International Conference and Workshop on Emerging Trends in Technology (ICWET 2011) – TCET, Mumbai, India

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Power Quality Disturbance Analysis Using WaveletTransforms

R RajarajeswariAssistant Professor(senior grade)

SRM Universitykattankulathur044-27452270

sneharajee@yahoo.co.in

A RathinamAssistant Professor (selection grade)

SRM Universitykattankulathur044-27452270

a_rathinam@yahoo.com

ABSTRACTThis paper presents an approach that is able to provide

the detection and location of power quality disturbances and theidentification of type of power quality problems. Wavelettransformation (WT) is a mathematical tool used for signalprocessing which is better than short time Fourier transforms(STFT). The proposed algorithm uses different kind of wavelets,each for a particular class of disturbance[1]. The given signal isdecomposed through wavelet transform and any change in thesmoothness of the signal can be detected at the finer wavelettransform resolution levels.Each power quality disturbance hasunique deviations from the pure sinusoidal waveform and this isadopted to provide a reliable classification of the type ofdisturbance. A qualitative comparison of results will show theadvantages and drawbacks of each wavelet when applied to thedetection of the disturbances. This method is tested for a largeclass of test conditions simulated in MATLAB. A few powersignals with power quality disturbances have been analyzed toshow the effectiveness of the proposed technique. Power qualitymonitoring with the ability of the proposed algorithm to classifythe disturbances will be a powerful tool for the power systemengineers.

Keywords: Power Quality, Wavelet Transforms

1. INTRODUCTIONThree different disturbance categories are examined

1.1 Voltage sagVoltage sag is described as a drop of 10-90% of the

rated system voltage lasting for half a cycle to 1 min. The causesof voltage sags are caused by system faults and energisation ofheavy loads. A 40% voltage Sag lasting for 2 cycles .Voltage sagsare usually associated with system faults but can also be caused byenergisation of heavy loads or starting of large motors[2].1.2 Voltage swells

Voltage swells are defined as the increase offundamental frequency voltage for a short duration lasting for half

a cycle to 1 min. The typical values are 110-180% of the ratedsystem voltage. A 40% swell disturbance lasting for 40ms issimulated. They appear on the un-faulted phase of a three phasecircuit with a single phase short circuit. They can also occur afterrejection of some load.

1.3 Voltage transientsThe term transient has long been used in the analysis of

power system variations to denote an event that is undesirable -larger Magnitude but momentary in nature.

2 MATLAB- SIMULATION AND RESULTSMATLAB Simulink is a software package that enables

you to model, simulate, and analyze systems whose outputschange over time. Simulink can be used to explore the behaviourof a wide range of real-world dynamic systems, includingelectrical circuits, shock absorbers, braking systems, and manyother electrical and thermodynamic systems.

2.1 Voltage Sag

A simple two bus system having two generators and a transformeris being considered. This system is simulated using MATLABsimulink. The simulation time is considered to be 0.2 seconds.The voltage sag is been created by introducing a three phase faultto the system. The fault occurring time is given as 0.1 to 0.4seconds. So the waveform obtained from the circuit is containinga voltage drop exactly at 0.1 seconds. This voltage drop continuestill the simulation gets over. Similarly the general input waveformfor this system is generated which has the magnitude equal to therated voltage. Now, the waveforms which is been simulated usingthis system is saved as mat file. This is done by connecting ascope in the system in their respective places.

Time (ms) Vs amplitude(volts)

Figure 2.1 simulated voltage sag waveform

Permission to make digital or hard copies of all or part of this work forpersonal or classroom use is granted without fee provided that copies arenot made or distributed for profit or commercial advantage and thatcopies bear this notice and the full citation on the first page. To copyotherwise, or republish, to post on servers or to redistribute to lists,requires prior specific permission and/or a fee.ICWET’11, February 25–26, 2011, Mumbai, Maharashtra, India.Copyright © 2011 ACM 978-1-4503-0449-8/11/02…$10.00.

International Conference and Workshop on Emerging Trends in Technology (ICWET 2011) – TCET, Mumbai, India

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It has sag at 0.1 seconds. The rated voltage of the system is 2.2kV. This waveform is decomposed using multi resolutiontechnique.

2.2 Voltage swellThe simulation time is considered to be 0.1 seconds.

The voltage swell is been created by introducing a three phasefault to the system. The fault occurring time is given as 0.05 to0.2 seconds. So the waveform obtained from the circuit iscontaining a voltage raise exactly at 0.05 seconds. This raise involtage continues till the simulation gets finished.

Time (ms) Vs amplitude (volts)Figure 2.2 simulated voltage swell waveform

The above waveform has a swell at 0.1 seconds. Therated voltage of the system is 2.0 kV. This waveform isdecomposed using multi resolution technique.

2.3 Voltage TransientThe simulation time is considered to be 0.2 seconds.

The voltage transient is been created by introducing a three phasefault to the system. The fault occurring time is given as 0.1 to 0.4seconds. So the waveform obtained from the circuit is containinga voltage raise exactly at 0.1 seconds.

Time(ms) Vs amplitude(volts)

Figure 2.3 simulated voltage transient waveform

2.4 WAVELET DECOMPOSITION

Figure 2.4 Wavelet decomposition

The discrete wavelet transform(DWT) uses a filter bankwith specified high pass and low pass FIR filters to decomposethe input into sub bands that have smaller bandwidths and slowersample rates[3]. The filters can be user-defined or wavelet-basedusually, the high pass and low pass filters designed to complementeach other.

When output is set to multi ports the block outputs eachsub band from a different port as a frame-based vector or matrix(the top most port outputs the sub band with the highest frequencyband). When output is set to single port, the block outputs onesample-based vector or matrix of concentrated sub bands. Inputsmust be frame-based with a frame size a multiple of 2, where n isthe value entered in the ‘Number of levels’ to create a filter bank

that accepts sample-based inputs and inputs of other sizes, usetwo-channel analysis sub band filter blocks in the multi rate filterslibrary.The inputs and outputs of different disturbances which areobtained from the MATLAB simulink are decomposed using theabove simulink system. The multi resolute waveforms are thensaved to the workspace as mat files. Now the input and output of aparticular system is been compared using a prescribed algorithmin order to find out the different disturbances like sag, swell andtransient.

3. ALGORITHM USING DWT Load the real time data or the simulated one. Consider the default input as a(i,j) and simulated output

as b(i,j) Give the condition for voltage swell as b(i,j)>[a(i,j)-

0.1*a(i,j)] If the output satisfies the above equation then display

the voltage swell along with the time period. Give the condition for voltage sag as b(i,j)<[a(i,j)-

0.1*a(i,j)] If the output satisfies the above equation then display

the voltage sag along with the time period. Give the condition for voltage transient as b(i,j)<[a(i,j)-

0.1*a(i,j)] If the output satisfies the above equation then display

the voltage transient along with the time period. If the output does not violates the above equation then

display as no error.

This accurately detects the different kind of power qualitydisturbances such as voltage sag, swell and transient. Thistechnique can be extended to find out other disturbances inpower quality. The decomposition which is done by the

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simulink model has a better resolution than the othermethods and gives better accuracy of using the debusheywavelets for finding out the power quality disturbances.

4. CONCLUSIONSThe proposed algorithm detects and classifies the power

quality disturbances present in the input signal accurately.This approach very accurately locates voltage sag, swell,

and voltage transient temporally. The results show accurateclassification of events can he performed by wavelet basedtime-frequency characteristics. Unlike Short Term FourierTransform, the analysis is not window dependent andnumerically efficient. This method can he extended to detectother PQ events that need to be monitored. Thus, an efficientyet simple technique has been developed to detect andcharacterise PQ disturbances. Further, this could be utilisedfor achieving on-line PQ monitoring.

REFERENCES[1] Malabika Basu , Biswajit Basu School of Control

Systems and Electrical Engg Dublin Institute ofTechnology, Ireland Application of wavelet transformfor power quality(PQ) disturbance analysis , Journal ofapplied sciences,2007.

[2] Sudipta Nath, Arindam Dey and Abhijit ChakrabartiDetection of Power Quality Disturbances using WaveletTransform, proceedings of world academy of science,January 2009

[3] W.A. Wikinson, Discrete Wavelet Analysis of PowerSystem Transients,IEEE Transactions on PowerSystems, November 1996.