

[3] M.I. Samesina, J.C. de Oliveira, E.M. Dias, “Frequency ResponseAnalysis and Modeling of Measurement Transformers Under DistortedCurrent and Voltage Supply”, IEEE Transactions on Power Delivery,Vol. 6, No. 4, pp. 1762-1768, October 1991.

[4] IEEE Standard Requirements for Instrument Transformers, IEEEstandard C57.13-1993, New York, 1994.

[5] Instrument Transformer, IEC standard 60044, Ed. 1, InternationalElectrotechnical Commission, 2002.

[6] M. Kezunovic, J.T. Cain, B. Perunicic, S. Kreso, “Digital ProtectiveRelaying Algorithm Sensitivity Study and Evaluation”, IEEETransactions on Power Delivery, Vol. 3, No. 3, pp. 912-922, July 1998

[7] E.A. Udren, J.A. Zipp, “Proposed Statistical Performance Measures forMicroprocessor-based Transmission Line Protective Relays, Part 1:“Explanation of the Statistics”, IEEE Transactions on Power Delivery,Vol. 12, No. 1, pp. 134-143, January 1997.

[8] E.A. Udren, J.A. Zipp, “Proposed Statistical Performance Measures forMicroprocessor-based Transmission Line Protective Relays, Part 2:“Collection and uses of data”, IEEE Transactions on Power Delivery,Vol. 12, No. 1, pp. 144-156, January 1997.

[9] M. Kezunovic, B. Kasztenny, “Design Optimization and PerformanceEvaluation of the Relay Algorithms, Relays and Protective SystemsUsing Advanced Testing Tools”, IEEE Transactions on Power Delivery,Vol. 15, No. 4, pp. 1129-1135, October 2000.

[10] B. Naodovic, M. Kezunovic, “A Methodology For Assessing TheInfluence Of Instrument Transformer Characteristics On Power SystemProtection Performance”, Power Systems Computation Conference,Liege, Belgium, August 2005.

[11] M. Kezunovic, A. Abur, G. Huang, A. Bose, K. Tomsovic, M.Venkatasubramanian “MERIT 2000 – Multidisciplinary EducationUsing Curriculum Re-Engineering, Industry Partnership and SimulationTechnology”, Final Report, National Science Foundation, July 2001.

TABLE XISAG AND SWELL CHARACTERIZATION INDICES

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TABLE XIIFLICKER CHARACTERIZATION INDICES

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TABLE XIIIHARMONICS CHARACTERIZATION INDICES

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TABLE XIVTRANSIENTS CHARACTERIZATION INDICES

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[12] D. Tziouvaras, P. McLaren, et all, “Mathematical Models for Current,Voltage and Coupling Capacitor Voltage Transformers”, IEEETransactions on Power Delivery, Vol. 15, No. 1, pp. 62-72, January2000.

[13] D. Ristanovic, S. Vasilic, M. Kezunovic, “Design and Implementation ofScenarios for Evaluating and Testing Distance Relays”, North AmericanPower Symposium - NAPS, College Station, Texas, October 2001.

VII. BIOGRAPHIES

Levi Portillo was born in 1979 in the state of Zulia, Venezuela. He receivedhis B.S. in Electrical Engineering from Zulia University in 2000. He iscurrently pursuing the M.S. degree in the Department of ElectricalEngineering, Texas A &M University, College Station. Email:leviportillo@tamu.edu.

Mladen Kezunovic (S’77, M’80, SM’85, F’99) has been with Texas A&MUniversity since 1987 where he is the Eugene E. Webb Professor and Directorof Electric Power and Power Electronics Institute. His main research interestsare digital simulators as well as application of intelligent methods to control,protection and monitoring. Dr. Kezunovic is a registered professional engineerin Texas, and a Fellow of the IEEE.

George Karady (SM’70–F’78) was born in Budapest, Hungary. He receivedthe B.S.E.E. and Doctor of Engineering degrees in electrical engineering fromthe Technical University of Budapest, Budapest, Hungary. He was appointedto Salt River Project Chair Professor at Arizona State University, Tempe, in1986. He performs research in diverse areas such as power electronics, high-voltage engineering, and electric power. Previously, he was Chief ConsultingElectrical Engineer, Manager of Electrical Systems, and Chief Engineer ofComputer Technology with EBASCO Services, New York. He was ElectricalTask supervisor for the Tokomak Fusion Test reactor project, Princeton, NJ.From 1969 to 1977, he worked as a Program Manager with the Hydro QuebecInstitute of Research, Montreal, QC, Canada, and in 1976 was elected as aResearch Fellow. From 1980 to 1986, he was an adjunct professor with theBrooklyn Polytechnic Institute, Brooklyn, NY. He is the author of manytechnical papers. Dr. Karady was a member of the CIGRE US TechnicalCommittee.

Sadik Kucuksari was born in Burdur, Turkey. He received his B.S and M.Sdegrees in electrical engineering from Yildiz Technical University, Istanbul,Turkey in 2000 and 2002 respectively. Currently, he is a graduate student inElectrical Engineering PhD program at Arizona State University, Tempe, AZ.