7 ANALYSIS OF GENERATED HARMONICS DUE TO … OF GENERATED HARMONICS DUE TO CFL LOAD ON POWER SYSTEM...

International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print),

ISSN 0976 – 6553(Online) Volume 5, Issue 3, March (2014), pp. 56-68 © IAEME

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ANALYSIS OF GENERATED HARMONICS DUE TO CFL LOAD ON

POWER SYSTEM USING ARTIFICIAL NEURAL NETWORK

Dharmendra Kumar singh [1]

, Pragya Patel [2]

, Anjali Karsh [3]

, Dr.A.S.Zadgaonkar [4]

Dr. C.V.Raman University Kargi Road Kota Bilaspur (C.G), INDIA

ABSTRACT

The mass usage of CFLs is the problem with the network voltage distortion that arises due to

their distorted current which contains a high level of harmonic components even at pure sine wave

supply voltage. The combined effect of the widespread adaptation of the CFL can be just as

detrimental as one large harmonic source. Moreover mitigation of harmonic distortion caused by

CFLs is very difficult once they are widely distributed over the large power system network .In this

paper we identified the harmonic component generated in power system due to current harmonics

using artificial neural network. The ANN based methods has the advantages of parallel information

processing learning distribution pattern and memory which can be used in the measurement of the

harmonic to construct an appropriate network. Harmonic on-line detection can be achieved through

the study of the sampling.

Keyword: Power system, Harmonics, Artificial Neural Network, CFL.

I. INTRODUCTION

The idea of replacing inefficacious and short-aged incandescent lamps with efficacious and

long aged fluorescent lamps has resulted in the development of compact fluorescent lamps (CFLs).

Compact fluorescent lamps were primarily intended for residential and commercial customers.

Lasting much longer and consuming much less energy than incandescent lamps with comparable

luminous output, they represented promising new lamp types. As a part of their energy saving

strategy, nations across the world were promoting the use of CFLs. These countries were even

offering CFLs at a highly subsidized price to make them popular. The basic problem arising in the

mass usage of CFLs is the problem with the network voltage distortion that arises due to their

distorted current which contains a high level of harmonic components even at pure sine wave supply

voltage. Various references discussing the behavior of CFLs under various operating conditions like

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different system voltage, voltage distortions in the power system etc. Literature referred suggests

harmonics introduced into the networks by CFLs has been ignored earlier as individual CFL’s

injection is very small. The combined effect of the widespread adaptation of the CFL can be just as

detrimental as one large harmonic source. Moreover mitigation of harmonic distortion caused by

CFLs is very difficult once they are widely distributed over the large power system network. [1] [2]

[3] [4].

Harmonics Analysis Methods

Harmonics analysis is done using five methods:

1. Analog filter based method

2. Instantaneous reactive power theory based method

3. Fast Fourier transform (FFT) based method

4. Wavelets transform based method

5. ANN based method

Analog filter method is simple and cheap but has big error and bad performance in real

situation. Instantaneous reactive power theory has a simple circuit and good at real time situation but

yields big error during variation of voltage. FFT based method has problem that had to leakage effect

picket fence effect and aliasing effect. Wavelets transform is more complex than FFT. The ANN

based methods has the advantages of parallel information processing learning distribution pattern and

memory which can be used in the measurement of the harmonic to construct an appropriate network.

Harmonic on-line detection can be achieved through the study of the sampling.

2. CFL

Figure 3.1 displays a typical CFL ballast circuit, and is divided into four blocks for analysis

purpose. The 1st block usually has the protection, filtering and current peak limiting components. It

attenuates the electromagnetic interference generated by the high frequency stages of the ballast, and

also protects the ballast against possible transient phenomenon. The 2nd block is the ac/dc

conversion using full-bridge diode rectifier. This is followed by a capacitor in block 3 to provide a

smooth dc voltage for the resonant inverter in block 4. The lamp is supplied by a resonant inverter

started by the DIAC, and self-oscillating between 10 and 40 kHz. It also provides a high voltage to

strike across the tube. Generally the lamp appears as a constant resistive load as far as the dc bus bar

is concerned. The first three blocks have enormous impact on the CFL harmonic performance. CFL

can be divided into the following three main categories in terms of ballast circuitry and their attempts

on power-factor correction injection are very small. The combined effect however, of the widespread

adoption of CFLs can be just as detrimental as one large harmonic source. Moreover mitigation of

the harmonic distortion caused by CFLs is very difficult once in the network due to the dispersed

nature. Having one large harmonic source, such as a converter is easier to deal with than a multitude

for small dispersed harmonic sources, as harmonic filters can be designed to meet the system

requirements and installed at the devices terminals [5].



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Figure (1): Typical CFL ballast circuit

3. ARTIFICIAL NEURAL NETWORK

Neural network which are simplified models of the biological neuron system, is a massively

parallel distributed processing system made up of highly interconnected neural computing elements

that have the ability to learn and thereby acquire knowledge and make it available for use. There

are several different training algorithms for feed-forward networks. All these algorithms use the

gradient of the performance function to determine how to adjust the weights to minimize

performance. The gradient is determined using a technique called back-propagation. Back-

propagation is a systematic method of training multilayer Artificial Neural Networks. It is built on

high mathematical foundation and has very good application potential. Even though it has its own

limitations, it is applied to a wide range of practical problems and has successfully demonstrated its

power. [6] [7] [8].

4. EXPERIMENTAL SET-UP

we have used Dr.C.V.Raman University machine lab for experiment . 20W ,9 CFL are used

whose electrical specification given in table(1) . Thses 9 cfl are connected to the different switches

so that from 20W to 180W load will be provided to the power system. The 220V supply is provided

in this work the physical experimental set-up have shown in the figure(2). The circuit block

diagram of this set-up have shown in fig(3).

Table 1: Electrical Specification of CFL used in experiment

Operating Voltage 22OV-240 Volts

Frequency 50Hz

Power Consuption 20W

Current 85mA

Standard ISI(IS:-15111)

Made in INDIA

5. ANN DESIGNING PROCESS

ANN designing process involves five steps: gathering input data, normalizing the data,

selecting the ANN architecture, and Training the Network, Validation-testing the network [9].

5.1 Gathering Input Data: The configuration of the experimental system and experimental system

block diagram is shown in below fig(2) and fig(3).



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Figure (2): Image of experimental set-up

Figure (3): Block diagram of experimental set-up

Figure (4): Hardware circuit for CFL ballast

In the above block diagram set-up, CFL with ballast circuit are connected to supply. A data

acquisition card is connected at power common connection to collect the distorted current/voltage

waveform or data. These collected waveform/data transmitted to PC through RS-485 for ANN input

which is designed in MATLAB.



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Figure (5): Supply current waveform when 180W CFL Load on supply



Figure (8): Supply current waveform when 120W CFL Load on s

5.2 Normalization of input data for ANN Normalization of data is a process of scaling the numbers in a data set to improve the

accuracy of the subsequent numeric computation and is an important stage for training of the ANN.

Normalization also helps in shaping the activation function. For this reason [-1, 1] normalization

function has been used.



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Figure (9): Normalised current waveform for ANN Input (180 W CFL)

Figure(10): Normalised current waveform for ANN Input (160 W CFL)





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5.3 Selecting the ANN Architecture The selection of ANN Architecture are described by [10].

Figure (14): Designed ANN for harmonics component identification

5.4 Training of the ANN Model

The training of the ANN model is described by [10].

Figure (15): Training of designed ANN

5.5 Testing To test the generalizing capabilities of the magnitude networks the distorted waveforms that

contained odd harmonics up to the 23rd

harmonic with no noise added were considered for the

training process.



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Figure (16): Waveform of ANN Output for magnitude (180W CFL)






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Figure (21): Bar graph of ANN output for 180W magnitude





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Figure ( 24): Bar graph of ANN output for 100W magnitude

Figure (25): Phase angle of harmonics when 180W CFL load

Figure (26): Phase angle of harmonics when 140W CFL load

Figure (27): Waveform of ANN Output for Phase angle 120W



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Figure (28): Waveform of ANN Output for Phase angle 100W

6. RESULT AND DISCUSSION

The output of the ANN is shown in fig (16), fig (17), fig (18), fig (19), fig (20) for different

wattage CFL.CFL generate odd harmonics in power system. The magnitude of harmonics for low

wattage CFL is larger than the high wattage CFL .The dominant harmonics are non-triplen. The

magnitude of triplen harmonics is less then non-triplen harmonics.

7. CONCLUSION

An artificial neural network model was developed and implemented for power system

harmonics component measurement. It was tested off-line under different conditions. The result of

the off-line test indicates that the ANN model has very high power system harmonics component

measurement accuracy. The developed ANN model was implemented on a PC with Matlab Software

(with ANN Toolbox) using a data acquisition card. The ANN model was able to measure the

harmonic components of voltage and current at various levels. The CFL load for different wattage

are tested by this ANN and find that CFL generate odd harmonics ion power system.

ACKNOWLEDGEMENTS

We would like to express our sincerest gratitude to all staff of EEE Department Dr. C. V.

Raman University who has contributed, directly or indirectly, in accomplishing this paper. Special

thanks to extend Miss Pallavee Jaiswal for her support in completing this Paper.

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BIOGRAPHIES

Dharmendra Kumar:- obtained M. Tech. Degree in Electronics Design and Technology from

Tezpur University, Tezpur, Assam in the year 2003. Currently he is pursuing research work in the

area of Power Quality under the guidance of Prof A. S. Zadgaonkar

Pragya patel:- has obtained B.E. degree in Electrical Engineering from Govt. Engineering

College,Bilaspur in 2011,currently she is pursuing M.Tech in power system engineering.

Anjali Karsh:- has obtained B.E. degree in Electrical and Electronic Engineering from Chhatrapati

shivaji Institute of Technology, Durg in 2009, currently she is pursuing M.Tech in power system

engineering.

Dr. A. S. Zadgaonkar:- has obtained B. E. degree in Electrical Engineering from Pt. Ravishankar

Shukla University, studying at Govt. Engineering College, Raipur in 1965. He obtained M. E. in

1978 from Nagpur University. His research paper for M. E. was awarded “best paper” by the

Institution of Engineers (India) in the year 1976 & 1977 respectively. The testing technique for

quality of wood developed by him was included in ISI in 1979. He was awarded Ph. D. in 1985 by

Indira Gandhi Kala & Sangeet University, Khairagah for his work on “Acoustical and Mechanical

Properties of Wood for Contemporary Indian Musical Instrument Making.” He obtained another Ph.

D. in 1986 by Pt. Ravishankar Shukla University on “Investigation of Dynamic Properties of Non-

Conducting Materials Using Electrical Analogy.” He has 47 years of teaching experience. He has

published more than 500 technical papers for journals, national and international conferences. He

was the Joint Director, Technical Education, Govt. of Chhattisgarh in 2004 & the Principal of NIT,

Raipur in 2005. He is life member of Acoustical Society of India, Biomedical Society of India,

Linguistic Society of India, Indian Society for Technical Education and many social bodies.

7 ANALYSIS OF GENERATED HARMONICS DUE TO … OF GENERATED HARMONICS DUE TO CFL LOAD ON POWER SYSTEM...

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