International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 2, February 2014)
Odd and Even Switching Pattern in PV Generation System
Coupled SHEPWM Inverter to Reduce Harmonics in Grid
Prof. D. Rajalakshmi1, Dr. K. Geetha2, M. Malathi3
1
3
Assistant Professor, PG scholar, EEE Department, Kumaraguru college of technology Coimbatore-641049
2
Head of the department, Information technology Karpagam Institute of technology, Coimbatore- 641105
Abstract— In this paper grid connected photovoltaic
generation system to mitigate the lower order harmonics by
using SHE PWM inverter is discussed. In Renewable sources,
solar photovoltaic system is more flexible and pollution free.
Then SHE PWM inverter is used to maintain the output
voltage with reduced selective harmonics ( 5th, 7th, 11th, 13th ).
The system is proposed to reduce selective harmonics in the
output using optimized SHEPWM inverter. The switching
angle is calculated using GA Tool. The analysis can be done
with grid connected photovoltaic system through SHE PWM
inverter. The proposed design will be done by using Matlab
simulation results can be observed.
Keywords— photovoltaic (pv) generation system, selective
Harmonic Elimination- Pulse width modulation (SHE-PWM)
inverter.
Fig 1: Block Diagram
I. INTRODUCTION
II. PHOTOVOLTAIC ARRAY
The grid connected photovoltaic generation by using
SHE-PWM inverter .Then PWM inverter is used to
maintain the output voltage with system with reduced the
lower order harmonics can be done reduced selective
harmonics. The system is proposed to reduce selective
harmonics in the output using optimized SHEPWM
inverter. The analysis can be done with grid connected
photovoltaic system through SHE PWM inverter. The
improvement of power quality has been the major issue in
power electronics [1]. The elimination of specific lower
order harmonics improves the performance of voltage
source inverter. The main classification of PWM
techniques are carrier modulated PWM and Selective
Harmonic Elimination based PWM [2]-[5]. In that SHE
based PWM technique offers best solution. It has been
dealt in enormous papers for single and three phase system
[8]. This method can provide the highest quality output and
offers several advantages compared to many modulation
methods including low switching frequency[10]. It is
generally accepted that the performance of an inverter with
any switching strategies, can be related to the harmonic
contents of its output voltage.
A photovoltaic system converts sunlight into electricity.
The basic device of a photovoltaic system is the
photovoltaic cell. Cells may be grouped to form panels or
modules. Panels can be grouped to form large photovoltaic
arrays. The term array is usually employed to describe a
photovoltaic panel (with several cells connected in series
and/or parallel) or a group of panels. Most of time one are
interested in modeling photovoltaic panels, which are the
commercial photovoltaic devices. This paper focuses on
modeling photovoltaic modules or panels composed of
several basic cells. The term array used henceforth means
any photovoltaic device composed of several basic cells.
The modeling and simulating large photovoltaic arrays
composed of several panels connected in series or in
parallel. The electricity available at the terminals of a
photovoltaic array may directly feed small loads such as
lighting systems and DC motors. Some applications require
electronic converters to process the electricity from the
photovoltaic device. These converters may be used to
regulate the voltage and current at the load, to control the
power flow in grid-connected systems.
105
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 2, February 2014)
The Genetic algorithm is used to solve a variety of
optimization problems that are not well suited for standard
optimization algorithms, including problems in which the
objective function is discontinuous,nondifferentiable,
stochastic, or highly nonlinear. The Genetic algorithm can
address problems of mixed integer programming, where
some components are restricted to be integer-value.
The genetic algorithm uses three main types of rules at
each step to create the next generation from the current
population:
III. BIPOLAR SWITCHING PATTERN
The switching pattern is of unipolar and bipolar type and
this includes one level, two levels and three level
waveform. For three phase inverters bipolar switching
pattern shown in fig 1 is used to find the appropriate
switching angles that include both odd and even angles. To
eliminate N-1 harmonics completely from the inverter
output waveform N switching angles have to be calculated
in quarter period of waveform.
In this paper optimized switching angles are produced to
eliminate the lower order harmonics such as 5th, 7th, 11th
and 13th. By including both even and odd values of
switching angles the harmonic content are much reduced.
The output voltage equation of the inverter is
 Selection rules select the individuals, called parents,
that contribute to the population at the next
generation.
 Crossover rules combine two parents to form
children for the next generation.
 Mutation rules apply random changes to individual
parents to form children.
The Genetic Algorithm tool is a graphical user interface
that enables you to use the genetic algorithm without
working at the command line. To open it, enter gatool. at
the MATLAB command prompt. The tool opens as shown
in the figure
To use GA at the command line, call the GA function ga
with the syntax
(1)
Whereas
is the fundamental component and have to
be improved and
is the even harmonics that are almost
zero and
is the odd harmonics have to be eliminated.
The range of switching angles should be between 0 to 90
degree.
[x fval] = ga (@fitnessfun, nvars, options) where
• @fitnessfun is a handle to the fitness function.
• nvars is the number of independent variables for the
fitness function.
• options is a structure containing options for the
genetic algorithm. If you do not pass in this argument,
ga uses its default options. The results are given by,
Fig 2: Bipolar waveform
IV. GENETIC ALGORITHM
• x — Point at which the final value is attained
The genetic algorithn is a method for solving both
constrained and unconstrained optimization problems that
is based on natural selection, the process that drives
biological evolution. The gentec algorithm selects
individual in random from the current population to be
parents and uses them to produce the children for the next
generation. Over sucessive generations , the population
―evolves‖ toward an optimal solution.
• fval — Final value of the fitness function using the
function ga is convenient if you want to
• Return results directly to the MATLAB workspace
• Run the genetic algorithm multiple times with
different options, by calling ga from an M-file.
106
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 2, February 2014)
Fig 3: GA TOOL
Fig 4: Simulation circuit
GA tool is performed in matlab software and optimized
odd and even switching angles are found. For satisfactory
results GA tool parameters are
The fig 4, shows the three phase inverter circuit that
includes Input voltage=24V, frequency=50HZ, Grid
voltage=230V. The objective function in GA is written in
such a way that it reduces 5th, 7th, 11th and 13th
harmonics. From the fig 8 it is clearly shown that the
proposed technique offers less harmonic content compared
to standard method.
The selected harmonics such as (5th, 7th, 11th and 13th )
which are reduced completely for odd and even values of
switching angles is shown in fig. 6 and fig. 7 respectively.
Initial population size=100
Maximum number of generation=50
Probability of cross over=0.5
Mutation probability=0.01
Performance measure=Lower order harmonics (5 th, 7th,
11th, 13th)
Performance measure=THD
V. SIMULATION CIRCUIT
The grid connected photovoltaic generation system with
voltage source inverter compared with SHE PWM inverter
results are obtained and simulated in MATLAB software.
Fig 5: Modeling of PV Array
107
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 2, February 2014)
VI. RESULTS AND DISCUSSION
Fig 8: comparison of THD values
Three phase inverter with SPWM technique is simulated
using matlab software. THD of this standard method is
compared with proposed method and results are shown in
fig 6. GA based SHEPWM technique with odd and even
values shows reduced THD compared to SPWM technique.
Fig 5: Results for grid connected Pv by using optimized SHE PWM
inverter
Table I
Harmonic Content For Three Phase Inverters
Odd values
of switching
angle
Even values
of switching
angle
(Harmonic
content in %)
(Harmonic
content in %)
5th
5.10
3.60
7th
2.24
0.74
11th
3.88
2.23
13th
1.98
1.08
Harmonics in
output
voltage
Fig 6: THD values for three phase inverter using even values of
switching angles
The harmonics affect the performance of the power
application. Due to 5th,11th,7th,13th harmonics attempt to
drive the motor in reverse direction causing overheating,
tripping of over current protection devices, skin effects,
destructive heating leads to de -rating of machine occurs.
The proposed method eliminates these particular harmonics
by proper selection of odd and even values of switching
angles.
VII. CONCLUSION
A new approach to reduce the lower order harmonics in
three phase SHEPWM inverter using GA has been
presented.
Fig 7: THD values for three phase inverter using odd values of
switching angles
108
International Journal of Emerging Technology and Advanced Engineering
Website: www.ijetae.com (ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 2, February 2014)
AUTHOR’S PROFILE
In the drive fields 5th and 11th harmonics create
negative sequences and attempt to drive the motor in
reverse direction causing overheating, tripping of over
current protection devices. Odd numbers of switching
angles are selected for eliminating 5th and 11th harmonics
completely. The 7th harmonics causes destructive heating
and leads to de-rating of machines like transformer and
capacitor bank. Selection of even number of switching
angles reduces the 7th harmonics completely. A simulated
result has been presented for the THD for three phase
inverter with odd and even values of switching angles is
simulated and also compared with standard PWM method.
D. Rajalakshmi received her bachelor’s
degree
from
Shanmuga
college
of
Engineering, Tanjore, Tamilnadu, India in
Electrical and Electronics Engineering during
2000. She received her Master’s degree from
Alagappa College of Engineering and
Technology,
Karaikudi,
India
during
2006.She has the teaching experience of more than 11 years.
She is currently working as a Assistant Professor-Senior Grade
at the department of Electrical and Electronics Engineering
in Kumaraguru College of Technology, Coimbatore, India.
REFERENCES
M. Malathi received her BE (Electrical and
Electronics Engineering) from Info Institute of
Engineering, Coimbatore, Tamil Nadu, India.
Now she is pursuing Master of Engineering
(Power Electronics and Drives) in Kumaraguru
College of Technology, Coimbatore, India.
[1]
Javier Napoles, Jose I. Leon, Ramon Portillo, Leopoldo G.
Franquelo, and Miguel A. Aguirre, ―Selective Harmonic Mitigation
Technique for High-Power Converters,‖ IEEE Transactions on
Industrial electronics, Vol. 57, No. 7, July 2010.
[2] V. G. Agelidis, A. Balouktsis, and C. Cossar, ―On attaining the
multiple solutions of selective harmonic elimination PWM threelevel waveforms through function minimization,‖ IEEE Trans. Ind.
Electron.,Vol.55, No. 3, pp. 996–1004, Mar. 2008.
[3] Ali M. Eltamaly, ―A Modified Harmonics Reduction Technique for
a Three-Phase Controlled Converter,‖ IEEE Transactions On
Industrial Electronics, Vol. 55, No. 3, March 2008.
[4] V. Blasko, ―A novel method for selective harmonic elimination in
powerbelectronic equipment,‖ IEEE Trans. Power Electron., Vol.
22, No. 1,pp. 223–228, Jan. 2007
[5] K. Sundareswaran, K. Jayant, and T. N. Shanavas, ―Inverter
harmonic elimination through a colony of continuously exploring
ants,‖ IEEE Trans.Ind. Electron., Vol. 54, No. 5, pp. 2558–2565,
Oct. 2007.
[6] Jason R. Wells, Xin Geng, Patrick L. Chapman,Philip T. Krein, and
Brett M. Nee, ―Modulation-Based Harmonic Elimination,‖ IEEE
Transactions on Power Electronics,Vol. 22, No. 1, January 2007.
[7] Vassilios G. Agelidis, AnastasiosBalouktsis, IoannisBalouktsis,
andCalumCossar ,―Multiple Sets of Solutions for Harmonic
Elimination PWM Bipolar Waveforms: Analysis and Experimental
Verification,‖ IEEE Transactions on Power Electronics, Vol. 21, No.
2, March 2006.
[8] K. L. Shi and H. Li, ―Optimized PWM strategy based on genetic
algorithms, ‖IEEE Trans. Ind. Electron., vol. 52, no. 5, pp. 1458–
1461,Oct. 2005.
[9] Jason R. Wells, Brett M. Nee, Patrick L. Chapman, and Philip T.
Krein, ―Selective Harmonic Control: A General Problem
Formulation and Selected Solutions,‖ IEEE Transactions on Power
Electronics, Vol. 20, No. 6, November 2005.
[10] John N. Chiasson, Leon M. Tolbert, Keith J. McKenzie, and Zhong
Du, ―A Complete Solution to the Harmonic Elimination Problem,‖
IEEE Transactions on Power Electronics, Vol. 19, No. 2, March
2004.
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